Data Processing Program Research Articles

THE CONCEPT OF A DANCE LESSON FOR PROMOTION OF WELL-BEING OF ADULTS

The context of the Covid-19 pandemic has highlighted the idea of improving the quality of life and health of people in the context of modern research. If a person is satisfied with himself, has self-realized, with a good physical well-being, he feels satisfied with life in general, thus promoting a quality of life for himself. There is an ageism perception in society that dance classes are suitable for young people. However, when forms of artistic expression are used to promote well-being in adults, it gains an existential dimension. Dance learning in this interpretation includes internalization of body management and dance technique, self-efficacy, positivity, and self-awareness. Therefore, studies focused on the positive effects of dance lessons on mental and physical health in adults are leading to increased interest, thereby contributing to promotion of well-being and healthy ageing. The aim of this publication is to identify the components of well-being in adult dance classes in the context of lifelong learning and to formulate the concept of dance classes. The study data were analysed using the qualitative data processing program NVivo 12.0. As a result, the components of the well-being of dance class participants have been identified, and an explanation of the individual dynamic balance of well-being content within the homeostasis approach is offered, which is the basis of the pedagogical concept.

PSYCHO-EMOTIONAL CLIMATE TO REDUCE THE RISK OF DROP OUT IN THE CONTEXT OF HIGHER EDUCATION

The high number of students who have dropped out of higher education prompts to find out both the reasons for dropping out and the causes of dissatisfaction. The psycho-emotional climate of an educational institution is considered to be one of the indicators of the quality of the institution's organizational culture and performance, which determines its pedagogical effectiveness. Therefore, at the moment when the idea of institutional accreditation seriously marks its place in the accreditation process, there is a growing interest in research, the subject of which is the psycho-emotional climate of a higher education institution as a pedagogical resource. The aim of this publication is to identify the psycho-emotional risks of drop out among the students. The research methodology consists of a set of qualitative data obtained by surveying 50 students who have expressed an intention to drop out. The study data were analysed using the qualitative data processing program NVivo 12.0. The study analysed and described the theoretical framework of the psycho-emotional climate and identified the main risks of drop out. It is concluded that the psycho-emotional climate is an essential component of students' desire to continue their studies, as it promotes the institutional sense of belonging and learning achievements. The results of this study complement existing research with qualitative data, operationalizing psycho-emotional support in higher education settings.

Construction of Artistic Design Patterns Based on Improved Distributed Data Parallel Computing of Heterogeneous Tasks

With the continuous upgrading of hardware in the terminal equipment, how to provide high-performance computing for low-tech threshold users has become a current research hotspot. In the era of green high-performance computing, the heterogeneous computing system can provide good versatility, performance, and efficiency and has broad development prospects. This article provides an in-depth analysis and research on the construction and application of improved models using the artistic design pattern of heterogeneous tasks and parallel computing. Based on the hardware resources in the existing desktop system, this article optimizes the original heterogeneous parallel technology from the aspects of task division and data transmission to reduce the complexity of data allocation and processing for users. Based on the analysis and study of the multicore CPU and GPU architectures in the desktop system, as well as the original CPU-GPU heterogeneous parallel technology, this article optimizes the solution of heterogeneous parallel computing, designs a heterogeneous parallel computing architecture, and deploys a heterogeneous parallel computing architecture. The nodes of the desktop system constitute the parallel computing system. In terms of task allocation, the computing system divides tasks according to the parallelism of tasks. According to the computing resources and bandwidth conditions of each heterogeneous node, starting from the parallel execution time, the task scheduling algorithm is optimized, and the load balancing scheduling scheme is designed to achieve the optimal allocation of resources. In terms of storage resources, the computing system adopts distributed storage as a whole. The CPU-GPU heterogeneous parallel in the desktop system adopts virtual unified storage. Global distributed storage and local shared storage are used to balance overall performance and programming complexity. This article introduces the design and implementation of JTangSync, a distributed heterogeneous data synchronization system. The system adopts a distributed architecture, and each node is organized by a data source module, a data transmission module, a processor module, etc. The data source module is responsible for extracting data, the data transmission module is mainly responsible for efficient data transmission, and the processor module is responsible for data processing. More importantly, each module is designed as a replaceable plug-in, which is convenient for secondary expansion. Each node relies on ZooKeeper to form a cluster, which realizes distributed functions such as centralized management of distributed resources, failover, and resumed transmission. Compared with the mainstream scheduling algorithms HEFT, CPOP, PEFT, and HSIP on heterogeneous systems participating in the experimental evaluation, the scheduling length ratio of DONF series algorithms is reduced by 36.3%–67.5% and the parallelism is increased by 17%–125% in terms of efficiency. Compared with the existing database synchronization system, the JTangSync system has built-in multiple heterogeneous database data sources and supports the synchronization of complex heterogeneous databases. The system supports users to develop and customize their own data sources and data processing programs, to promote secondary development. By adopting the custom compressed data exchange format and network optimization methods such as packet merging, caching, and adaptive compression algorithm, the system has high performance.

Lifestyles related to NCD and utilization of preventive services among adults

Leading behavioural risk factors for non communicable diseases (NCD) are smoking, harmful use of alcohol, physical inactivity and unhealthy diet. More than half of population between age 30 and 70 years die annually from NCDs which could be prevented by promotive and preventive measures. Goal of the paper is to determine lifesyle factors related to non communicable diseases and utilization of preventive services in primary health care center Zvezdara in Belgrade. Survey is cross sectional study with sample size of 210 adults randomly selected. The analysis of the survey data was performed using the statistical data processing program SPSS 19.0 for Windows. Lifestyles factors related to NCDs among adult population in Belgrade are smoking (38,1%), alcohol consumption (32,9%), poor eating habits with high salt intake, more than 5g (29%) and inadequate frequency of meals (61%), sedentary lifestyles during working time (27,1%) and during leisure time (20,4%). Only 16,7% of population have moderate physical activity according to WHO recommentations. Preventive services utilized each third men and each fifth women, people with high level of education (p=0.001), professionals (p=0.007) who are living in good social conditions (p=0.000). Preventive services need to be organized more flexible in relation to public opinion using modern methods of health education via electronic services, media and mobile communications.

A two-level formal model for Big Data processing programs

• A high-level model for iterative and non-iterative large-scale data processing programs. • Formalizing data flow with Petri Nets and data processing operations with Monoid Algebra. • Application of the model to formalize mutation operators for mutation testing in data flow programs. • Proposal of new mutation operators for iterative data flow programs. This paper proposes a model for specifying data flow-based parallel data processing programs agnostic of target Big Data processing frameworks. The paper focuses on the formal abstract specification of non-iterative and iterative programs, generalizing the strategies adopted by data flow Big Data processing frameworks. The proposed model relies on Monoid Algebra and Petri Nets to abstract Big Data processing programs in two levels: a higher level representing the program data flow and a lower level representing data transformation operations (e.g., filtering, aggregation, join). We extend the model for data processing programs proposed in [1] , for modeling iterative data processing programs. The general specification of these programs implemented by data flow-based parallel programming models is essential given the democratization of iterative and greedy Big Data analytics algorithms. Indeed, these algorithms call for revisiting parallel programming models to express iterations. The paper gives a comparative analysis of the iteration strategies proposed by Apache Spark, DryadLINQ, Apache Beam, and Apache Flink. It discusses how the model achieves to generalize these strategies.

PENGARUH KOMPENSASI, KOMUNIKASI, DAN BEBAN KERJA TERHADAP KEPUASAN KERJA KARYAWAN PT. PUSAKA

This study aims to determine the effect of Compensation, Communication, and Workload on Job Satisfaction of Employees of PT. Pusaka Graha Teknik. Determination of the sample in this study amounted to 54 samples using the census research method through the distribution of questionnaires. The analysis used is multiple linear analysis with this research is a research with causality with quantitative techniques. The data processing program used is the SPSS (Statistical Package for the Social Sciences) version 21 program. The results obtained that simultaneously Compensation, Communication, and Workload have a positive and significant effect on job satisfaction, and partially Compensation has a positive and significant effect on job satisfaction while communication and workload have no positive and significant effect on job satisfaction.

The role of nurses in the application of bedsores in palliative care

In palliative care, the role of the nurse is very important in the prevention of bedsores, as only by providing qualified care and early prevention can bedsores be prevented and thus improve the patient's quality of life in the last years of life. The role of nurses in the prevention of bedsores is mainly reflected in the use of bedding prevention and treatment mattresses and functional beds. Less than three-quarters of nurses often use biophysical agents, various bandages, auxiliary surfaces, heel guards, stationary lifts, flip-flops, transfer boards / stretchers / belts, and other positioning devices in palliative care. According to the recommendations of the EPUAP, almost half of nurses say that the most effective means of preventing bedsores in palliative care is flipping. Nurses perform many professional and effective actions, functions that improve the patient's health and well-being in the treatment of bedsores. Also, in the prevention of patients' bedsores and palliative care, nurses perform their work responsibly, reliably, and are able to empathize with patients.
 The aim. To elucidate the role of nurses in the application of bedsores in palliative care.
 Research methods: after analyzing the scientific literature, from 2021. A quantitative survey and an anonymous survey were conducted in November-December. The research data were analyzed by MS Office Excel 2016 data processing program. The research was conducted in accordance with ethical principles.
 Results of the study: 64 nurses (women) participated in the study. The productive role of nurse in the prevention of bedsores is reflected in the use of EPUAP guidelines in the prevention of patient bedsores.
 Conclusions: The study found that 94 percent. (n = 60) the role of nurses in the prevention of bedsores is reflected in the most common use of bedsores for the prevention and treatment of bedsores, 91%. (n = 58) - uses functional beds. On average, 67 percent. (n = 43) nurses often use biophysical agents, various bandages, auxiliary surfaces, heel guards, stationary lifts, flip-flops, transfer boards / boards / stretchers / belts and other positioning devices, with the least use of implants - 39%. (n = 25). According to the EPUAP, 46 percent. (n = 29) The most effective measures for nurses in the prevention of bedsores in palliative care are reversal, and 17%. (n = 11) - when more employees work, 11 percent. (n = 7) - patient hygiene and dry maintenance, 8 percent. (n = 5) - bed rest mattresses and functional beds.

Virtual Machine Task Classification Using Support Vector Machine and Improved MFO Based Task Scheduling

The processing of data in Big data computing necessitates a significant number of CPU cycles and network bandwidth. Dataflow is a huge data processing programming model that comprises of jobs structured in a graph structure. Scheduling these jobs is one of the most active study fields, with the primary goal of allocating tasks based on available resources. It is critical to efficiently schedule jobs in a way that minimizes task completion time and maximizes resource utilization. In recent years, many research works on task scheduling problems in cloud computing and various heuristic approaches have been evolved which the thesis focuses upon. Most of these efforts are focused on improving the performance such as minimizing the makespan and efficient utilization of cloud resources that benefits the cloud users and the providers. In this paper, Big Data analysis processing in cloud environment for efficient dynamic task scheduling by using different techniques as machine learning classifier and optimization approach. In machine learning classifier as Support Vector Machine (SVM) for classification of virtual machine task classification. In this classifier can classify the incoming request efficiently and reduce the makespan and execution time. Further, we used moth flame optimization technique for allocating the classified task from SVM classifier. In this proposed system have classification of virtual machine (VM) task and evaluate the resource allocation decision making procedures. In this experiment, we carried out by using cloud simulation environment to evaluate and analysis the proposed method. In this proposed scheme can efficiently reduce the makespan time and load balancing to improve the better VM Classification. And aslo we compare the proposed moth flame optimization (MFO) with min-max algorithm and particle swarm optimization to compare the performance respectively.

Serial X-ray Crystallography

Serial crystallography (SX) is an emerging technique to determine macromolecules at room temperature. SX with a pump–probe experiment provides the time-resolved dynamics of target molecules. SX has developed rapidly over the past decade as a technique that not only provides room-temperature structures with biomolecules, but also has the ability to time-resolve their molecular dynamics. The serial femtosecond crystallography (SFX) technique using an X-ray free electron laser (XFEL) has now been extended to serial synchrotron crystallography (SSX) using synchrotron X-rays. The development of a variety of sample delivery techniques and data processing programs is currently accelerating SX research, thereby increasing the research scope. In this editorial, I briefly review some of the experimental techniques that have contributed to advances in the field of SX research and recent major research achievements. This Special Issue will contribute to the field of SX research.

NFC/RFID sensor Tag for Wireless Temperature Monitoring in a Cold Chain

This work presents the design and validation of a temperature sensor tag, which can be queried either by a cell phone using the NFC protocol or an HF RFID reader. It will easily ensure the cold chain failures and the product integrity. The proposed recording sensor can be placed on the packaging box to measure the temperature of the product. This allows to observe and store its evolution in order to guarantee the products quality and to respect the applicable provisions during transport. Thanks to a cell phone with the NFC, this recording data can be easily available, contrary to existing tags on the market. The design of tag is summed up as the choice of components, and the size of the antenna. Then a program for data recording and processing is developed using C language. Indeed, to have a triple gain of place, speed, and cost; an optimization of values recorded is operated. The overall tag size is 5.1x4x1.6 mm3, and its operation has been validated by performing in a real scenario: the temperature monitoring of a water bottle inside a bag for at least 50 minutes. The results of this test will be presented and discussed.

The Effect of Financial Literacy, Financial Inclusion, Peers and Pocket Money on Student Saving Behaviour at Universities in Yogyakarta

One of the good qualities that students should have is to get used to being frugal by saving. This study aims to analyze the factors that influence saving behavior. The factors that are thought to influence the saving behavior of students to be studied are financial literacy, financial inclusion, peers and pocket money. The population in this study were students of private universities in Yogyakarta. Samples were taken by purposive sampling of 100 students from various private universities. Collecting data using a questionnaire that is distributed online using a google form. The analytical technique used to test the hypothesis is the multiple regression method which is processed with the SPSS version 25 data processing program. The results show that (1) financial literacy has a significant effect on the saving behavior of private university students in Yogyakarta, (2) financial inclusion has a significant effect on significant effect on the saving behavior of private university students in Yogyakarta, (3) peers significantly influence the saving behavior of private university students in Yogyakarta, and (4) pocket money significantly affects the saving behavior of private university students in Yogyakarta

Resource Configuration Tuning for Stream Data Processing Systems via Bayesian Optimization

Stream data processing systems are becoming increasingly popular in the big data era. Systems such as Apache Flink typically provide a number (e.g., 30) of configuration parameters to flexibly specify the amount of resources (e.g., CPU cores and memory) allocated for tasks. These parameters significantly affect task performance. However, it is hard to manually tune them for optimal performance for an unknown program running on a given cluster. An automatic as well as fast resource configuration tuning approach is therefore desired. To this end, we propose to leverage Bayesian optimization to automatically tune the resource configurations for stream data processing systems. We first select a machine learning model—Random Forest—to construct accurate performance models for a stream data processing program. We subsequently take the Bayesian optimization (BO) algorithm, along with the performance models, to iteratively search the optimal configurations for a stream data processing program. Experimental results show that our approach improves the 99th-percentile tail latency by a factor of 2.62× on average and up to 5.26× overall. Furthermore, our approach improves throughput by a factor of 1.05× on average and up to 1.21× overall.

NJOY+NCrystal: An open-source tool for creating thermal neutron scattering libraries with mixed elastic support

In this work we present NJOY+NCrystal, a tool to generate thermal neutron scattering libraries with support for coherent and incoherent elastic components for crystalline solid materials. This tool, which is a customized version of NJOY, was created by modifying the nuclear data processing program NJOY to call the thermal scattering software library NCrystal, and includes a proposed change in the ENDF-6 format to store both the coherent and incoherent elastic components. Necessary changes to enable this format in NJOY, as well as to sample it in the OpenMC Monte Carlo code, are detailed here. Examples of materials that are coherent–dominant, incoherent–dominant, and mixed elastic scatterers are presented, as well as the creation of novel libraries for MgH2 and MgD2, that are under consideration as advanced neutron reflectors in the HighNESS project at the European Spallation Source. NJOY+NCrystal greatly simplifies the process to generate thermal scattering libraries (TSL) and this is exemplified with 213 new and updated TSL evaluations.

Pengaruh Beban Pajak Tangguhan, Aktiva Pajak Tangguhan, Dan Akrual Terhadap Manajemen Laba Pada Perusahaan Aneka Industri Yang Terdaftar Di Bursa Efek Indonesia Periode 2015-2020

This study aims to determine the effect of deferred tax expense, deferred tax assets, and accruals on earnings management. The population in this study are various industrial companies listed on the Indonesia Stock Exchange for the 2015-2020 period. This research is a descriptive research with a quantitative approach. Data processing program using SPSS Version 25.By using 5 companies using purposive sampling. The data used in this study is secondary data, namely data on the financial statements of various industrial sector companies listedon the Indonesia Stock Exchange in the 2015-2020 period. The sample selection method used purposive sampling, namely the sampling method based on certain criteria. Of the 45 various industrialcompanies listed on the Indonesia Stock Exchange, there are only 5 companies that meet the research sample criteria that have been determined. The data analysis method used inthis research is multiple linear regression test, coefficient of determination (R^2) and correlation (R), partial test (t-test) and Simultaneous test (F-test) while earnings management is measured based on dummy variables. The results of this study indicate that deferred tax expense affects earnings management, deferred tax assets affect earnings management and accruals have no effect on earnings management.Based on the simultaneous test (F test) variable deferred tax expense, deferred tax assets andaccruals together have no effect on earnings management in various industrial companies listed on the Indonesia Stock Exchange in 2015-2020.

The impact of optical character recognition artificial intelligence on the labour market

Because of present day information technology, there is neither need to plant complicated computers for more millions price if we would like to process and store big amounts of data, nor modelling them. The microprocessors and CPUs produced nowadays by that kind of technology and calculating capacity could not have been imagined 10 years before. We can store, process and display more and more data. In addition to this level of data processing capacity, programs and applications using machine learning are also gaining ground. During machine learning, biologically inspired simulations are performed by using artificial neural networks to able to solve any kind of problems that can be solved by computers. The development of information technology is causing rapid and radical changes in technology, which require not only the digital adaptation of users, but also the adaptation of certain employment policy and labour market solutions. Artificial intelligence can fundamentally question individual labour law relations: in addition to reducing the living workforce, it forces new employee competencies. This is also indicated by the Supiot report published in 1998, the basic assumption of which was that the social and economic regulatory model on which labour law is based is in crisis.

HUBUNGAN JARAK LOKASI PENANGKAPAN TERHADAP HASIL TANGKAPAN DAN DISTRIBUSI FREKWENSI UKURAN RAJUNGAN DI PERAIRAN KABUPATEN PANGKEP

The purpose of this study is to find out the distance relationship of the location of the gill net rajungan fishing gear to the catch of knitting (Portunus pelagicus). This study was conducted from September to November 2019 in the waters of Balang Lompo Island, Pangkep Regency, South Sulawesi Province. The study used field observation methods to conduct observations, measurements and data retrieval, covering primary and secondary data. Data processing uses the help of statistical data processing programs. Based on the results of research that the distance relationship of the location of the gill net rajungan fishing gear to the catch of rajungan (Portunus pelagicus) in the waters of Balang Lompo Island, is very crowded, the farther from the beach the greater the number of catches.

The Effect of Corporate Governance on Firm Performance

This study aims to analyze the effect of corporate governance mechanisms on firm performance. The sample used in this study were companies listed on the Indonesia Stock Exchange (IDX) during the period of 2016 to 2019. The number of samples used in this study was 100 samples. The sampling technique used is purposive sampling method. The research data was obtained from the company’s annual report. This study uses multiple regression analysis method which operated through data processing program IBM SPSS Statistics 25. The results of this study showed that the proportion of independent commissioner, audit committee, and institutional ownership had a positive and significant effect on Adjusted Tobin’s Q. Meanwhile, size of board of directors and managerial ownership found to had no effect on Adjusted Tobin’s Q. Firm size and firm age as control variables found to had a positive effect on Adjusted Tobin’s Q, while leverage found to had no effect on Adjusted Tobin’s Q.

Capital Expenditure and Investment on Economic Growth in West Papua Province 2015-2019

This study was conducted to know the effect of capital expenditure and investment on economic growth in West Papua in 2015-2019. First, sampling was carried out using the saturated sampling technique with the number of samples obtained in 13 districts/cities. Panel data with Least Square Dummy Variable (SLDV) model estimation is used as an analysis method and Stata 16 functions as a data processing program. The research then found that the capital expenditure variable had a negative and insignificant effect on economic growth. Then it was found that the investment variable has a positive and significant impact on economic growth. Compared with the results of studies using only independent variables, the use of control variables (population and average length of schooling) will present the most significant coefficient of determination at the time of full regression. These results then indicate that the control variable has a strong influence on economic growth.

THE EFFICIENCY OF THE APPLICATION OF SPSS IN HIGHER EDUCATION TEACHING: AN EXPERIMENTAL STUDY

Acquiring statistical education is a prerequisite for the professional and scientific work of every pedagogue. Institutional support for the statistical education of students is a fundamental starting point in the development of research competencies necessary for a future pedagogue. The subject of this study was focused on examining the effectiveness of the application of a program for statistical data processing in teaching. The research aimed to examine whether students gained adequate knowledge in the field of Statistics in Pedagogical Research by applying the experimental factor SPSS in teaching. This means that the use of the SPSS program may significantly facilitate the acquisition of theoretical and practical knowledge pertaining to the field of statistics in pedagogical researches. The objective was to analyze whether using the SPSS software as part of university education would yield better knowledge of statistics than teaching without it. This objective was accomplished by analyzing the differences in the respondents’ scores on the knowledge test using the pre-test and the post-test groups of students. Three generations of pedagogy students at the Faculty of Philosophy, the University of Nis in Serbia, participated in the experimental research. The results showed statistically significant differences in the participants’ achievement in the initial and final tests.

A triple-layer microchannel array chip with micro through-holes for smartphone based point-of-care testing of biomarker

Colorimetric detection on a microchip frequently suffers the sensitivity problem due to the limited optical path length. Herein, a point-of-care testing (POCT) device based on the colorimetric detection on a microchip with an array of micro through holes for enlarged optical length and an optical imaging system was demonstrated. Each micro through hole has a depth of 2 mm and a volume roughly 0.6 μl, connecting to a microchannel for the efficient reaction. Up to 32 micro through holes were arranged compactly along a round region with a diameter of 13 mm to make them effectively captured by a smartphone camera in a short distance (6.5 cm). For reliable smartphone imaging, a handheld, battery powered optical imaging cassette was made by three-dimensional (3D) printing. A data processing program was also written to realize the detection area selection, RGB (red, green, blue) value reading and detection signal calculation. With the integrated device, a biomarker, human immunodeficiency virus (HIV) p24 antigen in human serum was detected down to 20 pg/ml, much better than that with microchannels. The proposed microchip and the imaging system can be a promising POCT or on-site detection tool based on colorimetric detection.