Reviewerly/exHarmony huggingface dataset:
Classifying Game Reviews by Using Natural Language Processing and Support Vector Machines with SMOTE-Tomek Algorithm

Online reviews of games are an important reference for social media users to make purchasing or downloading decisions. Such kind of electronic word-of-mouth (eWOM) provides people with important information. Thus reviews can maintain a good image and profit for game companies. Marketing managers can benefit from monitoring online reviews to understand product benefits or problems. Consumers can also use online reviews to understand the true meaning of the content. However, when facing class imbalance problems, classifiers tend to have a very high accuracy on the majority class, but an unacceptable error on the minority class which often is more important than the majority class. Therefore, this study aims to build an effective classifier to identify positive (recommendations) or negative (real thoughts) reviews by using natural language processing (NLP) and support vector machine (SVM) from real game comments. This study also used SMOTE and SMOTE-Tomek algorithms to deal with class balance problems. The results show that SVM with SMOTE-Tomek has the highest accuracy (98.52%), and the performance of SVM model is better than DT model. The results of the study can be used as a recommendation for game companies or game players.
Time-series eye-tracking data analysis in blood sampling technology

Recently, eye tracking data has been studied in a variety of fields. Most of those studies utilize heat maps that visualize gazing points. However, since the meaning of gazing points may differ depending on temporal changes, it is important to develop a method to analyze gaze data in a time-series manners. Therefore, in this research, we analyze the data of line of sight in chronological order, the one’s range of movement for a certain period as feature value and propose the method classifying the geometric features.
A Platform for Searching Texts for Desired Expressions in a User-Editable Pattern Matching Environment for Language Learning

In this paper we propose a platform of pattern matching system that can extract required phrases or sentences in texts. Finding certain expressions in texts are often needed in language learning, e.g., examples of case markers between a predicate and its argument, or possible nouns in subject of a verb in a certain meaning. In previous studies, several types of systems, containing concordancers, are proposed. However, it is not easy to apply combined patterns because the pattern matching templates are previously fixed. Thus, we propose a flexible phrase searching system in which users can create search patterns by combining blocks of basic search templates. One of the characteristics the proposed system is that user can also specify where to be highlighted in texts with the blocks. To realize the function of combining patterns by users, the proposed system employs Prolog as the base of the data structure. The platform of the searching system is implemented on an Web server with JavaScript-based interface and database system. In the performance test, we show that the proposed system can deal with relatively large scale texts (10,000 sentences), and also demonstrate the combined patterns can be applied to the texts. In this paper we discuss the system architecture and the extendability of the pattern matching.
Smart Grid Integration for Sustainable City Energy Management: A Paradigm Shift in Power Distribution Networks

This study focuses on the investigation of collective intelligent systems in the context of energy management in modern distribution networks. The main objective of the research is to explore the potential of utilizing collective intelligent systems for achieving sustainable and efficient energy management in cities. The study describes the concept of collective intelligent systems and their role in distribution networks. The research findings emphasize the importance of employing such systems for achieving optimal resource allocation, enhancing energy consumption efficiency, and promoting sustainable urban development. A novel approach to smart energy management based on collective intelligent systems is discussed in the study. The results of the research demonstrate the advantages of this approach, including more accurate and efficient energy management, reduction of losses, and improvement of network stability. This work summarizes the significant research outcomes of collective intelligent systems in the context of energy management. It enhances understanding of the pos-sibilities and benefits of utilizing such systems in distribution networks and encourages further research for advancing energy management in cities.
A Case Study on Integrating Google Translate into College EFL Writing Instruction

This case study focused on integrating Google Translate (GT) and post-editing skills into English as a Foreign Language (EFL) writing instruction for Korean college students. Over a four-day writing class, twelve students completed four drafts, and the use of GT output, along with paraphrasing and error correction skills, was examined in detail. Surveys and interviews were utilized to gather student feedback. The findings revealed that initially, the students heavily relied on the output of GT. However, as they learned post-editing skills, they began independently changing expressions and correcting errors. In Draft 3, 54 out of 58 expressions were paraphrased, and 67 out of 80 errors were corrected based on the GT output. Yet, with the employment of post-editing skills in Draft 4, there was a noticeable decrease in reliance on the GT output, with students making more efforts to paraphrase and correct errors independently. They also expressed high satisfaction with the effectiveness of paraphrasing for writing. Nevertheless, they still faced challenges in grammar, vocabulary, and sentence structure, highlighting the need for teacher involvement in writing classrooms. The study concluded by addressing the implications, limitations, and providing suggestions for future research.
CONTROLLED VERSUS UNCONTROLLED VIRTUAL REALITY: PSYCHOPHYSICAL RESPONSE

Virtual reality gains popularity due to its wide range of applications, starting with entertainment and ending with a whole set of educational programs. It surely has its positive sides and drawbacks. The current study focuses on the evaluation of the psychophysical response to the ability to control and manipulate virtual reality. It also focuses on the impact virtual reality has on the ability to perform spatial modeling. The study’s sample includes 140 participants. The research has form of a classic experiment involving two experimental groups and one control group. While the second experimental group consisted of 40 respondents and could only observe virtual reality without being able to influence their actions in it, the first experimental group consisted of 44 participants who could control their actions in virtual reality (they could move, jump and choose places from which you could look at nature in virtual reality). The control group only passed the proposed tests measuring spatial modeling skills and was not involved in virtual reality. Psychophysical response was measured using a polygraph. The results show that being able to control VR makes the experience more immersive, increasing emotional response and stress, while not being able to control it causes less stress and engagement. The conclusion is that short virtual reality sessions have a positive effect on the ability to perform spatial modeling tasks
CONTRIBUTION OF MEDIA TECHNOLOGIES TO THE DEVELOPMENT OF STUDIES IN THE FIELD OF PHILOLOGY

Philology is a science that gets many contributions from various disciplines, including media technology. The purpose of this study is to uncover the contribution of media technology to the development of philological studies. Philological studies were carried out on ancient manuscripts containing handwritten texts, so they needed to be handled for their preservation. The existence of media technology is very helpful in efforts to preserve ancient manuscripts to be read and studied by current and future generations. This research uses a descriptive method by searching for data to be analyzed in accordance with phenomena that occur in society related to perceptions of philological science. The data recorded are in the form of social events that generally show a lack of attention to philology and manuscripts left by ancestors as cultural heritage. The results showed that there was still a low public understanding of philology. So to arouse attention to philology and manuscripts as cultural heritage, philology really needs other fields of science, especially media technology. Along with the development of technology, the ease of accessing various manuscripts can be done through the internet media. Nowadays, there are many websites that provide manuscript documents found in various museums and libraries. In that regard, media technology plays a very important role in the development of the field of philology through the transfer of media from various manuscripts to be read and studied by current and future generations. It proves that media technology contributed greatly to the development of studies in the field of philology
The importance of a positive worldview in shaping the orientation of students’ personality

The article offers consideration of a positive worldview, personal self-awareness as a semantic and behavioral model of development and formation of a healthy lifestyle for students
The impact of globalization on income inequality: the mediating effect of intellectual potential

Purpose. This research aims to revisit the relationship between globalization and income inequality while improving on previous research. It also considers how technological advancements and human capital can alter this relationship in countries with different income levels worldwide. Methodology. This research is based on panel data regression models with multiplicative terms where, after controlling for other important inequality factors, different types of globalization are regressed using two alternative measures of income inequality. Multiplicative terms allowed us to analyze the heterogeneity of the globalization-inequality nexus, i.e., how it changed over the distribution of the moderating factors: technological advancements and human capital. Findings. The results show that different types of globalization impact income inequality differently: trade globalization reduces income inequality in some cases, while financial globalization can increase it. Education proved to moderate the effect of globalization on reducing income inequality; technological advancement, on the other hand, stimulates the impact of globalization in terms of increasing income inequality. Originality. This paper differs from previous research by focusing on multiple aspects of globalization, using additional TOP20/BOT20 estimates to measure income inequality and to explore the differences between the income inequality/globalization relationship based on the effects of education and technological advancement on countries with different income levels.
Phonological Fossilization in the Prosess of Mandarin Native Speakers Learning Indonesian as a Second Language

Phonological fossilization, particularly in terms of pronunciation, presents a significant obstacle for second language learners in further advancing their language proficiency. Therefore, this study, grounded in the theory of interlanguage fossilization, aimed to investigate Mandarin native speakers learning Indonesian as a second language. By designing tests for the target group, collecting data on phonological fossilization, and analyzing the fossilized phonemes produced during the process of learning Indonesian, this research identified the underlying causes of phonological fossilization from both phonetic production and knowledge perspectives. Subsequently, corresponding strategies were proposed to overcome phonological fossilization, with the ultimate objective of improving the language skills of second language learners. This study contributes to the understanding of phonological fossilization in second language acquisition and offers practical insights for language instruction.
THE INFLUENCE OF AUGMENTED REALITY TECHNOLOGIES ON THE ORGANIZATION OF THE EXHIBITION SPACE OF WORKS OF SCULPTURE

The article examines the advantages of using modern technologies in the organization of the exhibition space of creative sculptures and the problems of art aesthetics, immersive, interactivity, theatricality, digitalization of exhibition spaces. With the help of Augmented Reality (AR) technologies, the sculpture becomes more informative and accessible to everyone. The purpose of the publication is to help readers better understand the impact of AR on the art of sculpture and to show the perspectives and possibilities they can open for this art field. The article reveals the current problem of attracting viewers and admirers of the art of sculpture highlights possible means of organizing exhibition spaces with the involvement of modern technologies for a more effective demonstration of sculptural projects. Research methods are historical, structural-functional and phenomenological. Exploring the impact of augmented reality (AR) technologies on the way we perceive sculpture and organize exhibition experiences, the new perspective looks at the contemporary art landscape where AR is becoming an integral part of artists and visitors alike. Thanks to AR technology, the sculpture turns into an interactive and emotionally rich artistic experience that combines traditional art with innovation and technological advances. The use of these technologies in sculpture opens up new opportunities for the expression of artists, and also gives great prospects for the development of art in the world. Conclusions. As a result of the study, questions and ideas about how AR technology affects the organization of exhibition spaces for works of sculpture and the benefits and challenges it brings to the art world are highlighted and characterized.
Learnable Local Similarity for Face Forgery Detection and Localization

The emergence of many face forgery technologies has led to the widespread of forgery faces on the Internet, causing a series of serious social impacts, thus face forgery detection technology has attracted increasing attention. While many face forgery detection algorithms have demonstrated impressive performance against known manipulation methods, their efficacy tends to diminish severely when applied to unknown forgeries. Previous research commonly viewed face forgery detection as a binary classification problem, disregarding the crucial distinction between real and forged faces, thereby limiting the generalizability of detection algorithms. To overcome this issue, this paper proposes a novel face forgery detection method that utilizes a trainable metric to learn local similarity between local features of facial images, achieving a more generalized detection result. What’s more, it incorporate cross-level features to accurately locate forgery regions. After conducting extensive experiments on FaceForensics++, Celeb-DF-v2, and DFD, which demonstrate that the effectiveness of the proposed method is comparable to state-of-the-art detection algorithms.
A Hybrid Double Encryption Approach for Enhanced Cloud Data Security in Post-Quantum Cryptography

Quantum computers and research on quantum computers are increasing due to the efficiency and speed required for critical applications. This scenario also kindles the vitality of data protection needed against threats from quantum computers. Research in post-quantum threats is very minimal so far, but it is much needed to protect the enormous data stored in the cloud for healthcare, governmental, or any crucial data. This research work presents an advanced hybrid double encryption approach for cloud data security based on Post-Quantum Cryptography (PQC) to ensure the restriction of unauthorized access. The suggested approach combines the benefits of the NTRU encryption and AES encryption algorithms and works in hybrid mode, offering strong security while resolving issues with real-time performance and cost-efficiency. A streamlined key management system is set together to improve real-time processing, significantly reducing encryption and decryption delay times. Moreover, NTRU Encrypt dynamic parameter selection, which adapts security parameters based on data sensitivity, maintains accurate information and security. In addition to addressing real-time performance and data security, an innovative development in this method is known as Quantum-Adaptive Stream Flow Encryption (QASFE), which enables secure data sharing and collaborative working within a quantum-resistant framework. This innovative feature enhances data accessibility while maintaining the highest level of security. In the era of post-quantum cryptography, our multifactor authentication technique, integrating double encryption and QASFE, is a proactive and flexible solution for securing cloud data, and protecting data security and privacy against emerging threats.
Artificial Intelligence for Confidential Information Sharing Based on Knowledge-Based System

Ensuring the security of sensitive data and protecting user privacy remains one of the most significant challenges in our contemporary landscape. Organizations Companies cannot adopt a new technology without reassurance regarding data confidentiality. To address these challenges, we present an innovative system that draws upon extensive knowledge and expertise in the field of cryptography, especially in encryption methods. This system tailors its strategies to align with specific scenarios, prioritizing data confidentiality. Our solution is based on one of the Artificial Intelligence techniques, which is Knowledge-Based Systems (KBS) and extends the intelligent encryption methods from our previous research. However, this new system has taken a novel approach by reconfiguring this within KBS architecture. We have introduced additional technical components, including knowledge bases, an inference engine, and the Nearest Neighbor (NN) search algorithm. As a result, this revised architecture not only enhances security and system performance but also showcases improved maintainability and scalability.
BLOCKCHAIN TECHNOLOGY ADOPTION IN DEVELOPING COUNTRIES AND ITS EFFECT ON THEIR ACHIEVEMENT OF SUSTAINABILITY GOALS

This paper provides a comprehensive literature review on the barriers and drivers of blockchain technology adoption in developing countries and how it affects their achievement of sustainability goals. This study adopts a systematic approach to identify and analyze relevant articles from various databases and journals. This paper also discusses how blockchain technology can contribute to the economic, social, and environmental dimensions of sustainability in developing countries by enhancing transparency, traceability, efficiency, and inclusiveness in various sectors such as agriculture, health, education, and finance. The paper concludes with some implications for research and practice and suggests some directions for future studies. Keywords: Blockchain Technology, Sustainable Development Goals, Developing Countries DOI： https://doi.org/10.35741/issn.0258-2724.58.6.20
AFPM: A Low-Cost and Universal Adversarial Defense for Speaker Recognition Systems

Speaker recognition systems (SRSs) are commonly used for biometric identification. However, these systems are vulnerable to adversarial attacks. Several defenses have been proposed but they require high costs in terms of additional data and computational resources to ensure robustness. To address these issues, this paper proposes a low-cost input reconstruction defense method called adaptive F-ratio-based partial masking (AFPM), which utilizes a robust feature extraction process to guarantee high defensibility. The underlying distribution of non-robust features is explored and filtered out by partial masking (PM), which helps maintain a low defense construction cost. An F-ratio-based PM (FPM) defense strategy is proposed by integrating the F-ratio, which reflects the weight of each frequency band for distinguishing between speakers, to balance classification accuracy and defensiveness. AFPM, which introduces an adaptive threshold calculation algorithm to FPM, is proposed to achieve further improved defensiveness and flexibility. Comparative experimental results show that AFPM is low-cost, highly defensive and universal. The construction process of AFPM does not involve training and its implementation does not require the protected SRSs to be retrained, only fine-tuned. While maintaining the classification accuracy at 99.42%, the average defense capability of AFPM against five white-box adaptive attacks is 90.89%, which is 9.23% better than that of the low-cost input reconstruction defense method and 3.77% better than that of the high-cost Parallel WaveGAN (PWG) defense approach. Against grey- and black-box adaptive attacks, FAKEBOB and Kenansville, AFPM reaches maximum defense effects of 96.01% and 74.49%, respectively, surpassing PWG by 4.5% and 65.82%. Furthermore, AFPM is universal and capable of protecting various SRSs against different attack strengths.
Many Non-Reed-Solomon Type MDS Codes From Arbitrary Genus Algebraic Curves

It is always interesting and important to construct non-Reed-Solomon type MDS codes in coding theory and finite geometries. In this paper, we prove that many non-Reed-Solomon type MDS codes from arbitrary genus algebraic curves can be constructed. It is proved that MDS algebraic geometry (AG) codes from higher genus curves are not equivalent to MDS AG codes from lower genus curves. For genus one case, we construct MDS AG codes of small consecutive lengths from elliptic curves. New self-dual MDS AG codes over F <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2<sup><i>s</i></sup></sub> from elliptic curves are also constructed. These MDS AG codes are not equivalent to Reed-Solomon codes, not equivalent to known MDS twisted Reed-Solomon codes and not equivalent to Roth-Lempel MDS codes. Hence many non-Reed-Solomon type MDS AG codes, which are not equivalent to known MDS twisted-Reed-Solomon codes and Roth-Lempel MDS codes, can be obtained from arbitrary genus algebraic curves. It is interesting open problem to construct explicit longer MDS AG codes from maximal curves.