Zeitschriftenartikel: „Howe Machine Co“

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Booth, Kate. „The places within“. cultural geographies 25, Nr. 4 (18.02.2018): 637–41. http://dx.doi.org/10.1177/1474474018757504.

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There was a place in my life where I had the time and space to reflect more deeply on the intricacies of home. Here my sense of where I was shifted and stirred, along with my relationship with some of the ‘things’ that made up my home. The washing machine that seemingly existed as a complete, discrete ‘thing’ prior to arriving in my home transgressed into my washing machine. It became, as I describe below, co-produced within my home life – a co-production constituted through a myriad of near and far relationalities. This ‘thing’ lost its place as a machine conveniently located within the kitchen and became places.

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Tao, JIANG, ZHANG Gui-lin und GAO Jun-peng. „Illumination of a cylinder block transverse hole for machine vision inspection“. Chinese Optics 13, Nr. 6 (2020): 1–8. http://dx.doi.org/10.37188/co.2020-0054.

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Chen, Shun Tong, Zong Han Jiang, Yi Ying Wu und Hong Ye Yang. „Development of a Reverse Micro EDM-Drilling for Holing Diamond-Tool“. Advanced Materials Research 126-128 (August 2010): 802–7. http://dx.doi.org/10.4028/www.scientific.net/amr.126-128.802.

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This study presents the development of a drilling technique for an innovative tabletop drilling machine that combines micro-EDM with drilling to fabricate micro-holes in diamond-tool. The mechanisms designs of double V-shaped bearings and double spindles which provide a precision clamping and vertical alignment for diamond-tool and micro-tube are devised to enable to machine a co-centric micro-hole for micro-tool. A diamond-tool, made with copper-based sintered alloy, is drilled by using the developed technique of co-centric micro-hole EDM-drilling into a hollow shaft which can create equilibrium of drilling forces, prevent a drilling squeezing to be occurred and enable to offer a temporary storing space for drilling chips. Relative experiments including the determinations of drilling ratio and discharge capacitance are carried out via this established machine. Experimental results show that excellent geometric and dimensional accuracy of micro-holes on the diamond-tool can be achieved.

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Rychel, Kevin, Katherine Decker, Anand V. Sastry, Patrick V. Phaneuf, Saugat Poudel und Bernhard O. Palsson. „iModulonDB: a knowledgebase of microbial transcriptional regulation derived from machine learning“. Nucleic Acids Research 49, Nr. D1 (12.10.2020): D112—D120. http://dx.doi.org/10.1093/nar/gkaa810.

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Abstract Independent component analysis (ICA) of bacterial transcriptomes has emerged as a powerful tool for obtaining co-regulated, independently-modulated gene sets (iModulons), inferring their activities across a range of conditions, and enabling their association to known genetic regulators. By grouping and analyzing genes based on observations from big data alone, iModulons can provide a novel perspective into how the composition of the transcriptome adapts to environmental conditions. Here, we present iModulonDB (imodulondb.org), a knowledgebase of prokaryotic transcriptional regulation computed from high-quality transcriptomic datasets using ICA. Users select an organism from the home page and then search or browse the curated iModulons that make up its transcriptome. Each iModulon and gene has its own interactive dashboard, featuring plots and tables with clickable, hoverable, and downloadable features. This site enhances research by presenting scientists of all backgrounds with co-expressed gene sets and their activity levels, which lead to improved understanding of regulator-gene relationships, discovery of transcription factors, and the elucidation of unexpected relationships between conditions and genetic regulatory activity. The current release of iModulonDB covers three organisms (Escherichia coli, Staphylococcus aureus and Bacillus subtilis) with 204 iModulons, and can be expanded to cover many additional organisms.

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Cheney, Nick, Josh Bongard, Vytas SunSpiral und Hod Lipson. „Scalable co-optimization of morphology and control in embodied machines“. Journal of The Royal Society Interface 15, Nr. 143 (Juni 2018): 20170937. http://dx.doi.org/10.1098/rsif.2017.0937.

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Evolution sculpts both the body plans and nervous systems of agents together over time. By contrast, in artificial intelligence and robotics, a robot's body plan is usually designed by hand, and control policies are then optimized for that fixed design. The task of simultaneously co-optimizing the morphology and controller of an embodied robot has remained a challenge. In psychology, the theory of embodied cognition posits that behaviour arises from a close coupling between body plan and sensorimotor control, which suggests why co-optimizing these two subsystems is so difficult: most evolutionary changes to morphology tend to adversely impact sensorimotor control, leading to an overall decrease in behavioural performance. Here, we further examine this hypothesis and demonstrate a technique for ‘morphological innovation protection’, which temporarily reduces selection pressure on recently morphologically changed individuals, thus enabling evolution some time to ‘readapt’ to the new morphology with subsequent control policy mutations. We show the potential for this method to avoid local optima and converge to similar highly fit morphologies across widely varying initial conditions, while sustaining fitness improvements further into optimization. While this technique is admittedly only the first of many steps that must be taken to achieve scalable optimization of embodied machines, we hope that theoretical insight into the cause of evolutionary stagnation in current methods will help to enable the automation of robot design and behavioural training—while simultaneously providing a test bed to investigate the theory of embodied cognition.

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Kumari, K. Siva. „Home Air Quality Monitoring System“. International Journal for Research in Applied Science and Engineering Technology 12, Nr. 7 (31.07.2024): 318–25. http://dx.doi.org/10.22214/ijraset.2024.63566.

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Abstract: The quality of indoor air is a critical determinant of health and well-being, particularly Given the considerable amount of time individuals invest indoors. Recognizing the pivotal role of air quality, this paper introduces a novel Home Air Quality Monitoring System (HAQMS) designed to provide real-time, accurate assessments of air quality within residential environments. The HAQMS integrates advanced sensors and IoT (Internet of Things) technologies to detect and quantify a wide range of air pollutants, including particulate matter (PM2.5 and PM10), volatile organic compounds (VOCs), carbon dioxide (CO2), carbon monoxide (CO), and ozone (O3).The system architecture is delineated into three primary components: the sensor array for pollutant detection, a data processing unit employing advanced algorithms for real-time data analysis, and a user interface for displaying air quality metrics and providing health recommendations. Utilizing machine learning techniques, the system not only reports currentair quality but also predicts future air quality levels based on historical data and trend analysis. This predictive feature is pivotal for proactive measures in maintaining indoor air quality.

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Marques, Ana. „Writing with Automated Machines: Between Translation and Sabotage“. Matlit Revista do Programa de Doutoramento em Materialidades da Literatura 6, Nr. 3 (10.08.2018): 73–81. http://dx.doi.org/10.14195/2182-8830_6-3_6.

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A generative text is a system constituted by non-conscious and conscious cognizers, digital and analogue processes, and mathematical and linguistic modes of representation. But how do algorithms cognize? And how is meaning constructed in a system where authorial intentions and readers’ experiences and interpretations are mediated by algorithmic agents? Through the analysis of How It Is In Common Tongues (Cayley and Howe, 2012), I intend to discuss the tensions that arise from the encounter between algorithmic and human cognition, and between the regimes of information and expression. Drawing on Katherine Hayles’ view on the cognitive non-conscious and Claude Shannon’s information theory I will start by establishing a distinction between information and meaning, between communication and expression, and between the regimes of information and of the literary. To reflect on the political ecology of digital mediation (situated in the informational regime of cybernetics), I will consider Matteo Pasquinelli’s perspective on the co-evolution of technology and economics, and discuss how algorithmic cognitive processes embody and reinforce the structures of contemporary cognitive capitalism. Finally, I will discuss the strategies of resistance enabled by aesthetic approaches to computation, such as the ones explored in this case study.

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Zhao, Yibing, Feng Ding, Xuecai Yu, Ronghui Zhang und Xiumei Xiang. „A New Waters Hole Detection and Tracking Method for UGV in Cross-Country Environment“. International Journal of Pattern Recognition and Artificial Intelligence 30, Nr. 08 (17.07.2016): 1655024. http://dx.doi.org/10.1142/s0218001416550247.

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Environment perception is one of the important issues for unmanned ground vehicle (UGV). It is necessary to develop waters hole detection and tracking method in cross-country environment. This paper is related to the waters hole detection and tracking by using visual information. Image processing strategies based on support vector machine (SVM) and speeded up robust feature (SURF) methods are employed to detect and track waters hole. It focuses on how to extract the waters feature descriptor by exploring the machine learning algorithm. Based on the S/V color features and Gray Level Co-occurrence Matrix, the waters feature descriptor is extracted. The radial basis function (RBF) kernel function and the sampling-window size are determined by using the SVM classifier. The optimal parameters are obtained under the cross-validation conditions by the grid method. In terms of waters tracking, SURF feature matching method is applied to extract the remarkable feature points, then to observe the relation between feature point movement of adjacent frames and scale change ratio. Experiments show that SURF algorithm can still be effective to detect and match the remarkable feature points, against the negative effects of waters scale transformation and affine transform. The conclusion is that the computing speed of SURF algorithm is about three times faster than that of scale-invariant feature transform (SIFT) algorithm, and the comprehensive performance of SURF algorithm is better.

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Gunawan, Mikhael, Rasional Sitepu und Albert Gunadhi. „Sistem Pemadam Kebakaran Otomatis Berkonsep Smarthouse“. Widya Teknik 21, Nr. 1 (Mai 2022): 1–7. http://dx.doi.org/10.33508/wt.v21i1.3892.

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Home fire disasters are still common around us. This problem is a challenge in order to be able to find a solution. One solution to secure a home from a potential fire is to apply smarthome technology. Based on this problem, the idea arose to make an automatic fire extinguisher that can spray water with a water pump when it detects smoke (CO) due to a fire and circulates air in the room with an exhaust fan when an LPG gas cylinder leak is detected in the house so as to prevent a house fire. This tool is planned to be connected to the GSM module so that wherever we are we can find out if there is a fire in our home. This tool is made by utilizing the Smoke Gas Sensor (MQ 2), Temperature Sensor (LM35), Arduino Uno, GSM SIM 900 Module, Relay, Buzer, Exhaust Fan and Water Pump as its main components. Arduino Uno is used as the controller of this machine. The GSM SIM 900 Shield module is used for connection via SMS as a remote notification notification, LM35 as a temperature detector, and MQ 2 as a butane gas detector when there is a leak of LPG gas cylinders and fire smoke (CO) when a fire occurs. This tool can extinguish fires using a water pump from the detection of smoke (CO) and temperatures when more than 500 ppm and 40oC and circulate air using an exhaust fan with additional safety features when there is an LPG gas leak when gas is detected 500 ppm and send it with notification notification via SMS using the GSM SIM 900 module Shield. The measured voltage of the MQ2 sensor when clean air reaches 189.3 mV and the percent error of the LM35 reaches 0.88423%.

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Zou, Fan, Jiaqiang Dang, Xiaojiang Cai, Qinglong An, Weiwei Ming und Ming Chen. „Hole quality and tool wear when dry drilling of a new developed metal/composite co-cured material“. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 234, Nr. 6-7 (12.02.2020): 980–92. http://dx.doi.org/10.1177/0954405420901420.

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The new developed metal/composite co-cured material composed of carbon fiber–reinforced plastic and Al phases has been increasingly applied for manufacturing of attitude control flywheel in aerospace industry. However, drilling of co-cured material is still a challenging task to produce holes with high quality and low cost in the assembly chain and dynamic balance debugging of attitude control flywheel. In other words, the relevant mechanisms and experimental findings involved in the drilling process of carbon fiber–reinforced plastic/Al co-cured material is not clearly defined, which impedes the progress of attitude control flywheel production. To this end, this article specially addresses the experimental studies on the drilling process of carbon fiber–reinforced plastic/Al co-cured material with standard TiAlN-coated cemented carbide twist drill. The significance of this work aims to reveal the regardful cutting responses of the hole characteristics and tool wear modes during the practical drilling process of co-cured material. A full factorial experiment including three levels of feed rate and four levels of cutting speed was performed. The hole diameter shows different values in different positions while it indicates consistent pattern regardless of the cutting variables: the largest in the Al phase, followed by the upper and lower carbon fiber–reinforced plastic phases, respectively. Grooves and matrix degradation are the major machining defects for carbon fiber–reinforced plastic layers, while a great chip debris adhered to the machined surface is the case for Al layer. Subsequent wear analysis showed that abrasion was mainly maintained at the vicinity of major/minor cutting edges and drill edge corner, followed by chip adhesion on the chisel edge region. Carbide substrate of drill flank face is exposed, and thereafter cavities are formed under the strong mechanical abrasion. These results could provide several implications for industrial manufacturers during the attitude control flywheel production.

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Nandikotkur, Achyuth, Issa Traore und Mohammad Mamun. „SeniorSentry: Correlation and Mutual Information-Based Contextual Anomaly Detection for Aging in Place“. Sensors 23, Nr. 15 (28.07.2023): 6752. http://dx.doi.org/10.3390/s23156752.

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With the ever-growing reliance on IoT-enabled sensors to age in place, a need arises to protect them from malicious actors and detect malfunctions. In an IoT smart home, it is reasonable to hypothesize that sensors near one another can exhibit linear or nonlinear correlations. If substantiated, this property can be beneficial for constructing relationship trends between the sensors and, consequently, detecting attacks or other anomalies by measuring the deviation of their readings against these trends. In this work, we confirm the presence of correlations between co-located sensors by statistically analyzing two public smart-home datasets and a dataset we collected from our experimental setup. Additionally, we leverage the sliding window approach and supervised machine learning to develop a contextual-anomaly-detection model. This model reaches a true positive rate of 89.47% and a false positive rate of 0%. Our work not only substantiates the correlations but also introduces a novel anomaly-detection technique to enhance security in IoT smart homes.

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Zhao, ShiJie, Toshihiko Sasama, Takao Kawamura und Kazunori Sugahara. „Detection of Irregular Behavior in Room Using Environmental Sensors and Power Consumption of Home Appliances Learning in HMMs“. International Journal of New Media Technology 4, Nr. 2 (22.12.2017): 94–98. http://dx.doi.org/10.31937/ijnmt.v4i2.786.

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We propose a human behavior detect method based on our development system of multifunctional outlet. This is a low-power sensor network system that can recognize human behavior without any wearable devices. In order to detect human regular daily behaviors, we setup various sensors in rooms and use them to record daily lives. In this paper we present a monitoring method of unusual behaviors, and it also can be used for healthcare and so on. We use Hidden Markov Model(HMM), and set two series HMM input to recognize irregular movement from daily lives, One is time sequential sensor data blocks whose sensor values are binarized and splitted by its response. And the other is time sequential labels using Support Vector Machine (SVM). In experiments, our developed sensor network system logged 34days data. HMM learns data of the first 34days that include only usual daily behaviors as training data, and then evaluates the last 8 days that include unusual behaviors. Index Terms—multifunctional outlet system; behavior detection; hidden markov model; sensor network; support vector machine. REFERENCES [1] T.Sasama, S.Iwasaki, and T.Okamoto, “Sensor Data Classification for Indoor Situation Using the Multifunctional Outlet”, The Institute of Electrinical Engineers of Japan, vol.134(7),2014,pp.949-995 [2] M.Anjali Manikannan, R.Jayarajan, “Wireless Sensor Netwrork For Lonely Elderly Perple Wellness”, International Journal of Advanced Computational Engineering and Networking, ISSN: 2320-2106, vol. 3, 2015, pp.41-45 [3] Nagender Kumar Suryadevara, “Wireless Sensor Network Based Home Monitoring System for Wellness Determination of Elderly”, IEEE SENSORS JOURNAL, VOL. 12, NO. 6, JUNE 2012, pp. 1965-1972. [4] iTec Co., safety confirmation system: Mimamorou, http://www.minamoro.biz/. [6] Alexander Schliep's group for bioinformatics, The General Hidden Markov Model library(GHMM), http://ghmm.sourceforge.net/. [7] Jr Joe H.Ward, Joumal of the American Statistical Association, vol58(301), 1963, pp236-244 [5] SOLXYZ Co., status monitoring system:Ima-Irumo, http://www.imairumo.com/.

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Hegde, Sandeep Kumar, Sujidha B., K. Vimala Devi, K. Maheswari, K. Leela Krishna, Pallavi Singh und Varsha D. Jadhav. „Hybrid approach for lung cancer detection based on deep learning/machine learning“. Journal of Autonomous Intelligence 7, Nr. 5 (29.05.2024): 1605. http://dx.doi.org/10.32629/jai.v7i5.1605.

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<p>The incidence of Lung Cancer (LC) is rising in India. LC has been diagnosed and detected numerous times utilizing numerous data processing and identification strategies. Since the underlying origin of LC is still unknown, treatment is hopeless, making early diagnosis of lung tumors the only viable treatment option. So, a Machine Learning (ML) and Deep Learning (DL) based system is utilized to categorize CT scans for the existence of LC. The Visual Geometry Group (VGG-16) and Multi-Class Support Vector Machine (VGG-16+MSVM) technique is proposed in this research. Non-Local Means (NLM) Filter and Bi-Histogram Equalization (Bi-HE) are used, respectively; to filter out unwanted background noise in raw data samples and improve image quality. To isolate tumors in the raw data, the K-Means Clustering (KMC) technique is applied. The Gray Level Co-Occurrence Matrix (GLCM) is employed to generate features from the segmented data. The proposed approach is optimized with the use of a Genetic Algorithm (GA) that selects optimal feature subsets to maximize its performance. Combining ML and DL methods in Medical Image Processing is the most effective approach to detecting LC and its stages with the hope of achieving more precise findings. When accuracy is assessed and compared to other procedures, it becomes clear that the suggested methodology is more accurate (95%).</p>

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Chen, Jiangyu. „Design and Analysis of Home Control Complex System Based on PLC Technology“. Mobile Information Systems 2022 (18.08.2022): 1–9. http://dx.doi.org/10.1155/2022/6830120.

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The wide application of communication, automation, computer and other technologies not only provides a new direction for the development of home furnishing, but also makes the concept of “smart home” popular in recent years. The purpose of this study is to design a complex control system for smart healthcare home based on PLC technology. First, the research significance and background of this study are discussed, and the complex system, traditional PID control, and BP neural network algorithm are summarized. Second, the ZigBee wireless sensor network and PLC control system are studied, and the design of a smart health home control complex system based on PLC technology is analyzed. The experimental results show that when the indoor natural gas concentration is more than 1.25%, Y4 and Y3 are powered on, and Y2 is set as 1, that is, the alarm light is on, and the windows and exhaust fans are on. When the indoor flue gas (CO and CO2) concentration exceeds 0.06%, Y4 and Y3 are powered on, Y2 is set as 1, the alarm light is on, and the window exhaust fan is on. When the infrared detection output is 1, Y4 is powered on, Y2 is reset, the window is closed, and the alarm light is on. The human-machine interface of the Android mobile terminal of this system can be directly operated by the user and real-time monitoring data, reflecting the convenience of the design. Therefore, the design of complex home control system is of great significance in the home industry.

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Nasution, Arya Rudi, Fauzi S. Wahyudi, Chandra A. Siregar, Affandi Affandi und Zahrul Fuadi. „Pengaruh sudut twist drill terdahap kekasaran dan kebulatan pada proses pemesinan drilling“. SINTEK JURNAL: Jurnal Ilmiah Teknik Mesin 17, Nr. 1 (01.06.2023): 1. http://dx.doi.org/10.24853/sintek.17.1.1-6.

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Coolant and twist drill angle is one of the factors that affect the quality of the workpiece. Coolant selection and twist drill angle are useful for reducing hole roughness and increasing drill hole precision. In addition, the coolant must be easily degraded in the environment so that the environment is not polluted. An example of coconut oil is oil that can be degraded in the environment. This study aims to determine the effect of coconut oil (CO) and drill bit angle on the hole and hole precision obtained during the drilling process. In experimental testing, conventional drilling machines are used for test testing. the tests were carried out under various machining parameters, namely spindle rotation speed of 1100 rpm, drill bit angles of 130° and 135°. Based on these parameters, the spindle rotation speed of 1100 rpm and the drill bit angle of 135° is rougher than the drilling results for the spindle rotation speed of 1100 rpm and the drill bit angle of 130°. In addition, the roundness of the drilled holes for a spindle rotational speed of 1100 rpm and a drill bit angle of 130° is more precise than the spindle rotation speed of 1100 rpm and a drill bit angle of 135°.

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Tlhabadira, Isaac, Ilesanmi Daniyan und Abou El Hossein Khaled. „Determination of the Accuracy of Holes produced by Deep Drilling of Ti-6Al-4V Titanium Alloy“. International journal of applied engineering and technology (London) 5, Nr. 3 (29.09.2023): 171–84. http://dx.doi.org/10.61485/ijaet/v5-3-2023-22.

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Deep drilled holes in titanium alloys are broad in terms of the engineering and fabrication application in various products. The accuracy of deep drilling, tool wear, chip morphology and hole surface-wear are determined in this study. A sequence of machining tests were conducted to examine the deep drilling of Ti6Al4V alloy behaviour. Furthermore, a model that describes and improves the accuracy of holes in deep drilling of Ti6Al4V using High Speed Steel (HSS) drills was investigated, with the upshot of cutting limits on process indicators on tool wear and chips for modern manufacturing industries. The factorial design methodology for experiments was employed to investigate the influence of the cutting parameters on hole accuracy. Drilling were carried out on a solid cylindrical shaft of titanium alloy Ti-6Al4V using a 5-axis, Computer Numerical Control (CNC) milling machine and 13 piece of 10 mm diameter drill bits made from HSS Co and DMU 80 monoblock DECKEL MAHO. The surface corrosion and wear of the samples were also investigated using the Scanning Electron Microscopy (JEOL-SEM). The results obtained indicated that high tool wear results in short tool life when drilling at high speeds and feeds. The 10 mm HSS Co drill fails at high speeds of between 1272-640 rev/min and drill without failure at speeds of 630-318 rev/min for deep drilling of Ti-6Al-4V. The combination of 318 rev/min and 25 mm/min produces the preferred short and discontinuous chips. Thus study can assist drilling operators in obtaining accurate holes during deep drilling of Ti6Al4V.

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Bongard, Josh. „The Utility of Evolving Simulated Robot Morphology Increases with Task Complexity for Object Manipulation“. Artificial Life 16, Nr. 3 (Juli 2010): 201–23. http://dx.doi.org/10.1162/artl.2010.bongard.024.

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Embodied artificial intelligence argues that the body and brain play equally important roles in the generation of adaptive behavior. An increasingly common approach therefore is to evolve an agent's morphology along with its control in the hope that evolution will find a good coupled system. In order for embodied artificial intelligence to gain credibility within the robotics and cognitive science communities, however, it is necessary to amass evidence not only for how to co-optimize morphology and control of adaptive machines, but why. This work provides two new lines of evidence for why this co-optimization is useful: Here we show that for an object manipulation task in which a simulated robot must accomplish one, two, or three objectives simultaneously, subjugating more aspects of the robot's morphology to selective pressure allows for the evolution of better robots as the number of objectives increases. In addition, for robots that successfully evolved to accomplish all of their objectives, those composed of evolved rather than fixed morphologies generalized better to previously unseen environmental conditions.

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Kit Lim, Leonard Whye. „Recently Emerged Genome Wide Computational Enhancer Target Prediction Tools: A Brief Survey“. International Journal of Zoology and Animal Biology 6, Nr. 1 (2023): 1–8. http://dx.doi.org/10.23880/izab-16000440.

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Enhancers are non-coding genomic regulatory elements capable of elevating gene transcription in various biological as well as developmental stages in the host organism. Discovered since 1981, the enhancers play major roles in genetic disease onset and development, orchestrating gene regulation patterns even across the same species via the sequence variations. To date, predicting enhancers and their targets remain a daunting task as universal enhancer markers are yet to be discovered. Computational enhancer target prediction involves three major approaches: supervised, unsupervised and semi-supervised machine learning methods which work on enhancer target features such as enhancer-promoter distance, closest promoter, co-conservation and correlation of molecular signals. In this review, we introduced some recently emerged enhancer target prediction tools as well as their modus operandi, in hope that we can provide future directions towards the development of a more robust tool to aid in the advancement of enhancer targeted treatment researches.

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Owodiong-Idemeko, B.M und Adubi, K.O. „HOME ECONOMICS RETIREES: PROSPECTS AND CHALLENGES IN HARNESSING GARMENT CONSTRUCTION SKILLS FOR SECURING FAMILY FUTURE SUSTAINABILITY IN RETIREMENT.“ Nigeria Journal of Home Economics (ISSN: 2782-8131) 10, Nr. 6 (30.06.2022): 91–99. http://dx.doi.org/10.61868/njhe.v10i6.102.

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The study involved 120 Home Economics Association (HETAN) members from Badagry and Ojo Local Government areas of Lagos state. The objectives where to ascertain the various garment construction skills, evaluate the prospects of harnessing the various skills, assess the challenges faced by Home Economics retires in harnessing garment construction skills for sustenance in securing family future in retirement. Three hypotheses were formulated and a thirty-seven (37) item questionnaire was the main instrument used to collect data for the study. The statistical tools used were frequency count, percentages, mean, and Friedman test for significance. The study reveals that 114 (95.0%) agreed retirees should have the skill of handling the sewing machine. The majority 93(77.5%) agreed professionalism in pattern drafting is important. Majority 114(95.0%) agreed taking appropriate body measurements is necessary. Majority 105(87.5%) agreed skill of constructing garment according to use. 63(52.5%) have the challenge of setting money aside for business start-up before retirement. 78 (65.0%) do not want to have family responsibilities after retirement. 108 (90.0%) agreed gratuities are not promptly paid. 78(65.0%) agreed retirees who are not active die early. Majority 111(92.5%) agreed Home Economics retirees must be active in business. Majority 102 (85%) agreed they have thought of garment construction as a business when they retire. In conclusion, garment construction affords Home Economics retiree’s lots of opportunities for family sustenance in retirement. Therefore, the following recommendation is made: Lagos State Government should pay retirees benefits promptly; would-be retirees should join a functioning co-operative society.

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Liu, Wei, Xianming Tu, Zhenyuan Jia, Wenqiang Wang, Xin Ma und Xiaodan Bi. „An improved surface roughness measurement method for micro-heterogeneous texture in deep hole based on gray-level co-occurrence matrix and support vector machine“. International Journal of Advanced Manufacturing Technology 69, Nr. 1-4 (19.05.2013): 583–93. http://dx.doi.org/10.1007/s00170-013-5048-0.

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Ullah, Sehat, Paul Richard, Samir Otmane, Mickael Naud und Malik Mallem. „Human Performance in Cooperative Virtual Environments: the Effect of Visual Aids and Oral Communication“. International Journal of Virtual Reality 8, Nr. 4 (01.01.2009): 79–86. http://dx.doi.org/10.20870/ijvr.2009.8.4.2752.

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The Cooperative virtual environments, where users simultaneously manipulate objects, are one of the subfields of Collaborative virtual environments (CVEs). In this paper we simulate the use of two string based parallel robots in cooperative teleoperation task. Two users setting on separate machines connected through local network operate each robot. In this context, we investigate the effects of visual aids and oral communication on cooperation, co-presence and users performance. Ten volunteers had to cooperatively perform a peg-in-hole task. A second group of ten subjects perform the same task in a single user setup. The objective of the two experiments is twofold, firstly to compare the task's complexity of single user setup with that of the cooperative environment. Secondly we examine the influence of visual aids and oral communication on user's performance in the two different setups. Results revealed that shadow has a significant effect on task execution while arrows and oral communication not only increase users' performance but also enhance the sense of co-presence and awareness. We also observed that cooperative manipulation was more difficult as compared to single user manipulation.

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Weaver, Lindell K. „Three cases of clinically significant inaccurate carboxyhemoglobin measurement“. Undersea and Hyperbaric Medicine 49, Nr. 2 (01.03.2022): 172–77. http://dx.doi.org/10.22462/03.04.2022.2.

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Background: Clinicians often rely on measurement of carboxyhemoglobin (COHb) to confirm or rule out a diagnosis of carbon monoxide (CO) poisoning. Methods: We report two cases of false negative COHb in patients with CO poisoning and one case of false positive COHb in a patient without CO poisoning. Results: In the first case, a 20-year-old male developed headache, confusion, and near-syncope while operating a gasoline-powered pressure washer in an enclosed space. In the emergency department (ED), his COHb was 1.8%, but this level was disregarded, and he was referred for hyperbaric oxygen. His COHb just before hyperbaric oxygen was 4.1%, and later analysis of his blood collected at ED arrival revealed a COHb of 20.1%. The referral ED blood gas machine calibration and controls were within specification. In the second case, a 45-year-old male presented with several others to the ED with symptoms of CO poisoning after exposure at a conference. All others had elevated COHb levels, but his COHb was 2%. He was discharged but returned shortly with continued symptoms and requested his COHb be repeated. The repeat COHb was 17% (84 minutes after the first). After three hours of oxygen, his COHb was 7%. In the final case, an 83-year-old non-smoking male presented to an ED with breathlessness and tachypnea and was diagnosed with COVID-19 pneumonia. His COHb was 7.1%, but he reported living in an all-electric home. Another adult who lived with him and rode with him to the ED was asymptomatic and had a COHb of 3%. Later, COHb of 1.9% was measured from blood collected at ED arrival, and gas chromatography/mass spectrometry confirmed this result (2%). Conclusions: COHb levels are not always accurate. Clinicians should use clinical judgment to manage their patients, including rejecting laboratory values that do not fit the clinical situation.

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Hannibal, Joseph T. „The air-abrasive technique“. Paleontological Society Special Publications 4 (1989): 227–36. http://dx.doi.org/10.1017/s2475262200005189.

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AIR-ABRASIVE, also called Airbrasive (a trademark of the Pennwalt S.S. White Co.), units are in effect miniature sandblasting machines. The units propel an abrasive, by means of a gas, through a flexible hose attached to a handpiece. Originally designed for dental and industrial uses, these units are now widely used for preparing fossils. The air abrasive can be used by itself or in combination with other techniques to excavate fossils from matrix, to remove matrix from areas of specimens for detailed study, and to elevate specimens above the surface of the matrix for display and photography. The technique of preparing fossils using the air abrasive has been previously described and discussed by a number of authors, notably by Stucker (1961), Stucker et al. (1965), Rixon (1976, p. 75–77), and Converse (1984, p. 42–49).

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Kumar, Sanjay, und Aleksander Czekanski. „Optimization of parameters for SLS of WC-Co“. Rapid Prototyping Journal 23, Nr. 6 (17.10.2017): 1202–11. http://dx.doi.org/10.1108/rpj-10-2016-0168.

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Purpose WC-Co is a well-known material for conventional tooling but is not yet commercially available for additive manufacturing. Processing it by selective laser sintering (SLS) will pave the way for its commercialization and adoption. Design/methodology/approach It is intended to optimize process parameters (laser power, hatch spacing, scan speed) by fabricating a bigger part (minimum size of 10 mm diameter and 5 mm height). Microstructural analysis, EDX and hardness testing is used to study effects of process parameters. Optimized parameter is ascertained after fabricating 49 samples in preliminary experiment, 27 samples in pre-final experiment and 9 samples in final experiment. Findings Higher laser power gives rise to cracks and depletion of cobalt while higher scan speed increases porosity. Higher hatch spacing is responsible for delamination and displacement of parts. Optimized parameters are 270 W laser power, 500 mm/s scan speed, 0.04 mm layer thickness, 0.04 mm hatch spacing (resulting in energy density of 216 J/mm3) and 200°C powder bed temperature. A part comprising of small hole of 2 mm diameter, thin cylindrical pin of 0.5 mm diameter and thin wall of 2 mm width bent up to 30° angle to the base plate is fabricated. In order to calculate laser energy density, a new equation is introduced which takes into account both beam diameter and hatch spacing unlike old equation does. In order to calculate laser energy density, a new equation is formulated which takes into account both beam diameter and hatch spacing unlike old equation does. WC was not completely melted as intended giving rise to partial melting-type binding mechanism. This justified the name SLS for process in place of SLM (Selective Laser Melting). Research limitations/implications Using all possible combination of parameters plus heating the part bed to maximum shows limitation of state-of-the-art commercial powder bed fusion machine for shaping hardmetal consisting of high amount of WC (83 wt. per cent). Practical implications The research shows that microfeatures could be fabricated using WC-Co which will herald renewed interest in investigating hardmetals using SLS for manufacturing complex hard tools, molds and wear-resistance parts. Originality/value This is the first time micro features are successfully fabricated using WC-Co without post-processing (infiltration, machining) and without the help of additional binding material (such as Cu, Ni, Fe).

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Chiu, Po-Fan, Robert Chen-Hao Chang, Yung-Chi Lai, Kuo-Chen Wu, Kuan-Pin Wang, You-Pen Chiu, Hui-Ru Ji, Chia-Hung Kao und Cheng-Di Chiu. „Machine Learning Assisting the Prediction of Clinical Outcomes following Nucleoplasty for Lumbar Degenerative Disc Disease“. Diagnostics 13, Nr. 11 (26.05.2023): 1863. http://dx.doi.org/10.3390/diagnostics13111863.

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Background: Lumbar degenerative disc disease (LDDD) is a leading cause of chronic lower back pain; however, a lack of clear diagnostic criteria and solid LDDD interventional therapies have made predicting the benefits of therapeutic strategies challenging. Our goal is to develop machine learning (ML)–based radiomic models based on pre-treatment imaging for predicting the outcomes of lumbar nucleoplasty (LNP), which is one of the interventional therapies for LDDD. Methods: The input data included general patient characteristics, perioperative medical and surgical details, and pre-operative magnetic resonance imaging (MRI) results from 181 LDDD patients receiving lumbar nucleoplasty. Post-treatment pain improvements were categorized as clinically significant (defined as a ≥80% decrease in the visual analog scale) or non-significant. To develop the ML models, T2-weighted MRI images were subjected to radiomic feature extraction, which was combined with physiological clinical parameters. After data processing, we developed five ML models: support vector machine, light gradient boosting machine, extreme gradient boosting, extreme gradient boosting random forest, and improved random forest. Model performance was measured by evaluating indicators, such as the confusion matrix, accuracy, sensitivity, specificity, F1 score, and area under the receiver operating characteristic curve (AUC), which were acquired using an 8:2 allocation of training to testing sequences. Results: Among the five ML models, the improved random forest algorithm had the best performance, with an accuracy of 0.76, a sensitivity of 0.69, a specificity of 0.83, an F1 score of 0.73, and an AUC of 0.77. The most influential clinical features included in the ML models were pre-operative VAS and age. In contrast, the most influential radiomic features had the correlation coefficient and gray-scale co-occurrence matrix. Conclusions: We developed an ML-based model for predicting pain improvement after LNP for patients with LDDD. We hope this tool will provide both doctors and patients with better information for therapeutic planning and decision-making.

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Dharmawirawan, Dimas Ari, und Robiana Modjo. „Identifikasi Bahaya Keselamatan dan Kesehatan Kerja pada Penangkapan Ikan Nelayan Muroami“. Kesmas: National Public Health Journal 6, Nr. 4 (01.02.2012): 185. http://dx.doi.org/10.21109/kesmas.v6i4.98.

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Kelautan Kepulauan Seribu pada tahun 2009 terdapat 1.722 penduduk berprofesi sebagai nelayan. Sebanyak 299 orang berprofesi nelayan muroami yang menghadapi bahaya keselamatan dan kesehatan kerja tinggi dan hingga saat ini mereka belum mengetahui bahaya pekerjaan tersebut.Penelitian deskriptif dengan analisis kualitatif ini, bertujuan mendapatkan gambaran bahaya kegiatan penangkapan ikan nelayan muroami di Kelurahan Pulau Panggang, Kabupaten Kepulauan Seribu. Penelitian ini hanya mengamati para penyelam kompresor sebagai subjek penelitian dengan mengunakan metode identifikasi bahaya yaitu Job Hazard Analysis. Bahaya keselamatan dan kesehatan kerja pada tahapan aktivitas penangkapan ikan terdiri atas tahapan persiapan, tahapan penyelaman, dan tahapan penanganan hasil penangkapan. Bahaya yang dihadapi dikelompokkanmenjadi bahaya bagi keselamatan dan bahaya kesehatan, bahaya bagi keselamatan pekerja meliputi ombak, lantai licin, duri ikan, terjepit, bahan bakar mesin kompresor, selang api korosif, tekanan udara pada tabung mesin kompresor, tuas terlepas, karang, gigitan biota laut, selang tertekuk, terputus, atau bocor dan tubuh yang tersangkut baling-baling kapal. Bahaya kesehatan meliputi ergonomik, kebisingan, tekanan ekstrim, temperatur dingin, temperatur panas, sengatan ikan dan karang beracun, gas CO, CO2 dan nitrogen.Kata Kunci: Penangkapan ikan, nelayan, penyelam kompresorAbstractData from Fisheries and Maritime Affairs Thousand Islands goverment in 2009 there were 1722 people living as fishermen, with 299 people living as muroami fishermen. Muroami Fishermen is one of the informal sector jobs which have high dangers of occupational health and safety, until now the fishermen don’t know the danger of their jobs.The study is descriptive with the approach of this qualitative analysis, aims to find the description on the danger of muroami fishing activities catch of fish, in Kelurahan Panggang Island, Thousand Islands District. This study only observed without intervention to the compressor divers as subjects of research. Hazard identification methods used Job Hazard Analysis. The results obtained OHS hazard description of fishing activities, consisting of: stage of preparation, 2. Stages Stage diving and handling of the arrest. Based on these stages, found the picture hazards can be classified into 2, namely: a danger to the safety of workers (the waves, the ship slippery floors, thorn fish, stuck, compressor fuel, corrosive fire hose, air pressure in the tube compressor machines, lever regardless, the coral, marine biota bites, the bent hose, the hose is disconnected, the hose is leaking and body caught in the propeller ship) and health hazards (ergonomics, noise, extreme pressure, cold temperatures, hot temperatures, and fish stings toxic reef, gas CO, CO2 and nitrogen).Key words: Catch of fish, fisherman, compressor divers

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Lee, Chang-Shing, Mei-Hui Wang, Yi-Lin Tsai, Wei-Shan Chang, Marek Reformat, Giovanni Acampora und Naoyuki Kubota. „FML-Based Reinforcement Learning Agent with Fuzzy Ontology for Human-Robot Cooperative Edutainment“. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 28, Nr. 06 (25.11.2020): 1023–60. http://dx.doi.org/10.1142/s0218488520500440.

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The currently observed developments in Artificial Intelligence (AI) and its influence on different types of industries mean that human-robot cooperation is of special importance. Various types of robots have been applied to the so-called field of Edutainment, i.e., the field that combines education with entertainment. This paper introduces a novel fuzzy-based system for a human-robot cooperative Edutainment. This co-learning system includes a brain-computer interface (BCI) ontology model and a Fuzzy Markup Language (FML)-based Reinforcement Learning Agent (FRL-Agent). The proposed FRL-Agent is composed of (1) a human learning agent, (2) a robotic teaching agent, (3) a Bayesian estimation agent, (4) a robotic BCI agent, (5) a fuzzy machine learning agent, and (6) a fuzzy BCI ontology. In order to verify the effectiveness of the proposed system, the FRL-Agent is used as a robot teacher in a number of elementary schools, junior high schools, and at a university to allow robot teachers and students to learn together in the classroom. The participated students use handheld devices to indirectly or directly interact with the robot teachers to learn English. Additionally, a number of university students wear a commercial EEG device with eight electrode channels to learn English and listen to music. In the experiments, the robotic BCI agent analyzes the collected signals from the EEG device and transforms them into five physiological indices when the students are learning or listening. The Bayesian estimation agent and fuzzy machine learning agent optimize the parameters of the FRL agent and store them in the fuzzy BCI ontology. The experimental results show that the robot teachers motivate students to learn and stimulate their progress. The fuzzy machine learning agent is able to predict the five physiological indices based on the eight-channel EEG data and the trained model. In addition, we also train the model to predict the other students’ feelings based on the analyzed physiological indices and labeled feelings. The FRL agent is able to provide personalized learning content based on the developed human and robot cooperative edutainment approaches. To our knowledge, the FRL agent has not applied to the teaching fields such as elementary schools before and it opens up a promising new line of research in human and robot co-learning. In the future, we hope the FRL agent will solve such an existing problem in the classroom that the high-performing students feel the learning contents are too simple to motivate their learning or the low-performing students are unable to keep up with the learning progress to choose to give up learning.

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Manoharan, Samuel, und Narain Ponraj. „Analysis of Complex Non-Linear Environment Exploration in Speech Recognition by Hybrid Learning Technique“. December 2020 2, Nr. 4 (19.02.2021): 202–9. http://dx.doi.org/10.36548//jiip.2020.4.005.

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Recently, the application of voice-controlled interfaces plays a major role in many real-time environments such as a car, smart home and mobile phones. In signal processing, the accuracy of speech recognition remains a thought-provoking challenge. The filter designs assist speech recognition systems in terms of improving accuracy by parameter tuning. This task is some degree of form filter’s narrowed specifications which lead to complex nonlinear problems in speech recognition. This research aims to provide analysis on complex nonlinear environment and exploration with recent techniques in the combination of statistical-based design and Support Vector Machine (SVM) based learning techniques. Dynamic Bayes network is a dominant technique related to speech processing characterizing stack co-occurrences. This method is derived from mathematical and statistical formalism. It is also used to predict the word sequences along with the posterior probability method with the help of phonetic word unit recognition. This research involves the complexities of signal processing that it is possible to combine sentences with various types of noises at different signal-to-noise ratios (SNR) along with the measure of comparison between the two techniques.

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Manoharan, Samuel, und Narain Ponraj. „Analysis of Complex Non-Linear Environment Exploration in Speech Recognition by Hybrid Learning Technique“. December 2020 2, Nr. 4 (19.02.2021): 202–9. http://dx.doi.org/10.36548/jiip.2020.4.005.

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Recently, the application of voice-controlled interfaces plays a major role in many real-time environments such as a car, smart home and mobile phones. In signal processing, the accuracy of speech recognition remains a thought-provoking challenge. The filter designs assist speech recognition systems in terms of improving accuracy by parameter tuning. This task is some degree of form filter’s narrowed specifications which lead to complex nonlinear problems in speech recognition. This research aims to provide analysis on complex nonlinear environment and exploration with recent techniques in the combination of statistical-based design and Support Vector Machine (SVM) based learning techniques. Dynamic Bayes network is a dominant technique related to speech processing characterizing stack co-occurrences. This method is derived from mathematical and statistical formalism. It is also used to predict the word sequences along with the posterior probability method with the help of phonetic word unit recognition. This research involves the complexities of signal processing that it is possible to combine sentences with various types of noises at different signal-to-noise ratios (SNR) along with the measure of comparison between the two techniques.

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Yun, Y. N., H. M. Zhang und C. J. Li. „Automatic Detection Apparatus Development of Steel Cord Conveyor Belt“. Key Engineering Materials 455 (Dezember 2010): 516–20. http://dx.doi.org/10.4028/www.scientific.net/kem.455.516.

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Steel core belts are widely used in long-distance, large capacity, large angle of mine, metallurgy, port, electricity and other departments of the large-scale transportation systems. According to incomplete statistics, this kind of belt accident 93.75% occurred in the joints and most are due to joints tic was not timely detected. Hence, non-destructive detection of belt is the key to the whole transportation system’s safety. For steel core belt automatic detection technology, deep research has been carried out at home and abroad. Detection apparatus was developed based on the electromagnetic theory and principle of X-ray, however, some varying defects existed in the industrial applications. Automatic detection apparatus of steel cord conveyor belt, developed by Pingdingshan Industry Polytechnic College and Shanxi Huaning Beier Measurement & Control Co. Ltd., integrated both advantages of electromagnetic detection and X-ray detection. It overcomes the difficulties of X-ray machine explosion proof and long time radiation. This kind of automatic detection apparatus has been installed and worked well in more than 30 mines and achieved good economic and social benefits since it was installed in Zhong Ping Energy Chemical Group’s 12th main slope conveyor.

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Lee, Sang Bae, Jung Y. Cha, Doug Youn Lee, Kyeong Jun Park, Kyoung Nam Kim und Kwang Mahn Kim. „Effect of Cyanoacrylate-Based β-TCP Adhesive on Pullout Strength of Orthodontic Mini-Screw“. Key Engineering Materials 330-332 (Februar 2007): 1361–64. http://dx.doi.org/10.4028/www.scientific.net/kem.330-332.1361.

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In this study, the effect of cyanoacrylate-based β-tricalcium phosphate (β-TCP) on pullout strength of orthodontic mini-screw was evaluated. New cements were prepared by mixing Histoacryl® (n-butyl cyanoacrylate) and acid-treated β-tricalcium phosphate. The ratios of β-TCP to Histoacryl® were 0, 0.5, 1.0, and 2.0. Artificial bone blocks were used as a substrate for the miniscrew implantation. The test groups were divided into three groups (one solid bone block [group 1] and a bone block with a 0.9 mm hole [group 2], and a bone block with a 2.5 mm hole [group 3]). And each group was divided into subgroups according to cement usage and non-usage. The used artificial bone density was 0.64g/cm2. Pullout strengths were determined using a universal testing machine. Statistical analysis was performed using the SPSS 9.0 for Windows program. Paired samples t-tests and ANOVA were used with p<0.05. The maximum pullout strengths were 295.9 ± 3.8 N for group 1, 261.1±15.0 N for group 2, and 273.2±20.0 N for group 3. In group 1 and 2, the pullout strength in the subgroup using cement was higher than that of the subgroup of not using cement (p<0.05). In group 3, the pullout strength in the subgroups using cyanoacrylate-based β- TCP cement was higher than that of the subgroup using conventional glass ionomer cement (GC Fuji-I, GC Co., Tokyo, Japan) (p<0.05). These results indicate that our β-TCP/Histoacryl® cements have the potential to enhance pullout strength of the orthodontic mini-screw.

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Ihlenfeldt, S., U. Frieß, M. Wabner und R. Tehel. „Berücksichtigung des positionsabhängigen Maschinenverhaltens innerhalb der Simulation*/Position depending dynamic machine tool simulation by holistic FEM models“. wt Werkstattstechnik online 105, Nr. 05 (2015): 275–84. http://dx.doi.org/10.37544/1436-4980-2015-05-27.

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Die Leistungsfähigkeit und Ressourceneffizienz moderner Produktionssysteme wird wesentlich durch ihr dynamisch-mechatronisches Verhalten bestimmt. Um quantitative Aussagen hinsichtlich auftretender Bahnabweichungen zu erhalten, hat sich die kombinierte Simulation von mechanischer Struktur und Antriebsregelung etabliert. Während der Verfahrbewegung ändert sich jedoch das mechanische Strukturverhalten durch die Verlagerung von Komponenten wesentlich. In der flexiblen Mehrkörpersimulation (MKS) existieren verschiedene Ansätze dynamische Bahnbewegungen abzubilden, welche jedoch komplexe, genauigkeitsreduzierende Reduktionen der FEM (Finite-Elemente-Methode)-Submodelle und/oder aufwendige, zeitsynchronisierte Co-Simulation in unterschiedlichen Simulationsumgebungen erfordern. Innerhalb geschlossener FEM-Umgebungen bieten transiente Rechnungen eine hohe Abbildungsgüte für die Zeitbereichssimulation, die Berechnungsdauer für große Modelle schließt jedoch Parameterstudien und die Integration der Regelung de facto aus. Es wird ein alternativer Ansatz unter Nutzung holistischer FEM-Modelle beschrieben, welcher innerhalb der Grenzen der linearen Modalanalyse eine effiziente Simulation des dynamischen Bahnverhaltens unter Berücksichtigung großer Verfahrbewegungen erlaubt.   The capabilities of state-of-the art machine tools are significantly limited by their dynamic-mechatronic system properties. The combined simulation of the mechanical structure and control has been established to determine dynamic tool-path inaccuracies. While machining a work piece, the structural components of a machine tool change their position towards each other, which as a result leads to a different mechanical system. There exist different strategies to include that position dependent behavior within the coupled multi body simulation. However complex model-reduction methods for the flexible FEM substructures are necessary. Furthermore a time-synchronized parallel simulation between the simulation of the mechanical structure and the simulation of the control - typically carried out as digital block simulation - is necessary. On the other hand transient simulation approaches in the FEM environment of the overall structure are theoretically capable to represent realistic models but are by fare to complex and time-consuming to be implemented for time domain simulations including control. Based on these inadequatenesses the paper shows a new approach to consider the changing system behavior due to large movements of structural components based on holistic FEM-models. It allows an efficient integrated simulation inside the digital block simulation within the limits of a linear modal analysis.

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Zhou, Binghua, Yiguo Xue, Mingtian Li, Zhiqiang Li, Xueliang Zhang und Yufan Tao. „Longitudinal jet ventilation calculation and application of long highway tunnel“. Journal of Engineering, Design and Technology 16, Nr. 2 (03.04.2018): 256–69. http://dx.doi.org/10.1108/jedt-07-2017-0070.

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Purpose When a vehicle passes through a long highway tunnel, the smoke it discharges accumulates in the tunnel. High smoke concentration has an important influence on the driver’s health and driving safety. The use of numerous jet fans to diffuse the smoke causes excessive energy consumption, so it is of significant practical value to design suitable tunnel ventilation. Design/methodology/approach The study is based on the continuum hypothesis, incompressible hypothesis, steady flow hypothesis and similar hypothesis of gas in a long highway tunnel. These hypotheses calculate the gas emissions and wind demand in a long highway tunnel given the deployment of the jet fan program. Findings This program selects each of the two 1120-type jet machine group and sets up 13 groups; each group has an interval of 184.5 m in the end. The analysis of air test results when the tunnel is in operation shows that CO and smoke concentrations meet the design requirements, which can provide reference for a similar engineering design later. Originality/value At present, a highway tunnel is recognized at home and abroad by means of clearance of longitudinal ventilation, which is 2,000 m. In view of this, this paper is based on the theory of longitudinal jet ventilation of a highway tunnel, whose length is more than 2,000 m, to calculate the ventilation and apply it to a tunnel’s ventilation design.

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XU, YINCHAO, KANGHUA CHEN, SHEQUAN WANG, SONGYI CHEN und XIANGMING CHEN. „INFLUENCE OF PRETREATMENT ON DIAMOND-COATED TOOL NUCLEATION AND MACHINING PERFORMANCE“. Surface Review and Letters 24, Supp02 (November 2017): 1850020. http://dx.doi.org/10.1142/s0218625x18500208.

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The CVD diamond film with favorable adhesion and relatively thinner thickness is essential facing for its application on drills for machining carbon fiber reinforced plastics (CFRP), with regard to either the tool lifetime or the machining quality. A 500-nm-thick CrN layer was deposited by the cathode arc technique on slight chemical etched WC–Co 6[Formula: see text]wt.% drill, and nano-crystalline diamond (NCD) is subsequently deposited by the hot filament chemical vapor deposition (HFCVD) technique. The same NCD film is also deposited on the drills pretreated only by the slight chemical etching or the CrN interlayer, which are adopted as comparisons in the present study. The nucleation and growth of diamond film and the cutting performance of the coated drills are systematically studied. The results show that the drill pretreated by the slight chemical etching and CrN interlayer can acquire highest nucleation density (ND) compared to the other pretreatment methods as it sufficiently prevents the Co diffusion. The diamond-coated drill with deep chemical etching was used for comparison to study the machining quality when drilling CFRP. During machining the CFRP, the failure mode of the diamond-coated drill is mainly the delamination and peeling off of the diamond film at areas with stress concentration, while the diamond-coated drill pretreated by slight chemical etching [Formula: see text] CrN interlayer can retard such failure. The exit hole quality of CRFP machined by drill pretreated with slight chemical etching [Formula: see text] CrN interlayer is better than that by drill pretreated with deep chemical etching, which is ascribed to the different cutting edges of the drills.

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Pozhitkov, Alexander, Theophilus Tandoh, Mahmoud Singer, Allen Mao, Flavia Pichiorri und Samir Courdy. „Poseidon - a Collaborative Environment for the Daratumumab Sensitivity Research Trial“. Blood 142, Supplement 1 (28.11.2023): 7177. http://dx.doi.org/10.1182/blood-2023-182239.

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Precision Oncology Software Environment Interoperable Data Ontologies Network (POSEIDON) was conceived at City of Hope (COH) as a cloud-based computational and data storage platform. The platform brings together patient data from the COH electronic medical records (EMR), research data from the laboratories and enables parallelized computation on multiprocessor virtual machines. In POSEIDON, well-established computational environments, such as R, co-exist with custom-written pipelines. Daratumumab - an anti-CD38 therapeutic antibody - is a drug used for maintenance treatment of multiple myeloma. Daratumumab is administered after the stem cell transplant. Despite of its effectiveness, disease progression inevitably occurs after some time. This leads to patients not responding to daratumumab any longer. A Daratumumab sensitivity research trial is being conducted at COH, seeking to elucidate how multiple myeloma gains resistance to Daratumumab. Many patients undergo 20-22 treatment cycles, while some progress early and the cycles are stopped. Samples of peripheral blood of the patients on the trial are collected after each cycle of Daratumumab administration. All blood specimens are analyzed with CyTOF flow cytometry to determine and quantify cell populations. A fraction of samples is also analyzed with single-cell RNAseq to determine gene expression dynamics per population of cells. Finally, the laboratory values of each patient are added to the body of data. Given the multivariate longitudinal nature of the study as well as the sheer volume of the obtained data, a robust well-structured informatics system is needed. Here we present application of the POSEIDON environment to our ongoing trial. As shown on the Figure, POSEIDON is established within a cloud (AWS, Azure), which provides practically unlimited space for storage. The storage is redundantly distributed across multiple cloud nodes such that the data loss is unlikely. Also, any number of virtual machines may be deployed to perform computation. Specifically, the structured data are stored in POSEIDON in the SQLite database, which is in turn updated every two hours from the SQL Server located at COH. The SQL server at COH is populated by the laboratory with processed flow cytometry data and patient's records. R notebook(s) within POSEIDON communicate with the SQLite database to extract, transform and analyze the trial's data. The investigators from the collaborating laboratories (i.e., Hematology, Mathematical Oncology) are interacting with the notebooks to perform the analyses and present the results. In addition, the raw data are stored in POSEIDON as well. Therefore, POSEIDON establishes a single source of truth paradigm, which presents a single version of data to all involved parties. The cost associated with POSEIDON is twofold: computation and storage. Specifically, in our case a virtual machine of 4 CPU cores, 16 GB RAM and 128 GB solid-state storage space consumed $0.23 per hour when running. The storage cost for 14.6 GB of the project's data is $0.28 / month. In conclusion, it is important to note that POSEIDON can be scaled up beyond COH and beyond hematology.

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Sottas, Beat. „Blind Flight into the eHealth World? Deficits in the education of health professionals hamper process of professionalization. Contribution to the HoGe conference 2018 „Digital learning and teaching“ / Blindflug in die eHealth-Welt? Bildungsdefizite machen Professionalisierungsbemühungen der Gesundheitsberufe zunichte. Beitrag zur HoGe–Tagung 2018 „Digitales Lernen und Lehren““. International Journal of Health Professions 6, Nr. 1 (25.05.2019): 68–78. http://dx.doi.org/10.2478/ijhp-2019-0008.

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Abstract Educational strategies often derive from ideas of eminent founders. They convey traditional conceptions of good practice and professional identity. However, the environment changes dramatically. Megatrends such as multimorbidity, staff shortage, claims for outcome proofs, expectations of the Millennials, and also digitalization produce slow but steady efects. Yet, the question if education adequately tackles the challenges is avoided. Strategy papers show that arrangements and instruments have been adapted, but not contents. Deficits are visible primarily in facing the digital transformation which goes along with the implementation of industrial management models. Staf shortage and rising demands ease the introduction of digital assistants and robots also in Europe. Those entering a health profession shall have androids as colleagues. One should, therefore, not expect that conventional concepts about caregiving as exclusive human relation building will persist. In addition, professional may experience a hurtful transition from evidence-based to algorithm-based practice. Discussions about digital transformation are strikingly lopsided. Efficiency, cost containment and safety are prominent arguments, some also promise more time for patients. Besides the aspect of being replaced, it is not asked what happens to the individuals and professionals. One could e. g. ask in which way artificial intelligence shapes human interaction and professional practice, participation, self-determination, patient orientation, therapeutic strategies and adherence. Instead of improving skills for tablets and tools, education should ask how professions and professionals can adequately be prepared to co-work with machines which may take decisions and conduct processes, and which may be considered more reliable colleagues by employers.

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Colangelo, Dave, Patricio Dávila und Immony Mèn. „Receipts and Receipts NB“. Interactive Film & Media Journal 3, Nr. 1 (06.06.2023): 82–89. http://dx.doi.org/10.32920/ifmj.v3i1.1685.

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This paper reports on two iterations of our ongoing Receipts project. The project serves as a means to experiment with and propose processes that use social practice and machine learning technologies to prepare testimonies and listeners to more clearly and impactfully speak, hear, and feel what it is like to respond to mimetic trauma and be part of an equity-deserving group in public space. The work is guided by the following question: How can the process of facilitating the preparation and presention of anonymized testimonies of discriminatory aggression in public spaces with the witnesses and victims of said agressions create structures of accountability, solidarity, healing, and community? The first project, Receipts (2020), was presented as part of The Bentway’s Safe in Public Space program in Toronto, and addressed anti-Asian aggression in public spaces. The second project, Receipts NB, in collaboration with ArtFix, an organization that works with artists with substance abuse and mental health lived experience in North Bay, will address the stigmatization and isolation of this community during the pandemic. It will be presented as part of IceFollies 2023, a week-long public art festival on frozen Lake Nipissing. These explorations emerge from and reflect upon a theoretical framework that connects visual culture, data creation, visual perception, cognition, machine learning processes, human-computer interaction, social practice and a practice-based framework for research-creation. The work is also informed by an approach to technoscience that uses a critical race, feminist, and decolonial lens. A necessary component of this framework is to prioritize equity through an emphasis on critical pedagogy, co-creation, and participatory art and design practice. The critical media art practices and processes of Receipts do not aim to replace identifying video as an important means of holding people accountable. Instead, we hope that the project can shape technical, social, cultural practices of testimony and listening and make collectivized community resistance resonate more deeply. We also reflect on how computer vision and artificial intelligence tools increasingly deployed as part of “smart city” infrastructures have been proposed as a means to address these issues in real time by predicting, identifying, and aggregating transgressions. Yet, in practice, these tools lack nuance, approximate and automate-out the importance of relationship building with communities, and have generally been used to identify patterns and build predictive surveillance that disproportionately disadvantages already discriminated-against groups. We hope that Receipts can serve as an example of how to engage the potentials of urban technology while also highlighting some of its pitfalls.

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Pozzan, Mario Cesare, Francesco Grande, Edoardo Mochi Zamperoli, Fabio Tesini, Massimo Carossa und Santo Catapano. „Assessment of Preload Loss after Cyclic Loading in the OT Bridge System in an “All-on-Four” Rehabilitation Model in the Absence of One and Two Prosthesis Screws“. Materials 15, Nr. 4 (20.02.2022): 1582. http://dx.doi.org/10.3390/ma15041582.

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The aim of this study was to evaluate the stability of prosthetic screws after applying cyclic loadings in an “all-on-four” rehabilitation model with the OT Bridge system. The model was tested both with and without anterior screws. Four implant analogues following the “all-on-four” concept were inserted in an edentulous mandibular resin model. An OT Bridge system with a Cr–Co prosthetic framework was fabricated. Depending on the presence or absence of one or two anterior screws on the implant analogues, three groups were created, i.e., Gr.1: three tightening screws, Gr.2: two tightening screws, Control Group: four tightening screws. Each single group underwent subsequent 400,000 cyclic loads, simulating approximately a year of chewing by using a dynamometer machine. This cycle was repeated five times for each group, and preload loss values were evaluated on each prosthetic screw after each cycle. All the data obtained were analyzed by one-way ANOVA and Student’s t-test. No statistically significant differences after intragroup analysis were found. A statistically significant difference within the Gr.1 between the screws in positions 33 and 36, equal to 15.2% (p-value = 0.0176), was found. The OT Bridge seems a useful system to maintain the retention of a prosthesis during mechanical stress conditions even in the absence of one screw in an “all-on-four” rehabilitation. This could represent a good solution to solve the esthetic problem of the screw buccal access hole for fixed solutions.

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Cerutti Torres, Joeluis Cerutti, Pablo Sánchez-Palencia, José Carlos Jiménez-Sáez, Perla Wahnón und Pablo Palacios. „Effect of Changing and Combining Trivalent Metals in the Structural and Electronic Properties of Cu-Based Crystal Delafossite Materials“. Crystals 14, Nr. 5 (29.04.2024): 418. http://dx.doi.org/10.3390/cryst14050418.

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Cu-based ternary oxides with delafossite structure have received considerable attention in recent years for their versatility in a wide range of applications, among which is the possibility to use them in heterostructure solar cells as hole transport layers, due to their promising behavior as p-type conducting oxides. Ab initio calculations have been performed with density functional theory to investigate the role of the trivalent metal within the CuMO2 structure and the dependence of structural and electronic properties with the species (M = Al, Ga, In, Fe, Cr, Co, Sc, Y) occupying the site of the metal. Generalized Gradient Approximation also including a Hubbard term and nonlocal Heyd–Scuseria–Enzerhof screened hybrid functional schemes were tested and their results were compared. Excellent agreement with experimental lattice parameters and measured gaps have been found. The use of hybrid functionals in HSE approximation considerably improves the bandgaps when compared with the experimental results but takes considerable time to converge, hence the need to explore less demanding methodologies. Trends in the geometry as well as in the electronic properties are discussed, and the effect of mixing different metals (CuMxN1−xO2, M, N being the aforementioned elements) in the geometry and electronic properties of these delafossite materials is investigated. Due to the high cost of HSE calculations, especially when supercells are needed to model several x concentrations, statistical models and techniques based on machine learning have also been explored to predict HSE bandgap values from GGA and structural information.

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Vodencarevic, A., K. Tascilar, F. Hartmann, M. Reiser, S. Bayat, J. Knitza, L. Valor et al. „SAT0055 PREDICTION OF FLARES FOR RHEUMATOID ARTHRITIS PATIENTS ON BIOLOGIC DMARDS USING MACHINE LEARNING AND SUBSETS OF VARIABLES AVAILABLE TO PHYSICIANS, PATIENTS AND PAYERS“. Annals of the Rheumatic Diseases 79, Suppl 1 (Juni 2020): 959.2–960. http://dx.doi.org/10.1136/annrheumdis-2020-eular.1553.

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Background:Today approximately 50 percent of patients with RA reach sustained remission. In a specific subset of RA patients in stable remission, biological Disease Modifying Anti-Rheumatic Drugs (bDMARDs) may be successfully tapered. However, it remains challenging to predict the patients’ individual flare risk. As we have recently shown, machine learning based on extensive clinical and laboratory data could be used to estimate individual flare risk [1].Objectives:In this study we aimed to investigate the performance of machine learning models trained with variables that are typically (1) immediately available to a physician during patient visits (clinical and demographic variables without laboratory values and composite disease activity scores), (2) theoretically available to patients at home and (3) available to payers in large health-system databases.Methods:Longitudinal clinical data of RA patients on bDMARDs from the first interim analysis of the phase-3, multicentre, randomised, open, prospective, controlled, parallel-group RETRO study (EudraCT number 2009-015740-42) was used [2] to build a predictive model for estimating the flare probability within 3 months from the current patient visit. A flare was defined as a DAS-28 ESR score over 2.6. Four different models (log. regression, random forest, k-NN and naïve Bayes) were trained which output the flare probability at each patient visit. These probabilities were used as an input for a stacking logistic regression meta-classifier [3]. The final model performance expressed as the AUROC was assessed using nested cross-validation [4]. We applied this method to three variable subsets (physician, patient, payer, Table 1).Table 1.List of variables used in three subsets:Variable / RolePhysicianPatientPayerGender (m/f)xxxDisease duration (years)xxxMethotrexate co-use (yes/no)xxxOther DMARDs co-use (yes/no)xxxDrug ATC codexxxIV-administration (yes/no)xxxDose percentagexxxAgexxxBody mass indexxxxDose percentage changexxxSwollen joint countxTender joint countxVAS_GH (pat. global disease activity)xxHAQ (health assessment questionnaire)xxSmoking status (yes/no/ex)xxAlcohol consumption (yes/no)xxPrevious flares (yes/no)xResults:Data from 135 follow-ups of 41 patients were used. The measured AUROC of the best performing model using all RETRO variables was 0.802 (95%CI 0.717 – 0.887) [1]. When a subset based on demographic and clinical variables is used that is available to a physician immediately during a patient visit the AUROC drops about 5 percent points. When only variables theoretically available to patients at home are used, the performance drops about 10 percent points comparing to the original model. Similar observation holds for the variable subset typically available to payers (Figure 1).Conclusion:This study shows that predictive models for flares have the potential to support physicians in making decisions immediately during the patient visit, even though laboratory values and respective activity scores are not yet available. In the future, machine learning applications may allow fast and reliable decisions on flare prediction in RA patients. These data can guide decisions about DMARD tapering at in real time during the physician-patient contact and allow to reduce costs not only by selective treatment tapering but also by sparing additional laboratory examinations.References:[1] Vodencarevic A. et al. Arthritis Rheumatol. 2019; 71[2] Haschka J et al. Ann Rheum Dis 2016; 75:45-51.[3] Tang J et al. CRC Press 2015; 498-500[4] Cawley GC et al. J Mach Learn Res 2010; 11:2079-2107Disclosure of Interests:Asmir Vodencarevic Shareholder of: Siemens Healthcare GmbH. Siemens Healthcare GmbH is a medical technology company (NOT a pharmaceutical company)., Employee of: Siemens Healthcare GmbH. Siemens Healthcare GmbH is a medical technology company (NOT a pharmaceutical company)., Koray Tascilar: None declared, Fabian Hartmann: None declared, Michaela Reiser: None declared, Sara Bayat Speakers bureau: Novartis, Johannes Knitza Grant/research support from: Research Grant: Novartis, Larissa Valor: None declared, Melanie Hagen: None declared, Axel Hueber Grant/research support from: Novartis, Lilly, Pfizer, Consultant of: Abbvie, BMS, Celgene, Gilead, GSK, Lilly, Novartis, Speakers bureau: GSK, Lilly, Novartis, Arnd Kleyer Consultant of: Lilly, Gilead, Novartis,Abbvie, Speakers bureau: Novartis, Lilly, Marcus Zimmermann-Rittereiser Shareholder of: Siemens Healthcare GmbH. Siemens Healthcare GmbH is a medical technology company (NOT a pharmaceutical company)., Employee of: Siemens Healthcare GmbH. Siemens Healthcare GmbH is a medical technology company (NOT a pharmaceutical company)., Georg Schett Speakers bureau: AbbVie, BMS, Celgene, Janssen, Eli Lilly, Novartis, Roche and UCB, David Simon Grant/research support from: Else Kröner-Memorial Scholarship, Novartis, Consultant of: Novartis, Lilly

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Szczepura, Ala, Mark Collinson, Louise Moody, Yanguo Jing, Gill Ward, Kim Bul, Sylvester Arnab et al. „PP89 Living Lab Concept: An Innovation Hub For Elderly Residential Care“. International Journal of Technology Assessment in Health Care 34, S1 (2018): 99–100. http://dx.doi.org/10.1017/s0266462318002362.

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Introduction:Many countries face the challenge of an aging population. Development of suitable technologies to support frail elderly living in care homes, sheltered housing or at home remains a concern. Technology evaluation in real-life conditions is often lacking, and randomized controlled trials of ‘pre-designed’ technologies are expensive and fail to deliver. A novel alternative would be ‘living labs’-real-life test and experimentation environments where users and producers co-create innovations and large-scale data can be collected.Methods:The goal of the living labs and Data Driven Research and Innovation (DDRI) Programme is to use data driven analytics and insights to support technology development for independent living, healthy aging and more cost-effective care. This involves a cluster of long-term residential care facilities providing 24/7 living lab settings, linked to an embedded innovation hub. DDRI also encompasses private vehicles (e.g. sensors in cars) to enable elderly to drive safely for longer. Collaborations have been established with Universities in England, Scotland and Ireland and with international industry partners.Results:Several projects are underway: (i) develop machine learning algorithm from non-intrusive sensor data to build a well-being representation for individual residents/citizens; (ii) evaluate innovative interventions for good sleep environment and nutritional support; and (iii) establish ethics framework to ensure that needs of residents, families and staff are embedded in design, communication, and evaluation of future DDRI projects. In addition, fifteen interdisciplinary doctoral fellowships are in place, six universities are working closely with individual living lab settings, and an innovation hub has been established in one care home for horizon-scanning and strategic technology selection and implementation.Conclusions:Over the next five years, a national network of 20 residential living labs with over 1,500 participants will be established. Generation of new user-led technologies, blueprints for capture of individual data at significant scale, and ethical and organizational guidelines will be developed. Intelligent mobility via data capture/feedback in vehicles will be established.

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Hsu, Sharon Nienyun, Erika Wong En Hui, Mengzhen Liu, Di Wu, Thomas A. Hughes und James Smith. „Revealing nuclear receptor hub modules from Basal-like breast cancer expression networks“. PLOS ONE 16, Nr. 6 (23.06.2021): e0252901. http://dx.doi.org/10.1371/journal.pone.0252901.

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Nuclear receptors are a class of transcriptional factors. Together with their co-regulators, they regulate development, homeostasis, and metabolism in a ligand-dependent manner. Their ability to respond to environmental stimuli rapidly makes them versatile cellular components. Their coordinated activities regulate essential pathways in normal physiology and in disease. Due to their complexity, the challenge remains in understanding their direct associations in cancer development. Basal-like breast cancer is an aggressive form of breast cancer that often lacks ER, PR and Her2. The absence of these receptors limits the treatment for patients to the non-selective cytotoxic and cytostatic drugs. To identify potential drug targets it is essential to identify the most important nuclear receptor association network motifs in Basal-like subtype progression. This research aimed to reveal the transcriptional network patterns, in the hope to capture the underlying molecular state driving Basal-like oncogenesis. In this work, we illustrate a multidisciplinary approach of integrating an unsupervised machine learning clustering method with network modelling to reveal unique transcriptional patterns (network motifs) underlying Basal-like breast cancer. The unsupervised clustering method provides a natural stratification of breast cancer patients, revealing the underlying heterogeneity in Basal-like. Identification of gene correlation networks (GCNs) from Basal-like patients in both the TCGA and METABRIC databases revealed three critical transcriptional regulatory constellations that are enriched in Basal-like. These represent critical NR components implicated in Basal-like breast cancer transcription. This approach is easily adaptable and applicable to reveal critical signalling relationships in other diseases.

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Park, Jihyeon, und Jaeyoung Lee. „Performance Prediction of Alkaline Fuel Cell Via Gradient Boosting Algorithm“. ECS Meeting Abstracts MA2022-01, Nr. 35 (07.07.2022): 1508. http://dx.doi.org/10.1149/ma2022-01351508mtgabs.

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With the DFT theory at the forefront, non-PGM catalysts have begun to develop, and in much literature, results have shown that the performance of non-PGM catalysts is comparable to that of PGM catalysts. Jing et. al. synthesized Fe-Co dual sites on nitrogen-doped carbon for oxygen reduction reaction (ORR). (FeCo)/N-C had almost equal half-wave potential to commercial Pt/C.[1] Hanguang et. al. achieved high ORR-activated Fe-N-C catalysts by tuning the doped Fe content and active sites.[2] However, if both (FeCo)/N-C and Fe-N-C were applied to PEMFC, they were not comparable to PGM catalysts unlike in the results of the half-cell test. This discrepancy means that numerous factors should be considered and optimized in a practical system like a fuel cell. Besides, it is indicated that even if the DFT theory and deep-learning combine to suggest catalysts with high performance, it may not produce as much performance in the actual fuel cell system as expected. In this respect, the combination of fuel cell systems (not catalysts) and artificial intelligence (AI) seems more reasonable. Without human judgment or intervention, machine learning sets priorities between each index by learning from many databases. Herein, we newly developed an optimization model for alkaline liquid fuel cell (Hydrazine fuel cell) using gradient boosting algorithm (XGBoost) which is one of machine learning algorithms. We operated fuel cells in various conditions by changing humidity of cathode, back pressure of cathode, cell temperature, stoichiometric factor (air/fuel), and concentration of the fuel. And then, we categorized and classified with the specific algorithm. Finally, we re-organized and set as a function of weight which effects on fuel cell operation. We hope that these approach will help improve fuel cell performance by controlling a number of factors without human intervention. [1] J. Wang, Z. Huang, W. Liu, C. Chang, H. Tang, Z. Li, W. Chen, C. Jia, T. Yao, S. Wei, Y. Wu, Y. Li, J. Am. Chem. Soc. 139 (2017) 17281–17284. [2] H. Zhang, H.T. Chung, D.A. Cullen, S. Wagner, U.I. Kramm, K.L. More, P. Zelenay, G. Wu, Energy Environ. Sci. 12 (2019) 2548–2558.

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Jagannath Jijaba Kadam, Et al. „Optimal Prediction and Disease Severity Classification of Proteomic Survival in Pre and Post-Covid-19 Using Hybrid Machine Learning Approach“. International Journal on Recent and Innovation Trends in Computing and Communication 11, Nr. 9 (05.11.2023): 2204–14. http://dx.doi.org/10.17762/ijritcc.v11i9.9225.

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Uncertainty surrounds the underlying mechanisms of the severe COVID-19 disease of 2019. The capability to detect COVID-19 through artificial intelligence techniques, particularly deep learning, will help to do so in the early stages, which will increase the likelihood that patients around the world will recover rapidly. The load on the healthcare system globally will be relieved as a result. Several thousand plasmas and serum proteins from COVID-19 patients and symptomatic controls are longitudinally analysed in this study to identify non-immune and immune proteins associated with COVID-19. The development of predictive models thus involves taking into account the topological variations across networks from different scenarios (survivors vs. non-survivors). As a result, the study's test subjects, who weren't included in the machine learning (ML) training, had high prediction accuracy. This study successfully predicted the existence of critically ill (CI) patients both before and after COVID-19 by using an MLM built on a synonymic network that incorporates measurements of several proteins. A rise in some acute phase and inflammatory proteins (IP) with time (e.g. ITIH3, SAA1; CRP, SAA2, LBP, SERPINA1, and LRG1) is related to the danger of death after COVID-19, while an upsurge of kallikrein (KLKB1), kallistatin (SERPINA4), thrombin (F2), Apo lipoprotein C3 (APOC3), GPLD1, and the protease inhibitor A2M, is associated with survival. The same clinical symptoms, such as dry cough, fever, squatness of breath, and others, are linked to both severe and critical patients. The lesion outlines are then retrieved from the COVID-19-contaminated regions after the entropy texture features have been extracted using a Gray-level co-occurrence Matrix (GLCM) to confirm the infected regions (IR). Further, the study implemented a variety of features using CT images with a CNN-based Inception V3 model for selection algorithms to filter significant features. Finally, construct a model of transfer learning (TL) using the VGGNet16 model which could capture and further classify the disease severity. Based on Matlab software, the suggested work is assessed. With a compassion of 96.7% and specificity of 98.2%, the results demonstrate that VGGNet16 is the most suitable TL model to identify COVID-19, nonetheless, it also exceeds the most advanced methods at the moment. The clotting system and accompaniment cataract are home to the bulk of proteins in the forecast model with high significance. This work shows that plasma proteomics (PP) can result in prognostic predictions that vastly outperform the present prognostic markers in critical care, respectively.

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De Dieu, Mushimiyimana J., und Dushimimana J. De Dieu. „The relationship between smart classroom and learners’ academic performance in public boarding schools of Gicumbi District, Rwanda“. Inkanyiso 13, Nr. 2 (01.12.2021): 14. http://dx.doi.org/10.4102/ink.v13i2.5.

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The purpose of this study was to investigate the relationship between smart classrooms and learner’s academic performance in public boarding schools in Gicumbi District, Rwanda. The first objective was to assess the relationship between the availability of instructional facilities and learner’s academic performance in Rwandan public boarding schools. The second objective was to explore the relationship between IT-trained staff and learner’s academic performance in Rwandan public boarding schools. The study targeted 12 public boarding schools from Gicumbi District, where 4 public boarding schools were selected. The study population comprised 1334 respondents, while the final sample size was 308, people who had been selected using Yamane sample size determination. Reliability was ensured through a pilot study and by using Cronbach’s Alpha to measure co-efficient of internal consistency, which yielded good results for approving the study, of 85%. Data were analyzed using SPSS software version 21. Findings of the study revealed that there is a significant relationship between smart classrooms and learner’s academic performance in Rwandan public boarding schools. All the involved variables had a significant relationship with dependent variables which were the availability of instructional facilities (r=.923 and p-value=0.000), IT-trained staff (r=.949 and p-value=0.000). Researchers recommended that teachers need regular Continuous Professional Development to help them update knowledge on the use of smart classrooms. Parents should be mobilised on how to create a technological atmosphere at home for their children because any academic achievement of students depends on how parents have helped them at home. It would be better if parents were able to afford electronic devices to expose their children to technology. Government should make frequent schools supervision on the use of smart classrooms and make sure that sector education officers and head teachers do not keep those machines in hte store instead of letting learners use them. The implication is that if smart classrooms are increased and monitored in Rwanda, academic achievement will improve in boarding schools.

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Fricker, Simon P., Christopher J. Nicholson, Samuel J. Roth, Arudhir Singh, Caitlin Brown, Jon Hu, Petronela Buiga et al. „Abstract PO-037: Machine learning-enabled transomics identifies three therapeutic targets for MYC-driven diffuse large B cell lymphoma“. Blood Cancer Discovery 5, Nr. 3_Supplement (19.06.2024): PO—037—PO—037. http://dx.doi.org/10.1158/2643-3249.lymphoma24-po-037.

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Abstract MYC activation and dysregulation is a powerful oncogenic driver in multiple cancers, including diffuse large B cell lymphoma (DLBCL). There is a known correlation between MYC expression and poor prognosis. While the 5-year overall survival for DLBCL patients on first-line therapy, R-CHOP, is approximately 75%, the 5-year overall survival drops to a staggering 30% for patients co-expressing MYC and BCL2 (double expressor lymphoma). However, it is challenging to target MYC directly. Therefore, we identified a novel approach to circumvent targeting MYC directly by leveraging Pepper’s proprietary machine learning (ML) transomic analysis platform, COMPASS, to identify novel targets associated with high MYC activity that, when inhibited, are predicted to recapitulate the effect of MYC inactivation. Specifically, COMPASS unlocks functional drivers of disease to identify novel drug targets. To study the role of MYC in lymphoma biology, we utilize a MYC-conditional T cell acute lymphoblastic leukemia/lymphoma (T-ALL) cell line (4188) with tunable MYC expression. We collect genomic, transcriptomic, proteomic, and phosphoproteomic data from samples with MYC transgene expression “on” and “off” and compare these biological cell states via COMPASS to identify novel targets that reproduce MYC inactivation. This provides new hope for patients suffering from MYC driven DLBCL. The MYC-conditional cell line allows the regulation of MYC expression via the tetracycline regulatory (Tet-Off) system. Four omic datasets were collected from each sample: genomics (next-generation sequencing, NGS), transcriptomics (NGS), proteomics (mass spectrometry), and phosphoproteomics (mass spectrometry). We employed the COMPASS target prioritization algorithm to identify and rank novel targets that mimic “turning MYC off”. Targets were then filtered to select those with an available pharmacological tool compound (PTC). The PTCs were used to evaluate the targets in the SU-DHL-06 xenograft model of DLBCL. The PTCs inhibited tumor growth from 8-91%. A total of 20 targets were tested of which 13/20 (65%) were validated as evidenced by significant inhibition of tumor growth (p<0.05, two-way ANOVA). All targets were kinases or related to kinase activity and pathways. Three of the PTCs resulted in maximum tumor growth inhibition of 86%, 89% and 91% at end of treatment, resulting in stasis of tumor growth and increased survival compared with control vehicle-treated mice. We have previously shown how the COMPASS transomics analysis approach can identify novel drug targets for drug-resistant EGFRm NSCLC and for MYC-driven hepatocellular carcinoma (HCC). The success rate of target validation across several indications including EGFRm NSCLC, HCC and lymphoma is 73%. The data presented here on MYC-driven DLBCL further validates this approach. Further validation studies will investigate novel targets using gene silencing, as PTCs were unavailable for many of the novel high-ranked targets identified in this study. Citation Format: Simon P Fricker, Christopher J Nicholson, Samuel J Roth, Arudhir Singh, Caitlin Brown, Jon Hu, Petronela Buiga, Vishnu P Kanakaveti, Anja Deutzmann, Dean Felsher, Samantha D Strasser. Machine learning-enabled transomics identifies three therapeutic targets for MYC-driven diffuse large B cell lymphoma [abstract]. In: Proceedings of the Fourth AACR International Meeting on Advances in Malignant Lymphoma: Maximizing the Basic-Translational Interface for Clinical Application; 2024 Jun 19-22; Philadelphia, PA. Philadelphia (PA): AACR; Blood Cancer Discov 2024;5(3_Suppl):Abstract nr PO-037.

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Schwarz, Franziska, Klaus Schwarz, Daniel Fuchs, Reiner Creutzburg und David Akopian. „Firmware Vulnerability Analysis of Widely Used Low-Budget TP-Link Routers“. Electronic Imaging 2021, Nr. 3 (18.06.2021): 135–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.3.mobmu-135.

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TP-Link Technologies Co, Ltd. is a Chinese manufacturer of networking products and has a 42% share of the consumer WLAN market, making it the market leader. The company sells about 150 million devices per year. Many people worldwide use the Internet every day and are connected to the Internet with their computers. In the world of smart homes, even coffee machines, refrigerators, smart sockets, and light bulbs have found their way to the Internet, not to mention the many smartphones, which are, of course, also connected to the Internet. Since many different dangers come from a heater or printer and the many other smart devices directly connected to the Internet, there is a safe haven: the local area network. To connect to the Internet, one needs a modem, which is built into a router in many cases. Routers route network packets back and forth between several computer networks. They are used to connect to the Internet, and they are the bridge between the home network and the Internet in almost every household connected to the Internet. Because of their nature as a bridge between local and global networks, they are also the largest attack vector. [19] This paper examines how up-to-date the firmware of standard home network routers is and how secure the firmware is. In order to obtain a representative result, the examined routers were selected according to fixed rules. Each router had to be a product of the manufacturer TP-Link, the routers had to be in the low-budged range (less than 20 Euro) and be available from Amazon. Also, two different types of investigations were identified for the selected devices. Firstly, the devices were examined in the form of physically existing hardware, and secondly, an attempt was made to access the firmware via the manufacturer’s website. It was found that even the fixing of current vulnerabilities and recently released update files are no guarantee that older vulnerabilities have been fixed. Secrets such as private keys and certificates are hard-coded in the firmware and can be extracted from update files. Moreover, devices are deliberately built to make it impossible to install the latest alternative firmware.

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Tursucular, Omer Firat. „A review on Air-Jet Textured Yarn Spinning Technology (ATY) in the global textile industry“. Journal of Textile Engineering & Fashion Technology 10, Nr. 4 (09.07.2024): 151–57. http://dx.doi.org/10.15406/jteft.2024.10.00382.

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In this theoretical review study included Air-Jet Textured Yarn spinning technology (ATY); its importance, formation mechanism principle, yarns used, and general properties were explained in detail, supported by images and tables from various sources. Moreover, the specific ATY yarn process parameters required for ATY yarn production and the quantitative values of these process parameters were presented. Finally, the effects of ATY yarn types, and various ATY yarn process parameters on the thermal comfort, physical, and mechanical properties of textile-based woven, and knitted fabrics were explained. According to the results included ATY yarn production machines produced by DuPont and Heberlain Companies have generally used for the production of ATY yarns nowadays. Moreover, multi-jet systems (4 jets) called the Taslan have widely used because they affect the air pressure values, and air-flow regime more homogeneously in various yarn formation axes. Effective technical parameters for ATY yarn production are jet (nozzle) type, jet (nozzle) angle (°), overfeed ratio, amount of compressed air-flow (volumetric air-flow ratio), number of air-jets (nozzles), air-jet inner diameter (mm), production speed (m/min), heater and cooling plate temperatures (°C), times, lengths (mm), inner diameters, pre-tension values, types, and cross-sections of yarns and filaments, wetting of the yarn and the elasticity modulus of the deflection ball of the yarn (N/mm2). Additionally, FDY structure, yarn count (dtex)/filament count from 80/24 to 1666/1000, overfeed ratio value from 5.5 to 36, air pressure value from 7 bar to 10 bar, production speeds from 300 m/min to 500 m/min, a draft ratio value of between 1.75 and 2.19, and a temperature value of 180 °C to 200 °C are generally used in the production of ATY yarns. Texturing property (bulky volume), instability, and mass loss increase, but tensile strength decreases as air pressure increases. These effects are more evident in fine yarn counts (dtex). Tensile strength increases, but instability, and mass loss decrease as the texturing speed increases. Water consumption has no effect on the physical, mechanical, and thermal comfort properties of both woven, and knitted fabrics with ATY yarn structures. POY and FDY structured PET, PA 6, PA 6.6, PP, PI, CV, CO, CMD, PPD-T, and EA yarns are used in the production of ATY yarns. ATY yarns are widely used in home textiles, clothing, airbags, carpets, and upholstery fabrics. The multi-lobed section PET ratio should be high for high bursting strength, tensile strength, air permeability, maximum breaking force, texturing property (bulky volume) and linear density of the yarn values, high shear strength, maximum percent elongation at break, thermal conductivity, pilling resistance. The ratio of CMD, CV, PA 6, or PA 6.6 should be high for water vapor permeability values. The CO ratio should be high for high thermal resistance. The PET ratio should be high for high abrasion resistance values. Shear strength, maximum percent elongation at break, elastic recovery behavior, and abrasion resistance increase as the EA ratio increases. ATY yarns have lower tensile strength, maximum breaking force, maximum percent breaking elongation, breaking work, and abrasion resistance values compared to ring, and OE rotor yarns (except DTY), respectively. The issue of recycling is extremely important for the sustainability of the global textile industry in the future. For this important issue, textile waste must be classified, collected, and evaluated. Moreover, optimization of various experimental production process parameters should be ensured in order to preserve the mechanical properties of blended yarns, especially CO/PET, and CO/PA yarn structures, by reducing chemical, water, energy, and labor costs.

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Heikkinen, Liine, Mikko Äijälä, Kaspar R. Daellenbach, Gang Chen, Olga Garmash, Diego Aliaga, Frans Graeffe et al. „Eight years of sub-micrometre organic aerosol composition data from the boreal forest characterized using a machine-learning approach“. Atmospheric Chemistry and Physics 21, Nr. 13 (06.07.2021): 10081–109. http://dx.doi.org/10.5194/acp-21-10081-2021.

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Abstract. The Station for Measuring Ecosystem–Atmosphere Relations (SMEAR) II, located within the boreal forest of Finland, is a unique station in the world due to the wide range of long-term measurements tracking the Earth–atmosphere interface. In this study, we characterize the composition of organic aerosol (OA) at SMEAR II by quantifying its driving constituents. We utilize a multi-year data set of OA mass spectra measured in situ with an Aerosol Chemical Speciation Monitor (ACSM) at the station. To our knowledge, this mass spectral time series is the longest of its kind published to date. Similarly to other previously reported efforts in OA source apportionment from multi-seasonal or multi-annual data sets, we approached the OA characterization challenge through positive matrix factorization (PMF) using a rolling window approach. However, the existing methods for extracting minor OA components were found to be insufficient for our rather remote site. To overcome this issue, we tested a new statistical analysis framework. This included unsupervised feature extraction and classification stages to explore a large number of unconstrained PMF runs conducted on the measured OA mass spectra. Anchored by these results, we finally constructed a relaxed chemical mass balance (CMB) run that resolved different OA components from our observations. The presented combination of statistical tools provided a data-driven analysis methodology, which in our case achieved robust solutions with minimal subjectivity. Following the extensive statistical analyses, we were able to divide the 2012–2019 SMEAR II OA data (mass concentration interquartile range (IQR): 0.7, 1.3, and 2.6 µg m−3) into three sub-categories – low-volatility oxygenated OA (LV-OOA), semi-volatile oxygenated OA (SV-OOA), and primary OA (POA) – proving that the tested methodology was able to provide results consistent with literature. LV-OOA was the most dominant OA type (organic mass fraction IQR: 49 %, 62 %, and 73 %). The seasonal cycle of LV-OOA was bimodal, with peaks both in summer and in February. We associated the wintertime LV-OOA with anthropogenic sources and assumed biogenic influence in LV-OOA formation in summer. Through a brief trajectory analysis, we estimated summertime natural LV-OOA formation of tens of ng m−3 h−1 over the boreal forest. SV-OOA was the second highest contributor to OA mass (organic mass fraction IQR: 19 %, 31 %, and 43 %). Due to SV-OOA's clear peak in summer, we estimate biogenic processes as the main drivers in its formation. Unlike for LV-OOA, the highest SV-OOA concentrations were detected in stable summertime nocturnal surface layers. Two nearby sawmills also played a significant role in SV-OOA production as also exemplified by previous studies at SMEAR II. POA, taken as a mix of two different OA types reported previously, hydrocarbon-like OA (HOA) and biomass burning OA (BBOA), made up a minimal OA mass fraction (IQR: 2 %, 6 %, and 13 %). Notably, the quantification of POA at SMEAR II using ACSM data was not possible following existing rolling PMF methodologies. Both POA organic mass fraction and mass concentration peaked in winter. Its appearance at SMEAR II was linked to strong southerly winds. Similar wind direction and speed dependence was not observed among other OA types. The high wind speeds probably enabled the POA transport to SMEAR II from faraway sources in a relatively fresh state. In the event of slower wind speeds, POA likely evaporated and/or aged into oxidized organic aerosol before detection. The POA organic mass fraction was significantly lower than reported by aerosol mass spectrometer (AMS) measurements 2 to 4 years prior to the ACSM measurements. While the co-located long-term measurements of black carbon supported the hypothesis of higher POA loadings prior to year 2012, it is also possible that short-term (POA) pollution plumes were averaged out due to the slow time resolution of the ACSM combined with the further 3 h data averaging needed to ensure good signal-to-noise ratios (SNRs). Despite the length of the ACSM data set, we did not focus on quantifying long-term trends of POA (nor other components) due to the high sensitivity of OA composition to meteorological anomalies, the occurrence of which is likely not normally distributed over the 8-year measurement period. Due to the unique and realistic seasonal cycles and meteorology dependences of the independent OA subtypes complemented by the reasonably low degree of unexplained OA variability, we believe that the presented data analysis approach performs well. Therefore, we hope that these results encourage also other researchers possessing several-year-long time series of similar data to tackle the data analysis via similar semi- or unsupervised machine-learning approaches. This way the presented method could be further optimized and its usability explored and evaluated also in other environments.

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RATOV, B. T., B. V. FEDOROV, A. E. KUTTYBAYEV, S. E. KOIBAKOVA und A. R. BORASH. „SCIENTIFIC FOUNDATIONS OF THE CREATION OF DIAMOND DRILLING TOOLS OF THE RING TYPE“. Neft i Gaz 130, Nr. 4 (15.08.2022): 58–73. http://dx.doi.org/10.37878/2708-0080/2022-4.04.

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To solve the mentioned problem of accelerated commissioning of minerals occurring in hard rocks, studies have been carried out to formulate the following recommendations for the creation of high-performance diamond bits: - the crown matrix should contain several (five or more) impregnated diamond-bearing layers in height, separated by diamond-free layers of significantly lower hardness (for example, VK-20 hard alloy); - each diamond impregnated layer of the matrix must have a "comb" profile, representing annular wedge-shaped protrusions and depressions; - the impregnated diamond layers of the matrix during drilling should be equally loaded along the radius of the bit, which makes it possible to increase the wear resistance of the tool and reduce the number of rough diamonds for the manufacture of the latter; - to maintain the diameters of the well and the drilled core, the inner and outer side surfaces of the matrix must be equipped with wear-resistant diamond inserts (for example, from tvesala); - to produce a high-quality wear-resistant matrix, small amounts of various components should be added to the composition of the binder of the 94WC + Co + Cu type diamond grains. Recommendations 1-4 are embodied in the design of diamond impregnated crowns, for which the Republic of Kazakhstan has received patents. Crowns have been introduced into production with a significant effect. A diamond crown has been developed and patented, the impregnated layers placed in a matrix on a three-start helical surface with a slight pitch of 0.8 - 1.2 mm. It is expected that with this design, the pre-fracture zone will be involved in the bottom hole destruction process, which lies under the intrusion zone and represents a hard rock broken and weakened by cracks to a depth ten times greater than the intrusion depth of diamond grains. An experimental batch of multilayer crowns with an equally loaded comb profile and placement of impregnated layers on a three-start helical surface was made using software and CNC (numerical control) machines.

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