Reviewerly/exHarmony huggingface dataset:
CompleteInst: An Efficient Instance Segmentation Network for Missed Detection Scene of Autonomous Driving

As a fundamental computer vision task, instance segmentation is widely used in the field of autonomous driving because it can perform both instance-level distinction and pixel-level segmentation. We propose CompleteInst based on QueryInst as a solution to the problems of missed detection with a network structure designed from the feature level and the instance level. At the feature level, we propose Global Pyramid Networks (GPN) to collect global information of missed instances. Then, we introduce the semantic branch to complete the semantic features of the missed instances. At the instance level, we implement the query-based optimal transport assignment (OTA-Query) sample allocation strategy which enhances the quality of positive samples of missed instances. Both the semantic branch and OTA-Query are parallel, meaning that there is no interference between stages, and they are compatible with the parallel supervision mechanism of QueryInst. We also compare their performance to that of non-parallel structures, highlighting the superiority of the proposed parallel structure. Experiments were conducted on the Cityscapes and COCO dataset, and the recall of CompleteInst reached 56.7% and 54.2%, a 3.5% and 3.2% improvement over the baseline, outperforming other methods.
Classification of Emotional and Immersive Outcomes in the Context of Virtual Reality Scene Interactions

The constantly evolving technological landscape of the Metaverse has introduced a significant concern: cybersickness (CS). There is growing academic interest in detecting and mitigating these adverse effects within virtual environments (VEs). However, the development of effective methodologies in this field has been hindered by the lack of sufficient benchmark datasets. In pursuit of this objective, we meticulously compiled a comprehensive dataset by analyzing the impact of virtual reality (VR) environments on CS, immersion levels, and EEG-based emotion estimation. Our dataset encompasses both implicit and explicit measurements. Implicit measurements focus on brain signals, while explicit measurements are based on participant questionnaires. These measurements were used to collect data on the extent of cybersickness experienced by participants in VEs. Using statistical methods, we conducted a comparative analysis of CS levels in VEs tailored for specific tasks and their immersion factors. Our findings revealed statistically significant differences between VEs, highlighting crucial factors influencing participant engagement, engrossment, and immersion. Additionally, our study achieved a remarkable classification performance of 96.25% in distinguishing brain oscillations associated with VR scenes using the multi-instance learning method and 95.63% in predicting emotions within the valence-arousal space with four labels. The dataset presented in this study holds great promise for objectively evaluating CS in VR contexts, differentiating between VEs, and providing valuable insights for future research endeavors.
Are “well” teachers “better” teachers? A look into the relationship between first-year teacher emotion and use of evidence-based instructional strategies.

Teachers experience significant stress with 93% reported high levels of stress (Herman et al., 2018), and literature examining teacher stress levels during the COVID-19 pandemic reveals that 30 percent of teachers experience significantly high levels of stress (Silva et al., 2021). Low levels of teacher well-being and higher levels of stress have been linked to punitive behavior management (Jennings & Greenberg, 2009) and lower student academic achievement (Goddard et al., 2000). The aim of the present study is to explore the relationship between teacher emotion and use of evidence-based instructional strategies that promote student success. In this study, 17 first-year teachers completed a novel measurement, inclusive of single-item scales intended to assess feelings of stress, efficacy, and school connectedness, several times a day, each day of the week, for 1 month. The classroom strategies assessment system of evidence-based academic and behavioral instructional strategies was used in weekly teacher observations. Results indicated validity between these single-item scales and established measures of teacher well-being. A positive relationship between teachers' in-the-moment well-being and evidence-based instruction was found, as well as substantial variation in teacher emotional response across days and weeks. Implications and future directions are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
DESIGN OF DENTAL AND MOUTH CARE INFORMATION SYSTEM APPLICATION DESIGN

Background: Dental and oral health care services (Askesgilut) are planned care services within a certain period of time on an ongoing basis in the simple promotive, preventive, and curative fields to improve the degree of optimal dental and oral health in individual groups, and the community. by a dental and oral therapist (TGM). The results of the initial survey from the medical record or puskesmas information system show that there is no electronic record/recording of Askesgilut services, it is necessary to design an electronic Askesgilut record that is integrated with the information system. This study aims to obtain the design of the Askesgilut TGM information system at the Puskesmas&#x0D; Method: The design of the information system in this study uses a prototyping system design approach, namely a modern engineering-based design approach which is an interactive process that involves close working relationships between designers and users. The working relationship between designers and users is carried out through the Focus Group Discussion (FGD) method as well as in-depth interviews to obtain information/opinions/suggestions/inputs needed in designing the Askesgilut Information System application that will be used by TGM in Bandung City. This research involves the IT team as the main researcher. &#x0D; Result: The results of making this application are the first step in developing the Askesgilut application in order to facilitate TGM in carrying out its main tasks.&#x0D; Conclusion: It is hoped that the design of the Askesgilut Information System will not only make it easier for TGM at the Puskesmas in carrying out their duties, but also can be used by the management at the puskesmas, which can then be directly connected to the Health Office to the Ministry of Health.
Virtuous Data Monetisation Cycle: A Hybrid Consensus Substrate Automotive Consortium Blockchain Solution

We propose a data monetization architecture based on the Substrate blockchain framework for leveraging automotive radar data. The architecture is designed to enable a virtuous economic cycle involving the Radar automotive data for the consortium members of Automotive enterprises, Vehicle owners, and Radar Equipment manufacturers. The data represented as Non-Fungible Token (NFT) is sourced from the vehicle owners by the Radar component manufacturers and enhanced upon them. It is offered as a token road signature service (NFT) back to the vehicle owners completing the virtuous economic loop. All the participant interactions are monetized and incentivized by dynamic pricing and commission sharing. Data interactions are certified for integrity, and reviews for each NFT are maintained in the blockchain. Architecture respects the fairness, privacy concerns, as well as fidelity aspects. Architecture is implemented in the Substrate Blockchain framework and tested for hybrid consensus scalability of Proof of Authority algorithms. The algorithms evaluated are Aura and BABE, along with GRANDPA for block authoring and finalization, respectively, in a cloud-based implementation that suits the enterprise consortium networks.
Innovative Teaching Via Sustainable Vocational Education with an Improved Ant Colony Algorithm

Although students’ test scores provide an important reference for teaching and learning, research scholars still need to objectively analyze the scores. Under the current situation where English performance of vocational education students does not achieve satisfactory results, this research uses a clustering algorithm to improve on the ant colony optimization algorithm. This ant colony clustering analysis algorithm is improved by incorporating two optimization strategies, and the test scores of vocational education students are introduced as the original data for cluster analysis. The optimal number of ant colonies is nine, when the three error values of the two ant colony algorithms are minimized. The convergence values of the three ant colony algorithms are smallest when there are 200 training cycles or when the training batch size is 1000, resulting in upgraded ant colony clustering algorithm convergence values of 0.498 and 1.523, respectively. The performance of the student evaluation model combined with the ant colony clustering optimization algorithm improved, followed by CF, FOA, and BP. KNN had the worst performance. Data mining on student performance can be done via research that can provide specialized advice on students
STUDENTS' STRATEGIC EFFORTS RELATED TO MANDARIN LANGUAGE PRACTICING DURING INDUSTRIAL TRAINING

This study intends to investigate the Chinese language usage and communication requirements of Industrial Trainees, the difficulties they encountered, and the applicability of Diploma in Mandarin courses at PT Formosa Bag Indonesia to these requirements. The interviewees consist of 16 Mandarin diploma students in their last year who had recently finished their three months of industrial training at various companies make up the sample. The data was gathered use semi-structured interviews. The findings of the study demonstrated that Mandarin was not commonly used in companies and that all four linguistic skills were required to carry out a variety of tasks at work. The majority of trainees found it difficult to conduct briefings, respond to client concerns and complaints, negotiate a deal with clients face-to-face, deliver oral presentations, connect with other firms, set up the filing system, make flyers, brochures, posters, and advertisements, as well as prepare accounts. As a result, it is advised that the fundamental courses, particularly those pertaining to public speaking and interpersonal communication skills, prior to the students' internships being taught. The study's conclusions have some pedagogical repercussions. These data can be used to revise the curriculum for similar courses offered by higher education institutions. Program that complies with the current needs of the workforce and of education. Additionally, lecturers can reconsider how individual courses should be taught to accommodate students' requirements and let them engage in meaningful exploration learning through practical experience.
Secure Arcade: A Gamified Defense Against Cyber Attacks

In modernity, we continually receive increasingly intricate technologies that allow us to increase our lives’ convenience and efficiency. Our technology, particularly technology available over the internet, is advancing at unprecedented speed. However, this speed of advancement allows those behind malicious attacks to have an increasingly easier time taking advantage of those who know little about computer security. Unfortunately, education in the computer security field is generally limited only to tertiary education. This research addresses this problem through a gamified web-based application that drives users to reach learning goals to help them become more vigilant internet users: 1. Learn and memorize general computer security terminology, 2. Become familiar with basic cryptography concepts, 3. Learn to recognize potential phishing scams via email quickly, and 4. Learn common attacks on servers and how to deal with them.
Challenges and principled responses to privacy protection from biometric technology in China

Biometric technology has transformed human biological characteristics into a new form of privacy, and the misuse of this technology poses challenges to protecting this new privacy. This article initially defines biometric technology and biometric characteristics, further demonstrating why biometric characteristics belong to personal privacy and how biometric technology poses challenges to its protection. Through analysis, this article argues that the essence of these challenges is the conflicts between the ethical principle of privacy protection and the ethical principle of maximizing social benefits. In order to address these challenges, it is necessary first to weigh the fundamental ethical principles. The two basic principles of privacy protection and maximizing social benefits are not mutual antagonism but hierarchy, and this hierarchy should be based on the principle of practical feasibility. That is, applying biometric technology should first meet the principle of practical feasibility and, on this premise, realize the principle of maximizing social benefits based on not infringing on the principle of privacy protection.
P65-1 Development of genome data repository system for big data utilization and secure storage

Recent advances in sequence technology and molecular biology have dramatically increased the amount of data that can be analyzed computationally in cancer genome analysis. However, it isn't easy to properly manage and store such big data and analyze and interpret the results promptly on a local computer. A shift to a systematic IT infrastructure is necessary for clinical research.
A STUDY ON THE CHARACTERISTICS OF INDIVIDUALIZED ENGLISH LEARNING IN HIGHER VOCATIONAL COLLEGES

With the diversity of intake, the level of students tends to differ more. With the development of information technology, traditional teaching methods can no longer meet the requirements of learning. Promoting personalised learning is the direction of future teaching reform. This study investigated and analyzed the characteristics of individualized English learning. The results show that higher vocational students already have obvious characteristics of personalised learning, and the difference of student foundation will have a certain impact on the learning characteristics. It is imperative to implement the reform of personalised learning in higher vocational teaching in the future. This research can provide useful reference for higher vocational education reform and help relevant teaching workers to design more reasonable personalised learning programs.
Recommendation Engine on IPTV

In recent years IPTV (Internet Protocol Television) platforms are becoming one of the most popular entertainment multimedia services which are used to serve movies, tv-series and other video and audio attractive content using the Internet Protocol. VoD (Video on Demand) is the most popular multimedia IPTV service, which provides content without the need for the old traditional way of using video playback devices. Except that it is necessary to have high-quality VoD content, IPTV platforms must provide the best end-user experience. Moreover, it is imperative to provide new features to attract new customers and keep the existing ones. We confirmed the efficacy of this classifier thru simple trial and error. When we searched for movies that have sequels, our engine recommended those sequels. Since Cosine Similarity Classifier considers multiple factors, such as actor, genre, year, etc. Even if the movie does not have prequels or sequels this algorithm was able to provide us with movies that share other common characteristics.
“Fox Fables” an Adventure based 2D Game in Unity Game Engine

Abstract: This research paper explores "Fox Fables," a 2D adventure game developed with the Unity game engine, emphasizing dynamic storytelling and AI-driven gameplay. Players assume the role of Felix, a clever fox navigating an intricately designed world with unique characters and narratives. The Unity engine serves as the project's backbone, enabling the creation of visually stunning environments, 2D characters, and seamless gameplay mechanics. NPC characters, including Grunt Eagles, Frogs, and the formidable Gorilla, are brought to life through specific AI algorithms, such as pathfinding, Finite State Machines, and Behaviour Trees. A standout feature is the dynamic narrative system, adapting to player choices and influencing character alliances. Sparrow, Turtle, and Cat, as static NPCs, offer guidance, items, and in-game purchases. Player choices shape alliances, conflicts, and distinct outcomes in the climactic Dark Theme, where Felix faces the Gorilla in a final battle. Unity's user-friendliness and scalability contributed to an immersive and engaging gaming experience. AI algorithms effectively create realistic NPC behaviours, enriching gameplay. The dynamic narrative system enhances player engagement, providing unique storylines. In conclusion, "Fox Fables" exemplifies the fusion of narrative-driven gameplay and AI-driven character interactions. It underscores the potential of the Unity game engine and dynamic storytelling in modern game development, contributing insights to the broader field.
Comparative Study of Noise Reduction in MRI Images Using Filtering and Wavelet Transform in Medical Image Processing

Comparative Study of Noise Reduction in MRI Images Using Filtering and Wavelet Transform in Medical Image Processing
Does Blockchain and Internet of Things (BCoT) Help in Managing Customer Data?

The internet of things (IoT) is transforming the established sector into a smart sector with “data-driven decision making.” IoT's inherent characteristics, however, provide a variety of difficulties, including decentralization, weak interoperability, privacy concerns, and security flaws. Blockchain technology offers possibilities for overcoming IoT issues. In the realm of the internet of things, the introduction of blockchain has recently sparked a lot of attention. The existing blockchain system, however, has a number of non-trivial issues that prohibit it from serving as a general foundation for extensive IoT services and applications. This study provides a comprehensive analysis of BCoT and explores the lessons learned from this novel paradigm. In particular, the authors first briefly describe the IoT and its difficulties. Then, they provide an introduction to blockchain technology. Next, they focused on describing the IoT and blockchain convergence and outlining the BCoT architecture proposal. They talk about BCoT's industrial uses and the problems of adopting “blockchain for 5G beyond IoT.”
USABILITY EVALUATION THROUGH EYE TRACKING: A SYSTEMATIC LITERATURE REVIEW

ABSTRACT: Usability evaluation is traditionally carried out with techniques such as: questionnaires, think-aloud, cognitive walkthroughs, and heuristics. The research works in this area are significant, they show advances such as improvements to different techniques, new technologies, frameworks, prototypes, and approaches to work on usability. Eye tracking is a data collection technique used in visual research (reading patterns, mental fatigue) and recently in usability studies. In this research work, the result of the systematic review of the literature on the evaluation of the usability of software systems through eye-tracking techniques is presented. The review method allowed the identification of techniques, procedures, tools, and metrics used by researchers to evaluate usability. Similarly, the review allowed us to identify areas of opportunity to evaluate usability considering other usability metrics not yet explored.
Balanced Scorecard Model and Organization Performance in Rwanda

The purpose of this research was to examine the effect of the balanced scorecard model on organization performance in Rwanda, specifically focusing on a private institution of higher learning. The study assessed the impact of considering the financial perspective on the organization's performance, investigated the influence of the customer perspective on performance, explored the impact of the learning and growth perspective on performance, and determined the influence of internal process analysis on the organization's performance. Both descriptive and correlational research designs were used. The target population consisted of 150 employees, and 109 were selected randomly using basic random sampling methods. Inferential statistics, including correlation and regression analysis, were employed to determine the relationship between independent and dependent variables. Descriptive statistics, such as frequency, percentage, mean, and standard deviation, were used for variables and constructs. The results were presented in tables, and the research followed ethical guidelines throughout the study process. The correlation analysis revealed strong positive correlations between the financial perspective and organization performance (r = 0.770**, p = 0.000) and between the customer perspective and organization performance (r = 0.819**, p = 0.000). Learning and growth showed a moderate positive correlation (r = 0.617**, p = 0.000), and internal process analysis had a moderate positive correlation (r = 0.691**, p = 0.000). Since the p-values for all four variables were &lt;0.01, the correlations were statistically significant, leading to the rejection of the null hypotheses. The findings from the regression analysis indicated that the R Square value was 0.693, with the adjusted R Square at 0.680 when organization performance was regressed against independent variables. In conclusion, the study found that an organization's performance is positively impacted by the implementation of a balanced scorecard model. The study recommends that organizations, particularly those in the private higher education sector in Rwanda, should consider adopting and implementing the balanced scorecard model as a strategic management tool. Organizational management should adopt sustainable customer relationship strategies to improve their perception. The study also recommends continuous internal processes analysis such as customer complain analysis, timely customer feedback consideration and compliance to regulatory bodies to improve the decision-making processes. Keywords: Financial perspective, Customer perspective, Learning and growth perspective, Internal processes perspective and Performance
A COMPREHENSIVE ANALYSIS OF COASTAL AND MARINE TOURISM: EVALUATING THE IMPACT OF ACTIVITIES, INTENTIONS, AND REASON FOR VISITING ON VISITOR SATISFACTION: THE MODERATING INFLUENCE OF VISITOR TYPES

The major purpose of this study is to investigate the characteristics that contribute to visitor happiness, with an emphasis on Aqaba, Jordan's one-of-a-kind setting. Rather than selecting volunteers at random, the researchers took into account the entire community of Aqaba tourists. About 237 of the 500 surveys returned were usable for statistical purposes. In order to categorize the responses, a seven-point Likert scale was used. We use of Smart PLS 4 forms the basis of the analytical framework. There is strong statistical support for the findings of the study. Satisfaction (SA) is heavily influenced by the elements of Availability of Activities (AA), Intends to Participate (IP), and Reason for Visiting (RV). The T value for AA is 4.128 (p 0.001), which indicates statistical significance. IP also has a high T value (7.505, p 0.001), indicating a significant impact. The T value of 4.502 for RV (p 0.001) further demonstrates its statistically significant influence. Add the moderating variable TV to the research design to see how it affects the results. With a T-value of 1.971 (p = 0.049), we see that there is an interaction effect between (AA) and (SA), with (TV) serving as a moderator. The moderate influence of (IP) on (SA) results in a T value of 0.822 (p = 0.411), which is not statistically significant. However, the T value of 4.144 (p 0.001) demonstrates the significance of the interaction between RV and SA, indicating that TV has a moderating effect on the relationship between the two variables.