Reviewerly/exHarmony huggingface dataset:
Children’s Literature: The Significance and Other Impacts

It is worth noting that children’s literature is one of the rapidly growing fields in the literature on one hand, but on the other hand, it is also the most argumentative area of study among critics and all interested persons. The debatable feature of this literary genre underlies the broad scope of the literary texts that can include under its umbrella; fairy tales, short stories, novels, poems, and picture books. Additionally, these books’ commercial success and readability can have a long-lasting influence, and we can trace these impacts from one generation to another and from one culture to another. These books occupy a vital position in the scholar’s discussion to examine the suitability and goodness of their content to fit the mentality of children. No one can deny these books’ profound impacts on the young generation’s personal development, but we must admit that other impacts may scratch this bright image of these memorable books. In this paper, the researcher tries to detect both sides of children’s literature by referring to the role of the writer’s ideology.
HYBRID METHODS OF AUTHENTICATION IN NETWORK SECURITY

In this paper, we present a comprehensive taxonomy of the most popular authentication mechanisms, the main threats, vulnerabilities, the possible types of attacks and the security issues that are associated with computer systems. Our main contribution is to analyze the architecture of the current security environment from all aspects and to make a comparative assessment of different authentication methods in order to identify and develop a scalable and reliable mechanism that must deal with multi-level security and strong authentication requirements. We propose hybrid methods of authentication, which combine and integrate biometric technologies with cryptographic asymmetric algorithms, elements that play a vital role in the field of information security and aim to resolve the shortcomings of traditional methods of authentication and enhance the level of security.
Gaze Tracking 3-D Reconstruction of Object With Large-Scale Motion

Three-dimensional (3D) reconstruction of a moving object is a hotpot in structured-light research. However, large-scale motion causes sparse point cloud density and low reconstruction accuracy in a conventional structured-light system (SLS) because the field-of-view (FOV) of the camera is enlarged to prevent object loss. In this paper, we propose a gaze tracking 3D reconstruction system (GT3DRS), which utilizes a saccade mirror to construct a dynamic relationship between the camera and projector for an object with large-scale motion. In the GT3DRS, the real-time position of the moving object is obtained using a tracking algorithm, and a saccade mirror is adopted to keep the moving object constantly located at the center of the FOV according to the position, which enables the camera’s FOV to compactly cover the object. The GT3DRS increases the resolution of the object, effectively enhancing the point cloud density of the reconstructed 3D profile and improving the reconstruction accuracy. In addition, a new calibration framework is established for the proposed GT3DRS, which reduces the system errors by introducing an assumption of nonideal installation and improves calibration efficiency by building an extrinsic parameter transformation model (EPTM) to describe the dynamic relationship. Experimental results verify that the point cloud density is increased by 5.2 times, and the reconstruction accuracy is improved by an average of 10.6 times compared with a conventional SLS. Moreover, the tracking reconstruction video sequence reaches 15 fps.
METHODOLOGICAL AND METHODICAL FOUNDATIONS FOR THE DEVELOPMENT OF COMPUTATIONAL INTELLECTION OF A FUTURE ENGINEER

2, 5.8.3, 5.8.7)
Modelling Organizational Performance Manufacturing Companies in Indonesia: Feature Extraction

Purpose: The purpose of this research is to investigate the effect of knowledge sharing and Organizational Learning on Innovation and Organizational Performance, the innovation role as a mediator of knowledge sharing and Organizational.&#x0D; &#x0D; Theoretical framework: Good organizational learning affects organizational performance (Kittikunchotiwut, 2020). Besides, the company need not only source for information from the external environment. Rather, it also needs to search internally to create new ideas and organizational learning conducive and acceptable to the employees (Millmore, 2007). knowledge sharing in the organization ultimately contributes to employee performance Buckley &amp; Carter (2002).&#x0D; &#x0D; Design/methodology/approach: This is causality research with a sample comprising of 217 managers of manufacturing companies in East Java, Indonesia. Primary data were obtained using an instrument in the form of a questionnaire and analyzed using the PLS-SEM approach. Structural equation modeling is employed to explain the relationship between variables and the mediating effects.&#x0D; &#x0D; Findings: The results showed knowledge sharing and organizational learning had a direct effect on innovation and organizational performance. Furthermore, the findings illustrate that innovation was able to mediate the impact of organizational learning on organizational performance, but was unable to mediate knowledge sharing on organizational performance.&#x0D; &#x0D; Research, Practical &amp; Social implications: Knowledge sharing, organizational learning and innovation have been proven to improve organizational performance. Moreover, the managers need to convey a clear message to employees that the organization feels responsible for and appreciates them. The next step of this research topic are investigating spatial factor and changing in social live regarding with organizational performance.&#x0D; &#x0D; Originality/value: This reasearch focusses on studying effect of knowledge sharing and Organizational Learning on Innovation and Organizational Performance, the innovation role as a mediator. The higher the implementation of organizational learning and knowledge sharing, the higher the performance will be. The implementation of knowledge sharing in organizations causes employees to directly interact with their most knowledgeable colleagues, thereby acquiring new ideas and ultimately embracing innovation.
Feature augmentation based on information fusion rectification for few-shot image classification

Abstract In the issue of few-shot image classification, due to lack of sufficient data, directly training the model will lead to overfitting. In order to alleviate this problem, more and more methods focus on non-parametric data augmentation, which uses the information of known data to construct non-parametric normal distribution to expand samples in the support set. However, there are some differences between base class data and new ones, and the distribution of different samples belonging to same class is also different. The sample features generated by the current methods may have some deviations. A new few-shot image classification algorithm is proposed on the basis of information fusion rectification (IFR), which adequately uses the relationship between the data (including the relationship between base class data and new ones, and the relationship between support set and query set in the new class data), to rectify the distribution of support set in the new class data. In the proposed algorithm, feature of support set is expanded through sampling from the rectified normal distribution, so as to augment the data. Compared with other image augmentation algorithms, the experimental results on three few-shot datasets show that the accuracy of the proposed IFR algorithm is improved by 1.84–4.66% on 5-way 1-shot task and 0.99–1.43% on 5-way 5-shot task.
Perancangan Media Pembelajaran Interaktif Konsep Dasar Seluler Menggunakan Aplikasi Unity Berbasis Android

Telecommunication is the most important thing in this era of globalization, there are many ways to transfer information both conventionally and with the help of technology, the use of technology can be online or offline in the current era of digitalization, there have been many developments in telecommunication networks passed, the development of this cellular network has evolved from 1G, 2G, 3G even 4G, the "G" in 1G to 4G now refers to the term "generation". What is meant by generation here is the generation of wireless data and communication service technology, especially for mobile phones, because mobile social media users worldwide have increased rapidly from year to year. Android technology as a tool to use it. Interactive learning media are considered more effective in conveying material to students because students actively use interactive learning media to study the information in it. curriculum and seem too simple so that the educational program is not achieved. Using the Unity application in making Android-based interactive learning media is a form of learning that supports learning in the 21st century, especially the use of software. Of course, we need software to make a game. One of the software that can be used to make games is Unity. Unity is a cross-platform game engine designed to be easy to use. Like making a game that can be run on a computer. The material presented is in the form of general architecture of cellular systems using Unity.
The Impact of Information Technology Governance Under Cobit-5 Framework on Reducing the Audit Risk in Jordanian Companies

Purpose: The goal of this study is to ascertain how the COBIT 5 framework, which consists of (Planning and organization, Acquire and implementation, Support and Delivery, Monitoring and evaluation, Guidance and Control), affects audit risk. Theoretical framework: IT governance (ITG) is a strategic and administrative procedure that aids in an organization's efficient and responsible usage of IT. The efficacy of audit control and audit process can be significantly impacted by COBIT5. Design/methodology/approach: This study used a quantitative approach, with questionnaires distributed to 450 workers from each of the 150 Jordanian companies. The three employees served as a representative sample from the finance, internal audit, and IT departments. A total of 371 sets of questionnaires were returned with complete responses and were further examined. The data analysis employed descriptive analysis, Pearson correlation, and multiple linear regressions. Findings: The results of this investigation revealed that every independent variable, including Cobit 5, had a favorable and substantial impact on the decrease of audit risk. one of the most important results of this study showed that Monitoring and evaluation is one of the most influential dimensions of ITG to reducing audit risks, and perhaps this may be due to the nature of the delivery of IT within companies’ systems and the implementation of their applications and services to be delivered. Research, Practical &amp; Social implications: This study helps Jordanian companies to enhance the application of information technology governance, which contributes to raising the level of efficiency of their accounting systems and enabling them to compete. Originality/value: The findings showed that are a limited number of studies on IT governance and audit risk that have focused on developing countries, especially Jordan, and this is where the research comes in –to fill up the gap.
Investigation the Relationship Between Main Sources Knowledge Acquisition and Open Innovation at the Second Managerial Levels of the General Directorate of Traffic

Purpose: This study aims to examine and investigate the main sources of knowledge acquisition for individuals at the middle management levels and determine the relationship (degree of correlation and influence) between the variables of the study&#x0D; &#x0D; Theoretical framework: Recent and future studies literature reported the need for, knowledge acquisition takes place, and the best methods are those that come from outside sources such as partners, competitors, suppliers, and customers, as best practices when compared to other institutions.&#x0D; &#x0D; Design/methodology/approach: this study used the scientific methodology based on knowledge analysis, it used a questionnaire that was created taking into account the scientific requirements, Two main hypotheses have been developed. And it consisted of a sample of individuals who depended on learning new things, most similar to knowledge processes. The second organizational level of the General Traffic Department and (63) other individuals were used to generate this sample and adopted computer statistics (SPSS. V. 24) to analyze and process data and information&#x0D; &#x0D; Findings: The results concluded and found that the variables of acquiring knowledge and open innovation had a positive correlation and impact, as the variable (partners) obtained the highest correlation value.&#x0D; &#x0D; Research, Practical &amp; Social implications: Managers can find new visions and indicators for applying the knowledge acquisition system, and identifying their impact on achieving open innovation.&#x0D; &#x0D; Originality/value: The value of the study is to enhance the understanding of the literature related to The Relationship Between Main Sources of Knowledge Acquisition And Open Innovation by analysis, and provides an applied conception.
Classification and Resource Generation for Bangla Emails Based on Machine Learning Algorithms

Classification of emails is an important research issue since a huge number of emails are received every day. Emails become a most objective correspondence with others. Billions of emails that are sent per day all over the world become threatening to people. A spam email can be used to pick up things from our electrical gadgets by forcing or phishing. Besides that, we receive several other less important emails. Bangla emails are very common nowadays that are facing similar problems. But due to less collection of Bangla emails important emails are not correctly classified and the receiver missed them. Considering English or other important languages, there are accessible approaches to distinguishing the emails. In this paper, we propose a classification scheme for emails written in the Bangla language. We create a Bangla email dataset and propose a multilevel classification. We found the distinguished features to classify them. Important machine learning algorithms are used to classify them.
An Essential Robot Vision System for Robot Assisted Plant Disaster Prevention and Response Missions

Routine inspections and emergency response are unavoidable needs for power plants, oil refineries, iron works, and industrial units, as they directly influence output and safety. By utilizing autonomous robots, they can be improved. With the exception of facilities located in hazardous areas, such as off-shore factories, where dispatching people might be impossible, accidents caused by human mistakes can be prevented by autonomous inspections and diagnosis of facilities (pumps, tanks, boilers, and so on). Furthermore, if any disaster or accident happens in the plant victims should get immediate assistance. Autonomous robots can enable quick emergency assistance for victims once they are detected. The primary obstacles in robot-assisted inspection operations and victim detection are identifying various types of gauges and reading them, detecting the actual victims in any lighting condition, and taking appropriate actions. This study describes a unique robot vision system for plant inspection and victim detection system that may be used to enhance the frequency of routine checks, hence minimizing equipment faults and accidents (explosions or fires caused by gas leaks) caused by human mistakes or degradation and detecting victims to provide an immediate response. This suggested system can conduct facility inspections by detecting and reading a variety of gauges and finding victims, and it issues reports if any anomalies are discovered. Furthermore, this system can respond to unforeseen anomalous events that are potentially harmful to people and execute specific activities such as valve control if necessary.
A Hybrid Framework for Sentiment Analysis from Bangla Texts

Sentiment analysis has gained significant interest from multiple perspectives due to the rise of user interactions on social media and the web. It assists people in choosing the best service or product by analyzing the reviews of available options. Due to the current rise in demand, Bangla sentiment analysis has gained popularity throughout the research community. However, almost all Bangla sentiment analysis research has focused on a single approach, which has created a research gap in this domain. Therefore, this paper proposes a hybrid framework to perform sentiment analysis on Bangla texts that combines machine learning and a rule-based approach. This research starts with the machine learning approach and then integrates its intermediate result with the result of a newly proposed rule-based approach to produce the final sentiment of reviews. The experimental analysis states that the proposed hybrid framework outperforms the previous works with an accuracy of 95.54%, which assures its efficacy.
Noise reduction in single-shot images using an auto-encoder

ABSTRACT We present an application of auto-encoders to the problem of noise reduction in single-shot astronomical images and explore its suitability for upcoming large-scale surveys. Auto-encoders are a machine learning model that summarizes an input to identify its key features, and then from this knowledge predicts a representation of a different input. The broad aim of our auto-encoder model is to retain morphological information (e.g. non-parametric morphological information) from the survey data while simultaneously reducing the noise contained in the image. We implement an auto-encoder with convolutional and max pooling layers. We test our implementation on images from the Panoramic Survey Telescope and Rapid Response System that contain varying levels of noise and report how successful our auto-encoder is by considering mean squared error, structural similarity index, the second-order moment of the brightest 20 per cent of the galaxy’s flux M20, and the Gini coefficient, while noting how the results vary between original images, stacked images, and noise-reduced images. We show that we are able to reduce noise, over many different targets of observations, while retaining the galaxy’s morphology, with metric evaluation on a target-by-target analysis. We establish that this process manages to achieve a positive result in a matter of minutes, and by only using one single-shot image compared to multiple survey images found in other noise reduction techniques.
Introducing 6G technology to support metaverse for telecommunication engineering students in Universitas Pendidikan Indonesia

Research on 6G have been started with many applications including on the support of Metaverse, where humans can interact in cyberspace with real experiences. To introduce and provide an understanding of this technology, Program Studi Sistem Telekomunikasi Universitas Pendidikan Indonesia kampus Purwakarta held a Studium Generalle with the theme of "Knowing 6G Connectivity to Support the Metaverse" which was held in a hybrid manner. This Studium Generalle was filled by Assoc. Prof. Dr. Eng. Khoirul Anwar ST., M.Eng. (Director of The University Center of Excellence for Advanced Intelligent Communications or AICOMS and Lecturer of Tel-U). Participants were given a detailed description to contribute in the field of telecommunication research, such as 6G technology mainly on machine learning and quantum information processing. Participants have their understanding measured through Pre-Test and Post-Test. There are 8 multiple choices that are used as indicators of the success of knowledge transfer between the presenters and participants. Based on the answers of 174 participants who have taken the Post-Test, the percentage accuracy of participants's answers is 45%. With the majority of participants managed to answer 5 to 8 questions accurately. Overall, the public lecture is performed well as expected. Evaluation for the next activity is that students must first learn the basic understanding of the material to be delivered so that they can follow easily the lecture. Supporting devices are needed to improve audio quality for online participants and a wider venue for activities to accommodate more offline participants.
Criteria for the Development of the Aesthetic Culture of a Future Teacher of Fine Arts

The purpose of the article is to consider the specifics of the formation of the professional and aesthetic readiness of future teachers of fine arts. The empirical study involved 94 students of 1-4 years studying in the specialties "Technology and Fine Arts" and "Fine Arts and Drawing" in universities in Russia and Kazakhstan. Empirical research has revealed the predominance of algorithmic and stimulating-productive levels that are not characterized by an independent creative nature of activity, as well as the successful conscious and systematic application of analysis and assessment in new situations.&#x0D; &#x0D; Received: 11 September 2022 / Accepted: 17 February 2022 / Published: 5 March 2023
Teachers Challenges and Strategies of Using Microsoft Office 365 in Teaching Online Classroom during Pandemic

This study aims to explain (1) the teachers challenges in using Microsoft Office 365 in online teaching classroom during the pandemic, and (2) the strategies used by teachers to solve their problems in teaching online classes during the pandemic. The participants of this research were the teachers of SD Mustajabah. A qualitative method was employed in this research and using interviews via WhatsApp as a data collection technique. The findings showed that teachers had the challenges such as (1) operating the Microsoft Office 365 during online learning, and (2) discovering the suitable materials to gain students' attention during the online class. The strategies used by teachers to solve their problems in teaching online classes such as (1) maintaining the communication with parents of students, (2) developing thoughtful and creative materials, (3) making new agreements regarding online class.
Measuring the Performance of iCloud Private Relay

Recent developments in Internet protocols and services aim to provide enhanced security and privacy for users’ traffic. Apple’s iCloud Private Relay is a premier example of this trend, introducing a well-provisioned, multi-hop architecture to protect the privacy of users’ traffic while minimizing the traditional drawbacks of additional network hops (e.g., latency). Announced in 2021, the service is currently in the beta stage, offering an easy and cheap privacy-enhancing alternative directly integrated into Apple’s operating systems. This seamless integration makes a future massive adoption of the technology very likely, calling for studies on its impact on the Internet. Indeed, the iCloud Private Relay architecture inherently introduces computational and routing overheads, possibly hampering performance. In this work, we study the service from a performance perspective, across a variety of scenarios and locations. We show that iCloud Private Relay not only reduces speed test performance (up to 10x decrease) but also negatively affects page load time and download/upload throughput in different scenarios. Interestingly, we find that the overlay routing introduced by the service may increase performance in some cases. Our results call for further investigations into the effects of a large-scale deployment of similar multi-hop privacy-enhancing architectures. For increasing the impact of our work we contribute our software and measurements to the community.