Reviewerly/exHarmony huggingface dataset:
Software Quality Testing In Mobile Application (ArabEasy) Based on the PACMAD Model

ArabEasy is an application to learn and understand basic concepts of Arabic. This app has a problem with the user interface (UI); based on the comment from users, UI this app is confusing to use. This research focuses on measurement and testing based on usability level using the PACMAD model. Data collection was obtained from Performance Measurement, SUS Questionnaire, NASA-TLX Questionnaire, and RTA Questionnaire. The result from this process is measured using usability metrics, statistical testing, and calculation from the questionnaire, respectively. The next process, making a recommendation to improve UI, became a prototype based on The four Golden Rules of User Interface Design. The result of this process showed increased effectiveness 37.22%, efficiency 46.08%, satisfaction 24.25. Furthermore, errors aspect decreased 13.4%, and the cognitive load 18.54.
Measuring Objective Visual Quality of Real-Time Communication Systems in the Wild

During the outbreak of epidemic diseases, the importance of real-time communication (RTC) systems dramatically increases. People use RTC systems for communicating with others, presenting projects, attending online courses, and sharing videos. With different network conditions, applications, and scenarios, how to choose an appropriate system for high-quality RTC is an open question. To the best of our knowledge, there is no general and unified method to comprehensively evaluate the performance of the publicly available RTC systems. In this paper, we systematically evaluate several performances of RTC systems. Our method treats systems as a black-box, which can be easily adapted to other systems. Our method is also available for other video transmission systems, such as streaming and live broadcasting systems. According to our measurement method, we evaluate three web-based and three software-based RTC systems on two video conferencing (VC)-based and two screen sharing (SS)-based scenarios. We measure the received video quality (graphical quality and frame rate) at the receiver, the upload bitrate at the sender, and four usages of local resource. Furthermore, we propose a new metric to measure the ability of the system to handle insufficient bandwidth situations. Our proposed metric is the first one directly measure the ability of the rate adaptation mechanism for RTC systems. We expect the measurement method, the metric, and our findings can help system development in the future. Our detailed analysis reveals that (1) the software-based systems are more efficient than the web-based systems for bitrate usage; (2) the web-based systems are more tolerant to insufficient bandwidth conditions than the software-based systems; (3) the studied RTC systems currently are not designed for the scenario of sharing dynamic videos because of their low-frame-rate strategy, which limits the usage; and (4) decreasing graphical quality is more likely to be recognized than decreasing the frame rate. Frame rate adjustment for rate adaptation can be considered.
An Empirical Study on Intuitive Gesture Manipulation in Virtual Reality

Gesture manipulation is a new input mode for the modern virtual reality (VR) user experience. Current gesture manipulation can be performed with three types of devices: Hand-held, Bare-hand and Hand-worn devices. Each device has its own advantages and disadvantages. However, many studies have not discussed the difference between these three types of gesture manipulation. To address this gap, we conducted research on how to find their learnability, effectiveness, and extensibility. We introduce a VR cup stacking game to mimic the state-of-presence experiment to compare the completion time of each device. Moreover, a series of user studies were conducted to collect feedback from participants. The results show that despite the Hand-held device being familiar to general users, but most of them were expected that the Hand-worn and Bare-Hand device can be well developed and wildly adopted into other applications to provide more intuitive and immersive experience.
Nutritional Management Mode of Early Cardiac Rehabilitation in Patients with Stanford Type A Aortic Dissection

Malnutrition and metabolic disorders are common problems faced by patients with Stanford type A aortic dissection after surgery. Some patients have dietary problems such as malnutrition, unbalanced diet, and poor eating habits before surgery. Therefore, the nutritional management of early heart health can improve the nutritional support for perioperative recovery, to improve the pertinence. Therefore, active nutritional support after surgery will help to change malnutrition and metabolism and is of great significance to postoperative recovery and quality of life. This paper is aimed at studying the nutritional management mode of early cardiac rehabilitation in patients with Stanford type A aortic dissection. Based on the analysis of the pathogenesis of aortic dissection and the diagnosis of aortic dissection, two groups of patients were given individualized nutritional management scheme and routine nutritional scheme, respectively, and the nutritional risk differences between the two groups under different schemes were compared. The results showed that there was a statistical difference between the two groups at discharge. The NRS-2002 score of 14 cases in the observation group was less than 3 after nutritional intervention, indicating that there was no nutritional risk at discharge.
Agriculture Supply Chain Management Using Blockchain

Agricultural farmers have a number of challenges these days, including seasonal variations and a broken supply chain; their work is tough and time-consuming. In this circumstance, a separate information database with validated data would be extremely beneficial. Knowledge exchange is critical in all facets of our industry, whether it's regarding market trends or successful techniques. In this area, third-party influence could lead to the spread of incorrect information. To mitigate this risk, blockchain, a secure and immutable data ledger, can be used. The purpose of this study is to investigate the many ways in which blockchain technology can be applied as a transparent and dependable transaction mechanism in the agricultural supply chain. Keywords: ASC, BCT, AES, visual cryptography, SHA 256, Java, JSP, Servlet, Web, etc
Domain adaptive multi-task transformer for low-resource machine reading comprehension

In recent years, low-resource Machine Reading Comprehension (MRC) attracts increasing attention. Due to the difficulty in data collecting, current low-resource MRC approaches often suffer from poor generalizing capability: the model only learns limited task-aware and domain-aware knowledge from a small-scale training dataset. Previous works generally address such deficiency by learning the required knowledge from out-of-domain MRC datasets and in-domain self-supervised datasets. However, such approaches also introduce domain noise and task noise. This paper proposes a Domain Adaptive Multi-Task Transformer (DAMT2) to tackle these noises. For task noise, DAMT2 utilizes a well-designed Multi-Task Transformer (MT2) as the backbone to model the high-level features separately from different tasks. For domain noise, two kinds of domain adaptation approaches are incorporated into MT2 to learn domain-invariant representations. The experimental results show that our method outperforms several baselines on multiple datasets, and especially achieves a new SOTA on the RRC dataset. Moreover, using only 40%-60% training data, our work achieves comparable performance with the classic BERT model.
Model Pembelajaran Kooperatif Tipe Round Tabel Berbantuan Media Tas Pukaki Terhadap Keterampilan Manulis Puisi

Cooperative Learning Model Round Table Assisted by Pukaki Bag Media on Poetry Writing Skills in Fourth Grade Students of SD Negeri Girimulyo. This research uses Quasi Experimental Design with Time Series Design. The research subjects used a total sampling of fourth grade students. The sample used was 20 students. The data collection method was carried out using a performance test of 8. Test the construct validity of the poetry writing skill assessment sheet using expert opinion. The hypothesis was tested using the Wilcoxon matched pairs with the help of SPSS for Windows Cooperative learning model Round Table assisted by the media Bag Pukaki had a positive effect on poetry writing skills in fourth grade students of SD Negeri Girimulyo. This is evidenced by the results of the Wilcoxon matched pairs with the Asymp probability. Sig. (2-tailed) is 0.000&lt;0.05. Based on the results of the analysis, there are differences in the average scores on the pretest 1,2,3, and 4, the average value is 56 stable and the posttest 1,2,3, and 4 results are stable at 79.
Devops Adoption in Information Systems Projects; A Systematic Literature Review

The word DevOps derives from two different words Development and Operations. DevOps has recorded as an interesting and novel approach adopted to the commonly used Agile software development methodology. It raised agility of the software development process. Practical issues of Agile methodology emphasize the requirement for collaboration of software development and operating teams. This collaboration completed by the DevOps approach engages with the Agile methodology to improve the quality, performance, and speed of the software developments. Since DevOps is an accentuating approach in the software development industry, this research aimed to conduct a literature review to study the evolution of the DevOps approach and its adoption in information systems projects. This target has accomplished by reviewing the Agile methodology, issues of the Agile methodology, DevOps approach, challenges and overcoming strategies of DevOps, and success factors of the DevOps approach. Finally, the paper provides better acquaintance about the DevOps adoption in Information System projects developments.
Benchmarking domain adaptation for semantic segmentation

Deep Learning (DL) requires a massive, labeled dataset for supervised semantic segmentation. Getting massive labeled data under a new setting (target domain) to perform semantic segmentation requires huge efforts in time and resources. One possible solution is domain adaptation (DA) where researchers transform the data distribution of existent annotated public data (source domain) to resemble the target domain. We develop a model on this transformed data. Nevertheless, this poses the questions of what source domain/s to utilize, and what types of transformation to perform on that domain/s. In this research work, we study those answers by benchmarking different data transformation approaches on source-only and single-source domain adaptation setups. We provide a new well-suited dataset using unmanned ground vehicle Husarion ROSbot 2.0 to analyze and demonstrate the relative performance of different DA approaches.
Novel neural network architecture for energy prediction

Several classical statistical methods are commonly used for forecasting time-series data. However, due to a number of nonlinear characteristics, forecasting time-series data remains a challenge. Machine learning methods are better able to solve problems with high nonlinearity. RNNs (recurrent neural networks) are frequently used for time-series forecasting because their internal state, or memory, allows them to process a sequence of inputs. Specifically, LSTM (long short term memory), a type of RNN, is particularly useful, as it has both long-term and short-term components. Due to its feedback connections, ability to process a sequence of data of varying lengths, and ability to reset its own state, LSTMs are less sensitive to outliers and more forgiving to varying lags in time. Consequently, LSTMs are able to extract vital information and learn trends to forecast time-series data with high accuracy. We propose a novel neural network architecture using a combination of long short term memory and convolutional layers to predict time-series energy data with higher accuracy than comparable networks.
Instant Messaging Application Based on Android

Abstract: Through communication, an individual can express his ideas, feelings, and various aspects to others. Communication via the internet is becoming increasingly important these days. Through online communication, users can communicate with others remotely quickly, and conveniently irrespective of their physical location. With this in mind, communication applications should be able to instantly transfer files and messages with no delay or with minimal delay, depending on the transmission medium. For such a system to work, it needs a database that is updated in real-time to keep track of all the data sent. Google Firebase is a service that provides a real-time database server and various other functions. Firebase makes it relatively easy to develop communication-based applications. The main purpose of this paper is to initiate real-time communication between users through a software application that works on android devices connected to the internet such that the communication gap between the users gets reduced. Google Firebase is used to handle the communication process of the backend and text translation and image optical character recognition are among the features included in this application. Keywords: Android, Firebase, Instant messaging, ML translate, Text recognition
Backpropagation and Radial Basis Function Methods for Predicting Rainfall in Sukabumi City Using Artificial Neural Networks: A Comparative Analysis

The weather has a substantial impact on the ability to live organisms to carry out everyday activities, particularly outside activities. Weather data is helpful in various fields, including marine, aviation, and agriculture. The maritime domain is beneficial for establishing the optimal navigation time for a fisherman, the aviation domain helps reduce climate-related mishaps, and the agriculture sector uses weather information to develop harvest season models for agricultural products. Indonesia is a tropical nation with heavy precipitation. Utilized for various objectives, rainfall forecasting models seek the utmost precision, particularly in specialized areas such as flood control. This study is based on two techniques: the Radial Basis Function Neural Network (RBFNN) and Backpropagation Neural Network (BPNN) techniques using multiple training functions. The RBFNN approach yields less accurate results for predicting precipitation, but the multi-practice BPNN method yields more accurate results.
Dental health education game based-on IRVO model in augmented reality technology

Public Dental health must be maintained from an early age. However, it is not easy to make the children interested, understand, and aware of dental health. This paper discussed alternative methods for educating the children using IRVO model in augmented reality technology-based educational games. The game was built from several materials consisting of dental health education recommended by the dentist. Some of the interactions represented in the game application consist of point of view, selection and release, event creation, and manipulation. This educational game is implemented using the 3DS Max and D-Fusion Studio. This game has been approved for counsellors such as dentists, nurses, community health workers, and children. According to the resulting test, more than 75% of the dentists and children are interested in using this game and declared that they could use this application easily.
Position Deployment Optimization of Maneuvering Conventional Missile Based on Improved Whale Optimization Algorithm

To reasonably allocate mobile conventional missile battle positions and improve the survivability and combat effectiveness of the missile weapon system, a missile position deployment optimization design model based on Mixed-Integer Nonlinear Programming (MINLP) is established. First, for the multilevel position network, an optimization model with the goal of maximizing the viability is established, and a two-stage solution method is proposed. Second, the whale optimization algorithm (WOA) is improved, and the convergence factor which changes nonlinearly with the number of evolution is introduced to coordinate the local development and global search ability of the algorithm. The diversity mutation operation is carried out on the optimal individual to reduce the probability of premature convergence of the algorithm, and the improved whale algorithm is used to solve the optimization model. Finally, the performance of the improved algorithm is verified by example analysis and simulation experiments, which provides a reference for the deployment mode of mobile missile positions.
SECURE SOFTWARE DEVELOPMENT AWARENESS: A CASE STUDY OF UNDERGRADUATE DEVELOPERS

As ubiquitous computing becomes an increasingly inherent component of everyday life due to the rapid growth of communication technologies and globalization, threats against information systems have taken a more latent yet lethal dimension. This emergent digital security challenge has correspondingly motivated a proactive change in the software engineering process in recent decades. This change has inspired more intense research scrutiny on security as a crucial component of any software system. Moreover, in today’s virtual world of hyperconnectivity, the most significant vulnerabilities in modern information systems security are software centred. Nevertheless, research shows that software developers often lack the required knowledge and skills in secure software systems development (SSD). Such knowledge ensures that all the resultant software components of each development lifecycle are correctly implemented rather than merely following the SSD lifecycle. Also, the knowledge engenders software security consciousness as a professional attitude amongst developers. Therefore, investigating students’ awareness of SSD principles can generate insight into evolving the undergraduate software development curriculum – a path to building future career developers. The study used a voluntary online survey to recruit a sample of 76 undergraduate developers and employed a descriptive approach to data analysis. Among other findings, the study revealed that participants’ perception of the threat of software vulnerability impacts their attitude towards security on online and mobile platforms. And that though over 90% of the undergraduate developers took software vulnerability threats either “serious” or “extremely serious”, this disposition did not reflect the depth of their knowledge and experience in SSD.
Extensión universitaria en tiempos de pandemia por Covid-19: la experiencia de la Facultad de Ciencias Humanas de la UNRC

This article proposes to share, socialize and reflect the challenge of university extension in the Faculty of Human Sciences of the National University of Río Cuarto (Argentina), which in 2020 acquires very particular nuances facing the pandemic caused by Covid-19.The restrictions of isolation and social distancing imposed new institutional conditions in the work of knowing, listening, guiding, managing or trying to solve problems that arose with the pandemic.To address this issue, a record, systematization and analysis of the proposals that emerged at that time was carried out in order to characterize the extension scenario, some regulations and the main actions, in this context.In an introductory way, a brief tour is recovered that is developed around a process of strengthening the extension in the Faculty of Human Sciences, commenting on some outstanding points that provide the basis for the redefinition of action frameworks and the new activities undertaken.In this way, the potentiality of extension is situated as a strategic space to promote encounters between teaching and research, relations between University and Society, and the development of proposals in the face of the various situations that demand structural inequalities and the processes of violation visibles in the socio-territorial space.The context of the pandemic and its effects makes it possible to demonstrate some adaptations that were assumed from the management of university extension; the generation of new devices to channel initiatives of the extension teams, the reorientation of objectives and priority lines, and the combination of face-to-face and virtual activities, among other aspects.The training and communication activities also gave an account of the accompaniment that was promoted.
SOCIAL ENGINEERING, IMPERFECT HUMAN

The article introduces the concept of "Social Engineering". This term is used for a broad range of malicious activities accomplished through human interactions. The previous year has seen an enormous increase in the studies related to social engineering. This increase is partly due to the increasing number of social engineering attacks and partly due to people's inability to identify the attack. The authors define the subject of social engineering from a Cyber Security professional perspective. A literature review from the information technology, psychology, and business disciplines explains the interconnected nature of the topic as well as the necessity to comprehend it from multiple viewpoints. The article presents several case studies of successful attacks performed as well as their efficacy.
Optimizing JMeter on Performance Testing Using the Bulk Data Method

Company X is one of the companies engaged in the telecommunications business. To improve customer service, the company developed an Application Programming Interface). The developed API is used to promote product packages to customers. Sending data via API to millions of customers at the same time, can lead to failures due to the inability of the server to process that data. JMeter is one of the tools that can be used to perform performance testing of an API by providing TPS calculation output. Bulk data files are used as input to process large amounts of customer data on JMeter. Proper thread properties settings affect the TPS value, and the study has managed to achieve the TPS value to be achieved with error rate = 0, which means success.
Functionality Performance of Information Systems in Higher Education Institutions

The goal of this research was to evaluate the performance of information systems in terms of functionality of the in-house developed and outsourced information systems of Higher Education Institutions (HEIs) in Samar, Philippines. A descriptive research design was used in order to obtain information on the performance of the information systems in terms of functionality. The technique employed for data collection was physical evaluation using an observation sheet. A total of thirteen (13) information systems were subjected to performance evaluation as there were thirteen HEIs from the different provinces of Samar Island that participated in the study. The overall results showed that the outsourced systems had better performance in terms of functionality since most of the indicators were completely existing and functional. On the other hand, the in-house systems have performed fairly with regards to the required features and functionalities of the system. The results of the study suggest that HEIs should acquire information systems that are completely functional, regardless of what acquisition method is adopted. Having information systems equipped with the required functionality features, the administrative and academic functions of HEIs are effectively and efficiently delivered.