Готові списки джерел за темами / Work environment Data processing

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Добірка наукової літератури з теми "Work environment Data processing"

Автор: Grafiati

Опубліковано: 10 грудня 2022

Оновлено: 28 січня 2023

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Статті в журналах з теми "Work environment Data processing"

Smith, Robert, Emad Hemyari, Andrey Bakulin, and Abdullah Alramadhan. "Making seismic monitoring work in a complex desert environment — 4D processing." Leading Edge 38, no. 8 (August 2019): 637–45. http://dx.doi.org/10.1190/tle38080637.1.

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Seismic monitoring of an onshore carbonate reservoir in a desert environment has been achieved for the first time. Optimizing data repeatability was key to detecting the weak 4D (time-lapse) signal resulting from a fluid-injection program, which was achieved through a combination of specialized survey design, careful acquisition, and dedicated 4D processing. The hybrid acquisition system utilized buried geophones, which significantly reduced 4D noise caused by variability in the near-surface environment. Despite the extensive acquisition efforts, time-lapse processing is an essential component of achieving highly repeatable data. A fit-for-purpose workflow was developed to reduce the remaining 4D noise using a combination of parallel and simultaneous processing. Processing steps leading to the largest improvement in reflection signal-to-noise ratio, such as noise attenuation, amplitude balancing, and supergrouping, produced the largest reduction in 4D noise. Outstanding final migrated data repeatability has been achieved, comparable to levels reported for the more favorable permanent marine systems. However, the need to use surface sources results in a seasonal imprint on data repeatability, which hinders the interpretation of surveys acquired during different seasons. In the absence of a fully buried acquisition system, advanced processing techniques such as surface-consistent matching filters may be required to resolve these variations.

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Ganesan, Madhubala, Ah-Lian Kor, Colin Pattinson, and Eric Rondeau. "Green Cloud Software Engineering for Big Data Processing." Sustainability 12, no. 21 (November 7, 2020): 9255. http://dx.doi.org/10.3390/su12219255.

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Internet of Things (IoT) coupled with big data analytics is emerging as the core of smart and sustainable systems which bolsters economic, environmental and social sustainability. Cloud-based data centers provide high performance computing power to analyze voluminous IoT data to provide invaluable insights to support decision making. However, multifarious servers in data centers appear to be the black hole of superfluous energy consumption that contributes to 23% of the global carbon dioxide (CO2) emissions in ICT (Information and Communication Technology) industry. IoT-related energy research focuses on low-power sensors and enhanced machine-to-machine communication performance. To date, cloud-based data centers still face energy–related challenges which are detrimental to the environment. Virtual machine (VM) consolidation is a well-known approach to affect energy-efficient cloud infrastructures. Although several research works demonstrate positive results for VM consolidation in simulated environments, there is a gap for investigations on real, physical cloud infrastructure for big data workloads. This research work addresses the gap of conducting real physical cloud infrastructure-based experiments. The primary goal of setting up a real physical cloud infrastructure is for the evaluation of dynamic VM consolidation approaches which include integrated algorithms from existing relevant research. An open source VM consolidation framework, Openstack NEAT is adopted and experiments are conducted on a Multi-node Openstack Cloud with Apache Spark as the big data platform. Open sourced Openstack has been deployed because it enables rapid innovation, and boosts scalability as well as resource utilization. Additionally, this research work investigates the performance based on service level agreement (SLA) metrics and energy usage of compute hosts. Relevant results concerning the best performing combination of algorithms are presented and discussed.

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Oka Martini, Ida Ayu. "Improvement Of Motivation With Leadership And Work Environment And The Impact Of Work Satisfaction." Jurnal Ekonomi & Bisnis JAGADITHA 8, no. 1 (March 30, 2021): 94–104. http://dx.doi.org/10.22225/jj.8.1.2774.94-104.

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This research was conducted to analyze the role of leadership, work environment, and work motivation in increasing satisfaction a nurse's job at the Ganesha General Hospital. The number of nurses in the hospital was 135. Data collection was carried out by distributing questionnaires to research respondents namely all nurses totalling 35 nurses so that it included the saturated sample method. Data analysis techniques were performed using path analysis, hypothesis testing was performed at a significance level of 5 per cent. Data processing is done using computer applications. The results showed that work motivation, leadership and work environment were positively significantly able to increase nurse job satisfaction. Work motivation acts as a partial mediator in the relationship of leadership to job satisfaction and works environment to job satisfaction.

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Adjali, Omar, and Amar Ramdane-Cherif. "Knowledge Processing Using EKRL for Robotic Applications." International Journal of Cognitive Informatics and Natural Intelligence 11, no. 4 (October 2017): 1–21. http://dx.doi.org/10.4018/ijcini.2017100101.

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This article describes a semantic framework that demonstrates an approach for modeling and reasoning based on environment knowledge representation language (EKRL) to enhance interaction between robots and their environment. Unlike EKRL, standard Binary approaches like OWL language fails to represent knowledge in an expressive way. The authors show in this work how to: model environment and interaction in an expressive way with first-order and second-order EKRL data-structures, and reason for decision-making thanks to inference capabilities based on a complex unification algorithm. This is with the understanding that robot environments are inherently subject to noise and partial observability, the authors extended EKRL framework with probabilistic reasoning based on Markov logic networks to manage uncertainty.

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Diah Pranitasari, Wati Setianingsih, Dodi Prastuti, Pristina Hermastuti, and Enung Siti Saodah. "The effect of emotional intelligence, compensation and work environment on work engagement." Monas: Jurnal Inovasi Aparatur 4, no. 1 (June 14, 2022): 373–86. http://dx.doi.org/10.54849/monas.v4i1.94.

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This study aims to determine some factors that influence employee work engagement. The factors examined in this study were emotional intelligence, compensation and work environment. The results of this study are expected to be input for companies in order to enhance employee work engagement. The study was conducted in Gramedia Kelapa Gading Bookstore employees. The research method is a survey. The population in this study were all 100 employees of Gramedia Bookstore Kelapa Gading, using saturated sampling techniques. The data analysis techniques and data processing used are the Structural Equation Modeling (SEM) method and SmartPLS 3.0 consecutively. The results of this study are as follows: (1) the influence of the emotional intelligence on work engagement is 38%; (2) the effect of the compensation on work engagement is 6%; (3) the influence of the work environment on work engagement is 42%; (4) the effect of the emotional intelligence, compensation and work environment on work engagement is 52%; and the remaining 48% is influenced by other factors not examined in this study.

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Li, Jian, and Yue Liu. "Data Processing in Regional Energy, Economy and Environment System Development Theories Research." Advanced Materials Research 1046 (October 2014): 550–53. http://dx.doi.org/10.4028/www.scientific.net/amr.1046.550.

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Along with the social progress and rapid economic development, many countries appeared the contradiction between supply and demand of energy in different degree and the environment is destroyed, so it’s difficult to support the economy to continue to grow. In this context, how to coordinate the relations among the sources of energy, economy and environment system(3 e) is the prime issue must be solved in the road of human sustainable development. This paper established economic growth Translog Production Function with considering the energy consumption and presented the calculation method of contribution rate to economic growth. At the same time with the data processing and analysis on energy, economy, and environment system theory, it provided government and enterprises with scientific proof of work and production combining with panel data.

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Brazovsky, K. S., Ya S. Pekker, V. P. Dyomkin, O. S. Umansky, and I. V. Tolmachyov. "HIGH PERFORMANCE INFORMATIONAL ENVIRONMENT FOR CALCULATIONS IN BIOMEDICINE." Bulletin of Siberian Medicine 13, no. 4 (August 28, 2014): 21–26. http://dx.doi.org/10.20538/1682-0363-2014-4-21-26.

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This work represented one of the possible approaches to providing the required computational resources for solving the complex data processing tasks in biomedicine. The proposed solution is based on four tightly interacted key components of modern high performance computational systems: high performance computational cluster, data processing center, specialized data store and protected telecommunication channels. The examples of tasks, which have been solved in the developed information environment, are given.

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Muslih, Muslih, and Farhan Anshari Damanik. "Effect of Work Environment and Workload on Employee Performance." International Journal of Economics, Social Science, Entrepreneurship and Technology (IJESET) 1, no. 1 (January 2, 2022): 23–35. http://dx.doi.org/10.55983/ijeset.v1i1.24.

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The purpose of this research is to determine and analyze the effect of the work environment and workload on performance at PT. Perkebunan Nusantara IV (Persero) Medan either partially or simultaneously.The approach used in this study is an associative approach. The population in this study were all employees PT. Perkebunan Nusantara IV (Persero) Medan. The sample in this study using the slovin formula totaling 81 employees atPT. Perkebunan Nusantara IV (Persero) Medan. Data collection techniques in this study used interview techniques, documentation studies, observation, and questionnaires. The data analysis technique in this study uses Multiple Linear Regression Analysis Test, Hypothesis Testing (t Test and F Test), and Coefficient of Determination. The data processing in this study used the SPSS (Statistical Package for the Social Sciences) software program version 24.00. The results of this study prove that partially and simultaneouslywork environment and workload have a significant effect on employee performance at PT. Perkebunan Nusantara IV (Persero) Medan.

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Peng, Xiaodong, Hongbo Jin, Peng Xu, Zhi Wang, Ziren Luo, Xiaoshan Ma, Li-E. Qiang, et al. "System modeling in data processing of Taiji-1 mission." International Journal of Modern Physics A 36, no. 11n12 (April 9, 2021): 2140026. http://dx.doi.org/10.1142/s0217751x21400261.

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Taiji-1 is the first technology demonstration satellite of the Taiji Program in Space, which, served as the pre-PathFinder mission, had finished its nominal science operational phase and successfully accomplished the mission goal. The gravitational reference sensor (GRS) on-board Taiji-1 is one of the key science payloads that coupled strongly to other instruments, sub-systems and also the satellite platform itself. Fluctuations of the physical environment inside the satellite and mechanical disturbances of the platform generate important noises in the GRS measurements, therefore their science data can also be used to evaluate the performance of the [Formula: see text]-thrusters and the stability of the platform. In this work, we report on the methods employed in Taiji-1 GRS data processing in the systematical modelings of the spacecraft orbit and attitude perturbations, mechanical disturbances, and internal environment changes. The modeled noises are then removed carefully from the GRS science data to improve the data quality and the GRS in-orbit performance estimations.

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Andrews, Penny. "The compliant environment." Online Information Review 43, no. 6 (October 14, 2019): 1063–79. http://dx.doi.org/10.1108/oir-09-2018-0284.

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Purpose The purpose of this paper is to present the concept of institutions as compliant environments, using data to monitor and enforce compliance with a range of external policies and initiatives, using the particular example of UK higher education (HE) institutions. The paper differs from previous studies by bringing together a range of policies and uses of data covering different areas of HE and demonstrating how they contribute to the common goal of compliance. Design/methodology/approach The compliant environment is defined in this context and the author has applied the preliminary model to a range of policies and cases that use and reuse data from staff and students in HE. Findings The findings show that the focus on compliance with these policies and initiatives has resulted in a high level of surveillance of staff and students and a lack of resistance towards policies that work against the goals of education and academia. Research limitations/implications This is the first study to bring together the range of areas in which policy compliance and data processing are entwined in HE. The study contributes to the academic literature on data and surveillance and on academic institutions as organisations. Practical implications The paper offers suggestions for resistance to compliance and data processing initiatives in HE. Originality/value This is the first study to bring together the range of areas in which policy compliance and data processing are entwined in HE. The study contributes to the academic literature on data and surveillance and on academic institutions as organisations.

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Дисертації з теми "Work environment Data processing"

Wong, C. W., and 王振威. "An adaptive information retrieval environment for collaborative architectural design work." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B45015089.

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洪進德 and Chun-tak Hung. "Chinese workbench: an integrated environment for Chinese writers." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1992. http://hub.hku.hk/bib/B31210314.

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Bailey, Janet L. "Computer-Supported Collaborative Work and Its Application to Software Engineering in a Case Environment." Thesis, University of North Texas, 1997. https://digital.library.unt.edu/ark:/67531/metadc279296/.

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This study investigated, in the context of a field-based case study, possibilities for formation of a synergistic union between CSCW and CASE tools. A major dimension of today's software challenge is in gearing up for large-scale system development necessitating large teams of systems engineers. The principal goal of this research was to advance the body of knowledge regarding the nature of collaborative technological support in the software development process. Specifically, the study was designed to evaluate the potential for using a CSCW tool as an effective front-end to a CASE tool in the furtherance of SDLC goals.

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Tam, Weng Tong. "WeChat in work environment in Macao, a use and gratification study." Thesis, University of Macau, 2018. http://umaclib3.umac.mo/record=b3952599.

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JUETTNER, VIRGINIA WEAVER. "THE WORD PROCESSING ENVIRONMENT AND ITS IMPACT ON THE WRITING OF A GROUP OF HIGH SCHOOL STUDENTS." Diss., The University of Arizona, 1987. http://hdl.handle.net/10150/184071.

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This research project studied a class of high school 11th and 12th grade writing students, for one semester, as they learned to use word processors for composing and editing assignments. The goals of the study were to (a) determine whether the use of a word processor created a special learning environment, (b) document the learning environment created, (c) document the resultant student word processing concepts, schemata and strategies, and (d) document the effects on the writing of students. Five predictions, based on research on language thought and symbol systems, and the application of a theoretical model formed the basis for observations. The predictions were tested by collecting and analyzing student writing and observational data. Student concepts, schemata and strategies were documented through use of the checklists and through observation. Pre- and post-student writing samples were matched and analyzed using individual T-tests, ANOVA and MANCOVA to determine any impact on writing due to the use of word processors. Questionnaires provided background information on English teacher and student writing/word processing backgrounds. Findings indicate support for the research model and predictions 1-4. The research model was found to be useful in organizing data and summarizing prediction results, and may offer assistance to teachers and researchers who want to study the impact of microcomputers from a total learning environment perspective.

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Livingston, Alan. "A Comparative Analysis of Style of User Interface Look and Feel in a Synchronous Computer Supported Cooperative Work Environment." Thesis, University of North Texas, 2005. https://digital.library.unt.edu/ark:/67531/metadc4765/.

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The purpose of this study is to determine whether the style of a user interface (i.e., its look and feel) has an effect on the usability of a synchronous computer supported cooperative work (CSCW) environment for delivering Internet-based collaborative content. The problem motivating this study is that people who are located in different places need to be able to communicate with one another. One way to do this is by using complex computer tools that allow users to share information, documents, programs, etc. As an increasing number of business organizations require workers to use these types of complex communication tools, it is important to determine how users regard these types of tools and whether they are perceived to be useful. If a tool, or interface, is not perceived to be useful then it is often not used, or used ineffectively. As organizations strive to improve communication with and among users by providing more Internet-based collaborative environments, the users' experience in this form of delivery may be tied to a style of user interface look and feel that could negatively affect their overall acceptance and satisfaction of the collaborative environment. The significance of this study is that it applies the technology acceptance model (TAM) as a tool for evaluating style of user interface look and feel in a collaborative environment, and attempts to predict which factors of that model, perceived ease of use and/or perceived usefulness, could lead to better acceptance of collaborative tools within an organization.

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Reed, Gary. "TSPI DATA PROCESSING IN THE TELEMETRY ENVIRONMENT." International Foundation for Telemetering, 1985. http://hdl.handle.net/10150/615725.

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International Telemetering Conference Proceedings / October 28-31, 1985 / Riviera Hotel, Las Vegas, Nevada
Most test ranges are required to process both telemetry and Time Space Position Information (TSPI) data in real time. Using the Integrated Flight Data Processing System (IFDAPS) at Edwards AFB as an example, this paper identifies some of the basic differences between telemetry and TSPI data processing and discusses methods of integrating the two types of processing. Included for consideration in the integrated processing are data acquisition, measurement displays, recording, derived measurement computations using both types of data, and post flight merging of telemetry and TSPI data. Data processing is discussed in a concurrent, multiple operation environment using separate, integrated processors.

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Griffin, Alan R., and R. Stephen Wooten. "AUTOMATED DATA MANAGEMENT IN A HIGH-VOLUME TELEMETRY DATA PROCESSING ENVIRONMENT." International Foundation for Telemetering, 1992. http://hdl.handle.net/10150/608908.

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International Telemetering Conference Proceedings / October 26-29, 1992 / Town and Country Hotel and Convention Center, San Diego, California
The vast amount of data telemetered from space probe experiments requires careful management and tracking from initial receipt through acquisition, archiving, and distribution. This paper presents the automated system used at the Phillips Laboratory, Geophysics Directorate, for tracking telemetry data from its receipt at the facility to its distribution on various media to the research community. Features of the system include computerized databases, automated generation of media labels, automated generation of reports, and automated archiving.

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Emenike, Stanley Ugochukwu. "Data loss prevention in a remote work environment." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-20203.

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Data is one of the most valuable organizational assets that are susceptible to compromise when appropriate security measures are not in place. Preventing data loss is a dynamic and ongoing process that requires frequent effort and investment from organizations. This study provides a comprehensive overview of the risk to organizational data (i.e., data loss) due to the increase in remote work taking over the business landscape. In seeking answers to the research question, the study applies thematic analysis in analyzing qualitative data from the interview of 6 respondents with over 5 years of information security experience. The analysis identified four themes (threats, risk, security incident and security posture) that are relevant in answering the research questions. The findings show that there was an increase in phishing, malware and DOS attack against the organisation information assets since the inception of the global pandemic which has led to data loss and affected the organization’s competitive advantage and reputation. Also, the security posture before the pandemic was not effective in dealing with the increase in cyber attacks during the pandemic. The pandemic has led organizations to reassess their security posture to identify areas that need to be strengthened. The challenge in achieving an effective security posture is the attack surface is expanding and changing rapidly as well as the insufficient resources available (both human and financial). The organisation reassessed their security posture to identify gaps that need to be addressed. Employee training and awareness need to be done more frequently as well as implementing different technical security measures. Also, policies and procedures are implemented that outlines the acceptable use and management of the organization information assets.

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Wang, Yun, and Wenxuan Jiang. "Statistical Processing of IEEE 802.15.4 Data Collected in Industrial Environment." Thesis, Mittuniversitetet, Institutionen för informationsteknologi och medier, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-19619.

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Wireless sensor network, which is constitute of autonomous sensors, is used for monitoring physical or environmental conditions like temperature, sound, pressure, and so on. The dispersed sensors or nodes will respectively pass their data through the network to the main location. Currently, several standards are ratified or in developing for wireless sensor network, like Wireless Hart, ISA, 100.11a, WIA-PAA, IEEE 802.15.4, etc. Among the standards, Zigbee is often used in industrial applications that require short-range and low-rate wireless transfer. In the research, all the data is collected under industrial environment using IEEE 802.15.4 compliant physical layer, some packets are interfered only by multi-path fading while others are also interfered by Wi-Fi interference. The goal of the thesis is to find out the dependence between the received power (RSS), correlation value (CORR) and bit error rate (BER) of the received message, and their distribution in situations both when the packet is lost or not. Besides, the performance of bit error rate such as the distribution and the features of burst error length under Wi-Fi interference or not will also be tested. All of them are based on a precise statistical processing.

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Книги з теми "Work environment Data processing"

National Archives of Canada. Information Management Standards and Practices Division. Electronic work environment (EWE) vision. [Ottawa]: Information Management Standards and Practices Division, National Archives of Canada, 1996.

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National Archives of Canada. Information Management Standards and Practices Division. Record keeping in the electronic work environment: Vision. [Ottawa]: National Archives of Canada, 1996.

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McNeil, Jeannine. The effects of word processing and automated data entry technology on the quantity and quality of users' jobs: Summary. Laval, Quebec: Dept. of Communications of Canada, Canadian Workplace Automation Research Centre, Organizational Research Directorate, 1989.

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B, Wasson Barbara, Ludvigsen Sten, and Hoppe, Ulrich, 1954 Sept. 15-, eds. Designing for change in networked learning environments: Proceedings of the International Conference on Computer Support for Collaborative Learning 2003. Dordrecht: Kluwer Academic Publishers, 2003.

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1957-, MacLennan Mark Jeffrey, ed. Expert systems in geography and environmental studies: An annotated review of recent work in the field. [Waterloo, Ont.]: Dept. of Geography, University of Waterloo, 1990.

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Copyright law in the digital environment: Private ordering and the regulation of digital works. Saarbrücken: Lambert Academic, 2012.

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I, Houtman, and European Foundation for the Improvement of Living and Working Conditions., eds. Indicators of working conditions in the European Union. Loughlinstown, Co. Dublin, Ireland: European Foundation for the Improvement of Living and Working Conditions, 1997.

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Christina, Garsten, and Wulff Helena, eds. New technologies at work: People, screens, and social virtuality. Oxford: Berg, 2003.

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CSCL (Conference) (2003 Bergen, Norway). Designing for change in networked learning environments: Proceedings of the International Conference on Computer Support for Collaborative Learning 2003. Dordrecht: Springer, 2003.

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International Symposium on the Impact of New Information Technologies on the Workplace (1985 Montréal, Québec). Symposium international sur les répercussions de l'informatisation en milieu de travail: Les 3, 4, et 5 novembre 1985, Hôtel Le [sic] Quatre Saisons, Montréal = International Symposium on the Impact of New Information Technologies on the Workplace : November 3, 4 and 5, 1985, Four Seasons Hotel, Montreal. Montréal, Québec: Institut de recherches politiques, 1986.

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Частини книг з теми "Work environment Data processing"

Kirstein, Fabian, Dario Bacher, Vincent Bohlen, and Sonja Schimmler. "Ronda: Real-Time Data Provision, Processing and Publication for Open Data." In Lecture Notes in Computer Science, 165–77. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-84789-0_12.

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AbstractThe provision and dissemination of Open Data is a flourishing concept, which is highly recognized and established in the government and public administrations domains. Typically, the actual data is served as static file downloads, such as CSV or PDF, and the established software solutions for Open Data are mostly designed to manage this kind of data. However, the rising popularity of the Internet of things and smart devices in the public and private domain leads to an increase of available real-time data, like public transportation schedules, weather forecasts, or power grid data. Such timely and extensive data cannot be used to its full potential when published in a static, file-based fashion. Therefore, we designed and developed Ronda - an open source platform for gathering, processing and publishing real-time Open Data based on industry-proven and established big data and data processing tools. Our solution easily enables Open Data publishers to provide real-time interfaces for heterogeneous data sources, fostering more sophisticated and advanced Open Data use cases. We have evaluated our work through a practical application in a production environment.

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Fritzsch, Bernadette, and Wolfgang Hiller. "Collaborative Climate Community Data and Processing Grid—C3Grid: Workf lows for Data Selection, Pre- and Post-Processing in a Distributed Environment." In Earth System Modelling - Volume 6, 49–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37244-5_6.

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Traboulsi, Salam, and Stefan Knauth. "Monitoring Tool for Improving Indoor Environment Quality and Performance Based on IoT Sensors: State of the Art and Concept." In iCity. Transformative Research for the Livable, Intelligent, and Sustainable City, 307–14. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92096-8_20.

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AbstractIndoor temperature is one of the fundamental features of the indoor environment. It can be controlled with distributed IoT sensors, through wireless networks. It affects human indoor environment such as human thermal sensation, productivity at work, buildings’ quality, and several syndrome symptoms. In this study, we focus on the effects of the indoor temperature on the human work productivity and thermal sensation. Our research aims to develop an IoT monitoring tool to manage the challenges in smart buildings by extracting and processing relevant data. It proposes data analysis periodically and integrates newly generated data into the analytical cycle that allows improving human indoor environment.

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Picchi, G., J. Sandak, S. Grigolato, P. Panzacchi, and R. Tognetti. "Smart Harvest Operations and Timber Processing for Improved Forest Management." In Climate-Smart Forestry in Mountain Regions, 317–59. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80767-2_9.

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AbstractClimate-smart forestry can be regarded as the evolution of traditional silviculture. As such, it must rely on smart harvesting equipment and techniques for a reliable and effective application. The introduction of sensors and digital information technologies in forest inventories, operation planning, and work execution enables the achievement of the desired results and provides a range of additional opportunities and data. The latter may help to better understand the results of management options on forest health, timber quality, and many other applications. The introduction of intelligent forest machines may multiply the beneficial effect of digital data gathered for forest monitoring and management, resulting in forest harvesting operations being more sustainable in terms of costs and environment. The interaction can be pushed even further by including the timber processing industry, which assesses physical and chemical characteristics of wood with sensors to optimize the transformation process. With the support of an item-level traceability system, the same data could provide a formidable contribution to CSF. The “memory” of wood could support scientists to understand the response of trees to climate-induced stresses and to design accordingly an adaptive silviculture, contributing to forest resilience in the face of future changes due to human-induced climate alteration.

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Yuan, David Yu, and Tony Wildish. "Bioinformatics Application with Kubeflow for Batch Processing in Clouds." In Lecture Notes in Computer Science, 355–67. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59851-8_24.

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Abstract Bioinformatics pipelines make extensive use of HPC batch processing. The rapid growth of data volumes and computational complexity, especially for modern applications such as machine learning algorithms, imposes significant challenges to local HPC facilities. Many attempts have been made to burst HPC batch processing into clouds with virtual machines. They all suffer from some common issues, for example: very high overhead, slow to scale up and slow to scale down, and nearly impossible to be cloud-agnostic. We have successfully deployed and run several pipelines on Kubernetes in OpenStack, Google Cloud Platform and Amazon Web Services. In particular, we use Kubeflow on top of Kubernetes for more sophisticated job scheduling, workflow management, and first class support for machine learning. We choose Kubeflow/Kubernetes to avoid the overhead of provisioning of virtual machines, to achieve rapid scaling with containers, and to be truly cloud-agnostic in all cloud environments. Kubeflow on Kubernetes also creates some new challenges in deployment, data access, performance monitoring, etc. We will discuss the details of these challenges and provide our solutions. We will demonstrate how our solutions work across all three very different clouds for both classical pipelines and new ones for machine learning.

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Chen, Yuxin, Shun Li, and Jiahui Yao. "Processing Missing Information in Big Data Environment." In Data Mining and Big Data, 638–48. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93803-5_60.

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Rogers, James C., and Grant R. Gerhart. "Application of Acoustics in the Land Environment." In Underwater Acoustic Data Processing, 453–59. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-2289-1_49.

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Najeh, Houda, Christophe Lohr, and Benoit Leduc. "Real-Time Human Activity Recognition in Smart Home on Embedded Equipment: New Challenges." In Lecture Notes in Computer Science, 125–38. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-09593-1_10.

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AbstractBuilding Energy Management (BEM) and monitoring systems should not only consider HVAC systems and building physics but also human behaviors. These systems could provide information and advice to occupants about the significance of their practices with regard to the current state of a dwelling. It is also possible to provide services such as assistance to the elderly, comfort and health monitoring. For this, an intelligent building must know the daily activities of its residents and the algorithms of the smart environment must track and recognize the activities that the occupants normally perform as part of their daily routine. In the literature, deep learning is one of effective supervised learning model and cost-efficient for real-time HAR, but it still struggles with the quality of training data (missing values in time series and non-annotated event), the variability of data, the data segmentation and the ontology of activities. In this work, recent research works, existing algorithms and related challenges in this field are firstly highlighted. Then, new research directions and solutions (performing fault detection and diagnosis for drift detection, multi-label classification modeling for multi-occupant classification, new indicators for training data quality, new metrics weighted by the number of representations in dataset to handle the issue of missing data and finally language processing for complex activity recognition) are suggested to solve them respectively and to improve this field.

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Mok, Eppie, Hong Va Leong, and Antonio Si. "Transaction Processing in an Asymmetric Mobile Environment." In Mobile Data Access, 71–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-46669-x_7.

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Sfar, Hela, and Amel Bouzeghoub. "Dynamic Streaming Sensor Data Segmentation for Smart Environment Applications." In Neural Information Processing, 67–77. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04224-0_7.

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Тези доповідей конференцій з теми "Work environment Data processing"

Konstantinova, A. M., E. A. Loupian, I. V. Balashov, and A. V. Kashnitskii. "Approaches to monitoring natural and anthropogenic objects in an analysis of the environment around large industrial facilities." In Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes 2021. Crossref, 2021. http://dx.doi.org/10.25743/sdm.2021.46.67.017.

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The paper deals with the problems of a sharp increase in the number of remote sensing satellite systems and the amount of data received, and because of this, the need to develop new approaches to the processing and use of satellite information. An “object-oriented” approach to work with remote sensing data for monitoring natural and anthropogenic processes is proposed. The paper presents a subsystem for working with objects of observation created on the basis of the “IKI-Monitoring” Center for Collective Use for the implementation of this approach. The efficiency of the subsystem is confirmed by examples of its use for the organization of remote sensing of zones of potential contamination from large industrial facilities.

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Zagumennov, A. A., and V. V. Naumova. "Development of the computing node for processing satellite imagery and spatial data for earth sciences." In Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes 2021. Crossref, 2021. http://dx.doi.org/10.25743/sdm.2021.87.17.033.

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The work is devoted to the development of a computing node for processing satellite and spatial data for earth sciences by the example of its implementation as part of the Information and Analytical Environment to support scientific research in geology of the Vernadsky State Geological Museum (SGM RAS). The prerequisites for the creation of such a computing node and the requirements for it to solve geological problems are given. An overview of cloud platforms for access to satellite and spatial data and its processing has been presented. Based on the overview a conceptual diagram of a computing node has been proposed and the list of modern technologies required for building it has been determined. The developed node provides tools for searching data from external cloud providers, processing them with various built-in and custom algorithms, as well as tools for visualizing the results. It is an independent web service, although it is part of the Computational and Analytical Geological Environment of SGM RAS and is integrated with its services. This allows a wide range of users to access data and processing algorithms provided by computing node, including integrating it into other information systems as a third-party application for processing satellite and spatial data.

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Wang, Li. "Translation Strategies of Long and Difficult Sentences in English Linguistics Academic Works under Big Data Environment." In 2020 International Conference on Computers, Information Processing and Advanced Education (CIPAE). IEEE, 2020. http://dx.doi.org/10.1109/cipae51077.2020.00034.

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Lisowski, Przemysław, Adam Piórkowski, and Andrzej Lesniak. "Tools for the Storage and Analysis of Spatial Big Data." In Environmental Engineering. VGTU Technika, 2017. http://dx.doi.org/10.3846/enviro.2017.216.

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Storing large amounts of spatial data in GIS systems is problematic. This problem is growing due to ever- increasing data production from a variety of data sources. The phenomenon of collecting huge amounts of data is called Big Data. Existing solutions are capable of processing and storing large volumes of spatial data. These solutions also show new approaches to data processing. Conventional techniques work with ordinary data but are not suitable for large datasets. Their efficient action is possible only when connected to distributed file systems and algorithms able to reduce tasks. This review focuses on the characteristics of large spatial data and discusses opportunities offered by spatial big data systems. The work also draws attention to the problems of indexing and access to data, and proposed solutions in this area.

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Гегерь, Эмилия, Emilia Geger, Александр Подвесовский, Aleksandr Podvesovskiy, Сергей Кузьмин, Sergey Kuzmin, Виктория Толстенок, and Viktoriya Tolstenok. "Methods for the Intelligent Analysis of Biomedical Data." In 29th International Conference on Computer Graphics, Image Processing and Computer Vision, Visualization Systems and the Virtual Environment GraphiCon'2019. Bryansk State Technical University, 2019. http://dx.doi.org/10.30987/graphicon-2019-2-308-311.

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The paper discusses methodology of cleaning and analysis of small semi-structured samples of biomedical data. This methodology is aimed at statistical evaluation of harmful production factor correlation with workers’ laboratory test data. As a result of the analysis and interpretation of the data, a deviation from the norm is observed according to some indicators of a clinical blood test in individuals whose occupational activity is associated with harmful factors. Conclusions are drawn about the need for further research in the group of people whose work is related to harmful production factors. It is necessary to employ intelligent methods for analyzing possible health risks and their negative consequences in order to make management decisions. The presented assessment methodology can be used to create an occupational health and safety information system.

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Zhiqiang, Zhao, Chua Wei Quan, Ding Xiaoming, and Prabhu Vinayak Ashok. "Smart Factory of Industry 4.0: Connection Infrastructure, Data Acquisition, Data Processing, and Applications." In ASME 2019 14th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/msec2019-2703.

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Abstract Smart factory adopts cyber-physical technologies integrating independent discrete systems into a context-sensitive manufacturing environment to optimize manufacturing processes using decentralized information and real-time communication. This paper presents our work in the realization of a smart factory, which comprises of a four-layer hierarchical architecture, i.e. connection infrastructure, data acquisition, data processing and smart applications. In the connection infrastructure layer, all shopfloor machines are connected through diverse protocols, IoT sensors, PLC interfaces and DNC connectors. A centralized IoT gateway supports such a scalable and adaptable connection and ensures a reliable communication among all heterogeneous manufacturing systems. In the data acquisition layer, the real-time machine and job data are acquired from shopfloor systems. Machine data indicates machines’ working condition and job data reveals the production information. The data processing layer comprises of three modules, i.e. shopfloor monitoring, data visualization and data analytics, which monitor and visualize shopfloor activities and analyze the semantics of various data using AI-based TPM engines providing the scientific indicators for next-step decisions. The smart application layer provides with several decision-making and remote control functions for shopfloor productivity and efficiency, such as predictive maintenance, shopfloor management, machine & job optimization and digital twin. The smart factory system has been implemented in the manufacturing shopfloor at Nanyang Polytechnic. The results and validation show that the system can simultaneously collect and analyze the manufacturing data from shopfloor systems, and further communicate with and control the shopfloor systems with decision-support functions. The overall shopfloor efficiency and flexibility can be significantly improved towards a smart factory of Industry 4.0.

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Verma, Alakh K., and Dipendra K. Sinha. "Recent Developments in Cloud Computing, Data Storage and Handling." In ASME 2013 Conference on Information Storage and Processing Systems. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/isps2013-2815.

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As data center managers consider deployment of a Cloud Computing environment the most important issues they consider include critical application data availability, storage agility and data protection strategies. Early adopters of Cloud Computing have already deployed Virtualization as a key technology in their Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) offerings. Cloud computing extends the benefits of virtualization by increasing the efficiency of server and storage utilization, reducing costs, improving operational efficiency and optimizing datacenter rack and floor space. It builds on first-generation system and storage virtualization with features such as application portability and storage agility to enable higher efficiencies and greater efficiencies across the enterprise. With recent innovation in storage, key features such as thin-provisioning, compression and de-duplication work in concert with virtualized infrastructure on the Storage Appliance to eliminate duplicate data blocks, compress data and allocate the amount of storage being consumed by users. Data services such as snapshots and clones provide instant and optionally, unattended backups that can be used in the short term for recovery of critical data. Disaster recovery is all the more important within the cloud computing environment and built in replication services enable a robust solution in case of a catastrophic event or simply for purposes of backup and recovery.

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Eremenko, V. S., and V. V. Naumova. "A multi-platform ecosystem for computing in Earth sciences." In Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes 2021. Crossref, 2021. http://dx.doi.org/10.25743/sdm.2021.70.81.010.

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Analysis of diverse data in geosciences requires access to various processing tools, including specialized software packages, proprietary algorithms, GIS systems, web services, etc. Such tools require from the user a certain level of skills to work with them, form a software environment, the availability of the necessary computing power, and sometimes significant time and financial costs. With the development of information technology, more and more software products, including professional software packages for data processing, are provided to users in the format of various cloud services and platforms. In such systems, computation takes place on the side of the service provider and is accessed through a web browser. The emergence of such open-access services and platforms makes it possible to organize a single workspace for a researcher with the ability to analyze his own data using various processing methods, including tools traditionally used in earth sciences. The report is devoted to the development of an approach for the integration of various tools for processing heterogeneous data with open access within a single multi-platform ecosystem. The software system developed based on the proposed approach is demonstrated. The report describes software modules that implement the functions of access to processing and analysis tools, as well as service modules for system administration, component monitoring and event logging. Services and processing platforms integrated into the ecosystem are considered, as well as scenarios for solving some geological problems.

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Laurent, Vallet, Gutarov Pavel, Chevallier Bertrand, Converset Julien, Paterson Graeme, and Vaslin Antoine. "Multi Well Analysis Data Processing for Event Analysis and Mitigation." In IADC/SPE Asia Pacific Drilling Technology Conference. SPE, 2021. http://dx.doi.org/10.2118/201002-ms.

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Abstract In the current economic environment, delivering wells on time and on budget is paramount. Well construction is a significant cost of any field development and it is more important than ever to minimize these costs and to avoid unnecessary lost time and non-productive time. Invisible lost time and non-productive time can represent as much as 40% of the cost of well construction and can lead to more severe issues such as delaying first oil, losing the well or environmental impact. There has been much work developing systems to optimize well construction, but the industry still fails to routinely detect and avoid problematic events such as stuck pipe, kicks, losses and washouts. Standardizing drilling practice can help also to improve the efficiency, this practice has shown a 30% cost reduction through repetitive and systematic practices, automation becomes the key process to realize it and Machine Learning introduced by new technologies is the key to achieve it. Drilling data analysis is key to understanding reasons for bad performances and detecting at an early stage potential downhole events. It can be done efficiently to provide to the user tools to look at the well construction process in its whole instead of looking at the last few hours as it is done at the rig site. In order to analyze the drilling data, it is necessary to have access to reliable data in Real-Time to compare with a data model considering the context (BHA, fluids, well geometry). Well planning, including multi-well offset analysis of risks, drilling processes and geology enables a user to look at the full well construction process and define levels of automation. This paper applies machine learning to a post multi-well analysis of a deepwater field development known for its drilling challenges. Minimizing the human input through automation allowed us to compare offset wells and to define the root cause for non-productive time. In our case study an increase of the pressure while drilling should have led to immediate mitigation measures to avoid a wiper trip. This paper presents techniques used to systematize surface data analysis and a workflow to identify at an early stage a near pack off which was spotted in an automatic way. The application of this process during operations could have achieved a 10%-time reduction of the section 12 ¼’’.

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Shkundalov, Danylo, and Tatjana Vilutienė. "BUILDING MANAGEMENT SYSTEM IN WEBBIM ENVIRONMENT." In 11th International Conference “Environmental Engineering”. VGTU Technika, 2020. http://dx.doi.org/10.3846/enviro.2020.725.

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Geographical information systems (GIS) and Building information modelling (BIM) provide digital representation of building, its elements and environment. BIM focuses on micro-level representation of buildings and its elements, and GIS provide macro-level representation of the external elements of environment. Their combination can provide a comprehensive view of a built environment based on integrated data. There is an opportunity to make BIM and GIS unity not only to combine them in a single project but also to make a fully merged environment with difficult associations that extend the capabilities of both. Paper presents method that allows visualization and processing the BIM model in the web browser, external processing and analyzing, easy sharing and visualization, linking the 3D model and attribute information, working with the BIM model and GIS data, digital City mapping and etc. The developed method creates rich future for full BIM software products with all manner of functions and tools that will work through the Internet without installations, distributives, additional programs. The introduced technique can be used as a new part for BIM execution planning.

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Звіти організацій з теми "Work environment Data processing"

Selvaraju, Ragul, SHABARIRAJ SIDDESWARAN, and Hariharan Sankarasubramanian. The Validation of Auto Rickshaw Model for Frontal Crash Studies Using Video Capture Data. SAE International, September 2020. http://dx.doi.org/10.4271/2020-28-0490.

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Despite being Auto rickshaws are the most important public transportation around Asian countries and especially in India, the safety standards and regulations have not been established as much as for the car segment. The Crash simulations have evolved to analyze the vehicle crashworthiness since crash experimentations are costly. The work intends to provide the validation for an Auto rickshaw model by comparing frontal crash simulation with a random head-on crash video. MATLAB video processing tool has been used to process the crash video, and the impact velocity of the frontal crash is obtained. The vehicle modelled in CATIA is imported in the LS-DYNA software simulation environment to perform frontal crash simulation at the captured speed. The simulation is compared with the crash video at 5, 25, and 40 milliseconds respectively. The comparison shows that the crash pattern of simulation and real crash video are similar in detail. Thus the modelled Auto-rickshaw can be used in the future to validate the real-time crash for providing the scope of improvement in Three-wheeler safety.

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Бабець, Євген Костянтинович, Ірина Петрівна Антонік, Ірина Євгенівна Мельникова, and Антон Всеволодович Петрухін. nfluence of Mining and Concentration Works Activity on Land Resources. Petroșani, 2019. http://dx.doi.org/10.31812/123456789/3120.

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The research provides assessment of current and longer-term consequences of iron ore open pit mining for land resources of adjacent areas. There are applied methods of analysis of fund materials; comparison of topographic sheets and special maps, visual observation, soil testing, laboratory analyses and statistic processing of data obtained. It is revealed that facilities of iron ore mining and concentration waste accumulation (dumps and tailing ponds) are destructive factors for the local lithosphere, dust chemical contamination being the basic one. The steps aimed at reducing negative impacts of technogenic objects of the mining and raw material complex on the environment are under study.

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Collins, Belinda L., and Arthur I. Rubin. Analysis of work environment data from three army field stations. Gaithersburg, MD: National Bureau of Standards, 1988. http://dx.doi.org/10.6028/nist.ir.88-3871.

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Spore, Nicholas, and Katherine Brodie. Collection, processing, and accuracy of mobile terrestrial lidar survey data in the coastal environment. Coastal and Hydraulics Laboratory (U.S.), May 2017. http://dx.doi.org/10.21079/11681/22189.

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Jelinek, Raz, Paul Dawson, Timothy Hanks, William Pennington, and Julie Northcutt. Bacterial sensors for food processing environments. United States Department of Agriculture, January 2013. http://dx.doi.org/10.32747/2013.7598157.bard.

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The overall objective of this project was to develop a new bacterial contaminant sensor based upon polydiacetylene(PDA) which is a unique polymer that changes color and configuration in response to external molecular stimuli. While this polymer has been well studied and has been shown to respond to bacterial stimuli in the laboratory, application to food processing environments has not been demonstrated. One hurdle in the application of biosensors in a food processing environment is interference of food sanitizers with the detection of bacteria. Common food sanitizers were evaluated for their response to PDA and different concentrations paving the way for use of modified PDAs developed by the research team to be used in food plants. Further development of PDA bacterial sensors focused on simplifying its application by immobilizing PDA on cotton and paper for use on swabs, wipes and dip papers. Increasing the sensitivity of PDAs was investigated by attaching fluorophores. Future and continued work will include the decoration of PDAs with apatmers to improve the specificity of the biosensor to food pathogens.

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Bates, C. Richards, Melanie Chocholek, Clive Fox, John Howe, and Neil Jones. Scottish Inshore Fisheries Integrated Data System (SIFIDS): Work package (3) final report development of a novel, automated mechanism for the collection of scallop stock data. Edited by Mark James and Hannah Ladd-Jones. Marine Alliance for Science and Technology for Scotland (MASTS), 2019. http://dx.doi.org/10.15664/10023.23449.

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[Extract from Executive Summary] This project, aimed at the development of a novel, automated mechanism for the collection of scallop stock data was a sub-part of the Scottish Inshore Fisheries Integrated Data Systems (SIFIDS) project. The project reviewed the state-of-the-art remote sensing (geophysical and camera-based) technologies available from industry and compared these to inexpensive, off-the -shelf equipment. Sea trials were conducted on scallop dredge sites and also hand-dived scallop sites. Data was analysed manually, and tests conducted with automated processing methods. It was concluded that geophysical acoustic technologies cannot presently detect individual scallop but the remote sensing technologies can be used for broad scale habitat mapping of scallop harvest areas. Further, the techniques allow for monitoring these areas in terms of scallop dredging impact. Camera (video and still) imagery is effective for scallop count and provide data that compares favourably with diver-based ground truth information for recording scallop density. Deployment of cameras is possible through inexpensive drop-down camera frames which it is recommended be deployed on a wide area basis for further trials. In addition, implementation of a ‘citizen science’ approach to wide area recording is suggested to increase the stock assessment across the widest possible variety of seafloor types around Scotland. Armed with such data a full, statistical analysis could be completed and data used with automated processing routines for future long-term monitoring of stock.

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Pererva, Victoria V., Olena O. Lavrentieva, Olena I. Lakomova, Olena S. Zavalniuk, and Stanislav T. Tolmachev. The technique of the use of Virtual Learning Environment in the process of organizing the future teachers' terminological work by specialty. [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3868.

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This paper studies the concept related to E-learning and the Virtual Learning Environment (VLE) and their role in organizing future teachers’ terminological work by specialty. It is shown the creation and use of the VLE is a promising approach in qualitative restructuring of future specialists’ vocation training, a suitable complement rather than a complete replacement of traditional learning. The concept of VLE has been disclosed; its structure has been presented as a set of components, such as: the Data-based component, the Communication-based, the Management-and-Guiding ones, and the virtual environments. Some VLE’s potential contributions to the organization of terminological work of future biology teachers’ throughout a traditional classroom teaching, an independent work, and during the field practices has been considered. The content of professionally oriented e-courses “Botany with Basis of Geobotany” and “Latin. Botany Terminology” has been revealed; the ways of working with online definer (guide), with UkrBIN National Biodiversity Information Network, with mobile apps for determining the plant species, with digital virtual herbarium, with free software have been shown. The content of students’ activity in virtual biological laboratories and during virtual tours into natural environment has been demonstrated. The explanations about the potential of biological societies in social networks in view of students’ terminology work have been given. According to the results of empirical research, the expediency of using VLEs in the study of professional terminology by future biology teachers has been confirmed.

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Shapovalov, Yevhenii B., Viktor B. Shapovalov, and Vladimir I. Zaselskiy. TODOS as digital science-support environment to provide STEM-education. [б. в.], September 2019. http://dx.doi.org/10.31812/123456789/3250.

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The amount of scientific information has been growing exponentially. It became more complicated to process and systemize this amount of unstructured data. The approach to systematization of scientific information based on the ontological IT platform Transdisciplinary Ontological Dialogs of Object-Oriented Systems (TODOS) has many benefits. It has been proposed to select semantic characteristics of each work for their further introduction into the IT platform TODOS. An ontological graph with a ranking function for previous scientific research and for a system of selection of journals has been worked out. These systems provide high performance of information management of scientific information.

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Iatsyshyn, Anna V., Iryna H. Hubeladze, Valeriia O. Kovach, Valentyna V. Kovalenko, Volodymyr O. Artemchuk, Maryna S. Dvornyk, Oleksandr O. Popov, Andrii V. Iatsyshyn, and Arnold E. Kiv. Applying digital technologies for work management of young scientists' councils. [б. в.], June 2021. http://dx.doi.org/10.31812/123456789/4434.

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The publication explores the features of the digital technologies’ usage to organize the work of the Young Scientists’ Councils and describes the best practices. The digital transformation of society and the quarantine restrictions caused by the COVID-19 pandemic have forced the use of various digital technologies for scientific communication, the organization of work for youth associations, and the training of students and Ph.D. students. An important role in increasing the prestige of scientific activity and encouraging talented young people to participate in scientific projects belongs to the Young Scientists’ Councils, which are created at scientific institutions and higher education institutions. It is determined that the peculiarities of the work of Young Scientists’ Councils are in providing conditions for further staff development of the institution in which they operate; contribution to the social, psychological and material support of young scientists and Ph.D. students; creating an environment for teamwork and collaborative partnership; development of leadership and organizational qualities; contribution to the development of digital competence. The advantages of using electronic social networks in higher education and research institutions are analyzed, namely: general popularity and free of charge; prompt exchange of messages and multimedia data; user-friendly interface; availability of event planning functions, sending invitations, setting reminders; support of synchronous and asynchronous communication between network participants; possibility of access from various devices; a powerful tool for organizing the learning process; possibility of organization and work of closed and open groups; advertising of various events, etc. Peculiarities of managing the activity of the Young Scientists’ Council with the use of digital technologies are determined. The Young Scientists’ Council is a social system, and therefore the management of this system refers to social management. The effectiveness of the digital technologies’ usage to manage the activities of the Young Scientists’ Council depends on the intensity and need for their use to implement organizational, presentation functions and to ensure constant communication. The areas to apply digital technologies for the work managing of Young Scientists’ Councils are sorted as the presentation of activity; distribution of various information for young scientists; conducting questionnaires, surveys; organization and holding of scientific mass events; managing of thematic workgroups, holding of work meetings. It is generalized and described the experience of electronic social networks usage for organizing and conducting of scientific mass events.

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