Reviewerly/exHarmony huggingface dataset:
A Block Chain and IoT Based Hybrid Students Record System for E-Governance

Aims: This paper addresses a system for the students’ record management by the educational institutions using the IoT and Block chain technologies.&#x0D; Motive for this Research: The growth of the contemporary technologies around the world has made almost all the chores easier and faster. Yet, the government and private organizations are struggling to identify the appropriate candidates for the required positions and to verify their credentials during the recruitment process. The recruiting companies are facing the issue of deceitful activities during the certification and other credential verifications. Moreover, the data are available only in the universities and the verification processes are very often manually completed and they are time demanding. Thus maintaining data integrity and security becomes the major concern for the organizations, which have widely suggested considering AI technology applications in the educational institutions which are ubiquitous nowadays, especially with the current rapid change in the technology landscape. In higher education institutions as a modernization process they have started using the IoT devices for recording the students’ status and performing many activities automatically. The Block chain technology is used for secured peer to peer networks for the private data maintenance. Since it is demanding good Internet infrastructure and the transactions are computationally expensive, there are some hesitations in adapting Block chain technology for the regular activities by the organizations. Despite the security features of the Block chain, there are very few systems and proposals available using IoT and Block chain due to the technical complications while merging these technologies.&#x0D; Study Design: We have highlighted the various concepts of these two technologies, their applications, advantages, challenges, etc.&#x0D; Place and Duration of Study: Department of Information Technology, University of Technology and Applied Sciences – Salalah, Oman, from Dec 2019 to February 2021.&#x0D; Results: A system architecture is proposed and it explains and shows how the Block chain security is being imposed on the IoT based applications especially for the student data management system. The activity diagram of the proposed system helps and assists in understanding the flow of the correspondences among the organizations and the candidates (students) and the way the information is maintained.&#x0D; Conclusion: The proposed system architecture This system is secure, fast and it can be used by the government and the private institutions not only for the students’ record management and verification, but for many other different purposes within the scope of data management systems.
Cnerator: A Python application for the controlled stochastic generation of standard C source code

The Big Code and Mining Software Repositories research lines analyze large amounts of source code to improve software engineering practices. Massive codebases are used to train machine learning models aimed at improving the software development process. One example is decompilation, where C code and its compiled binaries can be used to train machine learning models to improve decompilation. However, obtaining massive codebases of portable C code is not an easy task, since most applications use particular libraries, operating systems, or language extensions. In this paper, we present Cnerator, a Python application that provides the stochastic generation of large amounts of standard C code. It is highly configurable, allowing the user to specify the probability distributions of each language construct, properties of the generated code, and post-processing modifications of the output programs. Cnerator has been successfully used to generate code that, utilized to train machine learning models, has improved the performance of existing decompilers. It has also been used in the implementation of an infrastructure for the automatic extraction of code patterns.
AN ANALYSIS OF LEARNING ENGLISH IN NEW NORMAL ERA OF SMP NEGERI 2 SURUH IN THE ACADEMIC YEAR 2020/2021

Pratiwi, Alfiah Asa 2020. An Analysis of Learning in New Normal Era of SMP Negeri 2 Suruh in The Academic Year 2019/2020.A Graduating Paper, English Education Department,Teacher Training, and Education Faculty, State Institute for Islamic Studies Salatiga. Counselor: Widiastuti, M.Pd.Keywords :New normal era, Blended Learning, AVM (Audio Visual Method), Communicative MethodThe purpose of this research is knowing determine the methods and readiness of English teachers in New Normal era. This research generally answered the: two questions : (1) What kind of learning method that are English teachers’ do in the face new normal of SMP Negeri 2 Suruh in the academic year 2020/2021. (2) What is English teachers’ readiness in facing a new normal era of SMP Negeri 2 Suruh in the academic year 2020/2021.The methodology of the research was qualitative research. The technique of collecting data were observation, interview, and documentation. The interview consist of 3 respondents from all English teacher at SMP Negeri 2 Suruh. The interview to find out the teachers about their method and their readiness to teach English learning. All of them uses communicative method in face to face or online learning. When online learning they uses media Whats App Group. One of the teacher uses AVM(Audio Visual Method) the teacher use many educational application to make students interesting with the material or assignments like YouTube and others. Two of the teachers just uses same application that are Google Classroom and Whats App. In new normal era SMP Negeri 2 Suruh uses blended learning.
The concrete application of lightning protection technology of electrical automation system in water conservancy and hydropower project

Abstract the development of science and technology has promoted the continuous progress of water conservancy and hydropower projects. Advanced equipment and advanced technology are widely used in water conservancy and hydropower projects, which improves the working efficiency and working level of staff in two directions, and also brings great economic benefits to the water conservancy and hydropower projects. Among them, electrical automation technology is widely used in water conservancy and hydropower projects as the basis of quality guarantee, therefore, correspondent research on it should be strengthened. The application of lightning protection technology in electrical automation system of water conservancy project is to provide guarantee for the stable operation of the electrical automation system of water conservancy project. This paper analyzes the lightning protection technology of electrical automation system used in water conservancy project from the practical point of view, and analyzes the main points of application of electrical automation in water conservancy and hydropower projects in detail.
A Survey of Recent Abstract Summarization Techniques

This paper surveys several recent abstract summarization methods: T5, Pegasus, and ProphetNet. We implement the systems in two languages: English and Indonesian languages. We investigate the impact of pre-training models (one T5, three Pegasuses, three ProphetNets) on several Wikipedia datasets in English and Indonesian language and compare the results to the Wikipedia systems’ summaries. The T5-Large, the Pegasus-XSum, and the ProphetNet-CNNDM provide the best summarization. The most significant factors that influence ROUGE performance are coverage, density, and compression. The higher the scores, the better the summary. Other factors that influence the ROUGE scores are the pre-training goal, the dataset's characteristics, the dataset used for testing the pre-trained model, and the cross-lingual function. Several suggestions to improve this paper's limitation are: (1) assure that the dataset used for the pre-training model must be sufficiently large, contains adequate instances for handling cross-lingual purpose; (2) advanced process (fine-tuning) shall be reasonable. We recommend using the large dataset consisting of comprehensive coverage of topics from many languages before implementing advanced processes such as the train-infer-train procedure to the zero-shot translation in the training stage of the pre-training model.
Building Survivable Software Systems by Automatically Adapting to Sensor Changes

Many software systems run on long-lifespan platforms that operate in diverse and dynamic environments. If these software systems could automatically adapt to hardware changes, it would significantly reduce the maintenance cost and enable rapid upgrade. In this paper, we study the problem of how to automatically adapt to sensor changes, as an important step towards building such long-lived, survivable software systems. We address challenges in sensor adaptation when a set of sensors are replaced by new sensors. Our approach reconstructs sensor values of replaced sensors by preserving distributions of sensor values before and after the sensor change, thereby not warranting a change in higher-layer software. Compared to existing work, our approach has the following advantages: (a) ability to exploit new sensors without requiring an overlapping period of time between the new sensors and the old ones; (b) ability to provide an estimation of adaptation quality; and (c) ability to scale to a large number of sensors. Experiments on weather data and Unmanned Undersea Vehicle (UUV) data demonstrate that our approach can automatically adapt to sensor changes with 5.7% higher accuracy compared to baseline methods.
Problems in Setting Teaching Objectives and Countermeasures to Work out Teaching Objectives in College English Class

The professional competence of college English teachers in setting teaching goal has a direct impact on their teaching design level. Enhancing college teachers’ ability in setting classroom teaching goal facilitates the improvement of their design level. By combining with the teaching design scheme of normal class, this paper defines the meaning of College English classroom teaching objectives, analyzes the problems that the college English teachers have in setting teaching objectives, and puts forward corresponding countermeasures to develop the college English teachers’ capability of setting teaching objectives, which are expected to promote college English teachers’ ability to design the activities for their class.
An Evaluation of English Textbook for Grade X of Senior High School

This paper aims to evaluate the English textbook that published by Kemendikbud 2014 whether it has fulfilled the criteria of good textbook as proposed by Permendikbud Number 08, 2016 or not. The descriptive quantitative method was applied in analyzing the data. The subjects of this research is Bahasa Inggris Textbook Published by Kemendikbud 2014. There are two books; the first semester and second semester books of Grade X (18 chapters). The instrument of the research was an observation checklist based on the criteria of English Textbook from Permendikbud Number 8, 2016. There were four aspects that were applied in analyzing the textbook;  material, linguistic, material presentation, and graph. The result showed that  English textbook Grade X published by Kemendikbud 2014 is in the good category. It means this textbook has fulfilled the criteria proposed by Kemendikbud. However the re-evaluation is needed to be implemented thoroughly concerning on the content of the textbook. Keywords: English textbook, Permendikbud, and Grade X
ISO 21526 Conform Metadata Editor for FAIR Unicode SKOS Thesauri

Metadata repositories are an indispensable component of data integration infrastructures and support semantic interoperability between knowledge organization systems. Standards for metadata representation like the ISO/IEC 11179 as well as the Resource Description Framework (RDF) and the Simple Knowledge Organization System (SKOS) by the World Wide Web Consortium were published to ensure metadata interoperability, maintainability and sustainability. The FAIR guidelines were composed to explicate those aspects in four principles divided in fifteen sub-principles. The ISO/IEC 21526 standard extends the 11179 standard for the domain of health care and mandates that SKOS be used for certain scenarios. In medical informatics, the composition of health care SKOS classification schemes is often managed by documentalists and data scientists. They use editors, which support them in producing comprehensive and valid metadata. Current metadata editors either do not properly support the SKOS resource annotations, require server applications or make use of additional databases for metadata storage. These characteristics are contrary to the application independency and versatility of raw Unicode SKOS files, e.g. the custom text arrangement, extensibility or copy & paste editing. We provide an application that adds navigation, auto completion and validity check capabilities on top of a regular Unicode text editor.
Quantum key distribution over free space optic (FSO) channel using higherorder Gaussian beam spatial modes

Quantum key distribution (QKD) has emerged as a secure solution of secret key distribution utilizing the well established theories of modern physics.Since its introduction in 1984, many interesting and innovative ideas have been proposed for QKD in order to improve the security and efficiency of the scheme keeping in view of its applications and practical implementation.High error rate QKD scheme for long distance communication -the so-called KMB09 protocol -is one such scheme which was designed to achieve longer communication distance in QKD, without compromising its security, by allowing the utilisation of higher dimensional photon states which is not possible with standard BB84 scheme.However the practical implementation of KMB09 protocol has not been presented yet because of its unique design.In this paper, we propose a framework for the practical implementation of QKD system that runs KMB09 protocol in two or more dimensions of photon states.We present the KMB09 based QKD system design and its simulation for practical implementation based on the encoding of secret bits in higher order Gaussian beam spatial modes.The proposed framework is specifically evaluated in terms of efficiency or success rate with two and four dimensions of photon states.We find that the simulation results of the proposed framework are inline with the numerical and analytical results of the same QKD model presented earlier.
Linear Regression Algorithm Results for a PV Dual-Axis Tracking-Type System

A photovoltaic (PV) module converts solar energy into electrical energy. In order to increase the output power of any PV module, several factors including tilt angle, orientation angle, load profile, environmental condition, latitude of the location site, and energy management techniques should be considered. It is essential to continuously deliver the highest possible power to a load for a given day, which may be achieved by using a tracking-type system as compared to a fixed-type system. The purpose of this paper is to present the results of an algorithm that may be applied to a dual-axis system located in an elevated plateau of the interior of South Africa in order to sustain a high output power. Two identical 310W PV modules were used for a fixed-type and tracking-type system. The fixed-type system was installed at a tilt angle of Latitude minus 10° serving as a baseline to the tracking-type system. A LabView user interface was developed to record and display the voltage and current measurements from the PV modules. Results indicate that the dual-axis tracking-type system extracted more power (on average 39.32% more power) as compared to the fixed-type system. A key recommendation is to use a linear regression algorithm with a tracking-type system to enable a higher output energy yield for a given day.
Efficient Classification of True Positive and False Positive XSS and CSRF Vulnerabilities Reported by the Testing Tool

Security testing is essential for website and web applications in current days. It is easy for an attacker to invade the security and do malicious activities through web applications if they are not properly protected against known attacks. General practice in web application before release is using testing tools to recognize the possible set of vulnerabilities, which can be true-positive or false-positive. Then the developer team will be asked to revise code to protect against true-positive vulnerabilities. For that, the testing team needs to classify each reported vulnerability into true-positive and false-positive individually, which is very time-consuming. This article suggests innovation in this practice to reduce the time of recognizing true-positive vulnerabilities. It presents a novel approach to classify reported multiple vulnerabilities of different attacks using a single script and in single go. These attacks should share common triggering events or testing process. Cross-Site Scripting (XSS) and Cross-Site Request Forgery (CSRF) attacks are chosen to illustrate the approach.
The Establishment of Supported Decision-making Model for Evaluation Teaches Professional Development Effects Based on Fuzzy Theory

A country’s competitiveness depends on the performance of its national education. Meanwhile, the effects of national education rely on the professional aptitude of teachers. Facing the current knowledge economy, all countries are trying to use quality education to develop highly competitive citizens through educational reform. Therefore, inspiring self-awareness of teachers through internal and external power and further enhancing the profession both spontaneously and continuously is the only way to achieve quality education. This study adopts the group decision technique of the (Delphi method) to identify the following four review factors: course design and teaching, class operation and guidance, professional research and educational development, and professional dedication and attitude, as well as relevant content through a questionnaire survey, analysis, and construction. Furthermore, the quantification function of the fuzzy logic theory is applied to establish a scientific and highly objective “supported decision-making model for evaluating the professional development effects of teachers”. In addition to providing evaluation for teaching self-assessment and the overall educational effects of the educational unit, our findings could be used as references for education and administrative departments to evaluate educational results.
Point-to-Block Matching in Depth Estimation

In this paper, the novel correspondence search method called point-to-block matching was proposed. Recently, in many proposed multimedia systems, depth estimation is performed on compressed input views. To address this problem and increase the quality of such depth maps, in the proposal, a point in a view is not compared simply with a point in another view, but to the most similar point in a small block surrounding it. The introduction of this method in the depth estimation process is beneficial to the quality of depth maps, as it decreases the influence of small shifts in images, caused e.g., by encoding-related errors introduced to input views. The method was implemented in one of the state-of-the-art depth estimation methods and tested in series of experiments. Based on the comparison of synthesized virtual views with the input views, the proposal increases the quality of estimated depth maps in most of the tested configurations.
Efficient Implementation using Multinomial Naive Bayes for Prediction of Fake Job Profile

The growing social media has increased the chances of fake job postings. To avoid fraudulent posts for job, an android application is designed for classification using machine learning. This paper proposes the implementation and working of machine learning based android application. For these various classifiers are used and results of these classifiers are compared for prediction of fake job profiles. Various single classifiers are used and based on the experimental results ,Multinomial Naive Bayes is the best classification to detect fake job over other classifiers.
Club-based format of teaching Russian as foreign language to Chinese students

The study deals with the issue of applying the communicative club format for organizing leisure, educational, and cultural activities for foreign students interested in the Russian language. The authors describe the structural and content model of the Almaz Russian-language Russian-Chinese communication club created based on centers for the Russian language, literature, and culture at the Ammosov North-Eastern Federal University. The model includes target, technological, and content components and implementation mechanisms. The authors conclude that interactive technologies of leisure show great potential for developing foreign students' communicative competence and creative abilities and enriching the individual with knowledge about the traditional culture of peoples inhabiting the multicultural territory of Russia.
Review Analysis on Factors Influencing the Design of Bus Station

Abstract In India, rapid increase in urbanization increases the demand of bus transportation usage with growth rate of 3% every year. This results in development of new routes in city and rural areas. The terminal operations in India are centric in nature for both pedestrians and vehicles. In order to design the efficient transportation system in terminal area the traffic operation should be centralized by implementing the correction factors. The previous research works were reviewed and the solution for developing the model was suggested in this study. The study of previous researches suggested various factors which influences the terminal design. All those factors were considered and the performance of each factor was studied and reframed with corrected values. This study integrated the terminal factors (Element factors + Operational factors + Structural factors + Dwell time factors (both vehicles and pedestrians)) for efficient terminal design and operations. In associated with the above-mentioned factors bus scheduling was included as a factor in this study and suggestion were made for improvements.
LENs: a Python library for Logic Explained Networks.

LENs is a Python module integrating a variety of state-of-the-art approaches to provide logic explanations from neural networks. This package focuses on bringing these methods to non-specialists. It has minimal dependencies and it is distributed under the Apache 2.0 licence allowing both academic and commercial use. Source code and documentation can be downloaded from the github repository: this https URL.