Reviewerly/exHarmony huggingface dataset:
Cognitive Modelling of the Socialization Process as a Digital Transformation Trend in Higher Education

The relevance of the study of this problem is due to the intensive implementation of new information technologies and various electronic courses that contribute to the introduction of digitalization in the educational system. According to the regulatory documents, the purpose of digitalization of the educational system is to ensure a broad access to information and digital resources, and the use of digital technologies in the educational process. In this regard, this article focuses on the identification and disclosure of the purpose and objectives of digitization in the education system, the implementation of the principle of organization of mastering of the optimally required knowledge, a particular algorithm, contributing to the development and transmission of knowledge by means of individual internal and external instruments of knowledge representing the cognitive organization of a personality. The leading method in the study of this problem is the interdisciplinary analysis of scientific literature, which allowed to reveal the essence of the digitalization of the educational process, optimization of the method of cognitive modeling in the educational process in order to develop internal instruments of knowledge of students; theoretical modeling, which allowed to structure the planning process of educational activities in higher education. The article reveals the changes determined by the new socio-cultural and economic situation of digital development, substantiates the new formats of collaboration and learning built around the student, requiring digital literacy teachers and responsibility of students for the quality of their education. The article is focused on the adaptation of teachers to the new conditions of professional activity in the field of education in the conditions of digitalization.
Specifics of organising supplementary education in rural areas

The article presents the factors that help to improve the accessibility and quality of supplementary education of rural schoolchildren, defines the objectives of supplementary education and describes the pedagogic means of solving the most topical problems. Special attention is paid to the ways of satisfying individual interests and wants of children, to the analysis of the results of supplementary education of rural children, to the usage of the rural community resources and to the social partnership development. The article shows the social environment potential and social partnership resources in creating the supplementary education municipal network. The authors suggest the variants of the interaction of the school with other rural subjects, the content and forms of participation of the organisations and local people in children's supplementary education (CSE). The article emphasises the role of parents (legal representatives) in the CSE, proposes the ways of informing parents of supplementary education and their involvement in organising the CSE.
A Survey on Reproducibility by Evaluating Deep Reinforcement Learning Algorithms on Real-World Robots

As reinforcement learning (RL) achieves more success in solving complex tasks, more care is needed to ensure that RL research is reproducible and that algorithms herein can be compared easily and fairly with minimal bias. RL results are, however, notoriously hard to reproduce due to the algorithms' intrinsic variance, the environments' stochasticity, and numerous (potentially unreported) hyper-parameters. In this work we investigate the many issues leading to irreproducible research and how to manage those. We further show how to utilise a rigorous and standardised evaluation approach for easing the process of documentation, evaluation and fair comparison of different algorithms, where we emphasise the importance of choosing the right measurement metrics and conducting proper statistics on the results, for unbiased reporting of the results.
Sistem Monitoring Penjualan Rumah Di Kawasan Perumahan Berbasis Android

Retraction to:Rozikin, C. &amp; Purwantoro. (2018). Rancang Bangun Aplikasi Supporting Sales Penjualan Rumah Di Perumahan Berbasis Android. Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi, 3, 52--67.DOI: https://doi.org/10.36805/technoxplore.v3i2.802This article has been retracted by the publisher based on the following reasonThis is based on the author's recognition to the editor that the author has committed acts of violation of publication ethics. The author has published a double publication by submitting the same article to two journals at the same time. The author admits that he forgot to have submitted the same article to another journal. This article can be found at Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi (Publisher: Universitas Buana Perjuangan Karawang), Volume 3, No. 2, October 2018. (http://journal.ubpkarawang.ac.id/index.php/TeknikInformatikaSistemInfor/article/view/802)This article has followed with the procedures that apply to journal management. The author has received the review results, and has improved the article according to the review result.One of the conditions of submission of a paper for publication in this journal is that authors declare explicitly that their work is original and has not appeared in a publication elsewhere, and also not considered by another journal. As such this article represents a severe abuse of the scientific publishing system. The scientific community takes a very strong view on this matter, and apologies are offered to readers of the journal that this was not detected during the submission process.
A Fully Stochastic Second-Order Trust Region Method

A stochastic second-order trust region method is proposed, which can be viewed as a second-order extension of the trust-region-ish (TRish) algorithm proposed by Curtis et al. (INFORMS J. Optim. 1(3) 200-220, 2019). In each iteration, a search direction is computed by (approximately) solving a trust region subproblem defined by stochastic gradient and Hessian estimates. The algorithm has convergence guarantees for stochastic minimization in the fully stochastic regime, meaning that guarantees hold when each stochastic gradient is required merely to be an unbiased estimate of the true gradient with bounded variance and when the stochastic Hessian estimates are bounded uniformly in norm. The algorithm is also equipped with a worst-case complexity guarantee in the nearly deterministic regime, i.e., when the stochastic gradient and Hessian estimates are very close in expectation to the true gradients and Hessians. The results of numerical experiments for training convolutional neural networks for image classification and training a recurrent neural network for time series forecasting are presented. These results show that the algorithm can outperform a stochastic gradient approach and the first-order TRish algorithm in practice.
Enhanced, Modified and Secured RSA Cryptosystem based on n Prime Numbers and Offline Storage for Medical Data Transmission via Mobile Phone

The transmission of medical data by mobile telephony is an innovation that constitutes the m-health or more generally e-health.This telemedicine handles personal data of patients who deserve to be protected when they are transmitted via the operator or private network, so that malicious people do not have access to them.This is where cryptography comes in to secure the medical data transmitted, while preserving their confidentiality, integrity and authenticity.In this field of personal data security, public key cryptography or asymmetric cryptography is becoming increasingly prevalent, as it provides a public key to encrypt the transmitted message and a second private key, linked to the first by formal mathematics, that only the final recipient has to decrypt the message.The RSA algorithm of River and Shamir provides this asymmetric cryptography based on a public key and a private key, on two prime numbers.However, the factorization of these two prime numbers to give the variable N of RSA can be discovered by a hacker and thus make the security of medical data vulnerable.In this article, we propose a more secured RSA algorithm with n primes and offline storage of the essential parameters of the RSA algorithm.We performed a triple encryption-decryption with these n prime numbers, which made it more difficult to break the factorization of the variable N. Thus, the key generation time is longer than that of traditional RSA.
Collaborative Homomorphic Computation on Data Encrypted under Multiple Keys

Homomorphic encryption (HE) is a promising cryptographic technique for enabling secure collaborative machine learning in the cloud. However, support for homomorphic computation on ciphertexts under multiple keys is inefficient. Current solutions often require key setup before any computation or incur large ciphertext size (at best, grow linearly to the number of involved keys). In this paper, we proposed a new approach that leverages threshold and multi-key HE to support computations on ciphertexts under different keys. Our new approach removes the need for key setup between each client and the set of model owners. At the same time, this approach reduces the number of encrypted models to be offloaded to the cloud evaluator, and the ciphertext size with a dimension reduction from (N+1)x2 to 2x2. We present the details of each step and discuss the complexity and security of our approach.
IMPLEMENTASI APLIKASI PEMBELAJARAN UNTUK ANAK BERBASIS ANDROID

Permendiknas No. 16/2007 concerning Academic Qualification Standards and Teacher Competence, Pedagogical Competence of 5th / Senior High School teachers says that "High School / Vocational Teachers must utilize information and communication technology for the benefit of learning". Reinforced in Permendiknas No. 41 of 2007 concerning Process Standards, in accordance with Graduates Competency Standards and Content Standards, the learning principle used in point 13 states that "Utilization of information and communication technology to improve the efficiency and effectiveness of learning". But now when the world is entering the era of the industrial revolution 4.0. or the fourth world industrial revolution where technology has become the basis in human life the use of information and communication technology for learning must begin at the Early Childhood Education level (PAUD) in order to be more interesting and interactive and increase children's interest and curiosity in what is taught . The method of applying science and technology used is mobile technology which is very popular at the moment, namely the Android-based children's learning application as an effort to increase knowledge and understanding as well as increase the learning interest of students in grades 2, 3 and 4 of Bereng Kajang Elementary School I. The purpose of this program is to increase knowledge and understanding and increase learning interest of students in grades 2, 3 and 4 of Bereng Kajang I Elementary School on various things including letters, numbers, colors, vegetables, animals, fruits, jobs and vehicles. Both in Indonesian and English pronunciation through the implementation / dissemination of learning applications for children based on Android. Keywords: Learning applications, Children, Android, Implementation
Empirical analysis of CASE tool impact on the development process in North Macedonian IT companies

Service architects and developers are interested to create software tools/applications that would help software analysts in the process of software requirements elicitation and specification, which then will improve the productivity and quality of the software being developed. Based on the idea tha t the use of computer aided software engineering (CASE) tools should improve the entire software development process, we have conducted a survey, aiming at exploring developers’ experience with the use of CASE tools in IT Companies based in North Macedonia. We have collected empirical data, examined the use and impact of CASE tools for management of software requirements at different software companies, and try to reveal the factors that influence toward the use of CASE tools.
The Usage of Apache Spark for Collection and Analysis of Social Networking Statistics

This paper investigates the new Facebook API for Instagram. During the work we implemented the live data stream from the Instagram social network and displayed the hashtags depending on their popularity at a specific moment or during some period. We also investigated the relationship between hashtags, depending on the time of data collection and analysis. As a result of the investigation, we developed grouping of related hashtags (based on the given hashtag), which are not placed directly in the same post but connected through the other posts with the intermediate hashtags, which also belong to a certain semantic group.
PERANCANGAN DAN IMPLEMENTASI APLIKASI UJIAN SEKOLAH BERBASIS KOMPUTER ATAU COMPUTER BASED TEST (CBT) DI SMK NEGERI 1 KABUPATEN SORONG

Conventional Test System means that the test is done using paper and pencil or the current term Paper-Based Test (PBT), the constraints and shortcomings of the PBT system are no longer effective &amp; efficient. Sorong State Vocational School 1 still uses Paper-Based Test (PBT) to carry out School Exams. Conventional systems must be replaced by computer information technology using Computer-based Tes&#x0D; This research resulted in an offline Computer Based Test (CBT) based test system at SMK Negeri 1 Kabupaten Sorong. The CBT system makes it easier for student and teacher examinations, the use of exam paper is reduced, examination of exam results is more efficient and effective, it can save time and money. This application system can be used for grading assignments, daily tests and midterm, final exam can even be used as a national exam tryout. The exam analysis system can make it easier for teachers or principals to accept student exam results and analyze students' abilities more quickly. Students at SMK Negeri 1 Sorong Regency will become accustomed to examinations using a computerized system or using an android mobile phone.
Dynamic Deep Multi-task Learning for Caricature-Visual Face Recognition

The following topics are dealt with: feature extraction; document image processing; learning (artificial intelligence); convolutional neural nets; image classification; image segmentation; computer graphics; graph theory; neural nets; text detection.
Neural Dependency Parsing of Biomedical Text: TurkuNLP entry in the CRAFT Structural Annotation Task

We present the approach taken by the TurkuNLP group in the CRAFT Structural Annotation task, a shared task on dependency parsing.Our approach builds primarily on the Turku neural parser, a native dependency parser that ranked among the best in the recent CoNLL tasks on parsing Universal Dependencies.To adapt the parser to the biomedical domain, we considered and evaluated a number of approaches, including the generation of custom word embeddings, combination with other in-domain resources, and the incorporation of information from named entity recognition.We achieved a labeled attachment score of 89.7%, the best result among task participants.
PEMBERDAYAN KELOMPOK GURU DALAM MEMBUAT MEDIA PEMBELAJARAN QUIZIZZ

Every teacher will deliver the subject matter to their students. So that the subject matter is factual and authentic, contextual, varied, and up to date in accordance with the learning objectives, then media assistance is needed that can cause attraction, arouse motivation and stimulation in learning. In order to improve teacher competence in the field of professional education for the transmission of teaching materials, empowerment activities are needed to create a quizizz learning media. Teachers in learning have not understood, mastered, and skilled in making digital-based learning media. The solution offered is to empower teacher groups to create quizizz learning media in order to implement digital applications to motivate interests and stimulate students in learning, increase the interactive power of teachers and students, and facilitate learning in the classroom. Besides this empowerment is also useful to develop the field of education, namely: the development of teacher competencies, especially in the field of instructional media as a support for learning in schools, which will improve the quality of learning in the classroom. The urgency in making this quizizz learning media is to provide learning media that are innovative, varied, dynamic, and not monotonous, and can help teachers in facilitating interactive education between teachers and students, especially in increasing the passion and motivation of students to follow learning, so that the learning objectives reached.
Effectiveness of the use of electronic educational blogs in teaching computers on the achievement of students

The purpose of this research was to know the effectiveness of using educational blogs in teaching computers on the achievement of students in the second year in the College of Education and retention of information. The researcher used the semi-experimental method. The sample of research consisted of (36) students in the second year in the department of Biology, the College of Education at the University of Samarra has been divided into two groups, one of which consists of (18) students which has been considered as control group and has been studied using the classical method, and the experimental group which consisted of 18 students studied using the educational blog. Both groups (experimental and control) were similar in number and equal in the number of variables that could affect the safety of experimental design of the research. The researcher choose Chapter 4 of (Microsoft PowerPoint 2010) and Chapter 5 (Inserting Objects and Adding Movements in Microsoft PowerPoint 2010) from Computer Basics Part 2, which is taught to students of the second stage at the College of Education / University of Samarra, the researcher used the test of achievement in the computer material, prepared by the researcher consists of (50) paragraphs of the multiple choice, and to test the validity of assumptions used researcher statistical packages program (SPSS).
Computational Design and Fabrication of Customized Gamepads

research-article Share on Computational Design and Fabrication of Customized Gamepads Authors: Chinmay Rajguru University of Sussex University of SussexView Profile , Christos Mousas Purdue University Purdue UniversityView Profile , Lap-Fai Yu George Mason University George Mason UniversityView Profile Authors Info & Claims VRCAI '19: Proceedings of the 17th International Conference on Virtual-Reality Continuum and its Applications in IndustryNovember 2019 Article No.: 11Pages 1–11https://doi.org/10.1145/3359997.3365695Published:14 November 2019Publication History 1citation126DownloadsMetricsTotal Citations1Total Downloads126Last 12 Months12Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual Recognition

One-shot fine-grained visual recognition often suffers from the problem of training data scarcity for new fine-grained classes. To alleviate this problem, an off-the-shelf image generator can be applied to synthesize additional training images, but these synthesized images are often not helpful for actually improving the accuracy of one-shot fine-grained recognition. This paper proposes a meta-learning framework to combine generated images with original images, so that the resulting ``hybrid'' training images can improve one-shot learning. Specifically, the generic image generator is updated by a few training instances of novel classes, and a Meta Image Reinforcing Network (MetaIRNet) is proposed to conduct one-shot fine-grained recognition as well as image reinforcement. The model is trained in an end-to-end manner, and our experiments demonstrate consistent improvement over baselines on one-shot fine-grained image classification benchmarks.
Principal Component Analysis Algorithm Based on Mutual Information Credibility

Data dimensionality reduction is the mapping of data sets from high-dimensional feature space to low-dimensional feature space. Traditional principal component analysis (PCA) algorithm is a kind of commonly used data dimensionality reduction algorithm. The computation time of the traditional PCA is usually quite long that it cannot meet the requirement of the classification for real world problems. Through the study of mutual information credibility, a PCA data dimensionality reduction algorithm based on mutual information synthesize credibility is proposed. Firstly, the ideas of mutual information (MI), relative mutual information credibility (MIR) and absolute mutual information credibility (MIA) are introduced. Then the mutual information synthesize credibility (MIS) is solved according to MIA and MIR, and feature selection is carried out by using the mutual information synthesize credibility. Finally, PCA algorithm is used to reduce the dimension of the processed data, and KNN and SVM algorithms are used to classify the data after dimensionality reduction. Compared with traditional PCA and PCA based on information entropy (E-PCA) algorithms, the results indicate that the proposed algorithm can achieve a better effect on the dimensionality reduction result and has improved classification accuracy.
Learning from a Teacher using Unlabeled Data

Knowledge distillation is a widely used technique for model compression. We posit that the teacher model used in a distillation setup, captures relationships between classes, that extend beyond the original dataset. We empirically show that a teacher model can transfer this knowledge to a student model even on an {\it out-of-distribution} dataset. Using this approach, we show promising results on MNIST, CIFAR-10, and Caltech-256 datasets using unlabeled image data from different sources. Our results are encouraging and help shed further light from the perspective of understanding knowledge distillation and utilizing unlabeled data to improve model quality.
Enhance manet usability for encrypted data retrieval from cloud computing

&lt;p&gt;Cloud computing has become a revolutionary computing model which provides an economical and flexible strategy for resource sharing and data management. Due to privacy concerns, sensitive data has to be encrypted before being uploaded to the cloud servers. Over the last few years, several keyword searchable encryption works have been described in the literature. However, existing works mostly focus on secure searching using keyword and only retrieve Boolean results that are not yet adequate. On the other hand, poor-resources of mobile networks play an important role on all applications area nowadays. Mobile nodes mostly act as information retrieval end which make it important to address this problem. In this paper, we present a secure keyword search scheme based on the Bloom filter(SKS-BF), which enhances the system’s usability by allowing ranking based on the relevance score of the search results and retrieves the top most relevant files instead of retrieving all the files. Further, the Bloom filter (BFs) can accelerate a search process involving a large number of keywords. Extensive experiments and network simulation confirm the efficiency of our proposed schemes.&lt;/p&gt;