Reviewerly/exHarmony huggingface dataset:
New Technologies of Internet Employment: Reducing Costs With an Economic Value Model

This paper focuses on examining the effect of applying the classical model of the economic value of the order on the employment activities of human resources in an organization. Initially, based on the classical model, the economic value of the order is modeled and the value of unique costs of employment activities such as human resource management and related coordination is obtained. Thereafter, the status in the two cases before and after the implementation of this technology is compared and this situation is analyzed by providing a numerical example. The optimal costs of investment are increasing rapidly. On the other hand, the development of efficient technologies in the employment system has caused the total number of employees to be hired to always be higher than the minimum required level set in this model. Investment in this area has declined. The result shows that with the implementation of this technology, due to the reduction of existing costs, on the one hand, the economic value of order decreases and on the other hand increases the total optimal profit.
Analysis on Career Guidance Mode of Application-Oriented University from the Perspective of Big Data

Application-Oriented University is an important place to cultivate high quality applied talents who owns bachelor degree at least for the regional economic development. Nowadays, the stage of China's economic development is transforming from high-speed growth to high-quality growth, which put forward new requirements for application-oriented universities’ graduates. This article aims to figure out the main aspects affecting students' employment by using big data analysis on the employment data of graduates. Furthermore, this article will explore the multi-modes of universities’ career guidance service, to not only improve the quality of employment for graduates, but also cultivate talents for local economic development.
Workplace Flexibility A Bibliometric Analysis

This research aims to further understand the effect of employee involvement and fairness in an organization that is perceived to have a positive workplace atmosphere. The mediating role of employee involvement in linking workplace flexibility with the behavior of co-workers, of course, the perception of fairness for every worker must absolutely be obtained in the work environment. Therefore, the aim of this research is to provide a reference for an extensive bibliometric study of the relationship between employees and the work environment. After managing the article data base compiled from Scopus from 55 articles found that were run from 2018-2020 there were 20 articles analyzed in this study. and analyzed managing with VOSviewer software to analyze co-authorship, co-accurance, and citation. Overall, this literature study provides an appropriate reference point for further research on the topic of Workplace Flexibility
Application of The Equivalent Partitioning Method in Testing for Automatic Test Case Generation on The Digi-OTA System

Software testing is one of the important phases in determining software quality. In the software development cycle, the testing phase takes more than 50% of the development time. The process of creating test cases in software testing is the most difficult process and determines the success of the testing phase. Test cases for software testing can be created based on the existing analytical modeling in the software specifications. This kind of testing technique is known as model-based testing, which is one of the black box testing approaches. In this study, the analytical model used is the UML Activity diagram. The reason for choosing UML Activity diagrams is because this diagram can model activities in software based on behaviors and conditions that are by the sequence. The output of this research is a prototype of a test case generator using an activity diagram. The analysis of the suitability of the test cases generated for the Digi-OTA application using the equivalence partitioning method is 100% when tested with valid data test specifications, while when tested with invalid test data specifications it produces 100% for approving actors, 95.98% for employee actors and 95.45% for detail officer actor.
Control of Security of Cyber Train Gateway

The presence of many moving elements in case of trains is the specific problem of railway transport infrastructures. The security of moving elements within the cyber-physical system (CPS) needs, therefore, to be ensured against both physical and cyber intrusion. We will deal with the cyber gateway of the train, which is called a mobile communication gateway (MCG). It is associated with problems of the standard cyber gateway and the problems specific to the moving systems. It is impossi-ble to secure communication between train and control centrum through a closed communication system only, it need to take place through open space because of extensive infrastructure with assistance of ground communication gateway (GCG). The MCG design shall ensure the security functions of the gateway as well as sufficient communication capacity. Our control over environmental conditions of MCG is limited because it is in open space, both physical and cyber, often in motion. The MCG, there-fore, needs to be able to respond dynamically to environmental changes caused by deliberate attacks or unintentional changes in the system. The ability of the adaptability must be given to the MCG in design
End-to-End Machine Learning Pipeline for Real-Time Network Traffic Classification and Monitoring in Android Automotive

The aim of this work is to build a network traffic monitoring application that is capable of categorizing network data traffic based on their application usage into 7 types: Browsing, Chat, Email, File Transfer, Streaming, VoIP and P2P. Flow-wise data is analyzed after the traffic stream is fed into the CICFlowmeter. Live traffic flow is fed to various ML models and algorithms such as K-Means Clustering algorithm, Agglomerative Clustering, Mean-shift algorithm, Random Forest Classifier, Adaptive Boosting algorithm, Gradient Boosting algorithm, Linear Discriminant analysis, Naive Bayes classifier, Classification and regression trees and the Support Vector Machine model. K-fold cross validation test is conducted, which derived results depicting the best of the models to be the Random Forest Classifier. We used 23 features for model training based on their importances. Model evaluation is done using the confusion matrix. Class imbalances are handled effectively with a comparative study of both under-sampling and oversampling of the dataset. Oversampling using SMOTE produces better results. The important timebased features in classification is recorded for further studies. The model used was fast enough to classify the flows in real time and display the analytics in the dashboard. The Flask framework is used to build a live dashboard to display the network traffic classified along with the several important features. We were able to prove that network traffic classification cam be done using time-based features which does not violate data protection laws. Network traffic classification using Random forest algorithm on oversampled dataset gave an overall accuracy of 0.92 was achieved.
https://habibiaislamicus.com/index.php/hirj/article/view/248

This research discusses English reading strategies and their effects on students learning performance in reading comprehension at SSC level in public schools in Karachi Pakistan. This study has found out the top three strategies such as: reading one by one loudly, correcting the pronunciation, and finding the meanings of difficult words from vocabulary that is used to teach reading comprehension in SSC classes. The researcher has analyzed the effects of teaching strategies on learning performance in reading comprehension at SSC level in public schools. This is a qualitative research where convenience sampling is used to carry out the study with the sample size containing four teachers and fifty students. The findings of this study revealed that majority of the students have very little command over English as they lack proficiency in reading. This research has also explored the differences and similarities that teachers had in their practices and the problems which they face in reading comprehension classroom teaching. Implementing reading strategies based on effective reading method should be considered cautiously as the teaching procedure may have some effects on both students and instructors. The current study was specifically limited to investigate the English reading strategies.
The Correlation between Anxiety and Blood Pressure Changes in Administering Computer-Based Competency Test of Ners Students

The study aimed to determine the correlation between anxiety and changes in blood pressure in administering the Ners Students computer-based Competency test. The study used a sphygmomanometer to measure blood pressure and used a HARS tool for anxiety. The research design used is a quasi-experimental method with a non-equivalent pretest-posttest design. The analysis method uses quantitative analysis of chi-square correlations and dependent T-test statistical tests. The results showed no significant association between the anxiety facing computer-based competency tests and changes in students' blood pressure, as evidenced by a score of p = 0.216. There was a significant difference in the average score between anxiety before and after taking the computer-based test p= 0.042. There was no significant difference on average between blood pressure before and after taking the computer-based competency exam p=0.231. This research concluded that the anxiety experienced by students in taking competency exams does not affect changes in blood pressure.
Analysis and Design of a Student and Admin Portal with a Pomodoro Technique Feature for Mindanao Kokusai Daigaku (Mindanao International College)

Academic institutions have become so accustomed to using antiquated paper recording methods to store and process student data that transitioning to a more advanced technological method may not be a top priority at first. Many educational advancements have been demonstrated to be beneficial, however, some educational institutions are falling behind. Mindanao Kokusai Daigaku's lack of a centralized system is the reason for the university's foregoing problems. The college is still managing student data through paper records and an obsolete enrollment information system, which has been very inconvenient for both students and admins, especially during the Covid-19 pandemic. The main objective of this paper is to design a student and admin portal for Mindanao Kokusai Daigaku with a Pomodoro technique feature as an advanced approach for the university's internal operations to improve user convenience, secure documents, and make information more accessible to students while also encouraging productivity. Various methodologies and models were used in this study to further clarify the proposed system's operations and purpose. Based on the results of the findings, the researchers conclude that the suggested portal system is feasible and will address Mindanao Kokusai Daigaku’s current challenges.
Teaching robots to see clearly: optimizing cross-modal domain adaptation models through sequential classification and user evaluation

As society becomes increasingly reliant on autonomous vehicles, it becomes necessary for these vehicles to have the ability to navigate new environments. Environmental data is expensive to label especially because it comes from many different sensors, and it can be difficult to interpret how the underlying models works. Therefore, an adequate machine learning model for multi-modal, unsupervised domain adaptation (UDA) that is accurate and explainable is necessary. We aim to improve xMUDA, a state-of-the-art multi-modal UDA model by incorporating a multi-step binary classification algorithm, which allows us to prioritize certain data labels, and alongside human evaluation, we report the mIoU and accuracy of the final output.
A Cooperative Lightweight Translation Algorithm Combined with Sparse-ReLU

In the field of natural language processing (NLP), machine translation algorithm based on Transformer is challenging to deploy on hardware due to a large number of parameters and low parametric sparsity of the network weights. Meanwhile, the accuracy of lightweight machine translation networks also needs to be improved. To solve this problem, we first design a new activation function, Sparse-ReLU, to improve the parametric sparsity of weights and feature maps, which facilitates hardware deployment. Secondly, we design a novel cooperative processing scheme with CNN and Transformer and use Sparse-ReLU to improve the accuracy of the translation algorithm. Experimental results show that our method, which combines Transformer and CNN with the Sparse-ReLU, achieves a 2.32% BLEU improvement in prediction accuracy and reduces the number of parameters of the model by 23%, and the sparsity of the inference model increases by more than 50%.
THE RELATIONSHIP BETWEEN LINGUISTIC INTELLIGENCE AND STUDENTS’ COGNITIVE ABILITIES IN THE SUB-CONCEPTS OF DISASTER RESPONSE ACTIONS

This research is a correlational study that develops quantitative descriptive research. This study aims to obtain information about the relationship between linguistic intelligence and cognitive abilities in the sub-concepts of disaster response actions and other factors that influence it besides linguistic intelligence. This research was conducted in September 2019. The population of this study was MTS Darul Irfan students of Serang City in the academic year 2019/2020. The sampling technique uses simple random sampling. The sample was 24 students of class VII-A. The data collection method is done by tests, documentation, student worksheets, and observations. Based on the regression and linearity test results, it can be concluded that the simple regression analysis with the equation Y=37.986+0.038X is linear. Based on the result of quantitative research, the correlation coefficient between linguistic intelligence and cognitive abilities is 0,0030. This correlation coefficient value indicates that H0is rejected and H1is accepted, meaning linguistic intelligence weakens student cognitive abilities. In this study, other factors affect student cognitive abilities, among others, strategies and learning methods, development of learning media in schools, and environmental factor of students.
ESL Lecturers’ Adaptation to the New-Norm of Online Teaching in Malaysia

Since March 2020 in Malaysia, tertiary educational sectors have been forced to shift to online classrooms under the Movement Control Order (MCO). The abrupt change to online learning has affected educators’ style of teaching and in navigating themselves for online classrooms. This study aimed to investigate ESL lecturers’ adaptation to online teaching and learning during the outbreak of COVID-19 in Malaysia. This paper adopted a case-study approach with four lecturers were interviewed. The findings of this study indicate that lecturers use online platforms such as Google Meet, Zoom. Additional applications such as Kahoot, Quizizz and Padlets are also used to reinforce students’ English skills. Additionally, issues on the effectiveness of online learning such as Internet connectivity, the paradigm shift from traditional to online classrooms are highlighted by the participants. The findings also highlighted other factors, such as understanding motivational strategies, language learner’s needs, and Sociocultural factors. This paper provides ramifications of online learning such as incentive, laptop rental, and mastering the applications of technology in education.
AB062. SOH22ABS166. BreastNet: a deep learning neural network model to aid breast cancer diagnosis using mammographic imaging

Background: Clinical radiology has evolved such that artificial intelligence and deep learning models show potential to improve the robustness of medical diagnostics, particularly in the setting of cancer. In breast cancer, there is limited data supporting these models to inform early diagnosis.
The Development of Practice Packages on Chinese Pronunciation Skills through Seesaw Online Classroom for Students Majoring in Chinese Language Teaching

This research aimed to 1) develop and measure the efficiency of a set of reading and pronunciation skills in Chinese phonetics via Seesaw online classroom; 2) examine the effectiveness of the set; and 3) evaluate students' satisfaction with practice packages on Chinese pronunciation via Seesaw online classroom. Thirty-six undergraduate students majoring in Chinese language teaching at a university in Thailand were the participants of this study. This study used descriptive statistics (mean and S.D.) and dependent samples t-test. The results of this research indicated a substantial increase in students' learning achievement due to the Seesaw online classroom. Additionally, the Development of Practice Packages for Chinese Pronunciation Skill Acquisition via Seesaw Online Classroom was greater (x̄=4.84, S.D.=0.37) than the researcher’s standard of 3.50, and achieved the efficiency standard criteria of 82.50/84.97, which was greater than the 80/80 efficiency standard criterion chosen. Students' satisfaction with learning was high when they utilized Seesaw's Chinese pronunciation practice packages (x̄= 4.50, S.D.= 0.54).
A case study in hospitals: Comorbidity modeling on Covid-19 mortality risk using logistic regression

Background: Comorbidities may have a role in Covid-19 patients' deaths. The goal of this research was to determine the impact of comorbidities on the risk of death from COVID-19. Methods: The research took place at one of the Covid-19 patients' referral hospitals, from March 2020 to February 2021, data on inpatients was collected, and a logistic regression analysis was used to find co-morbid COVID-19 in patients at high risk of death. Result: Model 1 predicts the risk of death from covid-19 based on age, sex, and the top ten co-morbid covid-19 with an accuracy of 85.3% and an R2 of 62.4%. With a p-value&gt;0.05, sex (SEX), hypertension (HP), diabetes mellitus (DM), cardiac arrest (CA), anemia (AN), hyperuricemia (HR), and urinary tract infection (UTR) do not affect the probability of death in Covid-19 patients in model 1. Model 2 is based on the variables that affect the risk of death (p-value 0.05) are age (AGE), moderate malnutrition (MM), unspecified malnutrition (MU), obesity (OB), and chronic renal disease (CKD). Model 2 is Ln [ þ / (1-þ) ] = -3,295 +0,046*AGE +0,667*OB +0,611*MM +1,53*MU +1,248*CKD showed an accuracy of 69.4% with an R2 of 17.1%. Conclusion: Model 2 is more effective since it only considers diseases with high mortality risk. The results of the model 2 simulation show that the higher the age and comorbid complications, the greater the risk of death for Covid-19 patients.
Scholarly Communication Librarian Tantangan Tupoksi Pustakawan di Era 4.0

Scholarly communication librarian (SCL) is the involvement of librarians to facilitate researchers to know the development of research conducted by other researchers. Scholarly communication is not a new thing in the library world, because scientific publishing has existed since the research was conducted. The purpose of this study was to find out SCL as a challenge for librarian duties in era 4.0 which includes three main tasks of librarians in legislation, library management, library services, and librarianship system development. The population in this study were members of the FPPTI Jawa Barat and a sample of 70 people based on the Slovin formula with an error rate of 10%. The study used a descriptive method with a quantitative approach and data collection techniques using a closed Likert scale questionnaire. Based on the results of the data analysis, it shows that the FPPTI Jawa Barat librarian gave a positive response with a very good category in the SCL. FPPTI Jawa Barat librarians in carrying out their role as SCL have been able to adapt quickly and make important contributions in conducting research. The results of the study illustrate that the FPPTI Jawa Barat librarian has carried out library management well, especially in planning and evaluation, providing various sources of information that are easily accessible to users, quick reference, and conducting scientific writing guidance, and being a facilitator. The involvement of librarians in conducting research shows that FPPTI Jawa Barat librarians are actively involved in research to improve library performance in realizing service excellence.
Proprietary Software Management System for Educational Institutes

Abstract: This College Management System project developed using specific programming languages. The main aim of this project is to develop an online website which covers all the details of college i.e., Student attendance details, Event details, Students fees transaction details, Marks details, Photo gallery, etc. Admin is the Super user of this project. All the record stores in MySQL Database. The proposed software will also reduce the cumbersome paperwork, manual labor as well as communication cost. The main objective of College Management System project is to provide an easy way to automate all record keeping work in the college. This project provides user friendly environment to the operator and admin. This college automation project is a simple yet powerful application for managing large number of student data. With this application admin can maintain record of students, courses, fee payment, library book record and students mark in different semesters. It also allows admin to generate various reports for decision making
Secure protection for covid-19 infographic using blockchain and discrete cosine transform-singular value decomposition (DCT-SVD) watermarking

Covid-19 infographics have a crucial role in mitigating the covid-19 pandemic by conveying the complex Covid19 information in a form of a simple yet understandable image. However, keenly to contribute to mitigating Covid-19, numerous parties and agencies had released Covid-19 infographics that might contain incorrect or inaccurate information. To prevent such recurrent, this paper proposed an authentication system by using a blockchain-based authorization service that lets the authority guarantee the correctness and validity of the infographics in a transparent manner. We proposed smart contract-based watermarking requests and approval management that let anyone track the watermarking process. To prevent unauthorized infographic fabrications, we use the DCT-SVD method considering its robustness against various attacks. We deployed and evaluated the smart contract on Ethereum test networks (Ropsten, Rinkeby, Goerli, and Kovan) to compare the efficiency and the ease of use. The result showed that the test networks have similar efficiency while the Ropsten and Goerli have better ease of use. The watermark validation service is accessible via a web-based interface for anyone to check the validity of the infographic’s watermark.