Reviewerly/exHarmony huggingface dataset:
A KNOWLEDGE-AS-A-SERVICE SUPPORT FRAMEWORK FOR AMBIENT LEARNING IN KENYA

Knowledge as a Service (KaaS) is a relatively new model, albeit one that is rapidly gaining popularity within cloud computing environments.Over the recent years, learners have experienced a constant need to access on demand knowledge that is fully aligned with the paradigm of cloud computing.This need stems from the knowledge that users will be able to access applications and the information therein on demand, without the restrictions that are usually imposed by time and space.The KaaS model terms knowledge as the understanding of information based on its relevance to a specific context and problem area, thus forming a valuable resource for the human decision-making process.As motivated by the global sustainable development goal of ensuring inclusive and equitable quality education to promote learning opportunities for all, this research has developed a framework that is hinged on KaaS and utilizes knowledge from ambient learning systems.The main aim is to provide a platform for disseminating and exploiting the available knowledge to aid the learning process and, thus, to improve the quality of education on the ambient learning system.The research further explores how collaborative effort can be used to form a knowledge network that allows access to heterogeneous sources of knowledge.The research outcomes will benefit knowledge consumers such as the developers of ambient learning systems.
Efektivitas Sistem Temu Kembali Informasi Online Public Catalog (OPAC) Dengan Tinjauan Precision Menggunakan Pendekatan Judul Dan Subjek Di Perpustakaan Universitas Muhammadiyah Bengkulu

Library as a centre for information resources is the backbone of the progress of an educational institution. Imbalance between the use of information retrieval system facilities advance search and a quick search of the catalogue are very common in a search. This study was aimed to know and to describe how the precision of information retrieval system by using title field and subject on OPAC (Online Public Access Catalog) ) at Muhammaddiyah University Library of Bengkulu is effective as an information retrieval system. This study was a quantitative descriptive study using analytical methods. The technique of data collection in this study was by using trace observation on the Online Public Access Catalog (OPAC). The study was carried out by using the title of the names of study programs and the subject to study program as the study sample a mounted to 206. Sample were taken by using purposive sampling techniques. The result of the study showed that search using advanced search features by using the section title of sociology subject obtained a precision marks of 0,98 while the use of advanced search features by using biology education subject obtainrd precision mark of 0,66. The use of quick search feature by using the sociology subjects get a precision marks of 0,98 while the use of quick search feature by using biology education subject obtained a precision marks of 0,99. The testing on the four search shows that the quick search and advanced search features in the title and subject are in the average range of 0,90 so it is said that the search system of OPAC at Muhammadiyah University Library of Bengkulu is effective as an information retrieval system.
Realitinship of Peer Social Interaction with Student Learning Motivation

The relationship of peer social interaction in school occurs when teaching and learning activities in the classroom and outside the classroom have an important role in fostering learning motivation that can increase the activity and effectiveness of student learning. This study aims to: (1) describe the social interaction of student peers, (2) describe student learning motivation, (3) test the significance of the relationship between peer social interactions with student learning motivation. This type of research is quantitative with a descriptive correlational approach. The population of this study were students of SMA Negeri 3 Padang Panjang which numbered 881 students. The sampling technique used was purposive random sampling, so that a sample of 275 students was obtained. The instruments used were peer social interaction questionnaires and learning motivation questionnaires. Data were analyzed by descriptive statistics and Pearson product moment technique using the SPSS version 20.0 program. The results of the study describe: (1) peer social interaction is in a good category with an average achievement of 57.09%, (2) learning motivation is in the high category with an average achievement of 66.18%, and (3) there is a relationship significant between peer interactions with learning motivation with the acquisition of 0.478 at a moderate level with a significance level of 0,000. The magnitude of the correlation is 0.478, meaning that if the social interaction of peers is good, then the students' motivation also tends to be high. Conversely, if peer social interactions are not good then learning motivation tends to be low.
Semi-supervised method for sensitivity based documents’ classification for online service providers

In today's digital era, many services providing companies exist on the web whereas service is the logical product of a company, which can be utilized through the Internet.Different service providers provide these services i.e., Online counselling service, online doctor consultation, cloud service provider, web hosting service, etc. to their customers.When customers face some problems, they may text to their providers.One solution is that providers can solve these issues based on the First-Come-First-Serve formula.But there should be an option to detect sensitive issue which may need to be solved first.How can this sensitivity be determined?Already there is a lot of researched work based on text to determine the polarity as positive and negative.Besides this classification, there are also some other classification methods investigated, such as aspect, not aspect, subjective, objective, spam, not spam, etc. regarding text sensitivity, whether it is sensitive or not?This classification is not yet considered for service providers.This paper presents a strategy for sensitivity based classification using Latent Semantic Indexing (LSI).The purpose of LSI is to rank documents concerning a given query.However, in this study, a mechanism was provided to generate query automatically based on sensitive general words with the words from all documents.This is a semi-supervised approach because 4782 sensitive words have been labeled from various sources and used based on an unsupervised approach to detect the sensitivity of the document.The sorted lists of documents based on the LSI scores generated by the sensitive-query were checked manually and were proved to be highly satisfactory.The topmost document in this list was the most sensitive, and the last document in the list was least sensitive.
New Association Proposition for Role implicit in Cloud Environment

Cloud computing has become a preferred service supplier for information technology on the users demands resources can be provided there over internet. Virtualization is a central innovation for empowering cloud resource sharing. Confidentiality of data storage is the essential alarm for assurance of data security so cloud computing does not provide robust data privacy.  We are addressing a main issue of cloud computing that is load balancing this paper is describing about the load balancing issue in cloud computing is providing an approach to for enhancing the load distribution process. In this exploration we tended to the difficulties in fulfilling of cloud computing environment regarding security hazard implementation strategies on cloud computing environment and comparison of different cloud computing architecture through comparative study In developed virtual machine migration plan, uses monitored technique the load on every host in the data center to decide whether or not to perform VM migration and then we established the criteria to deciding which VM to migrate. we explained different algorithms and techniques proposed for Virtual Machine Scheduling either at single data centre or multiple data center. Our implementation shows a better result of resource prediction accuracy with low cost and less time consuming than previous approaches. It not only increases the efficiency of virtual machines, also improves the performance of the system.
A Visual Content-Based Approach for Automatic Evaluation of Student Assignment Reports

The last few years have witnessed a surge of interest in artificial intelligence (AI). There is a significant increase in the number of students who major in or take courses related to AI.This inevitably brings great pressure to unit coordinators. Especially when the deadline of assignment approaches, dozens even hundreds of assignment reports will flood in almost simultaneously. The sharp rising of workload will cause a tremendous burden to the lecturersand tutors who are responsible for marking the reports. As a result, a preliminary evaluation or a rough assessment of the reports before marking is needed to propose some referential suggestions and boost the marking process.Another severe challenge in marking a large volume of assignment reports is the marking consistency issue which has been previously discussed by Blok (1985). Due to the diversity of report markers, there is no guarantee of a consistent assessment of all the assignment reports, even if a common evaluation criterion is provided. This inconsistency problem is more serious for the novice markers. With relatively less experience, they are prone to make a biased judgment according to their subjective viewpoints. Thus, for a consistent and fair review of the student assignment reports, a more objective approach is urgent to assist the report marking.“Whoever started the trouble should end it.” The extra burden caused by the fervour of AI should be released by AI. Because of the powerful learning and generalization ability, machine learning (ML) and deep learning (DL) models have been applied to a wide range of applications including those in the education sector. Currently, the examples of intelligent education include but not limited to Intelligent Tutoring Systems (ITS) (Chaudhri et al. 2013), virtual facilitators and learning environments (Swartout et al. 2013) and so on. However, as more time-consuming and tedious job.
Research on Image Processing Method of High Voltage Switchgear Temperature Measurement

Abstract Accurate monitoring of electrical equipment temperature can effectively ensure the safety of electrical equipment operation. It is worth further study to use limited temperature monitoring equipment to obtain a comprehensive temperature distribution of electrical equipment. Based on the study of nearest neighbor interpolation bilinear interpolation and bicubic interpolation these three methods are applied to image processing of temperature distribution in 10kV switchgear cabinets. Compared with the three methods, bilinear interpolation and bicubic interpolation can accurately reflect the non-measured temperature, and can be used in image processing of temperature distribution in high-voltage switchgear temperature measurement system.
Analysis of the Current State of Cloud Forensics: The Evolving Nature of Digital Forensics

Cloud computing and Cloud storage has drastically increased over the last decade and is expected to grow more in the coming decade as well. This has allowed business to grow and offers consumers cheap storage and the ability to rent virtual servers. However, due to the unique characteristics of cloud technologies, it has also introduced multiple challenges such as on-demand nature, resources pooling, and distribution, legal and investigation issues. These issues have introduced new issues for forensic investigators and law enforcement in access to evidence, data collection, data preservation, as well as many others. This paper examines the current challenges, acquisition methods, and analysis of cloud forensics. Furthermore, it explores the existing solutions and possible solutions moving forward for the next decade.
LibGuides: UL Library Systems, Applications and Online Services: Library Catalogue

A guide on how to access and utilise UL Library Systems, Applications and electronic resources
Rancangan Bangun Sistem E-Repository Skripsi Mahasiswa Berbasis Qr (Quick Response) Code

The Abulyatama University Final Assignment book is a condition for the graduation of a student in completing the final project whereby every book that has been previously made will be collected at the Information Systems Library, Along with the development of time and additional years will also increase the number of alumni who graduate each year, this will result space (capacity) of books in the Information Systems Library is increasingly decreasing and there is a density so that the Library will have difficulty if you want to add a new book list. On the background that arises above, the final project idea arises regarding Design of E-Repository Systems for Student Based Thesis (Quick Response) Code, this thesis aims to facilitate the search for books equipped with a qr scan code that allows members to search for a book title and research material.
Development of Solar Irradiance Forecast Confidence Intervals for Solar Electric Vehicle Energy Simulations

Solar electric vehicle racing is becoming ever more popular, especially in countries such as America, Australia, and South Africa. Teams are continuously looking for better and more effective ways to manage their energy as well as interpreting the solar irradiance forecasts. This paper shows how historical forecasts with measured data are used to create expected upper and lower forecast bounds to enable solar racing teams to make more informed energy decisions.
Games and spaces: semantics of a modal probabilistic logic

In this work we make a study of the different semantics for a modal probabilistic system. In the first part of the work, we compare two model-based semantics: relational and neighbourhood semantics. Nearly all the works in the field of probabilistic modal logic fall within the first label. We defend that neighbourhood semantics is more suitable for probabilistic modal logic, particularly for subjective probability logic. The main reasons of this are the following: - Neighbourhood semantics allows to distinguish between lack of probabilistic belief and the complementary probabilistic belief in the opposite proposition. - In neighbourhood semantics we can equate the composition of the doxastic and the probabilistic operator with the subjective probabilistic operator. - Relational models can be seen as isomorphic to a certain subset of neighbourhood models. - It is more adequate for future developments. For example, non-standard probabilistic believers or situations in which we distinguish between explicit and implicit belieg. In the second part of the work we choose to develop two dynamical semantics. We develop variations of dialogical games and semantic tableaux for probability modal logic for the probabilistic modal operator, establishing the corresponding rules for dealing with probabilies. We find the following remarkable results: • Being a non-normal modal operator, we can extablish a connection between the model-theoretical semantics for probability and the rules for our dynamical systems. • There is a connection between probabilistic semantic tableaux and dialogical games, so they can be seen in parallel.
A Framework for Track Consistency Processing Based on Blockchain

Track data consistency is a prerequisite to ensure battlefield situation consistency. This paper analyzed the structural characteristics of the existing track processing system and the causes of the consistency problem of track data under different structural characteristics, and summarized the key factors that caused the inconsistency of track data. In view of these factors, this paper proposed a track consistency processing framework based on the existing blockchain technology architecture and track processing procedure, and provided a new solution for the sea battlefield track consistency processing. The simulation results show that the new framework has greatly improved the track data consistency compared with the existing processing flow.
A Genetic Fuzzy Model for Investigating Security and Trust in E-Commerce with Genetic Algorithm

In e-commerce, the issue of security and trust has always been one of the most important principles.With the advancement of internet science, e-commerce has also become more advanced, always striving for greater security and trust.Of course, security and trust are not new issues in the area of e-commerce and a variety of techniques have been provided to improve the performance of this business.If an e-commerce business fails to meet the customer's expectations in terms of security and trust, it would be doomed to fail.Security in e-commerce is the protection of existing assets and information against attacks and unauthorized access to that e-commerce.In this study, it has been tried to prevent such attacks by preventive techniques and strategies and also by providing an artificial immune system based on agents and computational intelligence techniques including fuzzy control and Genetic algorithms.The rules generated by fuzzy logic are taught by Genetic algorithm and finally through these rules, the input patterns are categorized.In this study, the activities are classified into two categories of safe and unsafe and the incorrect boundaries between these activities are reduced by the proposed technique.
THE FALLACY ANALYSIS OF THE PROGRAM “WAKTU INDONESIA BERCANDA”

Recently, one of popular programs on TV is Waktu Indonesia Bercanda (WIB). It is a Quiz Show program that offers problems to solve and the host makes use fallacies as the core of its game. WIB offers the sense of achievement among its participants, but competitive atmosphere is hardly to find among them. This research tries to analyze the fallacies being used in WIB and figure out how such fallacies can encourage people to think critically. The research employs descriptive research design as it simply attempts to determine, describe or identify phenomena. 6 WIB from September through December were randomly selected as the subject of the research. The result shows that WIB demonstrates the use of fallacies of relevance but it avoids using argumentum ad hominem that contains personal attack. WIB may encourage the audiences and participants to think critically as fallacious arguments offered make the audiences work hard to think any possible implicatures. Eventually, WIB is the program that invites the participants and the viewers to think, evaluate and decide the answer or solution to the problem provided. In conclusion, WIB is a worth watching ShowQuiz as it is entertaining and encouraging its audience to think critically.
Semantic Segmentation of Printed Text from Marathi Document Images using Deep Learning Methods

Segmenting text from documents is a very important step prior to recognition. In this paper, semantic based text segmentation on Marathi document images using deep learning methods has been proposed. Semantic Segmentation using deep learning methods had given good results on various applications in the past. In this paper, U-Net and Residual U-Net (ResU-Net) architecture, are used for semantic segmentation on Marathi documents. Both the deep learning models (U-Net and ResUNet) had given a state-of-the-art performance on medical image segmentation. The models are tested on the dataset of scanned images taken from various Marathi books and articles. The experimental results show better performance on ResU-Net architecture than U-Net due to the presence of skip connection in the model. The model with skip connections avoids vanishing gradient problem, and also the feature accumulation in the model generalizes well on the segmentation task. U-Net and ResU-Net model gives 95% and 98% accuracy respectively on the dataset.
Substantiation Of Students Educational Routes Under Conditions Of New Schooling Formats

The article presents the results of a study devoted to the development of methodology and methods of modeling school students’ educational routes. Generated analysis of regional educational systems development shows that realized at present new forms of interaction between schools and universities, Russian Academy of Sciences, network learning actualizes searches of new approaches to individualization of education and students’ educational routes designing. It has been shown that since modern school education is carried out in an integrated regional space of project and research activities, it is necessary to conduct study of this process using traditional pedagogical, management and mathematical methods. As the main means of educational routes modeling, Saaty method of hierarchy’s analysis was used. It allows to select an optimal educational route among possible alternatives and on this basis to make substantiated pedagogical and managerial decisions. The following alternatives (types of learning trajectories) were taken into consideration: school-elective (optional courses), supplementary education at school, school-university, school-Russian Academy of Sciences, network training. For the purpose of the model building the following criteria were selected: students’ readiness, motivation for success, awareness of students about the opportunity to receive supplementary education, goal setting (or internal activity plan), willingness of the teachers. Numerical simulation carried out demonstrates that selecting among pedagogical alternatives for achieving optimal educational outcomes require considering of internal and external factors, establishing their relationship, justification of the preferred paths based on the evaluation of alternatives, identifying the influence of external factors on the process of selection an educational route.
STUDENTS’ TOLERANT BEHAVIOR IN A MULTICULTURAL ENVIRONMENT

Tomsk Polytechnic University trains not only the students from the Russian Federation, but also the students from Asia, Africa, East and West.The main teacher's aim is to teach students the subject as well as to build up their tolerance towards other cultures and each other.The study of works by E. Gellner, B. Anderson, and E. Hobsbawm allowed forming the theoretical basis of the article and the use of the Smart methodology promoted the practical implementation of the tasks set by the teachers.As a result, it was found that the lessons and activities undertaken in the framework of the curriculum, especially, in the framework of extracurricular activities, allowed students to demonstrate their cultural identity and contributed to the development of tolerance among students.In addition, by means of cultural information exchange students developed the mutual understanding and friendship.The students' adaptation in a new multicultural environment occurs much quicker.