Reviewerly/exHarmony huggingface dataset:
Design of “HANASHI KOTOBA Checker” with Machine Learning-based Sentence Expression Classification

In this study, we describe developing a learning support system for academic writing. The proposed system attempts to detect colloquial words based on subjective or objective sentences in student reports. To achieve this, we implemented a prototype machine learning model to realize effective detection. We then proposed the system design to incorporate this model into the previous colloquial words detection system.
Effects of the Attunement of an Attack Target by Whispering in AIWolf

Recently, research on AIWolf, which is artificial intelligence that plays the Werewolf game, has attracted much attention. Werewolves in the Werewolf game should cooperate using “whispers;” which are conversations among werewolves only. However, whispers have not been used effectively in the AIWolf Competition and little research has been conducted on this topic. Therefore, the purpose of this study is to clarify the effectiveness of strategies that use whispers in AIWolf. A wide variety of strategies use whispers, but we focus on unifying attack targets, which was shown to improve the winning rate in previous studies. In the strategy of unifying attack targets, the strategy of the guiding agents is important. Therefore, we used 13 AIWolf Competition finalists with a wide variety of strategies and added statements of whom to attack in whispers to each finalist as a guide for whom to attack. Because there are three werewolf competitions in the AIWolf Competition setting, we created two agents to be attuned to the attack target of one of the guiding agents. In an experiment, we used these agents in the same setting as in the AIWolf Competition, and analyzed the differences between when the attack targets were unified and when they were not. The results showed that when the werewolves were a combination of two attuning agents and one guiding agent, the werewolves’ win rate increased by an average of 2.3 percentage points. We also found that attuning to the agent with a high winning rate or high success rate in attacks improved the winning rate. These results indicate that attuning only the attack targets of agents with high winning rates and high success rates in attacks led to higher winning rates.
A Security-enhanced Steganography Scheme for RGBE-format HDR Images

Recently, the research of introducing data hiding techniques to High Dynamic Range (HDR) images has drawn much attention in academia. Yu et al. utilizes the homogeneity in RGBE format, one popular format of HDR, to propose a steganography scheme. The attractive contribution of Yu et al.’s scheme is the cover images are demonstrated only with slight and ignorable distortions after embedding. Unfortunately, Yu et al.’s steganography scheme may potentially lead an eavesdropper to arise suspicions because of the multiplication and division in the embedding process causing the abnormal distribution of pixel values. In this paper, a security-enhanced steganography scheme is proposed to avoid the potential security weakness by post-process: using additional random numbers to change the value of pixels. The experimental results accordingly show that the proposed scheme does improve the security level while achieving reasonable imperceptibility.
An ϵ-Approximation On-line Algorithm for Quantiles Based on Counters

The quantiles are very important as a statistic that gives an overview of big data. In this paper, we study the GK algorithm for finding $\epsilon$-approximate quantiles and point out its redundancy hidden the quantile summary. We introduce a counter mechanism and give a new approximation algorithm that is more space efficient. We theoretically guarantee that the maximum quantile error is within the range of the $\epsilon$-approximation, and confirm by computational experiments that the spatial complexity required to preserve the $\epsilon$-approximate quantile summary is significantly improved.
Pengaruh Model Pembelajaran Picture and Picture Terhadap Kemampuan Menulis Puisi Siswa Kelas V Kota Bengkulu

This research was aimed to analyze the effect of Picture and picture learning model towardstudents' writing poetry skill in 5th class of elementary school in Bengkulu City. This researchwas Quantitative reseacrh. The method used was quasi-experimental and the design wasmatching only posttest control group. The population of this research was 5th class of all elementary school in Bengkulu city whereas the sample was class V of elementary School No 51 was the control class. Both classes used School Based Curriculum (KTSP) and obtain accreditation A. The technique of sampling was stratified sampling. The instrument used wasessay posttest for both control and experimental class. The data of the research was analyzed byusing descriptive analysis, prerequisite test and t test. The result of the research was found that the average score of posttest of the control class was 75,41 and the average score of posttest of the experimental class was 83,18. The result of the t test was found that the t count about 2,02. So, Ha was accepted and Ho was rejected. This result showed that there was the effect of Picture andPicture model learning toward students’ writing poetry skill in 5th Class of elementary school inBengkulu City.
Support for Understanding Others by Visualizing Sentiment of Social Media Posts

Understanding people is critical in various aspects of our daily lives. We believe that extracting and visualizing the emotions included in social media posts will facilitate the understanding of people. Based on this idea, we developed a tool for understanding others using sentiment analysis of a user’s Twitter and Instagram posts. We experimentally evaluated our approach and the tool to understand professional baseball players as examples of others.
Aplikasi Model Pembelajaran TGT (Teams Games Tournament) Untuk Meningkatkan Hasil Belajar IPS Pada Siswa Kelas IV SD Negeri 12 Palembang

This research aims to improve the social studies learning achievement of fourth grade students at SD Negeri 12 Palembang by using the Teams Games Tournament (TGT) learning model, classroom action research on 31 fourth grade students who were used as research objects. It turns out that the Teams Games Tournament (TGT) model can improve learning achievement. social studies students. This can be seen from the increase in the average value of the pre-cycle, cycle I and cycle II. In the pre-cycle, only 4 students passed the KKM with average social studies score of 38.83 or 13%. In cycle I, 21 students passed the KKM with an average score of 70.64 or 67.74%. Meanwhile, in cycle II, 25 students passed the KKM with an average score of 79.03 or 80.64%. And this shows that cycle II has been successful or complete because it has achieved the expected classical KKM of 80%.
Young Korean EFL Learners’ Perception of Role-Playing Scripts: ChatGPT vs. Textbooks

This study explores the perceptions of elementary students in South Korea regarding two types of scripts used in reader’s theaters: those derived from textbooks and those generated by ChatGPT. The research involved 27 fourth-grade students from Gyeonggi Province. The scripts consisted of six topics, each with dialogues presented in the textbooks and those created by GPT-3.5 to match the language proficiency of 9-year-old EFL learners. Students performed both script types in reader’s theaters, and evaluations were conducted based on text flow, storyline attractiveness, English level, and practice process. Surveys were conducted twelve times, and results were analyzed using repeated measures of two-way ANOVA. The study revealed some statistical differences in the storyline attractiveness and English level, aligning with various student opinions. The study underscores the potential of integrating Artificial Intelligence (AI), such as ChatGPT, into English teaching while discussing pedagogical implications and emphasizing the need for differentiated approaches based on students’ linguistic abilities. Suggestions for future research involving Chat GPT in elementary English education are provided.
HOLOGRAPHIC TECHNOLOGIES OF EDUCATION AS A COMPONENT OF TRAINING OF FUTURE ENGINEERS IN THE CONDITIONS OF EDUCATIONAL AND INFORMATION ENVIRONMENT

The article presents the results of training future engineers with the help of holographic technologies for lectures, practical and laboratory classes. When there is a global change (pandemic, war), education faces the risk that it will not be able to continue its usual processes and will have to move to instant managerial change. The aim of the article is to identify and outline the positive elements of holographic technologies that will help increase interactivity in the teaching and learning process. The task of the study is to find an alternative solution to attract the latest learning technologies in the training of future engineers. Experience shows that in this case, the educational and information environment is the best solution for classes. But the problem of learning is the interactivity of the student to improve the motivation of future professionals with the help of new technologies. At the Technical University, we propose to introduce innovative teaching and learning methods, including games, simulations and holograms. Meanwhile, training is not only the transfer of knowledge, but also an active, constructive and cognitive process through which the future engineer manages internal resources for the formation of key professional competencies. Research methods are to study and generalize domestic and foreign experience to substantiate the conceptual provisions of holographic learning technologies, structural and scientific analysis, as well as monitoring the learning process. Results. To improve the training of future engineers in an educational information environment, holographic technologies can be useful and become another resource that can change the way you create and conduct classes. To obtain this result, it is necessary to study the feasibility of holographic technologies in accordance with the training in the educational and information environment. The article reveals the essence of the considered holographic technologies, describes the advantages and features of their implementation in the educational process of the Technical University. This helps students to intensify cognitive activities and stimulate them to self-education. In the course of elaboration of a number of research ideas, various scientific approaches to the interpretation of the term "holographic technologies" are proposed. Conclusion. According to existing concepts, holographic technologies can be considered as a result of the creative process and as a process of innovation. Peculiarities, prospects of introduction of holographic technologies into the educational process of the technical university are determined, which require further detailed analysis and study in complex interaction with information systems.
Exploration of Optimization Paths for Blended Teaching of College English in the Context of "Internet+"

In the wave of digital transformation, blended teaching in college English has emerged as an effective teaching strategy. It not only caters to the diverse learning needs of students but also provides them with a richer and multidimensional learning experience. This approach not only broadens students' learning avenues but also grants them more autonomy in their learning space. In the future, this teaching model can further integrate advanced technologies like artificial intelligence and big data analysis to offer students more personalized learning recommendations and paths.
Accumulation of words: lists in the Italian public discourse

In written and spoken language, lists are flexible instruments that take on different functions, such as grouping elements in a stable set or suggesting others to come. Umberto Eco perceives lists as a semiotic modality of vertigo-like accumulation, which offers a way to speak of something whose boundaries one does not know and to place a limit upon the entropy of the mass of things (Belknap 2004; Eco 2009). In public discourse, lists are a helpful device to express opinions and slogans in a constrained space (for example, on Twitter) through a cohesive and coherent collection of elements placed on the same level around a semantic area that the recipients must interpret. This article examines how verbal lists exploit two basic textual strategies in Italian public discourse. The first strategy consists of a collection with precise extensional boundaries and no alternative items. The second is an assortment of items that allude to a set of possibilities with nuanced extensional boundaries. Through these two strategies, the recipient can create two textual semiotic modalities due to the inference procedures: lists with a closed textual modality, closed fabula, and lists with an open textual modality, open fabula (Eco 1979a).
Antenna Array Analysis Through Universal Quantum Computing Processors—A Study on Noise Modeling and Impact

An in-depth study on the effect of real quantum computer noise is proposed in relation to the execution of the quantum Fourier transform (QFT) applied to electromagnetic simulations and in particular to phased array (PA) analysis. In this work, a mathematical formulation of the noise and information loss sources in quantum computers is detailed and embedded in a noise model. The effect of noise on quantum computations is studied using a real quantum computer as well as with the support of a quantum computer emulator.
Efficient Camouflaged Object Detection via Progressive Refinement Network

Camouflaged object detection (COD) aims to identify objects that are perfectly concealed in their surroundings and has attracted increasing attention in recent years. The challenge with COD is the intrinsic similarity between camouflaged objects and background, as well as the weak boundary that often accompanies camouflaged objects. In this paper, a Progressive Refinement Network called PRNet is proposed based on human perception of camouflaged images. Specifically, we develop a position-aware module to roughly locate the position of camouflaged objects by reverse-guiding with high-level semantic information. Moreover, an edge-guided fusion module is designed to simultaneously refine the boundaries and regions of camouflaged objects by using edge features as a guide in cross-level feature fusion. Benefited from the utility of the above two modules, our PRNet is able to identify camouflaged objects accurately and quickly. Numerous experiments on four widely used benchmark datasets demonstrate that the proposed PRNet is an efficient COD model, outperforming 14 state-of-the-art algorithms significantly and running at a real-time
Innovative Cost Estimation for Agile Technology: A Novel Energy Storage Technique Incorporating Modified Planning Poker

Effort estimation is a critical aspect of every software creation project, irrespective of its development discipline, is it traditional or agile. Despite the initial limited project knowledge, accurate estimation of workload and effort holds immense significance for project success. This study addresses the challenges surrounding precise effort estimation and introduces the poker planning method utilizing a modified Fibonacci sequence as a potential solution. The aim of this paper is to examine the behavior and effectiveness of the modified Fibonacci sequence in the context of cost estimation within the agile methodology. By leveraging historical data, expert opinions, and an iterative approach, the proposed technique is evaluated and compared against traditional methods. The results provide insights into the performance of the modified Fibonacci sequence, offering a valuable contribution to enhancing accuracy in cost estimation for agile software development projects.
LPDA: Cross-Project Software Defect Prediction Approach via Locality Preserving and Distribution Alignment

Cross-Project Defect Prediction (CPDP) based on domain adaptation aims to achieve defect prediction tasks in an unlabeled target software project by borrowing the defect knowledge extracted from well-annotated source software projects. Most existing CPDP approaches enhance transferability between projects but struggle with misalignments due to limited exploration of class-specific features and inability to preserve original local relationships in transformed features. In order to tackle these challenges, The article introduces a novel Cross-Project Defect Prediction (CPDP) approach called Local Preserving and Distribution Alignment (LPDA). This approach addresses the challenge of misalignments in CPDP due to limited exploration of discriminative feature representations and the failure to preserve original local relationship consistency. LPDA combines transferability and discriminability for CPDP tasks. It uses locality-preserving projection to maintain module consistency and distribution alignment, which includes transferable and discriminant distribution alignment. The former narrows the distributions of both source and target projects, while the latter increases the discrepancy between different classes across projects. The effectiveness of LPDA was tested through 118 cross-project prediction tasks involving 22 software projects from four distinct repositories. The results showed that LPDA outperforms baseline CPDP methods by efficiently learning representations that integrate transferability and discriminability while preserving local geometry to optimize distances within and between categories.
ASYMPTOTIC BEHAVIOR OF Pω(Y0, Y1,±∞)-SOLUTIONS OF THE SECOND ORDER DIFFERENTIAL EQUATIONS WITH THE PRODUCT OF DIFFERENT TYPES OF NONLINEARITIES FROM AN UNKNOWN FUNCTION AND ITS FIRST DERIVATIVE

The task of establishing the conditions of existence, as well as finding asymptotic images of solutions of differential equations, which contain nonlinearities of various types in the righthand side, is one of the most important tasks of the qualitative theory of differential equations. In this work, second-order differential equations, which contain in the right part the product of a regularly varying nonlinearity from an unknown function and a rapidly varying nonlinearity from the derivative of an unknown function when the corresponding arguments are directed to zero or infinity, are considered. Necessary and sufficient conditions for the existence of slowly varying P!(Y0; Y1;±∞) solutions of such equations have been obtained. Asymptotic representations of such solutions and their first-order derivatives have also been obtained. When additional conditions are imposed on the coefficients of the characteristic equation of the corresponding equivalent system of quasi-linear differential equations, it is established that there is a one-parameter family of such P!(Y0; Y1;±∞)-solutions to the equation. Similar results were obtained earlier when considering second-order equations, which contain on the right-hand side the product of a rapidly varying function from an unknown function and a properly varying function from the derivative of an unknown function when the arguments go to zero or infinity. Results for the equation, considered in this paper, are new.
A study on alternative container-based technologies for virtualization of components deployment in software product lines

The application containerization approach allows creating virtualization environments that could be used as a code. It allows running application in the isolated container that could be reproduced on any other hardware or cloud environment. One of the benefits of the containerization approach is the possibility to allocate necessary hardware resources like a RAM, CPU and storage. An approach to support agile development of software product lines (SPL) by using variability management techniques within the framework of the Scrum methodology has been proposed in the article. The main goal of the work is to analyze containers for virtualization of the runtime environment when deploying SPL. The information base for the proposed approach to managing the variability of deployment has been structured. The role of the approach in the general method of Scrum has been shown, and a conceptual diagram of the management process at the stage of application deployment has been proposed. The experimental analysis has been carried out and metrics for two types of containers, Docker and Vagrant, have been calculated. The following two metrics, namely, portability and productivity, for both containers have been analyzed. These metrics for the test component software solution have been calculated and executed in cloud environment with different configurations. The portability metric indicates how easily the application can be migrated to other platform basing on the time required to start container with the application. The second metric is the time necessary for the same operations in different container.
Improving Children’s Reading Motivation and Skills Through Read Aloud: A Mixed-Method Study in Orphanage Context

Generally speaking, children's reading motivation and skills are low, notably those in orphanages requiring solution, one of which is through reading activities applying read-aloud method. Most studies on the read-aloud method were qualitative. This study attempted to address the gap by employing a mixed-methods design with 10 foster children from an orphanage chosen using purposive sampling technique. Observations, tests, and interviews were used to collect the data. Quantitative data from observations and tests were statistically analyzed and reported in frequency and percentage to determine the difference in the number of children who improved following the program. Additionally, interviews were conducted to obtain qualitative data on children's and orphanages' perspectives of the program and its impacts, and the results were assessed using qualitative data analysis including data reduction, data display, and conclusion drawing. Both quantitative and qualitative data were gathered and analyzed concurrently. They were then merged and interpreted through a side-by-side comparison approach. Finally, convergence or divergence between the two sources of data was determined. The findings show that quantitative and qualitative data confirm each other, demonstrating that the read-aloud method improved children's reading motivation by significantly increasing the length of time for reading and the number of books read, as well as a slight increase in children's reading comprehension and confidence. In addition, the children's reading fluency improved substantially, while their reading accuracy and clarity improved slightly. Future research should focus on areas that need the most improvement and entail a larger sample size. Additionally, reading assistance for foster children is always recommended.
The Effect of the Implementation of Accounting Information Systems and Internal Audit on The Quality of Financial Statements with Organizational Commitment as a Moderating Variable (Empirical Studies at PT. Eastern Pro Engineering)

This research aims to determine the effect of implementing accounting information systems (X1) and internal audit (X2) on the quality of financial reports (Y) with organizational commitment (Z) as a moderating variable at PT. Eastern Pro Engineering. This type of research is quantitative with the method used being descriptive associative and the data analysis design is Moderated Regression Analysis (MRA), using questionnaire data filled in by 36 respondents. The results of this research are that organizational commitment as a moderating variable does not moderate the influence of the application of accounting information systems and internal audit on the quality of financial reports with a significant t test value of &gt;5% or 0.890 (X1) and 0.551 (X2) in equation 3, so H0 is accepted and Ha rejected.