Reviewerly/exHarmony huggingface dataset:
MAPPING LOCATIONS AND SHORTEST ROUTE OF TOURISM OBJECTS IN CENTRAL LOMBOK USING GIS-BASED A-STAR ALGORITHM

Central Lombok tourism is a tourism that foreign and domestic tourists often visit. There are many tourist objects offered by the Central Lombok Government, such as waterfall tours, beach tours, traditional village tours, cultural tours, and Pertamina Mandalika International Street Circuit. However, there are many tourist objects, and not all tourists know the location of these tourist objects. Tourists often experience constraints, are the location of tourist objects that is not quite right, it is still difficult to determine the shortest route to the location, and the lack of complete information about existing tourist objects, which can hinder the journey of tourists to the destination location. This study aims to map the location and shortest route of tourism objects in Central Lombok using an Android-based Geographic Information System by applying the A-Star algorithm. The results of this study are to develop an Android-based Geographic Information System or GIS by applying the star algorithm to Central Lombok tourism objects. So that the mapping of the location and information of tourist objects and obtain the search for the shortest route to tourist objects. The A-Star algorithm uses heuristic principles to find the shortest route to a tourism object and is optimal in finding the shortest route to tourism objects
Progress in Upcycled &amp; Sustainable Robotics: Developing an Accessible, Flexible, and Environmentally Friendly Robotics Platform

The development of a sustainable, environmentally aware and accessible robotic platform to be used in multiple applications is detailed. The robot utilizes upcycled components and serves as an economical and environmentally friendly robotic platform whose sensor loadout can easily be tailored for mission specific needs. The robot could serve as an intelligent system that might be applied to education, safety, environmental remediation, stewardship, physical impairment services, or in active sanitation applications. Some student projects using the platform are also discussed.
Diagnosis of the incorporation of telehealth resources in Primary Health Care in Brazil

The diagnosis of the national telehealth project, drawn up based on normative legal frameworks, the process of incorporating ICT in PHC and development of the national project, shows a continuous increase in the ICT infrastructure in PHC in Brazil and a decrease in the scope of telehealth activities in the country, despite continued investments.
Designing Long GPS Memory Codes Using the Cross Entropy Method

Beginning launches in 2026, the GPS IIIF satellite series will be the first GPS satellites to have a fully reprogrammable signal payload. This upcoming signal capability allows for the GPS signal to be modified and uploaded to satellites in orbit, providing new opportunities to re-explore the design of the GPS signal structure. Currently, all GPS signals use algorithmically generable codes (including Gold codes, short-cycled m-sequences, and Weil codes), which are binary sequences that can be generated from a smaller number of bits via an algorithmic procedure. However, there are several advantages to exploring the space of memory codes, which cannot be algorithmically generated, but must be defined and stored in memory as complete sequences. These advantages include increased flexibility in the choice of the code length and user-defined objective, as well as the ability to tailor the design to a particular code family size for improved overall performance. In this work, we explore memory code design using a novel, computationally efficient strategy called the cross-entropy method (CEM). This approach models a probabilistic search distribution over the exponentially large and discrete binary code design space, from which it samples candidate code families, and then improves its search distribution representation by finding a maximum likelihood distribution. The CEM can be applied to any user-defined code objective function, without requiring any functional properties (e.g. convexity, differentiability). We demonstrate the ability to design low-correlation codes for family sizes of up to 50 codes and lengths of up to 10223 chips – the first work to explore navigation memory code design for these lengths, to the best of the authors’ knowledge. We further demonstrate the ability to design codes with lower mean-squared auto- and cross-correlations than well-chosen families of equal-length Gold and Weil codes.
Improving Question Intent Identification by Exploiting Its Synergy With User Age

At their heart, community Question-Answering (cQA) services are social networks that allow their members to prompt any kind of question expecting different answers produced by several community peers. Most of previous research on cQA has shown that questions can reflect two intents: learning information and starting a conversation. The purpose of this research is investigating the intrinsic relationship between models predicting question intent and user age. And if this relatedness can assist in overcoming one of the chief obstacles when constructing effective question intent recognizers: the scarcity of annotated data. The method adopted in this work involves addressing question intent recognition in a Multi-Task (MT) learning setting, where asker age identification is used as its auxiliary task. In other words, we exploit their task synergy by integrating both training signals with the aim of boosting the classification rate of question intent. Since MT learning is regarded as fruitful when a target task is improved wrt. single-task models, in our experiments, we compare four frontier frameworks with several state-of-the-art single-task neural network classifiers. In brief, our results show that a MT implementation of T5 yielded an increase of at least 10% over the best single-task models, when trained on full questions. Our experimental results also unveil that extra substantial improvements can be obtained by adjusting its parameters. All in all, we conclude that both variables are inherently related. Last but not least, we also make available a new question set labelled with the age of their askers and their intents with the hope of encouraging the research of MT learning into cQA tasks.
Physics-based simulations for assessing the playability of heritage musical instruments: Impact of the soundboard assembly process on its low frequency behavior

Curators of heritage musical instruments are faced with a number of recurring questions concerning the objects in their collection. Can the instrument be played without damaging it? How might it best be restored? Can we understand how and why the instrument evolved in the way it did and the impact of the different steps in its construction? Indeed, the impact of the different steps in the assembly of a musical instrument must be anticipated in order to assess its playability. Curators may question whether the state of internal stress, deliberately introduced by the instrument maker during the assembly process, should be restored after it has relaxed over time. These questions are typically answered through expert judgment. Meanwhile, it may be possible to leverage detailed physics-based models to enrich the decision support in the museum environment. This novel strategy is illustrated in the present study to investigate the importance of the different steps in the assembly process in order to guide the restoration process. In particular, numerical and experimental studies that have been carried out on a facsimile of the soundboard of the Christoph Koch's archlute of 1654 (E.546) with the objective of quantifying the impact of its assembly and gluing processes on the low frequency vibratory behavior. It is shown that a nominal non validated numerical model is able to predict trends, validated via experimental studies, that can be useful in understanding the impact of the assembly process in order to guide future restorative measures.
KEMAMPUAN MEMBACA KRITIS TERHADAP KETERAMPILAN MENULIS KARYA ILMIAH

This research aims to determine students' critical reading skills, how they can write scientific papers, and how critical reading relates to students' ability to write scientific papers in class XI at SMK Negeri 6 Padang. Because these two skills are fundamental to master, this quantitative research uses a correlation approach. The population of this research is students in class XI at SMK Negeri 6 Padang who are registered in 2023/2024. The sample in this research was class XI students, totaling 31 people. The data collection technique uses a questionnaire and the data analysis carried out is correlation analysis between variables. The results of this research are first, the reading habits of the class secondly, the scientific work writing skills of the class third, there is a significant relationship between reading skills and scientific writing skills of class XI students at SMK Negeri 6 Padang. Based on these conclusions, teachers who teach Indonesian language subjects must be more innovative in improving students' reading and writing skills at SMK Negeri 6 Padang
Predicting Player Engagement in Tom Clancy's The Division 2: A Multimodal Approach via Pixels and Gamepad Actions

This paper introduces a large scale multimodal corpus collected for the purpose of analysing and predicting player engagement in commercial-standard games. The corpus is solicited from 25 players of the action role-playing game Tom Clancy’s The Division 2, who annotated their level of engagement using a time-continuous annotation tool. The cleaned and processed corpus presented in this paper consists of nearly 20 hours of annotated gameplay videos accompanied by logged gamepad actions. We report preliminary results on predicting long-term player engagement based on in-game footage and game controller actions using Convolutional Neural Network architectures. Results obtained suggest we can predict the player engagement with up to accuracy on average ( at best) when we fuse information from the game footage and the player’s controller input. Our findings validate the hypothesis that long-term (i.e. 1 hour of play) engagement can be predicted efficiently solely from pixels and gamepad actions.
Fourier Transform with Noisy Image

The noise is a major problem in computer vision because it affects image quality and impede the illation. In this paper, we suggest method works on instantaneous transformations that are used in the analysis of the signals representing the image and the frequencies they contain, through which the image can be retrieved or the areas containing the noise where the image is transformed within the complex range and then the original image. Result of this paper are 0.9804 in case SSIM measure and 32.9850 in case PSNR measure.
Multi-objective Optimization Design of the Structural Parameters of Swing Arm Crawler Rescue Robot

Aiming at the problem that the unreasonable structural parameters of swing arm crawler rescue robot directly lead to its poor obstacle crossing ability and low movement efficiency in complex search and rescue scenes, an optimization design method of robot structural parameters based on NSGA-II was proposed and verified. Firstly, based on the analysis of the motion mechanism of the robot, the model of robot motion performance and structural parameters is established. Then, NSGA-II multi-objective genetic algorithm based on non-dominated sorting was used to solve the model, and then the optimized structural design parameters of the robot prototype were determined. Finally, according to the optimization results, the 3D virtual prototype was designed for simulation. The results show that the maximum step climbing height of the robot is increased by 11.54 $$\%$$ , and the swing arm torque is reduced by 8.53 $$\%$$ , which verifies the effectiveness of the multi-objective optimization design method of structural parameters based on NSGA-II algorithm.
Path Planning of Mobile Robot Based on Improved A* Algorithm

This paper studies the path planning application of A* algorithm in substation inspection robot. The traditional A* algorithm has problems such as large memory consumption and slow computing speed when traversing too many redundant nodes in map path planning in a large environment. In this paper, an improved A* algorithm strategy is proposed to solve the above problems. On the premise of keeping the shortest path, the cost function of A* algorithm is adjusted, and the pruning strategy of Jump Point Search (JPS) algorithm is integrated, so as to shorten the search time, reduce the number of nodes and inflection points, and make the path smoother. The simulation results show that the new algorithm is better than the traditional A* algorithm in a larger search area, showing higher efficiency and path optimization performance. Finally, the effectiveness and practicability of the improved algorithm are verified on the experimental platform.
Topic Tracking from Classification Perspective: New Chinese Dataset and Novel Temporal Correlation Enhanced Model

Topic tracking focuses on linking novel events to existing topics and is critical for applications. In this work, a deep learning model called TDE is proposed to solve the topic-tracking problem. And the first industrial-level topic tracking dataset QBETTD with fine-grain score labeling is released. The TDE model topical correlations among events from semantic and temporal perspectives based on machine reading comprehension (MRC) structure, which captures the deep semantic meaning and inter-relationship of the events and topics. The empirical results show that the proposed method is suitable for the topic-tracking task, and the model can track a growing topic.
The Right to Cyberbully? A Gendered Analysis During COVID-19 in Malaysia

This paper explores the rhetoric of cyberbullying with a focus on Malaysian female influencers during the COVID-19 pandemic. The research objectives entailed identifying various critical rhetoric and attacks against female influencers on digital platforms, understanding diverse levels of cyberbullying experienced by influencers from different backgrounds, and analysing reasons behind online aggressive behaviours. The study's theoretical framework contributes to intersectionality theory by examining how the COVID-19 context shapes nuances in Female Cyber Victimisation. Methodologically, the research employs critical discourse analysis to study language in online comments and responses reflecting cyberbullying against Malaysian female influencers. The analysis covers social media platforms (YouTube, Instagram, Facebook, TikTok) and forums (Hardware Zone, Lowyat.net, Cari.com.my), focusing on cyberbullying content over two years. Three prominent Malaysian female influencers targeted by cyberbullying namely Cathryn Li, Veveonah and Ain Husniza were selected for their distinct demographics and contexts, showcasing varying cyberbullying rhetoric. Findings reveal male internet commenters' presumptions about female influencers are shaped by religion and modesty perceptions. Influencers challenging gender norms face escalated negativity. Cathryn Li, perceived as less modest and non-Muslim, faced extensive derogatory comments affecting her mental health. Ain Husniza faced mockery due to her Malay Muslim background, while Veveonah was targeted for political motives. Rooted in conservative gender roles, societal expectations contribute to targeting female influencers, resulting in ridicule and harassment. These cases underscore the intricate interplay of gender, cultural norms, and online harassment, highlighting the necessity for comprehensive interventions to combat cyberbullying and safeguard the well-being of female influencers. Keywords: COVID-19, cyberbullying, gender, influencers, female cyber victimization.
Implementation of Live Worksheets Assisted Interactive Student Worksheets Based on Discovery Learning

This study aims to ascertain the learning outcomes, effectiveness, and significant differences between printed worksheets on electrolytic cell material and interactive student worksheets based on discovery learning. This research is in a quasi-experimental design with a pretest-posttest control group design. The research instrument consisted of multiple-choice test questions with research subjects in classes XII MIPA 6 and XII MIPA 8 at Public High School 1 Kendari. Data analysis techniques consisted of descriptive analysis and inferential analysis. According to the investigation's findings, students who used interactive student worksheets based on discovery learning and supported by Live Worksheets with printed student worksheets experienced increased post-test learning outcomes. Still, the increase in the experimental class was higher than in the control class. As a result, Live Worksheets-assisted interactive student worksheets based on discovery learning on electrolytic cell material are helpful in education because they can enhance student learning outcomes.
Implications of generative artificial intelligence for the development of the media industry

As an important branch of artificial intelligence research, Generative Artificial Intelligence (GAI) mainly refers to artificial intelligence technology in which algorithms produce results under the given input data conditions. Generative artificial intelligence is one of the most active research directions in the field of artificial intelligence. Generative artificial intelligence has brought new technology innovation and content production mode. This paper discusses the new opportunities and challenges that generative artificial intelligence brings to the media industry from the aspects of technology realization, application status and application prospect. On this basis, it is proposed that the media industry should actively embrace and use generative artificial intelligence to promote its own intelligent transformation and achieve intelligent matching between information production mode and user needs.
Chances and Limitations of Immersive Augmented Reality for Game-based Learning in Museums

This article discusses opportunities and limitations of using immersive augmented reality (AR) with head-mounted displays for gaming and education in museums. We first report on a prototype application for HoloLens 2 that we developed and tested with 109 museum visitors in a recent project for an exhibition with large animal skeletons. The results show that the feedback from visitors was overall positive, while more steps are needed before it can be implemented in a museum routine. Based on the findings, we discuss hypotheses for the planned further development of the approaches towards game-based learning in the real environment of a natural history museum.
SwageXR: Designing Gamified AR Applications for Industrial Training

This paper presents a case study describing the design of SwageXR, an augmented reality (AR) application that gamifies a tubing assembly exercise. The aim of this paper is to contribute to the field of extended reality (XR) applications by providing a case study of a novel design process based on an existing framework by Gilardi et al. &#x0D; Design needs and requirements were gathered using a contextual design approach and qualitative research through interviews with training course instructors as well as a workshop involving them. The contextual design approach involved the PI taking part in the training course as one of the trainees to observe and build understanding of the taught practical content and the context in which the learning happened. This was followed by semi-structured interviews with 4 training instructors, with results indicating preferred course content to digitise, early concepts for gamification, and the storyline of the gamified content with respect to existing training. Using the data and experience gained from the contextual design approach and interviews, a paper prototype of the gamified AR application was developed, and feedback was obtained from the company technical director. The paper prototype and feedback were used as a basis for developing a 3D prototype in VR using ShapesXR. This led to a virtual reality (VR) workshop involving the technical director and training manager of the company where the 3D prototype was demonstrated and discussed. The workshop resulted in the flow of the overall application being refined including the storyline, gamification, training, and challenges. The design process aims to facilitate the development of a coded working prototype for SwageXR, with gamification elements such as score, time-based challenges and leaderboards. An initial experience playtest with course trainees will then be possible to gain insight on engagement levels and trainee attitudes about the initial game experience. &#x0D; The main outcome of this research is a design approach that tries to address the gap outlined by Krauß et al., the approach makes use of rehearsal techniques and virtual reality to provide context for AR application design.
Serious Game For Training To Escape From Disasters And Deal With Accidents

The purpose of this study is to consider training methods to increase the ability to respond to disasters and accidents, conduct experiments, and verify their effectiveness. Based on this method, we decided to develop a serious game. The serious game developed in this project focuses on learning how to respond to disasters and accidents. Players encounter disasters and accidents in their daily lives. Consequently, the protagonist is portrayed as having bad luck and experiencing various unfortunate events. To facilitate learning, a time limit is set, and the time limit is extended to encourage players to continue playing. Specifically, the game begins with a fortune teller informing the protagonist that they will face an unfortunate event, and if they do not successfully navigate it, they will die within a month. If the protagonist overcomes the event, they will receive a lucky item. Collecting ten lucky items will extend their life by one month. To motivate players, unique and numerous lucky items are provided to encourage continued play.To give players an incentive to play the game, we decided to provide unusual lucky items and numerous lucky items to encourage them to continue playing.To verify the effectiveness of this game, a control group experiment will be conducted at the end of the game development.