Journal articles on the topic 'Process control Dynamics Data processing'
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1
Park, Suk Yung, and Arthur D. Kuo. "An Optimal Estimator Model of Multi-Sensory Processing in Human Postural Control." Key Engineering Materials 277-279 (January 2005): 148–54. http://dx.doi.org/10.4028/www.scientific.net/kem.277-279.148.
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We hypothesized that multi-sensory processing at the central nervous system (CNS) in human postural control can be described using an optimal estimator model. The estimates on body dynamics from multi-sensory signals contain sensory noise, transmission delays, and process disturbances. The state estimates approximate actual body movement. Erroneous estimates degrade the performance of feedback control and could cause a loss of balance if distorted severely. To test the hypothesis, we examined the frequency response of a visually-induced postural sway with stimulus frequency ranging from 0.075 to 1Hz and established an optimal estimator model. Two healthy young (33yrs ± 1) subjects stood on a force platform located 1.25m behind a projection screen with their arms crossed over their chests. They were asked to maintain an upright posture against the sinusoidal visual field stimuli. Each sinusoidal visual stimulus was generated by a projector for 200secs in pitch direction with a maximum pitch angle of 20o. Kinematics data was recorded to calculate the frequency response function of the center of mass (COM). There were three components in the modeling procedure: a biomechanical model of body and sensor dynamics, a linear feedback control model to stabilize the biomechanical model, and a state estimator to estimate body dynamic states based on multi-sensory outputs. We modeled the sensor dynamics of the semicircular canal, otolth, vision, and muscle spindles at the ankle and hip joint. We used the Kalman filter and linear quadratic regulator to determine feedback gains. Results showed that the frequency response function of a visually-induced postural sway decreased as stimulus frequency increased, and this low-pass filtering characteristic with an approximate cutoff frequency of 0.2Hz was also simulated by the postural feedback control model with optimal estimator. Low-pass filtering characteristics of the frequency response are mainly due to body and sensor dynamics, which show reduced responses for high frequency stimulus. The Kalman filter represents that the CNS utilizes redundant sensory information in a way that minimizes discrepancies between actual body dynamics and estimated body dynamics based on sensory output and an internal model. The results suggest that the CNS may make use of an internal representation of body dynamics, and can integrate sensory information in an optimal way to best estimate human postural responses.
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Kotenko, Igor, and Igor Parashchuk. "Multi-criteria security assessment of control and diagnostic data on the technological processes." MATEC Web of Conferences 298 (2019): 00071. http://dx.doi.org/10.1051/matecconf/201929800071.
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A mathematical model of the dynamics of changes in the state of security indicators of control and diagnostic data on the technological process is proposed. It is constructed using Markov chains and takes into account the probabilistic-temporal mechanism for changing the state of data protection indicators of this class. Based on this model, a methodological approach has been developed for multi-criteria assessment of the security of control and diagnostic data on the technological process. The approach is based on the analysis of current deviations of the values of data protection indicators from the requirements for them, takes into account and eliminates the uncertainty of the initial diagnostic information. The proposed methodological approach also allows one to take into account transients that affect security when introducing control over the structure, parameters and modes of collection and processing of control and diagnostic data about the technological process in various conditions.
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Fu, Gang, Ming Xin Kou, and Ren Long Li. "Design and Implementation of Driving Mechanism on Software Aerospace Measurement and Control System." Advanced Materials Research 989-994 (July 2014): 3084–87. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.3084.
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According to the signal processing unit in aerospace measurement and control system between the flow of water features, this paper proposes a software suitable for aerospace measurement and control system of driving mechanism. This paper first introduces the basic structure of aerospace measurement and control system software, having studied the static and dynamic data stream driving mechanism on the basis of detailed discusses the design and implementation process of this kind of driving mechanism of data stream. It adopts the method of message control, according to the dynamic data flow driven mechanism, realize the process of the signal processing unit and each signal processing unit between the data flow between the internal thread. Compared the same sort of dynamic data stream driving mechanism, the drive mechanism possesses the advantages of flexibility and easy to implement.
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Rahmanov, Mikhail, Andrey Shishkin, Vladimir Komkov, and Irina Alpackaya. "Simulation of pedestrian dynamics based withemantic trajectory segmentation." E3S Web of Conferences 363 (2022): 04005. http://dx.doi.org/10.1051/e3sconf/202236304005.
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The article analyzes the existing methods of information processing necessary for the functioning of the system of intelligent control over unregulated pedestrian crossings based on aggregation and data processing by means of IOT. The state space model of the switching Kalman filter is considered, the development of mathematical software for the analysis and processing of information based on the results of intelligent control over unregulated pedestrian crossings, in particular with semantic segmentation of trajectories using agent-based models, is carried out. An MDA (Markov Decision Process) state space model is presented, a Hidden Markov Model (HMM) which has discrete hidden variables. The developments for the development of the following subsystems are presented: activity detector subsystem. Receives video frames as input, supports the static object model (background model) and returns the hotspot mask for the current frame; subsystems for detecting and tracking objects (pedestrians and cars). Based on the video frame and hotspot mask, it detects and accompanies objects of a given class, returning their coordinates; trajectory analysis subsystem. Analyzing the history of movement of pedestrians and cars, returns the facts of traffic violations.
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Umetalieva, Ch T., N. Y. Temirbaeva, and B. N. Nurtaev. "THEORY OF BUILDING AUTOMATED CONTROL SYSTEMS." Herald of KSUCTA, №2, Part 1, 2022, no. 2-1-2022 (April 30, 2022): 295–99. http://dx.doi.org/10.35803/1694-5298.2022.2.295-299.
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The task of collecting, processing and disseminating (exchanging) information stood at all stages of human development. For a long time, the main tools for solving it were the human brain, hearing and language. Storing information in computer memory gives a fundamentally new quality of dynamics, that is, the ability to quickly recover and use it directly in problems solved on a computer. Modern printing equipment, equipped with modern computers, allows, if necessary, to quickly present any selected information on paper. In the process of development of the administrative data management system, the need arose for an automated facility management system (ACS).
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Whitehead, Peter S., Mathilde M. Ooi, Tobias Egner, and Marty G. Woldorff. "Neural Dynamics of Cognitive Control over Working Memory Capture of Attention." Journal of Cognitive Neuroscience 31, no. 7 (July 2019): 1079–90. http://dx.doi.org/10.1162/jocn_a_01409.
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The contents of working memory (WM) guide visual attention toward matching features, with visual search being faster when the target and a feature of an item held in WM spatially overlap (validly cued) than when they occur at different locations (invalidly cued). Recent behavioral studies have indicated that attentional capture by WM content can be modulated by cognitive control: When WM cues are reliably helpful to visual search (predictably valid), capture is enhanced, but when reliably detrimental (predictably invalid), capture is attenuated. The neural mechanisms underlying this effect are not well understood, however. Here, we leveraged the high temporal resolution of ERPs time-locked to the onset of the search display to determine how and at what processing stage cognitive control modulates the search process. We manipulated predictability by grouping trials into unpredictable (50% valid/invalid) and predictable (100% valid, 100% invalid) blocks. Behavioral results confirmed that predictability modulated WM-related capture. Comparison of ERPs to the search arrays showed that the N2pc, a posteriorly distributed signature of initial attentional orienting toward a lateralized target, was not impacted by target validity predictability. However, a longer latency, more anterior, lateralized effect—here, termed the “contralateral attention-related negativity”—was reduced under predictable conditions. This reduction interacted with validity, with substantially greater reduction for invalid than valid trials. These data suggest cognitive control over attentional capture by WM content does not affect the initial attentional-orienting process but can reduce the need to marshal later control mechanisms for processing relevant items in the visual world.
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Eghbali, Zahra, and Mina Zolfy Lighvan. "A Hierarchical Approach for Accelerating IoT Data Management Process Based on SDN Principles." MENDEL 25, no. 1 (June 24, 2019): 121–30. http://dx.doi.org/10.13164/mendel.2019.1.121.
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Internet of things is a new technology that connects billions of smart devices through the Internet. This important technology is heavily affecting different aspects of human life and plays an important role in variety of domains. The number of smart devices connecting to IoT and the amount of data gathered or produced by these devices are increasing. This large volume of data requires a lot of effort for processing and analysis. In order to organize, secure and balance the load in IoT, the novel and creative ideas for IoT design and management are required. Software Defined Networking is a new and promising paradigm and its main idea is to decouple the control and management operations from physical devices and setting them inside a logically centralized control layer. Due to its unique capabilities, SDN can be a good choice for managing dynamic and complicated networks such as IoT. In this paper, a distributed approach is proposed for accelerating data management and balancing the load between IoT devices. The proposed framework makes it possible to apply different kinds of management, security and load balancing strategies using a distributed control plane. Experimental results indicate that our scheme exhibits a reduction in the average turnaround time and the average waiting time and it will improve the processing performance. The proposed approach will also distribute tasks between devices, so that there will be no under-loaded device when a part of network is under the processing pressure.
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Yailymova, Hanna, Bohdan Yailymov, Andrii Shelestov, and Tetiana Krasilnikova. "INTELLECTUAL METHODS AND MODELS OF SATELLITE DATA PROCESSING IN LANDFILLS MONITORING PROBLEMS." International Scientific Technical Journal "Problems of Control and Informatics" 2, no. 2 (March 1, 2022): 128–40. http://dx.doi.org/10.34229/2786-6505-2022-2-9.
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The article is devoted to solving an important applied problem of landfill search based on machine learning methods using high-resolution satellite data. The problem of accumulation and storage of waste in legal and unauthorized landfills is relevant today. Millions of tons of household waste are generated in Ukraine every year. The largest areas for landfills are occupied in Donetsk, Dnipropetrovsk, Odesa, Zaporizhzhia regions. So, in the Donetsk region the areas under landfills occupy 330 hectares. Various technologies based on satellite data and artificial intelligence methods are used to monitor landfills. Currently, there are services that track the location of landfills, but do not provide information about the territory of the landfill and changes in its area over time. In the process of research, the important task of separating landfills from quarries and artificial objects by combining pixel-based and object-based classification was solved. The main purpose of the work was to develop intelligent information technology based on the neural network approach and build on its basis a geospatial product of landfills for the Donetsk region, namely classification maps of landfills. The proposed machine learning algorithm based on historical and modern satellite data allows tracking the area of the landfill and its changes over time. The developed information technology was tested on the territory of four territorial communities in Donetsk region, namely Olhyn, Myrnohrad, Kurakhiv and Pokrovsky communities. As a result of the research, an information panel was also developed, which provides operational data and allows to assess the dynamics of changes in landfills in the region in time and space. The developed technology is of practical importance for the development of waste management and management programs in local communities.
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Joostberens, Jarosław, Aurelia Rybak, and Aleksandra Rybak. "Identification of the Dynamic Properties of the Coal Flotation Process as a Control Object with the Use of the Kalman Filter." Energies 15, no. 21 (October 25, 2022): 7926. http://dx.doi.org/10.3390/en15217926.
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For various sorts of hard coal, enrichment by flotation is used for feed consisting of grains smaller than 0.5 mm. Regarding process automation, coal flotation is a multidimensional, dynamic nonlinear object of control, for which the main control signal is the flow rate of the flotation agent. Typically, in Polish coal-processing facilities the monitoring and control systems of the flotation process can only measure the parameter of the waste quality (content of ash in flotation tailings). This naturally becomes an output signal, enabling an indirect assessment of the ongoing process. Therefore, knowledge of the dynamic properties of the flotation process, analysed as an object with one control input (the flow rate of the flotation agent) and with one output for measuring (content of ash in flotation tailings) may be material in designing automatic control systems for this operation. It is important to use an appropriate identification method when developing a model of the dynamics of the flotation process, especially if the model parameters are to be determined on an ongoing basis. This article discusses the research method and presents the results of applying the method of identifying the dynamic properties of the coal flotation process with the use of the Kalman filter. We carried out a comparative analysis of the results obtained by this method based on the Kalman algorithm and the method of least squares, taken as the reference method. The presented parameters of the dynamic models were calculated based on actual data obtained from industrial tests conducted at the coal-processing plant at one of the Polish mines. It was demonstrated that, for control purposes, the Kalman algorithm can be successfully applied in identification of the coal flotation process. This is due to the fact that it gives satisfactory results in relation to the adopted reference method despite the fact that it is a recursive algorithm.
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Zhao, Lin. "Numerical Control Lathe Cutting Force Signal On-Line Monitoring Design." Applied Mechanics and Materials 711 (December 2014): 329–32. http://dx.doi.org/10.4028/www.scientific.net/amm.711.329.
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The main research direction of Numerical control lathe cutting force signal on-line monitoring is to process real-time monitoring, using the sensor, charge amplifier, video acquisition card and computer to collect data and signal. Signal acquisition makes use of the piezoelectric sensor signals and send them to the computer in order to acquire the real-time data and display the dynamic signal so that monitor the process. Signal processing is the course that data will be collected for subsequent processing and analyzing. It includes display, filtering, correlation analysis, spectral analysis, etc. We can conclude the signal’s characteristics after the time domain and frequency domain analysis of signals.
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Yabanova, İsmail. "Digital Signal Processing–based Dynamic Mass Measurement System for Egg Weighing Process." Measurement and Control 50, no. 4 (May 2017): 97–102. http://dx.doi.org/10.1177/0020294017713768.
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In this study, an electronic, mechanical and software system, where the weight measurements of eggs can be performed dynamically, is developed. As the speed is an important factor in the production sector, it is of significant importance that the manufactured products be weighed in a rapid and correct manner. For this reason, systems where the products are dynamically weighed are developed. However, as the products are weighed while they are moving in dynamic weighing systems, undesired disturbing effects occur on the measurement signal. The product weights must be measured at required speeds by eliminating this disturbing effect. Dynamic weighing is performed using a load cell. A digital signal processing–based card has been developed to measure the signal received from the load cell and to send it to the computer. The eggs are weighed while they are moving as they roll over the load cell. A program has been developed using the LabVIEW program to receive, filter and analyze the data read and sent to the computer by digital signal processing. In addition, the configuration adjustments of the integrated analog-to-digital converter that reads data from the load cell can also be performed thanks to this program.
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Heo, Eunyoung, and Namhyun Yoo. "Numerical Control Machine Optimization Technologies through Analysis of Machining History Data Using Digital Twin." Applied Sciences 11, no. 7 (April 5, 2021): 3259. http://dx.doi.org/10.3390/app11073259.
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In numerical control (NC)-based machining, NC data-based tool paths affect both quality and productivity. NC data are generated according to cutting conditions. However, NC data causing excessive cutting load can accelerate tool wear and even result in tool damage. In the opposite case, increasing machining time can affect productivity. NC data can influence surface quality from the perspective of cutting dynamics according to machine tool–material–tool combination. There have been a lot of studies on tool-path optimization. However, it is impossible to perfectly predict cutting dynamics such as tool wear, material non-uniformity, chatter, and spindle deformation. In fact, such prediction-based tool-path optimization can cause errors. Therefore, this study attempts to synchronize spindle load and NC data and uniformize the machining load through the analysis of stored data using digital-twin technology, which stores and manages machining history. Uniformizing machining load can reduce rapid traverse in the event of no load, feed rate in an overload area, and shock on a tool when the tool and material are met by adding approach feed. Analyzing results of the attempts proposed in this paper, the chatter was completely removed in the machining with D100 and D16, although some chatter remained in the machining with D25 and D16R3 tools. In addition, the processing time could be reduced from a minimum of 7% to a maximum of 50% after optimization.
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Knyazev, A. S. "The use of the X-Plane flight simulator and SimInTech environment in the educational process during the practical lesson "Flight data processing"." Civil Aviation High Technologies 24, no. 6 (December 27, 2021): 42–53. http://dx.doi.org/10.26467/2079-0619-2021-24-6-42-53.
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During training sessions at an aviation university, it is advisable to demonstrate samples of aviation equipment, individual elements of systems and assemblies, or use specialized stands and posters. However, when conducting classes remotely, not all of these materials can be used, since it is not always possible to show them in dynamics and thus ensure the formation of a clear idea of students about the object being studied. The article considers an example of using a flight simulator in the educational process as a means of visualizing aviation equipment during a practical lesson "Flight data processing". Visual perception of the materials of objective control does not give a complete understanding of the dynamics of the aircraft flight, its attitude while executing pilotage and aerobatics elements, therefore, it is necessary to demonstrate the performance of flight elements with the simultaneous display of flight parameters in a graphical form. For this purpose, the X-Plane flight simulator is used, for interaction with which a project has been developed in the SimInTech environment that implements data exchange for flight control of an aircraft model and registration of parametric information for its further analysis. Schemes for simulating the operation of on-board recording devices are described. The ways of solving the tasks are described. The possibility of using the developed projects for remote training of aviation specialists, as well as the implementation of the results obtained in the educational process of aviation universities, is indicated.
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Baraniuk, Roman, and Welf-Guntram Drossel. "Simplification of the Model of Piezoelectric Actuator Control Based on Preliminary Measurements." Actuators 9, no. 3 (September 18, 2020): 90. http://dx.doi.org/10.3390/act9030090.
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This article describes a mathematical model simplification, designed to automate the iterative process of non-circular drilling with a precise shape. This model has been optimized for systems that already have experimental data for processing and analysis. Additionally, using optimization steps, the model can be used for systems with insufficient experimental data with a self-learning opportunity. The high-end model can be used for drilling systems represented as a “black box” without knowing of any parameters of the system. The simplification and assumptions algorithm is based on controlling the input signal for non-circular drilling in the cylinders of internal combustion engines using a drilling machine controlled by 8 piezoelectric actuators. The total dynamics of this system is unknown and consists of the dynamics of electrical converters, piezo-kinematics, and mechanics. Simplification is carried out starting from the methods of diacoptics for a complex system with different process-flow rates, and ending with one or the sum of linear models valid for a given system of assumptions.
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Kamiński, Marcin, and Krzysztof Szabat. "Adaptive Control Structure with Neural Data Processing Applied for Electrical Drive with Elastic Shaft." Energies 14, no. 12 (June 8, 2021): 3389. http://dx.doi.org/10.3390/en14123389.
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This paper presents issues related to the adaptive control of the drive system with an elastic clutch connecting the main motor and the load machine. Firstly, the problems and the main algorithms often implemented for the mentioned object are analyzed. Then, the control concept based on the RNN (recurrent neural network) for the drive system with the flexible coupling is thoroughly described. For this purpose, an adaptive model inspired by the Elman model is selected, which is related to internal feedback in the neural network. The indicated feature improves the processing of dynamic signals. During the design process, for the selection of constant coefficients of the controller, the PSO (particle swarm optimizer) is applied. Moreover, in order to obtain better dynamic properties and improve work in real conditions, one model based on the ADALINE (adaptive linear neuron) is introduced into the structure. Details of the algorithm used for the weights’ adaptation are presented (including stability analysis) to perform the shaft torque signal filtering. The effectiveness of the proposed approach is examined through simulation and experimental studies.
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Child, Sarah F., Leigh A. Stearns, Luc Girod, and Henry H. Brecher. "Structure-From-Motion Photogrammetry of Antarctic Historical Aerial Photographs in Conjunction with Ground Control Derived from Satellite Data." Remote Sensing 13, no. 1 (December 23, 2020): 21. http://dx.doi.org/10.3390/rs13010021.
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A longer temporal scale of Antarctic observations is vital to better understanding glacier dynamics and improving ice sheet model projections. One underutilized data source that expands the temporal scale is aerial photography, specifically imagery collected prior to 1990. However, processing Antarctic historical aerial imagery using modern photogrammetry software is difficult, as it requires precise information about the data collection process and extensive in situ ground control is required. Often, the necessary orientation metadata for older aerial imagery is lost and in situ data collection in regions like Antarctica is extremely difficult to obtain, limiting the use of traditional photogrammetric methods. Here, we test an alternative methodology to generate elevations from historical Antarctic aerial imagery. Instead of relying on pre-existing ground control, we use structure-from-motion photogrammetry techniques to process the imagery with manually derived ground control from high-resolution satellite imagery. This case study is based on vertical aerial image sets collected over Byrd Glacier, East Antarctica in December 1978 and January 1979. Our results are the oldest, highest resolution digital elevation models (DEMs) ever generated for an Antarctic glacier. We use these DEMs to estimate glacier dynamics and show that surface elevation of Byrd Glacier has been constant for the past ∼40 years.
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Leaver, Echo E., Kathy A. Low, Assunta DiVacri, Arcangelo Merla, Monica Fabiani, and Gabriele Gratton. "The Devil Is in the Detail: Brain Dynamics in Preparation for a Global–Local Task." Journal of Cognitive Neuroscience 27, no. 8 (August 2015): 1513–27. http://dx.doi.org/10.1162/jocn_a_00800.
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When analyzing visual scenes, it is sometimes important to determine the relevant “grain” size. Attention control mechanisms may help direct our processing to the intended grain size. Here we used the event-related optical signal, a method possessing high temporal and spatial resolution, to examine the involvement of brain structures within the dorsal attention network (DAN) and the visual processing network (VPN) in preparation for the appropriate level of analysis. Behavioral data indicate that the small features of a hierarchical stimulus (local condition) are more difficult to process than the large features (global condition). Consistent with this finding, cues predicting a local trial were associated with greater DAN activation. This activity was bilateral but more pronounced in the left hemisphere, where it showed a frontal-to-parietal progression over time. Furthermore, the amount of DAN activation, especially in the left hemisphere and in parietal regions, was predictive of subsequent performance. Although local cues elicited left-lateralized DAN activity, no preponderantly right activity was observed for global cues; however, the data indicated an interaction between level of analysis (local vs. global) and hemisphere in VPN. They further showed that local processing involves structures in the ventral VPN, whereas global processing involves structures in the dorsal VPN. These results indicate that in our study preparation for analyzing different size features is an asymmetric process, in which greater preparation is required to focus on small rather than large features, perhaps because of their lesser salience. This preparation involves the same DAN used for other attention control operations.
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Liu, Yuan Yuan, Chang Juan Jing, Da Li Liu, Qing Xi Hu, and Qing Wei Li. "Study on the Relation between Electrospinning Fiber Diameter Distribution and Taylor Cone Dynamics." Advanced Materials Research 311-313 (August 2011): 450–53. http://dx.doi.org/10.4028/www.scientific.net/amr.311-313.450.
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Electrospinning is an effective and versatile technology to fabricate ultrafine nanofiber,however further development is urgently limited due to the low uniformity distribution and unpredictable feature of the fiber deposited. For that sake, experiment has been done and analyzed to address these problems. Relation between process physics-Taylor cone and fiber diameter characters has been discovered. Furthermore, the feature parameters of the Taylor cone are extracted effectively by CCD detection and image processing. The above experiments results and processing data is analysis and examed by the steady jet theory. This paper offers significant theoretical guidance and technical support to the online control of electrospinning fiber diameter.
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Lin, Cheng-Jian, Chun-Hui Lin, and Shyh-Hau Wang. "Using Fuzzy Control for Feed Rate Scheduling of Computer Numerical Control Machine Tools." Applied Sciences 11, no. 10 (May 20, 2021): 4701. http://dx.doi.org/10.3390/app11104701.
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In industrial processing, workpiece quality and processing time have recently become important issues. To improve the machining accuracy and reduce the cutting time, the cutting feed rate will have a significant impact. Therefore, how to plan a dynamic cutting feed rate is very important. In this study, a fuzzy control system for feed rate scheduling based on the curvature and curvature variation is proposed. The proposed system is implemented in actual cutting, and to verify the data an optical three-dimensional scanner is used to measure the cutting trajectory of the workpiece. Experimental results prove that the proposed fuzzy control system for dynamic cutting feed rate scheduling increases the cutting accuracy by 41.8% under the same cutting time; moreover, it decreases the cutting time by 50.8% under approximately the same cutting accuracy.
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Beck, M. B., J. B. Watts, and S. Winkler. "An environmental process control laboratory: at the interface between instrumentation and model development." Water Science and Technology 37, no. 12 (June 1, 1998): 353–62. http://dx.doi.org/10.2166/wst.1998.0561.
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Success in the development and application of a model requires, as a rule, high-quality field data. In general, studies in controlling the dynamics of wastewater treatment processes have been poorly served in their access to such data. The Environmental Process Control Laboratory has been developed in order to rectify this limitation. The Laboratory is a mobile facility housing instrumentation for on-line respirometry and sensors for real-time monitoring of sludge blanket level and the concentrations of dissolved oxygen, suspended solids, ammonium-N, nitrite-N, total oxidised nitrogen, total organic carbon and orthophosphate-P concentrations. The Laboratory has been designed for deployment in a variety of contexts, but principally in the study of municipal and industrial wastewater treatment, protection of surface water quality, aquaculture, and groundwater contamination. Its purpose is to support the development of process models and, where appropriate, procedures of decision support and automatic control for these systems. Preliminary results from commissioning trials with the Laboratory at the Athens, Georgia, Water Pollution Control Facility Number 2 are reported. These expose some critical issues of signal pre-processing and the need to re-think a strategy for developing models in order to interpret the very large volumes of data generated by the Laboratory.
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Tall, Anne M., and Cliff C. Zou. "A Framework for Attribute-Based Access Control in Processing Big Data with Multiple Sensitivities." Applied Sciences 13, no. 2 (January 16, 2023): 1183. http://dx.doi.org/10.3390/app13021183.
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There is an increasing demand for processing large volumes of unstructured data for a wide variety of applications. However, protection measures for these big data sets are still in their infancy, which could lead to significant security and privacy issues. Attribute-based access control (ABAC) provides a dynamic and flexible solution that is effective for mediating access. We analyzed and implemented a prototype application of ABAC to large dataset processing in Amazon Web Services, using open-source versions of Apache Hadoop, Ranger, and Atlas. The Hadoop ecosystem is one of the most popular frameworks for large dataset processing and storage and is adopted by major cloud service providers. We conducted a rigorous analysis of cybersecurity in implementing ABAC policies in Hadoop, including developing a synthetic dataset of information at multiple sensitivity levels that realistically represents healthcare and connected social media data. We then developed Apache Spark programs that extract, connect, and transform data in a manner representative of a realistic use case. Our result is a framework for securing big data. Applying this framework ensures that serious cybersecurity concerns are addressed. We provide details of our analysis and experimentation code in a GitHub repository for further research by the community.
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Yan, Xin, and Guijiang Duan. "The Real-Time Prediction of Product Quality Based on the Equipment Parameters in a Smart Factory." Processes 10, no. 5 (May 11, 2022): 967. http://dx.doi.org/10.3390/pr10050967.
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Product quality is an important part of enterprise competitiveness. Product processing is the key process of quality formation. In smart factories, the improvement of data acquisition and processing capability provides a basis for data-based quality control. In order to reduce the occurrence of product quality problems, we abstracted the product processing process as a data processing unit, abstracted the process of changing the product quality state as a process of the processing quality characteristics data, divided the measured value of quality characteristics into three states according to the fluctuation of the measured value of product quality characteristics, and then the classification model of process equipment parameters was established. The experimental results show that the error rate of the real-time dynamic prediction of quality characteristics based on equipment parameters was acceptable, and its prediction could be used as a reference in real production. The research could be applied in product quality prediction, production process simulation, digital twin and other fields.
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Cai, Yun, Bangcheng Zhang, and Yu Yao. "Study on the dynamic coupling characteristics of 3PTT-2R numerical control serial–parallel machine based on singular constraints and position coupling factors." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 231, no. 9 (November 14, 2015): 1628–45. http://dx.doi.org/10.1177/0954405415599945.
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The dynamic coupling problem for the self-designed “3 parallel ∪ 2 series” mixed-type numerical control machine tool is studied based on the singular constraints and position coupling factors in order to ensure that the machine can have better dynamic characteristics and a higher quality of parts during the process of machining complex surface. This article puts forward a method based on singular constraints and the coupling factor. A whole dynamic coupling model of series and parallel mechanism is established and the coupling factors are determined. Numerical and parameter simulations of mechanism are analyzed and the real working space is obtained. And this article takes the simulation of the process of machining complex part and the force of the machine tool. The simulation results show that the established dynamics model is credible and reliable on the basis of considering singular constraints and position coupling factors. It is proved that the simulation data can correspond to the established model and the situation of force and kinematic suits the working mechanism. The cutting experiment of complex surface parts was took and the machine tool was run more smoothly and faster than the conventional machine tools. The velocity of the machine is regular and circular and there are no kinematic singularity data on the machine’s trajectory. The trajectory of the tool is in the working space completely and the accuracy of the part is good. The surface roughness results show that the kinematics accuracy of the machine tool is good. The interference fringe results show that the force of the machine tool is uniform. As there is no singular coupled vibration and collision, it is proved that the theoretical analysis is correct. The dynamics model of 3PTT serial and parallel mechanism is complete in this article. And the working space of the mechanism is obtained on the base of analysis of the singular constraints and position coupling factors. The article has carried out the dynamic simulation and processing experimental verification. Not only the method and process of this article was solved by dynamics coupling problem of 3PTT-2R numerical control machine tool actively, real-time and effectively, but also it was laid a foundation for accurate control of numerical control machine tools.
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Boncalo, Oana, Alexandru Amaricai, and Zsófia Lendek. "Fault Tolerant Digital Data-Path Design via Control Feedback Loops." Electronics 9, no. 10 (October 19, 2020): 1721. http://dx.doi.org/10.3390/electronics9101721.
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In this paper, we propose a novel fault tolerant methodology for digital pipelined data-paths called Control Feedback Loop Error Decimation (CFLED), that reduces the error magnitude at the outputs. The data-path is regarded from a control perspective as a process affected by perturbations or faults. Based on the corresponding dynamic model, we design feedback control loops with the goal of attenuating the effect of the faults on the output. The correction loops apply correction factors to selected data-path registers from blocks that have their execution rewinded. We apply the proposed methodology on the data-path of a controller designed for a 2-degree of freedom robot arm, and compare the cost and reliability to the generic triple modular redundancy. For Field Programmable Gate Array (FPGA) technology, the solution we propose uses 30% less slices with respect to Triple Modular Redundancy (TMR), while having a third less digital signal processing blocks. Simulation results show that our approach improves the reliability and error detection.
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Nayak, Siddharth, and Arthur C. Tsai. "Fronto—Parietal Regions Predict Transient Emotional States in Emotion Modulated Response Inhibition via Low Frequency and Beta Oscillations." Symmetry 14, no. 6 (June 15, 2022): 1244. http://dx.doi.org/10.3390/sym14061244.
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The current study evaluated the impact of task-relevant emotion on inhibitory control while focusing on midline cortical regions rather than brain asymmetry. Single-trial time-frequency analysis of electroencephalography recordings linked with response execution and response inhibition was done while thirty-four participants performed the emotion modulated stop-signal task. To evaluate individual differences across decision-making processes involved in inhibitory control, a hierarchical drift-diffusion model was used to fit data from Go-trials for each of the 34 participants. Response threshold in the early processing stage for happy and disgust emotions could be distinguished from the later processing stage at the mid-parietal and mid-frontal regions, respectively, by the single-trial power increments in low frequency (delta and theta) bands. Beta desynchronization in the mid-frontal region was specific for differentiating disgust from neutral emotion in the early as well as later processing stages. The findings are interpreted based on the influence of emotional stimuli on early perceptual processing originating as a bottom-up process in the mid-parietal region and later proceeding to the mid-frontal region responsible for cognitive control processing, which resulted in enhanced inhibitory performance. The results show the importance of mid-frontal and mid-parietal regions in single-trial dynamics of inhibitory control processing.
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Dorofieieva, Tatiana, and Serhii Kotliar. "Automated control and management system physical loads in skiing." Scientific Journal of National Pedagogical Dragomanov University. Series 15. Scientific and pedagogical problems of physical culture (physical culture and sports), no. 5(150) (May 27, 2022): 43–49. http://dx.doi.org/10.31392/npu-nc.series15.2022.5(150).10.
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Until recently, there is no research data and research on the control and modeling of training loads in skiing for children of children's and youth sports schools using modern databases in the training process. The purpose is to show one of the possible approaches to the analysis and generalization of training loads in the training of skiers, help scientists and trainers-practitioners, as well as encourage them to find alternative ways, forms and methods of studying the creative activity of the coach. Research methods: study, analysis and synthesis of literature, pedagogical observations, methods of mathematical statistics using Access database management system. Result. The automated information system of pedagogical control of educational and training loads on the example of skiing is presented, which is developed on the basis of the Access database management system. Its use allows: to carry out unified collection of information; to calculate derived indicators and do statistical data processing; to reflect the dynamics of the main parameters of training and competitive loads; to compile various types of reports for the period of any duration; to create models of various structural formations of the educational and training process in skiing.
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Kapoor, Komal, Christopher Amato, Nisheeth Srivastava, and Paul Schrater. "Using POMDPs to Control an Accuracy-Processing Time Trade-Off in Video Surveillance." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 2 (July 22, 2012): 2293–98. http://dx.doi.org/10.1609/aaai.v26i2.18972.
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With rapid profusion of video data, automated surveillance and intrusion detection is becoming closer to reality. In order to provide timely responses while limiting false alarms, an intrusion detection system must balance resources (e.g., time) and accuracy. In this paper, we show how such a system can be modeled with a partially observable Markov decision process (POMDP), representing possible computer vision filters and their costs in a way that is similar to human vision systems. The POMDP representation can be optimized to produce a dynamic sequence of operations and achieve a tradeoff between time and detection quality, taking into account uncertainty in the filter predictions. In a set of experiments on actual video data, we show that our method can both outperform static “expert” models and scale to large dynamic domains. These results suggest that our method could be used in real-world intrusion detection systems.
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Wang, Jin He, Hong Zhang, and Nan Zhang. "Software Design and Control Strategy for Polymerase Chain Reaction System." Advanced Materials Research 204-210 (February 2011): 1463–66. http://dx.doi.org/10.4028/www.scientific.net/amr.204-210.1463.
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This paper describes a method for software design and proposes a control strategy for data processing in temperature control system. According to the proposed method, a combined feed-forward plus PID control is proposed, with additional temperature sensors, the major load disturbance attached to the system is measured. The experimental results demonstrate that the temperature control strategy significantly improves the dynamic performance on the control process.
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Kwon, H., J. S. Kang, Y. Jo, and J. H. Kang. "Implementation of a GPS-RO data processing system for the KIAPS-LETKF data assimilation system." Atmospheric Measurement Techniques 8, no. 3 (March 16, 2015): 1259–73. http://dx.doi.org/10.5194/amt-8-1259-2015.
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Abstract. The Korea Institute of Atmospheric Prediction Systems (KIAPS) has been developing a new global numerical weather prediction model and an advanced data assimilation system. As part of the KIAPS package for observation processing (KPOP) system for data assimilation, preprocessing, and quality control modules for bending-angle measurements of global positioning system radio occultation (GPS-RO) data have been implemented and examined. The GPS-RO data processing system is composed of several steps for checking observation locations, missing values, physical values for Earth radius of curvature, and geoid undulation. An observation-minus-background check is implemented by use of a one-dimensional observational bending-angle operator, and tangent point drift is also considered in the quality control process. We have tested GPS-RO observations utilized by the Korean Meteorological Administration (KMA) within KPOP, based on both the KMA global model and the National Center for Atmospheric Research Community Atmosphere Model with Spectral Element dynamical core (CAM-SE) as a model background. Background fields from the CAM-SE model are incorporated for the preparation of assimilation experiments with the KIAPS local ensemble transform Kalman filter (LETKF) data assimilation system, which has been successfully implemented to a cubed-sphere model with unstructured quadrilateral meshes. As a result of data processing, the bending-angle departure statistics between observation and background show significant improvement. Also, the first experiment in assimilating GPS-RO bending angle from KPOP within KIAPS-LETKF shows encouraging results.
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Zavalov, Yury N., and Alexander V. Dubrov. "Short Time Correlation Analysis of Melt Pool Behavior in Laser Metal Deposition Using Coaxial Optical Monitoring." Sensors 21, no. 24 (December 16, 2021): 8402. http://dx.doi.org/10.3390/s21248402.
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The development and improvement of monitoring and process control systems is one of the important ways of advancing laser metal deposition (LMD). The control of hydrodynamic, heat and mass transfer processes in LMD is extremely important, since these processes directly affect the crystallization of the melt and, accordingly, the microstructural properties and the overall quality of the synthesized part. In this article, the data of coaxial video monitoring of the LMD process were used to assess the features of melt dynamics. The obtained images were used to calculate the time dependences of the characteristics of the melt pool (MP) (temperature, width, length and area), which were further processed using the short-time correlation (STC) method. This approach made it possible to reveal local features of the joint behavior of the MP characteristics, and to analyze the nature of the melt dynamics. It was found that the behavior of the melt in the LMD is characterized by the presence of many time periods (patterns), during which it retains a certain ordered character. The features of behavior that are important from the point of view of process control systems design are noted. The approach used for the analysis of melt dynamics based on STC distributions of MP characteristics, as well as the method for determining the moments of pattern termination through the calculation of the correlation power, can be used in processing the results of online LMD diagnostics, as well as in process control systems.
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Chen, Xiaodan, Desheng Zeng, Shuanglong Pang, and Fu Jun. "Cloud Computing Storage Data Access Control Method Based on Dynamic Re-Encryption." Security and Communication Networks 2021 (December 9, 2021): 1–10. http://dx.doi.org/10.1155/2021/4953074.
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In order to improve data security, ensure user privacy, and solve the problems of low data access control accuracy, long time consumption, and high energy consumption in traditional methods, a cloud computing storage data access control method based on dynamic re-encryption is proposed. The principal component analysis method is used to reduce the dimension of the cloud computing storage data, and the random forest algorithm is further used to classify and process the cloud computing storage data according to the processing results. On the basis of data preprocessing, an access control tree is established to obtain the correlation of data nodes. Finally, the dynamic re-encryption method is used for data security state transformation, and the data access control of cloud computing storage is realized through key generation, encryption, re-encryption key generation, and decryption. The experimental results show that the data access control accuracy of the method in this paper is high, time consumption is small, and energy consumption is small, and it is more suitable for cloud computing systems with huge data and information.
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Naikwad, S. N., and S. V. Dudul. "Identification of a Typical CSTR Using Optimal Focused Time Lagged Recurrent Neural Network Model with Gamma Memory Filter." Applied Computational Intelligence and Soft Computing 2009 (2009): 1–7. http://dx.doi.org/10.1155/2009/385757.
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A focused time lagged recurrent neural network (FTLR NN) with gamma memory filter is designed to learn the subtle complex dynamics of a typical CSTR process. Continuous stirred tank reactor exhibits complex nonlinear operations where reaction is exothermic. It is noticed from literature review that process control of CSTR using neuro-fuzzy systems was attempted by many, but optimal neural network model for identification of CSTR process is not yet available. As CSTR process includes temporal relationship in the input-output mappings, time lagged recurrent neural network is particularly used for identification purpose. The standard back propagation algorithm with momentum term has been proposed in this model. The various parameters like number of processing elements, number of hidden layers, training and testing percentage, learning rule and transfer function in hidden and output layer are investigated on the basis of performance measures like MSE, NMSE, and correlation coefficient on testing data set. Finally effects of different norms are tested along with variation in gamma memory filter. It is demonstrated that dynamic NN model has a remarkable system identification capability for the problems considered in this paper. Thus FTLR NN with gamma memory filter can be used to learn underlying highly nonlinear dynamics of the system, which is a major contribution of this paper.
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Chen, Yong, and Guo Qin Huang. "Development and Research on the Dynamics Simulation System for Surface Grinding Process with Diamond Wheel." Key Engineering Materials 589-590 (October 2013): 658–64. http://dx.doi.org/10.4028/www.scientific.net/kem.589-590.658.
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Vibration during high-speed surface grinding process is one of important factors to influence surface precision of machined workpieces and lead to low efficiency of grinding machine. Process parameters are usually obtained from empirical data or reference manuals for the avoidance of serious vibration even chatter and its effect. As a result, it generally leads to low rated power of machine tool and long processing cycle. To solve the problem, designing and development on a dynamics simulation system for surface grinding with high accuracy ,which will be capable to predict a series of dynamic characteristics in time and frequency domains, such as grinding force-vibration, as well as phase/frequency characteristics, relative power spectral analysis etc is necessary and shows good application prospect. Meanwhile, the system will be used to indicate the process parameters optimization and investigate distribution characteristics of grain chip thickness and surface topography precision. In the paper, surface grinding process with diamond wheel is chosen as the study object and its dynamic characteristics are investigated. Based on studies on the comprehensive influence mechanism of regenerative chatter theory and wheel run-out rotational model on instantaneous grinding chip thickness of grain unit, analytical models of grinding force are improved. Differential equations of damper grinding vibration system with two-degree-of-freedom and a close-loop control system model with regenerative chatter feedback circle on the basis of interaction behaviors of force and vibration are built. Several relevant numerical methods are introduced to develop the simulation system of grinding dynamics. By comparative analysis on solution accuracy, steadiness and convergence of the correlative algorithms, explicit Runge-Kutta formula is identified as the best solution to simulation system modeling. On the basis of the above work, main subsystems and functional modules in the system are presented. The whole designs of framework and prototype systems are finished.
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Puchała, Weronika, Michał Burdukiewicz, Michał Kistowski, Katarzyna A. Dąbrowska, Aleksandra E. Badaczewska-Dawid, Dominik Cysewski, and Michał Dadlez. "HaDeX: an R package and web-server for analysis of data from hydrogen–deuterium exchange mass spectrometry experiments." Bioinformatics 36, no. 16 (June 24, 2020): 4516–18. http://dx.doi.org/10.1093/bioinformatics/btaa587.
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Abstract Motivation Hydrogen–deuterium mass spectrometry (HDX-MS) is a rapidly developing technique for monitoring dynamics and interactions of proteins. The development of new devices has to be followed with new software suites addressing emerging standards in data analysis. Results We propose HaDeX, a novel tool for processing, analysis and visualization of HDX-MS experiments. HaDeX supports a reproducible analytical process, including data exploration, quality control and generation of publication-quality figures. Availability and implementation HaDeX is available primarily as a web-server (http://mslab-ibb.pl/shiny/HaDeX/), but its all functionalities are also accessible as the R package (https://CRAN.R-project.org/package=HaDeX) and standalone software (https://sourceforge.net/projects/HaDeX/). Supplementary information Supplementary data are available at Bioinformatics online.
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Li, Xilin, Malcolm S. Powell, and Tim Horberry. "Human Factors in Control Room Operations in Mineral Processing." Journal of Cognitive Engineering and Decision Making 6, no. 1 (January 5, 2012): 88–111. http://dx.doi.org/10.1177/1555343411432340.
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This study applied human factors research approaches to the complex and dynamic environment of mineral processing plants. In this domain, little formal human factors research has previously been undertaken, despite that human performance limitations are frequently noted as a bottleneck to effective production. This article presents a broad, operator-centered investigation on the current status of control room operations and explores the underlying barriers in the operators’ work environment. A total of 20 operators working at two types of Australian mineral processing plants were involved. Multiple data collection methods, including in situ observations and interviews, surveys, and reviews of documentation, were used. The findings revealed that operator control was essentially in a reactive mode, with operators often lacking the will or ability to engage in process optimization. A simplified work domain analysis was used to highlight the essential elements involved in operator control and to explore the gaps between the observed reactive behavior and the required proactive control employed by operators. Also, this study uncovered deficiencies in the current information and organizational environments constraining operator control ability. These deficiencies included poorly designed human-machine interface and alarms, insufficient operator training, and inappropriate task allocations. Further research for enhancing operator capacity is recommended and highlighted.
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Cican, Grigore, and Daniel Eugeniu Crunteanu. "Aerodynamic Noise Control Study of Nozzles with Triangular Chevrons." Applied Mechanics and Materials 436 (October 2013): 25–31. http://dx.doi.org/10.4028/www.scientific.net/amm.436.25.
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This paper has a small part of notion of chevron and the process that helps reducing the noise pollution. Based on the gas dynamic and geometrical parameters of a single flow jet engine one does a model of CFD data processing. In this process one observes the influence of chevrons on acoustic wave intensity produced by the jet . One studies a series of tests on triangular chevrons: immersions, the influence of the number of chevrons in order to settle the influence of the geometrical parameters on the flow and on the jet acoustics. Finally one presents the contribution of chevrons in noise pollution reduction.
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Basu, Aniruddha. "Post Boost Track Processing Using Conventional DBMS Software." Defence Science Journal 66, no. 2 (March 23, 2016): 130. http://dx.doi.org/10.14429/dsj.66.9244.
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<p>The design of air defence, traditional command control system is very challenging which has been used with basic methodologies. Traditional design is associated with unstructured and uncorrelated data and requires huge lines of code using hard disk drive (HDD) in the system. Hence an attempt was made for a better simplified database management system (DBMS) software data access methodology, which processed the incoming airborne data, message in RDBMS database to achieve full automation on real-time. The transaction is accomplished through SQL pass through method from the host decision making system into database. An algorithm of track identification during midcourse track separation was undertaken for prototype development on DBMS data access methodology. In this methodology Oracle C++ calls interface embedded query call was used from the host interface system. The purpose of this development was to find a comparison of online process timing between HDD and SSD using commercial database, and to evaluate performance of dynamic processing of RDBMS Database for identification of target vehicle and booster after separation. Produced experimentation results from improved performance of the proposed methodology on which futuristic command control system can rely.</p><p> </p>
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Jin, Jin, Qian Zhang, Jia He, and Hongnian Yu. "Quantum Dynamic Optimization Algorithm for Neural Architecture Search on Image Classification." Electronics 11, no. 23 (November 30, 2022): 3969. http://dx.doi.org/10.3390/electronics11233969.
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Deep neural networks have proven to be effective in solving computer vision and natural language processing problems. To fully leverage its power, manually designed network templates, i.e., Residual Networks, are introduced to deal with various vision and natural language tasks. These hand-crafted neural networks rely on a large number of parameters, which are both data-dependent and laborious. On the other hand, architectures suitable for specific tasks have also grown exponentially with their size and topology, which prohibits brute force search. To address these challenges, this paper proposes a quantum dynamic optimization algorithm to find the optimal structure for a candidate network using Quantum Dynamic Neural Architecture Search (QDNAS). Specifically, the proposed quantum dynamics optimization algorithm is used to search for meaningful architectures for vision tasks and dedicated rules to express and explore the search space. The proposed quantum dynamics optimization algorithm treats the iterative evolution process of the optimization over time as a quantum dynamic process. The tunneling effect and potential barrier estimation in quantum mechanics can effectively promote the evolution of the optimization algorithm to the global optimum. Extensive experiments on four benchmarks demonstrate the effectiveness of QDNAS, which is consistently better than all baseline methods in image classification tasks. Furthermore, an in-depth analysis is conducted on the searchable networks that provide inspiration for the design of other image classification networks.
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Statev, Vyacheslav Yu, Vladimir A. Dokuchaev, and Victoria V. Maklachkova. "Information security in the big data space." T-Comm 16, no. 4 (2022): 21–28. http://dx.doi.org/10.36724/2072-8735-2022-16-4-21-28.
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The purpose of this work is to develop the foundations of a new approach to the problem of information security in the context of "Big Data" technologies. The purpose of obtaining and processing information about the subject area is their subsequent use for the formation of targeted impacts on the control object. At the same time, observation and awareness of what is happening with the object was previously carried out through a certain system of informatization of the subject's activity, i.e. indirectly, and the implementation of the decision was carried out within the framework of the control object, i.e. directly. Under the conditions of Digital Transformation, the impact on the control object is carried out not directly, but on its "Digital Twin" with subsequent reduction, if necessary, of this impact on the physical control object. Thus, a system of digitalization of the subject's activity appears. When implementing such systems, one of the main principles is the principle of system security (ensuring information security). However, its implementation is hampered by the fact that "Big Data" technologies are associated not so much with their large volumes, but also with the need to process a variety of consolidated data that have a different structure, classification and indexing schemes. In this regard, it is proposed to analyze the DIKW-model and analyze the essence of the concepts included in it, which will make it possible to proceed to DIKW processing using "Big Data" technologies. At the same time, it becomes necessary to solve two problems: assessing the impact of the degree of consolidation of data, information and knowledge on the increase in their importance in ensuring the information security of the subject of the "Big Data" space and assessing the critical mass of data, information and knowledge available in the "Big Data" space, with from the point of view of their complex joint processing and obtaining more important information on their basis. To establish the necessary balance between the need for information exchange and the permissible restrictions on the dissemination of data, information and knowledge, a new virtual concept is introduced - "Information Boundary" and the issue of ensuring information security is reduced to the task of pragmatically justified access restriction for all levels of the DIKW-model and the concept of "DIKW - security. An intensional approach is proposed for controlling "Information Boundaries" in the process of using "Big Data" technologies, which ensures the transition from static solutions to the issues of ensuring the subject's information security to the implementation of dynamic procedures for such control using elements of Artificial Intelligence, monitoring this space and predicting one's "place" in the "Big Data" space.
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Krivonos, Roman A., Aleksey A. Rusinovich, Nikolay S. Motuzko, Aleksandr A. Lysenko, and Oleg Yu Chernykh. "Study of episootic situation and dynamics of episootic and infectious processes of bovine leukemia infection." Veterinaria Kubani, no. 6 (December 16, 2020): 5–7. http://dx.doi.org/10.33861/2071-8020-2020-6-5-7.
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One of the problems in dairy cattle breeding has become bovine leukemia since the middle of the 20th century in the Republic of Belarus. Initially, isolated cases of the disease were recorded according to the data of clinical signs and pathological changes in the case of death of animals and the results of veterinary sanitary examination at the section of meat processing plants. After the establishment of the infectious etiology of the disease and the introduction of the immune diffusion reaction into veterinary laboratory practice, the massive nature of its spread was established with corresponding economic losses for the livestock industry. Under the prevailing conditions, it was necessary to reliably study the indicators of the epizootic situation and the trends of the epizootic process affecting the spread of infection with the bovine leukemia virus in order to take effective measures to eliminate it. The authors considered the methodological approaches to the study of the epizootic situation and the dynamics of the epizootic process of bovine leukemia virus infection in the Republic of Belarus formed the basis of the developed monitoring system. It included 132 epizootic significant indicators, divided into 8 groups, reflecting the epizootic situation of bovine leukemia virus infection, taking into account age, sex, production, territorial and other characteristics of infectious and epizootic processes of the disease in the conditions of the Republic of Belarus, established the procedure for collecting and transmitting epizootic information for making management decisions. This made it possible to control the epizootic situation and predict its development, to determine the features and patterns of the epizootic process, to evaluate the results of diagnostic studies, the effectiveness of anti-leukemic measures and their socio-economic significance. The use of epizootic, clinical, pathomorphological, laboratory methods of research with subsequent statistical processing of the data obtained and their analysis in the monitoring system of infection of the cattle leukemia virus in the Republic of Belarus made it possible to control the epizootic situation, predict its development, determine the features and patterns of the epizootic process, evaluate the results of diagnostic research, the effectiveness of anti-leukemic measures and their socio-economic significance.
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Bointon, Patrick, Luke Todhunter, Adam Clare, and Richard Leach. "Performance Verification of a Flexible Vibration Monitoring System." Machines 8, no. 1 (January 3, 2020): 3. http://dx.doi.org/10.3390/machines8010003.
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The performance of measurement or manufacturing systems in high-precision applications is dependent upon the dynamics of the system, as vibration can be a significant contributor to the measurement uncertainty and process variability. Technologies making use of accelerometers and laser vibrometers are available to rapidly measure and process structural dynamic data but the software infrastructure is yet to be available in an open source or standardised format to allow rapid inter-platform use. In this paper, we present a novel condition monitoring system, which uses commercially available accelerometers in combination with a control-monitoring infrastructure to allow for the appraisal of the performance of a measurement or manufacturing system. A field-programmable gate array (FPGA)-based control system is implemented for high-speed data acquisition and signal processing of six triaxial accelerometers, with a frequency range of 1 Hz to 6000 Hz, a sensitivity of 102.5 mV/ms−2 and a maximum sample rate of 12,800 samples per second per channel. The system includes two methods of operation: real-time performance monitoring and detailed measurement/manufacturing verification. A lathe condition monitoring investigation is undertaken to demonstrate the utility of this system and acquire typical machining performance parameters in order to monitor the “health” of the system.
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BLEICHER, Friedrich, Paul SCHÖRGHOFER, and Christoph HABERSOHN. "IN-PROCESS CONTROL WITH A SENSORY TOOL HOLDER TO AVOID CHATTER." Journal of Machine Engineering 18, no. 3 (September 6, 2018): 16–27. http://dx.doi.org/10.5604/01.3001.0012.4604.
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Hydro-, steam- and gas- turbines, aircraft components or moulds are milled parts with complex geometries and high requirements for surface quality. The production of such industry components often necessitates the use of long and slender tools. However, instable machining situations together with work pieces with thin wall thickness can lead to dynamic instabilities in the milling processes. Resulting chatter vibrations cause chatter marks on the work piece surface and have influence on the tool lifetime. In order to detect and avoid the occurrence of process instabilities or process failures in an early stage, the Institute for Production Engineering and Laser Technology (IFT) developed an active control system to allow an in-process adaption of machining parameters. This system consists of a sensory tool holder with an integrated low cost acceleration sensor and wireless data transmission under real time conditions. A condition monitoring system using a signal-processing algorithm, which analyses the received acceleration values, is coupled to the NC- control system of the machine tool to apply new set points for feed rate and rotational speed depending on defined optimisation strategies. By the implementation of this system process instabilities can be avoided.
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Kahl, Matthias, Sebastian Schramm, Max Neumann, and Andreas Kroll. "Identification of a Spatio-Temporal Temperature Model for Laser Metal Deposition." Metals 11, no. 12 (December 18, 2021): 2050. http://dx.doi.org/10.3390/met11122050.
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Laser-based additive manufacturing enables the production of complex geometries via layer-wise cladding. Laser metal deposition (LMD) uses a scanning laser source to fuse in situ deposited metal powder layer by layer. However, due to the excessive number of influential factors in the physical transformation of the metal powder and the highly dynamic temperature fields caused by the melt pool dynamics and phase transitions, the quality and repeatability of parts built by this process is still challenging. In order to analyze and/or predict the spatially varying and time dependent thermal behavior in LMD, extensive work has been done to develop predictive models usually by using finite element method (FEM). From a control-oriented perspective, simulations based on these models are computationally too expensive and are thus not suitable for real-time control applications. In this contribution, a spatio-temporal input–output model based on the heat equation is proposed. In contrast to other works, the parameters of the model are directly estimated from measurements of the LMD process acquired with an infrared (IR) camera during processing specimens using AISI 316 L stainless steel. In order to deal with noisy data, system identification techniques are used taking different disturbing noise into account. By doing so, spatio-temporal models are developed, enabling the prediction of the thermal behavior by means of the radiance measured by the IR camera in the range of the considered processing parameters. Furthermore, in the considered modeling framework, the computational effort for thermal prediction is reduced compared to FEM, thus enabling the use in real-time control applications.
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Huang, Jie, and Dehua Wu. "Access Control Model Scheme based on Policy Grading in Natural Language Processing Blockchain Environment." Mobile Information Systems 2022 (August 8, 2022): 1–9. http://dx.doi.org/10.1155/2022/4365944.
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In order to solve many problems such as secure storage of access policies and distrust of third parties in complex and dynamic big data environment, a hierarchical access control model under block chain environment (BP-ABAC) is proposed. Access control policies are stored in blockchain in the form of smart contracts, and access control policies are classified in contract design. Users can obtain the access permission of the corresponding policy set according to the rating evaluation. Access to a resource is obtained when the request attribute matches the policy in the policy set. The simulation results show that the model can grant corresponding access control permissions according to different users’ access requests, improve the time efficiency and accuracy of the access control process, and improve the security and privacy of the storage of access policies and the interaction of data sharing.
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Lang, Wei Min, Yuan Cheng Zhu, and Hu Sheng Li. "Propagation of Spurious Data for Wireless Cognitive Sensor Network in the Smart Grid: A Social Network Method." Advanced Materials Research 546-547 (July 2012): 242–47. http://dx.doi.org/10.4028/www.scientific.net/amr.546-547.242.
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The nature of white space utilization, tremendous data processing, heterogeneous coexistence and security guarantees in Wireless Cognitive Sensor Network (WCSN) brings significant advantages over traditional Wireless Sensor Network (WSN) used in the smart grid. However, one of the main security threats to WCSN in the smart grid is the transmission of spurious data by malicious secondary users, which can induce the control center to make a wrong spectrum allocation and power dispatching decisions. In this paper, after analyzing the reference structure of smart grid and the feasibility of applying the epidemic theory into WCSN, we propose the UDG model of WCSN in the smart grid. Based on the epidemic theory in social network, we model and analyze the spurious data propagation process and identify key factors determining potential epidemic outbreaks in WCSN. In conclusion, we validate the feasibility of SIS model and perform investigations on the system dynamics.
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Alabugin, Anatoliy, Sergei Aliukov, and Konstantin Osintsev. "Combined Approach to Analysis and Regulation of Thermodynamic Processes in the Energy Technology Complex." Processes 9, no. 2 (January 21, 2021): 204. http://dx.doi.org/10.3390/pr9020204.
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The purpose of this work is to increase the theoretical and methodological approaches to value and regulate the dynamics of management processes. Application of these dynamics is implemented via methods of improving the quality of management of complex energy technology systems in the organization of recycling processes. As a result of the research, a technological model of a rotary kiln with a division into separate sections corresponding to the combustion zones for the production of cement clinker in recycling technology was developed. Mathematical modeling, analytical calculations of thermodynamic and gas-dynamic processes in the drums of rotating furnaces, and experimental studies were carried out. As a scientific novelty, an approximation of piecewise linear functions is obtained for modeling the processes of improving the quality of control by the criterion of reducing the error of data transmission for monitoring and regulating the thermodynamic parameters of the furnace via analog-to-digital methods. An algorithmic scheme of the method of in-depth analysis of management quality using data science tools in the concept of combining organizational, economic, technical, technological, and mathematical methods and methods of data collection, processing, and storage of big data is developed. This made it possible to apply the models in the formed energy technology complex using learning neural network algorithms. The possibilities of applying the methodology of combining methods for in-depth analysis and modeling of thermodynamic processes in an energy technological complex with any composition of equipment for the production of cement clinker are substantiated.
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Herceg, Srećko, Željka Ujević Andrijić, and Nenad Bolf. "Support Vector Machine-based Soft Sensors in the Isomerisation Process." Chemical & biochemical engineering quarterly 34, no. 4 (2021): 243–55. http://dx.doi.org/10.15255/cabeq.2020.1825.
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This paper presents the development of soft sensor empirical models using support<br /> vector machine (SVM) for the continual assessment of 2,3-dimethylbutane and 2-methylpentane mole percentage as important product quality indicators in the refinery isomerisation process. During the model development, critical steps were taken, including selection and pre-processing of the industrial process data, which are broadly discussed in this paper. The SVM model results were compared with dynamic linear output error model and nonlinear Hammerstein-Wiener model. Evaluation of the developed models on independent data sets showed their reliability in the assessment of the component contents. The soft sensors are to be embedded into the process control system, and serve primarily as a replacement during the process analysersb failure and service periods.
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Yakovenko, O. K., M. I. Linnik, V. I. Ignatieva, G. L. Gumenyuk, O. R. Tarasenko, and V. A. Svyatinenko. "Remote results of the course of non-acute viral pneumonia COVID-19 according to computed tomography." Tuberculosis, Lung Diseases, HIV Infection, no. 2 (June 17, 2022): 18–23. http://dx.doi.org/10.30978/tb-2022-2-18.
Full textAbstract:
Objective — to study the dynamics of changes in the structure of the lungs in patients with a complicated course of non-hospital viral pneumonia COVID-19 by programmatic processing of computed tomography (CT) scan data and to determine the features of changes to predict its course.
Materials and methods. The dynamics of these CT scan 70 patients for non-hospital pneumonia of viral etiology (COVID-19) was analyzed. The diagnosis of COVID-19 was established in accordance with the current protocols for the treatment of coronavirus disease. CT scan was performed on the scanner Aquilion TSX-101A Tochiba (Japan) with the recording of the results on digital media with their subsequent software processing.
Results and discussion. Of the 70 patients for non-hospital pneumonia of viral etiology (COVID-19), 21 patients (15 men and 6 women) were diagnosed with «disappearing lung syndrome», which accounted for 30 % of all those examined. Cases of the formation of massive fibrous post-inflammatory changes were not detected.We performed software processing of CT data of patients’ OGC in dynamics during 6—12 months. On average, control CT scans of the OGC were performed every 2—3 months. At the same time we determined the peculiarities of densitometric indexes dynamics, according to which we could predict the course of non-hospital pneumonia of viral etiology (COVID-19).
Conclusions. Given the high percentage of diagnosis of «disappearing lung syndrome» caused by the autoimmune process in patients with complicated non-hospital viral pneumonia COVID-19, it is necessary to develop methods for its treatment. In order to diagnose complications, prevent them and predict the course of severe forms of pneumonia pneumonia COVID-19, it is necessary to conduct a CT scan in dynamics with densitometric examinations of the pulmonary parenchyma.
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Li, Yue-jie. "Data Stream of Wireless Sensor Networks Based on Deep Learning." International Journal of Online Engineering (iJOE) 12, no. 11 (November 24, 2016): 22. http://dx.doi.org/10.3991/ijoe.v12i11.6232.
Full textAbstract:
The sensor data in wireless sensor networks are continuously arriving in multiple, rapid, time varying, possibly unpredictable, unbounded streams, and no record of historical information is kept. These limitations make conventional Database Management Systems and their evolution unsuitable for streams. Thereby there is a need to build a complete Data Streaming Management System (DSMS), which could process streams and perform dynamic continuous query processing. In this paper, a framework for Adaptive Distributed Data Streaming Management System (ADDSMS) is presented, which operates as streams control interface between arrays of distributed data stream sources and end-user clients who access and analyze these streams. Simulation results show that the proposed method can thus improve overall system performance substantially.
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Yan, Li Wen, and Qi Bao He. "The Study of Error Separation in On-Site Measurement Based on Bayesian Network." Applied Mechanics and Materials 229-231 (November 2012): 1369–72. http://dx.doi.org/10.4028/www.scientific.net/amm.229-231.1369.
Full textAbstract:
The measurement error contains many errors in NC machine tools processing and those errors will be mapped to workpiece at certain regularity. The control of error caused by cutting parameters during the precision and ultra precision process is one of the key technologies in NC machine tools processing. This article introduces Bayesian networks into the dynamic error separation modeling, with the learning process of Bayesian network structure and establishes the error separation model based on Bayesian networks, then carries out the comparison and analysis between simulate and experimental data to verify the feasibility of the method.