Reviewerly/exHarmony huggingface dataset:
MIND SET OF MANAGEMENT GRADUATES AND FACULTIES TOWARDS ONLINE LEARNING APPROACH: IMPACT AND RESPONSIVE STRATEGY IN AND AFTER COVID-19 PANDEMIC

Abstract: The main aim of the study is to investigate the mindset of the students towards teaching-learning approach of online education. In order to carry out this study, 300 structured questionnaires were sent amongst students of MBA, young entrepreneurs, banking professionals and others via an online Google questionnaire set. However, 120 respondents replied very vividly in this research question. 120 respondents were selected by applying a convenience sampling technique. This study is quantitative and qualitative in nature with both explorative and descriptive design. The inquiry has exposed the consequences of a new change in the scope of socio economic environment of different colleges and universities of Nepal. This is related to the perception of MBA students to adapt to online education systems introduced by these colleges, as they both have access to the Internet and technical resources. This sort of mind set and the current situation has greatly accelerated the digitalization of the means of education. Likewise, related institutions as such are also showing their readiness to adapt to this teaching-learning methodology and contribute to the human resource development objectives of a country. Keywords:- Covid-19, Online, Responsive Strategies, Management Education, Effectiveness.
The evaluation of English textbook entitled ‘Stop bullying now’

This research was aimed to analyze the eleventh grade of senior high school English textbook based on the standarization of good book criteria from Litz’s and BSNP in terms of content and presentation eligibilities. Moreover, the data were the whole parts of the textbook. For collecting the data, the researcher used questionnaires from Litz and BSNP. The result showed that the textbook fulfilled 5 Litz's criteria among 6 criteria, and fulfilled almost all criteria of BSNP (content and presentation eligibility). In addition, there were some weaknesses of this textbook such as there were no both listening activity and less of speaking skill, or in other words, this textbook had no balance language skill activities among writing, speaking, reading, and listening. In conclusion, the quality of the textbook which had analyzed is good enough although it still needs improvement and revision in several parts. Keywords: Evaluation, textbook, Litz’ and BSNP textbook criteria.
On the use of Markovian stick-breaking priors

In [10], a `Markovian stick-breaking' process which generalizes the Dirichlet process $(\mu, \theta)$ with respect to a discrete base space ${\mathfrak X}$ was introduced. In particular, a sample from from the `Markovian stick-breaking' processs may be represented in stick-breaking form $\sum_{i\geq 1} P_i \delta_{T_i}$ where $\{T_i\}$ is a stationary, irreducible Markov chain on ${\mathfrak X}$ with stationary distribution $\mu$, instead of i.i.d. $\{T_i\}$ each distributed as $\mu$ as in the Dirichlet case, and $\{P_i\}$ is a GEM$(\theta)$ residual allocation sequence. Although the motivation in [10] was to relate these Markovian stick-breaking processes to empirical distributional limits of types of simulated annealing chains, these processes may also be thought of as a class of priors in statistical problems. The aim of this work in this context is to identify the posterior distribution and to explore the role of the Markovian structure of $\{T_i\}$ in some inference test cases.
Analysis on the Application Prospect of Virtual Reality Technology and Material in Physical Education

With the update and growth of science and technology, educational concepts continue to innovate. In the sports field, the use of Virtual Reality (VR) technology is undoubtedly a brand new training experience. The use of VR technology in the physical education (PE) classroom has promoted the growth of PE and also allowed students to master physical skills more comprehensively through high technology. The purpose of this article is to understand VR technology, study the mterial of VR, improve the shortcomings of traditional PE through VR technology, and analyze the application prospects of VR technology in PE. This article mainly adopts the interview method, sample survey method and case analysis method to sample a survey of 120 students in three grades of a middle school to conduct questionnaire surveys and field visits to understand the students’ knowledge of VR technology and the use of VR technology. We also can know the views of the PE for students. Through this series of investigations, the prospects of VR technology being applied to PE are analyzed. Experimental research results show that the most supported PE activity for VR technology at this stage is situational setting, and 35% of students hope that VR technology will be prominent in the context of the picture. The application of VR technology in physical education will undoubtedly bring a different experience to school sports activities. However, due to the lack of funds and professionals, it is difficult to carry out VR technology in teaching activities. So we can start from the context setting and use economical means to pave the way for physical education.
The Impact of Modern Technology on Chinese Education

With the rapid development of the Internet and modern technology, education is becoming more and more technological.In particular, during the COVID-19 epidemic prevention and control period, online education was fully adopted in China.This paper makes a specific analysis on impact of modern technology on Chinese pedagogy in four aspects: "smart classroom", the transformation of the role of teachers, the responsibility and anxiety of parents under Internet teaching, and targeted poverty alleviation through Internet + education, and puts forward some useful suggestions.For example, to improve teachers' personal skills in using Internet technology; Lead parents to understand the benefits of Internet education and reduce parents' anxiety by limiting students' use of electronic devices; Vigorously develop Internet + education to promote the balance of education in China.
Re-using Adversarial Mask Discriminators for Test-time Training under Distribution Shifts

Thanks to their ability to learn flexible data-driven losses, Generative Adversarial Networks (GANs) are an integral part of many semi- and weakly-supervised methods for medical image segmentation. GANs jointly optimise a generator and an adversarial discriminator on a set of training data. After training is complete, the discriminator is usually discarded, and only the generator is used for inference. But should we discard discriminators? In this work, we argue that training stable discriminators produces expressive loss functions that we can re-use at inference to detect and \textit{correct} segmentation mistakes. First, we identify key challenges and suggest possible solutions to make discriminators re-usable at inference. Then, we show that we can combine discriminators with image reconstruction costs (via decoders) to endow a causal perspective to test-time training and further improve the model. Our method is simple and improves the test-time performance of pre-trained GANs. Moreover, we show that it is compatible with standard post-processing techniques and it has the potential to be used for Online Continual Learning. With our work, we open new research avenues for re-using adversarial discriminators at inference. Our code is available at https://vios-s.github.io/adversarial-test-time-training.
Graph Neural Networks: Methods, Applications, and Opportunities

In the last decade or so, we have witnessed deep learning reinvigorating the machine learning field. It has solved many problems in the domains of computer vision, speech recognition, natural language processing, and various other tasks with state-of-the-art performance. The data is generally represented in the Euclidean space in these domains. Various other domains conform to non-Euclidean space, for which graph is an ideal representation. Graphs are suitable for representing the dependencies and interrelationships between various entities. Traditionally, handcrafted features for graphs are incapable of providing the necessary inference for various tasks from this complex data representation. Recently, there is an emergence of employing various advances in deep learning to graph data-based tasks. This article provides a comprehensive survey of graph neural networks (GNNs) in each learning setting: supervised, unsupervised, semi-supervised, and self-supervised learning. Taxonomy of each graph based learning setting is provided with logical divisions of methods falling in the given learning setting. The approaches for each learning task are analyzed from both theoretical as well as empirical standpoints. Further, we provide general architecture guidelines for building GNNs. Various applications and benchmark datasets are also provided, along with open challenges still plaguing the general applicability of GNNs.
Design And Implementation IVR Outbound Service API Using Text-To-Speech

In business world, customer support is one way to build relationships with customers. Phone calls are one of the customer support media that is widely used because of its flexibility. But the limited customer support workers can cause customers to wait a long time to be served. One solution that can be done is to install an IVR (Interactive voice response) system. IVR is a system mechanism that provides automated talks based on the response of DTMF (Dual-tone multi frequency).In addition to serving customer complaints or inquiries, IVR can also be used to provide information to customers. This IVR is called the outbound IVR service because it is the companies that make phone calls to customers. In this study, an IVR system was created with outbound service model. The IVR system also provides a feature for companies to create and manage their own IVR menus by inputting response numbers and words that will be listened to customers. In the process, the system also uses a text-to-speech library to convert text to voice, using the PJSIP library to make phone calls over sip protocol, using MongoDB as database, and Redis as cache.
Amazon says it doesn't use sellers' data after Wall Street Journal story

Amazon said it's against its policy to use the data and that the company was launching an internal investigation into the issue.
MOOC영상 콘텐츠 제작 연구 - S대학교 MOOC강좌 개설을 위한 콘텐츠 자체제작을 중심으로

The purpose of this study is to review the possibility of producing MOOC textbooks by examining the process of creating contents for MOOC courses on campus and to propose a standard plan in relation to the K-MOOC development method. The subjects of this study were the MOOC content production process in conjunction with the start of the second semester of 2016 at S university. By independently producing MOOC content inside the school, the displayed features are summarized as follows. 1) The experience of opening an e-learning lecture was a positive motive for the production of MOOC lectures, and it is feasible to create all new content. 2) On-campus equipment and equipment for content production are prerequisites, and a country-wide approach is necessary to resolve copyright issues in an educational context. 3) The MOOC textbook should be structured to allow flexible time allocation and interaction between instructors and learners. 4) In order to realize MOOC's educational philosophy of mass online classes, it is necessary to formulate a comprehensive budget linked to the costs which will be incurred for interaction with an unspecified majority of users. The results of this review posit a reasonable means of complying with MOOC's philosophy to produce content for the opening of MOOC courses on campus.
Scaling Laws for Deep Learning

Running faster will only get you so far -- it is generally advisable to first understand where the roads lead, then get a car ... The renaissance of machine learning (ML) and deep learning (DL) over the last decade is accompanied by an unscalable computational cost, limiting its advancement and weighing on the field in practice. In this thesis we take a systematic approach to address the algorithmic and methodological limitations at the root of these costs. We first demonstrate that DL training and pruning are predictable and governed by scaling laws -- for state of the art models and tasks, spanning image classification and language modeling, as well as for state of the art model compression via iterative pruning. Predictability, via the establishment of these scaling laws, provides the path for principled design and trade-off reasoning, currently largely lacking in the field. We then continue to analyze the sources of the scaling laws, offering an approximation-theoretic view and showing through the exploration of a noiseless realizable case that DL is in fact dominated by error sources very far from the lower error limit. We conclude by building on the gained theoretical understanding of the scaling laws' origins. We present a conjectural path to eliminate one of the current dominant error sources -- through a data bandwidth limiting hypothesis and the introduction of Nyquist learners -- which can, in principle, reach the generalization error lower limit (e.g. 0 in the noiseless case), at finite dataset size.
번역 학습자의 서한 번역전략 분석 - 기사문 관계절을 중심으로 -

This study aims to examine how structural differences between Spanish and Korean in relative clauses affect the achievement of the translation goal of communicative translation. For this purpose, relative clauses of Spanish news texts used in actual translation class for graduate students (ST) and their translations in Korean (TT) were collected. For the analysis, the clauses were divided according to cases such as subjective, objective, oblique, possessive and appositive cases, and categorized into two types: restrictive and non-restrictive clauses, given that the two languages differ in the use of relative clauses. The analysis reveals that translation learners adopt distinct strategies for different types and cases of relative clauses by using connective endings, altering parts of speech in target language or switching the position of antecedent, etc. in accordance with the principle of conciseness of news texts. On the other hand, findings show that translations taking into account the differences between Spanish and Korean turn out to be more TL reader friendly, thus more communicative. The study concludes that when translating Spanish relative clauses into Korean, learners should consider the heterogeneity between the two languages, understand the function of the text to be translated and review the translation strategy from the perspective of the TL reader.
Effectiveness of OSForensic in Digital Forensic Investigation to Curb cybercrime

With the rapid development and higher level of dependence on new information and technology by various organizations across the world, cybercrime issues are increasing, and there are no technologies that seem flawless in combatting the issue. The use of concepts relating to digital forensic investigation of criminal activities and digital forensics will, therefore, tackle the problem with finding digital evidence in cybercrimes. OSForensics is one of the various digital forensic investigation tools that allows the use of Hash Sets for identifying known safe files in program and operating system files. The tool is essential for identifying suspected files like Trojans, viruses, and hacker scripts. The problem presented in this paper, therefore, entails utilizing combinations of digital forensic investigation of criminal activities and investigation concepts. The paper seeks to establish the effectiveness of OSForensic in Digital Forensic Investigation to curb cybercrime. That is, the capabilities of OSForensics and the accuracy of OSForensics with regards to retrieving and analyzing data from a hard drive in order to investigate and curb cybercrime at the workplace. The researcher investigated a case in which a company security had been threatened by an employee whose contract had recently been terminated. The company suspected that this employee had some serious pictures, locations, and employee details belong to company. The image of the employee’s personal flash was sent to the researcher to help initiate the investigation using OSForensicssoftware so as to establish any evidence that the employee still had pictures, locations, and employee details belong to company. In overall, OSForensic was able to identify company details that the employee was having. The research was able to identify sensitive information about the company that the suspect was having, including the names of the employees, images, company system structure and what seemed to be their respective identification numbers.
Predicting Bit Coin Price Using Deep Learning

Currently there is no fixed system who can value the real weight of bitcoins. All over the globe the authors argue about the merits and demerits of bitcoin. Due to the increasing valuation of Bitcoin many investors are investing large amount on bitcoin. Here in this paper we propose a Artificial Neural Network based Deep Learning approach to predict the future value of Bitcoin using the historical available data.
Ars Musica Mathematica: Connections and Relationships

The connections, similarities and relationships between music and mathematics are deep, multiple and complex, and include not only ways to mathematically express music, but also linkages and associations around matters of logic (Hofstadter, 1999); aesthetics (Kung, 2013); form, geometry and architecture (Menhinick, 2015); cosmology (James, 1995); cognition, mind and brain (Mazzola, 2018); computing (Muller, 2016); historiography and biography (Maor, 2018); research, improvisation & creativity (Schneiderman, 2011); phenomenology (del Cerro Santamaria, 2015); representation, metaphors and methods of abstraction (Rothstein, 2006), and others.
EFEKTIVITAS PENGGUNAAN PETA KONSEP TERHADAP HASIL BELAJAR SISWA KELAS VII SMP NEGERI 2 PONRE KECAMATAN PONRE KABUPATEN BONE.

Abstrack. This research is an experimental study aimed to determine the effectiveness of the use of the Concept Map Method on the Biology Learning Outcomes of Class VII Students at MTs Bulu-Bulu, Tonra District, Bone Regency. The research design was Posttest–Only Control Design. The population in this study were all seventh grade students of MTs Bulu-Bulu, Tonra District, Bone Regency and the sample consisted of two classes, namely class VII A as the control class and class VIIB as the experimental class. Data collection techniques are tests and documentation. The data analysis technique used is descriptive statistical analysis and inferential analysis. Based on the results of the analysis and discussion of the Effectiveness of the Use of the Concept Map Method on the Learning Outcomes of Class VII Students at MTs Bulu-Bulu, Tonra District, Bone Regency, it can be concluded that the average result of the Biology learning outcomes of students in the experimental class is 82.75 while in the control class is 82.75. 74.76. The results of hypothesis testing by t-test, in the calculation of t-test known 3.00 and ttable 2.023 with db of 39, obtained from 21+20 – 2, at a significant level of 0.05 (5 %), so that t count &gt; t table= 3.00 2.023, it can be concluded that the null hypothesis (H 0 ) is rejected and the alternative hypothesis (H 1 ) is accepted
Construction of College English Online Teaching Resources Based on Cluster Analysis Algorithm

The increasing popularity of the Internet enriches the learning channels for college students, promotes the sharingof college English teaching resources, and stimulates students' interest in learning while improving the quality ofEnglish teaching. The establishment of digital college English teaching resource library can realize the coconstructionand sharing of resources among teachers, students, schools and enterprises. English networkresource library can provide rich and high-quality teaching materials for English teachers to prepare lessons, andalso provide conditions for students to use the resource library to obtain information and learn independently. Thenetwork has the characteristics of openness and virtuality, which increases the dilemma of teaching resourcessharing to a certain extent. Therefore, how to use the advantages of the network to enhance the sharing of Englishteaching resources is an important and urgent issue facing college English teaching. Based on cluster analysisalgorithm, this paper analyzes the existing problems in the construction of English online teaching resourcesdatabase, and puts forward the principles that should be paid attention to in the construction of resources, in orderto realize the construction of efficient online teaching resources for college English and play its due role in modernEnglish teaching.
Target Detection via Quantum Illumination: Range Equation

In this article, the basic principle of target detection based on Gaussian state quantum illumination (QI) has introduced. The performance of such system has compared with its classical counterpart, which employs the most classical state of light, i.e., coherent state, to illuminate the target region. By deriving the maximum range equation, we have demonstrated that the quantum illumination based target detection system is especially advantageous at low transmission powers, which make these systems suitable for short range applications like biomedical imaging or covert detection schemes.
Development of Innovative Live Design Project (ILDP) based on IC-PBL for Higher Education

The purpose of this study is to develop an innovation model through industry-academia cooperation by grafting the concept of IC-PBL onto design methodologies and design processes. Another purpose is to evaluate the field applicability of the model by implementing a model-based project. First, as for the research method, an ILDP (Innovative Live Design Project) model was derived by grafting the design process onto the concept of IC-PBL. Second, a syllabus based on the model was presented, and the live design project implemented in the actual education. Third, through a questionnaire with 11 students who participated in the course, data on the field suitability of the model were derived. Three corporate executives and professors evaluated the innovativeness of the students’ design outcomes. As a result, the level of understanding and the difficulty of activities were shown to be high, exceeding the average values. Positive factors included ‘experience in actual company works’ and ‘experience in the feedback of persons in charge of actual work’. In addition, the evaluation of innovativeness, there were opinions that the viewpoint of problem solutions was remarkable, and the design outcomes were judged to have innovativeness. However, time allocation caused by continuous feedbacks of clients showed as the factor of problem, which should be improved for highly satisfactory through the refinement of time allocation of decision-making process. Therefore, the experiences gained from the practice based live project show that the ILDP model appropriate in aspects of the field suitability. Also, the reflections through industry linked courses improve students not only to be more responsible future practitioners but also to produce innovative outcomes. Keywords: Live Design Project, Innovative Design Learning Model, IC-PBL, Higher Education