Reviewerly/exHarmony huggingface dataset:
Research on Multi Core Parallel Knowledge Tracking Algorithm for Knowledge Combination

The traditional knowledge tracking model can only predict a single knowledge point, which is not enough to reflect the students' mastery of multiple knowledge: predicting multiple knowledge points and their combined knowledge involves a lot of calculations, which leads to low efficiency. This paper proposes a parallel knowledge tracking algorithm oriented to the combination of knowledge points. The algorithm proposes parallel HMM to estimate the mastery of multiple individual knowledge points, and predicts students' mastery of the combined knowledge points through least squares fitting and gradient descent fitting methods. Experiments show that this method can significantly improve the calculation efficiency and the accuracy of the combined knowledge point prediction.
Depth-Guided Two-Way Saliency Network for 2D Images

Depth is one of the primary visual cues which distinguish an object from its background. In recent years, salient object detection has achieved great success with the help of a convolution neural network and its corresponding depth map. Previous methods have already utilized depth map to improve the precision of the results; however, all of the previous methods are only concentrating on the available RGB-D datasets to train their network. In this paper, we used a depth estimation network to find the depth map of 2D images. That depth map has been used to train the depth-guided saliency network, which produces the intermediate depth saliency map. Finally, the depth saliency map has been fused with the coarse saliency map to obtain the final saliency map. Experiments demonstrate the effectiveness of the proposed method, which achieves state-of-the-art performance on six popular benchmarks.
Literasi Media Melalui Video Podcast pada Kalangan Mahasiswa Yogyakarta

Video podcasts become one of the digital content included in a combination format, combined writing, video, and audio packed so that it becomes content distributed in digital format. The ease of accessibility of podcast video content makes it important to apply media literacy to remain critical of the message's various meanings in the content in the video podcast. This study aims to determine the level of media literacy through video podcasts among students of Communication Sciences Yogyakarta. The method used in this study is a descriptive quantitative method with the concept of measuring individual competence framework media literacy. Samples from this study were active students of Communication Sciences in 2019/2020 at Ahmad Dahlan University, Mercu Buana University Yogyakarta, and AMIKOM University Yogyakarta, with a total sample of 368 respondents. This study showed that the level of media literacy through video podcasts among students of Communication Science Yogyakarta is at a high level (advanced) with details of technical skills are in the advanced category of 80%, critical understanding ability at the advanced level of 86%. Communicative abilities are at the medium level of 59%. This shows that Yogyakarta communication students can use very high media, analyze excellent information, and participate and communicate actively through social media.
Electronic Archives Management for Large-scale Cross-sea Infrastructures based on Project Management Platform

Large-scale cross-sea projects have huge construction scale, complex engineering technology, long construction period, and multiple participants. The traditional archives management methods are difficult to meet the requirements in terms of standardization and synchronization. Firstly, this study establishes a project management platform that allows electronic documents to be generated simultaneously with the construction process. Finally, the electronic documents generated in the management platform are automatically collected by an electronic archives management system. This platform greatly improves the quality and efficiency of electronic archives management.
Digital educational resources for the development of cognitive interests of primary school children in extracurricular activities

The article is devoted to the problem of using digital educational resources (COR) for the development of cognitive interests of younger students in extracurricular activities. Using the methods of theoretical analysis of scientific sources, questionnaires, comparison of digital educational resources located on educational Internet portals, websites and platforms, the author in her studies identifies necessary requirements for a modern teacher – the ability to navigate and use digital educational resources. The article discusses the features of primary school children of generation A (alpha). The author made an attempt to define the concept of “digital educational resources” in relation to extracurricular activities. The CORs contained in twenty-four educational Internet portals, sites and platforms were studied and the possibility of their use for the development of cognitive interests of younger students in extracurricular activities was analyzed. Parents were surveyed in order to establish their opinion about the use of Internet resources. The attitude of teachers to the use of COR in extracurricular work with younger students is determined. The conclusion is made that it is necessary to use the COR in the extracurricular activities of primary schoolchildren for developing cognitive interests. The author also noted that the number of such resources is insufficient.
PROFESSIONAL DEVELOPMENT OF TEACHERS FOR THE IMPLEMENTATION OF DISTANCE LEARNING AT SCHOOL

The article deals with the problem of increasing the level of competence of teachers associated with the use of digital educational technologies in the educational process of the school by organizing advanced training courses. Effective digital educational technologies for organizing distance learning are also described. The formation of digital competence is possible in the process of implementing educational programs of higher education, as well as professional development and professional training programs. The authors, based on the analysis of empirical data obtained during the survey of current teachers and future teachers - students of the pedagogical direction on the use of distance educational technologies in the educational process, identify problems and difficulties in using digital technologies, types of competence improvement for the successful implementation of distance learning. Based on the analysis of ICT competence in the field of education, the authors developed a program of a professional development course on the topic "Kashyktyktan okytudagi tsifrlyk bilim beru technologiyalary" and conducted teacher training. The survey revealed the degree of readiness and desire of teachers to use digital tools and services in the educational process. This suggests the need for further development of the organization of effective online communication of participants in the educational process, productive feedback with students using digital technologies; forming a critical assessment of students 'behavior and correcting their actions when working in a digital educational environment, monitoring the independence of students' performance of educational tasks; using the potential of digital tools and services in organizing group work and project activities of schoolchildren, and others.
The performance of a library in improving reading culture during the Covid-19 pandemic

The research aims to describe the strategy of the library in improving the reading culture and to find out what factors affect the performance of library services in increasing public interest in reading during a pandemic. The research method used is the descriptive method using surveys and interviews as well as qualitative analysis. Data was obtained through questionnaires, interviews and observations. The research was conducted in the library of state universities in Malang City. The results showed that the performance of library services in improving reading mints was not optimal; it was indicated that there were still user complaints, the attitude of service officers was not fully responsive and information on service programs was not widely known by users.
[Guest Editorial]

Evolutionary Algorithms (EAs) are nature-inspired population-based search methods which work on Darwinian principles of natural selection. Due to their strong search capability and simplicity of implementation, EAs have been successfully applied to solve many complex optimization problems, which cannot be easily solved by traditional mathematical programming approaches, such as linear programming, quadratic programming, and convex optimization. Despite the great success enjoyed by EAs, it is worth noting that existing EA solvers usually conduct the search process from scratch, regardless of how similar the new problem encountered is to those already solved in the past. Therefore, conventional EAs do not learn from previous problems and the search capabilities of the EA solvers do not automatically grow with problem-solving experiences. However, in reality, since problems seldom exist in isolation, solving one problem may thus yield useful information for solving other related problems. In the literature, there is a growing interest in conducting research on evolutionary transfer optimization (ETO) in recent years: a paradigm that integrates EA solvers with knowledge learning and transfer across related domains to achieve better optimization efficiency and performance.
If You Are Committed to Justice, Why Aren't You an Activist? Comments on Allen Buchanan

ABSTRACT In response to Buchanan's argument that ideologies function as doxastic immune systems, I invite him to expand on three issues. (1) What does it mean to have a perfect grasp of the principles of justice, and why should we think that someone with such a grasp should be in a position (even if unable) to act justly? (2) What is required to be fully epistemically responsible when in the grip of an ideology? (3) Might we learn more from contemporary Critical Theory about the workings of ‘doxastic immune systems’?
One-take video boundary point extraction based on frame characteristics

This paper deals with a system for extracting boundary points for unedited video. The term ‘unedited’ means that the user continuously shoots at once without stopping the shooting through a device such as a camera or mobile phone. In general, if image intrinsic pixel values or RGB characteristics are used to compare adjacent frames, it is difficult to extract a boundary point from continuous one-take video. However, the pixel mean and the standard deviation was obtained and the ratio was used as a primary filtering. Through key point extraction and comparison using SURF(Speeded-Up Robust Features), segmentation points were well extracted even in one-take videos with severe shaking. The entire system is tested with the a video shot directly through a mobile phone and a short film shot with one-take, and found that the speed of about 30fps of more was obtained, indicating real-time performance.
Feature Extraction

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Analysis of Digital Long Jump Take-off Wearable Sensor Monitoring System

The wearable sensor monitoring system builds a long jump take-off recognition network model based on different digital feature extraction methods (one-dimensional digital feature extraction method, two-dimensional digital feature extraction method, and feature extraction method combining one-dimensional digitization and recursion). Experimental verification and analysis are performed on the processed sample data, and the identification effects, advantages, and disadvantages of the four methods are obtained. First, the sensor behavior movement collection software is designed based on the Android system, and the collection time and frequency are specified at the same time. In addition, for the problem of multisensor behavior recognition, an effective result fusion method is proposed. In a multisensor behavior recognition system, constructing a parallel processing architecture is conducive to improving the rate of behavior recognition. To maintain or increase the rate of behavior recognition, the result fusion method plays a vital role. Finally, this paper analyzes the process of multitask behavior recognition and constructs a residual model that can effectively integrate multitask results and fully mine data information. The experimental results show that, for the monitoring of exercise volume, we use step count statistics to extract feature values that can distinguish activity types based on human motion characteristics. This paper proposes a sample autonomous learning method to find the optimal sample training set and avoid occurrence of overfitting problems. In the recognition of 11 types of long jump take-offs, the average accuracy rate reached 98.7%. The average replacement method is used to count the number of steps, which provides a data reference for the user’s daily exercise volume.
Research on Fault Prediction Method of Printing Equipment Based on GRU Neural Network

Aiming at the problem of low prediction accuracy caused by poor timing of existing printing equipment fault prediction methods, this paper proposes a fault prediction method based on the gated recurrent unit (GRU) neural network. Firstly, the data were preprocessed, the sample average value was used to fill the missing value of the sample, and the data was standardized. Then, the GRU neural network was built based on Keras deep learning framework, and the input data were trained and tested. At the same time, the model parameters were optimized by KerasClassifier and GridsearchCV of SkLearn. Finally, the proposed method is compared with RNN, LSTM, SVM and other methods, and the recognition accuracy and network convergence speed are regarded as quantitative characteristics. The experimental results show that the proposed method has smaller error and higher prediction accuracy.
From Positive to Death: A Corpus-Based Semantic Analysis of COVID-19 Representation in Malaysian English News Reports

More than a year after being declared a pandemic, Covid-19 has not shown any sure signs of dissipating even as the battle to curb it continues. In Malaysia, the Movement Control Order (MCO), or lockdown seems to be the most effective way to curb the spread of the disease. Unfortunately, studies show that lockdowns affect people’s livelihoods and lifestyle, as well as their emotional and mental state. This situation, in many countries, is exacerbated by the onslaught of negative news on Covid-19 and heightened news consumption via various media platforms. Given this, the objective of the current study is to analyse the representation of Covid-19 in Malaysian media based on a corpus of news reports during Malaysia’s first lockdown, i.e. MCO 1.0. This was a period of uncertainty lasting six weeks beginning from 18 March 2020 which saw increased reports of mental health cases and domestic violence cases in the country. News reports published in two Malaysian English online newspapers, The Star Online and Malaysiakini during MCO 1.0 formed the corpus of study. Using collocational analysis, the study examined the semantic prosody of Covid-19 and how it is represented in Malaysian new reports. The findings show that ‘Covid-19’ generally occurs in the company of unfavourable associations, causing it to acquire a negative prosody and in turn negatively represented in the news reports. The unfavourable portrayal of Covid-19, coupled with the increase in news consumption may adversely affect readers’ emotions and anxiety levels, which in turn, may contribute to crisis fatigue. Keywords: Covid-19; semantic prosody; evaluative meaning; representation; Malaysian English
Blockchain as a Secure and Reliable Technology in Business and Communication Systems

Today we are witnessing a constant growth of data from different sources and in different fields, like government, health, travel, business and entertainment. Traditionally, this data is stored in one central place located on company’s or organization’s server, providing easier control, management, analysis and business intelligence. However, this architecture has certain disadvantages like existence of single point of failure, vulnerability and privacy issues. Distributed ledger technology like Blockchain presents new architecture that does not store data in one location and that does not have central authority. Although Blockchain technology offers improvements in security, transparency and traceability, it is criticized for its resource consumption, complexity and its lack of clear usefulness. Because of its complexity and distributed architecture, users are still suspicious about its security and privacy of its data. This paper analyses various aspects of applying Block-chain technology in modern systems, focusing on data storage, processing and protection. By enumerating common threats and security issues, this paper tries to show that Blockchain is trustworthy, reliable and that can be a potential solution or participant for current security problems.
Work-life balance programs as personnel social and psychological support in organizations

Introduction. Today work environment becomes stressful, with many tasks and problems to solve. It is overloaded, imbalanced, complicated and often full of conflicts. In this climate, managing the boundary and balance between home and work is becoming more challenging. There is a need for organizations and personnel alike to find flexible and innovative solutions that maximize productivity without damaging personnel’ well-being, their personal life, family relationships. Aim. To analyse the main categories, resources and limitations of work-life balance, results of empirical study, main organizational and individual strategies for creating balance. Results. Work-life balance is a category defined by researchers as a person’s subjective general assessment of the interrelation between work and other life areas, family, as well as the ability to combine these spheres in a proper way. The empirical study has shown, that the work-life balance has been generally assessed as average. It should be noted that they have scored the load balance lower than other components: professional tasks complexity, work and content planning, and social intercourse. According to the results of the empirical study and to the theoretical approaches, the basic strategies in professional productivity increase programs in organizations may be the following: focus strategies, “resource/refusal” strategies, adaptive strategies, every of which is manifested in a certain kind of an individual strategy. The use of the adaptive individual strategies with the resource increase strategy perfectly contributes to the work-life balance achievement. Conclusion. Based on the results of theoretical and empirical research, we have identified organizational conditions and individual strategies for achieving the work-life balance, and also the main personal skills and traits contributing to the work-life balance achievement include the following ones: personal flexibility, a high level of self-discipline; trust-based relations; dynamic and independent work. These skills should be mature, and the work-life balance achievement psychological teaching programs for personnel can increase their level.
Parental Involvement and Reading-Related Activities of Struggling Readers of English as a Second Language

The focus of the study is to explore the way the parents took part in their children’s English as a second language (henceforth ESL) learning at home. This qualitative study utilised interviews to garner information from seven participating parents of struggling readers of English as a second language in a Malaysian primary classroom. This paper intends to report the findings from the research question, namely: “How do the participating parents work with their children at home?” Two major themes emerged from the data: involvement; and challenges. In this paper, the partial results of one of the main themes discovered, that is involvement will be presented. This paper highlights reading-related activities that were carried out by the parents at home with their children. It is hoped from this study that educators could exploit the home reading activities of the struggling readers to inform teaching practices to effectively support those students in the ESL classroom.
Real time pose detection of animals using HRNet

We design a machine learning algorithm for detection of the joints of a cat from an image. We compare the accuracy and the speed of the algorithm with weights initialised from a network trained on images of humans and with random initialisation of the weights. We also compare five networks with different sizes for speed and accuracy.
Understanding High-Level Behavior with Light-Traces Visualization Metaphor

The ninth IEEE Working Conference on Software Visualization (VISSOFT 2021) builds upon the success of the previous eight editions of VISSOFT, which in turn followed after six editions of the IEEE International Workshop on Visualizing Software for Understanding and Analysis (VISSOFT) and five editions of the ACM Sympo0sium on Software Visualization (SOFTVIS). In 2021, VISSOFT will take place and be co-located with ICSME.
Incorporating RTLS-Based Spatiotemporal Information in Studying Physical Activities of Clinical Staff

Clinicians and staff who work in intense hospital settings such as the emergency department (ED) are under an extended amount of mental and physical pressure every day. They may spend hours in active physical pressure to serve patients with severe injuries or stay in front of a computer to review patients' clinical history and update the patients’ electronic health records (EHR). Nurses on the other hand may stay for multiple consecutive days of 9-12 working hours. The amount of pressure is so much that they usually end up taking days off to recover the lost energy. Both of these extreme cases of low and high physical activities are shown to affect the physical and mental health of clinicians and may even lead to fatigue and burnout.In this study Real-Time location systems (RTLS) are used for the first time, to study the amount of physical activity exerted by clinicians. RTLS systems have traditionally been used in hospital settings for locating staff and equipment, whereas our proposed method combines both time and location information together to estimate the duration, length, and speed of movements within hospital wards such as the ED. It is also our first step towards utilizing non-wearable devices to measure sedentary behavior inside the ED. This information helps to assess the workload on the care team and identify means to reduce the risk of performance compromise, fatigue, and burnout.We used one year worth of raw RFID data that covers movement records of 38 physicians, 13 residents, 163 nurses, 33 staff in the ED. We defined a walking path as the continuous sequences of movements and stops and identified separate walking paths for each individual on each day. Walking duration, distance, and speed, along with the number of steps and the duration of sedentary behavior, are then estimated for each walking path. We compared our results to the values reported in the literature and showed despite the low spatial resolution of RTLS, our non-invasive estimations are closely comparable to the ones measured by Fitbit or other wearable pedometers.Clinical Relevance— Adequate assessment of workload in a dynamic care delivery space plays an important role in ensuring safe and optimal care delivery [7]. Systems capable of measuring physical activities on a continuous basis during daily work can provide precious information for a variety of purposes including automated assessment of sedentary behaviors and early detection of work pressure. Such systems could help facilitate targeted changes in the number of staff, duration of their working shifts leading to a safer and healthier environment for both clinicians and patients.