Reviewerly/exHarmony huggingface dataset:
Automating the Assessment of student’s Descriptive Answer Using Natural Language Processing

In educational institutions a major concern is evaluation of answer sheets of subjective type questions. Descriptive Answer Assessment Using NLP aims at making this time consuming and tedious task of correcting students answer scripts very easy by utilizing the techniques of Natural Language Processing. The objective of Descriptive Answer Assessment Using NLP is to automate the process of evaluating descriptive answer scripts. Various algorithms are used to find the similarity between the reference answers and the student answer scripts. If the similarity is high, more marks will be awarded. Using several text similarity algorithms, the similarity and relative accuracy will be determined. Marks are assigned to students based on the degree of similarity with the student answer and reference answer. The work aims in exploring various Text Similarity algorithms in identifying their relative accuracies. There are several advantages of using this automated system like it helps in reducing the time taken by faculty to correct  the papers, the tests or examinations can be conducted online, the answers can be evaluated immediately and  it would be beneficial for universities, schools and colleges for academic purpose by providing ease to faculties and the examination evaluation cell.
Optimization of Collaborative Filtering Algorithm in Movie Recommendation System

In the era of big data information explosion, people are faced with a large amount of information every day, and how to obtain the required content in a large amount of information. The appearance of intelligent recommendation system has brought great convenience to our life. The recommendation system can recommend corresponding functions, products and services according to users’ past browsing information, enabling users to get their desired information data from massive data more efficiently. As an indispensable part of most people’s entertainment life, movie recommendation has also become a very important part of Internet recommendation content. The collaborative filtering algorithm is used to realize the personalized recommendation of movies. However, in the process of movie recommendation, it is found that new users are only recommended movies based on their ratings without considering the attribute information between movies, which may lead to problems such as inaccurate recommendation accuracy. Therefore, this paper further optimizes the collaborative filtering algorithm and introduces the similarity calculation between movie attributes to improve the accuracy of movie recommendation.
تأثير استخدام الوسيلة التعليمية "صندوق الأسرار" لتنمية مهارة الكلام (دراسة كمية للفصل العاشر في المدرسة الثانوية الإسلامية "غزالية" سومبرموليا جوغوروتو جومبانج)

In this article, the purpose of this study is to determine the use of learning media Mystery Box, to determine learning speaking skills, and to determine the effect of using learning media Mystery Box to improve speaking skills. Researchers here use quantitative methods with observation, interviews, and documents. The research results: 1) The teacher there has taught very well. But it is better if there is a learning medium. 2) The results of the research are also different in the experimental class 15.50 and the control class 5.50. So it can be concluded that the Arabic language teaching process is better using learning media. 3) There is an influence between the experimental class and the control class in the application of the Mystery Box learning media. This is indicated by the results of the Mann-Whitney test with a Sig value of 0.000 <0.05
Efﬁcient Neural Architecture Search for Language Modeling

Neural networks have achieved great success in many difﬁcult learning tasks like image classiﬁcation, speech recognition and natural language processing. However, neural architectures are hard to design, which requires lots of knowledge and time of human experts. Therefore, there has been a growing interest in automating the process of designing neural architectures. Though these searched architectures have achieved competitive performance on various tasks, the efﬁciency of NAS still needs to be improved. Moreover, current neural architecture search approach disregards the dependency between a node and its predecessors and successors. This thesis builds upon BayesNAS which employs the classic Bayesian learning method to search for CNN architectures, and extends it to the problem of neural architecture search for recurrent architectures. Hierarchical sparse priors are used to model the architecture parameters to alleviate the dependency issue. Since the update of posterior variance is based on Laplace approximation, an efﬁcient method to compute the Hessian of recurrent layer is proposed. We can ﬁnd candidated architectures after training the over-parameterized network for only one epoch. Our experiments on Penn Treebank and WikiText-2 show that competitive architectures can be found in 0.3 GPU days using a single GPU for language modeling task. We ﬁnd that our algorithm is more efﬁcient than state-of-the-art.
While Appreciating Bernstein’s Work, We Need to Critically Evaluate His Ideas from the Vantage Point of Present Scientific Knowledge

Publication of the book by Nikolai Bernstein, On the Construction of Movements, is an essential scientific event that familiarizes the readers with thoughts of an outstanding scholar in the field of behavioral neuroscience. It is also a significant cultural event contributing to the always interesting history of science. Bernstein was brilliant in formulating several fundamental problems in the field. Some of these problems remain unsolved. The present comments are an attempt to identify the obstacles that prevented Bernstein from solving these problems. By identifying such obstacles, might be helpful in solving at least some of these problems in future research.
The Application of FP-Growth Algorithm on Data Mining of Association Rules From Law Lists

Law list is an important compliance management tool for enterprises. FP-growth algorithm is one of the comparatively effective algorithms in association rule data mining sector. FP-growth algorithm is simplified to dig frequent 2-itermset only. Association rules are mining in the Law-List Boolean form, which were created based on frequent 1-itermset and law lists.
POISSON REGRESSION MODEL PREDICTION ON THE VALUE OF ACADEMIC PUBLICATION

feasible implementation to predict the future outcomes is by using a poisson regression model to forecast the quantity of research publication which is supported by the time spent in developing research and the number of years experienced by an academician. Poisson regression method is a classification of General Linear models where the variable under observation follows a poisson distribution with discrete variables making it identical to poisson regression model. Research is a skill to be practiced; however there are numerous components of this skill that must be directed, so potential knowledge makers can navigate contradictory, unpredicted and sensitive situation successfully.
ARES: A Reading Comprehension Ensembling Service

We introduce ARES (A Reading Comprehension Ensembling Service): a novel Machine Reading Comprehension (MRC) demonstration system which utilizes an ensemble of models to increase F1 by 2.3 points.While many of the top leaderboard submissions in popular MRC benchmarks such as the Stanford Question Answering Dataset (SQuAD) and Natural Questions (NQ) use model ensembles, the accompanying papers do not publish their ensembling strategies.In this work, we detail and evaluate various ensembling strategies using the NQ dataset.ARES leverages the CFO (Chakravarti et al., 2019) and Reac-tJS distributed frameworks to provide a scalable interactive Question Answering experience that capitalizes on the agreement (or lack thereof) between models to improve the answer visualization experience.
HOPKIN CRITERIA IN BOOK ENTITLED “BUSINESS BASIC I” USED FOR STUDENT AT UNIVERSITY

English used for every reason at university for example English collaborated with business that must be more important in daily uses as the English for specific things or purposes. All we know it as English for Specific Purposes or ESP. Such as in the development of teaching and learning English especially English in university or in ESP we need a media or book in their procedure and its implementation. And for its procedures every materials or book are needs to be appropriates in their materials with the education aspect such as the philosophical aspects on its. On addition philosophical aspect is the main aspect on it that can be a hence to elaborates the material for the student need especially for ESP student. This research objective is to explain the appropriateness of the philosophical aspects by the Hopkin theory in book entitled “Business Basic I” for ESP Student in terms of its contents. The design of this study is descriptive qualitative, and it is taken from documents and material resumed in its book. This research is categorized as qualitative research design because this study is aimed to identify the book toward the criteria of good book and its content. Based on the result and analysis of the research that have been done, the writer can conclude that a book with the title “Business Basic I” was categories in an appropriate and a good book related to the description of the material. And for the interpretation toward the philosophical foundation aspects that consist six aspects such as Clarity, Consistency with the fact, Consistency with Experience, Consistency with other Beliefs, Utility and Simplicity it can be shown that this book run and construct by social reconstruction philosophy and structuralism philosophy. It can be shown from the several philosophical foundation aspects from the data collection result
IBM IMPLEMENTASI METODE AJAR INTERAKTIF MENGGUNAKAN VIRTUAL REALITY (VR) UNTUK PENDIDIKAN ANAK USIA DINI (PAUD) DI RUMAH QUR’AN AISYAH

The Science and Technology Service for the community is carried out to the manager and teacher of the House of Aisyah Quran (RQA) located on Jl. BuakanaNo. 60, Makassar. Our partner is an educational institution that focuses on early childhood education (PAUD) / Kindergarten, Day Care and Tahfidz Quran for children aged 0-6 Years. Our dedication activity aims to provide technology utilization training to partners in creating interactive, communicative, innovative and fun learning materials so that students are able to realistically rationalize learning materials and provide stimulation. In addition, the target achieved in implementing IbM activities is to increase partner knowledge regarding the use of technology-based learning media. Children's ability to rationalize or concretize the story told by the teaching staff becomes more realistic. It is hoped that through the learning application that we make, children's enthusiasm for learning will increase and be able to stimulate children's psychomotor. The method used in service activities is counseling and training in the use of technology in making teaching materials. Implementation of Virtual Reality based learning material applications. The result of this activity is a virtual reality based learning module in the form of software applications with hardware that will be used by the teaching team and students. With this activity, the partner team felt helped and was open-minded about the use of technology in making interactive learning media for young children.
DEEP LEARNING-BASED MOTION ACTIVITY RECOGNITION USING SMARTPHONE SENSORS

MHealth systems establish a new way to transfer the health service to remote places.These systems offer significant benefits for continuous health monitoring.Motion activity recognition is one of the challenging mHealth use cases that incorporates continuous data collection and analysis of measurements.The main goal of this research is to analyze physical activity data.We employ measurements from the WISDM lab dataset 1 .These data are collected from participants performing motion activities.This data is then used by deep learning algorithms to predict special activities.In particular, CNN and CNN-LSTM algorithms are used to compare their accuracy, which resulted in approximately 95% and 97% respectively.Thus, the CNN-LSTM has higher accuracy in this analysis.
La legalità disegnata. Appunti su disposizioni non testuali e diritto penale

The work aims to investigate – from a peculiar criminal law perspective – the constitutive-pragmatic and not only epistemic relevance of non-textual rules, which accompany the usual textual rules in different areas of the legal system. If traditionally social objects are inscribed in linguistic-verbal propositions, nevertheless the construction of social reality abounds with examples of non-textual rules. Once the possibility of theoretically conceiving social objects descended from non-textual provisions has been probed, the investigation identifies a working hypothesis to reconcile – in the criminal law context – this conclusion with the principle of legality. The analysis continues with an example of three different hypotheses of non-textual rules: non-textual rules integrating textual rules (the example is the road signals); non-textual rules complementary to textual ones (the example is the workplace health and safety signals); finally, autonomous non-textual rules (the example is the project).Parole chiave: Rules; Text; Drawing; Legality; LawIndice: 1. Suggestioni – 2. Documentalita, testualita e idiomaticita – 3. Le disposizioni non testuali nella prospettiva penalistica. Ipotesi di lavoro – 4. Disposizioni non testuali integratrici di disposizioni testuali: l’esempio della segnaletica stradale – 5. Disposizioni non testuali complementari di disposizioni testuali: l’esempio della segnaletica di salute e sicurezza sul lavoro – 6. Disposizioni non testuali autonome: l’esempio del progetto
Implementasi Sistem Informasi Geografis Persebaran Tempat Pembuangan Sampah Legal Di Kota Medan

The Medan City Sanitation and Gardening Service in presenting information on the location of legal landfills is still utilizing the Microsoft Word or it can be said to be manual. So it is less efficient in updating the object data. Researchers try to solve problems that occur by implementing geographic information systems that are implemented with the Google Maps API. In this study, data collection uses the RnD (Research and Development) method, while the system design used is OOAD (Object Oriented Analysis Design). The results of this study indicate that the GIS point of the location of legal waste dumps in the City of Medan Sanitation and Regulatory Service can provide benefits to the garbage transporters and the public towards effective and efficient legal waste disposal sites.
AWC 708C Laser Cutting Manual Learning Set

This research paper presents AWC 708C laser cutting manual learning set. It is a learning set which is relevant to high school courses and taught in a module (namely 30291 Creativity and Innovation). The researchers have developed a combination between the augmented reality technology and the AWC708C laser cutting learning kit to make them more attractive and reduce danger to users by adding additional security systems to the device. Also, it includes teaching how to use the machine through a designed worksheet to accompany with an augmented reality technology which is intended to be suitable for high school students in grade 10 (Mathayomsuksa 4). The results of this research found that overall quality of the AWC 708C laser cutting learning kit is in good quality level with average of 4.48±0.58. Outstanding results from an overall quality assessment are the convenience in preparing the equipment and the simple method of using the machine. Also, the quality level of the worksheet is in good quality level with average of 4.24±0.66. In addition, it was found that the results of the evaluation on satisfaction with the AWC 708C laser cutting machine learning kit is in very good level with average of 4.77±0.42. From the comparison of academic achievement between before and after using the learning set analyzed by t-test, it is found that the pre and post test scores of the sample groups had an average score of 5.50 and 8.96, respectively. From t distribution table which has df = 23, confidence value at 0.05 level with t = 2.707, the analysis result is 15.37 higher than the t distribution table. It is implied that the results of the pre-test achievement were different from the post-test achievement scores with significance level of 0.05. From the research hypothesis, it is found that those who studied with AWC708C laser cutting manual learning set had academic achievement after studied higher than before, according to the assumptions. Hence, in this research it can be concluded that the quality of the AWC 708C laser cutting machine learning kit can be increased.
Direct Scaling of Video Quality Dimensions

In the previous chapter, the unknown perceptual video quality space was investigated and identified. In this chapter, a new method in the domain of video quality assessment is presented, using the five identified quality dimensions.
Smart contracts ou “contratos inteligentes”: o direito na era da blockchain

One of the great innovations brought about by the use of Blockchain technology is smart contracts, in which the parties define all clauses that are enforced automatically without the intervention of a third party, not even the judiciary. It causes a big change in the traditional postulates of contract theory such as: Are they really contracts? What if mistakes are made? Impacts on governance and complete contract theory are analyzed in the text, as well as impacts on classical contract law, especially considering the perspective of neoconstitutionalism. From this last point of view, such contracts are seen as a new paradigm for the adjustment of wills, affecting the idea of depersonalization of civil law, under analysis by the Economic Theory of Law. Using bibliographic research as a methodology, it follows that smart contracts can be considered contracts in light of the Brazilian legal system, although they have a huge potential for disruption of traditional contract theory.
SISTEM INFORMASI PELAYANAN WARGA RW 01 KELURAHAN RAWA BUAYA BERBASIS WEBSITE

The process of managing data for residents in RW 01 RT 003 Kelurahan Rawa Buaya currently running, there are several identified problems, namely difficulties in finding data because it is still stored in the form of an agenda, making a cover letter that must take a long time because it is still manually recorded. The purpose of this thesis report is to design a citizen service information system using the waterfall method and for modeling the system using UML while the programming language uses PHP and for Database using MySQL. The results of this study indicate that the use of a citizen service information system can help the registration and data collection of residents in managing moving data and the process of making reports on monthly population and transparency in local RT finances as expected.
Low Rank Sample Reconstruction-Based Semi-supervised Feature Subspace Learning

Feature subspaces have been widely applied in image classification.However, majority conventional subspace learning models are supervised，the data containing only partial labeled samples will lead to unsatisfactory classification results in practical applications.To address this problem, in this paper, we design a graph semi-supervised feature subspace model named low rank sample reconstruction-based semi-supervised feature subspace learning, which combines graphbased semi-supervised learning and low lank sample reconstruction into a unified framework.The proposed model implementing low rank constraint on representation coefficient, exploits the graphbased label propagation algorithm to predict the unlabeled labels to obtain the labels of all samples.The experimental results demonstrate that the robustness and the classification efficiency of our model.
Quality Feature Space of Transmitted Video

In this chapter, the quality-relevant dimensions of transmitted video are identified. The results are obtained from exploratory experiments. This chapter gives a brief explanation of the used methods and a detailed description of the conducted experiments.
Joint Cross-view Heterogeneous Discriminative Subspace Learning via Low-rank Representation

The cross-view data are very unforced to capture due to the face that different viewpoints or data collected from different sensors are already very common in recent years.However, cross-view data from different views present a significant difference, that is, cross-view data from different categories but in the same view have a higher similarity than the same category but within different views.To solve this problem, we have developed a dual low-rank representation framework to unbind these interleaved structures in a learning space.In addition, we consider that each cross-view sample of the same category is from isomorphic and heterogeneous information of two interlaced structures.Hence, we propose a powerful joint cross-view heterogeneous subspace feature learning model.In addition, the subspace learned by our algorithm contains more useful information and is more adaptable to cross-view data.
PREVENTING TEACHER’S EMOTIONAL BURNOUT: PRESERVING AND STRENGTHENING TEACHER’S HEALTH

This article is devoted to the problem of early prevention of teacher’s emotional burnout to preserve theirhealth, stimulate personal and professional development.The main idea of the article is the need for early comprehensive psychodiagnostics of professional andpersonal development of teachers for the prevention of teacher’s emotional burnout. A theoretical analysisof diagnostics models of pedagogical activity of the teacher and methods of its diagnostics is carried outin the article. The analysis held revealed the problem of insufficient development of a comprehensivepsychodiagnostic approach to the prevention of emotional burnout of teachers. The article describes theauthor’s method of comprehensive psychodiagnostics of pedagogical activity, taking into account its threecomponents: design and gnostic, communicative-perceptive and reflective components. The application ofcomprehensive psycho-diagnostic approach to pedagogical activity of a teacher has shown its effectivenessin the prevention of emotional burnout of teachers.