Reviewerly/exHarmony huggingface dataset:
FUZZY ASSOCIATIVE CLASSIFIER FOR BIG DATA APPLICATIONS

The related blueprint field melds really intriguing cycles for building solid classifiers and any of those methodologies all issues mulled over works of art on 4 top-notch levels. The thought process of this work might be a novel developmental issue for profitably gathering helpful classifiers in huge information. Comfortable supportive hoarding has not been significantly examined inside the structure, anyway familiar classifiers have wrapped up being impeccable in particular genuine space programs. we advance a helpful pivoted delicate auxiliary depiction strategy subject to the Map decrease viewpoint. The framework mishandles a particularly appropriated discretize dependent on woolen entropy for productively making padded bundles of the attributes. Zeroing in on precision, rendition multifaceted nature, assessment time, and adaptability. We spotlight that, despite the way that the correctnesses result to be comparative, the flightiness, assessed with perceive to a number of guidelines, of the classifiers made through the smooth appropriated approach is not exactly the one among the non fuzzy classifiers. the total circuit of padded understanding grams to visual assessment of agreeable association manages a successful appropriated woolen familiar classiﬁcation model-dependent at the Map diminish demeanor. The preparation assessment ﬁrst mines an unprecedented arrangement of agreeable association classiﬁcation directs by utilizing the utilization of a dispersed variant of a smooth development of the putting FP-development tally number. We show the adaptability of our strategy by means of doing selective examinations on an appropriate critical dataset. A fuzzy affiliation rule-based solicitation gadget for high-dimensional issues trouble to two or three territories to advantage a specific and inconsequential delicate standard based absolutely classifier with an espresso computational expense.
A Study on the Role of Internet Emoticons in Business Communication from the Perspective of Symbolic Interactionism

Emoticons break down the traditional text communication and spread quickly across the Internet, becoming an indispensable network communication tool. They make up for the lack of non-verbal information in Internet communication, dispel the communication gap between the disseminator and the audience. Along with the advancement of information technology, many a business communication has changed from the traditional offline face-to-face communication to the virtual online kind. In daily life, due to the ritualistic, profit-oriented and transactional characteristics of business communication, emoticons in the customer service communication of the e-commerce platform are somewhat different from personal one. This paper selects 4 typical conversation texts from Taobao customer service to support the present case study. According to Mead and Blumer's symbolic interactionism, it analyses the role of emoticons used in business conversations as well as people’s motivations behind. On the basis of analyses, it attempts to summarize the role of emoticons in business communication and the problems existing in emoticons usage. The results demonstrate that emoticons can show professionalism and business etiquette, construct a communicator's business self-image, influence interpersonal mutual understanding so as to improve the accuracy and efficiency of business communication, and enhance group identification. Keywords: role of emoticons, non-verbal expressions, symbolic interactionism, business communication, customer service
CREATING VIRTUAL REALITY USING A SOCIAL VIRTUAL ENVIRONMENT: PHYGITAL EXHIBITION AT THE MUSEUM PASSION IN SORDEVOLO

Abstract. The paper addresses the digital curation of immersive and virtual spaces for the cultural heritage sector. One of the research objectives is to define a methodological and operational workflow for developing a virtual environment designed using a social virtual environment. The use of social worlds in virtual reality (VR) is one of the possible entry points to the metaverse, understood as a way of experiencing digital reality. The possibility of creating a digital space that replicates real space offers not only the opportunity for people to gather in a virtual place but also allows designers to provide a parallel and augmented experience in terms of content.The case study aims to create the digital twin of the temporary Phygital Exhibition, which opened in July 2022 at the Sordevolo Passion Museum in the Church of Santa Marta. Unlike the permanent collection, which recounts the tradition of popular theatre in Sordevolo for the performance of the Passion of Christ, the Phygital Exhibition focuses on documenting the activity related to the design and construction of the scenography. In the virtual environment, the physical space is replicated with a low level of detail to emphasize the VR exhibition, composed of a series of panels with the possibility to interact with historical documentation, drawings, and pictures. The virtual space is also enriched by video and 3D models not available in real space, which documents the transformation of the scenography over the years.
Optimization enabled deep learning approach with probabilistic fusion for image inpainting

Nowadays, various deep learning (DL) approaches have been devised for image inpainting, which provided a substantial improvement in image quality. However, these approaches have failed to reconstruct the accurate structure of the original image. Hence, this research devised a novel and effective image inpainting approach, namely Autoregressive Flower Pollination Student Psychology Optimization (ArFPSPO). The image inpainting is carried out based on a newly devised hybrid context DL with the hybrid optimization scheme. The designed hybrid context DL approach adopts three DL techniques, such as Context encoder (CE), Context-Conditional Generative Adversarial Networks (CC-GAN), and Partial convolutional layer to complete the image inpainting process so that the outcomes are fused using probabilistic fusion with maximum entropy, thereby the final inpainted image is attained. Each of these three DL techniques is separately trained using a developed hybrid optimization technique. The experimental outcome reveals that the devised model gives optimal performance.
Automatic generator of mathematical logic questions in French with automated correction

Automating the generation of questions to assess students remains a serious scientific problem in developing country. Several works have been carried out on the subject but, to date, the automation of the correction of the questions generated, their connection to identified educational objectives, their ability to address comprehension problems, the definition of their difficulty and the response time remain points that are not very much addressed. In developing countries, this problem is even more accentuated by the massification due to overstaffing. This article presents a mathematical logic question generator that provides the generation and correction of questions linked to objectives, testing comprehension, with the possibility of calculating a level of difficulty and automatic scoring using the connectors and quantifiers making up the question. This generator uses automatic language processing techniques based on rules, as well as a formalization of learning objectives allowing correspondence with the generated questions. The test of the generator among mathematics students shows that 100% of the automatically generated questions comply with the objectives for which they were generated. About 90% of generated questions are syntactically and semantically well-formed
Development of Picture Storytelling Books to Enhance Morality and Word Reading Ability of Special Needs Students in Thailand

This study aimed to 1) develop picture storytelling books for enhance morality and word reading ability of student with special needs.2) examine the effectiveness of picture storytelling books.The subjects were 40 students of grade 1 to 3 who had a learning disabilities or mild intellectual disabilities.The students were selected by using purposive sampling and were studying in the second semester of the 2021 academic year at eight government schools with special education programs: 1. Rajaprajanugroh 46 School 2. Wat Samuha Pradit School 3. Watnonsaparam School 4. Anuban Saohai School 5. Wat Sathu Prachasan School 6. Anuban Saradaeng School 7. Watkhaojumpa School 8. Anuban Saraburi School.The research instruments were employed: 1) the word reading test, 2) the lesson plan for word reading, 3) the awareness of morality evaluation, 4) the students' happiness questionnaire, and 5) the teachers' satisfaction questionnaire.Descriptive statistics (i.e., percentage, dependent sample t-test) were used to analyze the data.The main findings can be summarized as follows: 1) The picture storytelling books: The content was related to eight types of morality, which included diligence, saving, honesty, being disciplined, Manners, cleanliness, harmony and kindness.The CVI scores of stories 1, 4, and 7 were 0.97-1.00and stories 2, 3, 5, 6, and 8 were 1.00.2) the word reading ability of the students who had learning disabilities was excellent and mild intellectual disabilities was below average; 3) the word reading ability of both groups was higher; 4) the students' awareness of morality and happiness was high; and 5) the teachers were strongly satisfied with using the picture storytelling books.
Introducing the Double Validation Metric for Radar Sensor Models

Abstract In automated vehicles, environment perception is performed by various sensor types, such as cameras, radars, lidars, and ultrasonics. Simulation models of these, sensors as required in virtual validation methods, are available in various degrees of detail. However, proving the validity of such models is a subject of research. New metrics and methods for credibility assessment of simulation are needed to standardize the validation process in the future. The so-called Double Validation Metric (DVM) has shown advantages and allows an intuitive interpretability of the validation results. The DVM has so far only been applied to lidar sensor models. In this paper, an extension to the DVM is introduced, which is called the DVM Map. A static measurement scenario is conducted in reality and transferred into simulation. The novel method is demonstrated on the obtained real and simulated radar sensor data. In this simple scenario special focus is put on the position accuracy of GNSS reference sensors. Therefore, their impact on the result of sensor model validation is discussed. The paper shows that the method provides a more detailed and accurate validation of a radar simulation, revealing previously undetected simulation errors. Errors due to the environment model, signal propagation, and signal processing are separated and satellite imagery is used for intuitive visualization of the results. This method is a complementary tool to existing validation techniques to improve the interpretability and judging the trustworthiness of radar simulations.
Participative Production of Students in the Development of Math Video Games at Higher Level Education

This paper shows how, through a participative production of student’s community of the Metropolitan Polytechnic University of Hidalgo in Mexico, it is possible to improve the academic performance of new students in the propedeutic course of mathematics. The production consists of the design, development and application of an educational video game focused on mathematics, specifically algebra. As a result of the participation of students, there is a larger identification and a sense of belonging to their engineering. This is a benefit for students who aspire to be admitted in the Engineering of Animation and Visual Effects because, in addition to receiving feedback about the topics that are learnt in class, they can observe digital scenes and 3D animations that they will be able to create during their university studies.
A Web Based Employees’ Cyber Security Ethical Behavior Assessment (ECEBA) Model for Ugandan Commercial Banks

Purpose: Despite the existence of Cyber Security technical controls, checklists, and formal procedures in the banks; there exists no employees’ assessment tool for Cyber Security ethical behavior. This research presents the creation of such a tool. This research aimed at enhancing Cyber Security by developing a Cyber-Security Ethical Behavior Assessment (ECEBA) model.&#x0D; Methodology: ECEBA model was used as an experimentation instrument for the development of a web-based application (ETHICA) for assessing Cyber Security ethical behavior. Unified Modelling Language (UML) was used. The ECEBA model followed the reuse concept by customizing the 3-tier architecture of the web application development. The front end interface was done using HTML5 to design the web interfaces of the ETHICA Application. To style the interfaces, CSS3 was used. Then JavaScript was used as a client side script to validate the data before submitting it to the server. AJAX a JavaScript library was used to allow submission and loading of data. Bootstrap was used to achieve responsiveness of the user interfaces. XAMPP a local MySQL server was used to host the database and the system files. Object Oriented PHP was used to act as a GUI to manage data communication between the server and interfaces. PHP Data Object driver class was used to achieve this. SQL was used to write the queries purposely to perform data processing on the server.&#x0D; Findings: The ECEBA model was developed. Deployed to the internet via URL http://Cybersecurity.groxels.com. It guided the design of ETHICA Application.&#x0D; Recommendation: Ethical behavior questions based on virtue ethical theory, Theory of Planned Behavior (TPB) and Ethical climate theory are fed into the ETHICA Application. This provides a platform for managers in assessing those individuals who may present Cyber security unethical behavior. Banks should give employees opportunity to assess themselves. Banks to use the model in conducting Employee pre-hire screening and periodic assessments of current employees. Banks should integrate the model with other cyber security controls for better ethical decision making &amp; planning.&#x0D;
The Impact of Implementing Organizational Change Strategies on Achieving Strategic Success: An Applied Study at Princess Sumaya University for Technology in Jordan

The aim of this study was to investigate the impact of applying organizational change strategies on achieving strategic success. The study was conducted at Princess Sumaya University for Technology in Jordan using a descriptive-analytical methodology. The study population consisted of all employees in the university, totaling 300 workers from upper, middle, and lower management. A sample was selected using the stratified sampling method, representing 56.3% of the workers, or 169 subjects. To achieve the study objectives, a questionnaire was designed to collect data, which was distributed to the participants electronically. After retrieving the questionnaires, 7 were excluded for being invalid for statistical analysis purposes. The final sample size was 162 workers, representing 95.8% of the main sample. Descriptive statistical methods were used, including frequencies, percentages, Cronbach's alpha test, mean and standard deviation, and multiple linear regression, within the Statistical Package for the Social Sciences (SPSS). The study found that the dimensions of organizational change strategies were available and practiced collectively at a high level in Princess Sumaya University for Technology, and the dimensions of strategic success were also at a high level. The study recommended enhancing the concept of strategic change in the university, promoting the use of scientific research methods to help generate new knowledge and skills for university workers, increasing attention to skilled workers, creating a suitable climate to encourage them to stay and continue working, and enhancing the role of university management in activating strategic risk management to improve the university's strategic performance.
THE CORRELATION BETWEEN STUDENTS’ VOCABULARY MASTERY AND THEIR SPEAKING ABILITY AT EIGHT-GRADE STUDENTS OF SMPN 1 PRINGGABAYA ACADEMIC YEAR 2022/2023

For the academic year 2022–2023, this study aims to know the correlation between speaking ability a and vocabulary mastery at the eighth graders of SMPN 1 Pringgabaya's vocabulary and speaking proficiency. This study used quantitative methodologies and samples from as many as eleven classes in class VIII, with a representative from each class. The duration of this study was roughly six weeks. 33 students took multiple choice vocabulary examinations with up to 25 questions, and within 5 weeks, speaking assessments were given to the students. In addition, the average score for male vocabulary mastery was 58 and the average score for speking mastery female was 67.33. The average vocabulary mastery score for male was 63.33, and the average score for female speaking ability was 66.11. It can be said that there is no correlation between the 8th students at SMPN 1 Pringgabaya's vocabulary proficiency and their speaking skills. As a result, the alternative hypothesis (Ha) is disproved while the null hypothesis (Ho) is accepted. This indicates that the hypothesis assumption's correlation value is less than the significant value (Rxy rt).
Hyperparameter Optimization for Deep NeuralNetwork Models: A Comprehensive Study onMethods and Techniques

Abstract Advancements in computing and storage technologies have significantly contributed to the adoption of deep learning (DL)-based models among machinelearning (ML) experts. Although a generic model can be used in the search fora near-optimal solution in any problem domain, what makes these DL modelscontext-sensitive is the combination of the training data and the hyperparameters. Due to the lack of inherent explainability of DL models the HyperparameterOptimization (HPO) or tuning specific to each model is a combination of art,science, and experience. In this article, we have explored various existing methods or ways to identify the optimal set of values for the hyperparameters specificto the DL models along with the techniques to realize those methods in real-lifesituations. The article also includes a detailed comparative study among variousstate-of-the-art HPO techniques using the Keras Tuner tuning toolkit and highlights the observations describing how the model performance can be improvedby applying various HPO techniques.
Repeat Clicking: A Lack of Awareness Is Not the Problem

Although phishing is the most common social engineering tactic employed by cyber criminals, not everyone is equally susceptible. An important finding emerging across several research studies on phishing is that a subset of employees is especially susceptible to social engineering tactics and is responsible for a disproportionate number of successful phishing attempts. Sometimes referred to as repeat clickers, these employees habitually fail simulated phishing tests and are suspected of being responsible for a significant number of real-world phishing related data breaches. In contrast to repeat clickers, protective stewards are those employees who never fail simulated phishing exercises and habitually report phishing simulations to their security departments. This study explored some of the potential causes of these persistent behaviors (both good and bad) by administering six semi-structured interviews (three repeat clickers and three protective stewards). Surprisingly, both groups were able to identify message cues for identifying potentially malicious emails. Repeat clickers reported a more internally oriented locus of control and higher confidence in their ability to identify phishing emails, but also described more rigid email checking habits than did protective stewards. One unexpected finding was that repeat clickers failed to recall an identifier which they were explicitly informed that they would need to later recall, while the protective stewards recalled the identifier without error. Due to the small sample and exploratory nature of this study additional research should seek to confirm whether these findings extrapolate to larger populations.
Development of IoT Healthcare Platform Model for the Elderly using Bigdata and Artificial Intelligence

The entry into an ultra-old society in South Korea, the remarkable development of medical technology as well as the recent emergence of the Fourth Industrial Revolution have contributed to the steady growth of the silver industry in line with the demand for healthy lives of the elderly. However, the silver industry of South Korea is still a rudimentary level. The existing older telecare product was sensor-based and was able to respond at or after the accident. However, there are limitations in preventing and predicting accidents. In particular, preventive healthcare is very important because even in small accidents, older people can be at great risk. We intend to build a healthcare platform based on IoT, against this backdrop. Based on previous studies, we try to build a new concept of architecture by collecting, storing and analyzing data to overcome the limitations of existing platforms. It’s supposed to build cloud-based Bigdata storage that can collect and analyze real-time operating conditions for older people with cameras and mobile phones, and study algorithms for old-age care through Artificial Intelligence. This research would certainly give more safe accident prevention and health care for the elderly and the healthcare industry.
A STUDY ON EMPLOYEE MOTIVATION AND ITS EFFECTIVENESS AT MAFOI STRATEGIC CONSULTANTS PVT. LTD.

The objective of the study is to measure the employee motivation and the level of effectiveness in MA FOI STRATEGIC CONSULTANTS PVT. LTD.. For the purpose of this study primary data were collected from 100 employees of the firm and descriptive research design was adopted and convenience sampling technique was used. The primary data have been collected using structured questionnaires and the secondary data have been collected from books, journals, thesis and websites. Percentage analysis, Anova has been administered to analyze the data. The findings reveals that majority of the employees have positive attitude towards employee motivation but still it could be improved by implementing the suggestions like considering employees ideas while planning and implementing project also increase employee participation, involvement and also increase performance. So as employee feel them as a valuable firm.
INFORMATION AND COMMUNICATION TECHNOLOGIES (ICT) IN EDUCATION: INDICATORS OF IMPROVEMENT IN ECUADOR

A documentary review of the elaboration and production of studies related to Information and Communication Technologies and their Impact on Ecuadorian Education was carried out through a bibliometric study of the main characteristics of 1,576 publications registered in the Scopus database during the period 2018-2022. The results obtained from this database were organized in graphs and figures, categorizing the information by variables such as Year of Publication, Country of Origin and Area of Knowledge, which allowed to identify, through qualitative analysis, the position of different authors regarding the proposed topic. The main findings of this research were that Ecuador stood out for having the highest scientific production, leading the list with 1,576 publications. Likewise, the area of knowledge that made the greatest contribution to the construction of bibliographic material related to the study of variables was computer science, with 989 published documents.