Reviewerly/exHarmony huggingface dataset:
Overview of the annual international scientific conference on artificial intelligence “AI Global Dimension” 8-9 December 2022

The article provides an overview of the work of the sections of the annual international scientific conference AI Global Dimension on 8-9 December 2022, organized by the Centre for AI MGIMO. The event brought together representatives of science, business and government and contributed to the development of student research and business projects through the AI Showcase technology competition. During the conference experts discussed soft regulation in the field of artificial intelligence, new vectors of digital business development and technological innovations in the university educational process.
Digital twins in the information space as a reflection of a person

The article considers the phenomenon of the influence of information and communication technologies on human life and the growth of the scale of this influence in the modern era, characterized by the ubiquity of the Internet. The research proves that the growth in the number of Internet users, intensification of human immersion in the network, improvement of Internet technologies, have led to significant changes in social life. The development of electronic services and provision of roundthe-clock access to them have led to a significant increase in online sales of almost all types of everyday goods. In addition, the continuous improvement of electronic devices with a wide range of opportunities for users has led to a qualitative development of the infrastructure of interaction with the Internet. Under these conditions, the information space forms conditions and opportunities for the creation and preservation of digital doubles of a human, partially or fully reflecting his or her physical and personal characteristics. As technologies develop, these digital doubles can become more independent and closer to their originals not only in the information space, but also in the physical world. In this regard, the author notes the threats of such development and argues for the need to carefully analyze the possible consequences of the widespread use of digital doubles in order to ensure that their development is for the benefit of human beings.
Click-Through Rate Prediction Models based on Interest Modeling

Deep learning frameworks have achieved extraordinary results in popular technological frontiers, which also greatly inspires considerable researchers in recommender system. As one of the mainstream research frontiers, click-through rate (CTR) predictions have received increasing attention from both industrial and academic circles. Recently, Alibaba group has come up with novel idea of interest modeling that can effectively overcome the limitations brought by previous deep learning CTR prediction models, which is also the key to improve performance. For the past few years, more and more relevant works begin to explore approaches taking advantage of the learning, representation, and interpretation ability from neural networks. However, there are few comprehensive surveys targeted at this topic. In this paper, we systematically review and summarize recent CTR prediction models based on interest modeling. First, we elaborate their different design ideas and pay additional attention to their intrinsic relationship including improvements and extensions, similarities and differences, advantages and disadvantages and so on. Next, we deploy them separately according to official open-source code and compare their performance assessment in terms of accuracy and speed, looking for best optimizers and other hyperparameters. Furthermore, we briefly discuss some possible refinement directions and future research trends.
LFG: A Generative Network for Real-Time Recommendation

Recommender systems are essential information technologies today, and recommendation algorithms combined with deep learning have become a research hotspot in this field. The recommendation model known as LFM (Latent Factor Model), which captures latent features through matrix factorization and gradient descent to fit user preferences, has given rise to various recommendation algorithms that bring new improvements in recommendation accuracy. However, collaborative filtering recommendation models based on LFM lack flexibility and has shortcomings for real-time recommendations, as they need to redo the matrix factorization and retrain using gradient descent when new users arrive. In response to this, this paper innovatively proposes a Latent Factor Generator (LFG) network, and set the movie recommendation as research theme. The LFG dynamically generates user latent factors through deep neural networks without the need for re-factorization or retrain. Experimental results indicate that the LFG recommendation model outperforms traditional matrix factorization algorithms in recommendation accuracy, providing an effective solution to the challenges of real-time recommendations with LFM.
GERWkNN: GPU-accelerated Exact Random Walk-based kNN Query in Large Graphs

Finding the k-nearest-neighbor (k NN) of a query node in a large graph is a fundamental problem. Existing CPU-based local search for random walk methods can solve this problem but are not suitable for dense graphs. Recently, many k NN query algorithms have also been accelerated using GPU, but they are often designed typically for a specified proximity (similarity) measure and mostly return approximate results. To address these issues, in this paper, we propose a novel algorithm called GERW k NN. It explores only a portion of the graph to find the exact k NN and is generic across different proximity measures. We first develop a basic parallel algorithm that leverages GPU acceleration for proximity matrix computation. To further reduce the memory latency caused by data operation, we redesign the data structure and optimize set operation, fully harnessing the massive parallel processing power of the GPU. Extensive experiments on real datasets demonstrate the effectiveness of our approach. GERW k NN achieves over 5x speedup compared with single-threaded CPU-based FLoS, and reduces data operation time by more than 20%.
Comparison of methods for analyzing the correlation of user experience and information security

User experience (UX) is a quality requirement of software, but it can also negatively or positively influence the information security. It is not uncommon for users to misuse or even ignore information security mechanisms because the UX of the system is inadequate. Moreover, too complex information security mechanisms might also lead to a system not being used after development. The interaction of UX and information security should be designed in such a way that both individual aspects on the one hand and the overall effect on the other meet the requirements. In order to analyze the interaction of both aspects, suitable methods can be used. The methods can be used to assess the extent to which UX influences information security - vice versa. Subsequently, the software can be adapted so that UX and information security reach a sufficient level. In order to find such analysis methods, a systematic literature review was conduct out by 3 filter criteria. In the end, 189 publications remained, referencing a total of 22 different methods. These 22 methods were evaluated by 6 criteria and compared with each other. As a result, none of the identified methods can fully evaluate the correlation of UX, especially usability, and information security. Therefore, a new method should be developed that can potentially adapt some of the identified methods.
Mamamayan: A Mobile Community-based Emergency Reporting and Notification System for the City of Makati in the Philippines

Reliable public alert and warning systems are crucial for saving lives and protecting property during national, regional, and local disasters. Emergency notifications have become a significant concern for governments at both national and local levels. The Makati City Government aims to become the most livable city in the Philippines, emphasizing quality education, healthcare, and a clean environment. It is essential to prioritize disaster risk reduction and climate change adaptation, to achieve this goal of shared socioeconomic growth. This study focuses on designing and developing Mamamayan, an Android mobile community-based emergency reporting and notification system. Mamamayan is a mobile application that serves as a resilient emergency alert system, informing individuals about crises, accidents, or issues that require immediate attention from the local government. The project employed a feature-driven development (FDD) approach within the Agile methodology to bring the system to fruition. Various perspectives from different stakeholders were considered to promote social awareness, preparedness, and willingness to utilize the mobile app for reporting emergencies. The application paved the way for improved agency responses. It encouraged individuals to leverage IT solutions for resilience during emergencies, with 95% of respondents expressing their eagerness to report accidents or emergencies. Mamamayan can convey a wide range of emergencies, including fires, typhoon-related incidents, vehicular accidents with casualties, emergency health concerns, community-related incidents, and other situations that require an immediate and effective response from relevant authorities. The application utilizes the geolocation capabilities of smartphones to enable dispatchers to pinpoint the caller's exact location. A robust emergency alarm communication system like Mamamayan is crucial in a densely populated city like Makati. The proposed system was evaluated using IBM's Post-Study System Usability Questionnaire (PSSUQ) and the ISO 9126 standards, which resulted in high acceptance and perceived satisfaction among the evaluators. The PSSUQ usability test yielded an overall mean score of 1.50, indicating a high level of acceptance in terms of usefulness, information quality, interface quality, and overall satisfaction. The ISO/IEC 9126 software quality test also showed an overall mean score of 4.71, indicating that the system effectively captured respondents' perceptions of satisfaction. The evaluation considered various factors such as system performance, reliability, availability, efficiency, maintainability, and portability. It is recommended to observe a parallel implementation of the Mamamayan mobile app alongside the existing hotline phone call application.
Artificial Intelligence and Blockchain

The second chapter introduces the status and prospects of blockchain combined with AI in the field of healthcare. The core technologies of blockchain and the blockchain-based AI system framework are respectively presented. Then, the main applications in the intelligent sharing of eletronic medical records and traceability of drugs are listed.
Gestural Tendencies in Composing Pieces for Solo Clarinet in Sequenza IX for Clarinet, Garisan, and Klibat

Abstract: Gesture in a broader sense is more than a physical movement but, can also be modes of expression representing specific meanings. Movements with meaning embodies gesture and gesture exists in various artforms like music because of its capacity to express. Its capability to transform through time and space makes it akin to energy and it is parallel with the art of composing music. Musical gesture however, are being studied at different levels so as to classify and to relate different functions of gestures. This article intends to demonstrate the use of musical gestures into composing music for a solo wind instrument. Three solo pieces for clarinet were written by three different composers approaching musical composition through gestural writing. To realize the imagined sound and movements of the clarinet, the composers’ composing process concentrated more on the gestural movements and tone colours of the selected wind instrument. The musical gesture in these three solo pieces is actually capturing the movement and sense of movement through music, and its essence lies in the subconscious lines connected to create direction and motion in both pieces. This compositional approach also gives the composers more compositional freedom and enriches their compositional process.&#x0D; Keywords: music composition, musical gesture, solo pieces for clarinet, contemporary music.
The implementation of reciprocal teaching strategy in teaching critical reading

Low students’ interest in learning and reading English text influence to their critical reading ability. Teaching strategy is one of the solutions to solve the problem. An appropriate teaching strategy can influence to students’ interest in learning and reading English text. This study aims at describing the effect of reciprocal teaching strategy in teaching Critical and Evaluative Reading at second grade students of UIN Raden Mas Said Surakarta in the academic year of 2022/2023. Reciprocal teaching strategy consists of four activities, namely predicting, questioning, clarifying, and summarizing. The subjects are two classes of the second-grade students of English Education Study Program that consist of 60 students. The study used descriptive qualitative approach. Data were derived from observation and semi-structure interviews to the lecturer and students. The findings showed that the sequence activities of reciprocal teaching strategy encourage them to be more active and critical during teaching learning process. The activities that were done through working in group and sharing each other ideas help them overcome their difficulty during reading and facilitate them to be independent readers.
Quantum Communications ATP Systems: Challenges and Next Steps

We report on the current state of the art of quantum communications acquisition, tracking and pointing (ATP) systems. Challenges and next steps are explored.
Who Will Tell the Stories of Health Inequities? Platform Challenges (and Opportunities) in Local Civic Information Infrastructure

The decline in the number and quality of local news media has led to digital platforms becoming more central in circulating local information, affecting what information and issues are accessible to community residents. We demonstrate this by focusing on health disparities related to COVID-19, examining how both news and non-news civic organizations in six Great Lakes communities addressed pandemic-related racial inequities. Our analysis of interviews and a corpus of Facebook posts suggest that (1) very little discussion of health disparities emerged on Facebook from organizations in these communities, and (2) the majority of this content was produced by local news outlets. This article offers a vision of what local content might look like in the absence of robust local news outlets and highlights potential consequences of local civic information infrastructure with digital platforms playing a central role.
Development of K-Visual GKT Module for Improving Visualization Skill Based on The Art of Origami for Technical Drawing Subjects

Visualization skill is essential abbilites for every students who learn technical drawing, and mathematics in general. This skill could be improved through practical learning. K-Visual GKT designed to enhance students’ visualization skills through activities involving the art of origami and kirigami. This module, based on the Sidek Module Development Model, integrates origami and krigami to engage students in producing 3D paper folds independently. This paper will examine the validity and realibility of the module. This research conducted quantitatively and involves expert and students. The data collected will be analysis. The findings showed that the modules produced high validity values from experts (88%) and high reliability from all students (α=.846). The results affirm the effectiveness of the K-Visual GKT Module in enhancing students' visualization skills, providing a promising solution to address challenges in technical drawing education. Further examination of the module's potential impact on students' visualization skills is proposed, contributing to the ongoing efforts to improve visualization skills.
Retrospective analysis of the ideas of forming the ecological culture of life sciences university students

Ecological culture as a branch of science and a complex characteristic of an individual and his behavior in society has a complex genesis, the stages of its formation are clearly related to the development of human civilization from the stage of the birth of productive forces to the present. The ecological culture of a specialist's personality, especially one whose activity is related to the transformation of the environment, is a social order of modern society, aimed at solving the rules and conditions of effective and problem-free coexistence of dialectically contradictory unity in the «biosphere – humanity» system. The article raises the question of a retrospective analysis of the ideas of the formation of ecological culture: the prerequisites for the establishment of environmental protection activities in different periods of the development of human civilization are analyzed, the main historical periods are singled out and the trends of its development are characterized; the theory of the formation of the ecological culture of the individual is analyzed, which is based on the system of scientific knowledge, which, in turn, form the basis of pedagogy and are interconnected with such sciences as philosophy, ecology, cultural studies, sociology, psychology, each of which has its own unique epistemological position. The provisions and approaches of interdisciplinary integration of scientific findings regarding the personal phenomenon of ecological culture and its main aspects, which are based on the unity of ecological knowledge, value attitude to natural objects and demonstration of environmental protection behavior, are summarized.
Cultural approach to training future teachers of higher education institutions: theoretical and practical aspect

The article substantiates an adaptive interpretation of the cultural approach in the content of higher education as an orientation of the educational process towards the implementation of the leading provisions of cultural studies, the comprehension of which encourages the individual to realise the interconnection of personal, professional-subject, general professional, social, cultural and communicative, professional-methodical, managerial, organisational, methodological, psychological and pedagogical, cultural in the content of theoretical and practical support of the professional training of future teachers. It has been found that the professional training of future university teachers based on the implementation of the cultural approach enhances the formation of the following abilities: professional orientation of cultural knowledge; professionalism of cultural communication; professional cultural self-improvement. It is noted that the management of a culturally oriented environment in a higher education institution should be updated within the subjective, axiological and content, normative and regulatory, managerial and operational, and infrastructural segments of the educational process. In this regard, it is clarified that the functioning of a culturally oriented educational environment within the framework of the formation of professional competence of future university teachers involves the management of a dynamically open educational process of an innovative nature, which develops in accordance with public demands for the training of culturally competent specialists, is characterized by unity and integrity, combines the collective and individual cultural experience of the subjects of pedagogical interaction and ensures the purposeful formation of cultural competence. In accordance with the formulated theoretical foundations of the logical solution of the outlined problem, the article highlights the course of application of empirical research methods in the pedagogical environment of HEIs: questionnaires and expert evaluation. Their results confirm the partial effectiveness of established educational traditions in the current realities and the level of awareness, needs and motives of academic staff to initiate human-centred, civic, and national-patriotic content of educational content.
Enhancing Image Recommendations in Social Contexts using Hierarchical Attention

The paper introduces a novel approach to address the computational challenges faced by recommender systems operating on large-scale datasets, particularly in the context of social contextual image recommendation. Recognizing the need for a more efficient means of comparing numerous items to identify users' preferences, the proposed hierarchical consideration model delves into three crucial factors: transfer history, social impact, and owner adoration. These factors encapsulate nuanced aspects of user preferences, deriving from intricate relationships between users and images. To operationalize this, a hierarchical attention network is designed, explicitly reflecting the hierarchical nature of users' latent interests within the identified key aspects. Leveraging embeddings from state-of-the-art deep learning models tailored for different data types, the hierarchical attention network dynamically adjusts its focus on varying content levels. Extensive experimentation on real-world datasets underscores the model's superiority, with compelling results demonstrating its effectiveness and adaptability, particularly in contrast to existing approaches. The study culminates in highlighting the model's prowess in navigating diverse data landscapes, establishing its potential as an advanced solution for large-scale recommender systems.
Signature Verification using ResNet-50 Model

Signed documents are widely accepted as a means of confirming identification, which offers signature verification systems a major advantage over other kinds of technologies. There are two types of approaches to solving this issue using a signature verification system: online and offline. Offline signature verification uses less electronic administration and uses recorded signature images from a camera or scanner. An offline signature verification method uses extracted features from the scanned signature image. This study's primary contribution is the understanding of how deep learning network ResNet-50 can be applied to offline signature verification systems. This paper proposes the use of ResNet-50 for offline signature verification. One kind of pretrained model that enables us to extract higher representations for the image content is called ResNet-50. CNN trained the model using the raw pixel data from the image, then automatically extracted the features for improved categorization. ResNet-50's primary advantage over its predecessors is that it has the highest accuracy of all image prediction algorithms and can automatically identify essential characteristics without human supervision. The accuracy of the ResNet-50 model was 75.8%, indicating good performance.
Blockchain-Integrated Secure Framework for Enhanced E-Government Services

As the digital transformation of public services intensifies, e-government systems face significant challenges in identity verification and data security. This chapter proposes a blockchain-integrated identity system as a robust solution to these issues, thereby enhancing the efficiency and security of e-government services. By leveraging the decentralized, transparent, and immutable characteristics of blockchain technology, this system presents an innovative approach to identity management that reduces the risk of identity theft and fraud. The chapter explores the conceptual framework of the blockchain-integrated identity system, discusses its potential benefits and implementation challenges, and provides insights from real-world case studies. The findings underscore the considerable potential of blockchain technology in revolutionizing e-government services by offering more reliable, secure, and user-friendly identity verification processes.