Reviewerly/exHarmony huggingface dataset:
DATA PENELITIAN SEBAGAI SUMBER INFORMASI UNTUK MELAYANI PEMUSTAKA DI PERPUSTAKAAN PENELITIAN

This paper explains the importance of research data as a source of information in serving users in research libraries as a result of the open science movement that is spreading around the world. Researchers/scientists are no longer satisfied with the publication of their written work, but primary data produced from research activities also need to be shared through an online repository system. This is in line with the demands of users who are increasingly complex in finding sources of information. Still a small number of research libraries that serve research data make it difficult for users when looking for information on primary/research data. An aspect of the benefits of research data services for research libraries is that they can create opportunities to increase library visibility and expand the role of libraries. The competence of librarians must be prepared to support research data services, given that there is no formal education in this regard. The concept of embedded librarian is possible as a solution through training, internships, and further education related to research data management. The practice of applying the concept of embedded librarians in the context of research places librarians more than just supporting staff, but librarians are placed as partners of researchers in conducting research activities.
Time to join the Silly Squad for this year's digital Summer Reading Challenge

The Summer Reading Challenge is the biggest annual reading promotion for children in the UK - and this year, for the first ever time, it’s going digital.
A Teaching Model Based on Korean English Textbook Using Process Drama: Focusing on High School Students

This paper suggests a teaching model based on Korean English textbook using process drama. After extracting research tools from previous researches regarding process drama and analyzing Korean national English curriculum and an English text book published by K publisher, a teaching model for Korean high school students utilizing process drama is designed. Then, to confirm its suitability in Korean English classroom, this teaching model is tested with four high school students for four weeks. In conclusion, students show decent conversation with the consideration for previously learned contents in the textbook, while exposed to a teaching model with process drama. This finding suggests that for a practical usage of English in a real situation, students need to be learned with a teaching model adjusted from process drama.
How Can Ict Make The Lessons More Interesting

Patafta is convinced that children with special needs would feel better in ordinary secondary schools where they are more accepted by their peers. So they should receive more knowledge and at the same time feel accepted in this ordinary environment. Much has been said about the inclusion in education lately. UNSECO defines inclusion as the education system capacity enlargement, which should be available to all students. With this belief in mind we set common goals for our project. First year students of ZGNL (Zavod za gluhe in naglusne) were thus joined with a group of ordinary primary school youngsters with no special needs using Arnes VOX conference online tool. We wished to achieve the required secondary school knowledge standards in computer sciences via cooperation between the two. The same was tried with the optional primary school multimedia class. The goal was that the primary and secondary school students actively cooperate in studying and other activities. All the study material and the studying process itself was tailored for special needs students as well as for students with autism, that took part. In the end, we obtained feedback about the yearly cooperation between the primary and secondary school students.
A Multi-view Images Classification Based on Deep Graph Convolution

Multi-view images represent the target images from different viewpoints. Reasonable use of complementary information between multiple perspective images helps to improve the accuracy of classification. We propose a novel deep spectral graph convolutional neural network (DSGC) model, extracting the deep characteristics of multi-view images via five spectral graph convolutional layers. Moreover, we propose a new method, which combines the DSGC with the ideal of [1]. The ideal of [1] regards the images of predefined views as latent variables, outputting the category probability matrix. We propose a DualFeature layer, which is used to enhance the ability to extract features. A pair of techniques batch normalization (BN) and dropout are used to improve classification performance. Experimental results show that.
The Transition Process and Improvement Direction of Autonomous Student Recruit System in China

The current social trend of China’s university entrance has almost the same characteristics as Korea’s university entrance: a high education fever and educational competition, a keen competition for university entrance, and academic elitism for a rise of status.BR In China’s university entrance system, these social characteristics play a positive role for talented people selected through fierce competition to train top-level human resources in all areas of the country.BR On the other hand, it is unfortunate that the education system focuses only on university entrance exams, which hardly helps the discovery of students’ individuality and creativity and makes it difficult to cultivate creative and practical talented people who the modern societies require.BR To resolve this shortcoming, China has been executing an autonomous student recruitment system since 2003. The autonomous student recruitment system is a system focusing on discovering students’ potential capabilities such as specialty, individuality, creativity. It could be said that it is similar to an admission officer system in Korea.BR The Gaokao (College entrance examination), a scholastic ability test in China, is ceaselessly being reformed. A lot of attempts have been made to expand universities’ authorities at a national level and to establish a diversified assessment standard and an assessment system. It could be said that one of such important policies is an autonomous student recruit system.BR Accordingly, this study is intended to research China’s autonomous student recruitment system to help understand China’s educational system and improve Korea’s educational system. This is a good research topic, in that there is a lack of internal and external research related to this.
Guest Editors' Introduction to the Special Section on Computational Photography

The nine papers in this special section focus on computational photography. The development of increasingly successful visual inference algorithms has driven progress in a number of different application domains—ranging from photography to autonomous vehicles to graphics and virtual reality systems. As we continue to extend the capabilities of these computational algorithms, a complementary research direction lies in asking what the right visual measurements are for these algorithms to operate on. In computational photography, we seek to investigate both components—computational and sensory—of intelligent visual systems in synergy, to build measurement schemes and inference algorithms that are jointly optimal for a desired task, and thus create functionalities that go beyond what is possible with traditional cameras and computational tools. The call for papers for this section was co-ordinated with the 2020 IEEE International Conference on Computational Photography (ICCP) that was held from April 24-26, 2020.
Why Do You Need a Network Security Checklist

I.S. Partners, LLC. can help you create, or update, a solid network security checklist that gives you and your IT unprecedented system confidence!
WhatsApp Plus APK Download (The Latest Version)

Thinking about how you can download the app on your Android Smartphone? Well, if the answer is yes then we are here to help you out. As you read further ...
Create Your Single-Page Application

Creating a single-page application is crucial if you want to develop an application with a well-performing and productive user experience. But it can be complicated and hard to maintain if you do not approach the development correctly.
Learning Memory-Efficient Stable Linear Dynamical Systems for Prediction and Control.

Learning a stable Linear Dynamical System (LDS) from data involves creating models that both minimize reconstruction error and enforce stability of the learned representation. We propose a novel algorithm for learning stable LDSs. Using a recent characterization of stable matrices, we present an optimization method that ensures stability at every step and iteratively improves the reconstruction error using gradient directions derived in this paper. When applied to LDSs with inputs, our approach---in contrast to current methods for learning stable LDSs---updates both the state and control matrices, expanding the solution space and allowing for models with lower reconstruction error. We apply our algorithm in simulations and experiments to a variety of problems, including learning dynamic textures from image sequences and controlling a robotic manipulator. Compared to existing approaches, our proposed method achieves an orders-of-magnitude improvement in reconstruction error and superior results in terms of control performance. In addition, it is provably more memory-efficient, with an O(n^2) space complexity compared to O(n^4) of competing alternatives, thus scaling to higher-dimensional systems when the other methods fail.
Javanese Lexical Configuration

espanolEsta investigacion tiene como objetivo analizar el modelo de configuracion lexica en javanes. El metodo de investigacion es una investigacion cualitativa descriptiva, con fuentes de datos obtenidas de la conversacion de la comunidad de usuarios de Java en la ciudad de Yogyakarta y Solo en la provincia central de Java. Los resultados mostraron que la configuracion lexica javanesa de la estructura jerarquica consistia en una relacion de dominacion transitiva, una relacion de dominacion asimetrica y una relacion de dominacion simetrica. Ademas de la configuracion de la jerarquia sin ramas taxonomica, tambien se encuentran una configuracion de jerarquia sin ramas y una configuracion de sesion de propuesta. EnglishThis research aims to look at the lexical configuration model in Javanese. The research method is descriptive qualitative research, with data sources obtained from the conversation of the Javanese user community in the city of Yogyakarta and Solo in Central Java province. The results showed that the Javanese lexical configuration of the hierarchical structure consisted of transitive dominance relation, asymmetric domination relation, and symmetrical dominance relation. The analysis also shows that Javanese has a taxonomic branching hierarchy and a merging branching hierarchy. In addition to the taxonomic branchless hierarchy configuration, a branchless hierarchy configuration and proposal session configuration are also found.
FACIAL RECOGNITION SYSTEM USING IMAGE PROCESSING

Authentication is a major challenge in computer-based communication system operation. Human face recognition is an important branch of biometric verification and has been commonly used in many applications, including video monitoring system, human-computer interaction, door control system, and network protection. A computational neural network can be  implemented as a framework in the face classification process. In order to recognize dimensions within the intend-able limits, the test system offers acceptable performance. The device also allows multiple faces to be identified and recognized in live pictures. Using OpenCV and  programming with Python, we design a real-time face recognition system.
A Certificate Life-cycle Management System Based on Blockchain in 5G

Currently, there are a large number of certificates need to be authenticated in 5G. However, most telecom operators are not ready enough for this. We present a certificate life-cycle management system based on blockchain PKI to solve the problem of identity authentication of base stations. We give a system model based on SM2 and commitment based on SM2. In the system, the certificate authority (CA) detects the service capability of 5G RAN, generates certificates, issues to users, and stores them on the blockchain. The CA can extract certificates from the blockchain. Besides, users in the system can verify the validity of certificates on the blockchain. What is more, they can know exactly whether a certificate is a new one or not according to the certificate pointer. We implemented a prototype, and analysis shows that the blockchain PKI eradicates the problem of single point failure and slow response. Besides, it has a good security, privacy protection, and highly efficient.
The Development Of Reading Literacy In The Field Of Learning In The Context Of Self-Evaluation

The basis for the formation of the self-evaluation report is a necessity by law, which is written in the jurisdiction of the school council and the tasks of the headmaster, in articles 48 and 49 of The Law on the Organization and Financing of Education (Official Gazette of RS, Nos. 16/07, 36/08, 58/09, 64/09, 65/09, 20/11, 40/2012-ZUJF). The purpose of self-evaluation is the identification of strong and weak areas of school operations which focus on improvement. Every school working group participates in the preparation of a self-evaluation report. A self-evaluation team prepared a proposal for a report on learning objectives. The team has meetings quarterly. Quality is an important area of operation which contributes to the fundamental missions of the school: education, learning and teaching, i.e. pupils' achievements in the broadest sense. We have set a preferential task on the basis on several indices, analyses of NAK results, and international research. We were wondering how the school, work groups, and individuals respectively could improve on this area. The preferential task we attended to on the school level was the learning objective of reading literacy – formative tasks. Each work group performed their own activity for the analysis of the results. It was important that the school had uniform criteria and appropriate indices. Nine work groups carried out two measurements and interim activities with the pupils.
SHADOWCAST: Controlling Network Properties to Explain Graph Generation.

We introduce the problem of explaining graph generation, formulated as controlling the generative process to produce graphs of explainable desired structures. By directing this generative process, we can measure and explain the observed outcomes. We propose SHADOWCAST, a controllable generative model capable of mimicking real-world networks and directing the generation, as a novel approach to this problem. The proposed model is based on a conditional generative adversarial network for graph data. We design it with the capability to maintain generation control by managing the conditions. Comprehensive experiments on three real-world network datasets demonstrate our model's competitive performance in the graph generation task. Furthermore, we direct SHADOWCAST to generate explainable graphs of different structures to show its effective controllability. As the first work to pose the problem of explaining generated graphs by controlling the generation, SHADOWCAST paves the way for future research in this exciting area.
Guides: COVID-19 Resources: Families and Education

The Saint Paul Public Library COVID-19 Resource Collection: a guide to references on a wide variety of COVID-19 topics.
VIDEO RECORDING ASSIGNMENT ON ENGLISH FOR DAILY CONVERSATION CLASS: AN INVESTIGATION ON STUDENTS’ AFFECT

Video recording assignment becomes one of necessary and beneficial efforts for enhancing students’ speaking ability. However, that attempt will be advantageous and will not waste the time if the students own positive respon toward them. Therefore, this research aims at investigating students’ affect toward video recording assignment on English for daily conversation class. This belongs to descriptive research. There were 78 students participated. The instruments used to collect the data were questionaire along with interview guide. The data got from the questionnaire were analyzed based on formula suggested by Heaton and Djemari et. All.  Meanwhile, the data got from interview guide were analyzed based on the theory suggested by Miles and Huberman. The finding of this research revealed that there were fifty seven or 73.07% students had strongly positive affect toward video recording assignment applied by the lecturer on English for daily conversation subject. It indicated that most of students like to do video recording assignment since it can increase their creativity and they have more time to speak. Moreover, it also can reduce their anxiety in speaking. It can be concluded that there is no psychological problem of the students to do video recording assignment. It means that video recording assignment can be applied by the lecturer in order to increase their speaking ability.
Adversarial Image Generation and Training for Deep Convolutional Neural Networks.

Deep convolutional neural networks (DCNNs) have achieved great success in image classification, but they may be very vulnerable to adversarial attacks with small perturbations to images. Moreover, the adversarial training based on adversarial image samples has been shown to improve the robustness and generalization of DCNNs. The aim of this paper is to develop a novel framework based on information-geometry sensitivity analysis and the particle swarm optimization to improve two aspects of adversarial image generation and training for DCNNs. The first one is customized generation of adversarial examples. It can design adversarial attacks from options of the number of perturbed pixels, the misclassification probability, and the targeted incorrect class, and hence it is more flexible and effective to locate vulnerable pixels and also enjoys certain adversarial universality. The other is targeted adversarial training. DCNN models can be improved in training with the adversarial information using a manifold-based influence measure effective in vulnerable image/pixel detection as well as allowing for targeted attacks, thereby exhibiting an enhanced adversarial defense in testing.
Se il plurilinguismo entra in classe dalla porta principale Gli atteggiamenti degli insegnanti di fronte a un’esperienza di <i>éveil aux langues</i>

This article presents an approach to analysis of attitudes within a focus group regarding plurilingualism enhancement. In specific, the teachers and their primary school classes were involved in the project Noi e le nostre lingue , realised by the University of Turin to fostering processes of language awareness, namely of éveil aux langues . In the illustrated theoretical and methodological systemic framework, the analysis of focus group conversation will show some clues to attitudes dimensions regarding knowledges, beliefs, expectations, emotions that support the evaluations and the behavioural intentions in this specific context.
Quantum Criticism: a Tagged news Corpus Analysed for Sentiment and Named Entities

In this project, we continuously collect data from the RSS feeds of traditional news sources.We apply several pre-trained implementations of named entity recognition (NER) tools, quantifying the success of each implementation.We also perform sentiment analysis of each news article at the document, paragraph and sentence level, with the goal of creating a corpus of tagged news articles that is made available to the public through a web interface.Finally, we show how the data in this corpus could be used to identify bias in news reporting.
Methodological Challenges of Technical Higher Education

Massachusetts's Institute of Technology was the first university to provide web based university and post gradual courses, in 2002. These courses were available on Open Course Ware bases, which was open to anyone. The goal for the next 10 years was to provide as many online courses as possible also easily accessible to everyone. While the focus was more on the "e" part of learning, slowly the accent has be moved from training to learning. This initiative was one of many signs that e-learning will prove to be successful. Using this teaching strategy, learning becomes personalized, relevant, interactive and advantageous for both teacher and student. The University of Obuda has always emphasized on implementing, modern teaching and learning strategies. In 2012 the University has launched the Office of Digital learning, which coordinates all electronic courses and their publications. Students mostly have learning needs rather than e-learning needs, this makes us believe that eLearning is a solution not an end in its self. For successful realization of this concept could be effective in meeting learning needs, however it has proven to be more difficult as we expected due to the constant change which takes place in this field. In 2014 K-MOOC was founded having the goal to provide higher education courses for as many students as possible. The opportunity to take on our eLearning courses is open to anyone; they are not location related and the phase of learning is determined by the student.
Novel framework for optimized digital forensic for mitigating complex image attacks

Digital Image Forensic is significantly becoming popular owing to the increasing usage of the images as a media of information propagation. However, owing to the presence of various image editing tools and softwares, there is also an increasing threats over image content security. Reviewing the existing approaches of identify the traces or artifacts states that there is a large scope of optimization to be implmentation to further enhance teh processing. Therfore, this paper presents a novel framework that performs cost effective optmization of digital forensic tehnqiue with an idea of accurately localizing teh area of tampering as well as offers a capability to mitigate the attacks of various form. The study outcome shows that propsoed system offers better outcome in contrast to existing system to a significant scale to prove that minor novelty in design attribute could induce better improvement with respect to accuracy as well as resilience toward all potential image threats.
Generating realistic Arabic handwriting dataset

During the previous year's holistic approach showing satisfactory results to solve ‎the ‎problem of Arabic handwriting word recognition instead of word letters ‎‎segmentation.‎ ‎In this paper, we present an efficient system for ‎ generation realistic Arabic handwriting dataset from ASCII input ‎text. We carefully selected simple word list that contains most Arabic ‎letters normal and ligature connection cases. To improve the ‎performance of new letters reproduction we developed our ‎normalization method that adapt its clustering action according to ‎created Arabic letters families. We enhanced Gaussian Mixture ‎Model process to learn letters template by detecting the ‎number and position of Gaussian component by implementing ‎Ramer-Douglas-Peucker‎ algorithm which improve the new letters ‎shapes reproduced by using and Gaussian Mixture Regression. ‎‎We learn the translation distance between word-part to achieve ‎real handwriting word generation shape.‎ Using combination of LSTM and CTC layer as a recognizer to validate the ‎efficiency of our approach in generating new realistic Arabic handwriting words inherit user handwriting style as shown by the experimental results.‎