Reviewerly/exHarmony huggingface dataset:
The Effect of Achievement Motivation and Self-Regulated Learning on Student Learning Behavior in the Time of Online Learning in Indonesia

BACKGROUND: Self-regulated learning (SRL) and achievement motivation are important variables in students’ learning behavior. AIM: The purpose of this study was to examine the effect of achievement motivation and SRL on the learning behavior of junior high school students in Indonesia during the online learning period. METHODS: The research uses a quantitative approach with a causal associative research design. The research population is junior high school students in grades VII, VIII, and IX from various regions in Indonesia during the online learning period. Research respondents total 2,880 students, who were selected through random sampling technique. Respondent data were collected using a set of questionnaires in the form of a validated achievement motivation scale, SRL, and learning behavior, and processed and analyzed using the path-analysis method. RESULTS: The results of statistical processing show that the correlation coefficient between Achievement Motivation and SRL is 0.432 with a significant relationship and is included in the category of a fairly strong relationship. The correlation coefficient between Achievement Motivation and Learning Behavior is 0.632 with a significant relationship and is included in the category of a strong relationship. The correlation coefficient between SRL and Learning Behavior is 0.675 with a significant relationship and is included in the category of a strong relationship. Based on the Path Analysis Calculation Result Table, the path coefficient value for Achievement Motivation is 0.418 with a positive relationship direction. Simultaneous test results obtained the conclusion that there is an influence between Achievement Motivation and SRL variables on Learning Behavior of 59.8%, while the remaining 40.2% is the influence of other variables not involved in this study. The direct influence of Achievement Motivation on Learning Behavior is 17.5% and the indirect effect through SRL is 8.9%, so that if added up, the total effect is 26.4%. Then, the direct influence of SRL on Learning Behavior is 24.4% and the indirect effect through Achievement Motivation is 8.9% so that if added up, the total effect is 33.4%. CONCLUSION: There is a significant effect between achievement motivation and SRL on student learning behavior simultaneously; there is a significant influence between achievement motivations on student learning behavior partially. There is a significant influence between SRL on Student Learning Behavior partially.
Information Systems Stock Inventory in CV Kencana Motor using Laravel Frame

The system for recording stock inventory at CV Kencana Motor, which is done manually, causes errors in recording stock inventory. These errors make the stock item report inaccurate with the original. This study aims to design an income information system and recording stock goods at CV Kencana Motor. The design of this system is made using Data Flow Diagram (DFD) and Contek Digram and Flowchart. The results of this study indicate, this information system built can overcome errors in the calculation of sales transactions, purchases and can overcome the inventory data collection at CV Kencana Motor. Information system at CV Kencana Motor can help in making reports and searching for data more quickly and accurately when needed.
Natural Law in Editions of the 18th Century from the Library of the Irkutsk Theological Seminary as a Historical Source

The article gives a historical and book review of Western European publications of the XVIII century on natural law, preserved in the Scientific Library of the Ural State Law University (previously in the collection of the library of the Irkutsk Theological Seminary). Books are considered as a complex historical source with an inexhaustible source-study potential for studying the history of book culture. The facts of the history of the formation of the Irkutsk Theological Seminary library fund at the end of the XVIII – early XIX century and the geography of the spread of the ideas of lawyers of Western Europe, obtained by studying readers’ records, library labels and book signs, are presented. The article not only presents bibliographic descriptions of book rarities of the Enlightenment era (five books in 13 volumes), but also describes in detail all traces of their existence. As a result of the study, the picture of the development of book distribution, librarianship and reading in Siberia in the XVIII–XIX centuries is supplemented.
Artificially-intelligent robotic space manipulator using fuzzily-architected nonlinear controllers

The controlling of a selective compliance assembly robot arm (SCARA) manipulator in the space shuttle application is so complicated due to the targeted tasks' accuracy and precision [1]. Figure 1, depicted a typical SCARA.The SCARA robot manipulators are used extensively in the assembly of electronic components and small and medium-sized mechanical devices [2].SCARA robots are widely used in assembly manufacturing processes.
New Frontiers in Behavioral Strategy

Behavioral strategy has long been a central subject in organizational and strategy research. The goal of this panel symposium is to highlight theoretical and empirical gaps in the behavioral strategy literature and propose future directions to advance our understanding for the human element in strategy. Specifically, our distinguished group of panelists will discuss 1) intra-psychic mechanisms from the perspectives of cognitive and social psychology and neuroscience, 2) the situated and structural aspects of behavioral strategy in a multi-level context, and 3) how firm strategists make decisions at the collective level and communicate with stakeholders.
Weakness Analyzing and Performance Improvement for Image Encryption with Chaos Across Cylinder

We analyze and improve a type of chaotic image encryption algorithms which have no valid diffusion operation. The image encryption algorithm based on chaotic system crossing a cylinder is analyzed, and several security weaknesses due to inadequate diffusion are pointed out. An improved image encryption algorithm is proposed based on the original algorithm, which remedies the missing of diffusion and resists chosen plain-text attack and differential attack. The security analysis and tests show that the proposed algorithm can significantly increase the security while keeps all merits of the original algorithm.
Power Failure Sensitivity Analysis via Grouped 𝐿1/2 Sparsity Constrained Logistic Regression

To supply precise marketing and differentiated service for the electric power service department, it is very important to predict the customers with high sensitivity of electric power failure.To solve this problem, we propose a novel grouped 1/2 sparsity constrained logistic regression method for sensitivity assessment of electric power failure.Different from the 1 norm and k-support norm, the proposed grouped 1/2 sparsity constrained logistic regression method simultaneously imposes the inter-class information and tighter approximation to the nonconvex 0 sparsity to exploit multiple correlated attributions for prediction.Firstly, the attributes or factors for predicting the customer sensitivity of power failure are selected from customer sheets, such as customer information, electric consuming information, electrical bill, 95598 work sheet, power failure events, etc.Secondly, all these samples with attributes are clustered into several categories, and samples in the same category are assumed to be sharing similar properties.Then, 1/2 norm constrained logistic regression model is built to predict the customer's sensitivity of power failure.Alternating direction of multipliers (ADMM) algorithm is finally employed to solve the problem by splitting it into several sub-problems effectively.Experimental results on power electrical dataset with about one million customer data from a province validate that the proposed method has a good prediction accuracy.
Eficácia do hidratante Regenèr emulsão em pacientes diabéticos

This study aimed to evaluate the effectiveness of Regenèr Emulsion moisturizer in the process of regeneration and maintenance of skin health in the lower limbs of patients with Diabetes Mellitus. Qualitative, exploratory, case-study research, carried out in a public hospital in Greater Florianópolis, Santa Catarina, between August and October 2020. The results reported by the patients were the reduction of dryness of the skin on the legs and/or feet or xerosis, improvement in skin color related to diabetic dermopathy lesions, improvement in skin sensitivity and resistance, reduction of itching, reduction of skin discomfort and discomfort, as well as improvement in the skin and its color, when compared to the initial day and the day end of treatment. It is concluded that the study has great relevance for the field of nursing, it presents an approach to preventive care and effective hydration for maintaining the quality of the skin of the lower limbs of diabetic patients.
Research on algorithm of active power measurement on synchronous coordinate system

In the electrical system, determining the value of current, voltage are a very important role. They may serve the purpose of measuring or protecting electrical equipment. This paper researches active power measurement based on transforming voltage and current vectors from static frames into a synchronous rotating frame of reference. The sinusoidal values are replaced by direct current (DC) on the reference system, so the determination of the active power becomes simpler than the static reference system. The paper performed simulations and experimented on a simple physical model.
Inspædia, Inspiring a Collaborative Intelligence Network: Designing the User Experience

The main objective of this paper is to present the interface design concept of Inspædia focused on the user experience, to create knowledge in innovation and design and to facilitate collaborative intelligence. We consider innovation in the disciplinary context of the design to inspire new design processes and to expand and diversify the frame of references in order to stimulate ideation in design, as well as to offer to the inspædiers a stimulating interaction and knowledge experience. Whereas Inspædia is malleable enough to inspire and operating a network of collaborative intelligence in the areas of innovation and design - the results achieved are a significant contribution to knowledge in design and (hopefully) to the science of design (since not all knowledge is science).
ANALISIS SISTEM INFORMASI AKUNTANSI PENERIMAAN BIAYA TAGIHAN PEMAKAIAN AIR BERSIH PADA PERUSAHAAN DAERAH AIR MINUM (PDAM) TIRTAULI KOTA PEMATANGSIANTAR

This study aims to find out how the accounting information system for billing receipts is carried out at PDAM Tirtauli. The method used in this research is using descriptive qualitative research with data collection methods by observation and documentation. Based on the results of this study, it was found that the Accounting Information System from the receipt of clean water usage bills at PDAM Tirtauli, Pematangsiantar City was categorized as good, because the system used was clear and structured. However, the company is still experiencing problems in the Accounting Information System from the receipt of billing fees. These obstacles, such as in the Accounting Information System for receiving billing fees, there are still customers who are in arrears. Furthermore, the Accounting Information System depends on the network. So network errors can also occur so that they can interfere with the work of the system on the PDAM. Efforts made by PDAM are to collect customer arrears that have not been paid, and if the payment has not been made for more than 3 months, PDAM Tirtauli will terminate the customer's waterline. The next effort made by PDAM Tirtauli is to be more careful in implementing the system used in the company to minimize errors that occur in the Accounting Information System used in the company.
A customized 1D-CNN approach for sensor-based human activity recognition

Human activity recognition (HAR) is an emerging area of research that is applicable in several fields such as health care, security, smart homes, fitness assessment, sports competition and assisted living.HAR is performed by acquiring data from wearable sensors and external sensors like cameras, pressure sensors, and video recorders.Vision-based HAR plays an active role in the detection of suspicious activity and events in video surveillance.The requirement of computationally expensive image and video analytics, expensive hardware, and lack of portability are the main limitations of vision-based HAR [1].
Repositioning Secondary School Science Teachers’ Pedagogical Beliefs and Information and Communication Technology (ICT) Classroom Practices for Sustainable Science Education in Post Covid-19 Era

In today's global Education system, science education is much more than fact-based knowledge.Science education becomes meaningless and incomprehensible for learners if they are unable to relate it with their lives.This paper critically examines some issues and challenges of secondary school science teachers' pedagogical beliefs, information and communication technology (ICT) classroom practices, Covid-19 pandemic and the need to adopt science, technology and society approach for delivery of Science Education for sustainability in the post covid-19 Era.The paper concludes with recommendations for the overall improvement of Science Education in Nigeria.
EFL Agreeing and Disagreeing Discourses in Facebook

Agreeing and disagreeing are two common speech acts that occur in social conversations.Driven by the fact that there are direct and indirect way for expressing agreement and disagreement, and there are also mitigating strategies to protect interlocutors from face-threatening in disagreeing discourses, this study examined EFL students' use of discourse strategies in their Facebook interaction.Thirty-four pre-intermediate EFL students at a university in Vietnam took part in this study.Data analysis shows that direct discourses is linguistically limited while indirect ones exhibit wider language use.Students also demonstrate two different directions of using mitigating strategies for their disagreeing discourses.Some pedagogical implications are also suggested in this study.
MDBST: Multi-Different-Branch Siamese Network for Object Tracking

In the field of machine vision, object tracking tasks have always been a hot issue for many researchers. In recent years, many excellent trackers based on deep learning have achieved very advanced performance in object tracking tasks. However, many trackers use a single-branch feature extraction network to design trackers. Researchers are constantly increasing the depth of the feature extraction network while ignoring the width of the network. If the depth of the network is too deep, the size of the output feature map will be too small, which will affect the tracking results. Therefore, in order to balance the depth and feature extraction ability of the feature extraction network, this paper proposes a multi-different-branch feature extraction network. We design a feature extraction module and add the residual module at the same time, design two different branches to perform feature extraction in parallel, and concatenate the feature maps output by the two branches. Effectively extract all aspects of feature information of the object, and improve the accuracy and robustness of target tracking. We embed the feature extraction network into siamese network and conduct extensive experiments on the OTB2015 and VOT2016 benchmark datasets. The results show that our MDBST tracker has achieved excellent results.
Determinants of Firms’ Capacity Utilization in Ethiopia

Under-utilization of firms in Ethiopia is an overriding problem which requires empirical evidence pertinent to capacity utilization policy formulation and implementation.Capacity utilization of firms in developed countries ranges from 85 to 100% while in developing countries it is about 65 to 84%.In spite of these, firms' capacity utilization of less developed countries ranges from 50 to 64% while Ethiopian firm's capacity utilization is only 36% which is by far the lowest compared to the other world.This under-utilization of firms is the quest for knowing triggering factors.This paper investigates determinants of capacity utilization of firms where the data was collected by the World Bank from 848 firms in 2015 in all regions of the country.Capacity utilization (%) and number of hours of operation per week were measured to capture the determinants of overall capacity maneuver.A seemingly unrelated regression (SUR) model result of multiple equation estimation of the two measures suggested that about 73.64% and 53.57% of the variation, respectively, in capacity utilization and number of hours operated per week were explained by SUR model.The determinant factors which are idiosyncratic to both measures were cost of input measured in monetary terms as a proxy variable for quantity of intermediate goods and raw material, the percentage share of domestic inputs for the establishment, annual fuel cost and access to credit were contributing positively and significantly.However, foreign exchange constraint and foreign input were attributed to affect significantly but have adverse effect for both of the outcome variables.Moreover, capacity utilization and number of hours of operation have positive interdependency.The major contribution of this paper is to employ econometric estimation of capacity utilization and number of hours of operation per week and measures their interaction as well as identifies its determinants at firm level.
Detecting Six Different Types of Thyroid Diseases Using Deep Learning

Thyroid is the most common disease worldwide. More than 42 million people are affected by thyroid in India. Thyroid is a small gland in the neck region that secretes thyroid hormone which is responsible for directing all our metabolic functions. When the thyroid malfunctions, it can affect every facet of our health. Thyroid disease has become more challenging for both medical scientists and doctors. Detecting thyroid diseases in early stage is the first priority to save many people’s life. Typically, visual examination and manual techniques are used for these types of thyroid disease diagnoses. Thus, in this project, we apply deep learning algorithms to detect six different types of thyroid diseases and its presence without the need for several consultations from different doctors. This leads to earlier prediction of the presence of the disease and allows us to take prior actions immediately to avoid further consequences in an effective and cheap manner avoiding human error rate.
Corporate Socıal Responsıbılıty (CSR) as a Marketıng Tool: A Case of Multınatıonal Corporatıons in Nigeria

The study examined corporate social responsibility as a marketing tool amongst multinational corporations in Nigeria.Corporate social responsibility was broken down into four indicators which were accountability, transparency, responsibility and competitiveness.Therefore, the study was guided by four null hypotheses which state respectively that accountability, transparency, responsibility and competitiveness have no effect on marketing amongst multinational corporations in Nigeria.The study employed the path and factor technique for data analysis through the use of a statistical software package referred to as AMOS.The study employed Likert scale measurement in questionnaire examination and the sample consist of highly-placed managers in 15 multinational corporations in Nigeria.The questionnaire was properly structured and adequately developed and reviewed by experts.Essentially, the findings of the study were not surprising as they revealed that corporate social responsibility is a major factor influencing the level of marketing amongst multinational corporations in Nigeria.Specifically, responsibility and competitiveness were found to exert greater effect on organizational marketing strategy while accountability and transparency were found to exert lower effect on organizational marketing strategy as revealed by their respective path coefficients.The findings of the study were in addendum to the findings of Rindova et al. (2005) andHair et al., (2006) who discovered that corporate social responsibility through its indicators of accountability, transparency, responsibility and competitiveness significantly influence organizational performance.Given the above useful findings of the study, the study recommends for effective marketing of products, multinational corporations in Nigeria should improve their commitment towards giving back to the society.This can be achieved if multinational corporations carry out their respective activities in an accountable, transparent, responsible and competitive way.
CICM: A Collaborative Integrity Checking Blockchain Consensus Mechanism for Preserving the Originality of Data the Cloud for Forensic Investigation

The originality of data is very important for achieving correct results from forensic analysis of data for resolving the issue. Data may be analysed to resolve disputes or review issues by finding trends in the dataset that can give clues to the cause of the issue. Specially designed foolproof protection for data integrity is required for forensic purposes. Collaborative Integrity Checking Mechanism (CICM), for securing the chain-of-custody of data in a blockchain is proposed in this paper. Existing consensus mechanisms are fault-tolerant, allowing a threshold for faults. CICM avoids faults by using a transparent 100% agreement process for validating the originality of data in a blockchain. A group of agreement actors check and record the original status of data at its time of arrival. Acceptance is based on general agreement by all the participants in the consensus process. The solution was tested against practical byzantine fault tolerant (PBFT), Zyzzyva, and hybrid byzantine fault tolerant (hBFT) mechanisms for efficacy to yield correct results and operational performance costs. Binomial distribution was used to examine the CICM efficacy. CICM recorded zero probability of failure while the benchmarks recorded up to 8.44%. Throughput and latency were used to test its operational performance costs. The hBFT recorded the best performance among the benchmarks. CICM achieved 30.61% higher throughput and 21.47% lower latency than hBFT. In the robustness against faults tests, CICM performed better than hBFT with 16.5% higher throughput and 14.93% lower latency than the hBFT in the worst-case fault scenario.
PERANCANGAN APLIKASI PENGAJUAN DAN PERSETUJUAN CUTI KARYAWAN DENGAN METODE ENGINE TWIGE BERBASIS WEB

The design of the application for the application and approval of employee leave is very useful to simplify and speed up the process of filing for leave to be applied at PT. XXX and can help improve performance in the HRD (Human Resource Development) Section because nowadays technology is growing rapidly with website-based applications. It is also hoped that the studies that have been carried out can inspire readers. By using xampp, the CodeIgniter Framework that we need in designing this application which also includes employee data, leave requests, leave approvals and reports on submissions and approvals for taking leave. In addition, in the design and development of this application there is an engine twige method to assist the performance of making application designs to make it look more attractive. Application settings are carried out by the admin both in the process of data security and data confidentiality. All of these things are used to accommodate the necessary data and streamline the application.