Reviewerly/exHarmony huggingface dataset:
Comparison Of Filters (Dwt, Ksvd) And Edge Detection Methods (Canny And Sobel) On Medical Images

Application of Digital Image Processing on medical images could greatly contribute in the discovery of diseases and it would provide the physicians with valuable inputs in the process of diagnosing the diseases without any flaws. This is an experimental paper in which some of the filtering methods and edge detection methods have been applied and the results are being reviewed. Some of the important filtering techniques will be discussed in this paper and the results I have worked on will also be illustrated. Two types of edge detection methods have also been reviewed and their results are being illustrated.
Navigating Interactive Story Spaces

Over the past decade, journalists have created in-depth interactive narratives to provide an alternative to the relentless 24-hour news cycle. Combining different media forms, such as text, audio, video, and data visualisation with the interactive possibilities of digital media, these narratives involve users in the narrative in new ways. In journalism studies, the convergence of different media forms in this manner has gained significant attention. However, interactivity as part of this form has been left underappreciated. In this study, we scrutinise how navigational structure, expressed as navigational cues, shapes user agency in their individual explorations of the narrative. By approaching interactive narratives as story spaces with unique interactive architectures, in this article, we reconstruct the architecture of five Dutch interactive narratives using the walkthrough method. We find that the extensiveness of the interactive architectures can be described on a continuum between closed and open navigational structures that predetermine and thus shape users’ trajectories in diverse ways.
A Novel Framework for Multimodal Twitter Sentiment Analysis Using Feature Learning

Over the years there has been a lot of speculation with respect to single modal sentiment analysis of twitter (which is one of the world’s largest micro blogging platforms) data i.e. either text or image mining. But unfortunately most of the researchers didn’t use the non-trivial elements such as memes (i.e. combination of image and text data) and GIFs (i.e. combination of video and audio data) which dominate the twitter world today. Hence looking at the limitations of the existing systems we proposes a novel framework called “Multimodal Twitter Sentiment Analysis using Feature Learning” which defines the polarity of the tweets by considering all types of data such as text, image and GIFs. The framework consist of three main modules i.e. Data Collection for gathering real-time tweets using twitter streaming API, Data Processing module which has context-aware hybrid algorithm used for text sentiment analysis and ‘Fast R-CNN’ for image sentiment analysis. GIFs are handled using an optical character recognizer which separate texts from images for defining the polarity and finally multimodal sentiment scoring is done by aggregating polarity scores of images are texts. Evaluation results of proposed framework shows accuracy of 96.7% against SVM and Naïve Bayes which outperforms the single modal sentiment analysis models.
PENGEMBANGAN MODUL PELATIHAN PENGENALAN DASAR BAHASA PEMROGRAMAN JAVA DENGAN MODEL ARCS

&#x0D; 1048 / 5000&#x0D; &#x0D; &#x0D; Translation results&#x0D; &#x0D; &#x0D; The introduction of programming languages ​​to students is very rare. As a solution for the introduction of programming languages ​​for students is to hold training and workshops for students. The training module was developed by applying the ARCS (Attention, Relevance, Confidence and Satisfaction) model with the aim of increasing students' motivation to learn programming languages ​​further. The resulting module was applied to the training carried out for students of SMA Negeri 10 Jambi City. There were 30 participants, consisting of grade 10 and grade 11 students. Participants were mentored by 4 instructors who were also observers. The ARCS model can be used as a reference in developing Java programming training modules with the aim of motivating and enthusiastic students. The module has been used in basic java programming training at SMA 10 Jambi City, with observations (scale 100), for an average student attention of 91.25, participation 94, persistence 93.25, task completion 83.25, and activeness 93.5.&#x0D; &#x0D;
APPROACHES TO DEVELOPING STUDENTS’ INFORMATION CULTURE IN ENGINEERING EDUCATION

The article focuses on the importance of information culture as an integral part of professional culture of engineers, which affects the quality and safety of engineering solutions. The main two approaches to the definition of "information culture" are determined, which include an information approach when the information culture is reduced to the concept of computer or information literacy and a culturological approach when the concept "information culture" is seen as a way of human life in the information society. Development of the information culture acts as a process of harmonization of the inner world of man in the acquisition of socially significant information.&#x0D; The main components of information culture of engineers are highlighted, including literacy and competence in understanding the nature of information processes and relationships, humanistically oriented information value-semantic sphere, developed information reflection, creativity in information behaviour and socio-information activity.&#x0D; Based on a broad understanding of information culture as a qualitative characteristic of the life of a specialist in terms of receiving, transmitting, storing and using information, where universal moral values are the main priority, basic methodological approaches to forming information culture of future engineers are proposed, namely: system, personal, activity, integrative, culturological, axiological and reflexive approaches. The process of developing future engineers’ information culture in the process of professional training in higher educational institutions will be effective providing that it is based on the substantiated methodological approaches.
Formación de tutoras y tutores virtuales. Una experiencia educativa desde el punto de vista de los capacitadores (Experiencias)

The pandemic caused by the COVID-19 outbreak forced higher education institutions to make an emergency transition to remote teaching. In this context, several institutions initiated training processes for teachers to enhance and/or develop skills in using ICTs to continue the teachinglearning process. This work presents five trainers’ experience tutoring an intensive training course for virtual tutors in which 520 university professors participated. The results show difficulty using technological tools, netiquette rules, and a basic level of communication skills. Regarding the work with e-activities, the research identified that the most complex topics are planning and evaluation, while designing these e-activities is easier for them
LibGuides: Resources for Reading Instruction: Books for New Readers

A LibGuide for parents seeking books and other resources to help teach a child how to read and/or help improve existing English reading skills towards the goal of reading fluency. Books for New Readers page lists easy reader level books for children, which are decodable and have limited sight words. Subcategories are: Storybooks, Non-fiction picture books, Bilingual storybooks.
Enhancing Machine Translation: Neural and Hybrid MT engines Directing Strategies

MT direct engines are used excessively by language learners and in translation classrooms. Such MT engines don’t allow human interference while processing the translation task. Thus, applying some translation strategies during the preparation stage is essential in directing MT engines. The researcher of the present study trained a group of EFL learners in Qassim University to apply some strategies on Arabic source texts before submitting them to MT engines. The researcher used an electronic metric “BLEU” to assess the effect of the proposed strategies in directing MT engines toward accuracy. Furthermore, the responses of two neural MT engines (Google Translate and Systran) and four Hybrid MT engines (Yandix, Reverso, Collins, and Microsoft) to the premodified text (modified through the proposed strategies)were compared. Results showed that the translation strategies are effective and direct the MT engines toward accuracy. The pre-translation strategies led to 37.8 enhancement in MT translation. As for comparing the response of the six MT engines, results indicated that all the six MT engines responded effectively to the modified text and Neural Google Translate had the highest response of all.
Identifikasi Segmen Pasar Mahasiswa Perguruan Tinggi Menggunakan Analisis Klaster Berdasarkan Variabel Psikografis

The importance of the presence of higher education enables the private sector to participate in organizing academic activities in the form of higher education institutions. This causes the private higher education market to become more competitive, which implies a low number of students. Therefore, market segmentation needs to be applied to college students so that they can help to determine the model of marketing and promotional activities. The stages carried out in this study consisted of data collection, data exploration, and extracting segment. Cluster analysis was applied as a method for extracting segments of students with psychographics variables as partitioning factors. The K-Means algorithm was chosen as the method applied for cluster analysis because it produces better performance when compared to the use of K-Modes. Cluster analysis based on psychographics variables applied to this case succeeded in extracting the segment of the university students into 6 segments.
BRASS Business Guides: Scholarly Publishing for Business Librarians: About this Guide

The purpose of this guide is to assist business librarians with identifying reputable journals where they may want to submit for publication.
A Variant Q-Sorting Methodology for Building Diagnostic Trees

Diagnostic theories are fundamental to information system (IS) practice and are represented as trees. While there are approaches for validating diagnostic trees, these validate the overall performance of the tree rather than identifying ways incorrect diagnoses can occur. It is important to fully validate diagnostic trees because even if the tree gives the correct decision “most of the time,” it is possible for incorrect decisions traveling down little-used branches of the tree to result in catastrophic decisions. In this article, we describe the process of using a variant of q-sorting to validate diagnostic trees. In this methodology, diagnostic trees that independent experts develop are transformed into a quantitative form, and that quantitative form is tested to determine the inter-rater reliability of the individual branches in the tree. The trees are then successively transformed to incrementally test if they branch in the same way. The results help researchers not only identify quality items for use in a diagnostic tree but also facilitate diagnoses of problems with those items and facilitate the reconciliation of discrepant trees by experts. The methodology validates not only the whole tree but also its subparts. Full paper available at 10.1109/TEM.2021.3078582
Using the Moodle Platform for Organizing Training in Education (Introduction of Distance Learning Technologies in the Educational Process)

This article reveals the effectiveness of the mixed educational environment by analyzing the relationship between the characteristics of traditional learning, as well as the mechanisms of the learning management system – LMS) - a widely used and recognized all over the world, a set of teaching methods, the Moodle platform, the positive aspects and details of the Moodle platform in contrast to traditional learning are indicated. This item presents the results of surveys conducted with the aim of referring to the experiments of students and teachers with Moodle. The main focus is on providing information about options, surveys and possible relative restoration of the function and privacy when using its functions Summary: The contribution is a long-term experience and analysis of the Moodle system. In addition, the analysis of the use of this platform during the COVID-19 pandemic was carried out.
Ineffectual Panorama of Conflicting Rights in RTI Regime: Cocking a Snook on Citizen’s Right to Public Accountability

Right to Information (RTI) is an essential mechanism which ensures transparency in the decision-making process in order to make the government accountable and responsive to the people as indifferent governance gives rise to an exploitative system. RTI Act empowers every citizen the right to seek information from a public authority that is bound to furnish the information sought for as long as the same is not exempted from disclosure. Though it is true that exemption clauses can serve a useful function, but unfortunately, it is often seen that exemption clauses are misused by public authorities to protect certain vested interests. This paper highlights the curious case of Vipin Pandey Vs. South Asian University, wherein the Central Information Commission has inappropriately stated that the South Asian University enjoys the privileges and immunities as the subject matter falls with the United Nations (Privileges and Immunities) Act, 1947 while overlooking various well established precedents set by the same authority in previous cases. This paper also analyzes the Delhi High Court judgment of Vikas Verma Vs. The Director wherein the court has taken a conservative stand in interpreting Section 8 of the highly progressive regime of RTI Act in comparison to the interpretation in the Evans case by the UK's Supreme Court.
ANATOMY OF QUANTUM KEY DISTRIBUTION PROTOCOL: A COMPREHENSIVE ANALYSIS

Quantum mechanics and its underlying principles assures better security then classical world which are unable to provide unconditional security. A quantum entanglement phenomenon helps us to minimize the required assumptions needs to be made about devices, resulting towards Device Independent Quantum Key Distribution (DIQKD). What about guarantying security of the QKD protocol in case of quantum devices used in protocol are untrusted? DIQKD provides unconditional security without assuming anything about internal working of quantum devices. DIQKD allows users to not focus on integrity of devices being used in protocol. Quantum physical phenomena non-local correlations and no information exchange within and between the laboratories of Alice and Bob are bases of DIQKD. As quantum computing started becoming mature and commercially viable, need for quantum error correction became obvious. Quantum error correction can be accommodated in quantum key distribution to gain better efficiency with reference to error rate. Post processing quantum error correcting techniques can remove noise once the procedure is performed. Real time quantum error correction will lead towards large scale quantum computation.
Analisis Pelacakan Dan Pendataan Aset Di PT Indonesia Comnets Plus (Icon+) Kalimantan Tengah

Archiving and Collecting data from an asset needs to be done to ensure that the data written in archives is the same as what is in the workfield (actual), the information that required through the archives, can avoid mismatch and miscommunication, prevent duplication of work and help to achieve work efficiency. Archives have a very important role, namely to plan the next program of activities. Because with archives, it can be seen the various kind of information that are already owned, so that target can be determined next, by using the maximum available potential. As one of the companies engaged in Internet Service Provider (ISP), PT Indonesia Comnet Plus (ICON+) has various kinds of data that need to be archived for the purpose of data collection, data validation, and data tracking needs (allocation, costs, types, and so on) such as data on the number of poles, cable links, ONTs installed on customers, and others. Therefore an application is needed as a medium for archiving and collecting data, the application used in ICON+ is AMARTA. AMARTA helps to archive data from all data and monitor parameters that can be met for the next target.Keywords : AMARTA, Archiving, iconpln, asset, data collection
Research and Examination of Seismic Safety Evaluation and Function Maintenance for Important Equipment in Nuclear Facilities

Abstract Since the Fukushima accident, with the higher safety requirements of nuclear facilities in Japan, suppliers, manufacturers and academic societies have been actively considering the reconstruction of the safety of nuclear facilities from various perspectives. The Nuclear Regulation Authority has formulated new regulatory standards and is in operation. The new regulatory standards are based on defense in depth, and have significantly raised the levels of natural hazards and have requested to strengthen the countermeasures from the perspective of preventing the simultaneous loss of safety functions due to common factors. Facilities for dealing with specific serious accidents are required to have robustness to ensure functions against earthquakes that exceed the design standards to a certain extent. In addition, since the probabilistic risk assessment (PRA) and the safety margin evaluation are performed to include the range beyond the design assumption in the safety improvement evaluation, it is very important to extent the special knowledge in the strength of important equipment for seismic safety. This paper summarizes the research and examination results of specialized knowledge on the concept of maintaining the functions of important seismic facilities and the damage index to be considered by severe earthquakes. In the other paper, the study on reliability of seismic capacity analysis for important equipment in nuclear facilities will be reported.
Comprehensive Open Metrics for Repositories

Scholarly items in repositories often lack reliable indicators on citation counts, attention, and usage that can serve as the basis for comprehensive and recent view of the impact of such items and, as a result, their authors, institutions, and publication platforms.OpenAIRE works on solutions based on open metrics that are generated according to transparent and standardized procedures and which can be applied on scholarly items in repositories. Such metrics are aggregated and accumulated thanks to the de-duplication routines in OpenAIRE and they are exposed offering reuse and integration in repositories.The poster focuses on two approaches: the formation of a globally distributed network of usage statistics hubs where COUNTER-compliant usage statistics can be collocated, actually a collaboration activity carried out with EOSC-Hub but also IRUS-UK and La Referencia, and using the Open Citation Corpus as a source for citation counts related to scholarly items in repositories.
Label-efficient Bayesian Assessment of Black-box Classifiers

Author(s): Ji, Disi | Advisor(s): Smyth, Padhraic | Abstract: Machine learning classifiers are currently widely used to make decisions about individuals, across a broad variety of societal contexts: education admissions, health insurance, medical diagnosis, court decisions, marketing, face recognition, and more—and this trend is likely to continue to grow. It is now well-recognized that these machine learning models are susceptible to built-in biases that can lead to systematic discrimination against protected groups. The machine learning research community has begun to recognize this important issue and in the past few years had devoted considerable research resources towards developing principles, frameworks, and algorithmic solutions to address these problems.In this general context, this work addresses the understudied problem of how to assess how accurate, calibrated and fair a model may be, and how much confidence we should have in this assessment given access to a limited amount of labeled data. To be specific, we propose a Bayesian framework for assessing (with uncertainty) performance metrics of black-box classifiers, which is particularly important when only a limited amount of labeled data is available. To improve label-efficiency of the assessment, we develop active Bayesian assessment strategies for an array of fundamental tasks including (1) estimation of model performance; (2) identification of model deficiencies; (3) performance comparison between groups. When unlabeled data is available, we develop a new hierarchical Bayesian methodology that leverages information from both unlabeled and labeled data.We demonstrate that our proposed approaches need significantly fewer labels than baselines, via a series of experiments assessing the performance of modern neural classifiers (e.g., ResNet and BERT) on several standard image and text classification datasets. One particular example of how the proposed approach can be used is in the increasingly common situation where the user of a blackbox classification model needs to assess its performance from a fairness perspective, in a manner that is separate and independent from the claims made by the entity that trained the model. We demonstrate that the methodology developed in this work is well-suited to such an application.
F-Commerce as a Tool of Artificial Intelligence: A Modern Approach for Promoting Startups

Artificial intelligence (AI) is expanding and sprouting faster than ever. It is a swiftly mounting technology, made possible by the Internet. AI has a significant impact on digital commerce. Facebook commerce (F-commerce) refers to digital commerce that uses the social media platform to capture the masses. Facebook represents a frequently sprouting marketing stage and communication pathway. Worldwide, there are over 2.38 billion monthly active users, and India has the highest number of Facebook users in the world. Facebook has become a strategic element of marketing and business promotion activities. Such platforms are a boon chiefly for startups having controlled budgets. Facebook is all about people, social selling, and relationship building. It’s easy to access, low-cost marketing platform, connecting with existing and potential customers, targeted advertising, raise brand awareness, and positive word of mouth has proven to be the key to success for startups. The current chapter will throw the lights on the features of Facebook in the form of AI. The purpose of this chapter is to highlight the role of AI to create a new marketplace for all social media users.
THE EFFECTIVENESS OF THE SYSTEM FOR ASSESSING THE FUNCTIONAL LITERACY OF STUDENTS IN COMPUTER SCIENCE BASED ON THE CRITERION APPROACH

In the article, based on the criterion approach, the effectiveness of the system for assessing the functional literacy of students in computer science is proved by conducting a pedagogical experiment and conclusions are drawn about the results of practical work. The teaching experience consists of three stages. At the ascertaining stage, it was revealed to what extent the assessment tasks in computer science were compiled taking into account the directions of functional literacy of students. At the applicant stage, tasks and tasks were developed to assess the functional literacy of students based on a criteria-based approach in computer science. At the educational and control stage, the influence of the functional literacy assessment system, developed on the basis of a criterion approach in computer science, on the quality of knowledge and the methodology of teaching students in computer science was revealed. In addition, during the practice, the educational and methodological manual "tasks for assessing the functional literacy of students in computer science" was used. During the training in the control groups, the assessment of knowledge was carried out according to the traditional method, and in the experimental groups on tasks to assess the functional literacy of students based on the criteria approach.