Reviewerly/exHarmony huggingface dataset:
Local Search Element Decomposition Method to Solve Integer and m-Integer Problems

Integer problems are non-deterministic polynomial-time-hard and can be solved in polynomial time. However, the solution to large problems requires an unreasonably long time. This paper highlights the signifi cance of developing and modifying the local search element decomposition method (LSEDCM) for accurately and promptly solving general integer and m-integer problems. The study involves two parts: creating and developing the algorithm by applying the LSEDCM and modifying the LSEDCM, genetic algorithm, and ant system. Results obtained using this algorithm were then compared with the exact and approximated solutions in terms of their accuracy, number of steps, and solution time. It was found that general integer and m-integer problems involving 2–30000 variables could be effectively solved. For the general integer problem, the average difference from the exact solution was 0.37%; it took 91.28% fewer steps and 29.29% less time to solve the problem. The average difference from the approximated solutions for the modifi ed genetic algorithm (MGA) and modifi ed ant system (MAS) was 1.47 and 2.16%, respectively. For an m-integer problem, the average difference from the exact solution was 0.57%; it took 90.60% fewer steps and 49.33% lesser time to solve the problem. The average difference from the approximated solutions for the MGA and MAS was 1.58 and 2.69%, respectively. Compared with approximated solutions, the LSEDCM obtained the best solution for the large problems. It is thus proven that the LSEDCM could be used to solve large integer problems in a shorter time compared with m-integer problems, which are more complex and intrinsically require a longer time to obtain a solution.
The Education of Gifted Pre-School Children Using Information Communication Technology: the Opinions of Teachers

The 21st century is identified in the country’s strategic documents as a century of rapid technological, climatic and economic change, and countries must not be afraid of innovation and knowledge of the world through information technology. According to strategic documents, the education of gifted children is also one of the country’s priorities. Gifted pre-school children need to develop and continuously improve their abilities, and the stimulation of these abilities can be enhanced by information and communication technologies. The article analyses the educational possibilities for gifted pre-school children using information communication technology, the characteristics of gifted pre-schoolers, and the possibilities for the identification of gifted pre-schoolers. The study suggests that gifted pre-school children are educated in an individualised way according to their needs, they are identified by their abilities which stand out from their peers, information communication technologies are used to diversify the education of gifted pre-school children, and that the biggest problem educators face while developing gifted children is the lack of information and the lack of communication tools.
Detecting Emotions from Illustrator Gestures—The Italian Case

The evolution of computers in recent years has given a strong boost to research techniques aimed at improving human–machine interaction. These techniques tend to simulate the dynamics of the human–human interaction process, which is based on our innate ability to understand the emotions of other humans. In this work, we present the design of a classifier to recognize the emotions expressed by human beings, and we discuss the results of its testing in a culture-specific case study. The classifier relies exclusively on the gestures people perform, without the need to access additional information, such as facial expressions, the tone of a voice, or the words spoken. The specific purpose is to test whether a computer can correctly recognize emotions starting only from gestures. More generally, it is intended to allow interactive systems to be able to automatically change their behaviour based on the recognized mood, such as adapting the information contents proposed or the flow of interaction, in analogy to what normally happens in the interaction between humans. The document first introduces the operating context, giving an overview of the recognition of emotions and the approach used. Subsequently, the relevant bibliography is described and analysed, highlighting the strengths of the proposed solution. The document continues with a description of the design and implementation of the classifier and of the study we carried out to validate it. The paper ends with a discussion of the results and a short overview of possible implications.
Preface to the Special Issue “Natural Language Processing (NLP) and Machine Learning (ML)—Theory and Applications”

Natural language processing (NLP) is one of the most important technologies in use today, especially due to the large and growing amount of online text, which needs to be understood in order to fully ascertain its enormous value [...]
Relationship between convenience of online education, academic achievement, and learning satisfaction

Objectives The purpose of this study was to investigate learners' perception and relationship with convenience of online education, academic achievement, and learning satisfaction and to help develop more effective online education methods by emphasizing the importance of convenience. Methods For an empirical survey according to the purpose of this study, a Google form-based questionnaire was conducted for beauty majors nationwide from March 24, 2021 to June 20, 2021, and a total of 402 questionnaires were collected and used as final analysis data. The collected data were analyzed through SPSS 21.0, and frequency analysis, factor analysis, reliability analysis, and multiple regression analysis were performed. Results An 83.3% of the gender in the survey was women, in the age group of 20s, and a vocational college garduates (including enrolled students) as their highest level of achievement in education. The reason for online beauty education for beauty majors was efficient use of time, and they responded positively to convenient learning methods and time savings in online education. In addition, as the convenience of online education increased, the practical and theoretical achievement, which are sub-factors of academic achievement, was increased. Also, followed by the increase of convenience, the learning satisafaction increased. Conclusions This study investigated the relationship between convenience, academic achievement, and learning satisfaction of beauty major learners, and as a result, the relationship was found to be significant in the effect of independent variable, an academic achievement and learning satisfaction. Therefore, in order to increase the academic achievement and learning satisfaction of beauty majors in online education, the convenience of online education must be accompanied, which is an essential element of sustainable beauty major online education&#x0D;
The Effect of the Learner Participation-Centered Discussion Class on the Science Teaching Efficacy, Communication Capability, and Problem Solving Ability of Pre-service Early Childhood Teachers

Objectives The purpose of this study was to explore the effect of the learner participation-centered discussion class on the science teaching efficacy, communication capability, and problem solving ability of pre-service early childhood teachers. Methods The subjects of this study were 32 students enrolled in a four-year early childhood education program. The learner participation-centered discussion class were carried out through the science education class (45 hours) during the first semester in 2021. Data were collected from science teaching efficacy, communication capability, and problem solving ability rating scales. Results The results of quantitative analysis were as follows. First, the learner participation-centered discussion class brought statistically significant difference to pre-service early childhood teachers’ science teaching efficacy(both science teaching outcome expectancy and science teaching self-efficacy). Second, the learner participation-centered discussion class brought statistically significant difference to pre-service early childhood teachers’ communication capability(especially in message converting capability out of all sub-domains). Third, the learner participation-centered discussion class brought statistically significant difference to pre-service early childhood teachers’ problem solving ability(especially in the production of alternative resolution method, and the implement and confirmation of resolution method out of all sub-domains). Conclusions Therefore, the learner participation-centered discussion class is the meaningful teaching method to improve the science teaching professionality and problem solving ability of pre-service early childhood teachers.&#x0D;
Readability of Medication Package Inserts Accompanying Prescription Drugs and Conformity of the Package Inserts Information with Regulatory Requirements

Background: Medication package inserts (MPIs) provides patients with appropriate information on the rational use of drugs.This study evaluated the level of conformity of MPIs with the regulatory drug labelling requirements and determined the readability of selected prescription MPIs.Methods: One hundred and fifty-six MPIs of commonly used and prescribed antilipidemics, anticonvulsants, anti-diabetes, antiarthritis and antihypertensives in Nigeria were retrieved from four pharmacies.The MPIs were evaluated on the availability of 20 items drug labelling requirements for prescription drugs by the National Agency for Food and Drug Administration and Control (NAFDAC).The readability of 31 randomly selected MPIs was assessed with seven readability measures.Primary outcomes were percentage conformity with the labelling requirements and reading grade level of the MPIs.Secondary outcomes were the MPIs sentence characteristics.Results: The percentage conformity with NAFDAC drug requirements of the MPIs ranged from 82.9% to 89.6%.All the MPIs included information on active ingredient(s), adverse drug reactions, and indications.Few MPIs, 46.8% had section on product net content and 53 (34.0%) omitted information on overdose.The reading grade level for the MPIs was 14.55 ± 1.71 (undergraduate level).Most of the MPIs, 25 (80.6%), were very difficult to read.Conclusion: The percentage conformity of the MPIs with NAFDAC drug labelling requirements was high though few vital information were missing in some MPIs.Majority of the MPIs were very difficult to read.The regulatory authority may need to optimize MPIs readability and conformity of content with drug labelling requirements prior to marketing.
Mathematical Model of Short Circuit Fault Diagnosis in management and collaborative System Based On Improved SOM Neural Network

The existing mathematical model for short-circuit fault diagnosis of management and collaborative system has the problem that the session characteristics of communication link are not clear, resulting in the slow upload speed of fault data. In order to solve this problem, a short-circuit fault diagnosis mathematical model of communication system based on improved SOM neural network and the innovative strategies also management and collaborative system is describe in this paper. Firstly, the early warning information of the system is collected, combined with the repeated information, the session characteristics of the communication link are extracted by using the quasi Newton algorithm, the mutually orthogonal physical resource blocks are transformed, the short-circuit fault diagnosis mode is optimized, the parameters of the components to be detected are estimated, the feature space vector is truncated, and the mathematical model is established by using the improved SOM neural network. Experimental results: the average value of the management and collaborative system short-circuit fault diagnosis mathematical model designed in this paper is 8.244 Mbps, and the average values of the other two management and collaborative system short-circuit fault diagnosis mathematical models are 5.756 Mbps and 5.863 Mbps respectively. The results show that the designed mathematical model for short circuit fault diagnosis of management and collaborative system has high application value.
novel deep neural network framework for biomedical named entity recognition

With the dramatic improvements in the field of bio-informatics, extracting information from text and analyzing the association between the entities has received more attention in the past few years. Entity Recognition (ER) meant to extract and recognize the entities from any text. Biomedical Named Entity Recognition (BNER) gets more and more attention from the researchers since it is a fundamental task in biomedical information extraction. Various methods has been proposed to perform the task of BioNER. Different kind of approaches are dictionary based, rule based approaches, traditional machine learning approaches that combines supervised and unsupervised methods and neural network based approach. The state-of-art systems previously adopted various supervised machine learning methods Hidden Markov Models (HMMs), Maximum Entropy Markov Models (MEMMs), Support vector machines(SVM),Structural Support Vector Machines(SSVMS),Conditional Random Fields(CRF) to derive semantic and syntatic features from annotated datasets. However, CRF is one of the most successful method used for NER and it has obtained finest result because of the robustness and ability for sequence lebelling task. Recently, studies have demonstrated the application of deep learning based approaches for biomedical named entity recognition (BioNER) and shown promising results.
comprehensive study based on societal question and answer system using natural language processing with topic modelling for job assistantship in the world industry

This breakthrough study explores public opinion on technical words or topics using data from social media. Individuals seeking work assistance must consider public opinion on the existence of terminological or technical obstacles, as well as their impact on the environment and society. Public assistance is also required for the execution of legislation and mitigation programmes. A public opinion study is required to better understand the social environment and social processes. Researchers are paying special attention to social media data because it provides extremely significant information on public perceptions and responses to conflicting socio-technical terminology or issues, such as quorums, stack overflows, and yahoo! It also responds to Twitter and other social media platforms, and it's frequently used to monitor and analyze how society reacts to natural and social calamities. Search for keywords or topics in topic models to identify distinct topics to get the most out of social media data. In classic topic models, users may provide an erroneous number of subjects, resulting in unsatisfactory grouping results. For data retrieval and cluster trend identification in these scenarios, exact representations are essential.
Android-Based Mathematics Learning Media Development Research: A Bibliometric Analysis using VosViewer

The purpose of this research is to determine the title and abstract about Development Of Android Mathematics in 2017-2022. The research data is taken from articles published online through Google Scholar with the keywords development of mathematics. Methods Data collection is done by checking and recording all data information about the number of articles, citations, and authors. The analysis used is full counting in the VOSViewer application. The total number of articles sampled in this study were 1000 articles with the technique of analyzing the image results obtained from the VOSviewer application, including Network visualization, Overlay visualization, and Density visualization. By using VosViewer researchers can visualize several analyzes of a research that researchers want to do Keywords: bibliometrics, mathematics development, development of android mathematics. Abstrak: Tujuan dari penelitian ini adalah untuk menentukan judul dan abstrak tentang Development Of Android Mathematics pada tahun 2017-2022. Data penelitian dikutip dari artikel yang diterbitkan secara daring melalui Google Scholar dengan kata kunci development of mathematics. Metode Pengumpulan data dilakukan dengan memverifikasi dan merekam semua data informasi tentang jumlah artikel, kutipan dan penulis. Analisis yang digunakan yakni penghitungan penuh (full counting) dalam aplikasi VOSviewer. Total artikel yang dijadikan sampel pada penelitian ini adalah sebanyak 1000 artikel dengan teknik menganalisis hasil gambar yang diperoleh dari aplikasi VOSviewer, diantaranya Network visualization, Overlay visualization, dan Density visualization. Dengan menggunakan VOSviewer peneliti dapat memvisualisasikan beberapa analisis tentang suatu riset yang ingin dilakukan oleh peneliti. Kata kunci: bibliometrik, mathematics development, development of android mathematics. DOI: http://dx.doi.org/10.23960/jpmipa/v23i2.pp842-852
Digital Computation on Architectural Design Process in Universitas Multimedia Nusantara

In the digital era, BIM (Building Information Modelling) has enriched and transformed Architectural pedagogy, particularly in the architectural design studio.It has challenged students during design activity, either it helps or limits their design.We review students' achievements that employ BIM as part of the architectural design process.In this case, BIM parameters based on The International Union of Architects (UIA) revised edition 2017 include creative process, analyses and strategies for the design process, technical knowledge, and ability to communicate ideas such as drawing, modelling and documentation.This research focuses on the architectural design studio of the fourth semester of undergraduate study in Universitas Multimedia Nusantara (UMN).We use the correlational method to comprehend students' performance in the digital design process.First, we observed and followed students' design processes.Second, we collected final grade data from two applied BIM courses, Architecture Design 3 and Digital Computation 2. This research aims to assess the influence of BIM utilization on students' performance and achievement in the design process.The results will improve learning methods and their effectiveness in architectural design and digital computing.
Desain Dan Analisa Mekatronika Robot Fire Fighting

This research was made as a refinement of various research on fire fighting robots, which in this research emphasizes the value of improvement from electronic and mechanical designs, this robot is not controlled by anything either by remote control or by joystick, this robot moves itself from the truck. fire extinguisher to extinguish the fire based on the sensitivity of the existing sensor in detecting the presence of a fire point, as well as the navigation system that the robot has in the form of a proximity sensor, this sensor keeps the robot able to move without obstacles in the form of walls or other objects that block the robot's pace. . In this research analysis and calculations will be carried out about the design of the equipment that will be needed. The data used are data sourced from primary or secondary data from available data from several manufacturers of the equipment needed. Based on the data analysis carried out, it can be concluded that the robot equipment from time to time will continue to experience changes and / or improvements.
PERAN PENGELOLA RUMAH BACA DALAM MENINGKATKAN MINAT BACA PADA SISWA SEKOLAH DASAR DI KOTA PONTIANAK

The title of this study is "The Role of Reading House Managers in Increasing Reading Interest in Elementary School Students in Pontianak City". The purpose of this study was to determine the role of Reading House managers in organizing activities to increase reading interest in elementary school students at Rumah Baca, efforts made by the Reading House manager to increase reading interest in elementary school students at Rumah Baca and the obstacles faced by Rumah Baca managers in increasing interest read elementary students at Pontianak Reading House. The approach used is a qualitative approach with descriptive methods. Data collection techniques used were interview techniques and documentation, with data collection tools in the form of interview guides and documentation. Based on the results of interviews and documentation that researchers have carried out proves that the manager's role influences students' reading interest in the Reading House. There are supporting factors, namely the existence of educational institutions as a place of fostering and inhibiting factors, namely the scarcity of the existence of interesting books. The effort taken is to find the cause of the low interest in reading.
Feature Selection Algorithm Recommendation for Gene Expression data with Meta Learning

Feature selection is an important step in gene expression data analysis. However, many feature selection methods exist and a costly experimentation is usually needed to determine the most suitable one for a given problem. This paper presents the application of gradient boosting and neural network techniques for the construction of meta-models that can recommend rankings of {feature selection - classification} algorithm pairs for new gene expression classification problems through the usage of learning-to-rank and collaborative filtering approaches. Results in a corpus of 60 public datasets show the superiority of these techniques in producing more useful rankings in relation to classical meta-models
Privacy Preservation of Healthcare Data in Hybrid Cloud Using a Hybrid Meta-Heuristics Based Sanitization Technique

Over the recent years, the expansion of cloud computing services enable hospitals and institutions to transit their healthcare data to the cloud, thus it provides the worldwide data access and on-demand high quality services at a cheaper rate. Despite the benefits of healthcare cloud services, the associated privacy issues are widely concerned by individuals and governments. Privacy risks rise when outsourcing personal healthcare records to cloud due to the sensitive nature of health information and the social and legal implications for its disclosure. Over the recent years, a privacy-preserving data mining (PPDM) technique has become a critical issue for the problems. Our goal is to design a privacy-preserving outsourcing framework under the hybrid cloud model. In this work we propose a Hybrid Ant Colony Optimization and Gravitational Search Algorithm (ACOGSA) to express the problem of hiding sensitive data through transaction deletion. Thus, it reduces the side effects of the hybrid cloud. Substantive experiments will be carried to compare the performance of the designed algorithm with the state-of-the-art approaches in terms of the side effects and database similarity (integrity). Over the past to sanitize the databases used for hiding sensitive information, a few heuristic approaches have been proposed. The method used for the comparison involves GA, PSO, ACO, and Firefly framework.