Reviewerly/exHarmony huggingface dataset:
CHARACTER EDUCATION VALUES IN THE ELEMENTARY SCHOOL ENGLISH TEXTBOOK ENTITLED “BASIC ENGLISH” FOR GRADE SIX

One of the most important teaching materials is textbook. It is also inseparable from learning English in elementary school. Using English textbook in Elementary school to help a teacher in conveying material to their students. Textbooks that are suitable for use as teacher handbooks are those that are in accordance with the competency standards set by the ministry of education. The aims of the research are to analyze: the values of character education as reflected in the sixth grade English textbook of elementary school entitled "Basic English" which is used at SDN Jombatan 5 Jombang and how to implement character education values ??in the textbook. The method used in this study was a qualitative descriptive approach using interactive content analysis. The subjects of this study were 14 themes of subject matter in English textbook “Basic English”. The results of this study stated that the sixth grade English textbook entitled "Basic English" Religiousness, honesty, intelligence, toughness, democracy, care, independence, Logical thinking, critical, creative, and innovative, courage takes risk, action oriented, leadership, hard work, responsibility, healthy lifestyle, discipline, confidence, curiosity, loving science, Awareness of rights and self-and other obligations and Adherence to social rules and others characters education values are namely appreciating the work and achievements of others, politeness, nationalism, and respecting diversity. And those values are explained implicitly and explicitly.
Assessment of Lecturers’ Acceptance and Adoption of M-Learning Technology for Instructional Delivery in Tertiary Institutions in Kogi State, Nigeria

This study assessed lecturers’ acceptance and adoption of M-learning technology for instructional delivery in tertiary institution in Kogi State. The study was guided by six research questions and four of them were hypothesized. The study adopted a descriptive research of the cross sectional survey type. The population of the study consisted of lecturers in tertiary institutions in Kogi State. Purposive sampling technique was used to select one university, one polytechnic and one college of education that was used for the study. The sample size of the respondent was 333 lecturers. A researcher’s designed questionnaire titled LAAMTID was used as the instrument for data collection and the study instrument was validated by experts. Mean, ttest and ANOVA were used to analyze the data. The analysis was done using SPSS. The findings indicated that lecturers’ in tertiary institutions in Kogi State accept M-learning technology. That gender was not a moderating factor in lecturers’ acceptance of M-learning technology in instructional delivery in tertiary institutions in Kogi State. Also, that gender was a moderating factor in lecturers’ adoption of M-learning technology in instructional delivery in tertiary institutions in Kogi State. That area of specialization is not a moderating factor in the acceptance of M-learning technology among lecturers’ in tertiary institutions in Kogi State. Based on these findings, it was recommended that lecturers ’should be motivated and encouraged to incorporate the adoption of M-learning technology for instructional delivery in tertiary institutions by organizing of workshop through agencies such as TETFUND. Gender should be considered in the adoption of M-learning technology, authorities of tertiary institutions should adopt strategies that are gender sensitive while planning to integrate Mlearning technology. Also, lecturers irrespective of their area of specialization should be given equal opportunity to integrate and u
The optimized probabilistic recommendation model in exposure bias

Recommendation models play a significant part on the internet. They combine user and information data to create personalized recommendations for various users. But this may be hidden by bias. Exposure bias is a kind of bias that blurs the distinction between a disliked item and an unshown one that may be likable. Countless research has been done to minimize this kind of bias. Our research will focus on using a new algorithm called ExpoMF++", an enhanced version of Exposure Matrix Factorization. This enhancement is done in two ways: replacing the simple dot product with neural collaborative filtering and adding an optimization with the Gaussian mixture model. We tested this new model on different datasets of various sizes and attributes. Our model proves functional and works better than the original ExpoMF, significantly reducing problems caused by exposure bias. We then compared our model with other standard methods for exposure bias and found sound results.
Understanding the class separation process of convolutional neural networks

Extensive research shows that deep neural networks (DNNs) capture better feature representations than the previous handcrafted feature engineering, which leads to a significant performance improvement. However, it raises the question of how does the neural network spontaneously learn the intermediate representation, during the training process, to correctly separate the test data set into different categories? In this paper, based on the existing research work, we continue to take a small step towards understanding the dynamics of convolutional neural networks (CNN). Specifically, we model the test data set as a relationship graph, and each intermediate layer representation learned by CNN will transform the relationship graph correspondingly. Through these continuous transformations, we investigate the class separation process of CNN from two perspectives: 1) show the evolution of the degree of correlation between samples through the histogram of similarity between vertices; 2) by visualizing and quantifying the degree of separation (i.e., modularity) of the important relationship subgraph, we can show the contribution of each convolution layer of CNN to class separation. In the preliminary experiment, it can be found that: 1) each convolution layer of CNN gradually reduced the similarity of most edges between the samples to a very low level, that is, the dense relationship graph gradually evolved into a sparse graph; 2) the remaining important relationship subgraph consist of edges with high similarity shows evident modularity; 3) both visualization and quantification results show that the modularity of intra-class subgraph increases when the layers go deeper. Moreover, the degradation and plateau in the modularity curve reveal the existence of redundant layers. In this paper, we reveal some more in-depth dynamics of CNN, and introduced another modularity, which is widely used as the theoretical guidance tool of layer pruning. It can save more model parameters without losing the accuracy of classification.
Representation learning with CGAN for casual inference

Conditional Generative Adversarial Nets (CGAN) is often used to improve conditional image generation performance. However, there is little research on Representation learning with CGAN for causal inference. This paper proposes a new method for finding representation learning functions by adopting the adversarial idea. We apply the pattern of CGAN and theoretically demonstrate the feasibility of finding a suitable representation function in the context of two distributions being balanced. The theoretical result shows that when two distributions are balanced, the ideal representation function can be found and thus can be used to further research.
Formal Methods for an Agile Scrum Software Development Methodology

Efficient, high-quality software systems embodying dependable methods are in high demand, which has led to a wide range of competitive market solutions. One effective technique that arguably has excelled above others is the Agile Software Development Methodology (ASDM). Agile approaches’ capacity to produce software in a way that is flexible to changes is the main factor that makes them preferable. Scrum, a recommended Agile methodology, prioritises feature coverage and project structure. Because iterative methodologies encourage engagement from cross-functional teams, including consumers, Agile provides flexibility in responding to change. However, achieving methodological efficiency is insufficient while developing software; high-quality software should be achieved with equal consideration. Formal Methods (FMs), which are mathematically based techniques, can offer highly dependable software but suffer from a steep learning curve in mastering the underlying discrete mathematics and logic. This research investigates the extent to which FMs may be embedded in traditional Agile as embodied by Scrum. Future work in this area would be the development of a framework for embedding FMs in Scrum, followed by a survey among software practitioners to establish the feasibility of our technique.
A Framework for Detecting AI-Generated Text in Research Publications

The use of generative artificial intelligence is becoming increasingly prevalent in creating content in various formats such as text, video, and image. However, there is a need to distinguish between content that has been generated by humans and content that has been generated by AI as misuse of these technologies can raise scientific and social challenges. Moreover, there are concerns about the reliability and comprehensiveness of the content generated by AI without human validation. This paper presents a framework for AI-generated text. The prototype implementation of the proposed approach is to train a model using predefined datasets and deploy this model on a cloud-based service to predict whether a text was created by a human or AI. This approach is specifically focused on assessing the accuracy of scientific writings and research papers rather than general text. The proposed framework is compared with recently developed tools such as OpenAI Text Classifier, ZeroGPT, and Turnitin. The results show that training a text classifier can be highly useful in detecting whether a text is written by a human or AI. The source code and dataset are made open source so others can experiment with the prototype implementation and use it for future research.
Using a Soccer team as a test bed for multi-agent systems simulation

The STMAS system is intended to imitate a soccer team and its behavior; we believe it can be used effectively as a test bed for multi-agent systems. It is constructed utilizing distributed agents that interact, communicate, and negotiate with each other to achieve the team objectives. It is based on the Jade simulation platform. The system is tested and compared to a pure soccer team using multiple MAS techniques. The results demonstrated that applying MAS techniques of negotiation and task distribution improves team performance, and STMAS is offered as an efficient test bed for new and distinct MAS techniques with varied scenario experiments. In addition, a mathematical model is created to compare the simulation results. Overall, STMAS provides a versatile and efficient MAS simulation and evaluation test bed. It is an excellent platform for comparing and evaluating various MAS approaches.
Electromechanical Model of Jigsaw

This paper studies the electromechanical model of a jigsaw mechanism. The jigsaw is powered by a battery, which drives a DC motor. The rotational motion is converted into linear motion through a Scotch Yoke mechanism. The electromechanical equations are based on energy approach using the Lagrange-equation. The Lagrange function contains the energies of the model, i.e., the kinetic co-energy of the kinematic chain and the magnetic co-energy of the inductance. As regard the non-conservative elements their virtual works are written. The formulated equations of the jigsaw model allow us to examine this force-energy relationship.
Analysis and Design of Serviced Oriented Architecture (SOA) with Service-Oriented Modeling And Architechture (SOMA) Method in Trucking Services Company (Case Study: PT Argo Kencana Transindo)

Service Oriented Architecture (SOA) is an architectural approach which uses basic construction in the form of services to support rapid system development at low cost and has the ease of managing the composition of distributed applications even in heterogeneous environments. PT Argo Kencana Transindo (PT AKT) is a company in the field of transportation services or freight forwarding. Until now, the company in carrying out its operations still uses an information system that is only integrated with computerized applications, namely Microsoft excel, Microsoft word and also a simple system but there is no information system that is integrated between departments to be able to manage a lot of existing work. For the trucking industry, fast and efficient delivery times are essential to meet customer needs and maintain competitiveness in a competitive market. Facing the opportunity of changing business process needs in the future, SOA offers adaptive and reactive to the environment and offers solutions to business complexity, system diversity and technology. This research analyzes and designs SOA using the SOMA method which is expected to contribute to making it easier to integrate with other systems and services, helping to streamline communication and data sharing throughout the supply chain, leading to more efficient and effective operations.
Analysis and Design of a Knowledge Management System Using the Fernandez Method in the IT Operation Center Unit (Case Study: PT Citilink Indonesia)

The effect of improving business quality on companies is influenced by developments in technology and information. Utilization of Knowledge Management System (KMS) is one of the efforts to improve the quality of the company's business. In a company, the role of knowledge management is very important so that the company can grow rapidly. For the application of good organizational knowledge requires a planned and systematic knowledge management. The benefits derived from implementing knowledge management in companies are that it can improve service to customers, increase efficiency in processes and work methods, increase the number of services or products and save costs and time. The study of this matter, the IT Operation Center (ITOC) unit has difficulties in terms of sharing knowledge in the company, therefore a study is needed entitled "Analysis of Knowledge Management System Design Using the Fernandez Method in the IT Operation Center Unit (Case Study: PT Citilink Indonesia)” then the application of this Knowledge Management System can provide convenience for employees who have some problems related to IT operations.
PEDAGOGICAL DESIGN: CONCEPT, PRINCIPLES, MODELS

The article describes the issues of developing the learning process through digital technologies. The concept of" pedagogical design" is analyzed, the definitions given to this term are differentiated, and the basic principles are described. Several samples of foreign models necessary for the development of pedagogical design are given. In particular, the specific features and effectiveness of the ADDIE model in education are analyzed. A model of pedagogical design of a course consisting of 4 modules based on the ADDIE model is shown. Also, the pedagogical designer classifies the tasks to be solved and defines them. Reigeluth identifies three main characteristics that meet all the principles of pedagogical design theory. In the article, the concept of pedagogical design is considered, first of all, the creative activity of a teacher in creating, transforming and accompanying an information and educational environment in which the student is convenient to develop his psychological individual characteristics and achieve high results. And, secondly, this is the direction of pedagogical science associated with the study and development of strategies, learning scenarios and the creation of conditions for managing educational events with the help of various tools that ensure the mandatory achievement of the set goal with successful training. The article presents the structure and content of pedagogical design in the course of training from the author's point of view.
Online Learning of Bayesian Classifiers with Nonstationary Data Streams

Article Online Learning of Bayesian Classifiers with Nonstationary Data Streams Peng Wu 1,2,*, and Ning Xiong 1 1 School of Innovation, Design and Engineering Mälardalen University, Västerås 721 23, Sweden 2 Department of Computer Engineering, Taiyuan Institute of Technology, Taiyuan 030008, China * Correspondence: 14112078@bjtu.edu.cn Received: 31 March 2023 Accepted: 13 July 2023 Published: 26 September 2023 Abstract: The advancement in Internet of things and sensor technologies has enabled data to be continuously generated with a high rate, i.e., data streams. It is practically infeasible to store streaming data in a hard disk, and apply a traditional batch learning method to extract a relevant knowledge model from these data. This paper studies online incremental learning with data streams, in which one sample is processed at each time to update the existing model. For the learning target, the Bayesian classifier is adopted which is a computationally economical model of easy deployment for online processing in edges or devices. By using the individual new example, we first present an online learning algorithm to incrementally update classifier parameters in a way equivalent to the offline learning counterpart. In order to adapt to concept drifts in nonstationary environments, the proposed online learning algorithm is improved to enable recent examples to be more impactful during the sequential learning procedure. Preliminary simulation tests reveal that the improved online learning algorithm can lead to faster model adaption than the unimproved online algorithm when the data drift occurs. In case of presumed stationary data streams without drifts, the improved online algorithm is proved to be competent by performing at least as good as (sometimes, even better than) the unimproved algorithm.
The Role of TOEFL Preparation Courses in Improving Test Score

The study analyses the implementation of TOEFL Preparation and provides conclusions and suggestions to improve participants' ability to face the TOEFL test. In the study, 40 participants participated in the implementation of TOEFL preparation courses which consisted of three parts, namely listening, structure, and reading. The analysis results showed that the average TOEFL score of the participants was 448, with the highest score reaching 540 and the lowest score of 376. Although the average score met the minimum requirements at IBIK 57 Campus, there were participants who did not reach the standard. Suggestions included individual coaching, increased listening practice, strengthened knowledge of grammar and structure, reading comprehension strategies, as well as encouragement for self-study and use of additional resources.
English Teachers’ Strategies in Managing Large Classes

This study was to find out the teachers’ way in managing large classes and to know what strategies that used by the teachers when teaching the large classes. The design of this study is qualitative method. This study involved two English teachers at MTsN 3 Banda Aceh. The data of this study were collected through observation and interview. To analyze the data, Miles and Huberman’ concepts was applied. The finding of this study demonstrated that that the teachers of MTsN 3 Banda Aceh managed large class by applying the proper strategies to ease at teaching and controlling large number of students effectively. The implemented strategies by teachers included (1) planning the lesson plan; (2) creating the comfortable classroom; (3) grouping work and forcing discussion; and (4) making rules and providing learning media. It is suggested that teachers should employ the appropriate strategies in order to be able to manage a large class, so that they could keep students engaged in teaching and learning process.
The Impact of Practicing Social Intelligence in Enhancing Organizational Excellence: A Case Study in the Jordanian Civil Status and Passports Department

The study aimed to reveal the impact of the practice of social intelligence on organizational excellence in the Jordanian Department of Status and Passports. The study population consisted of all senior and middle leaderships, and the study relied on a comprehensive survey of (350) respondents to collect data. After conducting the analysis of the study data and its hypotheses، the study concluded that there is a statistically significant effect of social intelligence in its dimensions on organizational excellence. The study recommended promoting organizational excellence and linking it with excellence, goals and performance results on the short and long terms, as well as expanding the use of information technology and electronic transformation to maintain its ability to reinforce organizational excellence.
The Impact of Ethical Leadership in the Relationship between the Disclosure of Social Responsibility and Financial Performance in Jordanian Public Shareholding Industrial Companies

This study aimed to identify the impact of ethical leadership in the relationship between the disclosure of social responsibility and financial performance in Jordanian Public Shareholding industrial companies. The study population consisted of all of the (53) Jordanian Public Shareholding industrial companies listed in Amman Stock Exchange. To achieve the objectives of the study, a questionnaire was developed and distributed to (237) financial managers, heads of accounting departments, internal control managers, and internal auditors in these companies. As (181) questionnaires were retrieved, (169) of them were valid for analysis. In order to test the hypotheses, the structural equation model (PLS-SEM) was used.&#x0D; The study reached a number of results the most important of which is that ethical leadership has a positive impact on the relationship between disclosure of social responsibility and financial performance in Jordanian Public Shareholding industrial companies. Based on the results of this study, the researchers recommended many recommendations, the most important of which are: increasing the direction of the Jordanian Public Shareholding industrial companies by promoting disclosure of the social responsibility activities for environmental protection, as well as the necessity for the companies’ management to maintain positive relations with their subordinates and all employees. Additionally, the researchers recommend that the managements of these companies increase employee motivation and participation in order to improve the performance and productivity that they seek. Moreover, the researchers recommend conducting more studies on the impact of ethical leadership on the relationship between the disclosure of social responsibility and financial performance in other sectors and comparing their results with those in this study.