Reviewerly/exHarmony huggingface dataset:
The moderating effect of generation on the relationship between commitment and performance: Evidence from human resource management model

This research aimed to investigate the effect of leader-member exchange and employee motivation on organizational commitment, and the effect of organizational commitment on job performance.The research also examines the moderating effect of generation on the relationship between organizational commitment and job performance.The population of this research is the employees working in private organizations in Thailand.Data collection was performed using a convenient random method.400 usable questionnaires were used for statistical analysis.The author analyzed Descriptive statistics by SPSS program version 25 while the SmartPLS 3.3.0program was used to test the research hypotheses in Partial Least Square-Structural Equations Model (PLS-SEM).The finding revealed that leader-member exchange positively affected organizational commitment but employee motivation had no significant effect on organizational commitment.It also found that leadermember exchange had a positive effect on employee motivation.Another key point was organizational commitment significantly influenced on job performance.In addition, the study found the moderating effect of Generation on the relationship between commitment and job performance.
Simulation of tennis serve behavior based on video image processing and wireless sensor technology

Abstract Video-based human motion analysis is an important research direction in the field of computer vision. It detects moving objects from video sequences, extracts key parts of the human body, and obtains useful information for human movements. In this paper, the joints of the teeing arm are first color-coded. The tennis teeing video is collected by a high-speed camera. The coordinates of the tacking points in each frame are used instead of the knuckles to study the trajectory of the teeing arm. In the process of video processing, after constructing a dictionary for a series of noise maps, the sparse representation idea was used to reconstruct an interference-free service diagram, and a mixture of Gaussian background modeling was used to extract the foreground of the motion. After obtaining the motion foreground, the marker points are extracted through the color features, and binarization operations are performed on the marker points. Next, the outline of the marker points is searched, the outline is surrounded by the minimum circle, and the returned circle center coordinates are used as the joint point coordinates. Taking the trajectory of the shoulder marking point as a research object, a tennis serving model based on an improved support vector machine was established.
Digital Hausdorff distance on a connected digital image

A digital image X can be considered as a subset of Z n together with an adjacency relation where Z is the set of the integers and n is a natural number.The aim of this study is to measure the closeness of two subsets of a connected digital image.To do this, we adapt the Hausdor¤ distance in the topological setting to its digital version.In this paper, we de…ne a metric on a connected digital image by using the length of the shortest digital simple path.Then we use this metric to de…ne the r-thickening of the subsets of a connected digital image and de…ne the digital Hausdor¤ distance between them.
TRANSLATION STRATEGIES FOR TRANSLATING A NEWS ARTICLE

There are various kinds of translation strategies proposed by the experts of translation. This study aims to find out the translation strategies used by the English Education students from Faculty of Cultural Studies (FCS) of Universitas Brawijaya (UB) in translating a news article. The translation strategies used by the students are categorized based on the Baker's taxonomy. The result shows that the students employ all of the eight translation strategies from Baker's taxonomy in translating the news article. The three most used translation strategies are translation by using a more general word (95%), paraphrasing using related words (75%), cultural submission and omission (73%). On the contrary, the least used translation strategy is translation by illustration (31%). From the result of the study, it is suggested that researchers interested in translation can conduct more research about the students' translation in a deeper and more specific analysis.
Development of Instructional Media “Game Math Comic Story” Based Android on Number

This research was conducted with the purpose to produce mathematics instructional media based game and comic stories for android. This study aimed at assisting students in studying number material and increasing reading interest for 7th grade students. Media developed were stories that were made into an adventure game made with "appsgeyser.com". The research method was research and development. The development of this medium used 4D (Four-D) development techniques consisting of Define, Design, Develop, and Disseminate stages. To obtain quality media, validation and experiment were done. The result of this study indicated that mathematics instructional media comic game story based android could improve the positive nature and spirit of students in learning. The validity value of media was 3.2 and the practical value of media was 3.14
A Mobile QR Code Application for an Article: QR-ticle

With the developing technology, innovations have been started in many areas of life. New solutions based on technology have to be produced for new needs. The Internet has become an indispensable element of life with smartphones and mobile devices.&amp;nbsp; People can access information faster, less costly and independent of time and place by using mobile devices. As a requirement of the Internet era, many businesses support their business processes, services and products with their mobile applications. Academic institutions and publishers also need to keep up with this mobile transformation. In this study, a mobile application (QR-ticle) has been developed which provides reliable and fast access to the publication related to the references given in academic publications by using QR code. With this application, scientists will be able to create QR code for their own articles and will be able to access any of the articles by scanning the QR code.
KEBOLEHGUNAAN MODEL PENGURUSAN BILIK DARJAH PRASEKOLAH BERASASKAN EMPAT DIMENSI PENGURUSAN BILIK DARJAH [THE USABILITY OF PRESCHOOL CLASSROOM MANAGEMENT MODEL BASED ON FOUR DIMENSIONS OF CLASSROOM MANAGEMENT]

The study was conducted to obtain the respondents' agreement via the usability assesment toward the preschool classroom management model that has been developed.. The focus of the main components of the preschool classroom management model are dimension of the physical management of the classroom environment, dimension of the planning management and program/activitiy implementation, dimension of the child behaviour management in the classroom and dimension of the interaction and relationship management. The preschool classrooms managed by preschool teachers such as furniture layout, activities and learning materials provided by them are still inadequate and do not encourage children's learning. Therefore, the study conducted is to ensure that the model developed is appropriate and able to be used by the preschool teachers in managing preschool classroom. This study uses a design and development research approach that involves the evaluation phase of model usability. During the evaluation phase of model usability, the researcher uses modified nominal technique to identify the suitability as well as customer’s satisfaction and their perception toward the developing model. The results of the usability assessment shows that all of the 30 respondents agreed that the model developed in this study could be used as a guide for preschool teachers. The respondents also agreed that the model is very practical for preschool teachers to be implemented in the preschool classroom because the content of the model covers aspects that teachers need to take into account in order to manage the preschool classroom more effectively.
Adopting SCRUM Framework in a Software Development of Payroll Information System

To maximize the performance of the company, especially in parts of the payroll companies do a variety of ways to tackle this problem?Payroll was an administration payroll that is the work of the regular and including the most important part of a company that have employees.But in the operation payroll is still being done in a manual, reporting a difficult for the company, payroll data is not detailed, causing the performance of the company.In dealing with this problem then made payroll system app with the SCRUM.This method chosen because of the quickly and light in the development of the application and had to produce productivity and activities that was worth the high.There are three a role in the development of the SCRUM, namely the owner of the product, the SCRUM Master, and the developer.The owner of the products will define the needs of what is needed to run a business, then of the needs to be in transformation became one of the product backlog that is facilitated by a master of the SCRUM, then the product backlog this will altered back into the sprint backlog that will be developed by the developer.During the implementation of this requirement can change anytime and flexible with the consequences of development will be disrupted.The Output of the SCRUM this is the app provide module, consist of three modules, namely the administration of employees, absenteeism, and payroll as well as to report on any of the module.
Enhanced Pre-processing and Parameterization Process of Generic Code Clone Detection Model for Clones in Java Applications

Code clones are repeated source code in a program.There are four types of code clone which are: Type 1, Type 2, Type 3 and Type 4. Various code clone detection models have been used to detect code clone.Generic Code Clone model is a model that consists of a combination of five processes in detecting code clone from Type-1 until Type-4 in Java Applications.The five processes are Pre-processing, Transformation, Parameterization, Categorization and Match Detection process.This work aims to improve code clone detection by enhancing the Generic Code Clone Detection (GCCD) model.Therefore, the Preprocessing and Parameterization process is enhanced to achieve this aim.The enhancement is to determine the best constant and weightage that can be used to improve the code clone detection result.The code clone detection result from the proposed enhancement shows that private with its weightage is the best constant and weightage for the Generic Code Clone Detection Model.
Some group-theoretical results on Feistel Networks in a long-key scenario

The study of the trapdoors that can be hidden in a block cipher is and has always been a high-interest topic in symmetric cryptography. In this paper we focus on Feistel-network-like ciphers in a classical long-key scenario and we investigate some conditions which make such a construction immune to the partition-based attack introduced recently by Bannier et al.
Indoor intrusion detection based on deep signal feature fusion and minimized-MKMMD transfer learning

Indoor intrusion detection based on Wireless Local Area Network (WLAN) has been widely used for security monitoring, smart homes, entertainment games, and many other fields in the Beyond 5G (B5G) wireless communication network environment. Most existing indoor intrusion detection methods directly exploit the Received Signal Strength (RSS) data collected by Monitor Points (MPs) and pay little attention to the instability of WLAN signals in complex indoor environments. In response to this problem, this paper proposes a novel WLAN indoor intrusion detection method based on deep signal feature fusion and Minimized Multiple Kernel Maximum Mean Discrepancy (Minimized-MKMMD). Firstly, the multi-branch deep convolutional neural network is used to conduct the dimensionality reduction and feature fusion of the RSS data, and the tags are obtained according to the features of the offline and online RSS fusion features that are corresponding to the silence and intrusion states, and then based on this, the source domain and target domain are constructed respectively. Secondly, the optimal transfer matrix is constructed by minimizing MKMMD. Thirdly, the transferred RSS data in the source domain is utilized for training the classifiers that are applying in getting the classification of the RSS fusion features in the target domain in the same shared subspace. Finally, the intrusion detection of the target environment is realized by iteratively updating the process above until the algorithm converges. The experimental results show that the proposed method can effectively improve the accuracy and robustness of the intrusion detection system.
Intelligent information extraction from scholarly document databases

Extracting knowledge from big document databases has long been a challenge.Most researchers do a literature review and manage their document databases with tools thatjust provide a bibliography and when retrieving information (a list of concepts and ideas), thereis a severe lack of functionality. Researchers do need to extract specific information from theirscholarly document databases depending on their predefined breakdown structure. Thosedatabases usually contain a few hundred documents, information requirements are distinct ineach research project, and technique algorithms are not always the answer. As most retrievingand information extraction algorithms require manual training, supervision, and tuning, itcould be shorter and more efficient to do it by hand and dedicate time and effort to perform aneffective semantic search list definition that is the key to obtain the desired results. A robustrelative importance index definition is the final step to obtain a ranked importance concept listthat will be helpful both to measure trends and to find a quick path to the most appropriatepaper in each case.
ComPer: A Comprehensive Performance Evaluation Method for Recommender Systems

RecommenderSystems are receiving substantial attention in several application areas (such as healthcare systems and e-commerce), where each area has different requirements.These systems are multifaceted by nature.So, many metrics, which are sometimes contradictious, are introduced to assess different aspects.The existence of several alternatives and dimensions to recommendation approaches complicate the evaluation of recommender systems.In such a situation, it is desirable to evaluate and compare recommenders in a united way that assesses the multifaceted aspects of these systems fairly and uniformly.Despite the abundance of evaluation dimensions, the literature still lacks an evaluation method that evaluates the multiple properties of these systems, all at once.As a potential solution, this paper proposes an evaluation methodology that provides a multidimensional assessment of recommender systems.The proposed method, which we call ComPer, combines the most common evaluation dimensions into a single, yet, general evaluation metric.ComPer is inspired by the idea that a recommender system mimics human beings; hence, it can be seen as a human and its outputs can be assessed as human's outputs.Up to our knowledge, this is the first evaluation approach that deals with recommenders as humans.ComPer aims to be thorough (by combining multiple dimensions), simple (by presenting the final result as a single value), and independent (by providing setting-independent results).The applicability of the proposed methodology is evaluated empirically using three different datasets.The initial results are promising in the sense that ComPer is able to give comparable results regardless of the experimental settings.
HGKT : Introducing Problem Schema with Hierarchical Exercise Graph for Knowledge Tracing.

Knowledge tracing (KT) which aims at predicting learner's knowledge mastery plays an important role in the computer-aided educational system. In recent years, many deep learning models have been applied to tackle the KT task, which has shown promising results. However, limitations still exist. Most existing methods simplify the exercising records as knowledge sequence, which fails to explore rich information existed in exercise texts. Besides, the latent hierarchical graph nature of exercises and knowledge remains unexplored. Thus, in this paper, we propose a hierarchical graph knowledge tracing model framework (HGKT) which can leverage the advantages of hierarchical exercise graph and of sequence model to enhance the ability of knowledge tracing. Besides, we introduce the concept of problem schema to better represent a group of similar exercises and propose a hierarchical graph neural network to learn representations of problem schemas. Moreover, in the sequence model, we employ two attention mechanisms to highlight important historical states of students. In the testing stage, we present a K\&S diagnosis matrix that could trace the transition of mastery of knowledge and problem schema, which can be more easily applied to different applications. Extensive experiments show the effectiveness and interpretability of our proposed models.
Problems of the Formation of Readiness of Future Preschool Teachers for Professional Activities

This article is dedicated to theoretical and practical aspects of ensuring the readiness of future teachers of preschool education for professional activities.The aim of the research is to study the preparation of teachers of preschool education at a modern university; to determine the significance of the formation of professionally important qualities of future specialists; to determine the level of their psychological readiness for professional activities; and, based on the results obtained, to shape the stages of further research necessary for the subsequent development of programs for introducing the latest forms and methods in the studying process at universities.To implement the set tasks, we used a complex of interrelated research methods.The analysis of the criteria allowed us to estimate the level of the students' readiness for future professional activities.The analysis of the results of the research showed that the most effective formation of students' readiness is formed based on the personality criterion.The formation of the researched criterion of readiness based on the content-related and regulation-related parameters is also quite effective.The formation of students' readiness for future professional activities requires the development of new forms and methods of teaching both within the university and in course of practical training.It has been determined that shaping professional competencies and professional preparedness of future preschool teachers require further research, including that which is done through the development and implementation of comprehensive programs for the professional and psychological preparation of students, which include the latest forms and methods of teaching at modern universities.
Components of the Library Specialist’s Digital Culture

Today, library specialists are increasingly confident in providing webometric support for users’ research, mastering technologies for reflecting the results of Ukrainian researchers in international science metric databases, constantly improving their skills in information analytics, creating and maintaining library sites, blogs, and social network accounts.The presented article reveals the essence and correlation of such concepts as «digital skills», «digital literacy», «digital competence», «digital dividends», «digital intelligence», «digital culture». There are justified components of a digital culture library specialist as unity digital world, digital business and digital creativity, the formation of which will contribute to the success achievement and competitive advantages in the digital economy development and the knowledge society.A conceptual model for the formation of the basic components of digital culture of a modern library specialist has been outlined. It has been noted that working with large volumes of digital information requires a high level of emotional intelligence from the librarian, the ability to concentrate and manage attention, the ability to quickly relearn, tune in to constant development and improvement.To achieve the goal set in the research, we used terminological and comparative methods, as well as the method of conceptual modeling. This allowed us to identify and analyze the basic concepts of the subject area «digital culture», to determine the components of the conceptual model of a library specialist’ digital culture and which will allow us to substantiate the theoretical foundations of its effective formation.It has been proved that knowledge of the content and component composition of digital culture is the key to developing organizational and methodological foundations for its effective formation. At the same time, it is necessary to take into account the communication essence of the library profession, which equips librarians with a powerful arsenal of knowledge, skills, worldview guidelines and means of forming not only their own digital culture, but also library users and society as a whole.
A new behavior-assisted semantic recognition method for smart home

In the recent Smart Home (SH) research work, intelligent service recommendation technique based on behavior recognition, it has been extensively preferred by researchers. However, most current research uses the Semantic recognition to construct the user's basic behavior model. This method is usually restricted by environmental factors, the way these models are built makes it impossible for them to dynamically match the services that might be provided in the user environment. To solve this problem, this paper proposes a Semantic behavior assistance (Semantic behavior assistance, SBA). By joining the semantic model on the intelligent gateway, building an SA model, in this way, a logical Internet networks for smart home is established. At the same time, a behavior assistant method based on SBA model is proposed, among them, the user environment-related entities, sensors, devices, and user-related knowledge models exist in the logical interconnection network of the SH system through the semantic model. In this paper, the data simulation experiment is carried out on the method. The experimental results show that the SBA model is better than the knowledge-based pre-defined model.
Evaluation of net radiation using the autoregressive models with higher orders over Nigeria

In this study, monthly surface net radiation data were collected from the Nigeria Meteorological Agency, Lagos covering a duration of 31 years (1983- 2013) spatially distributed across the four climatic regions: Semi-Arid (SAR), Sub-humid Dry (SHD), Sub-humid Humid (SHH) and Humid (HUM) regions. The net radiation was evaluated using different forms of Auto-Regressive models – AR {p} where p is the number of orders of the auto-regressive. The analysis showed that AR {4} performed best in all the regions and stations investigated. Regionally, AR {4} has maximum values of coefficient of determination of 0.8127 in HUM, 0.7876 in SHH, 0.5765 in SHD and 0.7973 in SAR regions. It can be concluded that the higher the order of auto-regressive models, the more accurate estimation of net radiation it will give irrespective of location in Nigeria.