Reviewerly/exHarmony huggingface dataset:
Modeling and Analysis of Zenith based Passive Solar Tracking Mechanism

A novel gravity-based, power-free solar tracking mechanism is being developed to track the movement of the sun across day length. A compound parabolic collector having 3 parabolic segments is chosen due to its high intercept factor and suitability to the current tracking as compared to a cylindrical parabolic collector. Used to concentrate the incident solar radiation to the focal point, the Compound Parabolic Collector accumulates heat at the central coil, which is in turn used for process heating applications. The working of the tracking mechanism is studied to find the tracking loads in the east and the west sides of collector. We intend to simulate the tracking motion from the sunrise to sunset, in order to validate the empirical findings. The identified design variants are sprocket wheel diameter, suspension, solar collector’s weight, counter balance and loading on the shaft. The recommended diameter for the sprocket wheel and shaft is 2500mm and 50mm respectively.
NEW UKRAINIAN SCHOOL: INFORMATION AND COMMUNICATIVE TECHNOLOGIES IN QUARANTINE

The article analyzes the development of distance learning to quarantine with students, which was of a practical nature. The article substantiates the importance of the online platform Google Classroom. The first steps are introductory consultations and instructions on working remotely. Among the problems is the digital inequality of the target audience of students. As teachers, we first of all had to gather and use the tools we had mastered at webinars, trainings, online marathons, online schools, etc .. ", Educational project" On the lesson ", Geek Journal, Ukraїner, Matific, Duolingo, Childdevelop, Code Studio, Study-smile, My Class, etc. At first, students were interested in learning, they were creative, they created, but later they lacked "live" communication. It is justified that the educational process needs to change with the change of information and educational environment. But it is necessary to change gradually, involving students in: development of tests for schoolboys on platforms "All education", "On a lesson"; creation of own sites, blogs; rationally use interactive distance learning tools in their work with children. The emphasis is on the system "teacher-student (parents) -student". Everyone had the opportunity to build an individual learning trajectory, partially meet the needs of students by acquiring the knowledge that is important to them, which will contribute to the development of information and communication competence not only teachers but also all participants in the educational process. Particular attention is paid to the issue of substantiation of the main problems of development of digital competence of pedagogical staff of NUS. Emphasis is placed on the fact that the teacher can organize the following modes of learning: live online communication, when at the appointed time, you organize a video conference, chatting with students; distance learning, stretched in time, when using certain digital tools, a platform for independent learning is created with the active indirect participation of the teacher. It is noted that it is important not only to allow teachers to use distance learning tools, but also to modify the existing educational program to take into account the distance format.
Effectivity of Asynchronous Learning on Theoretical Compared to Theoretical-Practical Courses at Film Department Universitas Multimedia Nusantara

AbstractImplementation of the e-learning method is a necessity, both synchronous and asynchronous modes. Universitas Multimedia Nusantara (UMN) encourages all of its study programs to implement both synchronous and asynchronous. Meanwhile, there are two types, of course, theoretical and theoretical-practical courses. Due to the specific nature of its learning process, the effectiveness of asynchronous learning is not yet proven. This research aims to evaluate implementing the asynchronous method on theoretical and practical courses at Film Department, UMN. The research was done quantitatively, using descriptive analysis and comparative test method, involving two hundred ninety-five respondents who participated in the study by filling questionnaires. The evaluation was done on the effectiveness of seven courses categorized into two types: theoretical and theoretical-practical courses. The results indicate that the implementation of asynchronous e-learning on seven courses is effective. Furthermore, there is no significant difference between the implementation of asynchronous e-learning on theoretical and theoretical-practical courses. Based on this study, it is recommended that lecturers who apply asynchronous learning in their classes be more active in responding to the students. Challenging activities can also be added to make the discussion forum more active. Efektivitas Pembelajaran Asynchronous pada Mata Kuliah Teori dan Praktik di Prodi Film Universitas Multimedia Nusantara Abstrak Penerapan metode e-learning merupakan suatu kebutuhan, baik berbentuk sinkron maupun asinkron. Universitas Multimedia Nusantara (UMN) mendorong seluruh program studinya untuk menerapkan kedua bentuk e-learning ini. Sementara itu, ada dua jenis mata kuliah, teori dan praktik. Karena sifat spesifik dari proses pembelajarannya, efektivitas pembelajaran asinkron belum terbukti. Penelitian ini bertujuan untuk mengevaluasi efektivitas penerapan metode asinkron pada mata kuliah teori dan praktik di Prodi Film UMN. Penelitian ini dilakukan secara kuantitatif, menggunakan metode analisis deskriptif dan uji komparatif, dengan melibatkan dua ratus sembilan puluh lima responden yang berpartisipasi dalam penelitian dengan mengisi kuesioner. Evaluasi dilakukan terhadap efektivitas tujuh mata kuliah yang dikategorikan menjadi dua jenis, yaitu teori dan praktik. Hasil penelitian menunjukkan bahwa penerapan e-learning asynchronous pada tujuh mata kuliah sudah efektif. Tidak terdapat perbedaan yang signifikan antara penerapan e-learning asinkron pada mata kuliah teori dan praktik. Berdasarkan penelitian ini, disarankan agar dosen yang menerapkan pembelajaran asinkron di kelasnya lebih aktif dalam merespon mahasiswa. Kegiatan yang menarik juga dapat ditambahkan untuk membuat forum diskusi lebih aktif.
Authenticated Quantum Three Pass Protocol on One-Time Pad Cryptographic Technique

A double precision security based application is presented on one-time pad (OTP) technique cryptography using quantum three-pass protocol (QTPP) for subsequent encoding and decoding of plaintext(s).The encoding message first transformed to quantum state, called photon particles, used as qubit, and after encoding that quantum state is rotated randomly by an angle for each quantum bits.For the same, both parties agree over a random shared secret key generated by the system that are specific to the security services and works as hidden agents for the next session to establish.The encryption and decryption utilizes the quantum three-pass protocol for the OTP, and finally detailed analysis is presented.
LATENT DIRICHLET ALLOCATION DALAM IDENTIFIKASI RESPON MASYARAKAT INDONESIA TERHADAP COVID-19 TAHUN 2020-2021

Covid-19 is a very troubling disease in Indonesia. Therefore, understanding public opinion is required to find solutions and evaluate the government performance in handling the pandemic. Twitter can be helpful to identify the public opinion of significant events. Twitter’s tweet is a large dimension text-based big data. It requires text sampling and text mining to be processed efficiently and effectively. Stratified random sampling with 20 repetitions applied to assume days as strata followed by topic modeling with latent Dirichlet allocation (LDA). This research aims to find out public opinion regarding Covid-19 and itsgrowth over time. Other than that, this research also aims to find out sampling effects on tweet data using stratified random sampling. Therefore, the extracted topics will be transformed into time-series data and considering the variety of the pattern made. Afterward, the transformation results will be explored and interpreted. This research suggests that discussions related to Covid-19 are divided into four topics by the first model, namely: “Vaccine”, “Positive or affected people”, “Health protocol”, and “Indonesia” then nine topics by the second model, namely: “Vaccine”, “Prayer”, “Health protocol”, “Social aid and corruption”, “Affected people”, “Indonesian economy”, “Work”, “Persuading to wear mask”, and “Willing to watch”. Furthermore, some topics peak whenever a significant event occurs in Indonesia. Afterward, this research suggests that 20 repetitions of stratified random sampling could provide good results.
Integration Software for a Distributed Group of Mobile Service Robots

This article describes the study of the problems of testing and integration of the group of mobile service robots (Amur-307 type) hardware and software complex using the virtualization support library.The architecture of the software solution and its features, that simplify integration testing and speed up debugging of compilation and reliability errors are described.An approach to emulation of hardware, sensors and electric driver of robots with manipulators specific to this software and hardware complex is also outlined, which allows creating a complete virtual analogue of it and speeding up software development (especially in terms of routing a robotic complex) using unit tests.
Emotion Analysis of Social Media Based on CNN Bilstm

Sentiment analysis is application of natural language processing for understanding the opinions or views of public on various topics. This is also popularly known as opinion mining, the system collects, analyses and examines the sentiments present in the form of tweets. Our proposed model extracts the sentiment of the tweets and classifies them using CNN-BiLSTM which is a technique of deep learning and uses Word2Vec as word embedding layer. The Sentiment140 dataset is generated from Twitter API which consists 1.6 million tweets. BiLSTM cell state based on memory is used for tweets classification Sentiments are published on Social media in the form of texts for expressing social support, happiness, anger, friendship etc. Using deep learning approach, we will be classifying the tweets as positive or negative. CNN-BiLSTM is an effective technique as compared to others like SVM, Naive Bayes Classifier and CNN.
Optimization of Modified Hidden Markov Model for Vision-Based Indonesian Sign Languages Recognition

Sign language is one of the most popular language which is used as a communication bridge that depends on hand movement. As it is used worldwide, the variety of sign languages is very large and most of the people doesn’t understand it which makes the communication between deaf and normal people interrupted. This makes sign language recognition popular as it makes people doesn’t need to understand the sign but still understand the meaning of the sign. But sign language itself has many problems such as the possibility of different dataset has the same movement but different meaning, the method used of each dataset could be ineffective in other dataset, and many other else which makes it difficult to be implemented. Other than that, vision-based recognition is not as popular as sensor-based recognition because of the difference in feature accuracy even though it could give more area of improvement. That’s why the aim of this paper is to presents the combination of methods used to recognize vision-based Indonesian Sign Language and enhance the method using optimization technique. The methodology used in this study follows four steps framework of sign language recognition which is dataset collection, preprocessing, feature extraction, and recognition. Each method is improved in order to be compared and checked what is the method combination and optimization method is the best for sign language recognition. For dataset collection, the dataset that is used is formal Indonesian Sign Language which is called Sistem Isyarat Bahasa Indonesia (SIBI) with some constraint in order to make sure the quality of the dataset is good. The preprocessing methods are differentiated into two categories which is image enhancement and hand detection. Image enhancement methods include no image enhancement, Gaussian blur, Bilateral blur, and Contrast Limited Adaptive Histogram Equalization and hand detection methods include skin detection using YCbCr color space and edge detection using Canny algorithm. Feature that is used in this study is pair of left and right-side movement for each frame that is extracted by calculating the average value of each pixels from left and right-side image that could be a representative value of each frame. Lastly the recognition system that is used is Gaussian Hidden Markov Model and its’ state optimization which includes no optimization, Latin Hypercube optimization, Hill Climbing optimization, and Combination of Latin Hypercube and Hill Climbing optimization. The experiment result of the proposed method could recognize up to 82% accuracy rate. The improvement of this research could be implemented on educational studies or game development that need vision-based sign language recognition system.
IMPACT OF INSTITUTIONAL ENVIRONMENT AND PYRAMIDAL LAYER ON COMPLETION OF CHINESE SOES’ MIXED-OWNERSHIP TRANSACTIONS

This paper utilizes Chinese SOEs that undertake mixed-ownership transactions in 2019 as its research objects and discusses the impact of institutional environment (including the degree of marketization and governmental hierarchy) on the completion of mixed-ownership transactions. In addition, this study explores the moderating effect of pyramidal layer and the munificence of payment on the above relationships. The empirical results show that the main effect hypothesis is supported. Furthermore, pyramidal layer weakens the positive correlation between the marketization and the completion of mixed-ownership transactions, and strengthens the negative correlation between governmental hierarchy and the completion of mixed-ownership transactions. The munificence of payment has no significant moderating effect on the relationship between marketization and completion of mixed-ownership transactions; however, it weakens the negative correlation between the governmental level and the completion of mixed-ownership transactions.
Introduction to <i>topiCS</i> Volume 13, Issue 2

The current issue of Topics in Cognitive Science comprises two topics, both of which are devoted to award-winning research: one to the Rumelhart Prize and one to the Best Papers from the Cognitive Science Society Conference. Our lead topic honors Michael K. Tanenhaus, the eighteenth recipient of the David E. Rumelhart Prize. Tanenhaus received this award in 2018 for transforming “our understanding of human language and its relation to perception, action, and communication”—a field he has been working in for over 40 years. His achievements, his contributions to cognitive science, and his mentorship to numerous students, postdocs, and colleagues are expertly summarized by John Trueswell, who organized this topic and has served as editor for the three contributions to it. In his introduction, Trueswell also explains why Tanenhaus, instead of choosing from an army of former students, invited as contributors to his symposium colleagues he considered influential for his own work. The selection begins with a historical review by Dana H. Ballard and Ruohan Zhang of how computational models of human vision have evolved since David Marr proposed his three-level model, and how algorithm descriptions were again refined into distinct levels over time. Herbert Clark then highlights a neglected issue in research on language use—the anchoring of utterances to various aspects of the situation—and points out the perils for the field of ignoring this key process. Finally, Meredith Brown and Laura Dilley, together with Michael Tanenhaus, present an account of word recognition and segmentation that focuses on syllable inference as a mechanism for the understanding of spoken language. The topiCS team wishes to take this opportunity to congratulate all recipients of CSS prizes for their awards and for the outstanding work that earned them these awards—kudos! topiCS encourages letters and commentaries on all topics, as well as proposals for new topics. Letters are not longer than two published pages (ca. 400–1,000 words). Commentaries (between 1,000 and 2,000 words) are often solicited by Topic Editors prior to the publication of their topic, but they may also be considered after publication. Letters and commentaries typically come without abstract and with few references, if any. The Executive Editor and the Senior Editorial Board (SEB) are constantly searching for new and exciting topics for topiCS. Feel free to open communications with a short note to the Executive Editor (Andrea.Bender@uib.no) or a member of the SEB (for a list, see the publisher's homepage for topiCS: http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1756-8765/homepage/EditorialBoard.html).
Portrayal Matching Algorithm By using Sift

Image identification and matching is one of the very difficult assignment in different areas of mainframe view. Scale-Invariant Feature Transform is an algorithm to perceive and represent specific features in portryals to further use them as an image matching criteria. In this paper, the extracted SIFT matching features are against various image distortions such as rotation, scaling, fisheye and motion distortion are evaluated and false and true positive rates for a large number of image pairs are calculated and presented.
Quality certificates for homeopathic matrices

Background: To produce homeopathic medicines, pharmacies need raw materials (mother tinctures and diluted-agitated solutions, named ÃƒÂ¢Ã¢â€šÂ¬Ã…â€œmatricesÃƒÂ¢Ã¢â€šÂ¬Ã‚Â), provided by insumes suppliers. The ÃƒÂ¢Ã¢â€šÂ¬Ã…â€œmatricesÃƒÂ¢Ã¢â€šÂ¬Ã‚Â are ultra high dilutions and can not be tested against Analysis Reports.&#x0D; &#x0D; Aims: to propose alternatives to the matrices Analysis Report; to contribute to the quality of homeopathic medicines and treatment.&#x0D; &#x0D; Method: search of information present in the documentation provided from 2 national and 3 European suppliers in order to develop criteria.&#x0D; &#x0D; Discussion: the needed concepts for compliance with the orders throughout their production process were presented. The control of information involved in the process allows to trace the production of matrices, providing an indication of the quality with which they were obtained. Each supplier gives different approach to issuing a document, calling it Certificate of Conformity Protocol Preparation, Manufacturing Certificate or Quality Certificate. Summarizing, it is a supplier's declaration, which involves the quality control of raw materials, packaging materials and of the process used, but not a report that enables customers to repeat the analysis. A model was proposed for a Certificate of Quality, with the minimum information needed to indicate to the pharmacies that there is a control of the process. This certificate shall contain statements about the process.&#x0D; &#x0D; Conclusion: Quality Certificate seems to be the best document to ensure the pharmacy that the matrix obtained presents characteristics compatible with the preparation of a quality homeopathic medicine.
Successful Transitions from Public to Private-Sector Led Growth: Lessons for Benin

Many Sub-Saharan African (SSA) countries, like Benin, have scaled up public investment during the last decade.Such a strategy contributed to the improvement of infrastructure, but also to a build-up of debt vulnerabilities.Looking forward, the planned fiscal consolidation will result in some restraint of public spending, and, in particular, public investment.In this context, maintaining or even raising the region's economic growth will require an offset by the private sector.The analysis draws lessons from countries that have successfully transitioned from public investment to private investment-led growth using a global sample starting in the mid-1980s.These lessons highlight policies that have been crucial in fostering a rebound of private investment in the wake of a contraction of public investment.The analytical framework proposed by Hausman, Rodrik and Velasco ( 2005) is used to identify and classify such policies.Finally, the paper analyses how the identified policies could help Benin achieving a smooth transition from public to private sector-led growth.
Ivo Andrich: The Message to the Humankind (to the 60th Anniversary of the Nobel Prize)

The article examines the concept of the world and the man in Ivo Andrich’s works. The writer’s perception of the tragic reality makes him feel sympathy for the human being. At the same time, the author clearly expresses the desire to overcome the power of time and to achieve thumankind unity with the help of the recurring bridge image.
Speech De-identification with Deep Neural Networks

Cloud-based speech services are powerful practical tools but the privacy of the speakers raises important legal concerns when exposed to the Internet. We propose a deep neural network solution that removes personal characteristics from human speech by converting it to the voice of a Text-to-Speech (TTS) system before sending the utterance to the cloud. The network learns to transcode sequences of vocoder parameters, delta and delta-delta features of human speech to those of the TTS engine. We evaluated several TTS systems, vocoders and audio alignment techniques. We measured the performance of our method by (i) comparing the result of speech recognition on the de-identified utterances with the original texts, (ii) computing the Mel-Cepstral Distortion of the aligned TTS and the transcoded sequences, and (iii) questioning human participants in A-not-B, 2AFC and 6AFC tasks. Our approach achieves the level required by diverse applications.
Information Technology (IT) Users in Tertiary Education Institutions in Bulawayo, Zimbabwe: Case of Security Awareness

Information Technology (IT) expansion exposes organisations in developing countries to IT security risks. Zimbabwe’s tertiary education institutions (TEIs) are not spared. Every year, cyber-attacks increase and become more sophisticated, resulting in losses of personal and financial data for individuals, organisations and governments. As the world is interconnected, small and big organisations share the same internet platform. Therefore, IT security risks that affect one, affect all. When IT users are unaware of the risks and uninformed of ways to protect their IT systems, they remain vulnerable. Like other organisations in Zimbabwe, TEIs are vulnerable to cyber-attacks. The study that directed this article employed a quantitative methodological approach in the collection of the data and its analysis. A sample of 261 respondents was selected from the population of IT users in TEIs in Bulawayo. The results indicated that IT security awareness of IT users in TEIs in Bulawayo is low. This is evidenced by the low IT drivers’ contribution towards building IT users’ security awareness, and inadequate implementation and utilisation of IT security awareness tools. The prevailing phenomenon exposes TEIs in Bulawayo to a high risk of cyber-attacks. The results indicated a positive and significant correlation between IT security drivers’ contribution and IT security awareness tools utilisation in TEIs in Bulawayo. The implication is that an increase in IT security drivers’ contribution and IT security awareness tools utilisation will lead to increased IT security awareness. The study recommends that IT drivers double their contribution towards building IT security awareness through adequate implementation and utilisation of IT security awareness tools. This will safeguard the information that tertiary education institutions generate.