Reviewerly/exHarmony huggingface dataset:
Increasing awareness and empathy among university students through immersive exercises – testing of the virtual reality application: A pilot study

Background: This paper presents an overview of a pilot study focused on testing the effectiveness of immersive virtual reality (VR) exercises, within extended reality experiences, in increasing awareness and empathy among university students towards pregnant women, elderly people, people in wheelchairs, and people with some sort of sight impairment.The extended reality experience was designed to simulate various scenarios that reflect the experiences of people from diverse backgrounds, to promote a better understanding of different perspectives and social issues related to some of the challenges tackled by people whose limitations are many times overlooked.Material and Methods: A design-based research methodology was applied and qualitative and quantitative data were collected in samples of 20 students from 3 countries.Results: Overall, the results suggest that immersive VR applications can be an effective tool in increasing awareness and empathy among higher education students.The use of VR technology can create a sense of presence and immersion that allows students to experience situations that they may not have encountered otherwise.The results attained with the immersive experiences have provided evidence that these solutions can foster a greater understanding of different perspectives and promote empathy towards individuals from diverse backgrounds.Conclusions: Ongoing research correlated with the Mixed Reality on Universal Design's Secret Service (Mr. UD) project results is already expanding on these findings by testing the effectiveness of VR applications in different contexts and with larger and more diverse samples.Additionally, the research conducted has provided relevant evidence that suggests that VR applications and their inclusion in training programs may help promote behavior change and reduce prejudice and discrimination towards marginalized groups.Med Pr.
Physiotherapy Exercise Classification by Exploring Knowledge Distillation with Attention Modules

Automated AI-based physiotherapy assistive systems are gaining popularity owing to its practical necessity, particularly to the elderly people. The application of such an assistive system is highly reliant on the embedded AI model that needs to correctly classify exercise videos while being lightweight in order to be used for real-time purpose. In this paper, we take this issue into account, and present a deep learning framework for physiotherapy video classification task that preserves the competitively high accuracy while being lightweight as well. For this, we explore knowledge distillation techniques for model compression purpose. We use both the online and self-distillation techniques, and use Convolutional Long Short-Term Memory (ConvLSTM) & Long-Term Recurrent Convolutional Network (LRCN) as the networks. Moreover, we utilize different attention modules and explore different architectural combinations to further improve the classification performance. We conduct detailed experimentation by exploring different combination of distillation techniques and attention modules along with tweaking their hyperparameters as well. The best results found from our experiments are reported, and those combinations are recommended for further use while being utilized in relevant AI assistive systems.
Research on Human-computer Cooperation Accompanying Capability Based on Customer Service System

In recent years, the demographic dividend has gradually disappeared and the growth rate of the customer service's business development has slowed down. Enterprise is more focused on the improvement of service quality. However, at present, there are some common problems in the service process of agents, such as lack of solving ability, inconvenient use of tools, lack of human-computer cooperation and so on. This paper further improves the man-machine cooperation accompanying ability of intelligent tools by studying the accompanying technology of tools and interactive question and answer technology. Based on the interactive contents such as agent operation, voice and IM, the assistant tools are displayed in real time to improve the service quality of agents. At the same time, We intensive study the language features, semantic recognition of agent natural language input, to achieve intelligent matching of agent questions and answers, and timely recommend relevant questions to agents to improve agent search efficiency and customer service satisfaction.
Optimal Auction for Effective Energy Management in UAV-Assisted Vehicular Metaverse Synchronization Systems

In this article, we investigate an effective energy management scheme in a unmanned aerial vehicle (UAV)-assisted vehicular Metaverse synchronization system. UAVs purchase energy resources from an energy service provider (ESP) and collect data for a virtual service provider (VSP) to perform synchronization between physical objects and digital twins (DTs). The key issue is to motivate both ESP and UAVs to participate in the energy trading market. To doing so, we design an incentive mechanism that maximizes the revenue of the ESP while guaranteeing desired economic properties, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.</i> individual rationality (IR) and incentive compatibility (IC). In particular, we first consider a single energy unit market, where a deep learning (DL)-based auction scheme is developed to construct neural networks from the analytical results of Myerson auction. The proposed DL-based auction is guaranteed to fulfill the optimal auction. We then consider a general scenario in which ESP has multiple energy units available to UAVs. A novel DL-based auction with feed-forward neural networks (FNNs) is proposed to jointly optimize the energy unit allocation and payment rules. We provide numerical results to demonstrate the performance improvement of the DL-based auction schemes compared to the classical auctions in terms of revenue, IC and IR. In particular, for the single energy unit market, the proposed DL-based auction scheme significantly improves the revenue compared with the classical auction and more interestingly, is able to avoid prevent UAVs from submitting their false values.
Preface to the Special Issue on “Mathematical Methods for Computer Science”

In the last few decades, the relationship between mathematics and algorithms has become increasingly important and influential in computer science [...]
CP-ABE Unveiled: A Path to Fine-Tuned Cloud Data Security

Cloud computing has revolutionized data storage and processing, but it has also introduced significant challenges in ensuring data privacy and access control. In this research paper, we explore and understand the potential of Ciphertext Policy Attribute-Based Encryption (CP-ABE) as a cryptographic solution for enhancing cloud security through fine-grained access control. Our exploration begins with a comprehensive analysis of CP-ABE, including its architecture, components, and encryption/decryption processes. We delve into the security aspects of CP-ABE, evaluating its strengths, advantages, and vulnerabilities. We conduct a thorough performance evaluation, analyzing its computational overhead and comparingits efficiency with other encryption techniques commonly used in the cloud. Our findings indicate that CP-ABE offers fine-grained access control and data confidentiality, empowering data owners to enforce complex access policies. However, challenges related to attribute authority trust, key escrow, and policy complexity must be addressed to ensure its robustness in real-world deployments.Ciphertext Policy Attribute-Based Encryption (CP-ABE) introduces a hopeful method for dealing with the challenges related to controlling who can access information and keeping data private in cloud computing.Our research contributes valuable insights into CP-ABE's security, performance, and practical applications.
Identifikasi Perubahan Luasan Lahan di Wilayah Sub-DAS Cikeruh Menggunakan Citra Landsat 8 dengan Google Earth Engine (GEE)

Land cover information is the data neede in the management of watersheds. Identification to obtain land cover using a cloud-based spatial data processing platform Google Earth Engine (GEE). This study aims to identify changes in land area in the Cikeruh sub-watershed area by classifying them using a machine learning basis on GEE. Utilization of landsat imagery is applied in the operation of the Google Earth Engine (GEE) platform using landsat 8 imagery. The analysis method used is the interpretation of Support Vector Machine (SVM) imagery with the identified years since 2015 until 2020. This research still has deficiencies, especially in the validation of land cover classes and area mapped and analyzed.
SENTIMENT LABELING AND TEXT CLASSIFICATION MACHINE LEARNING FOR WHATSAPP GROUP

The use of WhatsApp Group (WAG) for communication is increasing nowadays. WAG communication data can be analyzed from various perspectives. However, this data is imported in the form of unstructured text files. The aim of this research is to explore the potential use of the SentiwordNet lexicon for labeling the positive, negative, or neutral sentiment of WAG data from "Alumni94" and training and testing it with machine learning text classification models. The training and testing were conducted on six models, namely Random Forest, Decision Tree, Logistic Regression, K-Nearest Neighbors (KNN), Linear Support Vector Machine (SVM), and Artificial Neural Network. The labeling results indicate that neutral sentiment is the majority with 7588 samples, followed by 324 negative and 1617 positive samples. Among all the models, Random Forest showed better precision and recall, i.e., 83% and 64%. On the other hand, Decision Tree had slightly lower precision and recall, i.e., 80% and 66%, but exhibited a better f-measure of 71%. The accuracy evaluation results of the Random Forest and Decision Tree models showed significant performance compared to others, achieving an accuracy of 89% in classifying new messages. This research demonstrates the potential use of the SentiwordNet lexicon and machine learning in sentiment analysis of WAG data using the Random Forest and Decision Tree models
Health Care 4.0: Challenges for the Elderly with IoT

5G technology provides a greater presence and ubiquitous use of artificial intelligence that transforms all daily routines and, consequently, people’s lives. With the increasing use of IoT in all environments, which include each one’s homes, it requires citizens to have digital skills to be able to enjoy all these potentialities. The problem will be for info-excluded citizens who do not have digital skills and, as such, will not be able to have a better quality of life and health. In this context, the elderly constitutes the most info-excluded range of citizens. In this sense, it is important to reflect and find measures and proposals so that the elderly can have a better quality of health and life with the use of emerging technologies and artificial intelligence that the IoT makes available.
Corrigendum: Design guidelines for limiting and eliminating virtual reality-induced symptoms and effects at work: a comprehensive, factor-oriented review

CORRECTION article Front. Psychol., 21 August 2023Sec. Media Psychology Volume 14 - 2023 | https://doi.org/10.3389/fpsyg.2023.1261103
In the Line of Fire: Risks of DPI-triggered Data Collection

Cybersecurity companies routinely rely on telemetry from inside customer networks to collect intelligence about new online threats. However, the mechanism by which such intelligence is gathered can itself create new security risks. In this paper, we explore one such subtle situation that arises from an intelligence gathering feature present in FireEye’s widely-deployed passive deep-packet inspection appliances. In particular, FireEye’s systems will report back to the company Web requests containing particular content strings of interest. Based on these reports, the company then schedules independent requests for the same content using distributed Internet proxies. By broadly scanning the Internet using a known trigger string we are able to reverse engineer how these measurements work. We show that these side-effects provide a means to empirically establish which networks and network links are protected by such appliances. Further, we also show how to influence the associatied proxies to issue requests to any URL.
USAGE OF BLOCKCHAIN IN INDIAN LAND REGISTRATION AND LAND RECORDING SYSTEM - A REVOLUTIONARY STEP

In present-day land recording and land registration systems of India can be professed as mistrustful, inefficient and outdated despite that India has completed 94.53% digitization of its land records. Due to loose coupling among different land related government departments and centralized data storage system, various types of forgery and lots of legal disputes are still there in the present system. For this reason real landowners are still suffering from numerous land related litigations and which creates confusion about the existing system's reliability and effectiveness. This causes judicial huge waste of time. The government needs to protect dwellers rights of records rendering a smart transparent web-application enabled e-Governance, supported by a competent substratum technology. Adoption of the Blockchain, the underlying technology of cryptocurrency, could be a most exclusive and assured way out to solve these issues related to land recording and land registration systems. Established systems could achieve a peer-to-peer, collaborative, trustworthy, secure, transparent, reliable, scalable and real-time based system. Blockchain technology assures users of inviolability and has no way to anticipate breach of contracts. The objective of the present study is to focus on how significant impacts we can observe through the implementation of a Blockchain based land registration and land recording system.
Determining the Basics of Strengthening Learning: How Students Overcome the Problem of New Testament Interpretation

This study aims to find the dominant reasons why students experience difficulties in conducting exegesis research in writing a thesis in determining the main points of strengthening learning for the New Testament Interpretation course of the Theological Department, Faculty of Theological Sciences Tarutung State Institute for Christian Studies in 2022. The primary data of this study was obtained from the answers to interview questions for 17 out of 20 student participants who this year are contracting a thesis course. The results of the analysis of the participants' answers showed that the dominant difficulty experienced by the participants was in the preparation of descriptions and analysis of apparatus text, which was at the level of 26%, which was at the level of 0-54% or at the level of difficulty 'unable to do'. Based on the answers of the participants, it was shown that they 'did not understand' in working on the preparation of descriptions and analysis of apparatus text as an answer to the problem of this study. Other reasons equivalent to this level are the difficulty of compiling: analysis of the sentence structure of the text, biblical context/theology (the sacred nature of the text), exegesis works with general patterns, text translation, comparative analysis of text translation, analysis of words, grammars and syntax of the text. The reasons for the difficulty of the second level at 55–64% namely 'not knowing enough or not understanding enough or confused' are in the area: compiling a literary analysis of the text, and establishing a sub-sub-focus of discussion. Based on the results of the data analysis, in addition to other factors, the research team concluded that the participants had limited understanding in working on the detailed instructions presented in the teaching materials of the New Testament Interpretation course. Based on the results of this analysis, recommendations were given: [1] in order to eliminate difficulties in conducting exegesis research in thesis writing, participants must understand and follow technical instructions and examples in working on each analysis of exegesis data on the texts of the New Testament Bible and [2] the teaching lecturers emphasized the two dominant levels of abstraction research difficulties in the learning process of the New Testament Interpretation course.
Development of Learning Design for English Courses Based on Learning Outcomes: Strategies of the Department of Christian Leadership in Achieving Graduate Science and Profession

This research aims to develop a learning design for English courses based on learning outcomes in the method and learning materials in the curriculum to support the scientific and professional achievements of graduates of the Christian Leadership Department. This research method is descriptive qualitative with a survey method of 3 lecturers and 12 students as respondents. The results showed that the results of the development of the learning design for the English course in the Christian Leadership Department curriculum obtained an average score of 4.1 ≥H≥3 in the high category and then converted into a percentage gain of 82% in the very good category. This study recommends improvement in students' writing skills which must be trained and continuously developed in writing prayers, reflections or short sermons in English.
Application of Personality Theory of Criminal Psychology to Nordic Noir: A Study

Crime fiction is a genre in literature that is mainly focused on crime, its detection, its solution, the criminal and his motives. Similar to the genre of crime fiction is the sub- genre within it called ‘Nordic Noir’ which is also known as ‘Scandinavian Noir’. It is a term given to the literature coming from the Nordic or Scandinavian countries like Iceland, Sweden, Norway, Denmark, Finland etc. It is mainly known for its dark and bleak settings, description of its landscape and strong female characters. There have been various approaches that have tried to understand criminal mind and behaviour. Relating crime fiction and criminal psychology and its various theories will yield new insight as psychology and literature share a very close bond. The Personality Theory argues that there are a number of personality traits which are associated with an act of crime or violent behaviour. Eysenck in his book Crime and Personality published in 1964 established a relationship between criminal behaviour and personality. According to him, personality traits play a key role in criminality. He was of the view that some genetic traits along with certain environmental forces lead to criminal behaviour or conduct. The three super factors about which Eysenck talks about and upon which the PEN model is based are psychoticism (P), extraversion (E) and neuroticism (N). This paper aims at the application of Personality Theory as given by Hans Eysenck to the new emerging sub-genre of Nordic noir. As the genre deals with crime and criminals, therefore it would be highly insightful to study it in the light of criminal psychology.
Reservoir computing with the electrochemical formation and reduction of gold oxide in aqueous solutions with a three-electrode electrochemical setup

Supervised classification of handwritten digits via physical reservoir computing (PRC) using electrochemistry with a three-electrode electrochemical setup was demonstrated.
On-yomi dan Kun-yomi pada Huruf Kanji

There are three important things in studying Kanji letters in Japanese. These are the way of writing, the way of reading, and the meaning. Of these three things the way of reading Kanji is quite difficult to study due to the way of reading kanji is still subdivided into three parts: onyomi and kunyomi (the way of reading on and kun) The way of reading on is the way of reading kanji which is taken from Chinese . whereas the way of reading kun is a way of reading originated from the Japanese itself. Generally, the way of reading on is the way of reading two letters or more which are combined into one and the result of this combination is a new word with the new meaning. The way of reading kun is not like that of on., however, it’s only a kanji that can stand alone which has its own meaning without combination The important things that we should study in reading on and kun in kanji letters are to know clearly the difference of the meaning of the new vocabulary either from the combined kanji or the kanji which is stand alone. It also helps us in translating a new vocabulary that arises when we are translating a sentence in a reading passage. We can also understand clearly how to use Kanji dictionary and to know the new vocabulary that arises from each sentence that we are translating. To know when the kanji letters is red in on way and when to read it in kun way, the following are the things that we need to study.
PEMANFAATAN PEMBELAJARAN LEARNING MANAGEMENT SYSTEM (LMS) DI SMK SYAFI’I AKROM PEKALONGAN

SMK Syafi'i Akrom Pekalongan is a vocational education institution that provides education with a national curriculum. During the COVID-19 pandemic, Syafi'i Akrom Vocational School played a role in implementing bold learning. However, there are teachers who have difficulty learning online. According to the Deputy Principal for the Curriculum field, he stated that there were teachers who had difficulty using the Learning Management System application for online learning. Based on the facts in the field, community service so that teachers get guidance in implementing the LMS application, namely Edmodo. Community service is carried out by teachers so they can understand the use of the Edmodo LMS. The purpose of the service is that teachers and students can use and utilize Learning Management System (LMS) learning with the Edmodo application at Syafi'i Akrom Pekalongan Vocational School. the method of service, namely by training carried out by teachers of SMK Syafi'i Akrom Pekalongan presenting 25 participants. The results of the study can be said that the guidance of the Syafi'i Akrom Vocational School teacher in using the LMS application helps carry out learning according to classroom learning. The results showed that 50% of teachers could use Edmodo in terms of sharing materials, assignments and student evaluations.
MENDONGENG UNTUK MENUMBUHKAN LITERASI MEMBACA SISWA SDN 1 MAGUAN

Storytelling activities for students of SDN 1 Maguan aim to foster student reading leteraticy. The methods used include 3 stages, namely preparation stage; implementation stage; and evaluation stage. Preparations include observations and interviews about students' reading literacy levels and programs that have been implemented by the school, planning activity formats, and budgets. The observation show that SDN 1 Maguan has never been carried out storytelling activities and students' reading literacy tends to be low when viewed from the frequency of visits to the library. The community service program is carried out with one storyteller who utilizes fairy tale aids in the form of hand puppets. The participants are students of Maguan 1 elementary school grade 1 to 4 which totals 84 students. The organizing committee for this activity is PGSD UNIRA students. This activity is well carried out and proven to increase students' interest in reading which will lead to reading literacy. The recommendation that can be submitted to the school is to design an advanced program to increase the learning experience of students in order to improve students' reading literacy that can make it easier for students to enrich their vocabulary. So that easier to achieve reading literacy.