Journal articles on the topic 'Electronic data processing personnel Victoria'
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1
Monaghan, Timothy, Jo-Anne Manski-Nankervis, and Rachel Canaway. "Big data or big risk: general practitioner, practice nurse and practice manager attitudes to providing de-identified patient health data from electronic medical records to researchers." Australian Journal of Primary Health 26, no. 6 (2020): 466. http://dx.doi.org/10.1071/py20153.
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Research utilising de-identified patient health information extracted from electronic medical records (EMRs) from general practices has steadily grown in recent years in response to calls to increase use of health data for research and other secondary purposes in Australia. Little is known about the views of key primary care personnel on this issue, which are important, as they may influence whether practices agree to provide EMR data for research. This exploratory qualitative study investigated the attitudes and beliefs of general practitioners (GPs), practice managers (PMs) and practice nurses (PNs) around sharing de-identified EMR patient health information with researchers. Semi-structured interviews were conducted with 11 participants (6 GPs, 3 PMs and 2 PNs) recruited via purposive sampling from general practices in Victoria, Australia. Transcripts were coded and thematically analysed. Participants were generally enthusiastic about research utilising de-identified health information extracted from EMRs for altruistic reasons, including: positive effects on primary care research, clinical practice and population health outcomes. Concerns raised included patient privacy and data breaches, third-party use of extracted data and patient consent. These findings can provide guidance to researchers and policymakers in designing and implementing projects involving de-identified health information extracted from EMRs.
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Mitrofanova, Elena, and Aleksandra Mitrofanova. "E-HRM As a Human Resource Management Tool in the Digital Economy." Management of the Personnel and Intellectual Resources in Russia 10, no. 5 (November 29, 2021): 73–77. http://dx.doi.org/10.12737/2305-7807-2021-10-5-73-77.
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The article substantiates the need to create a new model of a personnel management system - electronic human resource management, which is an advanced business solution that provides full online support in the management of all processes, actions, data and information necessary for human resource management in a modern company, it is determined the essence and content, the goal, objectives, levels of electronic human resource management are shown, functions and results are shown, methods and opportunities for the implementation of electronic human resource management are proposed. It is shown that the introduction of electronic human resource management increases the efficiency of HR management processes by concentrating information about personnel in a centralized data bank, speeding up information processing, reducing errors and the amount of duplicate work, reducing less productive activities in the field of human resources and its reorientation to strategic tasks.
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Solovova, Natalia V., Yulia N. Gorbunova, and Olga Yu Kalmykova. "Digitalized continuous learning system in the company: organizational aspect." Vestnik of Samara University. Economics and Management 12, no. 4 (December 30, 2021): 145–56. http://dx.doi.org/10.18287/2542-0461-2021-12-4-145-156.
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Information and technical support of the personnel management system is gaining more and more distribution, informatization is carried out in virtually all modern companies without exception. As a rule, in most companies, they primarily automate the functions of personnel records management and administration. These areas are associated with the storage and processing of information about employees: personal files, work books, employment contracts, data on the movement of personnel, payroll. Information technologies can be used not only for processing large amounts of data, but also for their analysis.Recently, the use of artificial intelligence in recruiting has become widespread; such technologies significantly reduce the time spent on the selection of candidates. Artificial intelligence is used at the initial stage of recruiting calling candidates, which allows the HR manager not to miss a promising specialist from the stream of vacancies. At the same time, there is a trend towards automating more complex HR functions such as employee assessment, development and training. In this study, the sought-after directions for improving the information and technical support of the personnel management service were highlighted: artificial intelligence, continuous learning, big data. The hierarchy analysis method based on expert judgment determined the criteria that guided the group of experts when choosing the most promising direction with growth potential. According to the results of the analysis, the largest number of points was received by the direction continuous learning in the format of electronic distance learning 56.1 %. Further, a technological scheme for information and technical support of the personnel management service was developed. The process of introducing distance learning in the company is described, the main items of expenses, the departments responsible for the implementation of this system, the preparation of the necessary regulatory documentation, the choice of software, the costs of administration of the system are given.
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KOLOSOK, Irina N., and Liudmila A. GURINA. "Identification of Cyberattacks on SCADA and WAMS Systems in Electric Power Systems when Processing Measurements by State Estimation Methods." Elektrichestvo 6, no. 6 (2021): 25–32. http://dx.doi.org/10.24160/0013-5380-2021-6-25-32.
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The hardware and software tools of the data acquisition and processing systems, as well as the state estimation procedure intended to support the actions of dispatching personnel in performing operational and emergency control of electric power systems (EPS), are critically important components of the EPS information and communication subsystem, but at the same time, they are most vulnerable to cyberattacks. To reduce the extent to which cyberattacks can affect the control quality, it is proposed to use statistical methods for processing measurement information. First of all, these are static and dynamic state estimation methods, including a procedure for verifying measurements or detecting bad data. An analysis of data quality can determine the type of cyberattack undertaken and identify overlooked vulnerabilities. The article presents the findings from a study of two most commonly used bad data detection methods: the a priori method for analyzing the residuals of test equations and the a posteriori method for analyzing the weighted estimation residuals to identify data distorted as a consequence of specially generated cyberattacks. An algorithm to detect erroneous measurements that appear during cyberattacks and are not identified by conventional measurement verification methods in performing EPS state estimation is proposed
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Graham, Andrew, Stephan Gmur, and Travis Scott. "Improved SCAT data workflow to increase efficiency and data accuracy." International Oil Spill Conference Proceedings 2017, no. 1 (May 1, 2017): 2674–93. http://dx.doi.org/10.7901/2169-3358-2017.1.2674.
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ABSTRACT #2017-302 Traditional Shoreline Cleanup Assessment Technique (SCAT) data workflows typically entail collecting data in the field using notebooks, handheld GPS units and digital cameras, transcribing these data onto paper forms, and then manually entering into a local database. Processed data are pushed to a SCAT geographical information system (GIS) specialist, ultimately providing exports as paper and electronic versions of maps, spreadsheets and reports. The multiple and sometimes iterative steps required can affect the dissemination of accurate and timely information to decision makers and compound the potential for introducing errors into the data. To improve this process a revised SCAT data workflow has been developed that decreases data processing steps and time requirements while increasing data accuracy in several facets of the process. The workflow involves using mobile data collection devices in the field to capture attribute data, photographs and geospatial data. These data are uploaded to a web-enabled database that allows field team members to complete, review and adjust their data, along with data manager approval before presentation to others in the response. For response personnel with internet access and proper login credentials, SCAT data, including photographs, reports and results can be searched for by attribute, time or location, and reviewed online in form view or on a web map. For traditional SCAT spatial analysis products, approved data can be exported and processed in a GIS as normal, but can also be returned to the web-enabled database to be viewed on a map or distributed via web mapping services (WMS) to other web GIS data viewers or common operating pictures (COPs). Field testing of the improved workflow shows decreased data processing time for data, a more robust yet streamlined quality assurance and quality control process (QA/QC), and easier more inclusive access to the data relative to traditional paper forms and data processing. While the improved workflow entails a steeper learning curve and a heavier reliance on technology than traditional SCAT workflows, the benefits are significant.
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Freimuth, Henk, and Markus König. "A Framework for Automated Acquisition and Processing of As-Built Data with Autonomous Unmanned Aerial Vehicles." Sensors 19, no. 20 (October 17, 2019): 4513. http://dx.doi.org/10.3390/s19204513.
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Planning and scheduling in construction heavily depend on current information about the state of construction processes. However, the acquisition process for visual data requires human personnel to take photographs of construction objects. We propose using unmanned aerial vehicle (UAVs) for automated creation of images and point cloud data of particular construction objects. The method extracts locations of objects that require inspection from Four Dimensional Building Information Modelling (4D-BIM). With this information at hand viable flight missions around the known structures of the construction site are computed. During flight, the UAV uses stereo cameras to detect and avoid any obstacles that are not known to the model, for example moving humans or machinery. The combination of pre-computed waypoint missions and reactive avoidance ensures deterministic routing from takeoff to landing and operational safety for humans and machines. During flight, an additional software component compares the captured point cloud data with the model data, enabling automatic per-object completion checking or reconstruction. The prototype is developed in the Robot Operating System (ROS) and evaluated in Software-In-The-Loop (SITL) simulations for the sake of being executable on real UAVs.
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Wang, Yiming, and Xidan Gong. "Optimization of Data Processing System for Exercise and Fitness Process Based on Internet of Things." Wireless Communications and Mobile Computing 2021 (July 6, 2021): 1–11. http://dx.doi.org/10.1155/2021/7132301.
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In the digital network era, people have higher requirements for physical fitness. In the future, physical fitness requires not only good fitness equipment and fitness environment but also more convenient and intelligent health management, service guidance, social entertainment, and other refined fitness services. The innovation of sports and fitness equipment for the digital network era will definitely depend on the development of information technology and network technology. Based on the cutting-edge Internet of Things technology, this thesis focuses on the development and application of a new generation of digital fitness equipment adapted to future development, advocating the new concept of seamless integration of fitness exercise and information services through human-oriented systematic design thinking and providing implementable solutions to realize the science, convenience, and life of public fitness. This thesis uses modern science and technology, especially the Internet of Things (IoT) technology, to fully meet the diversified fitness needs of the fitness crowd as the guide; IoT digital fitness equipment design and application research was newly generated, using a variety of research methods to explore the functional design and application of IoT fitness equipment; the goal is to create a more intelligent and three-dimensional IoT fitness service model in the future. Through the application research of intelligent devices in IoT fitness equipment, the realization of the functions of identity identification, environment perception, and data transmission of IoT fitness equipment is made faster. Intelligent devices can become the interaction channel between fitness service personnel, fitness equipment, and fitness users and also reduce the development cost of IoT fitness equipment. The construction of an IoT fitness cloud service platform and data management system integrates the application of IoT, cloud computing, mobile communication, and other technologies to make IoT fitness service supply remote, real-time, and diversified. While providing convenient and value-added fitness services for fitness people, it also brings sustainable development space for the health service industry.
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Sun, Qing, Tao Wu, and Jia Hua. "Design of Distributed Human Resource Management System of Spark Framework Based on Fuzzy Clustering." Journal of Sensors 2022 (March 11, 2022): 1–9. http://dx.doi.org/10.1155/2022/4827021.
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The construction of human resource management system is a key part of enterprise management and control. A perfect human resource management system is conducive to the long-term development of enterprises. Aiming at improving the current situation of enterprise human resource management, a distributed human resource management system is proposed in this paper based on Spark framework. Aiming at the disadvantages of traditional k -means algorithm in processing massive data, such as low computational efficiency and high time complexity, an improved k -means algorithm based on Spark computing framework is proposed. Through the spatial location relationship with the cluster center, redundant calculation is reduced and the ability of processing massive data is improved for the system. Combined with the actual situation of the enterprise, the human resource management system architecture is designed by using Java EE human-computer interaction. The proposed system can achieve user management, employee information, attendance, evaluation, performance, salary, personnel change, and other business management. The experimental results demonstrate that the system can effectively reduce the time complexity of calculation and improve the system efficiency.
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Fang, Ran, and Zhihuai Fang. "Analysis of Human Resource Allocation Scheme for Digital Media Big Data Based on Recurrent Neural Network Model." Journal of Sensors 2022 (September 30, 2022): 1–11. http://dx.doi.org/10.1155/2022/3430933.
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At present, all kinds of computing models used in human society are based on statistics. Due to the large amount of data, conventional statistical methods cannot solve these problems well. In view of the concealment of data, the processing of large data plays a great role in the rational allocation of human resources, training professional talents, improving the operation of human resources, and improving the use and efficiency of human resources. This paper combines the method of human resource allocation based on recurrent neural network and conventional human resource allocation, in order to find a suitable method for personnel position selection and recommendation in the field of talent work. In terms of algorithm test, the F1 value of the proposed method is 0.823, which is 20.1% and 7.4% higher than the previous two methods, respectively, indicating that the method can effectively improve the hidden features, improve the training effect, and improve the performance of the model.
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FIOFANOVA, OLGA. "Big Data-driven management in education." Public Administration 23, no. 3 (2021): 86–91. http://dx.doi.org/10.22394/2070-8378-2021-23-3-86-91.
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The article discusses a new technology in the field of administration – a method of data-based management. In the field of education, analytics is the necessary manager’s competence to fulfill his work duties. The author identified the problem of transforming legal norms when working with open data, which did not affect the change in institutional and cultural norms of “data- based management” in managerial decision-making practice. The article provides a comparative analysis of the professional standards’ requirements and educational programs for the managerial personnel’s professional development in the field of education. The author analyzed two aspects of the development of a data-based management system: personnel – the development of educational programs for training managerial specialists who can use such technology, and infrastructure – the development of digital open data services and digital data processing services for making managerial decisions. The tasks of developing education through the analysis of data for assessing its quality are reflected in the Decree of the President of the Russian Federation “On national goals and strategic objectives for the development of the Russian Federation for the period up to 2024” and can be implemented based on the professional capital of managers using tools for analyzing such data. It is necessary to improve the interaction of electronic information exchange services for more effective information interaction and the construction of analytical reporting. This will allow for the efficient integration of data from different information systems and electronic resources and obtain the necessary data of the information of interest.
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Zhou, Xianwen, Chaoyang Gu, Yuyu Sun, Chengjing Han, Wei Gu, and Wangqiang Niu. "Preventive Maintenance Strategy of Environmental Test Chamber Based on Particle Swarm Optimization Algorithm." International Journal of Circuits, Systems and Signal Processing 16 (January 15, 2022): 618–27. http://dx.doi.org/10.46300/9106.2022.16.77.
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With the development of various physical industries, people pay more attention to reliability tests and test equipment. To solve the problem of making maintenance strategy of an environmental test chamber for reliability test, a periodic preventive maintenance strategy based on RCM(Reliability Centre Maintenance) is proposed. Firstly, a multi-objective optimization model of reliability and maintenance cost is established by combining reliability theory and life distribution theory, and two objectives of equipment reliability and maintenance cost are considered. Secondly, the actual environmental test chamber fault maintenance data is analyzed, and it is found the fault distribution meets the dual parameter Weibull. Finally, the particle swarm optimization algorithm is used to solve the multi-objective model optimization, and a series of Pareto optimal solutions are obtained, that is, the number of maintenance times and the corresponding time interval in the operation cycle of the environmental test chamber, and these solutions might be good references for maintenance management personnel.
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Qin, Zhidan. "The Inventory Control System of Reverse Logistics for E-Commerce Packaging Recovery Based on BP Neural Network." International Journal of Circuits, Systems and Signal Processing 16 (January 13, 2022): 413–25. http://dx.doi.org/10.46300/9106.2022.16.51.
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The paper combines BP neural network to optimize the control system of e-commerce packaging and reverse logistics inventory. Through improving the hardware configuration structure of the system, the system can be improved and the operation effect of the system can be improved. The software flow and operation algorithm of the storage control system of e-commerce packaging recycling reverse logistics are optimized step by step, and the logistics is delivered by following the vehicle on the spot and visiting the logistics The distribution personnel collect the relevant data and data in the process of logistics and transportation, draw the reverse logistics business flow chart, point out the situation of reverse logistics before and after the goods distribution and distribution due to the cancellation of orders or transactions by customers, and the application for return of goods after the transaction. Meanwhile, it points out that the sales return operation site in the reverse logistics management process is chaotic and not formed the clear business process specification and other problems can effectively control the reverse logistics inventory of e-commerce packaging recovery. Finally, the experiment proves that the e-commerce packaging recycling reverse logistics inventory control system is more practical in the practical application process, and fully meets the research requirements.
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Smirnova, Arina, Kirill Varnavskiy, Fedor Nepsha, Roman Kostomarov, and Shaojie Chen. "The Development of Coal Mine Methane Utilization Infrastructure within the Framework of the Concept “Coal-Energy-Information”." Energies 15, no. 23 (November 26, 2022): 8948. http://dx.doi.org/10.3390/en15238948.
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The operation of coal mines is intricately linked with emitting a large quantity of coal mine methane, and in most cases, this methane releases into the atmosphere. In total, according to statistics, coal mining enterprises emit 8% of anthropogenic methane, determining a contribution to greenhouse gas emissions to the amount of 17%. There are various means for coal mine methane utilization. In this study, the concept “Coal-Energy-Information” is proposed. This concept implies both the construction of data processing centers on the industrial sites of coal mines and the usage of coal mine methane. Coal mine methane can be used as a primary energy source for the energy supply of data processing center consumers as well as coal mine consumers with necessary energy resources (electricity, heat, and cooling). Within the framework of the proposed concept, three options of coal mine methane utilization are considered. The first option is the use of gas genset for electrical and thermal energy generation (cogeneration) and their usage for coal mine and constructed data processing centers and consumers’ power supply. The second option is absorption refrigerator usage (with coal mine methane direct burning) for cooling the IT equipment of constructed data processing centers. The last one is the use of a gas genset and absorption refrigerator (trigeneration) for constructed data processing centers’ and coal mine consumers’ energy supplies (electricity, heat, and cooling). In conclusion, it is noted that proposed concept is closely correlated with the program for the development of the coal industry in Russia for the period up to 2035, since it allows creating a base for the implementation of innovative technologies based on digital platforms that ensure the development of coal mining technology without the constant presence of personnel in underground mining facilities.
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Murphy, Daniel R., Ashley ND Meyer, Dean F. Sittig, Derek W. Meeks, Eric J. Thomas, and Hardeep Singh. "Application of electronic trigger tools to identify targets for improving diagnostic safety." BMJ Quality & Safety 28, no. 2 (October 5, 2018): 151–59. http://dx.doi.org/10.1136/bmjqs-2018-008086.
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Progress in reducing diagnostic errors remains slow partly due to poorly defined methods to identify errors, high-risk situations, and adverse events. Electronic trigger (e-trigger) tools, which mine vast amounts of patient data to identify signals indicative of a likely error or adverse event, offer a promising method to efficiently identify errors. The increasing amounts of longitudinal electronic data and maturing data warehousing techniques and infrastructure offer an unprecedented opportunity to implement new types of e-trigger tools that use algorithms to identify risks and events related to the diagnostic process. We present a knowledge discovery framework, the Safer Dx Trigger Tools Framework, that enables health systems to develop and implement e-trigger tools to identify and measure diagnostic errors using comprehensive electronic health record (EHR) data. Safer Dx e-trigger tools detect potential diagnostic events, allowing health systems to monitor event rates, study contributory factors and identify targets for improving diagnostic safety. In addition to promoting organisational learning, some e-triggers can monitor data prospectively and help identify patients at high-risk for a future adverse event, enabling clinicians, patients or safety personnel to take preventive actions proactively. Successful application of electronic algorithms requires health systems to invest in clinical informaticists, information technology professionals, patient safety professionals and clinicians, all of who work closely together to overcome development and implementation challenges. We outline key future research, including advances in natural language processing and machine learning, needed to improve effectiveness of e-triggers. Integrating diagnostic safety e-triggers in institutional patient safety strategies can accelerate progress in reducing preventable harm from diagnostic errors.
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Asre, Shashank, and Adnan Anwar. "Synthetic Energy Data Generation Using Time Variant Generative Adversarial Network." Electronics 11, no. 3 (January 24, 2022): 355. http://dx.doi.org/10.3390/electronics11030355.
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Energy consumption data is being used for improving the energy efficiency and minimizing the cost. However, obtaining energy consumption data has two major challenges: (i) data collection is very expensive, time-consuming, and (ii) security and privacy concern of the users which can be revealed from the actual data. In this research, we have addressed these challenges by using generative adversarial networks for generating energy consumption profile. We have successfully generated synthetic data which is similar to the real energy consumption data. On the basis of the recent research conducted on TimeGAN, we have implemented a framework for synthetic energy consumption data generation that could be useful in research, data analysis and create business solutions. The framework is implemented using the real-world energy dataset, consisting of energy consumption data of the year 2020 for the Australian states of Victoria, New South Wales, South Australia, Queensland and Tasmania. The results of implementation is evaluated using various performance measures and the results are showcased using visualizations along with Principal Component Analysis (PCA) and t-distributed stochastic neighbor embedding (TSNE) plots. Overall, experimental results show that Synthetic data generated using the proposed implementation possess very similar characteristics to the real dataset with high comparison accuracy.
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Yatsenko, Oleh, Oleksii Vernik, and Yuliia Vernik. "UKRAINIAN NATIONAL BIOGRAPHY ARCHIVE (2000–2020): TRANSFORMATION OF CONTENT." Scientific journal “Library Science. Record Studies. Informology”, no. 2 (September 1, 2021): 32–41. http://dx.doi.org/10.32461/2409-9805.2.2021.238778.
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The purpose of the article is to present the process of formation of a biographical resource, to depict the current state of its updated version - the electronic Ukrainian National Biographical Archive (UNBA) to analyze the changes that occurred during 2000-2020 in the formation of the biographical array of the database (DB) "Personalities" - a fundamental component of the electronic UNBA. The methodology consists of a combination of general scientific methods of analysis of theoretical material and statistical and comparative methods of analysis of specific empirical data, their systematization, and generalization. The scientific novelty of the study is characterized by obtaining unique information about the dynamics of the distribution of UNBA personnel - important figures of Ukrainian culture - by thematic headings, chronological periods, gender distribution. Conclusions. Formed by UNBA, today is the largest national electronic biographical resource. The emergence of modern sources in Ukraine, which open to the reader new, undeservedly forgotten, silent for various reasons, contributes to a large-scale change in the volume of biographical resources. Qualitative processing of these sources significantly multiplies the UNBA register, significantly increases its informative aspect. The analysis showed the versatility of the presented information on its thematic, chronological, gender distribution. In addition, it identified problems that should be taken into account when further filling the resource, in particular the significant uneven distribution of personnel by domain and article, incomplete chronological information about births, deaths, and burials, insufficient attention to biographical sources before the XIX century.
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Capanang, Jean M., Jobelle P. Panganiban, Glenn N. Ortiz, and Mark Joseph B. Enojas. "Automated data monitoring of MEMS cleanroom parametric requirements." Indonesian Journal of Electrical Engineering and Computer Science 23, no. 2 (August 1, 2021): 701. http://dx.doi.org/10.11591/ijeecs.v23.i2.pp701-708.
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<p>Cleanroom parameters such as temperature, relative humidity and particle count are vital in maintaining cleanliness. People and machines working inside the cleanroom are main contributors for the sudden changes of the separameters. Measurements and monitoring of these parameters are therefore necessary to reduce rejects and downtime in the production of micro-electro-mechanical systems (MEMS). This paper presents a method of developmentof an automated data monitoring of MEMS cleanroom parametric requirements. The prototype developed uses DHT11 sensor and Sharp dust sensor for measuring the temperature, humidity and particle count respectively which are displayed in an LCD display. These parameters are recorded through a data logger for analysis and control. Additionally, agraphical user interface was also developed using visual studio for the working personnel and for supervisory monitoring and control. As a result, the possible quality compromise in the production of MEMS is detected when the monitored parameters are beyond the range.</p>
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González-Nóvoa, José A., Laura Busto, Silvia Campanioni, José Fariña, Juan J. Rodríguez-Andina, Dolores Vila, and César Veiga. "Two-Step Approach for Occupancy Estimation in Intensive Care Units Based on Bayesian Optimization Techniques." Sensors 23, no. 3 (January 19, 2023): 1162. http://dx.doi.org/10.3390/s23031162.
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Due to the high occupational pressure suffered by intensive care units (ICUs), a correct estimation of the patients’ length of stay (LoS) in the ICU is of great interest to predict possible situations of collapse, to help healthcare personnel to select appropriate treatment options and to predict patients’ conditions. There has been a high amount of data collected by biomedical sensors during the continuous monitoring process of patients in the ICU, so the use of artificial intelligence techniques in automatic LoS estimation would improve patients’ care and facilitate the work of healthcare personnel. In this work, a novel methodology to estimate the LoS using data of the first 24 hours in the ICU is presented. To achieve this, XGBoost, one of the most popular and efficient state-of-the-art algorithms, is used as an estimator model, and its performance is optimized both from computational and precision viewpoints using Bayesian techniques. For this optimization, a novel two-step approach is presented. The methodology was carefully designed to execute codes on a high-performance computing system based on graphics processing units, which considerably reduces the execution time. The algorithm scalability is analyzed. With the proposed methodology, the best set of XGBoost hyperparameters are identified, estimating LoS with a MAE of 2.529 days, improving the results reported in the current state of the art and probing the validity and utility of the proposed approach.
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Okoli, Chinweike, Boniface Anyaka, Chidiogo Nwokedi, and Victor Anya. "Application of Composite Method for Determining Fault Location on Electrical Power Distribution Lines." Journal of Electrical and Computer Engineering 2020 (September 1, 2020): 1–9. http://dx.doi.org/10.1155/2020/2836940.
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Distribution line is one of the most important components of the distribution system. Troubleshooting faults on these lines are often a tedious task requiring service vehicles and personnel moving from one place to another in order to locate the fault and fix the problem. The study, therefore, is on how a composite fault location technique can be applied to predict the location of faults on the distribution lines. The calculations for the estimation of the fault location are performed using one terminal voltage and current data of the distribution line. A composite method that combines the impedance-based method and the fuzzy inference system method is used in the fault location algorithm. The presented algorithm has been extensively tested using the MATLAB-Simulink model of a 33 KV 40-kilometer distribution line. The simulation result demonstrates good accuracy and robustness of the algorithm.
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Platus, David L. "Vibration Isolation Critical to Measuring Neuronal Patterns in the Brain." Microscopy Today 17, no. 3 (May 2009): 12–15. http://dx.doi.org/10.1017/s1551929500050057.
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Researchers at Georgetown University's Department of Physiology and Biophysics use negative-stiffness vibration isolators to help measure micron-level patterns of neuronal activity in the mammalian neocortex. The research is shedding new light into brain sensory and motor processing functions relating to cardiac fibrillation and epilepsy.Isolating a laboratory's sensitive microscopy equipment against low-frequency vibration has become increasingly more vital to maintaining imaging quality and data integrity for neurobiology researches. Ever more frequently, laboratory researchers are discovering that conventional air tables and the more recent active (electronic) vibration isolation systems are not able to adequately cancel out the lower frequency perturbations derived from air conditioning systems, outside vehicular movements and ambulatory personnel. Such was the case with the Department of Physiology and Biophysics at Georgetown University Medical Center, where Professor Jian-Young Wu has been conducting research on waves of neuronal activity in the neocortex of the brain.
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Wang, Cheng, Chenlong Yao, Pengfei Chen, Jiamin Shi, Zhe Gu, and Zheying Zhou. "Artificial Intelligence Algorithm with ICD Coding Technology Guided by the Embedded Electronic Medical Record System in Medical Record Information Management." Journal of Healthcare Engineering 2021 (August 30, 2021): 1–9. http://dx.doi.org/10.1155/2021/3293457.
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The study aims to explore the application of international classification of diseases (ICD) coding technology and embedded electronic medical record (EMR) system. The study established an EMR information knowledge system and collected the data of patient medical records and disease diagnostic codes on the front pages of 8 clinical departments of endocrinology, oncology, obstetrics and gynecology, ophthalmology, orthopedics, neurosurgery, and cardiovascular medicine for statistical analysis. Natural language processing-bidirectional recurrent neural network (NLP-BIRNN) algorithm was used to optimize medical records. The results showed that the coder was not clear about the basic rules of main diagnosis selection and the classification of disease coding and did not code according to the main diagnosis principles. The disease was not coded according to different conditions or specific classification, the code of postoperative complications was inaccurate, the disease diagnosis was incomplete, and the code selection was too general. The solutions adopted were as follows: communication and knowledge training should be strengthened for coders and medical personnel. BIRNN was compared with the convolutional neural network (CNN) and recurrent neural network (RNN) in accuracy, symptom accuracy, and symptom recall, and it suggested that the proposed BIRNN has higher value. Pathological language reading under artificial intelligence algorithm provides some convenience for disease diagnosis and treatment.
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Korolyov, Vyacheslav Yu, Maksim I. Ogurtsov, and Anatoliy I. Kochubinskyi. "Identification of Technical Objects in the Special Networks According to the Principle of "Friend or Foe"." Control Systems and Computers, no. 4 (294) (November 2021): 3–12. http://dx.doi.org/10.15407/csc.2021.04.003.
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Introduction. In recent years, military conflicts are moving to a fundamentally new level of development, which is associated with the widespread use of geographically distributed large groups of remotely controlled robotic systems, the rapid growth of information volumes, a significant increase in the speed of its processing, instant messaging to increase situational awareness, management, rapid response, etc. Purpose. The article is devoted to solving an urgent scientific problem — the development of an algorithm for state identification of military objects and personnel. The problems of using modern cryptographic algorithms for state identification, which use data obtained by other stations of the air defense system and radio intelligence, combined in a special network, are considered. Results. A new encryption key exchange protocol and a rationale for choosing a cryptographic algorithm that can be used in real-time systems with low computational performance are proposed. To ensure the stability of the use of electronic warfare tools, it is proposed to use software-defined radio stations based on programmable logic matrices as a hardware basis, since they allow changing the type of signal-code structures, which also applies frequency ranges without replacing radio engineering blocks. Conclusions. With the increase in the number of remotely controlled military equipment objects on the battlefield, the problem of positioning military personnel and equipping them with network communication means requires a review of the methods and algorithms used for state recognition. The paper proposes a new algorithm for state identification of objects and identification of military personnel using symmetric cryptographic algorithms and the use of a secure Protocol for exchanging information received from the network of the Armed Forces of Ukraine. This approach can potentially increase the performance and quality of the identification system.
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Magid, S. I., I. Sh Zagredtinov, S. V. Mishcheryakov, Ye N. Arkhipova, and V. L. Samoylov. "Standardization of digital technologies of simulator systems as a method of ensuring reliability of conditions of service of power engineering facilities (part 1)." Safety and Reliability of Power Industry 12, no. 3 (November 22, 2019): 177–89. http://dx.doi.org/10.24223/1999-5555-2019-12-3-177-189.
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Matters are considered of standardization of digital simulator systems for ensuring reliability of service of various power engineering facilities. Definitions are given to such terms as reliability, functioning conditions anf safety.Industry-specific reference normative documents are presented regulating requirements to technical means for training power engineering personnel. Mandatory minimum requirements and criteria are presented to simulators of operating personnel of power generation enterprises according to the rates established. Existing regulatory technical documents and regulations on requirements to simulators of operating personnel are presented in an overview. Particular emphasis is put on creating technical specifications for certification of applied software tools of simulators of thermal power plants and networks, including compliance with requirements to identification characteristics of software tools, to functional characteristics, to data processing functions, as well as to compatibility and safety, and to user interface.Of considerable importance is the method of evaluation of the simulator, especially with consideration of today’s information technology requirements. The current state of most of developments in Russia’s simulator-building is considered in details, including: creating electronic lectures on description of technical characteristics of power engineering facilities and processes therein, generalized models of process devices, limited mode models, partial topology models (nodal models), shells for construction of process devices, integrated analysers of electric equipment, analytic software complexes and ACS.Based on detailed analysis of implementation of applied software tools in the field of simulator-building at power plants and network enterprises of Russia, substantiated conclusions are presented on the software products under consideration, which have positive references from customers and known for various reasons as “simulators”; these, though meeting the requirements stipulated by regulatory documents, do not feature to the full extent the properties necessary for full-fledged training, namely, full-scale applicability, compatibility with all modes and topological adequacy, which largely reduces the efficiency of their application in commercial operation.
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Muñiz, Rubén, Juan Díaz, Juan A. Martínez, Fernando Nuño, Julio Bobes, Mᵃ Paz García-Portilla, and Pilar A. Sáiz. "A Smart Band for Automatic Supervision of Restrained Patients in a Hospital Environment." Sensors 20, no. 18 (September 12, 2020): 5211. http://dx.doi.org/10.3390/s20185211.
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Mechanical contention (MC) is a restrictive, vital but controversial measure, prescribed in the majority of EU countries to handle patients with psycho-motor agitation that do not respond to other types of intervention, with an imminent risk of physical violence and aggression involved. This last resort approach implies risks for the somatic health of the contained individual that go from trauma injuries to, in some extreme cases, sudden death. Despite these risks, somatic supervision and the monitoring of patients under MC is limited, being periodically and manually carried out by nursing personnel with portable equipment. In this context, ensuring continuous monitoring using fully automated equipment is an uncovered yet urgent need. There are several devices already in the market capable of monitoring vital signs, but they are not specifically designed for these type of patients and they can be expensive and/or difficult to integrate with other systems from a software perspective. The work described in this paper gives answers to these necessities with the introduction of a low-cost system, targeted at psychiatric patients, for the acquisition and wireless transmission in real-time of physiological parameters, making use of micro-controllers for collecting and processing sensor data, and WiFi technology to upload the information to the server where a patient’s profile with all the relevant vital parameters resides. In addition to data collection and processing, an application aimed at use by nursing staff has also been developed to raise alerts in case any critical condition is detected.
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Fidia Ardiani, Dinda, Daniel Happy Putra, Adi Widodo, and Noor Yulia. "Literature Review: Overview of Integrated Health Information System Management in Hospitals." KESANS : International Journal of Health and Science 1, no. 6 (March 20, 2022): 589–602. http://dx.doi.org/10.54543/kesans.v1i6.68.
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The Health Information System was developed primarily to support health management. The information system used is more focused on a computer-based information system supported by a medical record unit. Electronic Medical Record is the use of information technology devices for collecting, storing, processing and accessing data stored in patient medical records in hospitals in a data-based management system that collects various medical data sources. In managing the health information system, providing access to patient data in digital format, it is hoped that it will make it easier for medical officers to track patient data from time to time, making it easier to obtain patient health information. The process of implementing the system management in this study can be divided into five things, namely: 1.Human Resources, 2.Policies and institutions, 3. System implementation, 4. Data and its management, 5. Access and data integration. This serves to improve the quality of comprehensive health services to patients and medical personnel in helping to provide better health services. In the integrated patient health information system management model, it must provide access to patient health information and allow the exchange of data managed by several medical officers, patient data managers and other hospitals. This is supported by a health information system equipped with a data security system and support from the head of the hospital.
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Hsu, Shih-Yen, Tai-Been Chen, Wei-Chang Du, Jyh-Horng Wu, and Shih-Chieh Chen. "Integrate Weather Radar and Monitoring Devices for Urban Flooding Surveillance." Sensors 19, no. 4 (February 17, 2019): 825. http://dx.doi.org/10.3390/s19040825.
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With the increase of extreme weather events, the frequency and severity of urban flood events in the world are increasing drastically. Therefore, this study develops ARMT (automatic combined ground weather radar and CCTV (Closed Circuit Television System) images for real-time flood monitoring), which integrates real-time ground radar echo images and automatically estimates a rainfall hotspot according to the cloud intensity. Furthermore, ARMT combines CCTV image capturing, analysis, and Fourier processing, identification, water level estimation, and data transmission to provide real-time warning information. Furthermore, the hydrograph data can serve as references for relevant disaster prevention, and response personnel may take advantage of them and make judgements based on them. The ARMT was tested through historical data input, which showed its reliability to be between 83% to 92%. In addition, when applied to real-time monitoring and analysis (e.g., typhoon), it had a reliability of 79% to 93%. With the technology providing information about both images and quantified water levels in flood monitoring, decision makers can quickly better understand the on-site situation so as to make an evacuation decision before the flood disaster occurs as well as discuss appropriate mitigation measures after the disaster to reduce the adverse effects that flooding poses on urban areas.
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Peruzzi, Giacomo, Alessandro Pozzebon, and Mattia Van Der Meer. "Fight Fire with Fire: Detecting Forest Fires with Embedded Machine Learning Models Dealing with Audio and Images on Low Power IoT Devices." Sensors 23, no. 2 (January 10, 2023): 783. http://dx.doi.org/10.3390/s23020783.
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Forest fires are the main cause of desertification, and they have a disastrous impact on agricultural and forest ecosystems. Modern fire detection and warning systems rely on several techniques: satellite monitoring, sensor networks, image processing, data fusion, etc. Recently, Artificial Intelligence (AI) algorithms have been applied to fire recognition systems, enhancing their efficiency and reliability. However, these devices usually need constant data transmission along with a proper amount of computing power, entailing high costs and energy consumption. This paper presents the prototype of a Video Surveillance Unit (VSU) for recognising and signalling the presence of forest fires by exploiting two embedded Machine Learning (ML) algorithms running on a low power device. The ML models take audio samples and images as their respective inputs, allowing for timely fire detection. The main result is that while the performances of the two models are comparable when they work independently, their joint usage according to the proposed methodology provides a higher accuracy, precision, recall and F1 score (96.15%, 92.30%, 100.00%, and 96.00%, respectively). Eventually, each event is remotely signalled by making use of the Long Range Wide Area Network (LoRaWAN) protocol to ensure that the personnel in charge are able to operate promptly.
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Kucera, Matej, Miroslav Gutten, Milan Simko, Milan Sebok, Daniel Korenciak, Roman Jarina, and Martin Pitonak. "Electromagnetic Compatibility and Radiation Analysis in Control Room." Measurement Science Review 19, no. 3 (June 1, 2019): 126–31. http://dx.doi.org/10.2478/msr-2019-0018.
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Abstract The article presents a theoretical analysis of electromagnetic compatibility (EMC) and experimental measurement of effects of radiation and acoustic emission of high-voltage transformers for electronic equipment and working personnel in a control room. Electromagnetic compatibility and safety of equipment are not considered as two distinct areas of study in electric and electronic safety. Economic criteria cannot compromise safety but at the same time immunity levels must be relevant in order to establish a “Functional Safety”. Introducing Special Immunity Levels in the level of equipment testing allows us to combine the two areas of EMC and safety. The measurement was carried out in high-current of very high-voltage distribution station. A real-life analysis of effects of electric and electromagnetic field was carried out. FFT was used for mathematical processing of data which were later presented in a graphical form of a spectrally analyzed area. In the last part of the paper we discuss the suitability of acoustic camera to perform contactless monitoring of the health and operation conditions of the power transformer by analyzing acoustic field generated by the transformer core and windings in near control room.
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Wang, Liunai, Wen Jiang, and Weiwei Dong. "Design of an Underground Transmission Line Condition Fault Monitoring System for Power Grids Based on Data Analysis Algorithms." Journal of Sensors 2022 (October 12, 2022): 1–11. http://dx.doi.org/10.1155/2022/1161022.
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With the continuous expansion of the scale, capacity, and coverage of the modern transmission network, the role of the power system in the national economy is increasingly prominent, and the disconnection of the power system will have a huge impact on society and people’s lives. Due to the long transport distance and wide coverage of transmission lines, natural conditions and human factors have caused great difficulties in line operation and maintenance. How to effectively improve the operation and maintenance of transmission lines to ensure the stability and safety of the power grid has become a common problem for the power industry and scientific researchers to discuss. In recent years, the information society has stepped into the era of big data, and big data has developed rapidly, becoming a hot area favored by academia and industry, and is widely used. Through big data analysis, potential operation rules can be discovered from a large amount of grid information, providing maintenance personnel with corresponding maintenance decision support. Using big data technology for transmission line fault analysis can effectively reduce accident processing time and avoid accident expansion. Therefore, this paper combines the underground transmission line fault of power grid with the fuzzy KNN algorithm model to apply the underground transmission line state intelligent monitoring system and conducts the study of real-time data collection and fault diagnosis analysis of the underground transmission line fault of power grid, and this paper conducts the transmission line fault analysis experiment, which fully confirms the feasibility and effectiveness of the algorithm model proposed in the paper and concludes that the data analysis model proposed in this paper. The proposed data analysis model has good innovation and practical feasibility.
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Wu, Xingchen, Tianyu Gao, and Guodong Lee. "Method of Differential-Based Remote Upgrade for ECUs on Vehicles*." Journal of Physics: Conference Series 2216, no. 1 (March 1, 2022): 012004. http://dx.doi.org/10.1088/1742-6596/2216/1/012004.
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Abstract In view of the problem that the current update flashing of the traditional automotive electronic control unit (ECU) software highly relies on professional maintenance personnel and external equipment, a method for ECU remote data flashing is proposed to achieve remote and efficient upgrade of ECU software. Furthermore, through the introduction of backup partitions and differential upgrade methods, the problems of lack of fault-tolerant processing, high bandwidth requirements and low efficiency in traditional ECU software update flashing are also solved. In this article, a remote update system is built, including the server-side and the vehicle, and the interface and communication protocols are defined based on HTTPS. The above methods have been verified on NXP IMX 6 platform. Associated testing of the simulation of the ECU by the STM32 and ROCKCHIP demo board has been made based on the CAN and Ethernet simulating the vehicle network architecture. By the real data catching from Ethernet and the CAN, the details of the log file of the programs’ event tracking information are analyzed to obtain the experimental results. The results indicated that the incremental remote data updating system built in this article can remotely update the CAN software accurately and efficiently in all simulation tests, which proved the practicability, accuracy, and efficiency of this method.
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Juliani, Juliani, Bachtiar Efendi, and Rika Nofitri. "Implementasi E-KGB PNS Pada Pemerintah Kabupaten Asahan (Studi BKD Kabupaten Asahan)." JUTSI (Jurnal Teknologi dan Sistem Informasi) 2, no. 1 (June 7, 2021): 121–26. http://dx.doi.org/10.33330/jutsi.v2i1.1149.
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Abstract: Periodic salary increases are very important given to Civil Servants who have reached the group working period, which is every two years and if they have fulfilled the requirements based on laws and regulations. Regional Personnel Agency of Asahan Regency still uses word processing software, such as Microsoft Office Word to process decree of periodic salary increase. This allows delays to generate of decrees and periodic salary increases reports. In this research using UML as a system modeling language, MySQL as a database, and PHP as a programming language. The results of this research are electronic applications of periodic salary increases that can be used by staffing Information and Documentation staff easily and more efficiently to generate decrees and periodic salary increase reports. Whereas the Civil Servants can input data and upload requirement for periodic salary increases without the need to come to the Regional Personnel Agency of Asahan Regency. Keywords: Periodic Salary Increases, Electronic Application, MySQL, PHP Abstrak: Kenaikan gaji berkala sangat penting diberikan kepada Pegawai Negeri Sipil (PNS) yang telah mencapai masa kerja golongan yaitu setiap dua tahun sekali dan apabila telah memenuhi persyaratan berdasarkan peraturan perundang – undangan. Badan Kepegawaian Daerah (BKD) Kabupaten Asahan masih menggunakan software pengolah kata, seperti Microsoft Office Word untuk proses surat keputusan kenaikan gaji berkala. Hal ini memungkinkan terjadinya keterlambatan untuk menghasilkan surat keputusan dan laporan kenaikan gaji berkala. Dalam penelitian ini menggunakan UML sebagai bahasa pemodelan sistem, MySQL sebagai database, dan PHP sebagai bahasa pemrogramannya. Hasil dari penelitian ini adalah aplikasi elektronik kenaikan gaji berkala (E-KGB) yang dapat digunakan oleh staf Informasi dan Dokumentasi Kepegawaian dengan mudah dan lebih efisiensi untuk menghasilkan surat keputusan dan laporan kenaikan gaji berkala. Sedangkan Pegawai Negeri Sipil dapat melakukan input data dan upload syarat kenaikan gaji berkala tanpa perlu datang ke Badan Kepegawaian Daerah (BKD) Kabupaten Asahan. Kata kunci: Kenaikan Gaji Berkala, Aplikasi Elektronik, MySQL, PHP
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Zheregelya, A. V. "FEATURES OF DIGITALIZATION OF RELATIONSHIPS IN THE INDUSTRIAL MARKET." Vestnik Universiteta, no. 1 (March 23, 2020): 12–15. http://dx.doi.org/10.26425/1816-4277-2020-1-12-15.
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The digital economy is an economic activity, the key factor of which are digital data, automatic processing and use of analysis results that make it possible to improve significantly the quality and productivity of labor in comparison with traditional forms of management. Transformational digital processes affect the infrastructural foundations, associated with new communication mechanisms, trading platforms, electronic payments and document management. The most tangible results of digitalization in the industrial market, where there are factors restricting the development of digitalization, which leads to the lack of development of a digital business paradigm, that provokes the destabilization of existing and established relationships of real processes. Currently, there is a radical shift in the production paradigm towards automation, the introduction of information and computing systems that allow us replace human labor with a program, which is especially noticeable in the activities of the accounting, personnel, planning department at the enterprise. However, the issues of security, protectability, stability, continuity, integrity and reliability of operations and work with information are of particular importance, which makes high demands on the digital shell of the enterprise.
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Kovalenko, O. S., L. M. Kozak, E. V. Gorshkov, M. Najafian Tumajani, and T. A. Maresova. "Integration Environment Software Module for Accumulation and Exchange of Digital Medical Data." Control Systems and Computers, no. 5-6 (295-296) (December 2021): 88–99. http://dx.doi.org/10.15407/csc.2021.05-06.088.
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Introduction. The development of effective digital medicine tools is an intensive and complex process that requires the interdisciplinary efforts of a wide range of experts, from scientists and engineers to ethics experts and lawyers. Digital medicine products have great potential for improving medical measurement, diagnosis and treatment. One of the main challenges for the healthcare sector is to address the issue of fast, convenient and secure exchange of information about patients’ health. Service-oriented architectures of such products may accomplish many of the challenges facing healthcare systems. The purpose of the paper is to develop an information and software module ExchangeDMD to ensure the accumulation, storage and exchange of diagnostic medical data in accordance with modern medical information standards to maintain the interoperability function as one of the leading principles of digital medicine. Results. A special adaptive architecture of digital medicine infrastructure has been developed, which enables an integrated solution of data exchange between participants of providing medical services, which is carried out with the help of web services. The specifics of different types of medical information are analyzed and taken into account in accordance with the access regime for its processing. The module structure has been developed and implemented in software, which has three main levels: central virtual storage (virtual data center to implement certain functions), remote administration segment (technical support and administration network) and user segment (mobile devices and user-patient applications). Conclusions. The ExchangeDMD information and software module is designed to ensure the accumulation of patient data, integration between the various units within the system, as well as to ensure the management of this data by health care personnel. The ExchangeDMD module is built using the international standard HL7 CDA, which enables formalizing electronic medical records using RIM (information model links) to attract the necessary directories and classifiers when creating medical records and documents.
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Shammugam, Inthrani, Ganthan Narayana Samy, Pritheega Magalingam, Nurazean Maarop, Sundresan Perumal, and Bharanidharan Shanmugam. "Information security threats encountered by Malaysian public sector data centers." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 3 (March 10, 2021): 1820. http://dx.doi.org/10.11591/ijeecs.v21.i3.pp1820-1829.
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<span>D</span><span lang="EN-AU">ata centers are primarily the main targets of cybercriminals and security threats as they host various critical information and communication technology (ICT) services. Identifying the threats and </span><span>managing the risks associated with data centers have become a major challenge as this will enable organizations to optimize their resources to focus on the most hazardous threats to prevent the potential risks and damages. The objective of this paper is to identify major ICT security threats to data centers in the Malaysian public sector and their causes. The data for this study was collected through interview sessions. A total of 33 respondents from various government organizations were interviewed. The results revealed that the technical threats, </span><span lang="EN-MY">spyware, phishing, bluesnarfing threats, social engineering and virus, trojan, malware, ransomware, viral websites threats are the major categories of threats often encountered by the malaysian public sector organizations. The</span><span> causes for these threats </span><span lang="EN-MY">are lack of budget, competent personnel, and manpower for security tasks, user awareness; lack of </span><span>compliances and monitoring; insufficient security policies and procedures as well as deliberate cyber attacks. The outcome of this study will give a greater degree of awareness and understanding to the ICT security officers, who are entrusted with data center security.</span>
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Kamasetty, Badarinath, Mahesh Renduchintala, Lochan Lingaraja Shetty, Suresh Chandarshekar, and Rajashree Shettar. "Design and development of portable smart traffic signaling system with cloud-artificial intelligence enablement." Indonesian Journal of Electrical Engineering and Computer Science 26, no. 1 (April 1, 2022): 116. http://dx.doi.org/10.11591/ijeecs.v26.i1.pp116-126.
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With increasing traffic, <span lang="EN-US">apart from the major traffic junctions, there are few smaller junctions which witness heavy traffic only during a certain period of the day. For such cases, deploying of conventional traffic lights are not a viable option. A cost-effective internet of things (IoT) enabled portable smart traffic signaling system is designed using ESP32 dual core microcontroller, to assist traffic personnel working at small traffic junctions. It uses a foldable mechanical structure which can be carried easily. The system is designed to work with and without internet connectivity depending on its functionality and place of deployment. The system can be pre-programmed with default time value to work without human intervention. Using an android application, the user can manually control the traffic signal by analysing the traffic density. System gathers the traffic density information based on the operations performed by the traffic personnel and stores it in the cloud. In Smart mode, system computes the mean value and also runs K-means clustering algorithm on the dataset to generate optimized time values. Comparison of the data generated using manual and automatic modes infer the credibility of the system in generating optimized time values and reducing human effort.</span>
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Zhu, Rong, Zhaohui Chen, Jingshuai Liu, Tao Zhu, and Xuan Du. "Intelligent Online Partial Discharge Detection and Sensor." Wireless Communications and Mobile Computing 2022 (September 14, 2022): 1–8. http://dx.doi.org/10.1155/2022/7432750.
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In order to realize the online monitoring of partial discharge in solid switch cabinet, obtain the real partial discharge power and evaluate the insulation status of the switch cabinet, an online detection device based on partial discharge in solid switch cabinet was proposed. The ultrasonic sensor and resonant circuit used by the device to collect the high frequency signal generated when partial discharge occurs and the high frequency signal was converted into the voltage signal. The voltage signal was sent to the STM32 main control chip after data preprocessing and analog-to-digital conversion. Through the conversion of the collected electrical data, the local discharge quantity was obtained and displayed on LCD screen in real time. If the detected discharge power was greater than a set value, an alarm would be automatically issued to remind the on-site power personnel to pay attention to it and prevent major power accidents caused by insulation damage. From the experimental results, it was found that the value of intermittent partial discharge collected by the developed device was 63pC, which was basically consistent with the DMS data. The experimental results showed that the device had the characteristics of simple operation and signal processing speed, high testing data real-time, and low cost, which was suitable for the real-time monitoring of the high voltage equipment in internal partial discharge. It was convenient for operators to maintain the equipment and ensure the normal operation of the equipment, which was of great significance to improve the reliability of power supply.
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Hożyń, Stanisław. "A Review of Underwater Mine Detection and Classification in Sonar Imagery." Electronics 10, no. 23 (November 26, 2021): 2943. http://dx.doi.org/10.3390/electronics10232943.
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Underwater mines pose extreme danger for ships and submarines. Therefore, navies around the world use mine countermeasure (MCM) units to protect against them. One of the measures used by MCM units is mine hunting, which requires searching for all the mines in a suspicious area. It is generally divided into four stages: detection, classification, identification and disposal. The detection and classification steps are usually performed using a sonar mounted on a ship’s hull or on an underwater vehicle. After retrieving the sonar data, military personnel scan the seabed images to detect targets and classify them as mine-like objects (MLOs) or benign objects. To reduce the technical operator’s workload and decrease post-mission analysis time, computer-aided detection (CAD), computer-aided classification (CAC) and automated target recognition (ATR) algorithms have been introduced. This paper reviews mine detection and classification techniques used in the aforementioned systems. The author considered current and previous generation methods starting with classical image processing, and then machine learning followed by deep learning. This review can facilitate future research to introduce improved mine detection and classification algorithms.
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Li, Xiaoguang. "Optimization of Accounting Information System for Enterprises in Smart City by Intelligent Sensor under the Internet of Things." Wireless Communications and Mobile Computing 2022 (February 25, 2022): 1–11. http://dx.doi.org/10.1155/2022/6205940.
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In order to realize the continuous optimization of the enterprise financial accounting information system of the smart city, from the perspective of intelligent sensor technology, firstly, this paper understands the use feelings of the enterprise financial accounting-related personnel about the information system in the smart city based on the relevant theories of intelligent sensor, smart city, and accounting information. Secondly, the Internet of things technology and intelligent sensing technology are applied to the optimization of enterprise financial accounting information system. Finally, the corresponding opinions and suggestions are put forward from the perspectives of government, employees, and enterprises. The results show that about 40%∼60% of enterprise financial accountants believe that data integration and sharing, data governance, and data operation management systems need to be continuously optimized and upgraded. Applying the Internet of things technology and intelligent sensing technology to the optimization of enterprise financial accounting information system, it is found that it can not only improve the accuracy of financial data processing, but also receive the required results efficiently and in real time. It is more important to apply intelligent sensing technology to enterprise financial information system. After comparison, it is found that the net profit of the enterprise increased from 112.69 million yuan to 3329.33 million yuan. The owner’s equity of the enterprise increased from 2045.68 million yuan to 11177.34 million yuan. The cash flow of the enterprise increased from 1056.91 million yuan to 6892.56 million yuan. Therefore, this paper studies how to optimize the enterprise financial accounting information system based on the intelligent sensor of the Internet of things in the smart city, which has great reference significance for the management of enterprise financial operation.
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Alam, Arif Ul, Dennis Clyne, and M. Jamal Deen. "A Low-Cost Multi-Parameter Water Quality Monitoring System." Sensors 21, no. 11 (May 29, 2021): 3775. http://dx.doi.org/10.3390/s21113775.
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Multi-parameter water quality monitoring is crucial in resource-limited areas to provide persistent water safety. Conventional water monitoring techniques are time-consuming, require skilled personnel, are not user-friendly and are incompatible with operating on-site. Here, we develop a multi-parameter water quality monitoring system (MWQMS) that includes an array of low-cost, easy-to-use, high-sensitivity electrochemical sensors, as well as custom-designed sensor readout circuitry and smartphone application with wireless connectivity. The system overcomes the need of costly laboratory-based testing methods and the requirement of skilled workers. The proposed MWQMS system can simultaneously monitor pH, free chlorine, and temperature with sensitivities of 57.5 mV/pH, 186 nA/ppm and 16.9 mV/°C, respectively, as well as sensing of BPA with <10 nM limit of detection. The system also provides seamless interconnection between transduction of the sensors’ signal, signal processing, wireless data transfer and smartphone app-based operation. This interconnection was accomplished by fabricating nanomaterial and carbon nanotube-based sensors on a common substrate, integrating these sensors to a readout circuit and transmitting the sensor data to an Android application. The MWQMS system provides a general platform technology where an array of other water monitoring sensors can also be easily integrated and programmed. Such a system can offer tremendous opportunity for a broad range of environmental monitoring applications.
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Chouvarda, I., V. Koutkias, S. Meletiadis, K. Haris, E. A. Balas, and N. Maglaveras. "Information Technology Can Enhance Quality in Regional Health Delivery." Methods of Information in Medicine 41, no. 05 (2002): 393–400. http://dx.doi.org/10.1055/s-0038-1634368.
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Summary Objectives: a) The use of information technology (IT) based solutions for quality health delivery in regional health information networks and the study of the enabling factors for their use in a regional health care network from key classes of users such as the medical personnel and the citizens. b) Identification of potential technologies for usage from all citizens and health providers in a regional environment, in all aspects of everyday life. c) Presentation of a generic user model for reference when developing and assessing IT based health delivery solutions. Methods: After defining the major questions to be addressed, an overview of tele-health and tele-medicine technologies and solutions currently available shall be presented. Further, a generic user model applied to the use of IT based regional health delivery solutions both for the daily life and home care, and for research and clinical routine purposes are presented. Enabling technologies for integration of different IT modules, medical data processing and management procedures and the wireless application protocol (WAP) technology is discussed. Results: Different levels of user applications are presented such as mobile telephony driven health information monitoring and systems integrating electronic health care records with multimedia medical information management and processing modules. Conclusions: Although IT solutions are advanced and continue to evolve, still the user acceptance and user friendliness issues are unresolved. Mobile telecommunication solutions however may hold the key for wide scale implementation of IT solutions in regional health information networks and increased quality of health services.
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Nikiforov, O. V., O. G. Dodonov, and V. G. Putyatin. "The use of information technologies in risk management for the flight safety of aviation." Mathematical machines and systems 1 (2021): 32–41. http://dx.doi.org/10.34121/1028-9763-2021-1-32-41.
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At present, the problem of ensuring the necessary level of state aviation flights safety in terms of hu-man and organizational factors is very urgent. Despite the ongoing measures aimed at expanding and strengthening control over the processes of aviation activity, flight incidents caused by insufficient reli-ability of personnel work and organizational errors continue to occupy leading positions. There is an in-sufficient efficiency of the flight safety management system to identify hazardous factors in their latent stage, which is necessary for the early prevention of accidents. The difficulty of timely identification of the aviation system dangerous states associated with these factors is due to the need to account, corre-late and analyze data of a very large dimension and multifacetedness. According to the authors, a suc-cessful solution to this problem is possible through the use of automated processing and cognitive com-bination of large heterogeneous information arrays based on centralized electronic systems for collect-ing, information and analytical processing and storage of information about the functioning of the avia-tion system, identified abnormal and dangerous conditions, and incidents that have already occurred. The article presents the concept of creating a promising automated flight safety management system for state aviation. The proposed system will make it possible to implement the principle of proactive detec-tion and prevention of hazardous factors and risks for flight safety, taking into account human and or-ganizational factors, based on the implementation of processes for centralized collection, generalization and analysis of big data on the state of the aviation system. Topical scientific tasks for the creation of a methodological basis for the development of special software for such an automated system have been formulated.
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Su, Chen, and Wenting Chen. "Design of Remote Real-Time Monitoring and Control Management System for Smart Home Equipment Based on Wireless Multihop Sensor Network." Journal of Sensors 2022 (June 8, 2022): 1–10. http://dx.doi.org/10.1155/2022/6228440.
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With the intensification of the pace of modern urban life and the increase of work pressure, people have higher requirements for the safety and comfort of home. However, the rapid development of Internet of Things technology, wireless communication technology, embedded technology, and data fusion technology has made this desire possible, thus making intelligent and safe. Using wireless sensor network, intelligent home system can realize the real-time collection of object location and state information, remote operation of home equipment, as well as the monitoring of the information of personnel activities, etc. However, how to efficiently analyze and integrate these information to be applied to the intelligent home system is one of the problems that need to be solved; further study of the smart home system of personal behavior identifies fire monitoring and remote monitoring of mining applications. Such information collection and integration of technology and method are given based on wireless sensor network transfer of key technologies; intelligent home security monitoring system based on Bayesian networks is proposed and a card. According to the theoretical fire monitoring method, and based on the Bayesian belief network personal behavior identification model, this paper provides the theory and method for the remote safety monitoring and control in the intelligent home environment. In this paper, based on the multisensor data fusion of smart home security, real-time monitoring alarm platform is built. Through the multisensor detection module for the home fire gas human infrared monitoring, the detected data is transmitted to the data fusion center for processing; processed results are uploaded to the cloud through the Internet. When abnormal conditions occur, users can log in to the mobile phone client to view abnormal alarm results.
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Ali, Aitizaz, Hasliza A. Rahim, Muhammad Fermi Pasha, Rafael Dowsley, Mehedi Masud, Jehad Ali, and Mohammed Baz. "Security, Privacy, and Reliability in Digital Healthcare Systems Using Blockchain." Electronics 10, no. 16 (August 23, 2021): 2034. http://dx.doi.org/10.3390/electronics10162034.
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According to the security breach level index, millions of records are stolen worldwide on every single day. Personal health records are the most targeted records on the internet, and they are considered sensitive, and valuable. Security and privacy are the most important parameters of cryptography and encryption. They reduce the availability of data on patients and healthcare to the appropriate personnel and ultimately lead to a barrier in the transfer of healthcare into a digital health system. Using a permission blockchain to share healthcare data can reduce security and privacy issues. According to the literature, most healthcare systems rely on a centralized system, which is more prone to security vulnerabilities. The existing blockchain-based healthcare schemes provide only a data-sharing framework, but they lack security and privacy. To cope with these kinds of security issues, we have designed a novel security algorithm that provides security as well as privacy with much better efficiency and a lower cost. Hence, in this research, we have proposed a patient healthcare framework that provides greater security, reliability, and authentication compared to existing blockchain-based access control.
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Kim, Dae-Yeon, Dong-Sik Choi, Jaeyun Kim, Sung Wan Chun, Hyo-Wook Gil, Nam-Jun Cho, Ah Reum Kang, and Jiyoung Woo. "Developing an Individual Glucose Prediction Model Using Recurrent Neural Network." Sensors 20, no. 22 (November 12, 2020): 6460. http://dx.doi.org/10.3390/s20226460.
Full textAbstract:
In this study, we propose a personalized glucose prediction model using deep learning for hospitalized patients who experience Type-2 diabetes. We aim for our model to assist the medical personnel who check the blood glucose and control the amount of insulin doses. Herein, we employed a deep learning algorithm, especially a recurrent neural network (RNN), that consists of a sequence processing layer and a classification layer for the glucose prediction. We tested a simple RNN, gated recurrent unit (GRU), and long-short term memory (LSTM) and varied the architectures to determine the one with the best performance. For that, we collected data for a week using a continuous glucose monitoring device. Type-2 inpatients are usually experiencing bad health conditions and have a high variability of glucose level. However, there are few studies on the Type-2 glucose prediction model while many studies performed on Type-1 glucose prediction. This work has a contribution in that the proposed model exhibits a comparative performance to previous works on Type-1 patients. For 20 in-hospital patients, we achieved an average root mean squared error (RMSE) of 21.5 and an Mean absolute percentage error (MAPE) of 11.1%. The GRU with a single RNN layer and two dense layers was found to be sufficient to predict the glucose level. Moreover, to build a personalized model, at most, 50% of data are required for training.
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Yoo, Lee-Sun, Jung-Han Lee, Yong-Kuk Lee, Seom-Kyu Jung, and Yosoon Choi. "Application of a Drone Magnetometer System to Military Mine Detection in the Demilitarized Zone." Sensors 21, no. 9 (May 3, 2021): 3175. http://dx.doi.org/10.3390/s21093175.
Full textAbstract:
We propose a magnetometer system fitted on an unmanned aerial vehicle (UAV, or drone) and a data-processing method for detecting metal antipersonnel landmines (M16) in the demilitarized zone (DMZ) in Korea, which is an undeveloped natural environment. The performance of the laser altimeter was improved so that the drone could fly at a low and stable altitude, even in a natural environment with dust and bushes, and a magnetometer was installed on a pendulum to minimize the effects of magnetic noise and vibration from the drone. At a flight altitude of 1 m, the criterion for M16 is 5 nT. Simple low-pass filtering eliminates magnetic swing noise due to pendulum motion, and the moving average method eliminates changes related to the heading of the magnetometer. Magnetic exploration was conducted in an actual mine-removal area near the DMZ in Korea, with nine magnetic anomalies of more than 5 nT detected and a variety of metallic substances found within a 1-m radius of each detection site. The proposed UAV-based landmine detection system is expected to reduce risk to detection personnel and shorten the landmine-detection period by providing accurate scientific information about the detection area prior to military landmine-detection efforts.
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Al-qudah, Rabiah, Yaser Khamayseh, Monther Aldwairi, and Sarfraz Khan. "The Smart in Smart Cities: A Framework for Image Classification Using Deep Learning." Sensors 22, no. 12 (June 10, 2022): 4390. http://dx.doi.org/10.3390/s22124390.
Full textAbstract:
The need for a smart city is more pressing today due to the recent pandemic, lockouts, climate changes, population growth, and limitations on availability/access to natural resources. However, these challenges can be better faced with the utilization of new technologies. The zoning design of smart cities can mitigate these challenges. It identifies the main components of a new smart city and then proposes a general framework for designing a smart city that tackles these elements. Then, we propose a technology-driven model to support this framework. A mapping between the proposed general framework and the proposed technology model is then introduced. To highlight the importance and usefulness of the proposed framework, we designed and implemented a smart image handling system targeted at non-technical personnel. The high cost, security, and inconvenience issues may limit the cities’ abilities to adopt such solutions. Therefore, this work also proposes to design and implement a generalized image processing model using deep learning. The proposed model accepts images from users, then performs self-tuning operations to select the best deep network, and finally produces the required insights without any human intervention. This helps in automating the decision-making process without the need for a specialized data scientist.
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Roberts, Karen. "From Field to Filed: Minimising and Mitigating Risks of Data Error and Loss in a Vertebrate Zoology Collection." Biodiversity Information Science and Standards 2 (June 13, 2018): e26344. http://dx.doi.org/10.3897/biss.2.26344.
Full textAbstract:
One of the key risks identified for the Vertebrate Zoology (VZ) Collections at Museums Victoria has been data error, loss and dissociation. These risks are highest during the stages involved in preparing the specimen for lodgement in the collection (from collecting and accession of the specimen, to preparation, labelling and so on). The VZ Collections data are managed through an electronic collection information system (EMu) but the process of data transferral and input can be time-consuming and error-prone at many steps along the way. The two main methods of specimen acquisition in the Mammalogy, Ornithology and Herpetology collections in recent years have been internal field programs and external stakeholder donations. Prior to 2012, most specimen data from both of these methods of acquisition were handwritten and transcribed one or more times by multiple people before a specimen ended up in the primary database. An assortment of other identifying numbers or codes were used prior to a collection number being assigned, and sometimes these have been difficult to match up or reconcile. The amount of time needed to enter this information manually also increased the risk of data dissociation and specimen misplacement, as it could significantly delay getting specimens lodged correctly in the collection. Since 2012, a number of steps have been taken by the VZ Collection staff to reduce these risks and streamline data processing. For internal field programs in Mammalogy and Ornithology, a field data-collecting tool has been developed using FileMaker Pro. This enables direct input of specimen and field data into our FileMaker field database using the FileMaker Go app on iPad that is then exportable to an Excel spreadsheet for upload to EMu. Specimens are given field numbers initially, and a collection number once at the museum. Data processing is simplified as most specimens undergo full preparation in the field. We have also developed an upload spreadsheet in Excel that can be used by internal or external researchers who are lodging bulk lots of specimens. Thus we receive the mandatory data we require, and it is already in a format we can easily upload to EMu. For external stakeholder donations, preparation is completed at the museum so all data available upon donation are entered directly into EMu. A collection registration number is applied as soon as a specimen is accessioned so there is only one number required to track it during and after preparation. All specimen-related data generated during preparation are still handwritten and then transcribed direct to the electronic catalogue record by collection managers. These procedures continue to be refined, but have significantly enhanced specimen and associated data management. Accidental data loss through technical issues, for example possible iPad data-loss before backup, human error at data input stage such as overwriting a record, or incorrectly assigning field number, have been minimal. Also, we will continue to decrease the need for data transcription by encouraging internal and external researchers to use our data-upload spreadsheet, and training preparation staff to enter specimen data directly into the specimen catalogue record in EMu.
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Sudakov, Aleksandr N. "Prospects for the Use of Digital Technologies in the Work of a Poultry Zootechnician." Elektrotekhnologii i elektrooborudovanie v APK 48, no. 4 (December 2021): 95–102. http://dx.doi.org/10.22314/2658-4859-2021-68-4-95-102.
Full textAbstract:
Digitalization of technological processes makes it possible to optimize the cost for the poultry products. The low level of digitalization in determining the state of the poultry livestock is due to a significant amount of organoleptic research in the work of a zootechnician-poultry breeder. The absence of numerical indicators of controlled parameters entails a subjective assessment, limits the amount of information when transmitting data via electronic communication channels, complicates the process of training specialized personnel, reduces the efficiency of resources consumed (feed, heat and electricity, and others). (Research purpose) The research purpose is to study the prospects of digitalization of the functions of zootechnics in the optimization of technological processes of poultry farming. (Materials and methods) For the research, there were used documentary research, data analysis, and search experiments. (Results and discussion) The shortcomings of existing methods of determining the quality and comfort of livestock maintenance and its condition were revealed by the example of current recommendations on the content of highly productive meat of cross chickens. The following components of keeping poultry have the potential for optimization: maintaining the microclimate in the poultry house, veterinary care, wages, repair of fixed assets. The large amounts of digital data obtained by instrumental means for monitoring zootechnical indicators of poultry have the wide using possibilities. (Conclusions) The article presents a list of technical analogues of organoleptic control methods based on the use of thermal imaging equipment, video analytics, acoustic sensors, indirect signs using traditional technical control data. The article proposes an algorithm for processing large data arrays, which allows to increase the optimization of technological processes. Described modern technical solutions in the field of agricultural automation have wide prospectives.
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Yang, Nachuan, Yongjun Zhao, and Jinyang Chen. "Real-Time Φ-OTDR Vibration Event Recognition Based on Image Target Detection." Sensors 22, no. 3 (February 2, 2022): 1127. http://dx.doi.org/10.3390/s22031127.
Full textAbstract:
Accurate and fast identification of vibration signals detected based on the phase-sensitive optical time-domain reflectometer (Φ-OTDR) is crucial in reducing the false-alarm rate of the long-distance distributed vibration warning system. This study proposes a computer vision-based Φ-OTDR multi-vibration events detection method in real-time, which can effectively detect perimeter intrusion events and reduce personnel patrol costs. Pulse accumulation, pulse cancellers, median filter, and pseudo-color processing are employed for vibration signal feature enhancement to generate vibration spatio-temporal images and form a customized dataset. This dataset is used to train and evaluate an improved YOLO-A30 based on the YOLO target detection meta-architecture to improve system performance. Experiments show that using this method to process 8069 vibration data images generated from 5 abnormal vibration activities for two types of fiber optic laying scenarios, buried underground or hung on razor barbed wire at the perimeter of high-speed rail, the system mAP@.5 is 99.5%, 555 frames per second (FPS), and can detect a theoretical maximum distance of 135.1 km per second. It can quickly and effectively identify abnormal vibration activities, reduce the false-alarm rate of the system for long-distance multi-vibration along high-speed rail lines, and significantly reduce the computational cost while maintaining accuracy.
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Wong, Boon, and Julie A. McCann. "Failure Detection Methods for Pipeline Networks: From Acoustic Sensing to Cyber-Physical Systems." Sensors 21, no. 15 (July 21, 2021): 4959. http://dx.doi.org/10.3390/s21154959.
Full textAbstract:
Pipeline networks have been widely utilised in the transportation of water, natural gases, oil and waste materials efficiently and safely over varying distances with minimal human intervention. In order to optimise the spatial use of the pipeline infrastructure, pipelines are either buried underground, or located in submarine environments. Due to the continuous expansion of pipeline networks in locations that are inaccessible to maintenance personnel, research efforts have been ongoing to introduce and develop reliable detection methods for pipeline failures, such as blockages, leakages, cracks, corrosion and weld defects. In this paper, a taxonomy of existing pipeline failure detection techniques and technologies was created to comparatively analyse their respective advantages, drawbacks and limitations. This effort has effectively illuminated various unaddressed research challenges that are still present among a wide array of the state-of-the-art detection methods that have been employed in various pipeline domains. These challenges include the extension of the lifetime of a pipeline network for the reduction of maintenance costs, and the prevention of disruptive pipeline failures for the minimisation of downtime. Our taxonomy of various pipeline failure detection methods is also presented in the form of a look-up table to illustrate the suitability, key aspects and data or signal processing techniques of each individual method. We have also quantitatively evaluated the industrial relevance and practicality of each of the methods in the taxonomy in terms of their respective deployability, generality and computational cost. The outcome of the evaluation made in the taxonomy will contribute to our future works involving the utilisation of sensor fusion and data-centric frameworks to develop efficient, accurate and reliable failure detection solutions.