Reviewerly/exHarmony huggingface dataset:
Secure two-factor mutual authentication scheme using shared image in medical healthcare environment

The cloud healthcare system has become the essential online service during the COVID-19 pandemic. In this type of system, the authorized user may login to a distant server to acquire the service and resources they demand, we need full security procedures that cover criteria such as authentication, privacy, integrity, and availability. The journey of security for any healthcare system starts with the authentication of users based on their privileges. Traditional user authentication mechanisms, such as password and personal identification number (PIN) typing, are vulnerable to malicious attacks like on/offline, insider, replay, guessing, and shoulder surfing. To address these issues, we proposed a secure authentication scheme that uses the authenticated delegating mechanism based on two factors: a one-time password and generating a secure variable vector from a legible user's digital image to enable the permission of a user through the back-end database of a cloud server. The proposed mutual authentication can protect the information against well-known attacks, ensure the user's privacy, and key management. Moreover, comparisons with existing schemes show that the proposed scheme supplies more privacy, security metrics, and resistance to attacks than the others while being more efficient in computation and communication costs.
Efficient Integer Retrieval from Unordered Compressed Sequences

Abstract We investigate the problem of fast direct access to elements of an integer sequence given in a compressed form. If integers are sorted in ascending order, it can be reduced to performing the 'select' operation on a bitmap, which is very well investigated. We focus on more general and more complicated case of unordered integer sequence and propose to represent it with the help of variable-length Reverse Multi-Delimiter (RMD) codes. When applied to data compression, these codes combine a good compression ratio with fast decoding. In this paper, another property of RMD-codes is researched - the ability of direct access to codewords in the encoded bitstream. We present the method allowing us to extract and decode a codeword from an RMD-bitstream in almost constant time and make experiments on its application to natural language text compression. Due to properties of RMD-codes and compactness of auxiliary direct access structures our method appears to be very space efficient requiring only a few percent excess over the entropy.
A Hybrid Method on Emotion Detection for Indonesian Tweets of COVID-19

As a result of the COVID-19 pandemic, there have been restrictions on activities outside the home which has caused people to interact more and express their emotions through social media platforms, one of which is Twitter. Previous studies on emotion classification used only one feature extraction, namely the lexicon based or word embedding. Feature extraction using the emotion lexicon has the advantage of recognizing emotional words in a sentence while feature extraction using word embedding has the advantage of recognizing the semantic meaning. Therefore, the main contribution to this research is to use two lexicon feature extraction and word embedding to classify emotions. The classification technique used in this research is the Ensemble Voting Classifier by selecting the two best classifiers to try on both types of feature extraction. The experimental results for both types of feature extraction are the same, indicating that the best classifiers are Random Forest and SVM. Models using both types of feature extraction show increased accuracy compared to using only one feature extraction. The results of this emotional analysis can be used to determine the public's reaction to an event, product, or public policy.
Computational Complexity of Human Visualization Characteristics based on Well Known Metric

&lt;p&gt;My Research Interest lies with finding issue based on Hypothetical Assumptions&lt;/p&gt;
Art history research in scientific discourse

It is noted in the article that art historical research occupies a prominent place in the scientific discourse. The work on the identification of obscure views on music as a phenomenon in the cultural and anthropological tradition of music is carried out. It is proved that scientists interpret the painting as a semiotic system with its special image code, the information of which can be decoded. The secondary verbal expression of such messages in the text of art is possible due to the mechanism of interpretation. It is concluded that the non-verbal type of artistic creativity is comprehended by the subject in the form of the inclusion of the mechanism of reception, evaluated, transformed into a verbal code, and thus interpreted.
Towards a Transparent and an Environmental-Friendly Approach for Short Text Topic Detection: A Review of Methods for Performance, Transparency and Carbon Footprint

&lt;p&gt;Online social media platforms have contributed significantly to the dissemination of user-generated information. Many studies have proposed various techniques to analyse the publicly available short texts to automatically extract topics. The majority of these works have mainly focused on the competitive performance of the proposed approaches. In this paper our main focus is on how to tackle this problem by incorporating two other important qualities: Transparency and Carbon Footprint. These two pillars are cornerstones to fulfil the emerging international demands and to adhere to the new regulations, such as “Right to Explanation” and “Green AI”. Based on these three qualities, this paper compares the most prominent algorithms in this field, such as: Latent Dirichlet Allocation, Non-Negative Matrix Factorization and KMeans as well as two most recent approaches, such as: BERTopic and Contextual Analysis. By using two different corpuses, the methods were evaluated for Performance. On average, the results show that BERTopic is the best performing approach overall in terms of Performance. However, Contextual Analysis achieves the best Performance in one of the two corpuses used. When considering the three qualities together, the results demonstrate the effectiveness and the benefits of the Contextual Analysis method towards a more transparent and a greener approach for the topic detection task.&lt;/p&gt;
An adaptive coverage path planning method considering energy constraints

Coverage path planning algorithms are widely used by many robots conducting work like floor sweeping, map generating and underwater searching. One of the practical methods is the Backtracking Spiral Algorithm (BSA), which is efficient and complete coverage guaranteed. In practice, however, autonomous robots are faced with the problem of energy constraints. The duration of the battery of a robot is usually limited. This paper presents an adaptive coverage path planning method based on BSA considering the energy constraints. The objective of this method is to minimise the total length of the path the robot travelled to recharge while guaranteeing complete coverage. This method uses an estimation strategy which would use the energy consumption of the last round as a conjecture of that of the next round and recharge when the remaining energy would probably be insufficient to complete the next round while the robot passes nearby the recharging station. A simulation result is then provided to serve as proof of this method.
A Study on the Priority of Innovative Policies of KoreanDistribution Industry at the 4th Industrial Revolution Era

The purpose of this study is to analyze priorities of the recent Korean distributional policies to contribute establishment of the efficient midꠓand long term distributional policies. For this purpose, the important factors on the distributional policies were selected through the literature review, and conducted questionnaire to the experts on distributional industry using these factors. The factors selected for the first level AHP analysis were Promotion and Support of Distributional Industry, Establishment and Maintenance of Distributional Infra, Development and Proliferation of High frontier Distributional Technology, and Creation of Distributional Industry Environment. And factors selected for the second level AHP analysis were 15 factors. The results are as follows: The first level weighted value and relative importance degree showed that Promotion and Support of Distributional Industry was the highest on priority, Establishment and Maintenance of Distributional Infra was the second, Development and Proliferation of High frontier Distributional Technology was the third, and Creation of Distributional Industry Environment was the fourth. And most of lower level factors meet high position of 50 percent are Promotion and Support of Distribution Industry and Establishment and Maintenance of Distributional Infra. Through the results of this study, to establish the long time sustainable distribution policy for the growth and improvement of efficacy of domestic distribution industry, it needs to present intensive counter-move strategies on the each areas shown the higher priorities.
The Error in Modern Chinese Synonym of Korean Learner

In this paper, Chinese Synonym errors of Korean learners were analyzed in the field of Chinese teaching. In Chapter 2, two words related to Chinese synonyms were analyzed according to their morpheme and semantic relationship, and they were divided into three types. In Chapter 3, the error expression of ‘monosyllabic-disyllabic’ verb synonyms was analyzed, and in Chapter 4, the error expressions that existed between two adjective synonyms with similar morphemes were analyzed. Through this analysis, it is expected that the error expression, which is a regular error arising from the difference between the mother tongue and the foreign language to be learned, can be reduced.BR An error is a regular mistake that arises from the difference between the native language and the foreign language to be studied. For foreign learners who already have one native language, the intervention of the native language can cause a lot of confusion and mistakes in learning a new foreign language. For this fundamental and repetitive mistake, we need to analyze more and make efforts and countermeasures to overcome it.
EDUCATING PUPILS IN SOFT SKILLS

In education, the emphasis has been primarily on pupils' knowledge and skills. These were and even nowadays are considered crucial for a person's further application in life. In the literature, they are described as 'hard skills'. However, in view of the changing world, the manifestations and demands of social and working life, in which people enter into many contacts with each other, the demands of the times, which require not only knowledge but also social, communicative and other skills, it is necessary to pay attention to these aspects alongside knowledge and to prepare the growing generation for these new requirements. These are described as "soft skills". The paper describes them and also outlines ways to develop them.
Analysis of factors influencing blockchain implementation in finance sector in Sri Lanka

The global finance industry is highly impacted by fintech innovations and technology transformations due to rapidly evolving emerging technologies. Blockchain has become one of the key emerging technologies to bring promising results in the finance sector. These transformations and the use of decentralized ledger systems would contribute to significant changes in financial transaction processing and with the advent of distributed ledger technology and its ability to enforce better transparency, blockchain is becoming a disruptive force in the finance industry. This research investigated challenges in implementing blockchain solutions in the finance sector in Sri Lanka. The Interpretive Structural Modeling (ISM) based approach was used to investigate relationships between identified factors that influence blockchain solutions. According to the results of the study, the factors with higher driving power included lack of trust in new and immature technology, lack of regulations and governance, lack of standardization, cost of implementation, and interoperability issues with legacy systems. The results of the study emphasize the importance of regulatory bodies to develop new rules and regulations to support the technology transformation and blockchain vendors to provide better interoperability and standardization across platforms.
Pretty good state transfer in discrete-time quantum walks

We establish the theory for pretty good state transfer in discrete-time quantum walks. For a class of walks, we show that pretty good state transfer is characterized by the spectrum of certain Hermitian adjacency matrix of the graph; more specifically, the vertices involved in pretty good state transfer must be $m$-strongly cospectral relative to this matrix, and the arccosines of its eigenvalues must satisfy some number theoretic conditions. Using normalized adjacency matrices, cyclic covers, and the theory on linear relations between geodetic angles, we construct several infinite families of walks that exhibits this phenomenon.
Expense Tracker

Expense Tracker is a web application through which users can maintain their expenses on the machine efficiently instead of making a paper diary. It is an efficient way of managing one’s expenses without the need of manual calculations. It provides various categories for income and expenses like clothes, food, movies, investment, rent, salary, business and many more. There is a reminder feature which will give an alerting notification if the user has exceeded the limit set for maximum expense. It will also provide a monthly report to the individuals that will help to keep the record. This report will be calculated based on the user's daily input about their expenses and income. So, by using this web application one will get a clear idea about his expenditure and can think about savings that will be helpful in an emergency situation. Key Words: Expense Tracker, Income, MERN stack, Expense
DEPARTMENT APPLICATION USING ORACLE CLOUD SERVICES

There is a tremendous increase in users with an Android-based phone, Smartphone and tablet computers. This application provides generalized solution to monitor the various works that are carried out by a Department of College for managing it. “Department App provides a simple interface for maintenance of student information. This app will be praxis by students, lecturers, HOD and parents. It can be used by educational institutes or colleges to maintain the records of students. Department App deals with all kind of student details, academic related reports, department details, curriculum, batch details, placement details and other resource related details too. This proposed project will be implemented in applications such as online study material, notices, results and attendance, timetable, and all department records using Android applications. This paper aims to develop a department application for student &amp; staff information System. keywords: Oracle APEX, Home Page, Student Details,Marks,Attendance.
Review on Precise of Blockchain Technology

Blockchain technology is becoming widely popular nowadays along with their decentralized peer- to-peer network and its privacy. Bitcoin is also widely storming in the world. Blockchain technology changes the lifestyle of people and business views on many fields through its privacy and security. Many researches were done on this technology because of its security and requirements in various fields of life. In the current era major issues are security on online translation, cloud computing, large data and Blockchain more focus on designing secure service. The objective of writing this review paper is to summarize what Blockchain is and spread awareness about its usage, security and how it works. Key Words: Blockchain, Ethereum, Cryptocurrency, Bitcoin, Consensus Methodor Algorithm, consensus rules, Hash,Genesis Block, Applications of Blockchain, Booming Domain of Blockchain
Form Based Document Understanding using Sequential Model

DocFormer is a teachable transformer-based multi-modular start-to-finish model for various Visual Report Figuring out projects. Additionally, Doc Former facilitates the model's ability to link text and visual tokens by sharing learned spatial across modalities. For the study of various algorithms and computer vision, it is a crucial area of research. Some people fabricate documents and engage in illegal activities because the current document detection system is ineffective. In the proposed system, fake documents can be found in two ways. As the popularity of deep learning technology has grown, document AI, which includes things like document layout analysis, visual information extraction, document visual question answering, document image classification, and so on, has made significant progress in recent years. We are primarily focusing on the factors that contributed to crimes in previous years when it comes to the factors that contribute to the occurrence of crimes, such as the identity of the offender and other factors.
Adaptive and Efficient Hybrid In-loop Filter Based on Enhanced Generative Adversarial Networks with Sample Adaptive Offset Filter for HEVC/H-265

In this manuscript, an Adaptive and Efficient Hybrid In-loop Filter based on Enhanced Generative Adversarial Network Deblocking Filter (EGANDF) with Sample Adaptive Offset filter (EGANDF-SAO-HEVC) is proposed for High Efficiency Video Coding (HEVC)/H-265. In this, the proposed hybrid in-loop filter involves EGANDF and Sample Adaptive Offset (SAO) filter that lessens the blocking artifacts caused by block-wise processing for coding unit (CU), which is mainly used for improving the video quality. Initially, EGANDF is proposed for HEVC/H-265 for removing blocking artifacts along low computation. Here, the output of EGANDF is given to the SAO filter for reducing ringing artifacts by diminishing high-frequency components during quantization. Thus, the proposed method efficiently reduces artifacts for improving video quality performance. The proposed EGANDF-SAO-HEVC method is implemented in the working platform of HEVC reference software with MATLAB. Finally, the proposed EGANDF-SAO-HEVC model has attained 27.26%, 29.65%, 12.45% higher accuracy, 33.56%, 31.8%, 28.7% higher sensitivity, 34.7%, 33.5%, 32.6% higher specificity, 46.92%, 35.7%, 41.3% lower MSE, 25.7%, 29.7%, 35.6% higher PSNR, and 25.6%, 28.9%, 13.6% higher SSIM for using basketball video sequence when compared to the existing methods.
Counseling on Reading Culture for Teachers at Haleluyah Christian Kindergarten, Central Jakarta

The development of the times demands that everything can quickly accept change. This change occurs in almost all aspects of life, including the development of education in kindergarten. Indonesian is an important part of education. The importance of learning Indonesian because in it there are four aspects of language skills. Each skill has its own role and function. Likewise with reading skills in children. These skills are considered important in kindergarten education because children have started to be prepared for a higher level of education, namely elementary school. The habit or form of cultivating reading is very important because there will be many benefits for children. Culture has a simple meaning, namely something that is used to. Therefore, the culture of reading in the Kindergarten education environment is something that must be paid close attention to because children will be accustomed to and trained to read from an early age.
The effect of archivist competency and commitment on archive digitalization in Universitas Negeri Gorontalo

The research delivers an analysis of the partial and simultaneous effects of archivist competency and commitment on archive digitalization. It was descriptive research using a quantitative approach. Data were collected using questionaries having been tested for validity and reliability. The results demonstrated that (1) archivist competency had a positive and significant effect on archive digitalization at a partial determination of 15.7%, (2) archivist commitment had a positive and significant effect on archive digitalization at a partial determination of 38.1%, and (3) archivist competency and commitment had a simultaneous positive and significant effect on archive digitalization. As regards the coefficient of determinant, the Adjusted R-Square was 0.519. The figure exhibited that archivist competency and commitment could elucidate archive digitalization variability in Universitas Negeri Gorontalo by 51.9%. Based on the results, as featured in the partial determination of each variable, the archivist commitment was more dominant in affecting the implementation of archive digitalization management than archivist competency. And yet, archivist competency also contributed to defining successful archive digitalization management.
Mobile Application Development for Internship: A Case Study of Li2U

As the use of technology in education rapidly evolves, academia gains access to new intelligent devices and digital applications.Over the past few years, college and university students' use of mobile devices has increased.The use of mobile devices, such as smartphones and tablets, enhances lecturer-student communication and class activities.There is significant potential for mobile devices to revolutionise education by making the conventional classroom more interactive and engaging.This study proposes Li2U, a mobile application prototype that can help university students search for internship placement more effectively, which is more practical since internships are a critical element in determining career success.In fact, there are relationships between internship experience and securing a job after graduation.This prototype application has been introduced to replace the current administrative process that is done manually.The value of this research lies in the fact that these applications or their underlying prototypes can be expanded and actual applications can be developed following research into specific contexts.
UNESCO practices under the SDG4 and COVID-19 response framework: Topic modeling from 2003 to 2021

This study focused on the impacts of COVID-19 on SDG4 to resolve inequality through education and explored UNESCO's educational practices. We used text mining to analyze strategic and crisis-related reports published by UNESCO from 2003 to 2021 and LDA topic modeling analysis was used to determine their latent contexts. Two topics related to education strategies were 'sustainable development' and 'system and organization'. According to the themes, non-formal, formal and informal learning and skills and TVET topics were derived for lifelong learning, school and teacher, emergency and peace, policy and framework in the theme of crisis and conflict. Finally, latent topics during each MDGs, SDGs and COVID-19 period showed insignificant changes. However, compared to before the 2014 MDGs, strategic discourses tended to be discussed in detail. Moreover, we noted the change in global discourse from globalization to digital innovation. After the pandemic, the international community has emphasized the role of teachers and improved internet access for interaction. Such recommendations were intended to bridge the gap between countries including developing countries. As an alternative, UNESCO has suggested various partnership practices but there are nevertheless limitations that cannot be solved through a partnership or educational support. Therefore, reaching SDG4 requires global efforts to change the world by coordinating specific target countries and various social factors surrounding the countries' interior and exterior.