Reviewerly/exHarmony huggingface dataset:
Pengaruh Motivasi Pada Minat Mahasiswa Non Akuntansi Program Reguler Mengikuti Pendidikan Profesi Akuntansi

This study aims to determine the effect of social motivation, career motivation, quality motivation, economic motivation and degree motivation on the interest of non accounting students to take part in the accounting profession education program (PPAk). This research was conducted at the Faculty of Economics and Business, Udayana University, in the non-accounting S1 regular program students, using questionnaire techniques as data collection. The number of respondents in this study was 169 people. The analysis technique used is multiple linear analysis techniques. Based on the results of the research analysis, it is known that social motivation, career motivation, degree motivation, economic motivation, and quality motivation influence the interest of non accounting students to take part in Accounting Professional Education. Knowledge .&#x0D; Keywords : Social motivation, career motivation, degree motivation, economic motivation, quality motivation, interest in joining PPAk.
Searching for Work Ethics by Youth Worker

This study was conducted to determine the type of subjectivity of Work Ethics of youthwork by applying the Q-methodology and to understand the characteristics of each type. Through in-depth interviews and Literature review, 30 Q-statements were drawn. A total of 30 youthwork were selected as P-samples, and Q-sorting tasks were performed. The results of the analysis using the QUANL-PC program were divided into 4th types. The first type is ‘Respect for Youth Rights type’, the second type is ‘ Youth friendly Environment type’, and the third type is ‘Pursuit for Professionalism type’, the fourth type is ‘Organizational Cultual Orientation type’. The result of this study can be used as a guide to solve the ethical dilemma in the youthwork scene by cultivating the professional ethics consciousness of the youthwork by classifying the ethical perception that the youthwork should have as a professional.
Analysis of Humanities and Social Sciences-based Convergence Researchers Participation in the HubCon Conference and the Meaning

HubCon 컨퍼런스(Humanities Based Convergence Conference)는 한국연구-재단이 주관하고 건국대학교 융합연구총괄센터가 주최하는 행사로 전국에 흩어져 있는 인문사회기반 융합연구자들을 한데 모아 국가와 지역사회, 국민의 삶의 질을 높이기 위한 새로운 아젠다를 도출하자는 취지의 행사이다. 이 컨퍼런스에는 한국연구재단이 공모하여 연구 과제에 선정된 전국의 연구팀들이(20~30팀 100여명) 한데 모여, 1박 2일 동안 열띤 토의와 의견을 나누며 인적네트워크를 확장하는 장(場: field)으로 일반 학술대회에 버금가는 성시를 이루고 있다. 인문사회기반 융합연구 즉 학제간융합연구지원사업은 2009년 처음 시작되어 올해로 10년째가 되고 있다. 이 10년이라는 기간 동안 융합연구자들이 한데 모이는 모임이 특별히 존재하지 않았다는 점에서 HubCon 컨퍼런스를 주목할 가치가 있다. 본 연구는 인문학 홀대시대에 HubCon 컨퍼런스가 인문사회기반의 연구자들을 한데 모아 새로운 아젠다를 도출함은 물론 융합연구자들의 연구 네트워크 외연의 확장의 장, 타 전공과의 공생, 융합연구자로서의 정체성을 확립하는 장으로 발전할 수 있는 방안을 제언하고자 한다.The Humanities-Based Convergence Conference (referred to as HubCon Conference below) is an event that is supervised by the National Research Foundation of Korea and hosted by the General Center for Convergence Research at Konkuk University to develop new agendas with humanities and social sciences-based researchers with the intent of improving the quality of life for the country, communities, and the people. This conference provides a field upon which research teams (100 researchers from 20 to 30 teams) from around the country, invited by the National Research Foundation of Korea, may have heated discussions for two days and one night, allowing them to expand their networks. This conference is gaining popularity equivalent to general academic conferences. Humanities and social Sciences-based convergence research and the Interdisciplinary Convergence Research Support Project have been conducted for a decade since the project’s inception in 2009. There has been no special meeting for convergence researchers during this decade. Thus, the HubCon Conference warrants attention. This study aims to suggest measures by which the HubCon Conference can develop new agendas with humanities and social sciencesbased researchers in an age in which humanities is neglected, in order to allow convergence researchers to broaden their research networks, coexist with other disciplines, and establish identities as convergence researchers.
Multivalued function recognition based on spectral clustering

Abstract In scientific research, bioinformatics, Internet applications, e-commerce and many other application fields, the amount of data is growing at an extremely fast rate. To analyze and utilize these huge data resources, it is necessary to rely on effective data analysis technology. Big data application is a process of mining effective information from big data by using data analysis methods, providing auxiliary decisions for users and realizing the value of big data. In the process of data calculation and analysis, we will often find that the data from the same source will show multiple function images in the same coordinate system, which will make the same variable correspond to multiple values in data prediction analysis. We call it multivalued function here. This paper provides a method to identify multivalued functions. By using the maximum information coefficient (MIC) theory proposed by David n. Reshef, and using the data sampling method to calculate the function identifiability of the data set, then, the spectral clustering method is used for recognition, segment and mark the images of different functions. Finally, the regression function equations with different marks are obtained by Gauss-newton iteration method. The results can be used for data prediction and analysis to assist decision-makers to make reasonable judgments.
Double Backpropagation for Training Autoencoders against Adversarial Attack

Deep learning, as widely known, is vulnerable to adversarial samples. This paper focuses on the adversarial attack on autoencoders. Safety of the autoencoders (AEs) is important because they are widely used as a compression scheme for data storage and transmission, however, the current autoencoders are easily attacked, i.e., one can slightly modify an input but has totally different codes. The vulnerability is rooted the sensitivity of the autoencoders and to enhance the robustness, we propose to adopt double backpropagation (DBP) to secure autoencoder such as VAE and DRAW. We restrict the gradient from the reconstruction image to the original one so that the autoencoder is not sensitive to trivial perturbation produced by the adversarial attack. After smoothing the gradient by DBP, we further smooth the label by Gaussian Mixture Model (GMM), aiming for accurate and robust classification. We demonstrate in MNIST, CelebA, SVHN that our method leads to a robust autoencoder resistant to attack and a robust classifier able for image transition and immune to adversarial attack if combined with GMM.
The Influence of Sleep on Relearning and Long-term Retention of Verbal Items

We aimed to examine the generalizability of the results obtained by Mazza et al. (2016) on the effect of sleep on relearning and long-term retention. They showed that Swahili-French word pairs were relearned faster after a 12-hour interval when nocturnal sleep was interspersed during this interval, and that they were also better recalled one week later. They used an intensive relearning procedure using tests with feedback until a criterion of all 16 items correct in a row, possibly leading to overlearning. We replicated this original study with a less demanding criterion for relearning, i.e., one correct answer per item. The data are currently being collected. They will indicate whether the sleep effect on relearning and on long-term retention was due to the specific relearning methods, and possibly by overlearning, in Mazza et al.’s study, or whether they can be generalized to different relearning procedures.
LibGuides: Lower Grades Citation Guides: Kindergarten

This LibGuide is a resource for teachers of K-4. It provides collective information on citation lessons specialized by grade level.
Student online marketplace for university community

This research presents student online marketplace for university community. In this study, we identify current issues faced by university students while starting their business. Based on the preliminary investigation, it was found out that there are a number of students doing part-time jobs and doing business to support their living expenses. There are varieties of businesses and services offered among students especially students staying in colleges. However, the main problem faced by students either as the buyer or the seller is there is no business platform to promote their products or services. Al-so, there is a lack of information regarding the business or services since most communications are done through h instant messaging apps such as WhatsApp and social media. By having a student online marketplace, the exchange of goods and services take place by having buyers and sellers being in contact with one another. This student online marketplace also helps small businesses to boost their sales, encourage new business start-up and inspire students who have business idea to help them to kick-start their business. Students are able to perform their business in a safe and secure environment.
Heavy overload forecasting of distribution transformers based on neural network

The overload management is significance component in distribution network operation and maintenance to improve electricity service. According to the periodic characteristics of the electric load, this paper designs a new method to identify and predict the heavy overload states and highlight the dates where the distribution transformer most likely heavy overload through the historical load rate and meteorological data. The Attention-GRU neural network is introduced to predict electric load rate of the highlight dates to improve the prediction efficiency. In comparison with the performances traditional LSTM in prediction of distribution transformers, results show that the new method has higher accuracy and efficiency in predicting highlight dates’ load rates.
Feature Extraction of Gram-Negative Bacteria Texture Using Grey Level Co-Occurrence Matrix and Scale-Invariant Feature Transform

Gram-negative bacteria are one of the pathogenic bacteria in the respiratory tract.The presence of these bacteria should be identified correctly so that a doctor can do the proper handling of antibiotic therapy.Observations are still made under a microscope by a microbiology clinic or hospital team.This research uses image processing to replace visual inspection.One of the stages in image processing is feature extraction.This research uses a texture approach that is the Grey Level comatrix matrix and Scale-Invariant Feature Transform.The first method uses the grey level approach, while the second method uses the texture object direction approach.Data used in this research get from a sample of 50 patients.It exposed to Gramnegative pathogenic bacteria.The selected bacteria are Klebsiella pneumonia and Pseudomonas aeruginosa.Of the two methods used, the results were compared to obtain information on which method was more suitable for the observation of Gram-negative bacterial objects.The results of the view by examining the effect of object features with ground truth found that the level of accuracy using the grayscale with the similarity of objects approaching and using the object texture direction approach obtained an accuracy of 89%.
Teacher's Manual for The Past, Present and Future of the Safe Water Drinking Act

In order to encourage greater understanding and teaching of the Safe Drinking Water Act, I have written a user-friendly 20-page primer, posted on SSRN as The Past, Present and Future of the Safe Drinking Water Act. To aid teachers using the primer in the classroom, the Teacher's Manual describes how to teach the main features of the law and provides answers to the seven questions posed at the end of the primer.
GENERAL REQUIREMENTS FOR THE DESIGN AND CONTENT OF EDUCATIONAL EDITIONS

Lists and provides definitions of textbooks with the current regulations. The quantitative parameters of educational publications are indicated. The main requirements for their content&#x0D; are given. The structure of educational publications is defined and their main elements are indicated.&#x0D; The list of necessary information for the development and design of textbooks. Regulates the requirements for information and bibliographic apparatus textbooks.
Large-Scale Photonic Integrated Cross-Connects for Optical Communication and Computation

An 8×8 InP cross-connect chip for optical switching within ROADMs is employed for demonstrating optical feed-forward neural networks for analog data processing. An all-optical approach is also explored for deeper optical neuromorphic computing on chip.
La falsa simmetria tra i sessi nella surrogazione di maternità

The objective of this article is to unravel the complexity of the relationships and definitions that are found in the context of surrogacy, investigating, on the one hand, the actual relationships, both material and symbolic, and, on the other hand, the language used by the legal sources, to test the suitability of the language of laws and judgments – a language that holds power – in relation to its material and relational referents. Under examination is the public discourse, of the legislator or the courts, which establishes the rules by which one can officially distinguish a pregnancy “for oneselfµ from a pregnancy “for othersµ. The “subrogationµ, that is the substitution of motherhood, in fact means, in nuce, the affirmation, supported by the force of the law, that the women we see giving birth is not the mother, that the newborn is not her child.
Data-Free Adversarial Perturbations for Practical Black-Box Attack

Neural networks are vulnerable to adversarial examples, which are malicious inputs crafted to fool pre-trained models. Adversarial examples often exhibit black-box attacking transferability, which allows that adversarial examples crafted for one model can fool another model. However, existing black-box attack methods require samples from the training data distribution to improve the transferability of adversarial examples across different models. Because of the data dependence, the fooling ability of adversarial perturbations is only applicable when training data are accessible. In this paper, we present a data-free method for crafting adversarial perturbations that can fool a target model without any knowledge about the training data distribution. In the practical setting of a black-box attack scenario where attackers do not have access to target models and training data, our method achieves high fooling rates on target models and outperforms other universal adversarial perturbation methods. Our method empirically shows that current deep learning models are still at risk even when the attackers do not have access to training data.
Towards Visual Anomaly Detection in Domains with Limited Amount of Labeled Data

Computer image processing and its application in Slovenia 2020 is a professional conference that, since 2006, has been organised every year by the Institute of Computer Science of the Faculty of Electrical Engineering and Computer Science, University of Maribor.The conference connects researchers in the fields of Image Processing and Machine Vision with users of this knowledge, whereby users are coming from diverse industrial environments, such as Biomedicine, Sport, Entertainment, and related fields.The proceedings of ROSUS 2020 combine scientific articles by dozens of authors, including two invited lectures and several demonstration articles.Contributions represent the latest achievements of Slovenian experts in the fields of Image Processing and Vision, and also highlight trends and novelties in these areas.Great emphasis is on promotion of the economic usefulness of Image Processing and Vision applications in the Slovenian region.Namely, such software, due to high precision, robustness, and exceptional speed in information processing, provides new opportunities for penetration on the high technologies market.
Analysis and Study on Mathematical Modeling Classroom Learning Behavior of Higher Vocational Students

The purpose of this study is to analyze the learning behavior of vocational students in the mathematical modeling classroom through the classroom observation scale, and to provide teachers with the necessary cognitive experience and cognitive starting point for mathematical modeling teaching. This paper will class study based on relevant literature. The behavior is divided into five aspects: listening behavior, speech behavior, behavior, practical behavior, and irrelevant learning behavior. Through the development of classroom observation tables, record and statistics the specific behavioral performance of higher vocational students in the classroom. There are obvious differences in the learning behavior in the modeling classroom. The research proposes that interdisciplinary selection of teaching content, appropriate addition of pre-mathematics knowledge, and enhancement of the long thinking ability of higher vocational students, and the strengthening of multiple representation teaching is an improvement of mathematical modeling for higher vocational students. Effective means of teaching.
Student Loans As A Negative Phenomenon Of Educational Policy

The article analyses the current trend of paid higher education crediting. Despite the key role of human capital and technological progress in determining the standard of living achieved through education, the cost of higher education has increased dramatically in some developed countries in recent years. This trend has led to the development of a mechanism for lending to higher education, which has a mixed impact on the further development of the economy. In recent years, the educational systems of many developed countries have faced the problem of insufficient government financing of higher education, caused by numerous financial crises varying by degree of their intensity. As a result, there is an upward trend in private spending on higher education. This phenomenon is, to some extent, violation of rights to equality in education. The solution to this problem came out of the system of educational credits, well-established in many countries. Even those countries (for example, Germany and Sweden), where higher education is fully financed from the budget, apply this loan system, but in a cut form: borrowed funds are used by students for accommodation and cover other costs related to education. Generally educational lending has both positive and negative effects on the higher education system and the economy.
Obituary: Blagovest Sendov, 8 February 1932 – 19 January 2020

I first met Blagovest Sendov in 1963 as a student in mathematics at the Faculty of Physics and Mathematics atВ Sofia University. His first lecture was devoted to Mathematical modeling. On some real life situations Prof. Sendov revealed to us the philosophy of science. Prof. Sendov's ``philosophy'' included a deep understanding of the mechanisms of the underlying real processes, the mathematical description of these processes using contemporary mathematical theories and the solution of the formulated mathematical problems using advanced numerical and computational tools. Prof. Sendov possessed an enormous ability to formulate difficult tasks and problems that need years of efforts to be resolved. At the weekly seminar of ``Mathematical modeling''he used to pose such difficult problems and to make us young collaborators enthusiastic about working on them. He never pressed anybody of us to work on something particular, but he waited that everybody chooses a theme of interest by himself.
Pembelajaran Text Preprocessing berbasis Simulator Untuk Mata Kuliah Information Retrieval

Preprocessing is an important task and step in Information Retrieval.Information Retrieval (IR) is used to decide which documents in a collection must be taken to meet the user's information needs.The comparison is done in 4 steps in preprocessing, namely Case folding, Tokenizing, Filtering, Stemming.All stages of the preprocessing are done manually during the teaching-learning process.The lecturer explained by writing and explaining one by one the correct words at each stage and students also manually reviewed each stage.Simulator is needed to help solve existing problems.The simulator has been successfully created by displaying 6 menus.The simulator has succeeded in outputting each stage according to the manual theory.From the results of the testing questionnaire,> 90% of respondents thought that using this simulator made it easier to work on the four stages of text pre-processing so that the time needed also became efficient.
Terahertz-Frequency Spin Hall Oscillators for Logic Operations

Neuromorphic computing is a field of electronics that uses the similar principles as human brain does. In this paper we show that a spin Hall oscillator based on an antiferromagnetic dielectric material can operate as a terahertz-frequency neuron in neuromorphic schemes. Also, we show that such AFM-neurons can execute most of the logical operation.
application development: a qualitative study Website quality of malaysian technical university (mtun) (part 1)

University website is the platform for university to interact with people. It is also an interphase for people to infer and getting known about the university. In addition, quality of the university website is vital to let people get positive response to the university. Therefore, university website should be evaluated for better performance. This study evaluate website of Malaysian Technical University (MTUN) on year of 2016 based on the criteria selected using online web diagnostics tools. There are nine criteria selected to measure the website; load time, response time, page rank, traffic, design optimization, page size, number of items, markup validation and broken link. The result shows website of UMP performed better in design optimization, page rank and markup validation. Meanwhile, UTHM performed in page rank, load time and page size.  UTEM excellences in response time, number of items and broken link. Lastly, UniMAP performed in traffic criteria only. However, the (MTUN) University website is almost not meets with the criteria that selected with the quality standard that have been suggested.
<i>Migrating library data: A practical guide</i>, Banerjee, K. &amp; Parks, B. (Eds.).

"Migrating library data: A practical guide, Banerjee, K. & Parks, B. (Eds.).." Journal of Web Librarianship, 14(1-2), p. 54
Performing and Blocking Passes in Small Size League

The changes in the Small Size League rules, like increasing the field size and inclusion of more robots in the game have brought greater possibilities of playing and strategies. With the increased complexity of soccer matches, the positioning of the robots has become important as the defense and attack mechanisms. The learning of opposing team game playing has been shown to be effective, but an SSL soccer match indicates the need for solutions that analyze the strategy of the opposing team during the game and make necessary adaptations. This paper proposes the use of the Particle Swarm Optimization (PSO) algorithm as an option to determine the positioning for making and blocking passes during the match. A prototype has been developed to validate the configuration parameters. Experiments in a simulator and analysis of game logs have demonstrated the feasibility of applying the PSO algorithm to find the robots positions.