Reviewerly/exHarmony huggingface dataset:
A Bio-Inspired Method For Breast Histopathology Image Classification Using Transfer Learning

Breast cancer is one of the deadly cancer among the female population, and still a developing area of research in the field of medical imaging. The fatality rate is more in patients who are not early diagnosed and are given delayed treatment. Hence researchers are keeping their lot of efforts in developing breast cancer detection systems that could provide accurate diagnosis in the initial stages which are relied on medical imaging. Deep learning is offering key solutions to overcome many image classification tasks. Though deep learning techniques have extended their root to many medical fields even it suffers from the problem of lack of sufficient data. Convolutional Neural Networks are more preferred for medical image classification tasks. In this paper, we propose a transfer learning method that overcomes the issue of insufficient data. We use a familiar pre-trained network VGG-16 (Visual Geometric Group) + with Logistic Regression as a binary classifier. Since hyper-parameters of every CNN has a closer impact on the performance of the entire deep learning model, our method focus on optimizing hyper-parameters using particle swarm optimization which is a bio-inspired algorithm, The proposed model performs classification of Breast Histopathology images into benign and malignant images and produce better results. We use Break His Dataset to test our method and achieve an accuracy of around 96.9%. The experimental results show that this study has improved performance metrics when compared to other transfer learning methods.
Influence of Library Marketing Strategies on the Utilization of Library Virtual Reference Service

Virtual reference services in the library needs to be more utilized during the pandemic era as library users had to go online. This research study determined the influence of library marketing strategies to the library users’ utilization of virtual reference service. The concurrent nested mixed method of research was used. Participants of the study were the 206 students at a state university in the province of Bukidnon during the school year, 2021-2022. Descriptive statistics and regression analysis were used to organize the data of the study. Findings reveal that the participants assessed as high all the library marketing strategies high, and it was also found out the utilization of library virtual reference services was rated to a high extent. Moreover, the combination of library marketing strategies significantly influenced the variability in the utilization of library virtual reference service. The study concludes that through social media, the library can encourage library users to avail of its varied information sources. Marketing strategies significantly influence the library users’ utilization. This confirms the theory of confirmation expectancy which suggests that perceptions are influenced by pre-use expectations (marketing strategies) and consequently directly impact confirmation (utilization of the library virtual services). Based from the findings, the university library may consider other forms of social media such as Google hangouts, Twitter, and YouTube to enhance its virtual services and to attract more patrons to use its services. &#x0D;
Transdisciplinary Approach Using Ensemble Learning Model approach in Machine Learning Technology to Predict and Abort Cyber-Abuse Against Women

Cyber-abuse against women has become a pervasive issue in today's digital age, posing serious threats to their safety and well-being. To combat this problem, we propose an ensemble learning model approach in machine learning technology that aims to detect and abort instances of cyber-abuse targeting women on online platforms. The proposed model combines the machine learning techniques of both Support Vector Machine (SVM) and Random Forest (RF) algorithms to enhance performance and generalization. An ensemble model is constructed by combining the predictions of individual base models using aggregation techniques such as LightGBM (Light Gradient Machines). The trained ensemble learning model is integrated into a real-time monitoring system that continuously analyzes social media content. This system identifies and flags potentially abusive or harassing content directed towards women. By combining technological advancements, human expertise, and community engagement, our ensemble learning model approach offers a comprehensive solution to predict and prevent cyber-abuse against women, fostering safer and more inclusive online spaces. Additionally, our approach emphasizes the importance of jurisdictional considerations, and punitive measures implemented in different jurisdictions.
Development of Expert System Application to Detect Chicken Disease using the Forward Chaining Method

Chicken is the most widely kept and consumed poultry in Indonesia. Due to the large population of poultry, a variety of diseases have also emerged, from minor diseases to diseases that can kill chickens and infect humans. As a result of these diseases, there are implications for the losses suffered by chicken farmers. Most farmers find it very difficult to identify chicken diseases due to their lack of knowledge. On the other hand, expecting treatment from a veterinarian or expert is very limited and expensive. Therefore, a system is needed that can easily help chicken farmers detect diseases in their pet chickens. This research aims to build an expert system to detect chicken diseases by applying the forward chaining method. The expert system is implemented as a web-based application. The research stages start with identifying problems, collecting data, creating a knowledge base and production rules, building applications, and getting results. The results showed that the forward chaining method provides convenience in detecting chicken diseases. This is proven by only selecting the symptoms of the disease that appear, and then the application will provide conclusions regarding what type of disease is being suffered by chickens. In addition, this application also provides information related to ways of handling and control that can be done to overcome the chicken disease. Hopefully, the results of this research can facilitate chicken farmers in identifying and handling diseases effectively and efficiently.
Pengaruh Pembelajaran Literasi Dengan Aplikasi Quizizz Terhadap Kemampuan Literasi Siswa di MI Miftahul Ulum Pandanarum

Learning literacy with the quizizz application is considered fun and engaging for students at Islamic elementary school Miftahul Ulum Pandanarum, where the application can motivate students, and align with the opinion of the grade V teacher that the literacy learning implemented feels interesting and not boring. Therefore, one of the task of teachers is to improve student’s literacy skills, which can be done by using the quizizz application. This application enables the enhancement of student’s literacy skills.&#x0D; The main objective of this research is to investigate the impact of literacy learning with the quizizz application on student’s literacy skills. Non equivalent control group design with a quantitative approach is used in this study, involving a population of 25 participants. The data sampling technique used in this research is a written test (questionnaire). Based on the data analysis conducted, the average score before implementing the literacy learning treatment with quizizz application was 42,52. Meanwhile, after the literacy learning treatment using quizizz application, the score obtained was 76,20. Therefore, it can be concluded that literacy learning with quizizz application has an effect on student’s literacy ability.
Research on the Impact of Financial Resources on Industrial Growth in Sub-Saharan Africa

This study contributes to the literature on financial efficiency and industrial growth. We use the Autoregressive Distributive Lag (ARDL) method to find the impact of institutional financial quality on the industry sector's growth in 14 Sub-Saharan African countries from 1990 to 2020. Our results show that only gross fixed capital formation has long-run variables and a significant (at 1% level) causal effect on the magnitude of industrial value added. As for the short run, only credit has an effective (at a 1% level) causal impact on the magnitude of industrial value added. The error correction (EC) term shows a joint significance with the causality of all variables in the long term.
The Impact of Digital Human Resources Management Practices (DHRMPs) on Administrative Empowerment: Field Study in Telecommunications Companies in Jordan

The study aimed to analyze the impact of digital human resource management practices (DHRMPs) on administrative empowerment (AE) in Telecommunications Companies in Jordan (TCJs). The descriptive analytical approach and SPSS statistical package were relied upon in this study. Study population consisted of all (350) officials with leadership or supervisory positions in telecommunications companies (Zain, Orange, and Umniah) in Jordan. By adopting the comprehensive field survey method in collecting data, total of analyzed valid questionnaires was (260). The main study results are: The level of application of both DHRMPs and AE in TCJs had reached a high degree; there is a statistically significant impact of DHRMPs on AE. The study recommended the importance of continuing to maintain these levels.
Application and Methods of Deep Learning in IoT

In this talk, we provide a comprehensive overview of how to use a subset of advanced AI techniques, most specifically Deep Learning (DL), to bolster analytics as well as learning in the IoT URL. First and foremost, we define a development environment that integrates big data designs with deep learning models to promote rapid experimentation. There are three main promises made in the proposal: To begin, it illustrates a big data engineering that facilitates big data assortment in the same way that businesses facilitate deep learning models. Then, the language for creating a data perspective is shown, one that transforms the many streams of large data into a format that can be used by an advanced learning system. Third, it demonstrates the success of the framework by applying the tool to a wide range of deep learning use cases. We provide a generalized basis for a variety of DL architectures using numerical examples. We also evaluate and summarize major published research projects that made use of DL in the IoT context. Wonderful Internet of Things gadgets that have integrated DL into their prior knowledge are often discussed.
A Comparative Analysis of Grade 8 Learners' Reading Proficiency Levels: Post-test Performance from the Previous Year and Pre-test Results of the Current School Year

Reading is essential in acquiring knowledge, expanding vocabulary, and enhancing critical thinking abilities.It serves as a gateway to information and empowers individuals to engage with various forms of literature, opening doors to new worlds, perspectives, and ideas.This study aimed to determine the Reading Proficiency level and significant difference between Posttest Performance from the Previous Year and Pre-test results of the Current School Year of Grade 8 learners.The research employs a quantitative method to obtain a holistic understanding of the reading skills and competencies of Grade 8 learners.Findings revealed that post-reading of Grade 8 students last academic year is at the instructional level.Meanwhile, their prereading performance this academic year is also at the instructional level.The study also reveals that there is a significant difference between Post-test Performance from the Previous Year and Pre-test results of the Current School Year of Grade 8 learners.Moreover, learners have not yet reached the independent level.Furthermore, the study recommends that reading coordinators and reading teachers from school should intensify the intervention mechanism to improve reading and comprehension among students.More so, activities stipulated in Phil-IRI should be implemented with commitment among teachers to ensure proficient reading results among learners.
Intersections between spanish vocal technique in singing and aspects of voice physiology

The Spanish Vocal Technique of Singing, taught in Brazil by Prof. Victor Olivares in the period from the 60s to 2008, and by the author of this article, from 1990 to the present, offers specificities linked to aspects of voice physiology, in the work of Ph.-E. Souchard (1989a and 1989b), also compared to other vocal techniques such as French and German. In this article we discuss these peculiarities, dialoguing with information present in the work of Richard Miller (1997) about vocal techniques of different nationalities.
Classifier Model using Artificial Neural Network

When it comes to AI and ML, precision in categorization is of the utmost importance. In this research, the use of supervised instance selection (SIS) to improve the performance of artificial neural networks (ANNs) in classification is investigated. The goal of SIS is to enhance the accuracy of future classification tasks by identifying and selecting a subset of examples from the original dataset. The purpose of this research is to provide light on how useful SIS is as a preprocessing tool for artificial neural network-based classification. The work aims to improve the input dataset to ANNs by using SIS, which may help with problems caused by noisy or redundant data. The ultimate goal is to improve ANNs' ability to identify data points properly across a wide range of application areas.
FuzzyClass: A family of Fuzzy and Non-Fuzzy probabilistic-based classifiers

This paper presents a package written in the language R for classifiers based on Naive Bayes and Fuzzy Naive Bayes named FuzzyClass.This R package implements eight fuzzy classifiers, with option for using the classical ones too.An example in which the Fuzzy Gaussian Naive Bayes method is presented.
Pdf-Based Digital Comic Innovation Class V Human Respiratory System Material

This research is motivated by the limitations of learning media in science learning content, so students need help understanding the material. This study aims to examine the feasibility and test the effectiveness of PDF-based digital comic media material on the human respiratory system. This type of research is Research and Development (R&amp;D) with the Borg and Gall development model. The subjects of this study were fifth-grade students at SD Negeri 2 Pagersari with 36 students. Data collection techniques using observation, interviews, documentation, questionnaires, and tests. Data analysis techniques use product feasibility and initial and final data analysis (t-test and N-gain test). The research results show that; (1) it is appropriate to use the percentage of material experts and media experts who get percentages of 87% and 100%, as well as teacher and student responses of 97% and 93%; (2) it is effective in increasing student learning outcomes with the results of the t-test showing a significance value (Sig.) of the variable results of the Pretest and Posttest in class V SD Negeri 2 Pagersari is 0.001, so H0 is rejected. At the same time, the results of the N-gain test analysis showed 64.526 with the medium criteria category. This study concludes that PDF-based digital comic media has proven to be feasible and effective as a learning medium and can improve science learning outcomes on the material of the human respiratory system for class V SD Negeri 2 Pagersari.
The Implementation of ICT School Based in Indonesia: The Benefits and Challenges

Nowadays, the concept of learning is becoming modern that linear with the use of information and communication technology (ICT) which is programmed to be involved in all levels of Indonesia education system from Kindergarten to Higher Education. This research is library research that aims to to discuss about the benefits and challenges of ICT school-based implementation in Indonesia. As a country with majority schools located in rural areas, Indonesia has to determine the obstacles endurance and reduce the gab exists. This paper discusses on both sides of the ICT implication which are the benefits and challenges sides. Then, the recommendation is offered for those parties that have close relation to the application of ICT school based can work together to give support.
IMPROVEMENT OF THE LEARNING EXPERIENCE IN ENGINEERING COURSES THROUGH THREE SUCCESSFUL CASES OF IMPLEMENTATION OF EMERGING TECHNOLOGIES IN THE CLASSROOM

The challenges that arise in the teaching-learning process, added to unpredictable environments for its development, have led teachers to develop innovate new ways of teaching inside and outside the classroom, as well as with flexible digital models that allow distance learning. Whatever the innovation, it must allow the student to have a great experience in their learning process, as well as meaningful learning. Given these circumstances, the use of technologies that help and facilitate the learning path for students has become more recurrent and essential. But it cannot be any type of technology but rather those whose implementation is viable in terms of implementation, intelligence, coordination, control, policies and, of course, economically: Technologies that, complemented with teaching techniques such as gamification, have an efficient impact on the teaching process, making it more productive in terms of the use of resources and the achievement of objectives such as the development of skills. This study presents an in-depth analysis of three successful cases of technology implementation for education within the teaching model of our university, which focuses on the student and favors the development of competencies. In each of these experiences, the results obtained in the learning and development of students' skills will be shown and compared. The cases to be presented were implemented during the pandemic period in engineering school courses. The applied technologies were: Virtual reality, Simulation and Telepresence. The results and their impact were statistically validated to record their great contribution to the teaching-learning process. Having validated these technologies, their adoption is highly recommended to apply them for the benefit of education at different levels and areas.
A Review of the National Cybercrime Law and its Attendant Impact on National Security in Nigeria

Abstract: This paper is a study on the issues in cybercrime, offences and penalties, and challenges that provoke cyber policy established in Nigeria. It seeks to define what cybersecurity and cybercrimes are from the perspective of the National cybercrime law. The focus of this study, however, is to highlight crimes or offences considered to have an impact on national security, the related issues, the effects of cybercrimes, challenges, and prospects. The study concludes that the leading causes propelling Nigerians to indulge in cybercrimes are disorientation and the rate of unemployment
Science Education for Preschoolers Based on Superstar Learning Access Course Blended Teaching Practice

The rapid development of information technology is changing and even subverting the traditional mode of education and teaching practice. Mixed teaching is an effective way to reform the teaching mode, realize resource sharing and improve the quality of talent training. Based on the concept of hybrid teaching definition, this paper to master learning theory and active learning theory as the theoretical basis, based on super learning online platform of preschool children science education course hybrid teaching practice, further discussed before class, class, after class three stages of teachers and students, in order to provide the experience of mixed teaching reform.
SCIENTIFIC THESAURUS OF THE PROBLEM OF FORMATION OF METHODICAL COMPETENCE OF FUTURE TEACHERS OF ART SCHOOL IN THE PROCESS OF VOCAL TRAINING

The article highlights the results of scientific research of the state of problem of forming the methodical competence of future teachers of art school in solo singing classes in modern pedagogical science.The purpose of the article is to define the scientific thesaurus of our research, which presents key categories and related concepts, which are divided by meaning and relationship into three semantic groups.The research methodology consists of theoretical methods of analysis, systematization, classification, comparison and generalization of scientific works on the formation of professional, specialty and methodical competence of future specialists, pedagogues, teachers of musical art.It was found that the vocal and methodical competence of future teachers of art school includes the ability to form correct vocal and technical skills in students, effective, natural development of the singing voice.In the course of the research, it was determined that the methodical culture of future teachers of art school is an integral personal formation that is part of the professional and pedagogical culture of the vocal teacher and contains specific vocal and methodical knowledge, abilities, skills, methods of activity which are comply to the traditions of the vocal school and universal human values and social norms.The methodical mastery of art school teachers, is interpreted by the author as an important functional component of methodical competence, which ensures the effective use of vocal technologies and methods of teaching solo singing in pedagogical activities, the ability to combine and integrate teaching methods and techniques to achieve the maximum possible learning result.The analysis of scientific literature contributed to clarifying the essence of methodical creativity of future teachers of art school, which consists in the production of new methodical ideas, creative selection of methods and techniques in accordance with pedagogical tasks, development of unique, original methods, technologies and methodical systems of teaching solo singing.The author specifies that the methodical training of future teachers of art school in solo singing classes is aimed at the formation of
The Law of Nature, which Makes it Necessary to Develop the Fundamental Science of Cybernetics

Understanding the environment ultimately boils down to the exploration of the laws of nature. Many years of experience have shown that not all of these laws are currently within the scope of scientists' attention. This law produces the development of fundamental sciences: physics, chemistry, botany, biology, including cybernetics, thereby defining its subject of research. This law and its connection with the scientific achievements of V.M. Hlushkova are considered in this work. Keywords: cybernetics, physics, chemistry, botany, biology, problem, fundamental.
Negotiating Implicit Meaning on the Internet: A Case Study

Negotiating the meaning of words and sentences is a fundamental part of verbal interactions. This essay aims to examine a particular type of negotiation, that relating to the content of presuppositions, which are placed, together with the implicatures, in the phenomena of implicit communication. The research made use of automatic tools for querying empirical data: a database of lexical presupposition triggers for the Italian language, including approximately 20,000 entries (simple lexemes and multiword expressions) and the corpus of Computer Mediated Communication Web2Corpus_it, specifically in its public chat sections, which contains about 300,000 tokens. Quantitative data are provided in relation to the pragmatic function of negotiation, its initiation stage, and the types of presupposition triggers involved. In the context of the media characteristics of chats, which must be considered to discuss the results, the items of implicit meaning negotiation provide corpus-based evidence of the conditions under which presuppositions are available to the receiver’s monitoring of the meaning and consequent possible reaction.