Reviewerly/exHarmony huggingface dataset:
PERFORMANCE EVALUATIONS OF THE MANTA RAY FORAGING OPTIMIZATION ALGORITHM IN REAL-WORLD CONSTRAINED OPTIMIZATION PROBLEMS

Authors:
raw_author_name: Gülnur Yıldızdan
raw_affiliation_string: Selçuk Üniversitesi

Abstract: Metaheuristic algorithms are often preferred for solving constrained engineering design optimization problems. The most important reason for choosing these algorithms is that they guarantee a satisfactory response within a reasonable time. The swarm intelligence-based manta ray foraging optimization algorithm (MRFO) is a metaheuristic algorithm proposed to solve engineering applications. In this study, the performance of MRFO is evaluated on 19 mechanical engineering optimization problems in the CEC2020 real-world constrained optimization problem suite. In order to increase the MRFO performance, three modifications are made to the algorithm; in this way, the enhanced manta ray foraging optimization (EMRFO) algorithm is proposed. The effects of the modifications made are analyzed and interpreted separately. Its performance has been compared with the algorithms in the literature, and it has been shown that EMRFO is a successful and preferable algorithm for this problem suite.
The Impact of International Conflicts on the Cryptocurrency Market: The Case of Israel–Palestine Conflict

Authors:
raw_author_name: Zeliha Can Ergün
raw_affiliation_string: Adnan Menderes Üniversitesi

Abstract: In the financial markets, international conflicts have a crucial influence. The ongoing conflict between Israel and Palestine is one of them which poses hazards to international politics and the economy. This study is the first study that examines the potential influence of the Israel-Palestine conflict on the cryptocurrency market. To this end, the event study methodology is used for the period 01.03.2023 – 17.10.2023, and the top ten cryptocurrencies are chosen for analysis based on their market capitalization. The results show that although the Israel-Palestine conflict affected certain cryptocurrencies (including BTC, TRX, SOL, and ETH), it had no statistically significant effect on the market as a whole. Furthermore, the majority of the effect was statistically positive, which may be an indication that the cryptocurrency market is considered a safe haven. Moreover, the abnormal returns were usually recorded in the days before the event, suggesting that the event had been anticipated by some cryptocurrencies. Investors and financial analysts may benefit from these results by considering the cryptocurrency market as an alternative investment tool in these uncertain times and using these findings to diversify their portfolios and create hedging strategies.
Evolution and Efficiency in Neural Architecture Search: Bridging the Gap  Between Expert Design and Automated Optimization

Authors:
raw_author_name: Brown, Alexander

Abstract: The paper provides a comprehensive overview of Neural Architecture Search (NAS), emphasizing its evolution from manual design to automated, computationally-driven approaches. It covers the inception and growth of NAS, highlighting its application across various domains, including medical imaging and natural language processing. The document details the shift from expert-driven design to algorithm-driven processes, exploring initial methodologies like reinforcement learning and evolutionary algorithms. It also discusses the challenges of computational demands and the emergence of efficient NAS methodologies, such as Differentiable Architecture Search and hardware-aware NAS. The paper further elaborates on NAS's application in computer vision, NLP, and beyond, demonstrating its versatility and potential for optimizing neural network architectures across different tasks. Future directions and challenges, including computational efficiency and the integration with emerging AI domains, are addressed, showcasing NAS's dynamic nature and its continued evolution towards more sophisticated and efficient architecture search methods.
Beyond Cryptic Equations: Reimagining Concepts in Physics Through Metaheuristics and Fantasy Stories using Neutrosophic Venn Diagram

Authors:
raw_author_name: Victor Christianto
raw_author_name: Florentin Smarandache

Abstract: Physics, the grand narrative of the universe, has long been viewed as a realm of cold, hard equations. But what if we looked beyond the formulas and considered a more imaginative origin for some of its concepts? This article explores the intriguing possibility that physics, and even cosmology, might share a surprising kinship with metaheuristics and fantastical fiction. Metaheuristics, a branch of computer science, deals with finding approximate solutions to complex problems. Perhaps the universe, in its vastness, employs a set of "rules" that lead to the most likely outcomes, much like an algorithm searching for the best solution within a vast space of possibilities. The connection strengthens when we consider the fantastical. Argentine writer Jorge Luis Borges, known for his thought-provoking short stories, often explored themes of infinity, labyrinths, and forking realities. In this article, we discuss, among other things, how to look at physics laws from an alternative fundamental viewpoint that is fluid dynamics perspective. As an example, we provide an outline for deriving the Newton gravitational law from the Kutta-Joukowski theorem, and then deriving the Kutta-Joukowski theorem from Bernoulli principles. In the meantime, it is known that vortex flows, related to solar convective turbulent dynamics at granular scales and their interplay with magnetic fields within intergranular lanes, occur abundantly on the solar surface and in the atmosphere above.
Characteristics of Marketing Activities of Non-Profit Entities (Advertising and Pr in Scientific Libraries)

Authors:
raw_author_name: Alish Agamirzayev
raw_author_name: Nigar Seyidli

Abstract: Non-profit activities, depending on their nature, engage in advertising activities and do not pursue profit-making purposes in this activity. This approach gives rise to different thoughts for state educational institutions, cultural institutions and libraries. When organizing the activities of libraries, completely different methods and forms are used depending on their type and type. In recent years, depending on its goals and objectives, the library has begun to widely use modern PR technologies in organizing its work. Higher education libraries express their function as a research library in different ways. In the article we analyze the activities of leading scientific and university libraries and try to determine the general aspects of the organization of PR activities in these types of libraries. An attempt has been made to formulate a scientific-experimental model with the aim of obtaining modern PR effects through the use of both traditional and modern technologies.
The Practical Exploration of Information-based Teaching in Chinese Teaching in Secondary Vocational Schools

Authors:
raw_author_name: Zhang Qian

Abstract: Our country's science and technology is more and more developed, information technology is widely used in our life aspects, education is no exception, this for the secondary vocational school language teaching to modernization, closely follow the trend of The Times development is an opportunity, secondary vocational educators should seize the opportunity to realize the reform of vocational teaching. Chinese is the mother tongue of our country and the crystallization of our traditional culture and ancient wisdom. Students must learn it to strengthen their own reserves of Chinese knowledge. Chinese is one of the compulsory cultural courses carried out by schools.
Strategies for Integrating Ideological and Political Education Elements into Courses for English Majors through Generative AI: A Case Study of Comprehensive English Course

Authors:
raw_author_name: Jianhua Zhou

Abstract: This paper explores the strategies for integrating ideological and political education (IPE) elements into courses for English majors through the use of generative artificial intelligence (AI). Through a case study of the comprehensive English course, this paper examines how generative AI can facilitate the incorporation of IPE elements into English majors’ education. Various strategies are proposed to effectively integrate IPE elements into the curriculum, enhancing students' ideological and moral education while fostering language proficiency.
Beliefs on Second Language Learning among Pre-service Teachers in a Public University in Malaysia

Authors:
raw_author_name: Nurul Najwa Baharum
raw_author_name: Lilliati Ismail

Abstract: The purpose of this research was to identify the Teaching of English as a Second Language (TESL) pre-service teachers’ beliefs about second language (L2) learning, to determine whether there is a significant difference in beliefs among the TESL pre-service teachers of different years of study and how these beliefs were formed. These are important as the pre-service teachers’ beliefs would have a direct influence on their practices as a teacher in future. This research was conducted with a sample size of 113 respondents using a mixed method design. Data collection is using the Belief About Language Learning Inventory, often known as BALLI approach to ensure a comprehensive understanding of individuals' beliefs. In addition, data was gathered using semi-structured interviews thus, guaranteeing a more in-depth understanding of the participants' experiences and beliefs. Descriptive statistics showed that the highest mean score was recorded for the “motivation and expectations” dimensions. The ANOVA results showed statistically significant difference in the mean scores amongst the different years of study. Interview results indicated that beliefs were dominantly influenced by social support and exposure to the L2, and intrinsic and extrinsic motivation. Results of the study could inform course developers and lecturers as to which aspects of language learning and pedagogical knowledge need to be focused on in the pre-service teachers’ curriculum.
PENGOLAHAN FOTO UDARA UAV (UNMANNED AERIAL VEHICLE) MENGGUNAKAN SOFTWARE AGISOFT METASHAPE

Authors:
raw_author_name: Frederik Samuel Papilaya

Abstract: This research aims to explain the method of utilizing UAV (Unmanned Aerial Vehicle) for aerial data photography and processing of UAV aerial photos using Agisoft Metashape software. In this context, the author will discuss the key steps in data processing, including aerial photo preprocessing, 3D model generation, digital elevation model (DEM) extraction, orthomosaic extraction, and the provision of processing information from the aerial photo data. The research flow is structured in a series of steps, encompassing all stages performed during the research process, allowing for a clear direction of the research's progression. The final results, in the form of DEM and orthomosaic, hold significant value in mapping and geospatial analysis. This research is expected to enhance the understanding of UAV usage in surveying and mapping, enabling broader applications in various sectors. Careful supervision and control of UAV flights are highly emphasized to ensure data quality. The use of UAVs and Agisoft Metashape opens up new opportunities for accurate, efficient, and effective surveying and mapping.
BIBLIOMETRIC MAPPING PUBLICATIONS OF SCIENTIFIC WORK OF INFORMATION SYSTEMS LECTURER AT UIN SYARIF HIDAYATULLAH JAKARTA ON GOOGLE SCHOLAR SYSTEMATIC REVIEW USING RESEARCH RABBIT

Authors:
raw_author_name: Elvi Fetrina
raw_author_name: None Murni

Abstract: ABSTRACT&#x0D; In the modern era dominated by technology, understanding academic developments in the Information Systems Department of UIN Syarif Hidayatullah Jakarta through Google Scholar and Research Rabbit is very important. The research focuses on identifying lecturers' research interests, with the aim of developing a more relevant curriculum for students. Literature studies are used to collect and analyze information from various sources. The research results reveal the latest research topics that lecturers publish, becoming the basis for future research and guidelines for curriculum development according to technological developments. The conclusion emphasizes the importance of adapting research to technological developments and a deep understanding of lecturers' interests to maintain the relevance of the curriculum in an ever-changing academic world. This step is key in preparing students to succeed in a rapidly developing environment. In this context, lecturers' understanding and research helps shape a curriculum that is able to face the challenges of modern technology and produce graduates who are ready to face continuous change.&#x0D; Keywords : Bibliometrics, Publications, Scientific Work, Google Scholar, Research Rabbit
Digital-Based Collaborative Reading-Writing Performance of Elementary School Students

Authors:
raw_author_name: Chaeeun Kim

Abstract: Thation.
The Improvement of the Educational Environment for Information Literacy Education in Japan

Authors:
raw_author_name: Minjung Kim
raw_author_name: Eunju Lee

Abstract: Thion.
A Study on the Differences in Quantity and Quality of Student Response Writings Between Reading Text and Watching Video: Focusing on the classic ‘The Old Man and the Sea’

Authors:
raw_author_name: Jiyoung Lee

Abstract: Thnemedia.
Undergraduate International Students’ Use of Online Machine Translation and Instructor Perceptions － Focusing on Korean Writing

Authors:
raw_author_name: Jiyoung Choi

Abstract: Thies
Writing Education for Sutainable Life: Focusing on the Possibility of Reflection and Value of Communication through writing

Authors:
raw_author_name: Ji-hye Jang

Abstract: Thisners.
Gender and Age Estimation By Image Processing

Authors:
raw_author_name: Mehmet Fatih Demiral
raw_affiliation_string: MEHMET AKIF ERSOY UNIVERSITY

Abstract: Today, with the increasing interest in technology, very useful studies are carried out in the field of image processing. Image technologies are also used in many fields such as security, defense, medicine, and industry. In this study, age, gender, and ethnicity were found in the image by using different deep learning techniques and by building our own model in CNN. The 23705 images taken from the csv file named Face Data taken from Kaggle were categorized as different gender, race, and age within the application and the accuracy and losses of the results were transferred with graphs. In addition, by creating an interface with the help of the Python flask library, the results of the snapshot taken from the camera (age, gender, and race) can also be found. Out of the 23705 images, approximately 12000 male and 11000 female profiles were obtained. These profiles were classified according to 5 different genetics specified in the dataset. The genetics in the application (0 represented White, 1 represented Black, 2 represented Asian, 3 represented Indian, 4 represented Others.) The most difficult part of this study is that the picture changes depending on many factors such as posture, pose angle, brightness, and resolution at the time of shooting..
Computing Longest Common Subsequence under Cartesian-Tree Matching Model

Authors:
raw_author_name: Mieno, Takuya
raw_author_name: Nakashima, Yuto
raw_author_name: Inenaga, Shunsuke

Abstract: Two strings of the same length are said to Cartesian-tree match (CT-match) if their Cartesian-trees are isomorphic [Park et al., TCS 2020]. Cartesian-tree matching is a natural model that allows for capturing similarities of numerical sequences. Oizumi et al. [CPM 2022] showed that subsequence pattern matching under CT-matching model can be solved in polynomial time. This current article follows and extends this line of research: We present the first polynomial-time algorithm that finds the longest common subsequence under CT-matching of two given strings $S$ and $T$ of length $n$, in $O(n^6)$ time and $O(n^4)$ space for general ordered alphabets. We then show that the problem has a faster solution in the binary case, by presenting an $O(n^2 / \log n)$-time and space algorithm.
Analysis of The Sentiment of Indonesian Presidential Candidates for 2024 on The YouTube Social Media Platform using The Support Vector Machine Method

Authors:
raw_author_name: Adhi Wahyudi
raw_affiliation_string: Informatics Study Program, Faculty of Industrial Technology, University of Trisakti
raw_author_name: Gatot Budi Santoso
raw_affiliation_string: Informatics Study Program, Faculty of Industrial Technology, University of Trisakti
raw_author_name: Binti Sholihah
raw_affiliation_string: Informatics Study Program, Faculty of Industrial Technology, University of Trisakti

Abstract: Indonesia is a country led by a president. The term of office of a president will be democratically elected every five years. The current president will end his term of office in 2024. So that in that year, the people will hold direct general elections to determine the president between 2024 and 2029. Before the general elections are held in Indonesia itself, it is closely related to the campaigns of each presidential candidate carried out by their supporters. Campaigns are usually carried out directly to village locations and social media Twitter/Facebook/YouTube. This study aims to analyze the sentiment of comments on the YouTube platform for three Indonesian presidential candidates, Anies Baswedan, Ganjar Pranowo, and Prabowo Subianto in the context of the 2024 PresidentialElection.. Indonesia is a nation led by a president, with the presidential term lasting five years, determined through democratic elections. The incumbent president's tenure will conclude in 2024. Consequently, during that year, citizens will participate in a direct general election to select the president for the 2024- 2029 period. Prior to the domestic general elections, there is a strong link to the campaigning efforts of each presidential contender, which are conducted by their respective supporters. Campaign activities typically extend to rural areas and popular social media platforms such as Twitter, Facebook, and YouTube. This research aims to assess the sentiment of comments on the YouTube platform regarding three potential Indonesian presidential candidates: Anies Baswedan, Ganjar Pranowo, and Prabowo Subianto. This analysis takes place in the context of the upcoming 2024 Presidential Election.
Designing a University Environment for Inclusive Digital Education – Methods and Approaches

Authors:
raw_author_name: Mariya Monova-Zheleva

Abstract: The rapid development and implementation of digital technologies in education and the forced shift to fully distance learning due to the COVID-19 pandemic, which has exacerbated the existing problems and challenges of access to higher education for disadvantaged students, have brought to the fore the need for systemic change, aimed at building crisis-resilient university ecosystems where inclusive education and digital transformation are considered in their interconnectedness to provide appropriate infrastructures and technologies for inclusive digital learning. Designing such systems requires applying an interdisciplinary design approach with careful consideration of the needs and wants of all user groups and especially those vulnerable to exclusion. The article presents the methodology and results of a study aimed at identifying the needs, barriers and issues faced by students of low socio-economic status, which is part of a wider international initiative to develop university ecosystems for inclusive digital learning, in in which universities from six countries of the European Union participate.
Leukemia detection using Artificial Neural Networks in Images of Human Blood Sample

Authors:
raw_author_name: Ahmet Çınar
raw_affiliation_string: Department of Computer Engineering, College of Engineering, Fırat, University, Elazığ, Türkiye

Abstract: This article presents a preliminary report that uses minuscule images of blood tests to develop a diagnosis of leukemia. Examining through images is crucial since illnesses can be recognized and examined at an earlier stage using the images. The framework will be centered on leukemia and white blood cell illness. In fact, even the hematologist has trouble organizing the leukemic cells, and manually arranging the platelets takes a long time and is quite loose. In this way, early detection of leukemia recurrence allows the patient to receive the appropriate treatment. In order to address this problem, the framework will make use of the capabilities in small images and examine surface, geometry, shading, and quantifiable investigation modifications. These features' variations will be utilized as the classifier input. has transformed the use of images K proposes that (NN) and agglomeration. Examining a wide range of failure measures and increasing the intricacy of every system, the findings are examined. Utilizing feedforward (NN), image division is accomplished with less noise and a very sluggish conjunction rate. K-means agglomeration and (ANN) are intentionally used in this analysis to create a collection of processes that will work together to produce a much better presentation in (IS). An analysis has been conducted to determine the best rule for (IS).
Frog-Snake prey-predation Relationship Optimization (FSRO) : A novel  nature-inspired metaheuristic algorithm for feature selection

Authors:
raw_author_name: Saitou, Hayata
raw_author_name: Haraguchi, Harumi

Abstract: Swarm intelligence algorithms have traditionally been designed for continuous optimization problems, and these algorithms have been modified and extended for application to discrete optimization problems. Notably, their application in feature selection for machine learning has demonstrated improvements in model accuracy, reduction of unnecessary data, and decreased computational time. This study proposes the Frog-Snake prey-predation Relationship Optimization (FSRO) algorithm, inspired by the prey-predation relationship between frogs and snakes for application to discrete optimization problems. The algorithm models three stages of a snake's foraging behavior "search", "approach", and "capture" as well as the frog's characteristic behavior of staying still to attract and then escaping. Furthermore, the introduction of the concept of evolutionary game theory enables dynamic control of the search process. The proposed algorithm conducts computational experiments on feature selection using 26 types of machine learning datasets to analyze its performance and identify improvements. In computer experiments, the proposed algorithm showed better performance than the comparison algorithms in terms of the best and standard deviation of fitness value and Accuracy. It was also proved that dynamic search control by evolutionary game theory is an effective method, and the proposed algorithm has the ability of a well-balanced search, achieving the two objectives of improving accuracy and reducing data.