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Journal articles on the topic 'Work environment Data processing'
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1
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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Dmitruk, V. V., A. A. Kasyanenko, E. B. Kovinchenko, and I. V. Kravchenko. "Data Processing Method of Well Testing." Oil and Gas Technologies 134, no. 3 (2021): 55–59. http://dx.doi.org/10.32935/1815-2600-221-134-3-55-59.
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This publication discusses research work to improve the existing process for cooling compressed gas at the Yuzhno-Russkoye oil and gas condensate field of OJSC «Severneftegazprom». This project consisted in a scientific study of technological processes for the treatment, compression and transportation of natural gas. Based on the results of the research project, a system for additional cooling of compressed gas after the gas pumping units of the booster compressor station was developed (independent of the ambient temperature). When implementing into the existing technological process of cooling the compressed gas, the developed system will provide the required temperature parameters of the natural gas together with the operated air cooling units of gas and recuperative heat exchangers. To select an additional gas cooling system providing the required cooling capacity, taking into account existing energy resources (electricity, natural gas) and climatic conditions of the Yuzhno-Russkoe oil and gas condensate field, a detailed modeling of the different options of cooling systems of gas actually available on the market of this equipment in Russia and the option selection with the highest rates of integral effect and performance index. The proposed solution guarantees a stable supply of commercial natural gas within the framework of contractual obligations and excludes the influence of temperature factors of the environment on technological processes.
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Julita, Sari, Indra Prasetyo, and Woro Utari. "PENGARUH LINGKUNGAN KERJA DAN KOMPENSASI TERHADAP KINERJA PEGAWAI MELALUI KEPUASAN KERJA DI KANTOR SEKRETARIAT DPRD KABUPATEN KEPULAUAN MERANTI." BBM (Buletin Bisnis & Manajemen) 8, no. 2 (August 1, 2022): 100. http://dx.doi.org/10.47686/bbm.v8i2.405.
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The purpose of this study was to determine and describe the work environment, compensation, job satisfaction and employee performance in the Secretariat Office of the DPRD Meranti Islands District Court, Law and Aspiration Data Processing and to determine and analyze the influence between work environment and compensation on employee performance through satisfaction. work. The population and sample used in the study were 37 employees with a total sampling technique. Data collection through questionnaires. Data processing in this study using SPSS Statistics version 25. The analysis technique uses path analysis. The results showed that the work environment, compensation, job satisfaction and employee performance could be categorized quite well. Work environment and compensation have a significant effect on job satisfaction. Work environment and job satisfaction have a significant effect on employee performance while compensation has no significant effect on employee performance. The work environment has a significant effect on employee performance through job satisfaction, while compensation has no significant effect on employee performance through job satisfaction
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Latif, Abdul. "Pursuit of Well-being: Testing the Role of Empowerment, Transformational leadership, Work Engagement and Work Environment." International Journal of Business, Technology and Organizational Behavior (IJBTOB) 2, no. 6 (December 9, 2022): 688–99. http://dx.doi.org/10.52218/ijbtob.v2i6.242.
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This study aims to determine the effect of Empowerment, Transformational Leadership, Work Engagement, Work Environment. Employee well-being is an important topic in human resource management studies because it is believed to be able to produce a positive effect on company achievements. The population in this study were all employees in North Sumatra who had at least 3 years of work experience. The sample in this study was 265 employees, sampling was carried out using a saturated sampling technique or census sampling, where all members of the population were sampled. The data analysis technique used is Structural Equation Modeling (SEM) partial least square. Data processing in this study was assisted by using the Smart PLS3 application. The results showed that: Empowerment has a positive and significant effect on employee well-being.
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Wahyuni, Dini, Harmein Nasution, Irwan Budiman, and Khairini Wijaya. "Analysis of Work Design in Rubber Processing Plant." E3S Web of Conferences 31 (2018): 06009. http://dx.doi.org/10.1051/e3sconf/20183106009.
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The work design illustrates how structured jobs, tasks, and roles are defined and modified and their impact on individuals, groups, and organizations. If the work is not designed well, the company must pay greater costs for workers’ health, longer production processes or even penalties for not being able to meet the delivery schedule. This is visible to the condition in a rubber processing factory in North Sumatra. Work design aspects such as layouts, machinery and equipment, worker's physical working environment, work methods, and organizational policies have not been well-organized. Coagulum grinding machines into sheets are often damaged, resulting in 4 times the delay of product delivery in 2016, the presence of complaints of heat exposure submitted by workers, and workstation that has not been properly arranged is an indication of the need for work design. The research data will be collected through field observation, and distribution of questionnaires related aspects of work design. The result of the analysis depends on the respondent's answer from the distributed questionnaire regarding the 6 aspects studied.
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Dritsas, Elias, Andreas Kanavos, Maria Trigka, Gerasimos Vonitsanos, Spyros Sioutas, and Athanasios Tsakalidis. "Trajectory Clustering and k-NN for Robust Privacy Preserving k-NN Query Processing in GeoSpark." Algorithms 13, no. 8 (July 28, 2020): 182. http://dx.doi.org/10.3390/a13080182.
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Privacy Preserving and Anonymity have gained significant concern from the big data perspective. We have the view that the forthcoming frameworks and theories will establish several solutions for privacy protection. The k-anonymity is considered a key solution that has been widely employed to prevent data re-identifcation and concerns us in the context of this work. Data modeling has also gained significant attention from the big data perspective. It is believed that the advancing distributed environments will provide users with several solutions for efficient spatio-temporal data management. GeoSpark will be utilized in the current work as it is a key solution that has been widely employed for spatial data. Specifically, it works on the top of Apache Spark, the main framework leveraged from the research community and organizations for big data transformation, processing and visualization. To this end, we focused on trajectory data representation so as to be applicable to the GeoSpark environment, and a GeoSpark-based approach is designed for the efficient management of real spatio-temporal data. Th next step is to gain deeper understanding of the data through the application of k nearest neighbor (k-NN) queries either using indexing methods or otherwise. The k-anonymity set computation, which is the main component for privacy preservation evaluation and the main issue of our previous works, is evaluated in the GeoSpark environment. More to the point, the focus here is on the time cost of k-anonymity set computation along with vulnerability measurement. The extracted results are presented into tables and figures for visual inspection.
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Agusta, Rika Omala, and Romat Saragih. "PENGARUH LINGKUNGAN KERJA TERHADAP KINERJA KARYAWAN BADAN NARKOTIKA NASIONAL PROVINSI JAWA BARAT." PERFORMANCE: Jurnal Bisnis & Akuntansi 9, no. 2 (November 8, 2019): 33–42. http://dx.doi.org/10.24929/feb.v9i2.790.
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An organization is synonymous with performance, which is defined as a measure of where an organization is success in achieving the target or not, in the province of West Java BNN in 2017 whose activities realized only reached 54.25%. One of the external factors that can influence is the work environment, it shows that BNN province of West Java has a working environment can create a disgruntled employee.This study was conducted to determine the effect of the work environment on employee performance. The method used in this research is quantitative. Using multiple linear regression with SPSS Ver.23 as data processing tools. From the data processing showed the physical work environment affects 33.1% and non-physical work environment has a greater influence second known 43.2% a significant impact on employee performance. It was concluded that the effect on the performance of employees in the province of West Java BNN is a non-physical work environment, because BNN itself has activities associated with various organizations outside the office.
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A. Karthika, R., K. Dhinakaran, D. Poorvaja, and A. V. Shanbaga Priya. "Cloud Based Medical Image Data Analytics in Healthcare Management." International Journal of Engineering & Technology 7, no. 3.27 (August 15, 2018): 135. http://dx.doi.org/10.14419/ijet.v7i3.27.17744.
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In today’s world, the images form a huge amount of unstructured data from the public and the corporate sector. As a result of the growth of these types of data, modern analytical systems need to interpret and assimilate images. This brings in the need of image processing which involves the transformation from images to analytically organized and structured data. It performs required operation on the given input image and returns the related outputs based on the query. Digital image processing has pushed the envelope for the appraisal in various domains such as healthcare, defense and security, remote sensing, robotic visions, pattern recognitions and satellites. The complication involved in the healthcare domain makes it suitable to explore and induce the concept of image processing and increases the potential for prescriptive analytics. The cloud combined with the Image Processing provides the best environment for analyzing these images using the proposed technique. The proposed work involves processing the input images using the cloud data analytics that provides a user-friendly environment and retrieves the relevant images as well as text for the given user query which produces the outputs that are more efficient in terms of parameters like time, size, security and speed comparatively with the existing data mining process.
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Bolya, Mátyás. "AI-SUPPORTED PROCESSING OF HANDWRITTEN TRANSCRIPTIONS FOR HUNGARIAN FOLK SONGS IN A DIGITAL ENVIRONMENT." Ethnomusic 18, no. 1 (December 2022): 65–82. http://dx.doi.org/10.33398/2523-4846-2022-18-1-65-82.
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My research focuses on creating an AI-supported Digital Research Environment (DRE) that helps analysing and systematizing folk music tunes with the help of the latest information theory and database management results. The study may be ex- tended to the entire source material accumulated by researchers so far, thus inte- grating Hungarian ethnomusicology results of the last hundred years. In this way, new dimensions of structural analysis open up and a large amount of information can be processed that already exceeds the limits of human musical memory. Previous computerized music analysis experiments in Hungary have inadequate- ly defined the role of artificial intelligence. In our case, the AI-supported digital en- vironment that is the subject of the research does not work independently, because the researcher’s scientifically abstract thinking, preferences, and the recognition of characteristic melodic elements cannot yet be replaced by computer data processing. Crucial goal of the research is to precisely define the researcher’s role in musi- cal data processing. Thus the attitude of researchers rejecting software support may 1 The institute previously belonged to the Hungarian Academy of Science, currently it belongs to the ELKH (Eötvös Lóránd Research Network). 2 List of publications: MTMT. Hungarian Scientific Bibliography. URL: https:// m2.mtmt.hu/gui2/?type=authors&mode=browse&sel=10063399 (Access: 23.10.2022). https://doi.org/10.33398/2523-4846-2022-18-1-65-82 66 change in favour of actually using our digital framework. For the first time in Hungar- ian folk music research history, a detailed and documented digital research environ- ment can be created, integrating the useful, relevant software tools. We can map out data entry problems and define the standard format of the musical data suitable for mass input and analysis. If possible, we will replace the previously widely used op- tional data with scalable data to have a broader range of parametrization and search options, and their free combination allows us to study new scientific models. With DRE, the validity range of the previous scientific musical classification can be more precisely specified and the processing as well as classification of unreported melodies and the process of type creating can be significantly accelerated. The most significant debate in the previous research has been the dataset speci- fication of analyses. I am convinced that only similarly processed tune-data-elements can be compared, so one of the most critical tasks is to determine the input data’s standard format and information density. As a first step, the digital conversion of the musical manuscript needs to be solved. International research has mainly led to results in the recognition of printed music, some of which can be used in the project, but many new developments are also needed. Keywords: AI-supported Digital Research Environment (DRE), Optical Music Recognition (OMR), Musical Manuscripts, Hungarian Folk Songs, scientific musical classification, ethnomusicology, digital archives, folklore database.
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Bolya, Mátyás. "AI-SUPPORTED PROCESSING OF HANDWRITTEN TRANSCRIPTIONS FOR HUNGARIAN FOLK SONGS IN A DIGITAL ENVIRONMENT." Ethnomusic 18, no. 1 (December 2022): 65–82. http://dx.doi.org/10.33398/2523-4846-2022-18-2-65-82.
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My research focuses on creating an AI-supported Digital Research Environment (DRE) that helps analysing and systematizing folk music tunes with the help of the latest information theory and database management results. The study may be ex- tended to the entire source material accumulated by researchers so far, thus inte- grating Hungarian ethnomusicology results of the last hundred years. In this way, new dimensions of structural analysis open up and a large amount of information can be processed that already exceeds the limits of human musical memory. Previous computerized music analysis experiments in Hungary have inadequate- ly defined the role of artificial intelligence. In our case, the AI-supported digital en- vironment that is the subject of the research does not work independently, because the researcher’s scientifically abstract thinking, preferences, and the recognition of characteristic melodic elements cannot yet be replaced by computer data processing. Crucial goal of the research is to precisely define the researcher’s role in musi- cal data processing. Thus the attitude of researchers rejecting software support may 1 The institute previously belonged to the Hungarian Academy of Science, currently it belongs to the ELKH (Eötvös Lóránd Research Network). 2 List of publications: MTMT. Hungarian Scientific Bibliography. URL: https:// m2.mtmt.hu/gui2/?type=authors&mode=browse&sel=10063399 (Access: 23.10.2022). https://doi.org/10.33398/2523-4846-2022-18-1-65-82 66 change in favour of actually using our digital framework. For the first time in Hungar- ian folk music research history, a detailed and documented digital research environ- ment can be created, integrating the useful, relevant software tools. We can map out data entry problems and define the standard format of the musical data suitable for mass input and analysis. If possible, we will replace the previously widely used op- tional data with scalable data to have a broader range of parametrization and search options, and their free combination allows us to study new scientific models. With DRE, the validity range of the previous scientific musical classification can be more precisely specified and the processing as well as classification of unreported melodies and the process of type creating can be significantly accelerated. The most significant debate in the previous research has been the dataset speci- fication of analyses. I am convinced that only similarly processed tune-data-elements can be compared, so one of the most critical tasks is to determine the input data’s standard format and information density. As a first step, the digital conversion of the musical manuscript needs to be solved. International research has mainly led to results in the recognition of printed music, some of which can be used in the project, but many new developments are also needed. Keywords: AI-supported Digital Research Environment (DRE), Optical Music Recognition (OMR), Musical Manuscripts, Hungarian Folk Songs, scientific musical classification, ethnomusicology, digital archives, folklore database.
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Et. al., G. Srinivas Reddy,. "DATA PROCESSING THROUGH AN ADDITIVE ROTATIONAL PERTURBATION TECHNIQUE IN A SECURED ENVIRONMENT OF PPRIVACY." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 2 (March 21, 2021): 131–35. http://dx.doi.org/10.17762/itii.v9i2.315.
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As the usage of internet and web applications emerges faster, security and privacy of the data is the most challenging issue which we are facing, leading to the possibility of being easily damaged. Various conventional techniques are used for privacy preservation like condensation, randomization and tree structure etc., the limitations of the existing approaches are, they are not able to maintain proper balance between the data utility and privacy and it may have the problem with privacy violations. This paper presents an Additive Rotation Perturbation approach for Privacy Preserving Data Mining (PPDM). In this proposed work, various dataset from UCI Machine Learning Repository was collected and it is protected with a New Additive Rotational Perturbation Technique under Privacy Preserving Data Mining. Experimental result shows that the proposed algorithm’s strength is high for all the datasets and it is estimated using the DoV (Difference of Variance) method.
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Annapoorani, S., and B. Srinivasan. "Implementation of Effective Data Emplacement Algorithm in Heterogeneous Cloud Environment." Asian Journal of Computer Science and Technology 8, S1 (February 5, 2019): 87–88. http://dx.doi.org/10.51983/ajcst-2019.8.s1.1944.
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This paper is concerned with the study and implementation of effective Data Emplacement Algorithm in large set of databases called Big Data and proposes a model for improving the efficiency of data processing and storage utilization for dynamic load imbalance among nodes in a heterogeneous cloud environment. With the era of explosive information and data receiving, more and more fields need to deal with massive, large scale of data. A method has been proposed with an improved Data Placement algorithm called Effective Data Emplacement Algorithm with computing capacity of each node as a predominant factor that promotes and improves the efficiency in data processing in a short duration time from large set of data. The adaptability of the proposed model can be obtained by minimizing the time with processing efficiency through the computing capacity of each node in the cluster. The proposed solution improves the performance of the heterogeneous cluster environment by effectively distributing data based on the performance oriented sampling as the experimental results made with word count applications.
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Rapiński, Bednarczyk, and Zinkiewicz. "JupyTEP IDE as an Online Tool for Earth Observation Data Processing." Remote Sensing 11, no. 17 (August 21, 2019): 1973. http://dx.doi.org/10.3390/rs11171973.
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The paper describes a new tool called JupyTEP integrated development environment (IDE), which is an online integrated development environment for earth observation data processing available in the cloud. This work is a result of the project entitled “JupyTEP IDE—Jupyter-based IDE as an interactive and collaborative environment for the development of notebook style EO algorithms on network of exploitation platforms infrastructure” carried out in cooperation with European Space Agency. The main goal of this project was to provide a universal earth observation data processing tool to the community. JupyTEP IDE is an extension of Jupyter software ecosystem with customization of existing components for the needs of earth observation scientists and other professional and non-professional users. The approach is based on configuration, customization, adaptation, and extension of Jupyter, Jupyter Hub, and Docker components on earth observation data cloud infrastructure in the most flexible way; integration with accessible libraries and earth observation data tools (sentinel application platform (SNAP), geospatial data abstraction library (GDAL), etc.); adaptation of existing web processing service (WPS)-oriented earth observation services. The user-oriented product is based on a web-related user interface in the form of extended and modified Jupyter user interface (frontend) with customized layout, earth observation data processing extension, and a set of predefined notebooks, widgets, and tools. The final IDE is addressed to the remote sensing experts and other users who intend to develop Jupyter notebooks with the reuse of embedded tools, common WPS interfaces, and existing notebooks. The paper describes the background of the system, its architecture, and possible use cases.
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Zhao, Jia, Jia Sun, Yunan Zhai, Yan Ding, Chunyi Wu, and Ming Hu. "A Novel Clustering-Based Sampling Approach for Minimum Sample Set in Big Data Environment." International Journal of Pattern Recognition and Artificial Intelligence 32, no. 02 (November 12, 2017): 1850003. http://dx.doi.org/10.1142/s0218001418500039.
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The data are rapidly expanding nowadays, which makes it very difficult to analyze valuable information from big data. Most of the existing data mining algorithms deal with big data problems at large time and space costs. This paper focuses on the sampling problem of big data and puts forward an efficient heuristic Cluster Sampling Arithmetic, called CSA. Many of the former researchers adopted random method to extract early sample set from the original data and then made a variety of different processing of the sample in order to obtain the corresponding minimum sample set, which is regarded as a representation of the original big data set. However, the final processing results of big data will be severely affected by the random sampling process at the beginning, resulting in lower comprehensiveness and quality of the final data results and longer processing time. Based on this view, CSA introduces the idea of clustering to obtain minimum sample set of big data, which is in contrast to the random sampling method in the current literature. CSA makes cluster analysis of the original data set and selects the center of each class as centralized members of the minimum sample set. It aims at ensuring that the sample distribution accords with the characteristics of the original data, guarantees the data integrity and reduces the processing time. The max–min distance means that the pattern recognition has been integrated into the clustering process in order to get the clustering center and prevent algorithm from local optimum. The final experimental results show that, compared with the existing work, CSA algorithm can efficiently reflect the characteristics of the original data and reduce the time of data processing. The obtained minimum sample set has also achieved good effects in the classification algorithm.
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Vidal, Vinicius, Leonardo Honório, Milena Pinto, Mario Dantas, Maria Aguiar, and Miriam Capretz. "An Edge-Fog Architecture for Distributed 3D Reconstruction and Remote Monitoring of a Power Plant Site in the Context of 5G." Sensors 22, no. 12 (June 14, 2022): 4494. http://dx.doi.org/10.3390/s22124494.
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It is well known that power plants worldwide present access to difficult and hazardous environments, which may cause harm to on-site employees. The remote and autonomous operations in such places are currently increasing with the aid of technology improvements in communications and processing hardware. Virtual and augmented reality provide applications for crew training and remote monitoring, which also rely on 3D environment reconstruction techniques with near real-time requirements for environment inspection. Nowadays, most techniques rely on offline data processing, heavy computation algorithms, or mobile robots, which can be dangerous in confined environments. Other solutions rely on robots, edge computing, and post-processing algorithms, constraining scalability, and near real-time requirements. This work uses an edge-fog computing architecture for data and processing offload applied to a 3D reconstruction problem, where the robots are at the edge and computer nodes at the fog. The sequential processes are parallelized and layered, leading to a highly scalable approach. The architecture is analyzed against a traditional edge computing approach. Both are implemented in our scanning robots mounted in a real power plant. The 5G network application is presented along with a brief discussion on how this technology can benefit and allow the overall distributed processing. Unlike other works, we present real data for more than one proposed robot working in parallel on site, exploring hardware processing capabilities and the local Wi-Fi network characteristics. We also conclude with the required scenario for the remote monitoring to take place with a private 5G network.
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Ye, Jiu Yan, Bin Chen, Zun Lin Ke, Jian Chen, and Yu Fang. "The Application of Big Geospatial Data in Smart Agriculture." Advanced Materials Research 955-959 (June 2014): 3835–39. http://dx.doi.org/10.4028/www.scientific.net/amr.955-959.3835.
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With the fast development of data acquisition and web transmission, the age of big geospatial data(BGD) has come. BGD will greatly change peoples’ life-style of and our society’s work mode. In agriculture field, there will also be a lot of changes brought by BGD in future. In this paper, we had a study on the processing of BGD and its application in agriculture. Firstly, we introduced BGD including its definition, value and application areas. Secondly, we summarized the research progress and key technologies of BGD processing in the cloud computing environment. Lastly, we talked about the application of BGD in agriculture industry and looked forward to its development trend.
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Pirotti, F., A. Guarnieri, A. Masiero, A. Vettore, and E. Lingua. "Processing lidar waveform data for 3D visual assessment of forest environments." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-5 (June 6, 2014): 493–99. http://dx.doi.org/10.5194/isprsarchives-xl-5-493-2014.
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The objective of this report is to present and discuss a work-flow for extracting, from full-waveform (FW) lidar data, formats which are compatible with common information systems (GIS) and statistical software packages. Full-waveform, specifically for forestry, got attention from the scientific community because a more in-depth analysis can add valuable information for classification and modelling of related variables (e.g. biomass). In order to assess if this is feasible and if the results are useful, the end-user has to deal with raw datasets from lidar sensors. In this study case we propose and test a work-flow which is implemented through a selfdeveloped software integrating ad-hoc C++ libraries and a graphical user interface for an easier approach by end-users. This software allows the user to add raw FW data and produce several products which can successively be easily imported in GIS or statistical software. To achieve this we used some state-of-the-art methods which have been extensively reported in literature and we discuss results and future developments. Results show that this software package can effectively work as a tool for linking raw FW data with forest-related spatial processing by providing punctual information directly derived from the FW data or area-based aggregated information for a more generalized description of the earth surface.
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S, Antony. "Effect of Work Environment, Leadership, Compensation and Employment Training to Employee Involvement." Journal of Global Business and Management Review 1, no. 2 (December 26, 2019): 10. http://dx.doi.org/10.37253/jgbmr.v1i2.651.
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This study was conducted with the aim to determine the effect of the work environment, leadership, compensation and work training variables on employee involvement variables in star hotels in Batam. This research was conducted using a survey method through a questionnaire to 380 respondents, namely employees of five-star hotels in Batam. After being distributed directly to respondents, the questionnaire was collected and managed to get 340 questionnaires filled out completely and then the authors tested the regression data using the SPSS program. From the results of data processing with SPSS it is known that there is a relationship in all variables studied. Based on the results of this study, the relationship between work environment variables, leadership, compensation and work training in employee attachment variables is known, so it is expected that star hotel management can pay attention to the variables studied earlier and manage employee attachments as one of the added values and advantages of the hotel.
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Verma, Garima, and Soumen Kanrar. "A novel model to enhance the data security in cloud environment." Multiagent and Grid Systems 18, no. 1 (May 23, 2022): 45–63. http://dx.doi.org/10.3233/mgs-220361.
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Nowadays cloud computing has given a new paradigm of computing. Despite several benefits of cloud computing there is still a big challenge of ensuring confidentiality and integrity for sensitive information on the cloud. Therefore to address these challenges without loss of any sensitive information and privacy, we present a novel and robust model called ‘Enhanced Cloud Security using Hyper Elliptic Curve and Biometric’ (ECSHB). The model ECSHB ensures the preservation of data security, privacy, and authentication of data in a cloud environment. The proposed approach combines biometric and hyperelliptic curve cryptography (HECC) techniques to elevate the security of data accessing and resource preservations in the cloud. ECSHB provides a high level of security using less processing power, which will automatically reduce the overall cost. The efficacy of the ECSHB has been evaluated in the form of recognition rate, biometric similarity score, False Matching Ratio (FMR), and False NonMatching Ratio (FNMR). ECSHB has been validated using security threat model analysis in terms of confidentiality. The measure of collision attack, replay attack and non-repudiation is also considered in this work. The evidence of results is compared with some existing work, and the results obtained exhibit better performance in terms of data security and privacy in the cloud environment.
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Tajitsu, Yoshiro, Jun Takarada, Kohei Takatani, Riku Nakanishi, Hiroki Yanagimoto, Seita Shiomi, Isamu Nakagawa, et al. "A Prototype Sensor System Using Fabricated Piezoelectric Braided Cord for Work-Environment Measurement during Work from Home." Micromachines 12, no. 8 (August 15, 2021): 966. http://dx.doi.org/10.3390/mi12080966.
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We proposed a new prototype sensor system to understand the workload of employees during telework. The goal of sensing using such a system is to index the degree of stress experienced by employees during work and recognize how to improve their work environment. Currently, to realize this, image processing technology with a Web camera is generally used for vital sign sensing. However, it creates a sense of discomfort at work because of a strong sense of surveillance. To truly evaluate a working environment, it is necessary that an employee be unaware of the sensor system and for the system to be as unobtrusive as possible. To overcome these practical barriers, we have developed a new removable piezoelectric sensor incorporated in a piezoelectric poly-L-lactic acid (PLLA) braided cord. This cord is soft and flexible, and it does not cause any discomfort when attached to the cushion cover sheet. Thus, it was possible to measure the workload of an employee working from home without the employee being aware of the presence of a sensor. Additionally, we developed a system for storing data in a cloud system. We succeeded in acquiring continuous long-term data on the vital signs of employees during telework using this system. The analysis of the data revealed a strong correlation between behavior and stress.
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Li, Xilin, Malcolm S. Powell, and Tim Horberry. "Human Factors in Control Room Operations in Mineral Processing." Journal of Cognitive Engineering and Decision Making 6, no. 1 (January 5, 2012): 88–111. http://dx.doi.org/10.1177/1555343411432340.
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This study applied human factors research approaches to the complex and dynamic environment of mineral processing plants. In this domain, little formal human factors research has previously been undertaken, despite that human performance limitations are frequently noted as a bottleneck to effective production. This article presents a broad, operator-centered investigation on the current status of control room operations and explores the underlying barriers in the operators’ work environment. A total of 20 operators working at two types of Australian mineral processing plants were involved. Multiple data collection methods, including in situ observations and interviews, surveys, and reviews of documentation, were used. The findings revealed that operator control was essentially in a reactive mode, with operators often lacking the will or ability to engage in process optimization. A simplified work domain analysis was used to highlight the essential elements involved in operator control and to explore the gaps between the observed reactive behavior and the required proactive control employed by operators. Also, this study uncovered deficiencies in the current information and organizational environments constraining operator control ability. These deficiencies included poorly designed human-machine interface and alarms, insufficient operator training, and inappropriate task allocations. Further research for enhancing operator capacity is recommended and highlighted.
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Prabha A, Jothi, Bhargavi R, and Ramesh Ragala. "Prediction of dyslexia using support vector machine in distributed environment." International Journal of Engineering & Technology 7, no. 4 (October 6, 2018): 2795. http://dx.doi.org/10.14419/ijet.v7i4.17222.
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Dyslexia is a learning disorder characterized by lack of reading and /or writing skills, difficulty in rapid word naming and also poor in spelling. Dyslexic individuals have great difficulty to read and interpret words or letters. Research work is carried out to classify dyslexic from non-dyslexics by various approaches such as machine learning, image processing, understanding the brain behavior through psychology, studying the differences in anatomy of brain. In addition to it several assistive tools are developed to support dyslexics. In this work, brain images are used for screening individuals who have high risk to dyslexia. This work also motivates the application of machine learning in distributed environment. The proposed predictive model uses the machine-learning algorithm Support Vector Machine (SVM). The model is designed in Apache SPARK framework to support voluminous data. The prediction accuracy of 92.5% is achieved using SVM.
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Omar, Hoger Khayrolla, and Alaa Khalil Jumaa. "Distributed big data analysis using spark parallel data processing." Bulletin of Electrical Engineering and Informatics 11, no. 3 (June 1, 2022): 1505–15. http://dx.doi.org/10.11591/eei.v11i3.3187.
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Nowadays, the big data marketplace is rising rapidly. The big challenge is finding a system that can store and handle a huge size of data and then processing that huge data for mining the hidden knowledge. This paper proposed a comprehensive system that is used for improving big data analysis performance. It contains a fast big data processing engine using Apache Spark and a big data storage environment using Apache Hadoop. The system tests about 11 Gigabytes of text data which are collected from multiple sources for sentiment analysis. Three different machine learning (ML) algorithms are used in this system which is already supported by the Spark ML package. The system programs were written in Java and Scala programming languages and the constructed model consists of the classification algorithms as well as the pre-processing steps in a figure of ML pipeline. The proposed system was implemented in both central and distributed data processing. Moreover, some datasets manipulation manners have been applied in the system tests to check which manner provides the best accuracy and time performance. The results showed that the system works efficiently for treating big data, it gains excellent accuracy with fast execution time especially in the distributed data nodes.
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Taufik, Mokhamad, and Sukma Irdiana. "Influence Of Leadership, Motivation, Cylinary And Work Environment To Employee Performance." Wiga : Jurnal Penelitian Ilmu Ekonomi 7, no. 2 (September 1, 2017): 88–96. http://dx.doi.org/10.30741/wiga.v7i2.152.
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This study aims to determine the influence of leadership, motivation, discipline, and work environment significantly partially and simultaneously to the performance of subdistrict officials in Lumajang District. In this study used quantitative research methods using multiple linear regression analysis tools. Respondents were 78 subdistrict officials in Lumajang District. Thenresults of this study are and documentation and continued with data processing to draw conclusions. From this research, it can be concluded that Leadership, motivation and work environment there is no significant partial positive effect on the performance of sub-district officials in Lumajang District. partially on the performance While the discipline there is a significant positive influence of subdistrict officials in Lumajang District. Simultaneously Leadership, motivation, discipline and work environment there is a significant positive influence partially on the performance of subdistrict officials in Lumajang District. The variables studied have an effect of 40.2% on employee performance, and the rest is influenced by other variables.
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Taufik, Mokhamad, and Sukma Irdiana. "Influence of leadership, motivation, cylinary and work environment to employee performance." Wiga : Jurnal Penelitian Ilmu Ekonomi 7, no. 2 (December 12, 2018): 88–96. http://dx.doi.org/10.30741/wiga.v7i2.343.
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This study aims to determine the influence of leadership, motivation, discipline, and work environment significantly partially and simultaneously to the performance of subdistrict officials in Lumajang District. In this study used quantitative research methods using multiple linear regression analysis tools. Respondents were 78 subdistrict officials in Lumajang District. The results of this study are and documentation and continued with data processing to draw conclusions. From this research, it can be concluded that Leadership, motivation and work environment there is no significant partial positive effect on the performance of sub-district officials in Lumajang District. partially on the performance While the discipline there is a significant positive influence of subdistrict officials in Lumajang District. Simultaneously Leadership, motivation, discipline and work environment there is a significant positive influence partially on the performance of subdistrict officials in Lumajang District. The variables studied have an effect of 40.2% on employee performance, and the rest is influenced by other variables.
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Schüffler, Arnulf Sebastian, Christof Thim, Jennifer Haase, Norbert Gronau, and Annette Kluge. "Information Processing in Work Environment 4.0 and the Beneficial Impact of Intentional Forgetting on Change Management." Zeitschrift für Arbeits- und Organisationspsychologie A&O 64, no. 1 (January 2020): 17–29. http://dx.doi.org/10.1026/0932-4089/a000307.
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Abstract. Industry 4.0, based on increasingly progressive digitalization, is a global phenomenon that affects every part of our work. The Internet of Things (IoT) is pushing the process of automation, culminating in the total autonomy of cyber-physical systems. This process is accompanied by a massive amount of data, information, and new dimensions of flexibility. As the amount of available data increases, their specific timeliness decreases. Mastering Industry 4.0 requires humans to master the new dimensions of information and to adapt to relevant ongoing changes. Intentional forgetting can make a difference in this context, as it discards nonprevailing information and actions in favor of prevailing ones. Intentional forgetting is the basis of any adaptation to change, as it ensures that nonprevailing memory items are not retrieved while prevailing ones are retained. This study presents a novel experimental approach that was introduced in a learning factory (the Research and Application Center Industry 4.0) to investigate intentional forgetting as it applies to production routines. In the first experiment ( N = 18), in which the participants collectively performed 3046 routine related actions (t1 = 1402, t2 = 1644), the results showed that highly proceduralized actions were more difficult to forget than actions that were less well-learned. Additionally, we found that the quality of cues that trigger the execution of routine actions had no effect on the extent of intentional forgetting.
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Zhu, Wei. "Personal Information Security Environment Monitoring and Law Protection Using Big Data Analysis." Journal of Environmental and Public Health 2022 (October 7, 2022): 1–12. http://dx.doi.org/10.1155/2022/1558161.
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This article explores the causes of the issues with personal data privacy and outlines the limitations of China’s current legal framework. This article makes the argument that, in the information age, self-discipline and legal protection should be combined in order to safeguard personal information safety. It also makes specific recommendations for strengthening legal protection. This research also develops a data processing platform for data safety and privacy protection while studying the technology of data safety environment monitoring and privacy protection. This work develops optimization methodologies, such as dynamic privacy budget allocation, to increase the model’s speed of convergence and the calibre of the generated data. It adjusts to various privacy and timeliness needs under the assumption that the objective of selective matching of private safety will be satisfied. According to the experimental findings, this algorithm’s accuracy can reach 96.27%. This method enhances the model’s speed of convergence and the calibre of the data created, and it addresses the flaw that the present data fusion publishing procedure cannot withstand the attack of background information. The study’s findings can serve as a starting point for future work on data security and the protection of personal information.
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Smelyanskii, R. L. "МС2Е: The Meta-Cloud Computing Environment for Interdisciplinary Studies." Herald of the Russian Academy of Sciences 92, no. 1 (February 2022): 40–48. http://dx.doi.org/10.1134/s1019331622010051.
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Abstract The Meta-Cloud Computing Environment (MC2E) is a Russian‒Chinese project dedicated to the study of methods and tools for building an information and computing environment for scientific computational experiments and interdisciplinary research, which ended in 2020. Work in this area was focused on the federation principle of organizing computations and data management, providing for the creation of a specialized heterogeneous ecosystem of data centers with virtualized infrastructure and high-performance computers, united by telecommunication resources—a data transmission network. One of the key problems of building such an ecosystem, central to the MC2E project, is the integration of high-performance computers and data processing centers—cloud computing environments based on server clusters. A brief overview of the main results of the project are presented.
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B. A. Alaasam, Ameer. "The Challenges and Prerequisites of Data Stream Processing in Fog Environment for Digital Twin in Smart Industry." International Journal of Interactive Mobile Technologies (iJIM) 15, no. 15 (August 11, 2021): 126. http://dx.doi.org/10.3991/ijim.v15i15.24181.
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<p class="0abstract">Smart industry systems are based on integrating historical and current data from sensors with physical and digital systems to control product states. For example, Digital Twin (DT) system predicts the future state of physical assets using live simulation and controls the current state through real-time feedback. These systems rely on the ability to process big data stream to provide real-time responses. For, example it is estimated that one autonomous vehicle (AV) could produce 30 terabytes of data per day. AV will not be on the road before using an effective way to managing its big data and solve latency challenges. Cloud computing failed in the latency challenge, while Fog computing addresses it by moving parts of the computations from the Cloud to the edge of the network near the asset to reduce the latency. This work studies the challenges in data stream processing for DT in a fog environment. The challenges include fog architecture, the necessity of loosely-coupling design, the used virtual machine versus container, the stateful versus stateless operations, the stream processing tools, and live migration between fog nodes. The work also proposes a fog computing architecture and provides a vision of the prerequisites to meet the challenges.</p>
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Sadewo, I. Putu, Surachman Surachman, and Rofiaty Rofiaty. "The influence of working environment to employee performance mediated by work motivation." International Journal of Research in Business and Social Science (2147- 4478) 10, no. 3 (May 1, 2021): 213–22. http://dx.doi.org/10.20525/ijrbs.v10i3.1112.
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This study examines the effect of work environment on retail store employee performance in Malang, Indonesia with the role of work motivation as a mediation. Respondents in this study used 152 respondents who were millennials employees of retail stores in Malang Indonesia. This study uses a statistical analysis of the Structured Equation Model and Partial Least Square. WarpPLS is used as a data processing program for hypothesis testing. The test results show that the work environment has a significant effect of 0.259 on employee performance. The work environment at the retail stores also has a significant effect of 0.742 on work motivation. Work motivation also provides significant results on employee performance of 0.234. The mediating role of work motivation on the work environment and employee performance in retail stores throughout Malang, Indonesia has a significant mediating effect of 0.170
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Kh-madhloom, Jamal. "Fog Integrated Secured and Distributed Environment for Healthcare Industry with Software Defined Networking." Wasit Journal of Computer and Mathematics Science 1, no. 1 (March 17, 2021): 17–30. http://dx.doi.org/10.31185/wjcm.vol1.iss1.5.
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Fog computing is a segment of cloud computing where a vast number of peripheral equipment links to the internet. The term "fog" indicates the edges of a cloud in which high performance can be achieved. Many of these devices will generate voluminous raw data as from sensors, and rather than forward all this data to cloud-based servers to be processed, the idea behind fog computing is to do as much processing as possible using computing units co-located with the data-generating devices, so that processed rather than raw data is forwarded, and bandwidth requirements are reduced. A major advantage of processing locally is that data is more often used for the same computation machine which produced the data. Also, the latency between data production and data consumption was reduced. This example is not fully original, since specially programmed hardware has long been used for signal processing. The work presents the integration of software defined networking with the association of fog environment to have the cavernous implementation patterns in the health care industry with higher degree of accuracy.
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Wijaya, Welly Saputri, Vince Ratnawati, and Andreas Andreas. "THE EFFECT OF JOB STRESS AND WORK ENVIRONMENT ON TAX AUDITOR PERFORMANCE: MOTIVATION AS A VARIABLE OF MEDIATION." INTERNATIONAL JOURNAL OF ECONOMICS, BUSINESS AND APPLICATIONS 6, no. 1 (June 27, 2021): 1. http://dx.doi.org/10.31258/ijeba.6.1.1-10.
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This study has several objectives, first to analyze the effect of job stress, work environment and motivation on the performance of tax auditors. Second, analyze the effect of job stress, work environment on the motivation. Third, to analyze the effect of job stress and work environment on the performance of tax auditors after being mediated by motivation. Motivation is expected to have an influence on the performance of tax auditors. The population of this research are 166 tax auditors in the Riau General Directorate Regional Office environment as many as 153 people and the sampling method is saturated samples. Data processed is primary data obtained by processing questionnaire data and were analyzed with the help of the Smart PLS Version 3.2.8 program. The results of the study prove that job stress does not affect the performance of the tax auditors. Work environment and motivation positively and significantly affect the performance of tax auditors. Job stress and work environment significantly affect the motivation. The last, that motivation does mediate the relationship between job stress and work environment to the performance of tax auditors.
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Enguix, Ivan Felis, Pablo Ruiz, and Manuel de la Torre. "Online Digitalization Technologies for Monitoring Activities in the Marine Environment." Proceedings 42, no. 1 (November 14, 2019): 59. http://dx.doi.org/10.3390/ecsa-6-06530.
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This proceeding shows the results of the investigation of the techniques of the integration, management, and visualization of massive data from the digitalization of environmental and procedural parameters of facilities that operate in the marine environment. The work focuses on three main lines: (1) research on the development of a cloud-based system for big data, which allows the hosting of the data generated by different devices to be monitored (GPS, sounds, vibrations, video, temperature, emissions, consumption, power, etc.); (2) the implementation of a first layer of analysis and visualization of information; and (3) big data analytics research for the post-processing of information. The studies will be applied to underwater noise monitoring. With this, progress has been made in another of the pillars of Web 4.0—the use of context information—as the application is in charge of intelligently processing the data of the different variables together although they are not, in principle, directly related.
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Kulakova, Irina. "AUTOMATED PROCESSING OF PACS DATA IN SPREADSHEETS." Modern Technologies and Scientific and Technological Progress 2022, no. 1 (May 16, 2022): 119–20. http://dx.doi.org/10.36629/2686-9896-2022-1-119-120.
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The problem of automated processing of ACS data on fixing the movement of employees, determining the time of passage through the turnstile during working hours and the absence of employee movements during the work shift is considered. The implementation was carried out in spreadsheets with the help of calculations in the cells of the table
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Huang, Weihua. "Research on the Revolution of Multidimensional Learning Space in the Big Data Environment." Complexity 2021 (May 18, 2021): 1–12. http://dx.doi.org/10.1155/2021/6583491.
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Multiuser fair sharing of clusters is a classic problem in cluster construction. However, the cluster computing system for hybrid big data applications has the characteristics of heterogeneous requirements, which makes more and more cluster resource managers support fine-grained multidimensional learning resource management. In this context, it is oriented to multiusers of multidimensional learning resources. Shared clusters have become a new topic. A single consideration of a fair-shared cluster will result in a huge waste of resources in the context of discrete and dynamic resource allocation. Fairness and efficiency of cluster resource sharing for multidimensional learning resources are equally important. This paper studies big data processing technology and representative systems and analyzes multidimensional analysis and performance optimization technology. This article discusses the importance of discrete multidimensional learning resource allocation optimization in dynamic scenarios. At the same time, in view of the fact that most of the resources of the big data application cluster system are supplied to large jobs that account for a small proportion of job submissions, while the small jobs that account for a large proportion only use the characteristics of a small part of the system’s resources, the expected residual multidimensionality of large-scale work is proposed. The server with the least learning resources is allocated first, and only fair strategies are considered for small assignments. The topic index is distributed and stored on the system to realize the parallel processing of search to improve the efficiency of search processing. The effectiveness of RDIBT is verified through experimental simulation. The results show that RDIBT has higher performance than LSII index technology in index creation speed and search response speed. In addition, RDIBT can also ensure the scalability of the index system.
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Rulianti, Erina, Giri Nurpribadi, and Roni Amirudin. "Peran Motivasi dalam Memediasi Pengaruh Lingkungan Kerja terhadap Kinerja Karyawan." Jesya (Jurnal Ekonomi & Ekonomi Syariah) 4, no. 2 (May 29, 2021): 963–73. http://dx.doi.org/10.36778/jesya.v4i2.458.
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The purpose of this study is to explain the role of motivational mediation on the influence of the work environment on the performance of employees of PT Hung-A Indonesia. This research is quantitative in nature using a questionnaire as a data collection tool. The population in this study were employees of PT Hung-A Indonesai Hi End Factory division with 81 samples obtained from the Slovin formula. The independent variable in this study is the work environment, the dependent variable is employee performance and the work motivation variable is the mediating variable. Data analysis in this study used path analysis. By processing data using Smart PLS 3.0. The results showed that work environment variables had an effect on employee performance. Work environment variables affect motivation. Motivation variables have an effect on employee performance, and motivation is able to mediate the influence of the work environment on employee performance.
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Kaur, Jaspreet, and Navdeep Kaler. "DESIGN AND IMPLEMENTATION OF AN OTP BASED DATA SECURITY MODEL INCOPERATING AES AND SHA2 IN CLOUD ENVIRONMENT." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 17, no. 1 (January 16, 2018): 7081–91. http://dx.doi.org/10.24297/ijct.v17i1.6930.
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Cloud computing has revolutionized the way computing and software services are delivered to the clients on demand. It offers users the ability to connect to computing resources and access IT managed services with a previously unknown level of ease. Thus, security concerns among users of the cloud have become a major barrier to the widespread growth of cloud computing. In this research work, we have used the 3 step security mechanism for the keeping the data secure at the cloud. We have implemented the strong authentication mechanism using AES encrypted OTP and enhanced the security of data using Cloud Broker and AES. When you log on to your machine and then try to access a resource, say a file server or database, something needs to assure that your username and password are valid. With sensitive data stored in the cloud of the different users, we need a strong authentication mechanism along with OTP. Data breaches because of no/weak authentication. Afterwards we have verified the integrity of data stored at cloud provider using SHA2. Multiple parameters like processing time, processing cost, AES encryption time, OTP generation and encryption time have been calculated and analyzed. We have been able to enhance the security by optimizing the processing time as well as processing cost. After implementing the proposed methodology, it has been summarized that the cloud security can be enhanced by applying the proposed mechanism. The proposed system has reduced the complexity, processing cost which increases the overall efficiency of the system.
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Tajboš, Jozef, and Valéria Messingerová. "Carbon monoxide contamination by wood harvesting and processing." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 57, no. 2 (2009): 135–44. http://dx.doi.org/10.11118/actaun200957020135.
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Analysis of work environment contamination with carbon oxide by harvesting and wood processing with using of motomanually technology – one-man chainsaw is presented in this paper. This activity belongs to categories of heavy up to very heavy works according to power consumption. Due to psychophysiological load is considered as dynamic work, combined with neuropsychical load by decisions about assortments and safe motion during harvesting and manipulation process.Risk of carbon monoxide (CO) intoxication is inflicted his strong affinity to haemoglobin (Hb). Carbon monoxide produce with haemoglobin karboxyhemoglobin (COHb), whereby disable transmission of oxygen in form oxyhaemoglogin (OHb) from lungs to tissues. Binding of oxide carbon on haemoglobin is approximately two-hundred times stronger as with oxygen.The measures was made with use of multichannel detector of gas and exhalation Drager X-am 7000 (Germany). Data about contamination was recording in one second intervals, with precision on 1 ppm. By harvesting and too by wood processing were realized three independent observation. Data were processing with standard mathematical-statistic methods – sorting and ranking, regression analysis, test of average deuces and evaluation of frequency in classes.
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Maharani, Anita, Moch Zaenal Abidin, Cipto Adi Pringgodigdo, and Indra Priyahutama. "Dinamika Lingkungan Kerja, Pengalaman Kerja, Karakteristik Pekerjaan Dan Kompetensi Manajerial Di Perusahaan Pertambangan Di Indonesia." Jurnal Manajemen 12, no. 2 (June 2, 2021): 168. http://dx.doi.org/10.32832/jm-uika.v12i2.4355.
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<p><em>This study aims to see how the work environment's dynamics, work experience, job characteristics, and managerial competencies affect managerial competence. The literature that this research refers to primarily uses the concept of competence and other concepts relevant to the study's discussion. This research method is through a quantitative approach, data collection through distributing questionnaires to 279 respondents who work in mining companies in Indonesia, and data processing using SPSS concerning the regression value to determine whether the research hypothesis is proven or not. This study indicates that work environment, work experience, and job characteristics affect managerial competence.</em></p>
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Hes, Aleš. "Global communication environment For B2B markets." SHS Web of Conferences 74 (2020): 02007. http://dx.doi.org/10.1051/shsconf/20207402007.
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Currently, there is an unprecedented development of modern communication technologies in B2B markets. In the context of Industry 4.0, globalization influences are increasingly reflected in the new information technologies that are becoming the domain of communication in B2B markets. The manufacturing environment is shaped by the ability to work with Big Data Analysis, use computer simulation tools and augmented reality and today’s phenomenon is evolving in the processing and business environment - linking the Internet of Things, Services and People to Potential production environment. An important role in this global interconnection of both manufacturing and processing - business environments is played by the communication conditions determined by sufficient capacity computing power. One of the real preconditions for B2B markets is to make full use of the cloud-based platform based on the establishment of dedicated data centres with the possibility of using high level of Service Level Agreement for B2B business partners. The paper deals with the evaluation and analysis of the possibilities of digitalization development in the company space, to examine the new global communication environment by using cloud computing and its impact on the quality of information service for customers. The influence of intercultural communication on the behaviour of business partners is examined.
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Ullah, Wasi, Irshad Hussain, Iram Shehzadi, Zahid Rahman, and Peerapong Uthansakul. "Tracking a Decentralized Linear Trajectory in an Intermittent Observation Environment." Sensors 20, no. 7 (April 9, 2020): 2127. http://dx.doi.org/10.3390/s20072127.
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Faults and failures are familiar case studies in centralized and decentralized tracking systems. The processing of sensor data becomes more severe in the presence of faults/failures and/or noise. Effective schemes have been presented for decentralized systems, in the presence of faults only. In some practical scenarios of systems, there are certain interruptions in addition to these faults. These interruptions may occur in the form of noise. However it is expected that the decision about the sensor data is difficult in the presence of noise. This is because the noise adversely affects the communication amongst sensors and the processing unit. More complexity is expected when there are faults and noise simultaneously. To deal with this problem, in addition to existing fault detection and isolation schemes, the Kalman filter is employed. Here, a generic discussion is provided, which is equally applicable to other situations. This work addresses various faults in the presence of noise for decentralized tracking systems. Local single faults and multiple faults in the presence of noise are the core issues addressed in this paper. The proposed work is comprised of a general scenario for a decentralized tracking system followed by a case study of a target tracking scenario with and without noise. The presented schemes are also tested for different types of faults. The proposed work presents effective tracking in the presence of noise and faults. The results obtained demonstrate the acceptable performance of the scheme of this work.