Reviewerly/exHarmony huggingface dataset:
Sample-Based Human Movement Detection for Interactive Videos Applied to Performing Arts

In the performing arts context, video analysis plays a significant role in analyzing the artists’ movement in educational and professional artistic environments. However, current research lacks user-centered systems for artists to directly engage with movement detection in their respective practice recordings. Our framework presents an annotation tool capable of automatically analyzing human poses of individual examples in real-time and presenting motion data in the form of simple reports. At the core of this system, augmenting multimedia content by manually adding different types of annotations to the intended video segment is possible. Therefore, we developed novel features that combine automatic intelligent movement analysis with manual annotation capabilities for a more rewarding and efficient user experience. We demonstrate how pose estimation techniques can be employed to set up customized sets of human poses that can be automatically identified in videos. In addition, this paper discusses the results obtained from two system evaluation phases, where we report our findings based on expert feedback.
The Effect of Teleporting Versus Room-Scale Walking for Interacting with Immersive Visualizations

The use of different locomotion techniques such as walking or teleportation affects the way people explore and build an understanding of complex data in immersive visualizations. We report results from a quantitative user study (14 participants) comparing the effect of room-scale real walking versus teleportation on information search and task performance in a word-cloud immersive visualization. Participants performed an ordering task and we measured performance, post-task recall, workload and flow. Results suggest that room-scale real walking favors interaction and short-term recall but could imply higher workload.
Towards an Automatic Easy-to-Read Adaptation of Morphological Features in Spanish Texts

The Easy-to-Read (E2R) Methodology was created to improve the daily life of people with cognitive disabilities. This methodology aims to present clear and easily understood documents. The E2R Methodology includes, among others, a set of guidelines related to the writing of texts. Some of these guidelines focus on morphological features that may cause difficulties in reading comprehension. Examples of those guidelines are: (a) to avoid the use of adverbs ending in -mente (-ly in English), and (b) to avoid the use of superlative forms. Both linguistic structures are quite long, which is also related to another E2R guideline (“The use of long words should be avoided”). Currently, E2R guidelines are applied manually to create easy-to-read text materials. To help in such a manual process, our research line is focused on applying the E2R Methodology in Spanish texts in a (semi)-automatic fashion. Specifically, in this paper we present (a) the inclusive design approach for the development of E2R adaptation methods for avoiding adverbs ending in -mente and superlative forms, (b) the initial methods for adapting those morphological features to an E2R version, and (c) a preliminary user-based evaluation of the implementation of those methods.
The Relationship between Social Activity and Emotional Well-Being by Age Group: The Moderating Effect of Technology Literacy

This study verified the moderating effect of technology literacy on the relationship between social activities and the emotional well-being of the middle-aged, young-old, and old-old groups. To this end, we conducted the ｢2019 Technology Adoption Study of Middle-aged&#x0D; and Older Koreans(TASK)｣. We collected data from 500 community-dwelling Koreans aged 55 years and older. After that, performed analysis&#x0D; of variance(ANOVA) and controlled regression analysis by dividing the age group into 247 middle-aged(55-64 years old), 140 young-old&#x0D; groups(65-74 years old), and 113 old-old groups(75 years or older). As a result, in the case of middle-aged and young-old groups, social&#x0D; activity and technology literacy had a significant effect on emotional well-being. The middle-aged found technology literacy to have a moderating&#x0D; effect. However, the case of the old-old group found that social activities did not have a statistical relationship with emotional well-being.&#x0D; Therefore, this study expanded the academic discussion by examining the effects of social activities on the emotional well-being of middle-aged,&#x0D; young-old, and old-old. In particular, the practical and policy implications of promoting a high level of emotional well-being by enhancing&#x0D; technology literacy for middle-aged people and maximizing the positive impact of social activities on emotional well-being were proposed.
Fair and Private Data Preprocessing through Microaggregation

Privacy protection for personal data and fairness in automated decisions are fundamental requirements for responsible Machine Learning. Both may be enforced through data preprocessing and share a common target: data should remain useful for a task, while becoming uninformative of the sensitive information. The intrinsic connection between privacy and fairness implies that modifications performed to guarantee one of these goals, may have an effect on the other, e.g., hiding a sensitive attribute from a classification algorithm might prevent a biased decision rule having such attribute as a criterion. This work resides at the intersection of algorithmic fairness and privacy. We show how the two goals are compatible, and may be simultaneously achieved, with a small loss in predictive performance. Our results are competitive with both state-of-the-art fairness correcting algorithms and hybrid privacy-fairness methods. Experiments were performed on three widely used benchmark datasets: Adult Income , COMPAS, and German Credit .
Improving Live Migration Efficiency in QEMU: A Paravirtualized Approach

Virtual Machines are the key technology in cloud computing. In order to upgrade, repair or service the physical machine where a Virtual Machine is hosted, a common practice is to live-migrate the Virtual Machine to a different server. This involves copying all the guest memory over the network, which may take a non-negligible amount of time. In this work, we propose a technique to speed up the migration time by reducing the amount of guest memory to be transferred with the help of the guest OS. In particular, during live-migration, a paravirtualized driver running in the guest kernel obtains, and sends to the Virtual Machine Monitor, the list of guest page frames that are currently unused. The VMM can then safely skip these pages during the copy. We have integrated this technique in the live-migration implementation of QEMU [3], and we show the effects of our work in some experiments comparing the results against QEMU default implementation and VirtIO-Balloon.
Rancang Bangun Sistem Informasi Apotek Manajemen dan Penjualan Obat Berbasis Web

This research aims to design and develop a web-based pharmacy information system to enhance efficiency and effectiveness of services in pharmacies. This web-based pharmacy information system has the potential to provide significant benefits in medication management, including accurate information about medications, improved inventory management, and enhanced patient care. The development method used in this research is the waterfall model, which includes stages such as requirements analysis, system design, coding, implementation, and testing. By using this method, the pharmacy information system was successfully designed and implemented, incorporating essential features such as medication data management, purchase and sales transactions, and reports that support efficient pharmacy management. The results of system testing show that the pharmacy information system functions well and meets expectations. This system facilitates users in managing medication data and transactions in the pharmacy. With this information system, pharmacy managers can operate their businesses more efficiently and provide better service to customers.
TRUHSH: Developing NTRU Cryptosystem in Terms of Security and Performance

The rapid advancement of technology, the creation of new communication channels, the globalization of some aspects of society, and the reliance on networks for the distribution of different types of data have all increased the risk of information leakage and unauthorized access, making it urgent to maintain information security. In this work, we presented the improvement of the NTRU system, which is still effective, by introducing a new system called TRUHSH based on a new algebra called hexat, in addition to a new mathematical construction of the encryption stages, while giving high security and efficient performance.
ANALISIS KECERDASAN SOSIAL SISWA DALAM PEMBELAJARAN IPA

This research is a qualitative research that aims to describe the social intelligence of the VB grade students at SD Negeri 2 Manurunge, Tanete Riattang District, Bone Regency. The research subjects were VB Grades homeroom teachers and 25 persons of VB Grade. Collecting data using interviews, observation and questionnaires. Data analysis techniques namely data reduction, data display, and drawing conclusions. The results and conclusions of the study were the social intelligence of VB Grade students at SD Negeri 2 Manurunge, Tanete Riattang District, Bone Regency, namely: being able to be a good listener, generally having a sense of empathy, and being able to position themselves as a student at school, students have focus and dare to appear in front of his friends to convey his ideas or ideas with confidence when carrying out the science learning process
Relative-Posture-Fixed Model Predictive Human-Following Control with Visibility Constraints in Obstacle Environments

The relative-posture-fixed human following is critical for the human-robot interaction and cooperation in daily scenes such as domestic service and healthcare. However, few of previous researches have discussed the difficulties faced by mobile robots in the real world, including the limitation of sensing range and hindrance from obstacles. For practicality, in this paper we investigate the relative-posture-fixed following control with collision avoidance and visibility constraints. The control task is formulated as a receding-horizon optimization problem and solved under the Nonlinear Model Predictive Control (NMPC) framework, while an Extended Kalman Filter (EKF) based human trajectory predict algorithm is integrated into the robot controller. The effectiveness of the proposed algorithm is verified in a simulation, and the results demonstrate a promising performance of our controller for the human-following task in complicated environments.
Camouflaged Object Detection with Feature Grafting and Distractor Aware

The task of Camouflaged Object Detection (COD) aims to accurately segment camouflaged objects that integrated into the environment, which is more challenging than ordinary detection as the texture between the target and background is visually indistinguishable. In this paper, we proposed a novel Feature Grafting and Distractor Aware network (FDNet) to handle the COD task. Specifically, we use CNN and Transformer to encode multi-scale images in parallel. In order to better explore the advantages of the two encoders, we design a cross-attention-based Feature Grafting Module to graft features extracted from Transformer branch into CNN branch, after which the features are aggregated in the Feature Fusion Module. A Distractor Aware Module is designed to explicitly model the two possible distractor in the COD task to refine the coarse camouflage map. We also proposed the largest artificial camouflaged object dataset which contains 2000 images with annotations, named ACOD2K. We conducted extensive experiments on four widely used benchmark datasets and the ACOD2K dataset. The results show that our method significantly outperforms other state-of-the-art methods. The code and the ACOD2K will be available at https://github.com/syxvision/FDNet.
Constrained Density Peak Clustering

Clustering is a commonly used tool for discovering knowledge in data mining. Density peak clustering (DPC) has recently gained attention for its ability to detect clusters with various shapes and noise, using just one parameter. DPC has shown advantages over other methods, such as DBSCAN and K-means, but it struggles with datasets that have both high and low-density clusters. To overcome this limitation, the paper introduces a new semi-supervised DPC method that improves clustering results with a small set of constraints expressed as must-link and cannot-link. The proposed method combines constraints and a k-nearest neighbor graph to filter out peaks and find the center for each cluster. Constraints are also used to support label assignment during the clustering procedure. The efficacy of this method is demonstrated through experiments on well-known data sets from UCI and benchmarked against contemporary semi-supervised clustering techniques.
Bidirectional Jump Point Search Path-Planning Algorithm Based on Electricity-Guided Navigation Behavior of Electric Eels and Map Preprocessing

The electric eel has an organ made up of hundreds of electrocytes, which is called the electric organ. This organ is used to sense and detect weak electric field signals. By sensing electric field signals, the electric eel can identify changes in their surroundings, detect potential prey or other electric eels, and use it for navigation and orientation. Path-finding algorithms are currently facing optimality challenges such as the shortest path, shortest time, and minimum memory overhead. In order to improve the search performance of a traditional A* algorithm, this paper proposes a bidirectional jump point search algorithm (BJPS+) based on the electricity-guided navigation behavior of electric eels and map preprocessing. Firstly, a heuristic strategy based on the electrically induced navigation behavior of electric eels is proposed to speed up the node search. Secondly, an improved jump point search strategy is proposed to reduce the complexity of jump point screening. Then, a new map preprocessing strategy is proposed to construct the relationship between map nodes. Finally, path planning is performed based on the processed map information. In addition, a rewiring strategy is proposed to reduce the number of path inflection points and path length. The simulation results show that the proposed BJPS+ algorithm can generate optimal paths quickly and with less search time when the map is known.
Designing AR Applications for People Living with Dementia

Given the extensive use of Augmented Reality (AR) for learning and training in different domains, this technology could support traditional therapies for people with dementia. However, to devise useful experiences, it is crucial to involve specialists and patients to fully understand the potential and limitations of ad-hoc AR applications considering the patients’ medical conditions as well as their expectations about the technology. In the context of a project aimed at improving healthcare service centers, following an action research approach, we codesigned two AR applications, tablet- and glass-based, to practice specific cognitive competencies (memory, recognition, and association) involving two specialists in psychiatry and two patients diagnosed with mild cognitive impairment. In an initial phase, we identified key issues about how the patients interact with the two devices and the interfaces in the doctors’ room that helped to improve the final prototypes. These prototypes were tested in a clinical study with ten patients diagnosed with mild cognitive impairment in the presence of their therapist.
Articulate Storyline-Based E-Module to Improve Social Studies Learning Outcomes for Class V Elementary School

The Problems at SDN Sukorejo 02 regarding the need for more utilization of technology-based teaching materials and learning outcomes are less than optimal in social studies learning. The formulation of the problem in this research is how to develop, validate and improve student learning outcomes after using e-module teaching materials based on Articulate Storyline materials on human interaction with the environment. This development research aims to develop instructional media and determine the feasibility and effectiveness of e-module media based on articulate storylines. This research was conducted using the research model R &amp; D (Research and Development) in Sugiono, which includes ten stages, namely: (1) potential and problems; (2) data collection; (3) product design; (4) design validation; (5) design revisions; (6) product testing (7) product version; (8) trial use; (9) product revisions; (10) produce products. The research objective was to determine the results of the development and effectiveness of the articulate storyline-based module. The results of this study indicate that e-module teaching materials based on articulate storylines are teaching materials that can be used in human-environment interaction material in Social Studies class V SD. E-module teaching materials based on articulate storylines were developed by looking at the feasibility assessment by material, media and language experts in very feasible criteria. The percentage of material eligibility is 95% with possible standards, the rate of media eligibility is 94% with very achievable criteria, and the portion of language eligibility is 93% with very feasible measures. They increased student learning outcomes by 16.9%. At the same time, the results of the n-gain test on the pretest-posttest obtained an average difference in learning outcomes of 0.4922 in the medium criteria. Thus, e-module teaching materials based on articulate storylines can be used as supporting teaching materials in learning to improve student learning outcomes. The following research is expected to produce more compatible media with each device and improve students' affective and psychomotor skills. Keywords: Social, Contextual learning, E-module, Articulate Storyline.
Quantifying the Usability of a Learner Data Management System: A Descriptive Analysis of Perceived Usefulness, Perceived Ease of Use, and Intention to Use

Lamlifew IP Integrated School, situated at Barangay Datal Tampal, Malungon, Sarangani Province, used Dess Application Program (DAP), an innovative application to address problems encountered among teachers in learners’ data management. This study aimed to measure the usability of DAP. The focus was on assessing perceived usefulness, perceived ease of use, and intention to use as key usability indicators based on the Technology Acceptance Model (TAM). The study had 127 respondents. Weighted mean () was used as the statistical tool. The findings of this study suggest that the DAP implemented at Lamlifew IP Integrated School was perceived as highly useful, easy to use, and strongly encouraged the intention to use among the respondents. It is recommended that Lamlifew IP Integrated School should continue to use DAP in learners’ data management, improve the school’s IT infrastructure, provide ongoing training and support for teachers and students, and allocate sufficient resources to maintain and upgrade the DAP.
VR content and its prosocial impact: predictors, moderators, and mediators of media effects. A systematic literature review

The main purpose of this paper is to explore the prosocial impact of virtual reality (VR) audiovisual content based on a systematic literature review of empirical research on immersive VR media's potential to elicit prosocial behaviors. The illusion of place, verisimilitude, and virtual corporeality are the main elements that underpin the creation of immersive experiences that can turn the user into an active subject of the narrative, engaging with the audiovisual content and feeling the emotions it elicits. A virtual reality system that can offer these three elements provides the means to transform not only the user's sensation of space and reality, but even the users themselves. The question this paper seeks to answer is whether audiovisual VR content can influence an individual's thoughts and feelings about otherness, thereby eliciting prosocial behaviors rooted in a sense of social justice, equality and fairness. To this end, it presents a systematic literature review in accordance with the guidelines of the PRISMA statement, applying a self-deductive coding system based on the Differential Susceptibility to Media Effects Model. The review identifies trends in research on the prosocial potential of VR content, among which perspective taking stands out as one of the most common strategies. In addition, predictors, moderators, mediators, effects, and their correlations are identified in the research reviewed.
ANALYSIS OF IAIN PAREPARE STUDENTS’ ACADEMIC WRITING LEVELS ON IELTS PREPARATION CLASS

This research is intended to describe the academic writing levels of 13 EFL students at IAIN Parepare and to consider what is the students’ perceptions are about IELTS academic writing levels after finishing the IELTS Preparation class. The researcher used qualitative descriptive method. The researcher collected the students’ worksheet and assessed based on IELTS writing band score descriptors that consists of four aspects writing assessment criteria: task achievement and response, coherence and cohesion, lexical resource, grammatical range and accuracy. To gain information about students’ perception, the researcher guided an interview.The result found that 2 students achieved 7 band scores (Good User Level) as the highest achiever. Then, 2 students achieved 5,5 band scores (Modest User Level) as the medium achievement, and only 1 student achieved 3 band score (Extremely Limited User level) as the lowest achiever. The researcher chose three selected texts were written by MA who represents the lowest level of achievement, NQA who represents medium level achievement, and SHB who represents the highest level of achievement. The results showed that the essays mostly had difficulty in grammatical range (accuracy) and lexical resources, both in task 1 and task 2. Furthermore, the students assumed that the IELTS academic writing level/task were difficult. The students’ difficulties appear in vocabulary and grammar. The students’ difficulties appear in vocabulary and grammar. Achieving expert user level was difficult because English was not their first language. Also, it was the first time for them to introduce the IELTS test.
Threat model of the testing subsystem for rare mobile device owners

Testing mobile applications for owners of rare mobile devices is a complex task because of the diversity of devices. The goal of this study is to create a threat model of the testing subsystem for owners of sparse mobile devices. The authors of the paper describe step by step the classes of users and the key components of the subsystem. The article defines the level of security and the dominant classes of subsystem vulnerabilities. The authors created an intruder model for the testing subsystem, defined the security class, and planned measures to protect the testing subsystem.
Conclusion

The approach presented in this paper is ascribed in the realm of AI that is based on separation of representation and use of knowledge in a given implementation with an emphasis on the modeling of context for real-world use. We consider a stricter separation of representation and use than in previous works on the web: On the one hand, knowledge is not “tailored” for entering the representation formalism, and in the other hand, the formalism does not focus on some (more or less hidden) restrictive goals for use of the knowledge.
From Context Modeling to Implementation for Group Activity

Our research was initially led for modeling context when the focus is addressed by a unique actor. This section presents the natural extension that includes the management of group members addressing the focus. From the point of view of modeling, implementation and use of context, the changes were an accommodation of the conceptual and operational aspects of context and of the CxG representation formalism.