Reviewerly/exHarmony huggingface dataset:
Cross-Modality Person Re-Identification Based on Shared Feature Attention Aggregation Algorithm

Person re-identification in the visible-infrared spectrum (VI-ReID) is a challenging task due to significant difference of modalities, making it difficult to extract salient features across modalities. To solve this problem, in this paper, we propose a novel Cross-Modality Shared Feature Attention Aggregation algorithm (cm-SFAA) for VI-ReID. In the cm-SFAA approach, we first design a Random Channel Alternation Erasure Network to better learn robust features against occlusions and noise, as well as diverse feature representations under different channel combinations. This enhances the generalization ability of the model. Furthermore, a Local Feature Aggregation module is introduced in cm-SFAA, which utilizes an adaptive weighting mechanism to aggregate features from different levels and domains, thereby improving the performance of the model. Extensive experiments on two mainstream datasets SYSU-MMOI and RegDB show that cm-SFAA outperforms several baseline methods and acquires state-of-the-art performance. The source code of our proposed cm-SFAA is available at https://github.com/wdqlndVcm-SFAA.
Differentially Private Decentralized Weakly Convex Delay-Tolerance Optimization in Robust Phase Retrieval

This paper studies a particular facet of the Decentralized Robust Phase Retrieval (DRPR) problem under random time-delay interference. The problem setting encompasses a network of agents, each possessing exclusive access to a localized weakly convex (WC) objective function, and engaging in communication with their neighboring entities under delays. In addressing this intricate issue, we put forth a novel differential privacy distributed Weakly Convex Optimization (WCO) algorithm, termed as DP-DWDTA. We validate the convergence of the DP-DWDTA by employing diminishing step-sizes and assessing it through Moreau Envelope (ME) measurement. Furthermore, we establish the privacy of the DP-DWDTA by introducing differential privacy through the addition of Laplacian noise. Finally, the empirical results procured from an array of DRPR experiments featuring four distinct images subject to noise substantiate the efficiency of the DP-DWDTA. These findings reinforce DP-DWDTA's capabilities in adeptly addressing privacy preservation in DRPR circumstances under time delay interference.
A Simple Unknown-Instance-Aware Framework for Open-Set Object Detection

Open-set object detection aims to detect training set objects (known classes) and non-training set objects (unknown classes). The current frameworks rely on human-in-the-loop, i.e., humans provide training data of unknown classes, to be aware of unknown-instance. However, it is difficult to collect unknown-class images in the real world. In this work, we propose a simple unknown-instance-aware framework for open-set object detection, which can extend close-set detectors to open-set object detection. The proposed framework consists of a class-agnostic proposal module and a prompt-guided semantic module. The class-agnostic proposal module generates region proposals, which are used by the prompt-guided semantic module. The prompt-guided semantic module distinguishes unknown instances by the similarity score between embeddings and image features, which is based on the aligned image-text space of pre-trained vision-language models, e.g., CLIP. The experiments show the class-agnostic proposal module is better than the class-aware locator in localization performance, and the prompt-guided semantic module has better unknown-class recognition performance.
Digital Security in Youth: The Salvadoran Case

This manuscript provides a detailed account of the original findings from a research project on digital security in Salvadoran youth conducted in 2021 and published in 2022. This work falls within the action framework of the Media and Information Literacy Program "Alfabeta Media Lab," involving two Salvadoran universities. The research aims to understand the digital security practices and tools used by Salvadoran youth aged 16 to 24, identifying shortcomings that can inform future support and solutions. The methodology adopts a quantitative-qualitative approach, employing a questionnaire with a representative sample of 976 young individuals from both rural and urban areas across 13 of the 14 departments of the country, along with three focus groups consisting of 28 participants in total. The study's results underscore the importance of fostering digital security competencies within Media and Information Literacy to enhance critical thinking and responsible, active citizenship, promoting an ethical and contextually relevant approach to media products. Within this framework, digital security transcends mere technological instrumentality and becomes a practice with social consciousness.
Optimization Technique for Deep Learning Methodology on Power Side Channel Attacks

The first non-profiled side-channel attack (SCA) method using deep learning is Timon's Differential Deep Learning Analysis (DDLA). This method is effective in retrieving the secret key with the help of deep learning metrics. The Neural Network (NN) has to be trained numerous times since the proposed approach increases the learning cost with the key sizes, making it hard to assess the results from the intermediate stage. In this research, we provide three possible answers to the issues raised above, along with any challenges that could result from trying to solve these issues. We will start by offering an updated algorithm that has been modified to be able to keep track of the metrics during the intermediary stage. Next, we provide a parallel NN structure and training technique for a single network. This saves a lot of time by eliminating the need to repeatedly retrain the same model. The newly designed algorithm significantly sped up attacks when compared to the previous one. Thus, we propose employing shared layers to overcome memory challenges in parallel structure and improve performance. We evaluated our approaches by presenting non-profiled attacks on ASCAD dataset and a Chip Whisperer-Lite power usage dataset. Power utilisation was studied using both datasets. The shared layers strategy we created was up to 134 times more successful than the prior technique when used to the ASCAD database.
Hubungan Antara Motivasi Belajar Dengan Hasil Belajar Pada Pembelajaran Tematik Di Kelas V SDN Gugus III Kota Bengkulu

This study aims to determine the relationship between learning motivation and student learning outcomes in thematic learning in class V SD cluster III City of Bengkulu. This study uses a quantitative approach to the type of correlational. The population in Bengkulu City Elementary School III, namely SDN 17 Bengkulu City, 48 SDN Bengkulu City, Bengkulu City SDN 57, Bengkulu City SDN 03, and SDN 25, with a total of 189 students. Using sample selection guidelines according to Arikunto's opinion: if the subjects are less than 100 people should be taken altogether, if the subject is large or more than 100 people can be taken 10-15% or 20-25%, then the sample in this study was taken 25% randomly ( random) of the entire population. The sample in this study amounted to 47 students from all students in Elementary School III Bengkulu City. Research methods using questionnaire and documentation. All instruments meet the requirements as a measurement requirement, because they have been tested so that they meet the product moment T-test requirements with a significance level of 5%. The instrument used in this study was a questionnaire (questionnaire) of motivation and documentation of the repeat scores of 1 thematic learning theme for the fifth grade elementary school cluster III Bengkulu City. Data analysis techniques are used to find validity, reliability, and test the correlation coefficient.
THE ROLE OF LAW IN TRANSFORMING INDUSTRY 4.0: HOW DATA ANALYSTS ARE SHAPING THE LEGAL FUTURE

The advent of Industry 4.0 is bringing profound transformations to the legal sector, and the role of law is reinventing itself in response to these changes. Data analysts play a key role in this transformation, shaping the future of the legal field. Industry 4.0, characterized by the interconnection of machines and systems, generates a massive amount of data. Law, in turn, needs to deal with complex and vast information to meet legal demands. Here, data analysts come into play, applying data analysis, artificial intelligence, and machine learning techniques to optimize legal research, predict trends, and identify critical insights. This not only saves time but also increases the accuracy of legal analyses. Furthermore, regulatory compliance in the Industry 4.0 era is challenging. Data analysts help constantly monitor evolving regulations and ensure companies are compliant. They also play a crucial role in dispute resolution by offering forensic data analysis for court cases. In short, law in the era of Industry 4.0 is becoming highly dependent on data analytics and technology. Data analysts play a vital role, enabling lawyers to provide more effective, accurate and efficient legal services while shaping the future of the legal profession.
Hyperspectral image restoration based on color superpixel segmentation

Hyperspectral images (HSI) are often degraded by various types of noise during the acquisition process, such as Gaussian noise, impulse noise, dead lines and stripes, etc. Recently, there exists a growing attenrion on low-rank matrix/tensor-based methods for HSI data restoration, assuming that the overall data is low-rank. However, the assumption of overall low-rankness often proves inaccurate due to the spatially heterogeneous local similarity characteristics of HSI. Traditional cube-based methods involve dividing the HSI into fixed-size cubes. However, using fixed-size cubes does not provide flexible coverage of locally similar regions at varying scales. Inspired by superpixel segmentation, this paper proposes the Shrink Low-rank Super-tensor (SLRST) approach for HSI recovery. Instead of using fixed-size cubes, SLRST employs a size-adaptive super-tensor. The proposed approach is effectively solved using the Alternating Direction Method of Multipliers (ADMM). Numerical experiments on HSI data verify that the proposed method outperforms other competing methods.
INTERACTION IN AN EDUCATIONAL ENVIRONMENT WITH VIRTUAL AND AUGMENTED REALITY

The article is devoted to the problem and features of the use of virtual and augmented reality at general school. The integration of virtual reality (VR) and augmented reality (AR) in educational environment has opened up new possibilities for engaging and immersive learning experiences. This paper aims to explore the features of participants' interaction within an educational context using VR and AR technologies. To achieve the purpose of our study and also to clarify the problem of determining the features of interaction models of participants in the educational process of a general education institution using virtual and augmented reality we used the following methods: systematic and comparative analysis of pedagogical, psychological, philosophical and sociological works, methodological and specialized literature; analysis of the pedagogical experience of using virtual and augmented reality in general school; synthesis and generalization to formulate the main points of the study; interpretation of the research results. A research study was conducted in a general educational institution, where an educational project using virtual and augmented reality was developed and implemented. The purpose of the project was to investigate the issues surrounding the interaction among participants in the educational process when utilizing these technologies. The results of the questionnaire showed the following: the participants' interaction in the educational process with the use of VR needs improvement, methodological recommendations and research on the organization of this environment for various purposes, such as, for example, students' research of new educational material, performance of laboratory work, joint work of students on research, instructions for the teacher's activities in working with students in VR, etc.; the participants’ interaction in the educational process with the use of AR is best understood by teachers and students, they use both ready-made AR technologies and personally created ones. We concluded that the use of virtual and augmented reality technologies in the educational process provides a wealth of teaching and learning resources that can enhance the learning experience and free participants from limitations in time and space. However, the effective organization of interaction between participants in the educational process using VR and AR requires careful consideration of educational space and pedagogical and methodological recommendations.
PROVIDING DISTANCE EDUCATION DURING THE WAR: THE EXPERIENCE OF UKRAINE

The sphere of education is multidimensional, it forms economic, political, and cultural impacts on society. Interruption (or complete stoppage) of the educational process in emergency situations caused by natural disasters, epidemics, and man-made disasters, results in extremely negative social consequences for society. The most negative impact on education occurs in the context of the war, as students are deprived of opportunities to learn. Destroyed schools and forced displacement can result in students no longer being able to learn in their typical learning environments. Even for students who are not affected by flight and displacement, learning opportunities in war zones can be limited because of newly dangerous circumstances. In such cases, distance education can offer students the opportunity to use distance learning technologies even under extremely difficult and challenging conditions and, in this way, contribute to a stable learning environment for students in times of war. However, little is known about distance education, the conditions for ensuring the continuity of the learning process during wartime, and how educational systems can be prepared to provide distance learning opportunities in such adverse conditions. Therefore, we explore how Ukraine is using distance education during the Russian war against Ukraine, in particular, by introducing IT innovations in distance learning. We also analyze the impact of digital technologies and educational IT infrastructure on the viability of the educational process under unfavorable social conditions. In addition, by constructing an educational regression model, we investigate various factors that may have influenced students’ achievement before the war (e.g., the availability of computers for students and teachers, schools’ access to high-speed internet, etc.), and identify the relationships between these factors. Our findings provide the first insights into the social implications and how countries can prepare to create distance-learning opportunities for their students during wartime and highlight the relevance of IT infrastructure in this context.
GIOS ONLINE PLATFORM AS A TOOL FOR OVERCOMING LEARNING LOSSES IN MATHEMATICS

The COVID-19 pandemic worldwide has led to a shift from face-to-face to distance learning. The sudden change in the learning format and the unpreparedness of the education system led to learning losses of students. The most researched and documented learning losses are the ones in mathematics, reading, and science. In Ukraine, face-to-face learning has not fully resumed yet, as a full-scale war broke out after 2 years into the pandemic. Consequently, the problem of overcoming learning losses in mathematics is particularly acute, as the country's economy depends on it in the future. According to the research reviewed in this article, the use of information and communication technologies in the educational process helps to overcome learning losses. These technologies can be used to organize synchronous or asynchronous learning. The article examines the effectiveness of students' independent use of GIOS platform materials to overcome learning losses in mathematics. The results of the entrance and exit tests of students, along with a survey of students and their parents after 1.5 months of independent learning on the platform are described. It is concluded that the independent learning format without a teacher or tutor is not suitable for everyone. Nevertheless, one of the components of overcoming learning losses can be students' independent study of multimedia materials. It has been found that the older students are, the more effective this kind of learning is. Based on a survey of students, the characteristics of the GIOS platform that motivated students to learn and helped them to understand the material were identified. Among the characteristics are: the integrity of the course, elements of gamification, the availability of theoretical material in several forms (videos, schemes, examples of solved tasks), the ability to view it several times and return at any time, the availability of training tasks, tasks of different levels and formats (including non-standard ones), the ability to review the covered materials to analyze errors, the ability to improve results by solving similar tasks. It is noted that in order to help their students overcome learning losses, teachers should either develop mathematics materials independently or use ready-made materials.
Exploring the Reasons behind the Emergence of Internet Memes and Their Impact: A Case Study of the "泰裤辣" Phenomenon

The viral spread of the "泰裤辣" meme in China has turned it into a phenomenon in the online world. From a functionalist perspective, "泰裤辣" has become a means of emotional release, a tool for social interaction, and a material medium for social and cultural expression, leading to its popularity on the internet. As a meme with strong postmodernist characteristics, the complete journey of "泰裤辣" from its birth, deconstruction, construction, to reconstruction reflects a facet of the current online society. "泰裤辣" acts as a mirror, reflecting the interplay between the online and real-world societies, as well as the differences between self and the other.
Strategi Belajar dalam Motivasi Membaca Siswa

In Indonesia, there are still many people who read minimally. There are several factors that cause the lack of reading in Indonesia. The purpose of this research is to analyze the influence of reading interest on learning outcomes, analyze the influence of learning motivation on learning outcomes, and analyze the influence of reading interest and learning motivation on student learning outcomes. Reading activities among school students are still not optimal, students' reading enthusiasm is still very low. Teachers' awareness of students' reading motivation is also still low. This type of research uses qualitative, this research uses research analysis techniques and case studies in journals. It cannot be denied that low interest in reading is a problem that deserves attention. To overcome this problem, we must be able to do something simple by realizing that reading is very important, and we must also implement our reading culture.
Application Of Flipped Classroom Teaching Mode In Dance Teaching Of Secondary School

With the rapid development of modern information technology, dance education in secondary schools also needs to follow the development trend of the Times and carry out reform and innovation. Flipped classroom teaching mode is one of the popular new teaching modes, which makes up for the deficiencies of traditional teaching mode and promotes the improvement of teaching level and educational efficiency. Based on this, this paper mainly discusses the application of flipped classroom teaching mode in dance teaching of secondary school.
Library Culture Among Students of Bachelor in Public Service and Governance (BPSG)

This study explores Library Culture among students at BPSG of Padmakanya Multiple Campus. The study population comprises 80 students from the 2nd, 4th, 6th, and 7th semesters, with 55 samples selected using stratified random sampling. The questionnaire, structured according to predetermined objectives, serves as the primary research tool. Data collected are analyzed using MS Excel, and the findings are presented through tables, pie charts, and bar diagrams.&#x0D; The analysis indicates that the library is generally clean, tidy, and offers good accessibility and comfortable reading spaces. However, improvements are needed in these areas, along with addressing dissatisfaction in technology integration, book variety, and quality. From the students’ perspective, the library culture at BPSG is found to be unsatisfactory and poor. This is evident in their infrequent library visits, underutilization of available resources, and a lack of awareness regarding library facilities.&#x0D; Several recommendations are provided, emphasizing the necessity for serious consideration and effective measures. These suggestions aim to enhance the library’s physical environment, technological aspects, and book collection. Addressing these concerns will likely contribute to an improved library culture among BPSG students.
ÜNİVERSİTE ÖĞRENCİLERİNİN SÜRDÜRÜLEBİLİR DEPREM FARKINDALIK DÜZEYLERİNİN FARKLI DEĞİŞKENLER AÇISINDAN İNCELENMESİ

Earthquakes have a significant impact on social, economic, and educational aspects of life. The negative effects of earthquakes on education and training are well documented. It is crucial to be adequately prepared to minimize these effects. This study aims to investigate the earthquake awareness of university students from a sustainable perspective. The survey model, a quantitative research method, was employed in this study. The research study comprised of 200 male (36.10%) and 354 female (63.90%) students who voluntarily participated from a university in the Western Black Sea Region during the 2022-2023 academic year. The Sustainable Earthquake Awareness Scale results show an average of 3.23 (Undecided) for the first factor, Earthquake Structure Relationship, 2.32 (Disagree) for the second factor, Earthquake Preparation Application, and 2.27 (Disagree) for the third factor, Earthquake Preparedness. The overall mean of the scale was 2.61 (Undecided). The results indicate that university students are not adequately prepared for possible earthquakes. There is no significant difference in Sustainable Earthquake Awareness Levels between male and female university students in all sub-factors and the total scale. Furthermore, as the grade level of university students increases, their sustainable earthquake awareness also increases. Furthermore, there is a notable contrast in the earthquake awareness levels of students from the faculties of engineering, health, and theology, with engineering students exhibiting a higher level of awareness. The study found no statistically significant difference between the sustainable earthquake awareness levels of university students and the number of floors in the building where they reside, both in terms of sub-factors and the overall scale.