Reviewerly/exHarmony huggingface dataset:
El rol de la familia en la educación en casa durante el confinamiento

After the declaration of Covid 19 as a pandemic by the WHO, any change, the confinements decreed to avoid the spread of the virus, caused the paralysis of economic activity worldwide. Education has been one of the hardest hit, having to receive an education at home is a great responsibility of parents who are not used to spending so much time with their children studying separately that many lack the ability to teach. The research methodology is a bibliographic review. In general, the family role and the maintenance of harmony during social isolation is very important so as not to distract children's attention from negative things added to those they are already experiencing because they cannot go out to play and interact with friends. The technology available at home is essential to carry out distance education, access to the internet, to a computer or mobile phone where you can interact with teachers makes this new situation more bearable. Training or guidance for parents who do not have the ability to help children at home is ideal for parenting.
An Autonomous Obstacle Avoidance Robot Using Ultrasonic Sensor

The use of robot and its enormous technological applications in today‟s era of industrial and intelligent systems has been seen to be highly impactful. The ability of these robots to move freely with minimal control is posing a real challenge. In this paper, the development of an autonomous obstacle avoidance robot using ultrasonic sensors is presented. In the design, the ultrasonic sensor serves as the eye of the robot to aid its autonomous movement. The robot is a wheeled type which can either be control using a dedicated control application (Android App) or autonomously. The control application was an added feature in case there is need to manually control the robot. The accuracy of the robot obstacle avoidance is highly encouraging scoring 87.5%, although, there are other challenges which are noted for further study.&#x0D; Keywords: Robotic, Obstacle avoidance, Autonomous system, Ultrasonic sensor.
Neuro-Symbolic Probabilistic Argumentation Machines

Neural-symbolic systems combine the strengths of neural networks and symbolic formalisms. In this paper, we introduce a neural-symbolic system which combines restricted Boltzmann machines and probabilistic semi-abstract argumentation. We propose to train networks on argument labellings explaining the data, so that any sampled data outcome is associated with an argument labelling. Argument labellings are integrated as constraints within restricted Boltzmann machines, so that the neural networks are used to learn probabilistic dependencies amongst argument labels. Given a dataset and an argumentation graph as prior knowledge, for every example/case K in the dataset, we use a so-called K-maxconsistent labelling of the graph, and an explanation of case K refers to a K-maxconsistent labelling of the given argumentation graph. The abilities of the proposed system to predict correct labellings were evaluated and compared with standard machine learning techniques. Experiments revealed that such argumentation Boltzmann machines can outperform other classification models, especially in noisy settings.
Structural And Content Characteristic Of Didactic Competencyof A Modern Educator

The article presents a structural and meaningful characteristic of the teacher's didactic competence, due to the changes in the requirements for the modern learning process. The work analyzes the views of researchers on this problem and the situation with the didactic competence of the teacher in the educational practice. It is concluded that there is a need in pedagogical science and practice to rethink the content of the didactic competence of the teacher in accordance with the challenges of the time to the education system. The results of the study of the nature and structural-contentious content of the teacher's didactic competence, aspects in its consideration, levels of manifestation are established, a relationship with the didactic culture of the teacher are presented. It is justified that didactic culture includes the choice of philosophy, strategy and tactics of learning and the teaching activity itself. Didactic competence is its functional characteristic, reflecting the technological aspect of the teacher's professional life, its ability to make specific didactic decisions. The profile of the didactic competence of the modern teacher has been defined and the description of its five blocks (value-meaning, knowledgeable, operational, personal, reflexive) has been given. The pedagogical strategy of the modern teacher, oriented to teaching as to communication, reflection, understanding, design is justified. The implementation of this strategy involves the construction of educational and educational situations in the logic of the model "Pyramid of doctrine as a system 6 C" for the development of the student as a subject of teaching.
A Hybrid Proof based Consensus Algorithm for Permission less Blockchain

Digital growth with latest technologies have rendered more comfort to end-users in terms of online transactions. But such online transactions have paved for a steep increase in the crime rate with more fraudulent activities. Major cryptocurrencies such as Bitcoin and Ethereum play a major role in handling such illegal behavior of hackers. Blockchain is the basic concept of cryptocurrencies. It is realized as an immutable ledger which implements transactions in a decentralized manner. As the network is decentralized; achieving consensus between each node can be quite a difficult task. Fortunately, this problem can be solved with the help of consensus algorithms. There are numerous ways in which consensus can be achieved. However, in this paper, on proof-based consensus methods are primarily focused on. The majorities of the proof-based consensus algorithms are susceptible to a 51% attack and also lead to high transaction times. These problems can be overcome using a modified approach on an already existing hybrid proof-based algorithm known as “2-hop blockchain”.
Telepathology Support System with Gross Specimen Image Using High Resolution 4K Multispectral Camera

This study reports on the development of a high-resolution 4K multispectral camera designed to enhance telepathology support systems for remote gross-pathological diagnosis. We experimentally examine and evaluate the camera's effectiveness in three subjects: the reconstruction of precise color images, the emphasis of cancerous tissue areas, and pre-fixed image reproduction from fixed images. The evaluation results of the first and second subjects showed that the camera and supporting methods could be effectively used in gross pathology diagnosis. The images obtained in the third subject received positive evaluations from some pathologists, but others expressed reservations as to its utility.
The GaussianSketch for Almost Relative Error Kernel Distance.

We introduce two versions of a new sketch for approximately embedding the Gaussian kernel into Euclidean inner product space. These work by truncating infinite expansions of the Gaussian kernel, and carefully invoking the RecursiveTensorSketch [Ahle et al. SODA 2020]. After providing concentration and approximation properties of these sketches, we use them to approximate the kernel distance between points sets. These sketches yield almost (1+e)-relative error, but with a small additive α term. In the first variants the dependence on 1/α is poly-logarithmic, but has higher degree of polynomial dependence on the original dimension d. In the second variant, the dependence on 1/α is still poly-logarithmic, but the dependence on d is linear.
Incorporating External Annotation to improve Named Entity Translation in NMT.

The correct translation of named entities (NEs) still poses a challenge for conventional neural machine translation (NMT) systems. This study explores methods incorporating named entity recognition (NER) into NMT with the aim to improve named entity translation. It proposes an annotation method that integrates named entities and inside–outside–beginning (IOB) tagging into the neural network input with the use of source factors. Our experiments on English→German and English→ Chinese show that just by including different NE classes and IOB tagging, we can increase the BLEU score by around 1 point using the standard test set from WMT2019 and achieve up to 12% increase in NE translation rates over a strong baseline.
PECULIARITIES OF PSYCHOLOGICAL READYNESS OF STUDENT YOUTH OF PEDAGOGICAL SPECIALTIES FOR INTRODUCTION OF EDUCATIONAL INNOVATIONS

The problem of computer games as an alternative to reality]
Burnout Among Correctional Staff: Effects of Job Satisfaction

The article is devoted to the effects of job satisfaction of penitentiaries on their burnout in a developing country. Postmodern as an age of freedom and expansion of individualism contrasts with the role of penitentiaries, obliged to restrict the freedom of other people, and also exacerbates the dual nature of penitentiaries, responsible for both supervision and correction of convicts. The authors used JSS to measure job satisfaction with workers in correctional facilities of Ukraine (n = 78) and MBI-HSS to identify their level of professional burnout. The authors used descriptive statistics methods, the Kolmogorov-Smirnov test, the Shapiro–Wilk test. the correlation analysis with the Pearson correlation coefficient, Spearman’s rank order correlation coefficient and Fisher's criterion. A high level of correctional staff burnout was revealed in comparison with other developed and developing countries. Vocational burnout (emotional exhaustion and depersonalization) is likely to be affected by dissatisfaction with contingent rewards, communication field, and operating conditions. At least a statistically significant relationship between these phenomena has been identified. At the same time, only a weak relationship between the total job satisfaction and the aggregated global measure of burnout was revealed. Along with a high level of emotional exhaustion and depersonalization, officers have maintained a high level of personal accomplishment, which requires additional research and application of another methods.
Data Embeddable Texture Synthesis with Fast Data Extraction

Texture synthesis which grows source texture image into a bigger texture image is applied for data embedding, instead of using a readily available digital image as a carrier for data.The patch based texture synthesis is used to embed the data in patches.The selection of a suitable patch for texture synthesis is dependent on data to be hidden.At receiver, embedded data is recovered along with source texture.The efforts are taken to improve the speed of the data extraction.In the process of data extraction, the matched candidate patch is identified at every patch location of stego synthetic texture image.If it is done by referring to the energy value of the kernel region than by comparing the whole patch with all candidate patches for similarity, data extraction is almost 40 times faster.
Using Outreach Weeks to Examine Labor, Assessment and Value in Open Advocacy

INTRODUCTION Like the scholarly communication system it aims to transform, open advocacy work is broad in scope and reflects many influences, practices, and players. Despite having a rewarding mission, scholarly communication librarians frequently juggle multiple roles, may experience isolation and career stagnation, and produce outputs that are not readily understood. METHODS These challenges inspired the creation of the Open Action Kit, a suite of tools to help practitioners plan, execute, and assess open advocacy weeks, particularly Open Access Week. This resource sought to make explicit parallels between the activities and scope of open advocacy work and leadership skills that could aid in career progression. RESULTS The project’s aims and structure matured to focus on a broader, critical appraisal of the nature of scholarly communication work. Its encouragement of dialogue between its members and audience more thoroughly recognized and addressed the tensions between open advocacy work and professional success. DISCUSSION Open advocates expressed many frustrations with their work: they often felt isolated or burnt out, hindered by structures or expectations from their organization. While relational work is fundamental to the cultural change inherent in scholarly communication work, the overly simplistic, quantitative measures typical of library assessment do not accurately capture its nuance or complexity. CONCLUSION Centering the relational components of open advocacy work is necessary for it to be successful, sustainable, and appropriately valued. While the Open Action Kit has not been updated since 2017, it serves as a useful model for translating and centering relational work through distributed leadership, advocacy, and skill development.
Adding Artificial Noise for Dynamic Code Rate Matching in Continuous-Variable Quantum Key Distribution

CV-QKD over long distances requires high reconciliation efficiencies, hence matching error correction code rate vs. SNR. For time-varying quantum channels, we achieve this by adding a controlled amount of digital noise to the measured data.
Interpretable Machine Learning: Shapley Values (Seminar Slides)

Machine learning (ML) algorithms utilize the power of computers to solve tasks that are beyond the grasp of classical statistical methods. However, ML is often perceived as a black-box, hindering its adoption. This seminar demonstrates the use of Shapley values to interpret the outputs of ML models. With the help of interpretability methods, ML is becoming the primary tool of scientific discovery, through induction as well as abduction.
PERANCANGAN SISTEM INFORMASI DATA REKAM MEDIS PUSKESMAS KUMANIS KABUPATEN SIJUNJUNG DENGAN MENGGUNAKAN BAHASA PEMROGRAMAN VISUAL BASIC.NET

Puskesmas Kumanis in Sijunjung District is currently in need of an accurate and reliable information system that is sufficient to improve the services available in the Kumanis Health Centre for patients who come for treatment.The purpose of this system is designed to help the process of processing medical record data become more effective and can assist employees in searching patient health history data quickly and easily.This medical record system can help health centre staff in providing medical treatment and determine the drugs to be given to patients to overcome the problems that exist in the processing of medical record data at the Kumanis Health Centre which currently still uses manual recording methods that have not been effective, such as: all data recorded in a book.In this process the system that is running is not optimal, because there is still a manual system in the process.With enough patients every day, we need an application that aims to help the processing of patient data.Therefore a patient data processing application was built using the Visual Basic programming language.Net and MySQL database.
Open-Source Satellite-Derived Solar Resource Databases Comparison and Validation for Indonesia

Solar resource data derived from satellite imagery are widely available nowadays, either as an open-source or paid database. This article is intended to assess open-source databases, which cover the region of Indonesia. Here, four known solar resource databases, which spatially cover the Indonesian archipelago, have been used, namely, Prediction of Worldwide Energy Resource (POWER), Surface Solar Radiation–Heliosat-East (SARAH-E), CM SAF Cloud, Albedo, Radiation edition 2 (CLARA-A2), and SolarGIS. In addition, a minor portion of the Meteonorm database by Meteotest, around five sample points across Indonesia, has been assessed in terms of coherency to the four mentioned databases. Correlation coefficient and relative bias of the multiyear monthly mean annual cycle global horizontal irradiation (GHI) between pairs of databases are inspected. Three out of four databases are then validated through the available irradiation ground measurement data provided by the World Radiation Data Centre (WRDC). The correlation between each pair varies mostly between 0.7 and 1, which shows that the four databases to a certain extent agree on how the intermonthly variation would behave throughout the year. On the other hand, the validation result reveals that the three databases, i.e., POWER, CLARA-A2, and SARAH-E, are suffering from positive bias error ranging from 3% to 7%. Despite that fact, the correlation between measured and estimated values is still acceptable with SARAH-E showing the best performance among the three. Careful selections and adjustment enable the possibility of these databases to be utilized as a tool for depicting interannual and intermonthly variations of solar irradiation throughout the Indonesian archipelago.
EDUCATION IN REMOTE ACCESS: A TEACHER’S VIEW

The problems faced by teachers in the conditions of forced transition to distance learning due to the pandemic COVID-19 have been analysed, when interaction with students was carried out only with the use of information technologies. The advantages and disadvantages of organizing training sessions using various educational platforms have been highlighted: Zoom, Microsoft Office 365, Skype. Psychological and pedagogical barriers that affect the perception of educational material by students, the performance of the teacher and student, including the effectiveness of educational interaction between them, have been considered. The problems of organizing and conducting intermediate certification in remote access have been emphasized: difficulties in identifying students ‘ identities, and the use of proctoring technologies.
Evaluation of a Mobile SMS based Twitter Information Service for Rural communities: A Case study of Ipologama Vidatha Resource Center, Sri Lanka

Mobile phones have been effectively used to fulfill the information needs of rural communities in different contexts. This study was aimed to assess the effectiveness of a mobile-based twitter information dissemination service implemented by the Vidatha Resource Center, Ipologama, Sri Lanka applying the Technology Acceptance Model. Fifty-six respondents who have been using the service were selected for the study. Data were collected through an interview schedule. According to the results, the service was useful, easy to use and cost-effective depicting the potential use of such systems to fulfill the information needs of the rural communities.
Dynamic Gesture Design and Recognition for Human-Robot Collaboration With Convolutional Neural Networks

Abstract Human-robot collaboration (HRC) is a challenging task in modern industry and gesture communication in HRC has attracted much interest. This paper proposes and demonstrates a dynamic gesture recognition system based on Motion History Image (MHI) and Convolutional Neural Networks (CNN). Firstly, ten dynamic gestures are designed for a human worker to communicate with an industrial robot. Secondly, the MHI method is adopted to extract the gesture features from video clips and generate static images of dynamic gestures as inputs to CNN. Finally, a CNN model is constructed for gesture recognition. The experimental results show very promising classification accuracy using this method.
HiPHET: A Hybrid Approach to Translate Code Mixed Language (Hinglish) to Pure Languages (Hindi and English)

Bilingual code mixed (hybrid) languages has become very popular in India as a result of the spread of Western technology in the form of the television, the Internet and social media. Due to this increase in usage of code-mixed languages in day-to-day communication, the need for maintaining the integrity of Indian languages has arisen. As a result of this need the tool named Hinglish to Pure Hindi and English Translator was developed. The tool translated in three ways, namely, Hinglish to Pure Hindi and Pure English, Pure Hindi to Pure English and vice versa. The tool has achieved accuracy of 91% in giving Hindi sentences as output and of 84% in giving English sentences as output, where the input sentences were in Hinglish. The tool has also been compared with another similar tool in the paper.
Investigating and Suggesting the Evaluation Dataset for Image Classification Model

Image processing systems are widespread with the digital transformation of artificial intelligence. Many researchers developed and tested several image classification models using machine learning and statistical techniques. Nevertheless, the current research seldom focuses on the quality assurance of these models. The existing methods lack to verify the quality assurance, with the lack of test cases to prepare the evaluation dataset to test the model, which can cause critical drawbacks in the nuclear field and defense system. In this article, we discuss and suggest the preparation of the evaluation dataset using improved test cases through Cause-Effect Graphing. The proposed method can generate the evaluation dataset with automated test cases through the quantification method, which consists of 1) image characteristic selection 2) creating the Cause-Effect graphing approach of the image with the feature, and 3) generate all possible test coverage. The testing is performed with the COCO dataset, which shows the declining prediction accuracy with the adjusted brightness and sharpness ranging between -75 to 75%, which indicates the negligence of the important characteristics in the existing test dataset. The experiment shows the prediction fails while sharpness is less than the 0%, and the brightness fails at -75% with less number of detection object between -50% and 75%. This indicates that characteristic changes affects the prediction accuracy and the number of detected objects in an image. Our approach proves the importance of the characteristic selection process for the overall image to generate a more efficient model and increase the accuracy of object detection.
On the Security of Symmetric Encryption Against Mass Surveillance

For mass surveillance, the algorithm substitution attacks (ASAs) are serious security threats to the symmetric encryption schemes. At CRYPTO 2014, Bellare, Paterson, and Rogaway (BPR) formally developed the security notions of decryptability, undetectability, and surveillance and presented a unique ciphertext symmetric encryption scheme against all possible ASAs. At FSE 2015, Degabriele, Farshim, and Poettering (DFP) relaxed the correctness of decryptability and presented an input-triggered ASA, which meets the BPR security definitions but violates the security of the BPR unique ciphertext scheme. Hence, DFP refined the security notions of detectability and subversion resistance to remove their ASA from the BPR unique ciphertext scheme. At CCS 2015, Bellare, Jaeger, and Kane (BJK) also developed the security notion of key recovery to make the input-triggered ASA infeasible. We investigate ASAs on the symmetric encryption scheme. Our contribution is twofold. (1) We propose a new trigger ASA against the symmetric encryption scheme. Our proposed ASA cannot be captured by the BJK security definitions. Comparatively, the DFP security definitions can detect our proposed ASA. In the view of ASAs, this result demonstrates that the DFP security definitions are not identical to the BJK security definitions. (2) We improve the DFP definition of subversion resistance. DFP proved that the BPR unique ciphertext scheme defeats the input-triggered ASA under their subversion resistance definition. However, we show that the BPR unique ciphertext scheme fails to meet the DFP subversion resistance definition due to our proposed ASA. Therefore, an improved definition on subversion resistance is proposed to cover all existing trigger ASAs. We prove that the BPR unique ciphertext scheme is secure under our improved definition. Therefore, we believe that our improved definition is more suitable to evaluate the ASA security of the symmetric encryption scheme.