Reviewerly/exHarmony huggingface dataset:
Management of Information Security in Public Universities in Nigeria

Information security aims at protecting information assets of an organization from any unauthorized access, disclosure, interference or destruction.It is a well-known fact that educational institutions store immense amounts of information, which they rely on for effective and hitch-free running of their operations.This information can arguably be classified as one of the most important assets and life blood of any organization.Astute managers increasingly recognize that information security is a critical means of securing these assets.This paper seeks to explore the importance and propriety of information security management in public or state-owned tertiary institutions. Information SecurityAny valuable asset owned by a person or entity needs to be properly kept away from danger of being damaged, stolen or compromised in any form whatsoever.In order words, it needs to be secure.
Method for Using Rubric Ratings on Fishbone Diagrams to Compare Case Studies

Background: In multi-case study program evaluations, the large amount of qualitative data that are generated from interviews can be difficult to utilize. This is particularly so when inference must be made as to why some cases succeed and some fail.&#x0D; Purpose: This paper shows a method for comparing multiple evaluation sites by using a rubric to define ratings for relevant factors, and an Ishikawa fishbone diagram as a model to show relationships among those factors. We show how this technique identified reasons for differences in outcomes among the sites.&#x0D; Setting: The evaluation setting was a large-scale safety innovation in the U.S. railroad industry. Four cases were considered—two passenger railroads and two freight railroads. &#x0D; Intervention: The Confidential Close Call Reporting System (C3RS) program allowed railroad workers to confidentially submit “close calls” which were reviewed by a team made up of labor, management, and the Federal Railroad administration to determine ways to improve safety.&#x0D; Research design: Multiple comparative case study, Ishikawa root and contributing cause modeling, evaluative rubric scoring, and data visualization techniques.&#x0D; Data collection &amp; analysis: Interview data were collected from four pilot railroad sites, each of which participated in a five-year test of C3RS. Testing periods overlapped, with the entire evaluation lasting about 12 years.&#x0D; Findings: The method of using Ishikawa fishbone diagrams with ratings from an evaluative rubric was an effective method to summarize, analyze, and present large quantities of qualitative data. The approach succeeded in explaining degrees of success and failure across the sites. The sponsor and industry stakeholders were able to understand the analysis and the findings, and to develop deep insight into how to promote successful implementation.&#x0D; Keywords: Multiple comparative case studies; qualitative methodology; qualitative coding; data visualization; fishbone diagrams; Ishikawa diagrams; evaluative rubrics; close calls; near miss; data visualization.
Artificial Intelligence with Light Supervision: Application to Neuroimaging

textabstractRecent developments in artificial intelligence research have resulted in tremendous success in computer vision, natural language processing and medical imaging tasks, often reaching human or superhuman performance. In this thesis, I further developed artificial intelligence methods based on convolutional neural networks with a special focus on the automated analysis of brain magnetic resonance imaging scans (MRI). I showed that efficient artificial intelligence systems can be created using only minimal supervision, by reducing the quantity and quality of annotations used for training. I applied those methods to the automated assessment of the burden of enlarged perivascular spaces, brain structural changes that may be related to dementia, stroke, multiple sclerosis, and sleep.
Topical Neural Theorem Prover that Induces Rules

Various sub-symbolic approaches for reasoning and learning have been proposed in the literature. Among these approaches, the neural theorem prover (NTP) approach uses a backward chaining reasoning mechanism to guide a machine learning architecture to learn vector embedding representations of predicates and to induce first-order clauses from a given knowledge base. NTP is however known for being not scalable, as the computation trees generated by the backward chaining process can grow exponentially with the size of the given knowledge base. In this paper we address this limitation by extending the NTP approach with a topic-based method for controlling the induction of first-order clauses. Our proposed approach, called TNTP for Topical NTP, identifies topic-based clusters over a large knowledge-base and uses these clusters to control the soft unification of predicates during the learning process with the effect of reducing the size of the computation tree needed to induce first-order clauses. Our TNTP framework is capable of learning a diverse set of induced rules that have improved predictive accuracy, whilst reducing the computational time by several orders of magnitude. We demonstrated this by evaluating our approach on three different datasets (UMLS, Kinship and Nations) and comparing our results with that of the NTP method, chosen here as our baseline.
A Study on the Plan for Academic Writing Classes for Foreign University Students : Focusing on the Use of Survey Research Methods

This paper aims to present how to use the survey research method in the academic writing classes for foreign university students. Students should submit a ‘terminal essay’ based on the ‘theory of academic writing’ learned in class. According to the results of a basic survey, most of the students had taken a TOPIK test, and it was expected that if ‘TOPIK no.53 writing question’ would be presented in linkage with ‘survey research methods’, students could more easily approach the methods. Based on this hypothesis, a stage to infer the questions and answers from the example of question no.53 was set.BR Thereafter, theoretical and practical classes for
The Covid Cyborg and Protecting the Unaugmented Human

This article examines the increasing tendency towards governance of people through their representation via data. In its most contemporary iteration, the COVID-19 pandemic has raised the prospect of contact tracing apps. While public discourse about the apps has focused principally on the important issue of data privacy, there are other possible effects whereby participation in such schemes might become a pre-requisite to accessing services or basic rights—either from government or from corporations. The pathway to acceptability of applying our data in this way is already paved, through fitness monitors and other technologies by which we represent ourselves. This article sets out the foundation of such technologies and their application, before outlining their effect on the recognised boundaries of governance and the conception of the holder of rights and the substance of those rights.
Bee Swarm Simulator Codes: Complete Valid and Active List

Codes are little lifts that help your ongoing interaction. Codes can be accomplished by setting off to the System Icon and composing it in the code. ...
The Effect of STEAM-based Coding Classes for Mathematical Prodigies on Math Learning Attitudes

The cognitive achievement on Mathematics of Korean students is excellent, but their affective characteristics such as confidence and interest form the lowest rank. However it is also same to prodigies who seem to be positive for Mathematics studying. For this reason, the Education Ministry is striving to integrate Mathematics with other subjects to recognize the usefulness of Mathematics in order to promote easy and interesting Mathematics education and to enhance a positive attitude toward Mathematics learning. This study want to see how effect STEAM education that is emerging globally to enhance a positive attitude of Mathematics gifted students’ learning. To this purpose, we developed STEAM-based coding class program of 8 times for 2nd grades students. We measured attitude of students toward Mathematics learning through surveys before and after took the program. After analyzed the result, there is statistically significant changes in the formation of positive attitudes in Mathematics learning.
Study on statistical analysis of ground boring data and prediction of layer construction

Accurate prediction of layer construction consisting of clay, silt, sand and gravel is important to improve the ground for the construction of high-rise buildings, because the process parameters in jet grouting must be controlled to make the improvement structure with high-quality. Even if the core sample is obtained to know the layer construction, it is not uniform over wide area. Therefore, when drilling the ground before inserting a rod equipped with a nozzle for cement ejection, some physical quantities were monitored and used for the prediction of layer construction. Since rapidly oscillating data was obtained in the real ground boring, statistical analysis of the obtained ground boring data was performed. To this end, cumulative probability of the electric current and that of the water pressure were found to be useful to distinguish the soil type.
MOBILE ASSISTED LANGUAGE LEARNING FOR ENGINEERS

This paper is meant to provide a brief introduction to a variety of emerging Web 3.0 and mobile technologies and its application that can be used in Foreign Language Teaching and Second Language Teaching. Especially, the unique potential and anticipated growth of mobile technologies for language production and consumption are discussed as an ideal opportunity to improve the reliability, involvement and functionality, and overall effectiveness of language learning within and beyond the classroom. A number of representatives‟ mobile Web 3.0 technologies will be examined and their applications to language pedagogy will be elucidated in conjunction with relevant shifts of second language acquisition theory and instructional praxis. Implications for future innovation and opportunities for additional research will be discussed.
Теоретична модель психологічних чинників організаційної лояльності персоналу

Introduction. In modern organizational psychology and human resource management, the problem of enhancing employee organizational commitment plays a significant role. The aim of the study is to analyze the recent publications on the current problems of positive and organizational psychology as well as to create a theoretical model of staff organizational commitment psychological factors. Research results. Based on the principles of positive psychology, the author has made a theoretical model of organizational commitment. According to the literature, organizational commitment can be divided into affective (positive emotional attitude to the organization), continuance (desire to continue work in the organization) and normative (obeying the rules and norms of the organization). The author analyzes the organizational commitment components (psychological capital, vitality, job satisfaction, social well-being), social and psychological factors (cultural factors, the situation on the regional labor market, stability of the organization, its corporate culture and the prospect of career and professional growth of employees) as well as personal factors (motivation, career orientation, work values, ambiguity tolerance, individual work style). Conclusions. The theoretical model proposed by the author can be used as a basis for further empirical studies of organizational commitment of staff.
Breast cancer detection/diagnosis with upstream data fusion and machine learning

Machine learning (ML) has made great advancements in imaging for breast cancer detection, including reducing radiologists read times, yet its performance is still reported to be at best similar to that of expert radiologists. This leaves a performance gap between what is desired by radiologists and what can actually be achieved in terms of early detection, reduction of excessive false positives and minimization of unnecessary biopsies. We have seen a similar situation with military intelligence that is expressed by operators as “drowning in data and starving for information”. We invented Upstream Data Fusion (UDF) to help fill the gap. ML is used to produce candidate detections for individual sensing modalities with high detection rates and high false positive rates. Data fusion is used to combine modalities and dramatically diminish false positives. Upstream data, that is closer to raw data, is hard for operators to visualize. Yet it is used for fusion to recover information that would otherwise be lost by the processing to make it visually acceptable to humans. Our research with breast cancer detection involving the fusion of Digital Breast Tomosynthesis (DBT) with Magnetic Resonance Imaging (MRI) and also the fusion of DBT with ultrasound (US) data has yielded preliminary results which lead us to conclude that UDF can help to both fill the performance gap and reduce radiologist read time. Our findings suggest that UDF, combined with ML techniques, can result in paradigm changes in the achievable accuracy and efficiency of early breast cancer detection.
Experiential learning with augmented reality

We all know that we remember better what we see instead of what we hear or do. Augmented reality is proving just that. With AR apps, a 3D view helps students understand better. By superimposing the real world with an interactive digital layer, augmented reality has the power to free education from conventional and limited teaching models that see the student primarily as a mere recipient of what is being transmitted. Augmented Reality changes the model into one in which teachers become facilitators and guides, accompanying students in shared paths of interactive discovery. Learners of any age acquire knowledge more profoundly when they learn through interactive and multisensory experiences, instead of simply listening to someone or reading textbooks. The beauty of augmented reality in education is that it can bring experiential learning into the classroom, for example by transforming textbooks into 3D representations of learning topics, while extending those experiences to the outside world. It should be pointed out that in the experiential learning what is given is not the notion, but the controllable approach, as a premise to the experiential learning. Like that, we avoid transmitting notions already made, asking the receiver for a return in the form of verification. Instead, it stimulates in the subject new experiences similar to those made, which can be subsequently processed through an invitation to personal research. Many teachers increasingly complain about the inattention of students in the classroom. The motivation could be that they are bored by traditional teaching methods. Very often it can be seen how easily children are distracted / attracted by smartphones and tablets. We can easily imagine what would happen if we could exploit these devices in the learning processes. We all know that we remember better what we see instead of what we hear or do. Augmented reality is proving just that. With AR apps, a 3D view helps students understand better. Furthermore, a new research frontier is related to the applications of Augmented Reality in an inclusive perspective, thanks to which it is possible to improve educational interventions towards pupils with Special Educational Needs. This, thanks to experiential learning, allows them to more easily approach the educational content.
이븐-맨서 스킴의 변형된 스킴에 관한 분석

There have been many papers on minimalism of cryptography. Secure minimal block cipher is one of these topics and Even and Mansour suggested a simple block cipher. The Even-Mansour scheme is a block cipher with one permutation and two whitening keys. Studying related to the Even-Mansour scheme gives great insight into the security and design of block cipher. There have been suggested many trials to analyze the security of the Even-Mansour scheme and variants of the Even-Mansour scheme. We present a new variant of the Even-Mansour scheme and introduce a variant of the Even-Mansour scheme. We focus on the security of these variants of the Even-Mansour scheme and present variation of the security according to key size. We prove the security of a variant of the Even-Mansour scheme and show that a generalized Even-Mansour scheme is not proper for a minimal block cipher.
Problems of Meter in Early-Seventeenth-Century and Twentieth-Century Music

This chapter assesses meter in early-seventeenth-century and twentieth-century music. Specifically, it analyzes compositions by Monteverdi, Schütz, Webern, and Babbitt. Monteverdi's “Ohimè, se tanto amate” from the fourth book of madrigals presents a metrical subtlety rarely encountered in eighteenth- and nineteenth-century music. Here the projective field is very mobile, and mensural determinacy is restricted to relatively small measures. Meanwhile, Schütz's concertato motet “Adjoro vos, filiae Jerusalem” from the <italic>Symphoniae sacrae</italic>, Book I (1629), demonstrates extremely subtle rhythmic detail and great projective contrast used in the service of a compelling larger gesture. Here the repetition of small melodic figures is used for the creation of complex projective fields that serve the continuity of phrases and sections. The chapter then looks at the much smaller measures and much greater ambiguity in some music of the twentieth century.
The Artistic Value of Body Language in Chorus Conducting

Body language is used by every person to express, and each person shows different body movements, and the meaning of expression is also different. Not everyone needs to use body language when expressing, but the use of certain body movements can make one's content richer, and at the same time make other people more clearly understand the content and emotion they expressed. Body movements can be seen everywhere in daily life, especially the conductor of the chorus who is often seen on the TV screen. By analyzing the function of body language in chorus command, this paper discusses the artistic value of body language in chorus command.
A Researchon Customer Awareness towards Digital Wallet among People at Chennai City

An advanced wallet is an digital machine that enables a person to perform digital exchanges. This incorporates acquiring things through on line PC or making use of a complicated mobile. Automatic wallet be fine to the regular on line clients which might be monetarily on hand for ,, pocket PC hand held and palm-sized work place. Computerized wallet (e-pockets/D-pockets) permits the handler to make electronic alternate exchanges rapidly and correctly. This examination factors mindfulness for computerized wallet amongst people within the city of Chennai. The exam additionally offers a few motivation to inclining in the direction of automatic wallet.
Are Magnets Bad For Phones

Have you ever wondered what a magnet may do to your phone? I will answer that questions and I will tell you everything you need to know on this topic in ...
EUREKATAX: A Taxonomy for the Representation and Analysis of Qualitative Usability Test Data

Usability tests serve as an insightful source of feedback for product teams that want to deliver user-centered solutions and enhance the User Experience (UX) of their products and services. However, in many cases, formative usability tests in particular may generate a large volume of qualitative and unstructured data that need to be analyzed for decision making and further actions. In this paper, we discuss a more formal method of analyzing empirical data, using a taxonomy, namely Engineering Usability Research Empirical Knowledge and Artifacts Taxonomy (EUREKATAX). We describe how it can provide guidance and openness for transforming fuzzy feedback statements into actionable items. The main aim of the proposed method is to facilitate a more holistic and standardized process to empirical data analysis while adapting on the solution or context. The main contributions of this work comprise the: (a) definition of the proposed taxonomy which represents an organization of information structured in a hierarchy of four main categories (discover, learn, act, and monitor), eight sub-categories, and 52 items (actions/operations with their respective properties); (b) description of a method, that is expressed through the taxonomy, and adheres to a systematic but modular approach for analyzing data collected from the usability studies for decision making and implementation; (c) formulation of the taxonomy’s theoretical framework based on meticulously selected principles like experiential learning, activity theory: learning by expanding, and metacognition, and (d) extended evaluation into two phases, with 80 UX experts and business professionals, showing on the one hand the strong reliability of the taxonomy and high perceived fit of the items in the various classifications, and on the other hand the high perceived usability, usefulness and acceptability of the taxonomy when put into practice in real-life conditions. These findings are really encouraging, in an attempt to generate comparable, generalizable and replicable results of usability tests’ qualitative data analysis, thereby improving the UX and impact of software solutions.
The Development of AKK Learning Model (Active, Creative, Communicative) through Cartoon Media for Reading Comprehension of Mandarin Language Learning For the Tenth Graders

This study aimed to examine the development of Mandarin learning models using AKK (Active, Creative, Communicative) based on cartoon media for reading comprehension learning, which contains (1) the process of developing the AKK learning model (Active, Creative, Communicative) through cartoon media, ( 2) the quality of the AKK learning model (Active, Creative, Communicative) through cartoon media, (3) the effectiveness of the AKK learning model (Active, Creative, Communicative) through cartoon media for reading comprehension learning to master Mandarin text for tenth graders. This developmental research uses the Research and Development (R&amp;D) model proposed by Borg and Gall. Based on the use of this R&amp;D model, the data collection of this study used questionnaire, interview, and documentation. The results of this study are the AKK learning model (Active, Creative, Communicative) through cartoon media for reading comprehension learning to master Mandarin language gets some results (1) the process of developing the AKK learning model (Active, Creative, Communicative) through cartoon media runs smoothly and appropriately, (2) the quality of the AKK learning model (Active, Creative, Communicative) through cartoon media for reading comprehension learning to master Mandarin language is very suitable as seen from the results of the RPP validator, material, instruments, and media validation, (3) the effectiveness of the AKK learning model (Active, Creative , Communicative) through cartoon media for reading comprehension learning to master Mandarin language, obtained results for products of 5.77 with a significance level of 5% and for the results of observations made continue to increase from 85%, 82.5%, 95%, and 97.5% based on Likerrt scale is very strong. The AKK Learning Model (Active, Creative, Communicative) through cartoon media for reading comprehension learning to master Mandarin language is very appropriate to be used in the learning process and there is an increase in the learning outcomes of students in class X IPS 1 of SMA Khadijah Surabaya.