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Ferrero, A., S. Leva, and A. P. Morando. "An approach to the non-active power concept in terms of the poynting-park vector." European Transactions on Electrical Power 11, no. 5 (September 2001): 291–99. http://dx.doi.org/10.1002/etep.4450110503.
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Corne, Bram, Bram Vervisch, Stijn Derammelaere, Jos Knockaert, and Jan Desmet. "The reflection of evolving bearing faults in the stator current’s extended park vector approach for induction machines." Mechanical Systems and Signal Processing 107 (July 2018): 168–82. http://dx.doi.org/10.1016/j.ymssp.2017.12.010.
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Jačková, Kateřina, and Dušan Romportl. "The Relationship Between Geodiversity and Habitat Richness in Šumava National Park and Křivoklátsko PLA (Czech Republic): A Quantitative Analysis Approach." Journal of Landscape Ecology 1, no. 1 (January 1, 2008): 23–38. http://dx.doi.org/10.2478/v10285-012-0003-6.
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The Relationship Between Geodiversity and Habitat Richness in Šumava National Park and Křivoklátsko PLA (Czech Republic): A Quantitative Analysis Approach This paper focuses on the development of a quantitative method for evaluating the relationship between abiotic heterogeneity and habitat richness at the landscape level. The study took place in the Křivoklátsko protected landscape area and Šumava national park (Czech Republic). Our initial hypothesis was that habitat richness should be high in areas with high abiotic heterogeneity, and vice versa. GIS vector layers of habitat were used for the formulation of habitat richness. A geological layer, a digital terrain model and hydrographic layers were used to determine abiotic heterogeneity. The study areas were overlain by a grid square and habitat richness and abiotic heterogeneity were assessed in each study cell. The data obtained were used in a statistical model (multiple spatial linear regression, with maximum credibility). The results of the statistical model indicated a significant influence of abiotic heterogeneity on habitat richness.
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KLYUCHNIKOV, Anatoly T. "A Speed Observer for Sensorless Control of an Induction Motor." Elektrichestvo 2, no. 2 (2021): 54–59. http://dx.doi.org/10.24160/0013-5380-2021-2-54-59.
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Half a century has passed since the time F. Blaschke received a patent for vector control of an induction motor with a speed sensor and a Hall sensor. Since that time, the transformation of generalized vectors in the Park—Gorev equations as projections on the axes in different coordinate frames aft, dq, and xy has been regarded to be a commonly accepted one. With this approach, five differential and four algebraic equations with cross-links have to be solved for studying the processes in an induction motor, which involves certain inconvenience of analyzing the processes in the machine. Eventually, many versions of high-quality electric motor control systems have been developed. Owing to the progress achieved in computer engineering, it has become possible to solve a fewer number of the Park—Gorev equations in complex form without decomposing the vectors into projections on the coordinate ases aft, dq, xy. At present, the majority of widely used programming languages (FORTRAN, C+, MathCAD, MatLAB, etc.) offer efficient tools for implementing the operations of summing and multiplying complex quantities. In the article, the Park-Gorev equations are solved without decomposing the vectors into their projections on the coordinate axes вб, dq, xy. In so doing, the induction motor complex speed observer uses only two voltage equations and two flux linkage equations. The rotor motion equation is not used to determine the speed. The obtained algorithms for solving by means of a complex speed observer made it possible to determine the currents, electromagnetic torque and motor’s moment of inertia. The proposed algorithms written in the б-в and x-y coordinate systems made it possible to determine the motor speed in its fast start-up process (0.2 s) with an error of less than 1%.
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Rijal, Seftiawan Samsu, Tien Dat Pham, Salma Noer ‘Aulia, Muhammad Ikbal Putera, and Neil Saintilan. "Mapping Mangrove Above-Ground Carbon Using Multi-Source Remote Sensing Data and Machine Learning Approach in Loh Buaya, Komodo National Park, Indonesia." Forests 14, no. 1 (January 4, 2023): 94. http://dx.doi.org/10.3390/f14010094.
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Mangrove forests provide numerous valuable ecosystem services and can sequester a large volume of carbon that can help mitigate climate change impacts. Modeling mangrove carbon with robust and valid approaches is crucial to better understanding existing conditions. The study aims to estimate mangrove Above-Ground Carbon (AGC) at Loh Buaya located in the Komodo National Park (Indonesia) using novel Extreme Gradient Boosting (XGB) and Genetic Algorithm (GA) analyses integrating multiple sources of remote sensing (optical, Synthetic Aperture Radar (SAR), and Digital Elevation Model (DEM)) data. Several steps were conducted to assess the model’s accuracy, starting with a field survey of 50 sampling plots, processing the images, selecting the variables, and examining the appropriate machine learning (ML) models. The effectiveness of the proposed XGB-GA was assessed via comparison with other well-known ML techniques, i.e., the Random Forest (RF) and the Support Vector Machine (SVM) models. Our results show that the hybrid XGB-GA model yielded the best results (R2 = 0.857 in the training and R2 = 0.758 in the testing phase). The proposed hybrid model optimized by the GA consisted of six spectral bands and five vegetation indices generated from Sentinel 2B together with a national DEM that had an RMSE = 15.40 Mg C ha−1 and outperformed other ML models for quantifying mangrove AGC. The XGB-GA model estimated mangrove AGC ranging from 2.52 to 123.89 Mg C ha−1 (with an average of 57.16 Mg C ha−1). Our findings contribute an innovative method, which is fast and reliable using open-source data and software. Multisource remotely sensed data combined with advanced machine learning techniques can potentially be used to estimate AGC in tropical mangrove ecosystems worldwide.
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Rahmatullah, Rohullah, Necibe Fusun Oyman Serteller, and Vedat Topuz. "Modeling and Simulation of Faulty Induction Motor in DQ Reference Frame Using MATLAB/SIMULINK with MATLAB/GUIDE for Educational Purpose." International Journal of Education and Information Technologies 17 (March 13, 2023): 7–20. http://dx.doi.org/10.46300/9109.2023.17.2.
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Owing to their robust structure, induction motors are preferred to be used under difficult working conditions. Therefore, various faults may occur in the motor due to unexpected forces during the operations. Obtaining the data through experimental methods by physically creating faults in the induction motors, and analyzing their behavior is not efficient in terms of cost and time for educational purposes. Considering the above negative situation, in this paper, mathematical models have been developed in the dq0 stationary reference frame expressing three-phase stator windings short-circuit fault and broken rotor bar fault in induction motors. The proposed models are faster as compared to the other analytical models in terms of computation due to the rotor position independence of the inductance matrix. The faulty induction motor mathematical models have been implemented in the MATLAB/SIMULINK software environment with detailed explanations of each faulty model’s subsystem. As a visual laboratory that can be used as an educational tool for the analysis of a three-phase faulty induction motor, a graphical user interface application has been developed in MATLAB/GUIDE, which allows users to simulate models from a single interface. As a case study, the behaviors of faulty induction motors in transient and steady states have been simulated in different severity scenarios of the faults. The park vector method has been used as a fault diagnosis approach to investigate fault types and the fault severity effects on the park vector pattern in each fault scenario. In addition, to observe the success of the developed Simulink toolboxes, they were used at Marmara University through courses in electrical machinery and evaluated by the graduated students at the end of the semester.
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Yuan, Jinlong, Yunbin Wu, Zhifeng Shu, Lian Su, Dawei Tang, Yuanjian Yang, Jingjing Dong, Saifen Yu, Zhen Zhang, and Haiyun Xia. "Real-Time Synchronous 3-D Detection of Air Pollution and Wind Using a Solo Coherent Doppler Wind Lidar." Remote Sensing 14, no. 12 (June 11, 2022): 2809. http://dx.doi.org/10.3390/rs14122809.
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The monitoring and tracking of urban air pollution is a challenging environmental issue. The approach of synchronous 3-D detection of wind and pollution using a solo coherent Doppler wind lidar (CDWL) is developed and demonstrated. The 3-D distribution of pollutant is depicted by the backscatter coefficient based on signal intensity of CDWL. Then, a high-resolution wind field is derived to track the local air pollution source with its diffusion and to analyze transboundary air pollution episodes. The approach is experimentally implemented in a chemical industry park. Smoke plumes caused by point source pollutions are captured well using plan position indicator (PPI) scanning with low elevation. A typical source of pollution is located, combining the trajectory of the smoke plume and the horizontal wind vector. In addition, transboundary air pollution caused by the transport of dust storms is detected in a vertical profile scanning pattern, which is consistent with the results of national monitoring stations and backward trajectory models. Our present work provides a significant 3-D detection approach to air pollution monitoring with its sources, paths, and heights by using a solo-CDWL system.
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Soufi, Youcef, Tahar Bahi, H. Merabet, and S. Lekhchine. "Short Circuit between Turns in Stator Winding of Induction Machine Fault Detection and Diagnosis." Applied Mechanics and Materials 416-417 (September 2013): 565–71. http://dx.doi.org/10.4028/www.scientific.net/amm.416-417.565.
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The induction motor is one of the most used electric machines in variable speed system in the different field of industry due to its robustness, mechanical strength and low cost. Despite these qualities, the induction machine is subjected during its operation to a number of constraints of various natures (electrical, mechanical and environmental). This paper focuses on the diagnosis and the detection of the short circuit fault between turns in the stator winding of an induction machine, based on analyzing the evolution of the stator current in each stator phase, using tools based both on motor current spectral analysis and Park vector approach. A study by simulation was presented. The obtained results show that the considered methods can effectively diagnose and detect abnormal operating conditions in induction motor applications. Therefore, they clearly show the possibility of extracting signatures and the application of these techniques offered reliable and satisfactory results for the diagnosis and detection of such fault.
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de Sousa, Matheus Martins, Osvaldo Moura Rezende, Ana Caroline Pitzer Jacob, Luiza Batista de França Ribeiro, Paula Morais Canedo de Magalhães, Gladys Maquera, and Marcelo Gomes Miguez. "Flood Risk Assessment Index for Urban Mobility with the Aid of Quasi-2d Flood Model Applied to an Industrial Park in São Paulo, Brazil." Infrastructures 7, no. 11 (November 18, 2022): 158. http://dx.doi.org/10.3390/infrastructures7110158.
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Risk can be defined as the relationship between the likelihood of a hazard causing a potential disaster and its consequences. This study aims to assess the likelihood that a new industrial region, located in the state of São Paulo (Brazil), will be flooded, causing the disruption of the mobility system and local economic activities. To fulfill this aim, a new approach is proposed by combining the vector information of the highway network that serves the region with the result of a quasi 2-D raster flood model, generating a set of interpreting rules for classifying the safety of routes. The model called MODCEL is a quasi-2D hydrodynamic model that represents the watershed using compartments called cells, and it was adapted to work using a raster file format in which each pixel is represented as a flow cell connected to its surroundings by the Saint-Venant equations without the inertia terms. Therefore, this study proposes an assessment framework that can be replicated for similar problems of flood risks to mobility. The possible effects of flood events on the accessibility to areas of interest are determined, indicating a possible disruption to economic activities and transportation and allowing for planning alternatives in advance.
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Herrero, Southworth, Bunting, Kohlhaas, and Child. "Integrating Surface-Based Temperature and Vegetation Abundance Estimates into Land Cover Classifications for Conservation Efforts in Savanna Landscapes." Sensors 19, no. 16 (August 7, 2019): 3456. http://dx.doi.org/10.3390/s19163456.
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Southern African savannas are an important dryland ecosystem, as they account for up to 54% of the landscape, support a rich variety of biodiversity, and are areas of key landscape change. This paper aims to address the challenges of studying this highly gradient landscape with a grass–shrub–tree continuum. This study takes place in South Luangwa National Park (SLNP) in eastern Zambia. Discretely classifying land cover in savannas is notoriously difficult because vegetation species and structural groups may be very similar, giving off nearly indistinguishable spectral signatures. A support vector machine classification was tested and it produced an accuracy of only 34.48%. Therefore, we took a novel continuous approach in evaluating this change by coupling in situ data with Landsat-level normalized difference vegetation index data (NDVI, as a proxy for vegetation abundance) and blackbody surface temperature (BBST) data into a rule-based classification for November 2015 (wet season) that was 79.31% accurate. The resultant rule-based classification was used to extract mean Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI values by season over time from 2000 to 2016. This showed a distinct separation between each of the classes consistently over time, with woodland having the highest NDVI, followed by shrubland and then grassland, but an overall decrease in NDVI over time in all three classes. These changes may be due to a combination of precipitation, herbivory, fire, and humans. This study highlights the usefulness of a continuous time-series-based approach, which specifically integrates surface temperature and vegetation abundance-based NDVI data into a study of land cover and vegetation health for savanna landscapes, which will be useful for park managers and conservationists globally.
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Dong, Hao, Han Wu, Pengfei Sun, and Yunhong Ding. "Wildfire Prediction Model Based on Spatial and Temporal Characteristics: A Case Study of a Wildfire in Portugal’s Montesinho Natural Park." Sustainability 14, no. 16 (August 15, 2022): 10107. http://dx.doi.org/10.3390/su141610107.
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Wildfires influence the global carbon cycle, and the regularity of wildfires is mostly determined by elements such as meteorological conditions, combustible material states, and human activities. The time series and spatial dispersion of wildfires have been studied by some scholars. Wildfire samples were acquired in a monthly series for the Montesinho Natural Park historical fire site dataset (January 2000 to December 2003), which can be used to assess the possible effects of geographical and temporal variations on forest fires. Based on the above dataset, dynamic wildfire distribution thresholds were examined using a K-means++ clustering technique for each subgroup, and monthly series data were categorized as flammable or non-flammable depending on the thresholds. A five-fold hierarchical cross-validation strategy was used to train four machine learning models: extreme gradient boosting (XGBoost), random forest (RF), support vector machine (SVM), and decision tree (DT). Finally, to explore the performance of those we have mentioned, we used accuracy (ACC), F1 score (F1), and the values for the area under the curve (AUC) of the receiver operating characteristics (ROCs). The results depicted that the XGBoost model works best under the evaluation of the three metrics (ACC = 0.8132, F1 = 0.7862, and AUC = 0.8052). The model performance is significantly improved when compared to the approach of classifying wildfires by burned area size (ACC = 72.3%), demonstrating that spatiotemporal heterogeneity has a broad influence on wildfire occurrence. The law of a spatiotemporal distribution connection in wildfires could aid in the prediction and management of wildfires and fire disasters.
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Liu, Jianqiang, Hu Tan, Yunming Shi, Yu Ai, Shaoyong Chen, and Chenyang Zhang. "Research on Diagnosis and Prediction Method of Stator Interturn Short-Circuit Fault of Traction Motor." Energies 15, no. 10 (May 20, 2022): 3759. http://dx.doi.org/10.3390/en15103759.
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The traction motor (TM) is an essential part of the high-speed train, the health condition of which determines the quality and safety of the vehicle. Hence, this study proposed a novel approach to diagnosing and predicting the TM stator interturn short-circuit fault (SISCF). Based on the Park vector (PV) of the stator current, this method could overcome the interference of current sensor errors, null shift, and motor frequency fluctuations in the actual conditions. More specifically, Park’s transformation was used to obtain the PV of the stator current. Then, the PV was fitted to obtain the elliptical trajectory and its parameters from which the negative sequence component of the stator current could be calculated. Finally, the SISCF diagnosis and prediction method were realized by the magnitude and trend of the negative current as well as the inclination of the trajectory ellipse. Furthermore, the performance of the proposed method was validated by a simulation model and a series of experiments. The simulation results were consistent with the experimental results, supporting the validity and correctness of the method proposed in this study.
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Merylovа, Іryna. "RECREATIONAL CLUSTER IN THE STRUCTURE OF DNIPRO." Urban development and spatial planning, no. 81 (August 31, 2022): 254–62. http://dx.doi.org/10.32347/2076-815x.2022.81.254-262.
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The relevance of the article is due to the search for new forms and methods of creating recreation that correspond to the time and social needs. In accordance with the method of experimental design, on the example of the territory of the industrial hub ‘Fabrychnyi’ (Dnipro), the rationality of using the cluster approach to the creation of recreational facilities was demonstrated.
It is noted that the cluster is both a flexible structural unit of the regional system of recreation and tourism, and a self-sufficient form of territorial organization with its own system of connections and relations.
The purpose of the project is to empty the territory from industrial buildings for recreation, as well as to redevelop industrial buildings of historical, architectural and aesthetic value into cultural ones. The main focus of the project is to create an exhibition and museum complex with an ‘open-air museum’ and develop pedestrian infrastructure in the park.
The article considers the possibility of creating a recreational cluster, which will ensure certain continuity of natural framework, regarding its multi-vector formation in the urban structure. This connection of the recreational cluster with water area, will allow reestablishing a pedestrian and recreational framework in the city. It is established that the introduction of a cluster approach will contribute to the greening of the city, and will affect the modeling of ecological infrastructure.
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Cañete, Guillermo Herrador, Marta Zalacain, Sara Labiano, Javier Martinez, Cristian Smerdou, and Marta Alonso. "741 Expression of galectin-3 inhibitors from a self-replicating RNA vector as treatment for pediatric osteasarcoma." Journal for ImmunoTherapy of Cancer 9, Suppl 2 (November 2021): A772. http://dx.doi.org/10.1136/jitc-2021-sitc2021.741.
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BackgroundOsteosarcoma is an aggressive bone tumor, primarily arising in the pediatric age. Despite years of intensive research, outcome for metastatic and non-responder patients is very poor and has not improved in the last 30 years. These tumors harbor a highly immunosuppressive environment, making the existing immunotherapies ineffective. Inhibition of galectin-3 (Gal3), a protein involved in immunosuppression,1–3 adhesion of tumor cells,4 5 and metastases,6–9 has been demonstrated to reduce tumor progression in different tumor models, including osteosarcoma.10–12 On the other hand, virotherapy based on recombinant Semliki Forest Virus (SFV), a self-replicating RNA virus, has shown therapeutic effect in orthotopic osteosarcoma mouse models.13MethodsWe generated SFV vectors expressing truncated forms of Gal3, including its carboxy-terminal domain (SFV-Gal3-C) and its amino-terminal domain alone (SFV-Gal3-N) or fused to the Gal3 inhibitor peptide C12 (SFV-Gal3-N-C12). An additional construct expressed the C12 peptide14 15 (SFV-C12). We analyzed Gal3 expression in different murine and human osteosarcoma cell lines. Orthotopic osteosarcoma tumors, induced by intratibial injection of K7M2 murine cells, which showed high expression of Gal3, were treated with SFV vectors expressing Gal3 inhibitors or luciferase or with PBS (control). Animals were maintained under standard conditions, and all procedures were approved by the Institutional Ethical Committee (CEEA) in accordance with the guidelines of the University of Navarra, approval number 044-21.ResultsTreatment with the SFV-Gal3-N-C12 vector showed the highest antitumor activity, significantly reducing tumor growth compared to control mice that received PBS. In fact, this vector prolonged animal survival, leading to 47% of complete regressions. Among the other vectors, SFV-Gal3-N and SFV-C12 were also able to transiently decrease tumor growth, although they had no impact on animal survival. Moreover, the number of spontaneous lung metastasis were reduced in mice treated with SFV vectors expressing Gal3 inhibitors. Preliminary mechanistic studies showed an increase of CD3 cells infiltration in tumors treated with SFV-Gal3-N-C12 and SFV-Gal3-N vectors. Despite the antitumor effect observed with SFV-Gal3-N-C12, no protection against tumor rechallenge was observed in cured mice, indicating the lack or insufficient memory immune response generation. These data suggested that this therapeutic approach might benefit from combination with other immunodulatory strategies. We are currently characterizing the underpinnings of the mechanisms underlying this strategy.ConclusionsIn summary, we believe that inhibition of Gal3 using SFV vectors could constitute a potential approach to explore as therapy for pediatric osteosarcoma.ReferencesFarhad M, Rolig AS, Redmond WL. The role of Galectin-3 in modulating tumor growth and immunosuppression within the tumor microenvironment. Oncoimmunology 2018;7(6):p.e1434467.Ruvolo PP. Galectin 3 as a guardian of the tumor microenvironment. Biochim Biophys Acta 2016;1863(3):427–437.Guo Y, et al. Roles of galectin3 in the tumor microenvironment and tumor metabolism (Review). Oncol Rep 2020;44(5):1799–1809.Cao Z, et al. Endogenous and exogenous galectin-3 promote the adhesion of tumor cells with low expression of MUC1 to HUVECs through upregulation of N-cadherin and CD44. Lab Invest 2018;98(12):1642–1656.Kim SJ, Chun KH. Non-classical role of Galectin-3 in cancer progression: translocation to nucleus by carbohydrate-recognition independent manner. BMB Rep 2020;53(4):173–180.Pereira JX, et al. Galectin-3 regulates the expression of tumor glycosaminoglycans and increases the metastatic potential of breast cancer. J Oncol 2019;2019:9827147.Song M, et al. Galectin-3 favours tumour metastasis via the activation of beta-catenin signalling in hepatocellular carcinoma. Br J Cancer 2020;123(10):1521–1534.Fortuna-Costa A, et al. Extracellular galectin-3 in tumor progression and metastasis. Front Oncol 2014;4:138.Nakajima K, et al. Galectin-3 in bone tumor microenvironment: a beacon for individual skeletal metastasis management. Cancer Metastasis Rev 2016;35(2):333–46.Nakajima K, Balan V, Raz A. Galectin-3: an immune checkpoint target for musculoskeletal tumor patients. Cancer Metastasis Rev 2021;40(1):297–302.Lei P, et al. Small interfering RNA-induced silencing of galectin-3 inhibits the malignant phenotypes of osteosarcoma in vitro. Mol Med Rep 2015;12(4):6316–22.Park GB, et al. Silencing of galectin-3 represses osteosarcoma cell migration and invasion through inhibition of FAK/Src/Lyn activation and beta-catenin expression and increases susceptibility to chemotherapeutic agents. Int J Oncol 2015;46(1):185–94.Ketola A, et al. Oncolytic Semliki forest virus vector as a novel candidate against unresectable osteosarcoma. Cancer Res 2008;68(20):8342–50.Sun W, et al. G3-C12 peptide reverses galectin-3 from Foe to friend for active targeting cancer treatment. Mol Pharm 2015;12(11):4124–36.Sun W, et al. Two birds, one stone: dual targeting of the cancer cell surface and subcellular mitochondria by the galectin-3-binding peptide G3-C12. Acta Pharmacol Sin 2017;38(6):806–822.Ethics ApprovalAnimals were maintained under standard conditions, and all procedures were approved by the Institutional Ethical Committee (CEEA) in accordance with the guidelines of the University of Navarra, approval number 044-21.
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Chen, Zhenghang, Yawen Kang, Zhongxiao Sun, Feng Wu, and Qian Zhang. "Extraction of Photovoltaic Plants Using Machine Learning Methods: A Case Study of the Pilot Energy City of Golmud, China." Remote Sensing 14, no. 11 (June 3, 2022): 2697. http://dx.doi.org/10.3390/rs14112697.
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Solar energy is an abundant, clean, and renewable source that can mitigate global climate change, environmental pollution, and energy shortage. However, comprehensive datasets and efficient identification models for the spatial distribution of photovoltaic (PV) plants locally and globally over time remain limited. In the present study, a model that combines original spectral features, PV extraction indexes, and terrain features for the identification of PV plants is established based on the pilot energy city Golmud in China, which covers 71,298.7 km2 and has the highest density of PV plants in the world. High-performance machine learning algorithms were integrated with PV plant extraction models, and performances of the XGBoost, random forest (RF), and support vector machine (SVM) algorithms were compared. According to results from the investigations, the XGBoost produced the highest accuracy (OA = 99.65%, F1score = 0.9631) using Landsat 8 OLI imagery. The total area occupied by PV plants in Golmud City in 2020 was 10,715.85 ha based on the optimum model. The model also revealed that the area covered by the PV plant park in the east of Golmud City increased by approximately 10% from 2018 (5344.2 ha) to 2020 (5879.34 ha). The proposed approach in this study is one of the first attempts to identify time-series large-scale PV plants based on a pixel-based machine learning algorithm with medium-resolution free images in an efficient way. The study also confirmed the effectiveness of combining original spectral features, PV extraction indexes, and terrain features for the identification of PV plants. It will shed light on larger- and longer-scale identification of PV plants around the world and the evaluation of the associated dynamics of PV plants.
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Kim, Seunghyun, Joongsik Kim, Moonsoo Ra, and Whoi-Yul Kim. "Vacant Parking Slot Recognition Method for Practical Autonomous Valet Parking System Using around View Image." Symmetry 12, no. 10 (October 19, 2020): 1725. http://dx.doi.org/10.3390/sym12101725.
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The parking assist system (PAS) provides information of parking slots around the vehicle. As the demand for an autonomous system is increasing, intelligent PAS has been developed to park the vehicle without the driver’s intervention. To locate parking slots, most existing methods detect slot markings on the ground using an around-view monitoring (AVM) image. There are many types of parking slots of different shapes in the real world. Due to this fact, these methods either limit their target types or use predefined slot information of different types to cover the types. However, the approach using predefined slot information cannot handle more complex cases where the slot markings are connected to other line markings and the angle between slot marking is slightly different from the predefined settings. To overcome this problem, we propose a method to detect parking slots of various shapes without predefined type information. The proposed method is the first to introduce a free junction type feature to represent the structure of parking slot junction. Since the parking slot has a modular or repeated junction pattern at both sides, junction pair consisting of one parking slot can be detected using the free junction type feature. In this process, the geometrically symmetric characteristic of the junction pair is crucial to find each junction pair. The entrance of parking slot is reconstructed according to the structure of junction pair. Then, the vacancy of the parking slot is determined by a support vector machine. The Kalman tracker is applied for each detected parking slot to ensure stability of the detection in consecutive frames. We evaluate the performance of the proposed method by using manually collected datasets, captured in different parking environments. The experimental results show that the proposed method successfully detects various types of parking slots without predefined slot type information in different environments.
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Korovin, Aleksandr V., and Ivan V. Aleksandrov. "COORDINATE TRANSFORMATIONS OF THREE-PHASE VARIABLES USING QUATERNIONS." Vestnik Chuvashskogo universiteta, no. 1 (March 30, 2022): 65–72. http://dx.doi.org/10.47026/1810-1909-2022-1-65-72.
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Among the variety of modern approaches to the mathematical description of the power quality indicators during the processes of transmission, distribution, conversion and calculation of the ac electric power, the representation of three-phase models in the form of a purely imaginary quaternion located in a separate subspace of the four-dimensional hypercomplex space allows, in relation to the generally accepted method of analyzing linear circuits, for example, symmetrical components with the selection of a direct, reverse and zero phase sequence for the fundamental harmonic, to take into a more complete account the features of energy consumption, especially in the presence of distortion in the modified forms of harmonic signals. In addition, the division of the quaternion into scalar (real) and partial (imaginary) makes it possible to significantly simplify the subsequent analytical processing of synthesis of a power converters control signals for active filtering and power supply of autonomous loads of an arbitrary type, including a single-phase configuration, by extracting from its composition individual components responsible for both the amplitude-phase asymmetry and the nonlinearity of the characteristics.
The main algorithmic principles of organizing control structures as part of three-phase systems of various functional purposes, as a rule, are based on the conversion of reference signals and current values of measured currents and voltages into state coordinates obtained by rotating the three-dimensional space plane by a given angle. At the same time, the calculated ratios for the numerical determination of the initial variables transformed by rotation in the quaternion basis are a function of only four kinematic parameters, which, other things being equal, leads to a simplification of the control law in relation to the traditional vector-matrix approach using nine direction cosines with six connection equations. In this regard, this paper is devoted to the applied problems of implementing linear transformations by E. Clarke and R.H. Park in terms of four-dimensional hypercomplex numbers, in compliance with the additional requirement of the invariance of scalar quantities after the transition.
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Bidnichenko, Olena. "CURRENT TRENDS IN THE DEVELOPMENT OF AUTOMATED COMPUTER MODELING SYSTEMS." Management of Development of Complex Systems, no. 49 (April 11, 2022): 59–65. http://dx.doi.org/10.32347/2412-9933.2022.49.59-65.
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This work is devoted to the study of the features of computer modeling systems, their analysis and development. The classification of modeling systems is given, the content and possibilities of existing systems are analyzed. Particular attention is paid to the division of all systems into groups according to the logic of construction and functionality. The advantages and disadvantages of the systems of each group are noted. Basic (light) level systems that work in vector space have a closed mathematical model. It is emphasized that the modeling process depends on the considerations of the designer and is reduced to the iterative process of creating a drawing. Features of systems are given and variants of 2-D and 3-D models of real technical units and mechanisms in AutoCAD and Compass-graph systems are given. The systems of the middle group, which are created for 3-D modeling of products and calculations, are considered. Working in such programs, the developer uses electronic copies of real models, which allows you to use the modeling logic of assembly objects. The most complex are the higher level systems used for complex products, which include elements of complex shape and dense layout of a large number of assembly units. The study identified software packages Unigraphics (NX), ProEngineer, Catia, Creo. Complex systems have an open mathematical model of construction and allow end-to-end analysis of the model according to certain parameters. The paper also draws attention to another approach to modeling. So-called PLM and BIM technologies greatly facilitate the process of modeling objects, using a system of well-organized computer models instead of a separate set of drawings. The rapid development of cloud CAD operating in a virtual computing environment is noted. From the made analysis the prospects of further qualitative development of automated systems by parallel development of equipment park together with modeling technology are resulted.
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Awuah, Kwame T., Paul Aplin, Christopher G. Marston, Ian Powell, and Izak P. J. Smit. "Probabilistic Mapping and Spatial Pattern Analysis of Grazing Lawns in Southern African Savannahs Using WorldView-3 Imagery and Machine Learning Techniques." Remote Sensing 12, no. 20 (October 15, 2020): 3357. http://dx.doi.org/10.3390/rs12203357.
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Savannah grazing lawns are a key food resource for large herbivores such as blue wildebeest (Connochaetes taurinus), hippopotamus (Hippopotamus amphibius) and white rhino (Ceratotherium simum), and impact herbivore densities, movement and recruitment rates. They also exert a strong influence on fire behaviour including frequency, intensity and spread. Thus, variation in grazing lawn cover can have a profound impact on broader savannah ecosystem dynamics. However, knowledge of their present cover and distribution is limited. Importantly, we lack a robust, broad-scale approach for detecting and monitoring grazing lawns, which is critical to enhancing understanding of the ecology of these vital grassland systems. We selected two sites in the Lower Sabie and Satara regions of Kruger National Park, South Africa with mesic and semiarid conditions, respectively. Using spectral and texture features derived from WorldView-3 imagery, we (i) parameterised and assessed the quality of Random Forest (RF), Support Vector Machines (SVM), Classification and Regression Trees (CART) and Multilayer Perceptron (MLP) models for general discrimination of plant functional types (PFTs) within a sub-area of the Lower Sabie landscape, and (ii) compared model performance for probabilistic mapping of grazing lawns in the broader Lower Sabie and Satara landscapes. Further, we used spatial metrics to analyse spatial patterns in grazing lawn distribution in both landscapes along a gradient of distance from waterbodies. All machine learning models achieved high F-scores (F1) and overall accuracy (OA) scores in general savannah PFTs classification, with RF (F1 = 95.73±0.004%, OA = 94.16±0.004%), SVM (F1 = 95.64±0.002%, OA = 94.02±0.002%) and MLP (F1 = 95.71±0.003%, OA = 94.27±0.003%) forming a cluster of the better performing models and marginally outperforming CART (F1 = 92.74±0.006%, OA = 90.93±0.003%). Grazing lawn detection accuracy followed a similar trend within the Lower Sabie landscape, with RF, SVM, MLP and CART achieving F-scores of 0.89, 0.93, 0.94 and 0.81, respectively. Transferring models to the Satara landscape however resulted in relatively lower but high grazing lawn detection accuracies across models (RF = 0.87, SVM = 0.88, MLP = 0.85 and CART = 0.75). Results from spatial pattern analysis revealed a relatively higher proportion of grazing lawn cover under semiarid savannah conditions (Satara) compared to the mesic savannah landscape (Lower Sabie). Additionally, the results show strong negative correlation between grazing lawn spatial structure (fractional cover, patch size and connectivity) and distance from waterbodies, with larger and contiguous grazing lawn patches occurring in close proximity to waterbodies in both landscapes. The proposed machine learning approach provides a novel and robust workflow for accurate and consistent landscape-scale monitoring of grazing lawns, while our findings and research outputs provide timely information critical for understanding habitat heterogeneity in southern African savannahs.
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GULIYEVA, AYGUN. "Methodological approaches to measuring quality of life." Brazilian Journal of Political Economy 42, no. 2 (April 2022): 364–77. http://dx.doi.org/10.1590/0101-31572022-3256.
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ABSTRACT The ultimate goal of the present work lay in creating a vector methodology for measuring QoL. Application of an integrated approach to the results of the classification analysis and SWOT analysis enabled elaborating a vector methodology of a recommendatory type aimed at improving QoL measurement approaches. It was established that this methodology should include four major updates taking into account the challenges of tomorrow. The study results may be of interest to public authorities responsible for taking measures directed at raising the country’s international ranking as well as be used for reducing contradictions on the part of QoL measuring procedures.
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Dahiya, Anchal, and Pooja Mittal. "Evaluation of Data Mining Techniques and Its Fusion with IoT Enabled Smart Technologies for Effective Prediction of Available Parking Space." International journal of electrical and computer engineering systems 12, no. 4 (November 26, 2021): 187–97. http://dx.doi.org/10.32985/ijeces.12.4.2.
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After experiencing the hard times of pandemic situations we learned that if we could have a smart system that can help us in automatic parking of the vehicles then it could be a great help to society. This idea motivated us to carry out this current work. Though, nowadays, in almost every application domain, IoT techniques are the buzzword. IoT techniques can also be used to achieve efficacy in predicting free available parking space in advance. But the biggest challenge with IoT techniques is that they generate numerous data, which makes its analysis intangible. It was realized that if IoT techniques can be fused with outperforming data mining techniques, more efficient predictions can be performed. Thus, for this purpose, the main objective of our paper is to firstly, select the most appropriate data mining technique, based on performance evaluation, and then to perform prediction of available parking space in advance by fusing it with IoT techniques. Due to the busy schedule, the drivers need to get information about free parking spaces in advance by using smart phones. With the help of this information, it will be easy for the drivers to park their vehicle in the exact location without wasting their precious time and will maintain social distancing in crowded areas too. Data mining techniques can play an important role in the prediction of available parking space, by extracting only relevant and important information when applied to the given dataset. For this purpose, a comparative analysis of five data mining techniques such as the Support Vector Machine, K- Nearest approach, Decision Tree, Random Forest, and Ensemble learning approaches are applied on PK lot data set by using Python language. For calculation of result anaconda (spyder) is used as a supportive tool. The main outcome of the paper is to find the technique that will give better results for the prediction of the available space and if we fused data mining techniques with IoT technologies results are improvised. Evaluation parameters that are used for finding the best technique are precision, recall, accuracy, and F1-Score. For numerical calculation of the results, the k-fold cross-validation method is used. As the empirical results are calculated using the Pk lot dataset, the decision tree outperformed the best among all the techniques that are selected for analysis.
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Sánchez-López, Iván, Mónica Bonilla-del-Río, and Ismar Oliveira Soares. "Digital creativity to transform learning: Empowerment from a com-educational approach." Comunicar 29, no. 69 (October 1, 2021): 113–23. http://dx.doi.org/10.3916/c69-2021-09.
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Daily media use by an entire generation shows the distance that exists between the reality experienced by young people and the institutions responsible for their education. Formal education is still closely linked to the passive role of literary receivers, ignoring the potential of connected communication for student empowerment. At the same time, there is a growing interest in education from the professional media field. We have called this line of force the com-educational vector. In this study, we aim to describe the potential of a com-educational perspective to favor the empowerment of young people. The implemented methodology combines a chained articulation involving the analysis of multimodal discourse of com-educational platforms with interviews with privileged observers. The results show that the implementation of digital creation can be used for the construction of identity, interaction and socialization of students through emotion, empathy and the capacity for transformation. It enables the establishment of nodes between concepts, relational understanding, meaningful reconstruction and appropriation. It is concluded that, under this proposal, formal education institutions could move from a reactive model to a prospective model, revising the codes of emission and reception, and proposing meanings from creative action and feedback with the community. Los usos mediáticos cotidianos de toda una generación evidencian la distancia que existe entre la realidad que vive la juventud y las instituciones responsables de su formación. La educación formal sigue estrechamente vinculada al rol pasivo de los receptores literarios, obviándose el potencial de la comunicación conectada y la narrativa digital para el empoderamiento del alumnado. Al mismo tiempo, se está produciendo un interés creciente desde el ámbito mediático profesional por la educación. A esta línea de fuerza la hemos denominado vector com-educativo. En esta investigación, tenemos como objetivo describir potencialidades para favorecer el empoderamiento de los jóvenes desde una perspectiva com-educativa. La metodología implementada combina, en una articulación encadenada, el análisis del discurso multimodal de plataformas de carácter com-educativo con entrevistas a observadores privilegiados. En los resultados se explicita que la implementación de la creación digital se puede emplear para la construcción de la identidad, la interacción y la sociabilización del alumnado a través de la emoción, la empatía y la capacidad de transformación. Permite establecer nodos entre conceptos, la comprensión relacional, la reconstrucción significativa y su apropiación. Se concluye que, bajo esta propuesta, las instituciones de educación formal podrían transitar de un modelo reactivo a un modelo prospectivo, revisando los códigos de emisión y recepción, y proponiendo significados desde la acción creativa y la retroalimentación con la comunidad.
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Théry, Neli de Mello ThéryNeli de Mello, and Patrick Caron. "CONTROVERSIES AND TRANSITIONS FOR SUSTAINABLE DEVELOPMENT." Mercator 19, no. 2020 (December 15, 2020): 1–12. http://dx.doi.org/10.4215/rm2020.e19027.
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Science does not progress without controversy as well the societies. In this article, this approach is privileged, aiming to analyze whether they can hinder or speed up the agricultural and food, environmental and sanitary transitions necessary to achieve the Sustainable Development Goals (SDGs). It begins with an alert to the past development model and the limits of the planet, highlighting some themes and forms of action chosen by international institutions and / or scientist’s networks. Then, we selected some controversies and their arguments, related to environmental issues and the evolution of food systems. In the subsequent item, its actors and five sub controversies sought to highlight the difficulties for the transition to circular systems, considered as a vector of sustainability. It is concluded that controversies can block advances for transitions, being essential the design of methods, criteria and indicators for a better understanding of oppositions, as well as the need to include both themes and new approaches in research agendas.
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Carmona Cortes, Omar Andres, Leticia De Fátima Corrêa Costa, and Jo˜ao Pedro Augusto Costa. "Uma Nova Meta-heurística Adaptativa Baseada em Vetor de Avaliações para Otimização de Portfólios de Investimentos." Inteligencia Artificial 22, no. 64 (December 9, 2019): 85–101. http://dx.doi.org/10.4114/intartif.vol22iss64pp85-101.
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This article describes a new adaptive metaheuristic based on a vector evaluated approach for solving multiobjective problems. We called our proposed algorithm Vector Evaluated Meta-Heuristic. Its main idea is to evolve two populations independently, exchanging information between them, i.e., the first population evolves according to the best individual of the second population and vice-versa. The choice of which algorithm will be executed on each generation is carried out stochastically among three evolutionary algorithms well known in the literature: PSO, DE, ABC. In order to evaluate the results, we used an established metric in multiobjective evolutionary algorithms called hypervolume. Tests have shown that the adaptive metaheuristic reaches the best hyper-volumes in three of ZDT benchmarks functions and, also, in two portfolios of a real-world problem called portfolio investment optimization. The results show that our algorithm improved the Pareto curve when compared to the hypervolumes of each heuristic separately.
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Pereira, Marcos Vinicius Lopes, Leonardo Carneiro De Araújo, and Robert Aldo Iquiapaza. "Cointegração e previsibilidade de abordagens VECM para o Ibovespa." Brazilian Review of Finance 18, no. 2 (July 12, 2020): 82. http://dx.doi.org/10.12660/rbfin.v18n2.2020.79162.
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<p>The present research compares multivariate models applied to the IBovespa time series analysis. Macroeconomic variables, commodities and market indices are regressors suggested by the literature. The chosen approach uses a vector error correction model (VECM) alongside unit root and cointegration tests, robust under heteroskedasticity. The impact of national and international economic instability was controlled. To accomplish this, recessive cycles, in Brazil or in the United States, and the Brazilian electoral period were taken into account. In general, the evaluated models failed to meet the estimation’s assumptions, have low explanatory power and do not present significant relationship between IBOVESPA and dependent variables. However, evidence indicates that long-term relationships could exist, although this may not imply accuracy<br />in short-term predictions.</p>
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Sánchez-López, Iván, Amor Pérez-Rodríguez, and Manuel Fandos-Igado. "Com-educational Platforms: Creativity and Community for Learning." Journal of New Approaches in Educational Research 8, no. 2 (July 15, 2019): 214. http://dx.doi.org/10.7821/naer.2019.7.437.
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Education is at a time of redefinition and transformation, in line with an era characterized by considerable technological development and profound social changes. One would expect it to be accompanied by a media context in which narrative models are transformed by the impact of digitalization, affecting student-teacher interactions. However, it has been observed that the media usage of an entire generation emphasizes the gap between formal education and young people's everyday digital life. Within this framework, and at the international level, a series of innovative pedagogical proposals have emerged, which approach education from the field of communication: Minecraft Education, NFB Education, Educ'Arte, Scratch and 7 de Cinema. We have called them com-educational platforms, because of their investment in the education-communication vector, based on an educommunicative idea. The proposed study implements a multimodal discourse analysis (MDA) to gain an in-depth knowledge of its characteristics. Beyond their individual idiosyncrasies, our analysis reveals a common central feature: the placement of community-creativity combination as the core phenomenon for learning.
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Casas, Arturo. "El eje local-mundial como reto para la Historia literaria." Tropelías: Revista de Teoría de la Literatura y Literatura Comparada, no. 15-17 (February 26, 2011): 43. http://dx.doi.org/10.26754/ojs_tropelias/tropelias.200415-17503.
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En el marco general de la crisis de la Historia y con atención a las nuevas coordenadas derivadas de la mundialización y el multiculturalismo, este artículo analiza las dimensiones local, regional, nacional y supranacional/mundial de la Historia literaria y explora la posibilidad de que su vertiente temporal-cronológica ceda parte de su protagonismo a un vector espacial-territorial, propiciando con ello una aproximación a la Semiótica de la cultura, a la Geografía cultural y a otras disciplinas. Se observan además las correlaciones establecidas entre las dimensiones citadas en la práctica de varios modelos actualmente vigentes en la Historia comparada de las culturas y las literaturas –los correspondientes a Dionýz Ďurišin y a Mario J. Valdés y los vinculados con las teorías empírico-sistémicas y los Subaltern Studies–, con atención particular a los niveles heurístico, metodológico, discursivo y metatextual, así como al tipo de recepción previsto en cada caso. Within the general framework of the crisis of History and with attention to the new coordinates derived from globalization and multiculturalism, this article analyzes the local, regional, national and supranational/worldwide dimensions of Literary History and explores the possibility of its temporal-chronological aspect granting part of its protagonism to a spatial-territorial vector, thereby favoring an approach to Cultural Semiotics, Cultural Geography, and other disciplines. The correlations established between these aforementioned dimensions in the practice of several of the most current models in Comparative Cultural and Literary History are also observed –those corresponding to Dionýz Ďurišin and Mario J. Valdés and the connections to empirical-systemic theories and Subaltern Studies–, with particular attention to heuristic, methodological, discursive, and metatextual levels, as well as the type of reception foreseen in each case.
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Nandika, Muhammad Rizki, Azura Ulfa, Andi Ibrahim, and Anang Dwi Purwanto. "Assessing the Shallow Water Habitat Mapping Extracted from High-Resolution Satellite Image with Multi Classification Algorithms." Geomatics and Environmental Engineering 17, no. 2 (January 30, 2023): 69–87. http://dx.doi.org/10.7494/geom.2023.17.2.69.
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Remote sensing technology is reliable in identifying the distribution of seabed cover yet there are still challenges in retrieving the data collection of shallow water habitats than with other objects on land. Classification algorithms based on remote sensing technology have been developed for application to map benthic habitats, such as Maximum Likelihood, Minimum Distance, and Support Vector Machine. This study focuses on examining those three classification algorithms to retrieve information on the benthic habitat in Pari Island, Jakarta using visual interpretation data for classification, and data field measurements for accuracy testing. This study used five classes of benthic objects, namely sand, sand-seagrass, rubble, seagrass, and coral. The results show how the proposed approach in this study provides an overall good classification of marine habitat with an accuracy produced 63.89–81.95%. The Support Vector Machine algorithm produced the highest accuracy rate of about 81.95%. The Support Vector Machine algorithm at a very high spatial resolution is considered to be capable of identifying, monitoring, and performing the rapid assessment of benthic habitat objects.
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BORODINA, O. A. "CLUSTER MODEL OF NEOINDUSTRIAL MODERNIZATION OF REGIONAL ECONOMY: PREREQUISITES, FACTORS, CURRENT EXAMPLES." Economic innovations 23, no. 3(80) (August 20, 2021): 50–63. http://dx.doi.org/10.31520/ei.2021.23.3(80).50-63.
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Topicality. The urgent need for modernization and neo-industrialization of industry, given the projected materialist nature of the sixth technological mode, is unconditional. After all, the fifth technological way, which ushered in the era of intangible post-industrial production (innovations in the field of microelectronics, information and bio-technologies, space exploration) (soft skills IT-technology), is coming to an end in developed countries. smart techology) is likely to focus on the synthesis of the use of tangible and intangible resources, the widespread use of nano- and biotechnologies, and those still in the process of discovery.One of the first priorities of the global development of the neo-industrial stage is based on the study of best practices, must adapt to modern Ukrainian realities at both national and regional levels, which determines the relevance of the study..Aim and tasks. The aim of the article is to analyze and determine the preconditions and factors of cluster formation in modern conditions of neo-industrial modernization of the economy, to consider the example of self-organized scientific and educational cluster of relocated free economic zones and provide effective recommendations for certain regional systems.Research results. The idea of "smart specialization" (RIS3, Research and innovation strategies for smart-specialization, S3) has a scientific basis, has proven effective in overcoming the effects of the crisis of the global financial system, and, as a result, quickly gained popularity among European politicians. In addition, smart specialization and cluster model of economic development of the region, in the development of strategic documents, provided by regulations at both national and regional levels. It is stated that the principles of modernization of industrial development, digitalization and stimulation of innovation and investment activities should become a guide for old industrial regions of Ukraine in search of relevant and viable smart priorities for cluster development in the direction of European integration and Euro partnership. Comparative analysis of the criteria of technological development of social systems allowed to present the available evidence of belonging of the current stage of socio-economic development of Donetsk and Dnieper regions to the first phase of the neo-industrial stage of development. It is determined that for Ukraine the way of innovative transformation of the economy is a necessary way to reduce the significant gap in economic indicators with other countries, because it affects the inflow of investment, job creation, small and medium business development, potential work in global joint European and global projects. Clusters are recognized as one of the mechanisms for implementing priority areas of innovation to ensure the development of territorial communities in the region. It is proved that for Ukraine in the post-war period, the most convenient way to attract a lot of foreign investment are industrial parks, as the next link in the chain of integration into the European and world industrial ecosystems after the science park. In order to analyze the formation of scientific and educational space, the classification of relocated higher education institutions by their location. The effect of self-organization of the scientific and educational cluster for Donetsk and Prydiniprovsk regions is demonstrated.Conclusion. The article proves the need to provide a comprehensive approach to the formation of the vector of innovative development, which has as components scientific and industrial parks and aimed at integration into European and world economic and social systems. In order to continue the ongoing reforms, effective formation and operation of scientific and educational clusters, implementation in the national scientific and educational space of the best achievements and practices abroad, proposals for the implementation of a number of measures ranked by level of implementation (national, regional, local).
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Rodrigues, Luiz de Souza, and Danilo Roberto Pereira. "APRENDIZADO DE MÁQUINA APLICADO EM IMAGEM NDVI PARA PREVISÃO DA PRODUTIVIDADE DA CANA-DE-AÇÚCAR." COLLOQUIUM EXACTARUM 13, no. 4 (December 20, 2021): 82–98. http://dx.doi.org/10.5747/ce.2021.v13.n4.e378.
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This article presents an approach through models based on ML (Machine Learning) applied to NDVI (Normalized Difference Vegetation Index) images to estimate productivity in the sugarcane crop. The use of human techniques based on cognitive experiences is predominant to anticipate productivity. The images used were provided by the NDVI Sentinel-2 satellite, since the datasets were obtained from two georeferenced points, two plots and applied to the images for extraction and processing. Two predictive algorithms are used for the models: (i) CNN (Convolution Neural Network), (ii) KNN (K-Nearest Neighbors), (iii) RF (Random Forest), (iv) SVM (Support Vector Machie) , (v) AdaBoost (Adaptive Boost). The RF algorithm was presented or more efficient, so that the results for the DP (Standard Deviation) and the formula for the MSE (Mean Square Error) obtained 30.71 tons (t) and the MAE (Mean Absolute Error) obtained 3.73(t). Regarding the estimates, the DP formula for the MSE obtains 34.71 (t) and the MAE of 3.97 (t). The EM (Mean Error) for the estimates was -8.80% and the RF algorithm was 0.012%. The results will show consistency for the productivity estimates in the sugarcane crop.
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Husada, Hendry Cipta, and Adi Suryaputra Paramita. "Analisis Sentimen Pada Maskapai Penerbangan di Platform Twitter Menggunakan Algoritma Support Vector Machine (SVM)." Teknika 10, no. 1 (February 2, 2021): 18–26. http://dx.doi.org/10.34148/teknika.v10i1.311.
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Perkembangan teknologi saat ini telah memberikan kemudahan bagi banyak orang dalam mendapatkan dan menyebarkan informasi di berbagai social media platform. Twitter merupakan salah satu media yang kerap digunakan untuk menyampaikan opini sebagai bentuk reaksi seseorang atas suatu hal. Opini yang terdapat di Twitter dapat digunakan perusahaan maskapai penerbangan sebagai parameter kunci untuk mengetahui tingkat kepuasan publik sekaligus bahan evaluasi bagi perusahaan. Berdasarkan hal tersebut, diperlukan sebuah metode yang dapat secara otomatis melakukan klasifikasi opini ke dalam kategori positif, negatif, atau netral melalui proses analisis sentimen. Proses analisis sentimen dilakukan dengan proses data preprocessing, pembobotan kata menggunakan metode TF-IDF, penerapan algoritma, dan pembahasan atas hasil klasifikasi. Klasifikasi opini dilakukan dengan machine learning approach memanfaatkan algoritma multi-class Support Vector Machine (SVM). Data yang digunakan dalam penelitian ini adalah opini dalam bahasa Inggris dari para pengguna Twitter terhadap maskapai penerbangan. Berdasarkan pengujian yang telah dilakukan, hasil klasifikasi terbaik diperoleh menggunakan SVM kernel RBF pada nilai parameter 𝐶(complexity) = 10 dan 𝛾(gamma) = 1, dengan nilai accuracy sebesar 84,37% dan 80,41% ketika menggunakan 10-fold cross validation.
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Acuña Medina, Doris Isabel, Piedad Felisinda Gañán Rojo, and Syra Bibiana Arango Alzate. "Etnoturismo: una aproximación a las oportunidades y amenazas que implica para las culturas indígenas." Cuadernos de Turismo, no. 43 (May 6, 2019): 17–38. http://dx.doi.org/10.6018/turismo.43.01.
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Este estudio, primera aproximación de su tipo realizada a partir del análisis bibliográfico de información científica especializada en la temática, examina potenciales oportunidades y amenazas que enfrenta el etnoturismo a nivel mundial, que deben ser consideradas cuyo se desee promover actividades de transferencia, apropiación de tecnología o innovación, porque se constituirán bien sea en vectores de cambio o en elementos a superar. Debates del tema serían importantes para que micro y pequeñas organizaciones étnicas sean competitivas logryo cambios del sistema con equidad y justicia social. This study, the first approach of its kind based on the bibliographic analysis of specialized scientific information on the subject, examines potential opportunities or threats facing ethnotourism worldwide, which should be considered when promoting transfer activities, technology appropriation or innovation, because they will be constituted either in vectors of change or in elements to overcome. Debates on the theme would be important for micro y small ethnic organizations to be competitive, achieving systemic changes with equity y social justice.
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Harahap, Lukman Adlin, Ridzuan Ikaram Fajri, Mohammad Fadly Syahputra, Romi Fadillah Rahmat, and Erna Budhiarti Nababan. "Identifikasi Penyakit Daun Tanaman Kelapa Sawit dengan Teknologi Image Processing Menggunakan Aplikasi Support Vector Machine." Talenta Conference Series: Agricultural and Natural Resources (ANR) 1, no. 1 (October 16, 2018): 53–59. http://dx.doi.org/10.32734/anr.v1i1.96.
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Pengelolaan perkebunan kelapa sawit sering mengalami kendala, antara lain masalah organisme pengganggu tumbuhan (OPT) terutama masalah penyakit. Oleh karena itu, dibuatlah pendekatan untuk mengenali penyakit pada daun kelapa sawit agar dapat membantu kinerja dari para petani kelapa sawit dalam menentukan jenis penyakit pada daun sehingga mendapatkan hasil yang lebih maksimal. Deteksi tepi adalah perubahan nilai intensitas derajat keabuan yang mendadak (besar) dalam jarak yang singkat. Sobel operator digunakan untuk pengidentifikasikan pola wajah, khususnya terdapat di dalam algoritma deteksi tepi. Support Vector Machine (SVM) digunakan sebagai metode klasifikasi. Oleh karena itu, dalam penelitian ini penulis akan menerapkan metode deteksi tepi dengan menggabungkan teknik algoritma Sobel Operator untuk menghilangkan derau dan metode Support Vector Machine sebagai pengklasifikasian data penyakit pada daun kelapa sawit.
The management of oil palm plantations often experiences obstacles, including problems with plant pest organisms (OPT), especially disease problems. Therefore, an approach was made to encourage the disease in the leaves of oil palm so that it can help the performance of oil palm farmers in determining the type of disease in the leaves so as to get maximum results. Edge detection is a change in the value of the sudden intensity of the degree of gray (large) in a short distance. Sobel operators are used to identifying face patterns, especially those found in edge detection algorithms. Support Vector Machine (SVM) is used as a classification method. Therefore in this study, the author will apply the edge detection method by combining the Sobel Operator algorithm technique to eliminate noise and the Support Vector Machine method as a classification of disease data on palm oil leaves.
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Purves, R. S., J. S. Barton, W. A. Mackaness, and D. E. Sugden. "The development of a rule-based spatial model of wind transport and deposition of snow." Annals of Glaciology 26 (1998): 197–202. http://dx.doi.org/10.3189/1998aog26-1-197-202.
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This paper describes the early stages in the development and testing of a spatio-temporal rule-based model of snow transport by wind over complex terrain. The model uses a cell-based approach and takes into account a range of meteorological, snow-pack and topographic variables. Simple rules are used to determine movement of material from cell-to-cell within the model.A geographic information system is utilized in modelling wind vectors and the influence of topography upon those vectors, and creating the resulting pattern of snow accumulation at a resolution of 50 m. These patterns of accumulation have been compared with empirical work in the field and, although field data were limited, a good qualitative correlation has been found; for example, modelled accumulations correlate with known areas of accumulation such as gullies and hollows.
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Purves, R. S., J. S. Barton, W. A. Mackaness, and D. E. Sugden. "The development of a rule-based spatial model of wind transport and deposition of snow." Annals of Glaciology 26 (1998): 197–202. http://dx.doi.org/10.1017/s0260305500014804.
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This paper describes the early stages in the development and testing of a spatio-temporal rule-based model of snow transport by wind over complex terrain. The model uses a cell-based approach and takes into account a range of meteorological, snow-pack and topographic variables. Simple rules are used to determine movement of material from cell-to-cell within the model.A geographic information system is utilized in modelling wind vectors and the influence of topography upon those vectors, and creating the resulting pattern of snow accumulation at a resolution of 50 m. These patterns of accumulation have been compared with empirical work in the field and, although field data were limited, a good qualitative correlation has been found; for example, modelled accumulations correlate with known areas of accumulation such as gullies and hollows.
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Correa, Daniel Veras, Ana Paula Marques Ramos, Lucas Prado Osco, and Lúcio André de Castro Jorge. "APRENDIZAGEM DE MÁQUINA PARA IDENTIFICAÇÃO DE PLANTAS DE SOJA SOB ATAQUE DE INSETOS USANDO DADOS HIPERESPECTRAIS." COLLOQUIUM EXACTARUM 14, no. 1 (January 5, 2023): 146–53. http://dx.doi.org/10.5747/ce.2022.v14.e393.
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The integration between the areas of remote sensing and machine learning has allowed an advance in the way of mapping agricultural fields and monitoring crops. This work investigates the ability of machine learning algorithms to classify soybean plants under insect attack, using reflectance spectroscopy measurements collected at the leaf level. To this end, tests were developed with different algorithms using a set of 991 spectral curves referring to healthy soybean plants under attack by pests, collected in eight consecutive days. These curves were measured by the EMBRAPA team, using a portable spectroradiometer, which records in the range of 350 to 2500 nm. Such curves were, initially, pre-processed to remove the regions of atmospheric absorption by water vapor, and then subdivided into a set of training, validation and testing of the machine learning algorithms. The Google Collabs interpreter was used and the algorithms were written in Python language, using libraries such as Skit Sklearn. Among the algorithms used, there are Random Forest, Decision Tree, Support Vector Machine, Logistic Regression and Extra-Tree. The Extra-tree has better performance (F1-score = 80.40%; precision = 81%; recall = 80%) in the proposed task. It is concluded that it is possible to process reflectance spectroscopy measurements with machine learning algorithms to monitor insect attack on soybean plants. It is recommended that the applied approach be tested in other cultures.
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Pola Jiménez, Eddy Alberto, MAXIMO LOPEZ SANCHEZ, JUAN GABRIEL GONZALEZ SEMA, NIMROD GONZALEZ FRANCO, DANTE MUJICA VARGAS, and GUILLERMO SANTAMARIA BONFIL. "COMPARATIVE ANALYSIS OF VARIABLES USED IN ZIGBEE DISTRIBUTED NETWORKS FOR INTRUSION DETECTION ON END DEVICES IN AN UNMANNED AUTONOMOUS VEHICLES NETWORK." DYNA 97, no. 6 (November 1, 2022): 606–12. http://dx.doi.org/10.6036/10620.
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Cyber attacks have become more common and sophisticated in the new age of technology. Intrusion detection systems were designed to detect attacks while they are being carried out and many applications have been deployed in IoT, showing great effectiveness to identify anomalies. However, almost all of them are built under a conventional scheme where network traffic is generated by services based on a client-server architecture. Pure Zigbee networks are distinguished by the connection between end devices and do not generate this kind of network traffic because Zigbee protocol stack is limited. Because of this, many of the variables presented in related works to train machine learning algorithms are not present in such a network. This would generate effects such as data theft, identity theft, permanent loss of information and even manipulation of devices, something significantly serious in the area of unmanned vehicles. The purpose of this article is to expose variables obtained from pure Zigbee in a distributed environment can be used to identify intrusions in a simulated test case such as the connection between unmanned vehicles. In this way, a new identification approach is introduced, within end devices are focused instead network traffic only to identify anomalies. It is intended to demonstrate that CPU and RAM variables analysis directly from end devices allow an effective identification in packet storm denial of service attacks and that they would be a considerable option to avoid end effects. Keywords: Intrusion Detection System, Zigbee Networks, Unmanned Aerial Vehicles, Denial of Service, Support Vector Machines.
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Coca-Castro, Alejandro, Maycol A. Zaraza-Aguilera, Yilsey T. Benavides-Miranda, Yeimy M. Montilla-Montilla, Heidy B. Posada-Fandiño, Angie L. Avendaño-Gomez, Hernando A. Hernández-Hamon, Sonia C. Garzón-Martinez, and Carlos A. Franco-Prieto. "Evaluación de algoritmos de clasificación en la plataforma Google Earth Engine para la identificación y detección de cambios de construcciones rurales y periurbanas a partir de imágenes de alta resolución." Revista de Teledetección, no. 58 (July 21, 2021): 71. http://dx.doi.org/10.4995/raet.2021.15026.
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<p>Building change detection based on remote sensing imagery is a key task for land management and planning e.g., detection of illegal settlements, updating land records and disaster response. Under the post- classification comparison approach, this research aimed to evaluate the feasibility of several classification algorithms to identify and capture buildings and their change between two time steps using very-high resolution images (<1 m/pixel) across rural areas and urban/rural perimeter boundaries. Through an App implemented on the Google Earth Engine (GEE) platform, we selected two study areas in Colombia with different images and input data. In total, eight traditional classification algorithms, three unsupervised (K-means, X-Means y Cascade K-Means) and five supervised (Random Forest, Support Vector Machine, Naive Bayes, GMO maximum Entropy and Minimum distance) available at GEE were trained. Additionally, a deep neural network named Feature Pyramid Networks (FPN) was added and trained using a pre-trained model, EfficientNetB3 model. Three evaluation zones per study area were proposed to quantify the performance of the algorithms through the Intersection over Union (IoU) metric. This metric, with a range between 0 and 1, represents the degree of overlapping between two regions, where the higher agreement the higher IoU values. The results indicate that the models configured with the FPN network have the best performance followed by the traditional supervised algorithms. The performance differences were specific to the study area. For the rural area, the best FPN configuration obtained an IoU averaged for both time steps of 0.4, being this four times higher than the best supervised model, Support Vector Machines using a linear kernel with an average IoU of 0.1. Regarding the setting of urban/rural perimeter boundaries, this difference was less marked, having an average IoU of 0.53 in comparison to 0.38 obtained by the best supervised classification model, in this case Random Forest. The results are relevant for institutions tracking the dynamics of building areas from cloud computing platfo future assessments of classifiers in likewise platforms in other contexts.</p>
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Morgan-Benita, Jorge, Ana G. Sánchez-Reyna, Carlos H. Espino-Salinas, Juan José Oropeza-Valdez, Huizilopoztli Luna-García, Carlos E. Galván-Tejada, Jorge I. Galván-Tejada, Hamurabi Gamboa-Rosales, Jose Antonio Enciso-Moreno, and José Celaya-Padilla. "Metabolomic Selection in the Progression of Type 2 Diabetes Mellitus: A Genetic Algorithm Approach." Diagnostics 12, no. 11 (November 15, 2022): 2803. http://dx.doi.org/10.3390/diagnostics12112803.
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According to the World Health Organization (WHO), type 2 diabetes mellitus (T2DM) is a result of the inefficient use of insulin by the body. More than 95% of people with diabetes have T2DM, which is largely due to excess weight and physical inactivity. This study proposes an intelligent feature selection of metabolites related to different stages of diabetes, with the use of genetic algorithms (GA) and the implementation of support vector machines (SVMs), K-Nearest Neighbors (KNNs) and Nearest Centroid (NEARCENT) and with a dataset obtained from the Instituto Mexicano del Seguro Social with the protocol name of the following: “Análisis metabolómico y transcriptómico diferencial en orina y suero de pacientes pre diabéticos, diabéticos y con nefropatía diabética para identificar potenciales biomarcadores pronósticos de daño renal” (differential metabolomic and transcriptomic analyses in the urine and serum of pre-diabetic, diabetic and diabetic nephropathy patients to identify potential prognostic biomarkers of kidney damage). In order to analyze which machine learning (ML) model is the most optimal for classifying patients with some stage of T2DM, the novelty of this work is to provide a genetic algorithm approach that detects significant metabolites in each stage of progression. More than 100 metabolites were identified as significant between all stages; with the data analyzed, the average accuracies obtained in each of the five most-accurate implementations of genetic algorithms were in the range of 0.8214–0.9893 with respect to average accuracy, providing a precise tool to use in detections and backing up a diagnosis constructed entirely with metabolomics. By providing five potential biomarkers for progression, these extremely significant metabolites are as follows: “Cer(d18:1/24:1) i2”, “PC(20:3-OH/P-18:1)”, “Ganoderic acid C2”, “TG(16:0/17:1/18:1)” and “GPEtn(18:0/20:4)”.
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Jeż, Bartłomiej, Jerzy Wysłocki, Simon Walters, Przemysław Postawa, and Marcin Nabiałek. "The Process of Magnetizing FeNbYHfB Bulk Amorphous Alloys in Strong Magnetic Fields." Materials 13, no. 6 (March 18, 2020): 1367. http://dx.doi.org/10.3390/ma13061367.
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The structure of amorphous alloys still has not been described satisfactorily due to the lack of direct methods for observing structural defects. The magnetizing process of amorphous alloys is closely related to its disordered structure. The sensitivity of the magnetization vector to any heterogeneity allows indirect assessment of the structure of amorphous ferromagnetic alloys. In strong magnetic fields, the magnetization process involves the rotation of a magnetization vector around point and line defects. Based on analysis of primary magnetization curves, it is possible to identify the type of these defects. This paper presents the results of research into the magnetization process of amorphous alloys that are based on iron, in the areas called the approach to ferromagnetic saturation and the Holstein–Primakoff para-process. The structure of a range of specially produced materials was examined using X-ray diffraction. Primary magnetization curves were measured over the range of 0 to 2 T. The process of magnetizing all of the tested alloys was associated with the presence of linear defects, satisfying the relationship Ddi p < 1H. It was found that the addition of yttrium, at the expense of hafnium, impedes the magnetization process. The alloy with an atomic content of Y = 10% was characterized by the highest saturation magnetization value and the lowest value of the Dspf parameter, which may indicate the occurrence of antiferromagnetic ordering in certain regions of this alloy sample.
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Martins, Cristiano M., Williams A. Lima, Valeria C. Barbosa, and João B. Silva. "Total variation regularization for depth-to-basement estimate: Part 1 — Mathematical details and applications." GEOPHYSICS 76, no. 1 (January 2011): I1—I12. http://dx.doi.org/10.1190/1.3524286.
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We have developed an inversion approach that estimates the basement relief of a fault-bounded sedimentary basin. The sedimentary pack is approximated by a grid of 3D or 2D vertical prisms juxtaposed in the horizontal directions of a right-handed coordinate system. The prisms’ thicknesses represent the depths to the basement and are the parameters to be estimated from the gravity data. To obtain depth-to-basement estimates, we introduce the total variation (TV) regularization as a stabilizing function. This approach lets us estimate a nonsmooth basement relief because it does not penalize sharp features of the solution. We have deduced a compact matrix form of the gradient vector and the Hessian matrix of the approximation to the TV function that allows a regularized Gauss-Newton minimization approach. Because the Hessian matrix of the approximation to the TV function is ill conditioned, we have modified this Hessian matrix to improve its condition and to accelerate the convergence of the Gauss-Newton algorithm. Tests conducted with synthetic data show that the inversion method can delineate discontinuous basements presenting large slips or sequences of small-slip step faults. Tests on field data from the Almada Basin, Brazil, and from the San Jacinto Graben, California, U.S.A., confirm the potential of the method in detecting and locating in-depth normal faults in the basement relief of a sedimentary basin.
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Allio, Robert J. "Learning to be a leader." Strategy & Leadership 44, no. 4 (July 18, 2016): 3–9. http://dx.doi.org/10.1108/sl-06-2016-0041.
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Purpose The author believes it is possible to select a better strategy for improving leadership effectiveness. His hypothesis: although leadership cannot be taught, paradoxically, leadership can be learned. Design/methodology/approach The playbook for developing potential leaders comprises these three elements: Establish a leadership identity and persona. Acquire relevant leadership knowledge and skills. Practice acts of leadership. Findings We preach the need for moral leaders, but in pursuit of maximizing shareholder returns and stock option bonuses for CEOs society embraces rogues and celebrates robber barons who successfully elbow their way ahead of the pack! Practical implications Whatever other personal traits the leader may possess, the one absolute prerequisite is the judicious exercise of power – specifically, the power to change the way followers think and behave. Originality/value Success leadership ultimately depends on the ability to communicate, to tell a story that explains the proposed corporate vector and inspires the followers to sign on for the adventure.
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Carollo, Brett. "Nietzsche and Transhumanism: A Reassessment." Agonist 16, no. 2 (December 24, 2022): 67–81. http://dx.doi.org/10.33182/agon.v16i2.2800.
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This paper addresses the scholarly debate over Nietzsche’s relationship to transhumanism. Most writing on this topic has focused almost exclusively on whether or not Nietzsche’s thought is philosophically compatible with transhumanist philosophy. Because ideas are not always transmitted in philosophically cogent ways, this approach is inadequate to address the question of how Nietzsche may have influenced transhumanism. I propose replacing the current approach with a history of ideas approach that also tracks “para-philosophical” vectors of influence. Bringing to bear such an approach, I argue that Nietzsche was crucial in laying the groundwork for transhumanism. First, his rejection of Being, of a fixed ontological order, decisively undermined essentialist conceptions of human nature, opening the door to a radical refashioning of the human being such as that envisioned in the transhumanist “posthuman.” Second, Nietzsche’s superman and the transhumanist posthuman are instantiations of apotheosis, a perennial impulse toward self-divinization at the core of many mystical and esoteric systems. The superman represents the ideal of apotheosis filtered through Nietzsche’s materialism and his processual turn, and it is in this modified, post-Nietzschean form that the ideal passes to transhumanism. Finally, I demonstrate that Nietzsche’s thought is not as philosophically incompatible with transhumanism as some critics claim.
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Ruíz García, David, Héctor Javier Vásquez Enríquez, Saiveth Hernández Hernández, Arturo Téllez Velázquez, and Raúl Cruz Barbosa. "Reconocimiento de Glaucoma usando Imágenes de fondo de la Retina." Tecnología Educativa Revista CONAIC 7, no. 1 (December 29, 2020): 66–71. http://dx.doi.org/10.32671/terc.v7i1.18.
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En este trabajo se presenta un enfoque de reconocimiento de glaucoma donde la aportación principal es un criterio de selección de características basado en la sensibilidad. El sistema utiliza el conjunto de datos público RIMONE-r3, del cual utiliza las imágenes del fondo de retina y sus segmentaciones de disco y copa óptica para crear un conjunto de 165 características. Se utiliza un método empaquetador para realizar una selección de características hacia adelante, usando sensibilidad como criterio de selección, para reducir el conjunto a un subconjunto de 120 características. Los resultados de la clasificación realizados por una máquina de soporte vectorial son de 92% de exactitud, 100% de sensibilidad y 88.23% de especificidad, logrando un modelo altamente sensible al reconocimiento de glaucoma, el cual mejora a varios trabajos relacionados.
This work presents a glaucoma recognition approach where the main contribution is a sensitivity selection criterion for characteristics. The system uses the public RIMONE-r3 data set, from which it uses images of the retina background and its disc and optical cup segmentations to create a set of 165 features. A packaging method is used to perform a forward feature selection, using sensitivity as the selection criteria, to reduce the set to a subset of 120 features. The results of the classification performed by a vector support machine are 92% accurate, 100% sensitive, and 88.23% specific, achieving a highly sensitive model for glaucoma recognition, which improves several related works.
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Wong, Ching-Chang, Li-Yu Yeh, Chih-Cheng Liu, Chi-Yi Tsai, and Hisasuki Aoyama. "Manipulation Planning for Object Re-Orientation Based on Semantic Segmentation Keypoint Detection." Sensors 21, no. 7 (March 24, 2021): 2280. http://dx.doi.org/10.3390/s21072280.
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In this paper, a manipulation planning method for object re-orientation based on semantic segmentation keypoint detection is proposed for robot manipulator which is able to detect and re-orientate the randomly placed objects to a specified position and pose. There are two main parts: (1) 3D keypoint detection system; and (2) manipulation planning system for object re-orientation. In the 3D keypoint detection system, an RGB-D camera is used to obtain the information of the environment and can generate 3D keypoints of the target object as inputs to represent its corresponding position and pose. This process simplifies the 3D model representation so that the manipulation planning for object re-orientation can be executed in a category-level manner by adding various training data of the object in the training phase. In addition, 3D suction points in both the object’s current and expected poses are also generated as the inputs of the next operation stage. During the next stage, Mask Region-Convolutional Neural Network (Mask R-CNN) algorithm is used for preliminary object detection and object image. The highest confidence index image is selected as the input of the semantic segmentation system in order to classify each pixel in the picture for the corresponding pack unit of the object. In addition, after using a convolutional neural network for semantic segmentation, the Conditional Random Fields (CRFs) method is used to perform several iterations to obtain a more accurate result of object recognition. When the target object is segmented into the pack units of image process, the center position of each pack unit can be obtained. Then, a normal vector of each pack unit’s center points is generated by the depth image information and pose of the object, which can be obtained by connecting the center points of each pack unit. In the manipulation planning system for object re-orientation, the pose of the object and the normal vector of each pack unit are first converted into the working coordinate system of the robot manipulator. Then, according to the current and expected pose of the object, the spherical linear interpolation (Slerp) algorithm is used to generate a series of movements in the workspace for object re-orientation on the robot manipulator. In addition, the pose of the object is adjusted on the z-axis of the object’s geodetic coordinate system based on the image features on the surface of the object, so that the pose of the placed object can approach the desired pose. Finally, a robot manipulator and a vacuum suction cup made by the laboratory are used to verify that the proposed system can indeed complete the planned task of object re-orientation.
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Fitriani, Dwi, Mursid Raharjo, Mursid Raharjo, Martini Martini, Martini Martini, Onny Setiani, Onny Setiani, Nur Endah Wahyuningsih, and Nur Endah Wahyuningsih. "Penerapan Integrated Vector Management (IVM) Dalam Upaya Eliminasi Malaria Di Daerah Endemis Kabupaten Purworejo." Jurnal Kesehatan Lingkungan Indonesia 22, no. 1 (January 24, 2023): 112–21. http://dx.doi.org/10.14710/jkli.22.1.112-121.
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Latar belakang: Satu-satunya kabupaten yang belum mencapai eliminasi di pulau jawa bali adalah Purworejo. Re-emerging disease malaria yang terjadi pada bulan Juli 2021 menyebabkan Purworejo gagal mendapatkan sertifikat bebas malaria. Integrated Vector Management (IVM) ditujukan untuk memudahkan para pemangku kebijakan dalam menerapkan program pengendalian vektor agar lebih efektif dan efisien. Tujuan penelitian ini menganalisis penerapan IVM di kabupaten Purworejo dalam mencapai target eliminasi malaria tahun 2023Metode: Penelitian ini menggunakan metode kualitatif deskriptif. Pengambilan data dilakukan dengan wawancara mendalam. Informan dipilih langsung oleh peneliti (purposive sampling). Data diolah menggunakan aplikasi Nvivo 12 Plus. Nilai koding menunjukkan seringnya variabel tersebut dibahas informan selama penelitian.Hasil: Berdasarkan analisis referensi pengkodean Nvivo 12 Plus menunjukkan variabel pendekatan terintegrasi (110 koding), kapasitas sumber daya (30 koding), kerjasama lintas sektor (97 koding), Advokasi, Mobilisasi dan Regulasi (28 koding), dan pengambilan keputusan berdasarkan bukti (51 koding). Sumber Daya Manusia dalam pengendalian malaria di Puskesmas Kaligesing merangkap tugas dan kompetensi belum sesuai. JMD dinilai masih kurang apalagi ketika terjadi outbreak. Analisis situasi hanya berfokus pada kasus dan kondisi masyarakat, belum maksimal pada kajian epidemiologis maupun entomologis. Pencegahan dan pengendalian malaria terfokus setelah terjadi kasus. Kerjasama lintas sektor masih sebatas koordinasi belum maksimal dalam implementasi. Persepsi terkait masalah kesehatan menjadi tanggung jawab sektor kesehatan sedangkan sektor lain hanya mendukung. Penanganan malaria masih menjadi kegiatan mandiri dan belum kolaboratif. Belum ada program lintas institusi dalam penanganan malaria.Simpulan: Penerapan IVM Malaria di Kabupaten Purworejo belum maksimal. ABSTRACTTitle: Application of Integrated Vector Management (IVM) in Efforts to Eliminate Malaria in Endemic Areas, Purworejo RegencyBackground: The only district that has not achieved elimination on the island of Java Bali is Purworejo. The re-emerging malaria disease that occurred in July 2021 caused Purworejo to fail to get a malaria-free certificate. Integrated Vector Management (IVM) is intended to make it easier for policymakers to implement vector control programs to be more effective and efficient. The purpose of this study is to analyze the application of IVM in Purworejo district in achieving the malaria elimination target in 2023Method: This research uses descriptive qualitative methods. Data collection was carried out with in-depth interviews. Informants are selected directly by the researcher (purposive sampling). Data is processed using the Nvivo 12 Plus application. The coding value indicates the frequent discussion of these variables by informants during the study.Result: Based on the Nvivo 12 Plus coding reference analysis, it shows the variables of integrated approach (110 coding), resource capacity (30 coding), cross-sectoral cooperation (97 coding), Advocacy, Mobilization and Regulation (28 coding), and evidence-based decision making (51 coding). Human Resources in malaria control at the Kaligesing Health Center concurrently have tasks and competencies that are not yet appropriate. JMD is considered to be lacking, especially when there is an outbreak. Situation analysis only focuses on cases and community conditions, not yet optimally in epidemiological and entomological studies. Malaria prevention and control is focused after a case occurs. Cross-sectoral cooperation is still limited to coordination has not been maximized in implementation. Perceptions related to health problems are the responsibility of the health sector while other sectors are only supportive. Malaria management is still an independent and not yet collaborative activity. There is no cross-institutional program in malaria management.Conclusion: The application of IVM Malaria in Purworejo Regency has not been maximized
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Luo, Laijin, Chaolong Zhang, Youhui Tian, and Huihan Liu. "State-of-Health Estimate for the Lithium-Ion Battery Based on Constant Voltage Current Entropy and Charging Duration." World Electric Vehicle Journal 13, no. 8 (August 5, 2022): 148. http://dx.doi.org/10.3390/wevj13080148.
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An accurate state-of-health (SOH) estimation is vital to guarantee the safety and reliability of a lithium-ion battery management system. In application, the electrical vehicles generally start charging when the battery is at a non-zero state of charge (SOC), which will influence the charging current, voltage and duration, greatly hindering many traditional health features to estimate the SOH. However, the constant voltage charging phase is not limited by the previous non-zero SOC starting charge. In order to overcome the difficulty, a method of estimating the battery SOH based on the information entropy of battery currents of the constant voltage charging phase and charging duration is proposed. Firstly, the time series of charging current data from the constant voltage phase are measured, and then the information entropy of battery currents and charging time are calculated as new indicators. The penalty coefficient and width factor of a support vector machine (SVM) improved by the sparrow search algorithm is utilized to establish the underlying mapping relationships between the current entropy, charging duration and battery SOH. Additionally, the results indicate the adaptability and effectiveness of the proposed approach for a battery pack and cell SOH estimation.
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Hart, Jamie, Bruno Tremblay, Charles Brunette, Carolina Dufour, and Robert Newton. "Examining the Transition from a perennial to a seasonal sea ice cover in the Arctic Ocean: A Lagrangian Approach." McGill Science Undergraduate Research Journal 14, no. 1 (April 10, 2019): 28–32. http://dx.doi.org/10.26443/msurj.v14i1.50.
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Background: Declining Arctic sea ice extent has been accompanied by a large loss in multiyear ice (MYI). The dynamic and thermodynamic processes which affect this transition include promotion of first year ice (FYI) to MYI, demotion (melting) of MYI to open water, and ice export through Fram Strait. In this study we quantify the relative importance of these three processes. Methods: We use the Lagrangian Ice Tracking System which employs satellite-derived sea ice drift vectors combined with sea ice concentrations to find annual areas of promotion, demotion, and export. Results: Over the satellite record (1989-2015), we quantify the total contributions to sea ice extent loss from promotion (+30 million km2), demotion (-19.7 million km2), and export of MYI (-18.6 million km2). The result is a total net loss of 8.3 million km2 of MYI. We find that all three processes are positively correlated with minimum sea ice extent and are increasing with rates of +0.165 million km2/decade, -0.146 million km2/ decade, and -0.096 million km2/decade for promotion, demotion, and export respectively. We also compute the negative ice growth feedback at 0.59 (with r2=0.27). This indicates that ice pack recovers, on average, 59% of the MYI area lost to demotion/export through promotion of FYI the following winter. Limitations: Uncertainties in the drift speed are compounded by the weekly temporal resolution of the model, which affects the resulting estimates of demotion and promotion area. Conclusion: Demotion and export combined are increasing faster than promotion and represent a larger area contribution. This imbalance accounts for the observed loss of MYI area.
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Błoch, Katarzyna, Marcin Nabiałek, Przemysław Postawa, Andrei Victor Sandu, Agata Śliwa, and Bartłomiej Jeż. "The Magnetisation Process of Bulk Amorphous Alloys: Fe36+xCo36−xY8B20, Where: x = 0, 3, 7, or 12." Materials 13, no. 4 (February 13, 2020): 846. http://dx.doi.org/10.3390/ma13040846.
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Amorphous Fe- and Co-based alloys possess so-called soft magnetic properties. Due to the high sensitivity of the magnetisation vector to any inhomogeneities occurring in these alloys, it is possible to assess indirectly structural defects. This paper presents the results of research on the structure and magnetic properties of bulk amorphous alloys with a high content of Fe and Co. The magnetic properties of the produced alloys were tested using a Faraday magnetic balance and a vibrating sample magnetometer (VSM). Analysis of the magnetisation process in the region known as the approach to ferromagnetic saturation was carried out in accordance with Kronmüller’s theorem. Magnetisation in magnetic fields of greater than the effective anisotropy field (Holstein-Primakoff para-process) was also studied. For the studied alloys, it was found that an increase in Fe content causesan increase in saturation magnetisation, and decreases in the values of the coercive field and thespin-wave stiffness parameter, Dspf. A relationship was observed between the width of the amorphous halo and the value of the coercive field. However, no significant links were found between either the presence of structural defects and the properties of these materials, or between the Co content and the value of the coercive field.
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Feng, Jingge, Yeping He, Qiuming Tao, and Hengtai Ma. "An SLP Vectorization Method Based on Equivalent Extended Transformation." Wireless Communications and Mobile Computing 2022 (March 9, 2022): 1–16. http://dx.doi.org/10.1155/2022/1832522.
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SIMD extensions provide an efficient energy consumption platform to support mobile systems. How to use SIMD instructions to improve program performance is a challenge. SLP (superword level parallelism) is an efficient solution to exploit the parallelism, oriented to SIMD, between statements in the basic blocks, and it has been widely used in almost all the mainstream compilers. SLP relies on finding isomorphic statements to pack together into vectors. However, the capability of autovectorization for nonisomorphic statements is insufficient. In this paper, we introduce SLP-E, a novel autovectorization method that can automatically vectorize the codes which contain nonisomorphic statements, translate the nonisomorphic statements into the isomorphic statements by equivalent extended transformation of expressions, and vectorize the isomorphic statements. SLP-E improves the application scope and benefits of SLP. We implement the SLP-E in LLVM and compare it with prior approaches. A set of applications that benefit from autovectorization are taken from the SPEC CPU 2017 benchmark to compare our approach and prior techniques. Experimental results show that SLP-E achieves more than 43.9% speedup, on average, over other similar methods.