Reviewerly/exHarmony huggingface dataset:
Printer Service Application

Abstract-- printer service application is an application that maintains the information about the printer models,service Centers, customer details, and appointment details. This isn't easy to organize manually. Maintenance of all this Information manually is a very complex task. The advancement of technology makes the organization of printer service Applications much more straightforward. The printer service application has been designed to computerize and Automate the operations performed over the information about the members, appointment issues and returns, and all Other operations. Customers can create, read, update and delete the appointment. Admin can add, delete, view, and Update the service center. This computerization of the printer service helps in many instances of its maintenance. It Reduces the management workload as most of the manual work is reduced.
Face Biometric Authentication System for ATM using Deep Learning

Abstract: Automated Teller Machines also known as ATM's are widely used nowadays by each and everyone. There is an urgent need for improving security in banking region. Due to tremendous increase in the number of criminals and their activities, the ATM has become insecure. ATM systems today use no more than an access card and PIN for identity verification. The recent progress in biometric identification techniques, including finger printing, retina scanning, and facial recognition has made a great effort to rescue the unsafe situation at the ATM. This project proposes an automatic teller machine security model that would combine a physical access card and electronic facial recognition using Deep Convolutional Neural Network. If this technology becomes widely used, faces would be protected as well as their accounts. Face Verification Link will be generated and sent to user to verify the identity of unauthorized user through some dedicated artificial intelligent agents, for remote certification. However, it obvious that man’s biometric features cannot be replicated, this proposal will go a long way to solve the problem of Account safety making it possible for the actual account owner alone have access to his accounts.
Conditions for improving serendipity encounter and attainment probability

While we cannot ensure the occurrence of serendipity due to its nature of unexpectedness, we can try to prepare the optimal conditions to improve the possibility. This chapter first describes two types of unexpected information: within or from beyond one’s perceivable range. Next, we describe four stages of the serendipity attainment process: navigation, noticing, evaluation, and implementation. On this basis, we discuss six scenarios in the order of serendipity encounter and attainment probability, which are determined by information availability in the environment and the mindset in terms of information processing. The serendipity attainment process has a higher success rate when acquiring precise navigation and employing the 3D principles of creativity (best expertise within discipline, the best expertise out of discipline, and discipline process).
Development of a Scheme for Correcting Arbitrary Errors and Averaging Noise in Quantum Computing

Abstract Intensive research is currently being carried out to develop and create quantum computers and their software. This work is devoted to study of the influence of the environment on the quantum system of qubits. Quantum error correction is a set of methods for protecting quantum information and quantum state from unwanted interactions of the environment (decoherence) and other forms and types of noise. The article discusses the solution to the problem of research and development of corrective codes for rectifying several types of quantum errors that occur during computational processes in quantum algorithms and models of quantum computing devices. The aim of the work is to study existing methods for correcting various types of quantum errors and to create a corrective code for quantum error rectification. The scientific novelty is expressed in the exclusion of one of the shortcomings of the quantum computing process.
University Instructors’ Views on Courses Delivered Online

The health emergency is compelling us to adopt new habits, including education-related practices. Therefore, it may be worth considering targeted teaching strategies and their future development. Current research in e-learning and technology-supported teaching has recently developed in an attempt to identify possible future transformations at all levels of education.This paper focuses on tertiary-level education and describes a study on educators’ views on courses delivered via Moodle during the pandemic and on the most commonly used pedagogical models.Using a case study on methodology, the author analyses some possible forms of online education, from the most basic, to those implemented through a combination of digital activities and resources, and their application at the University of Urbino (Italy). Data were collected by means of a questionnaire administered to 231 university teachers during the first year of the pandemic.The findings suggest that there is a good basic tendency to use technology but also inevitable stress that is however combined with an underlying sense of satisfaction. The educators’ technological skills, their tools, and the advice offered by the institution appear satisfactory, while students seem to have found some basic difficulties in accessing online lessons. The most commonly used didactic practices are sharing files via Moodle, using web conferencing software and text chats during lessons. Finally, future developments are to be expected as lecturers express their willingness to continue using the same technological resources that they have found most effective during the COVID-19 emergency.
Analysis Of Information Technology Services Management Using ITIL V3 Domain Service Operation (Case Study: Hotel Sinar Sidoarjo)

Information system is one of the most rapid developments of information technology in its development. This information system itself aims to help human work to be more efficient and effective. The quality of technology has many aspects that must be measured to evaluate in order to continue to develop. Service is an important aspect that needs to be improved in order to support the applied Information Technology. ITIL as a framework that focuses on the assessment of information technology services was chosen as the method to be applied in this research. The problem that often occurs in this Sinar Hotel is the existence of obstacles in customer data in the Front Office department. Customer data is often not inputted into the system so that customers have to re-enter data and this is time consuming and less efficient. The incoming data also sometimes does not match the customer's personal data which also results in the customer needing to re-enter the data. The Service Operation domain was chosen to assess the extent to which the problem management and incident management processes were implemented properly. The results of this study will produce a recommendation to overcome problems and incidents that often occur in order to facilitate the operational activities of Hotel Sinar.
Differentially Private Maximal Information Coefficients

The Maximal Information Coefficient (MIC) is a powerful statistic to identify dependencies between variables. However, it may be applied to sensitive data, and publishing it could leak private information. As a solution, we present algorithms to approximate MIC in a way that provides differential privacy. We show that the natural application of the classic Laplace mechanism yields insufficient accuracy. We therefore introduce the MICr statistic, which is a new MIC approximation that is more compatible with differential privacy. We prove MICr is a consistent estimator for MIC, and we provide two differentially private versions of it. We perform experiments on a variety of real and synthetic datasets. The results show that the private MICr statistics significantly outperform direct application of the Laplace mechanism. Moreover, experiments on real-world datasets show accuracy that is usable when the sample size is at least moderately large.
Product Anti-Counterfeiting Using Blockchain

Abstract: Fake Products is a serious issue, as in today’s world we can’t really distinguish between real and fake product. And some people make these fake products just to make some profit without thinking about its impact on user and also affects company’s name, profit and sales. Blockchain technology can be used to detect whether the product is real or fake and assure user about the authenticity of the product. Blockchain technology is the technology where information is stored in the form of blocks in many databases which is connected with the chains and it doesn’t require any third-party users for permission. We can use QR code or an encrypted unique codewhich is a very efficient technique to detect fake product. When the QR code is scanned or theunique code is entered, it will redirect us to the blockchain containing the information of the product and provides us the details of the manufacturer and information of owner to make decision easy for buyer if they are looking to buy the product.
Similarity Measure of Images using SIFT and ORB Feature Matching

Abstract: In this study, similarities between images are identified and examined. A collection of images made from an image of the same scene or item taken under varied atmospheric conditions, such as different perspectives or lighting settings, and then altered in myriad ways by the very same starting image. The process of determining picture similarity is comparing visual information to evaluate how similar it is. Based on the input, it finds good matches and presents the proportion percent exceptional matches between the photos. It compares the supplied input to calculate the similarity measure. For decades, picture resemblance has been a fundamental problem in the fields of object recognition.When two photos are compared, Image Similarity generates a result that represents how physically similar they are. The measure of comparison of the two photographs is given a numerical number in this test. The similarity score between two photos ranges from 0 to 1 respectively.We have proposed a solution using SIFT &amp; ORB Feature Matching
KIMCHI: Aplikasi Pembelajaran Bahasa Korea Berbasis Android dengan Fitur Latihan Menulis HANGUL

http://dx.doi.org/10.32409/jikstik.21.1.2897
Common inhibiting factors for technology shifting from physical to virtual computing

Due to the rapid growth of cloud computing demands and the high cost of managing traditional physical IT infrastructure, virtualization technique has emerged as a foremost and key success factor for technology adopters to attain the intended benefits. However, the transition from physical to virtual computing is confronted with overwhelming adoption inhibitors rarely known to adopters. This paper examines inhibiting factors which have triggered to low adoption rate of virtualized computing infrastructure despite being the fastest growing and globally accepted technology. Survey results from 24 companies indicate that lack of relevant virtualization skills, security uncertainties, low computing demands and change management issues are the utmost inhibitors. In public entities, the slowness in the adoption process is highly caused by the low computing demands, lack of virtualization coverage in ICT policies, resistance to change, choice of technology and the lack of virtualization project priority in the ICT master plans. On the other hand, the use of open-source hypervisors and support and maintenance are specific inhibitors affecting the private sectors. This paper is useful for adopters who have virtualized their server resources or have a plan to virtualize in the near future.
Strengthening Chemistry Teachers' Technological Pedagogical Content Knowledge through the Introduction of Augmented Reality and Learning Management Systems

Strengthening of Technological Pedagogical Content Knowledge (TPACK) needs to be done as an effort to present chemistry learning that is following the times. The purpose of this activity is to identify the TPACK conditions of chemistry teachers, as well as to seek initial activities to strengthen teachers’ TPACK through the introduction of augmented reality technology according to chemical content, as well as classroom management based on a learning management system platform. The implementation method included Focus Group Discussion (FGD) activities, lectures, and implementation practices. Participants in this activity consisted of chemistry teachers who were active members of the Chemistry Teacher Groups of Kudus Regency, as many as 17 teachers. This community service activity is in the form of a series of activities that include (1) identification of difficult chemistry materials, most of which show microscopic concepts as one of the difficult materials, (2) identification of the condition of the teacher's level of mastery of technology which is generally still at a moderate level, (3) introduce the potential use of technology in the chemistry learning process in the form of Augmented Reality, namely RAppChemistry, and (4) the use of a learning management system in the form of the Google Classroom platform that can be used in electronic-based teaching and learning processes. Further partnerships need to be implemented to implement the technology on a classroom scale. Activities that may be carried out are lesson study activities to optimize the integration of technology in chemistry learning.&#x0D; Keywords: Pedagogical Content Knowledge, Augmented Reality, Learning Management System
REGRESSION METHODS FOR SOCIAL MEDIA DATA ANALYSIS

In the early 2000s, the more traditional modes of communication via mobile devices were voice calls, emails, and short message services (SMS). Nowadays, communication through mobile applications such as WhatsApp, Facebook, Twitter, Instagram, etc. About Facebook the leading social network with monthly active users of about 2.85 billion people. With this number of users, a large amount of data is generated. Exploring this data provides an insight into the users’ activities which can aid in tackling security challenges and business planning, among other benefits. This study presents a neighborhood component analysis (NCA) and relief-based weight generation methods for a regression task on Facebook data. The features are calculated using the weight generated and four widely used activation functions. The features are then fed to four regression models for prediction. The proposed model is used to predict nine different attributes of the FB dataset whose values are continuous. RMSE, R-squared, MSE, MAE, and training time were calculated and used as evaluation metrics for all nine cases. The average R-square value of the Relief and NCA-based methods were calculated as 0.9689 and 0.9667, respectively. The results indicated that our proposed methods are very efficient and successful for regression tasks on Facebook data.
A Big Data Analysis of K-POP on Social Media: focused on Images, Figures, and Public Attitude

This study aims to present the image and thoughts about K-POP among the public through objective data as we realized that it is necessary to conduct a systematic analysis of the public mentality and attitude toward K-POP to sustain the movement of Hallyu or Korean Wave. To this end, we used the big data in 2014 and 2021 to compare and analyze the K-POP-related images, figures, and public attitude between the two time points. The result can be summarized as follows: First, between 2014 and 2021, the changes over time in the media, where K-POP can be accessed by the audience, are more pronounced than common images about K-POP; Second, the figures that appeared consistently and commonly in 2014 and 2021 were found to be EXO and BTS, popular South Korean boy-bands. In the case of EXO, there was no commonly related figure at both points of time, but as for BTS, it was found that their fan club, A.R.M.Y, appeared as a common related figure; Third, compared to 2014, the rate of positive response toward K-POP decreased while negative response increased in 2021; in other words, the attitude toward K-POP turned negative. Unlike the previous studies that collect data with questionnaires or materials and analyze them, we used the already stored data and Sometrend, Korea’s big data analysis software, provided by VAIV Company, to find out what people think about K-POP. This study is significant as it extracts information from the existing data, analyzes the contents, and reinterprets the results from various angles to derive meaningful results. It is expected that the findings of this study, presented through precise data—the K-POP-related images, figures, and public attitude—will be used as basic material to contribute to the sustaining of the K-POP wave.
Predicate Concepts and their Normal Form

This paper argues that a simple system of meaning relations drawn from words/lexical items in a natural language and framed in terms of syntax-free relations in linguistic texts can help ground linguistic predicates or concepts thereof in a number of meaning relations. These relations are constrained by the logical structures of linguistic meanings across sentence and discourse contexts. Significantly, such meaning relations are not defined over, or do not ride on, the syntactic structure of a given language. Nor do they (necessarily) turn on compositional relations for the computation of meaning values. This facilitates the formulation of meaning relations to be defined on the symbolic elements of a lexicon. This specific insight is carried over to the reduction of predicates or predicate concepts in natural language to the minimal form they can assume. This minimal form is formulated in terms of meaning relations in a manner that all complex predicates or predicate concepts can be reduced to a sort of normal form defined by meaning relations.
New Key Agreement Protocol and Cryptosystem over ECC under SET Protocol Environment in E-Commerce

Cryptographic technologies are the most cost-effective and practical way to secure data transfer over an open public network.Although ECC (Elliptic Curve Cryptography) has a much smaller key size than standard cryptography methods and most of the research uses the cryptography technique to offer information authentication and integrity.Additionally, the computing effort required by EC-Diffie-Hellman (EC-DH) for equivalent key lengths is comparable and provides additional security benefits.This study provides a New Key Agreement Protocol with EC-Diffie-Hellman in the SET (Secure Electronic Transaction) environment (NKAP-ECDH-SET) to improve security.This NKAP-ECDH-SET protocol successfully implemented the key in the SET environment for digital payments and was used to encrypt and decrypt the confirmation evidence.This NKAP-ECDH-SET Protocol is used in an E-Commerce payment gateway to provide high-level security analysis, quick authentication, and security for the proposed cryptosystem.The proposed NKAP-ECDH-SET produces better security enhancement in terms of communication cost (1251 bits), computational time (4.27 ms), and data sizes (165 bytes), when compared to existing Password-Based Key Agreement and American Standard Code for Information Interchange-ECC protocols.
Quantum Switching in Resistor Networks

&lt;p&gt;In this paper quantum switches, qswitches, are introduced to generate a superposition of resistor networks. Measuring the qswitches results in one resistor network with specific values for the electrical variables; then using the probabilities for each network with the currents and voltages, expectation values are calculated. Finally a control signal, or feedback, is used to change the qswitches probability amplitudes.&lt;br&gt; &lt;/p&gt;
Non-parametric Method of Detecting Differential Item Functioning in Senior School Certificate Examination (SSCE) 2019 Economics Multiple Choice Items

This study analyzed Non-Parametric Methods of Detecting Differential Item Functioning (DIF) in SSCE 2019 Economics Multiple Choice Items. Three (3) research questions were raised to guide the study. The survey research design was employed. The population of the study consists of 14,400 SS II Economics students from Edo South Senatorial District of Edo State, Nigeria. The number of sample size used in the study was 1,440 SS II Economics students. The stratified random sampling technique was adopted for this study. The instrument used to gather information was 60 Economics multiple choice items of NECO SSCE 2019 June/July. The instrument was validated by experts in Economics and Measurement and Evaluation and Quality Assurance Unit of National Examination Council (NECO) officials. Reliability was determined using Cronbach’s Alpha Statistics and coefficient of 0.72 was obtained to detect the items that functioned differentially by sex, three (3) DIF methods (Mantel Haenszel, Standardized p-diff and transform item difficulty (delta plot) were used. The findings showed that the three (3) methods displayed DIF. It was found that standardized p-difference and transform item difficulty are most suitable methods than Mantel Haenszel statistics in detecting 2019 Economics Multiple Choice Items prepared by SSCE 2019. It was also recommended that other non-parametric statistics be used to detect differential item functioning.
CUTTING EDGE LIBRARIES: DIGITAL VS VIRTUAL LIBRARY

This article is devoted to types of modern libraries and their differences and usage of e-library around the world as well as its beneficial sides. Additionally in this article describes the competence between digital and virtual libraries.
Bocce Training Based on Computer Technology Has an Effect on Physical Education in Colleges and Universities

Computer technology refers to the technical methods and technical means used in the computer field, which have the function of data storage, modification, and calculation of related logic and data. Physical education in colleges and universities has various levels and complex contents. From the perspective of bocce training in college physical education, this paper proposes a research direction for bocce training based on computer technology for the development of college physical education. First, a brief introduction to bocce is given, and then the traditional training methods of bocce are explained. It mainly includes technical training, physical fitness training, and psychological quality training. Then, the computer-assisted teaching is explained. Finally, the computer-assisted teaching and the traditional mode of teaching are contrasted. The experimental results show that the overall performance of students’ technical training, physical fitness training, and psychological training assisted by computer technology is 3.53% higher than that of students under traditional teaching. This shows that bocce training based on computer technology is more conducive to improving the level of sports training of students, thereby improving the quality of physical education.