Reviewerly/exHarmony huggingface dataset:
Improving Matsui’s Search Algorithm For The Best Differential/Linear Trails And Its Applications For DES, DESL And GIFT

Abstract Automatic search methods have been widely used for cryptanalysis of block ciphers, especially for the most classic cryptanalysis methods—differential and linear cryptanalysis. However, the automatic search methods, no matter based on MILP, SMT/SAT or CP techniques, can be inefficient when the search space is too large. In this paper, we propose three new methods to improve Matsui’s branch-and-bound search algorithm, which is known as the first generic algorithm for finding the best differential and linear trails. The three methods, named reconstructing DDT and LAT according to weight, executing linear layer operations in minimal cost and merging two 4-bit S-boxes into one 8-bit S-box, respectively, can efficiently speed up the search process by reducing the search space as much as possible and reducing the cost of executing linear layer operations. We apply our improved algorithm to DESL and GIFT, which are still the hard instances for the automatic search methods. As a result, we find the best differential trails for DESL (up to 14-round) and GIFT-128 (up to 19-round). The best linear trails for DESL (up to 16-round), GIFT-128 (up to 10-round) and GIFT-64 (up to 15-round) are also found. To the best of our knowledge, these security bounds for DESL and GIFT under single-key scenario are given for the first time. Meanwhile, it is the longest exploitable (differential or linear) trails for DESL and GIFT. Furthermore, benefiting from the efficiency of the improved algorithm, we do experiments to demonstrate that the clustering effect of differential trails for 13-round DES and DESL are both weak.
INCREASE THE AWARENESS OF ALS PATIENTS THROUGH A VIRTUAL REALITY APPLICATION

Appears in: EDULEARN20 Proceedings Publication year: 2020Pages: 4403-4408ISBN: 978-84-09-17979-4ISSN: 2340-1117doi: 10.21125/edulearn.2020.1166Conference name: 12th International Conference on Education and New Learning TechnologiesDates: 6-7 July, 2020Location: Online Conference
Signature restriction for polymorphic algebraic effects

The naive combination of polymorphic effects and polymorphic type assignment has been well known to break type safety. Existing approaches to this problem are classified into two groups: one for restricting how effects are triggered and the other for restricting how they are implemented. This work explores a new approach to ensuring the safety of polymorphic effects in polymorphic type assignment. A novelty of our work lies in finding a restriction on effect interfaces. To formalize our idea, we employ algebraic effects and handlers, where an effect interface is given by a set of operations coupled with type signatures. We propose signature restriction, a new notion to restrict the type signatures of operations, and show that signature restriction is sufficient to ensure type safety of an effectful language equipped with unrestricted polymorphic type assignment. We also develop a type-and-effect system to enable the use of both operations that satisfy and do not satisfy the signature restriction in a single program.
Designing and configuring context-aware semantic web applications

Context-aware services are attracting attention of world as the use of web services are rapidly growing. We designed an architecture of context-aware semantic web which provides on demand flexibility and scalability in extracting and mining the research papers from well-known digital libraries i.e. ACM, IEEE and SpringerLink. This paper proposes a context-aware administrations system, which supports programmed revelation and incorporation of setting dependent on Semantic Web administrations. This work has been done using the python programming language with a dedicated library for the semantic web analysis named as “Cubic-Web” on any defined dataset, in our case as we have used a dataset for extracting and studying several publications to measure the impact of context aware semantic web application on the results. We have found the average recall and averge accuracy for all the context aware research journals in our research work. Moreover, as this study is limited journal documents, other future studies can be approached by examining different types of publications using this advance research. An efficient system has been designed considering the parameters of research article meta-data to find out the papers from the web using semantic web technology. Parameters like year of publication, type of publication, number of contributors, evaluation methods and analysis method used in publication. All this data has been extracted using the designed context-aware semantic web technology.
SCHOLARSHIPS OF TEACHING &amp; LEARNING AMIDST THE PREPARATION FOR INDUSTRY REVOLUTION 4.0: IMPLICATIONS FOR THE ACADEMICS’ PROFESSIONAL DEVELOPMENT TRAINING NEEDS

SCHOLARSHIPS OF TEACHING & LEARNING AMIDST THE PREPARATION FOR INDUSTRY REVOLUTION 4.0: IMPLICATIONS FOR THE ACADEMICS’ PROFESSIONAL DEVELOPMENT TRAINING NEEDS
Applying Systems’ Similarities to Assess the Plausibility of Armed Conflicts

An assessment of the similarity of situations and developments in decision-making processes is under consideration. Specifically, mathematical and IT tools that make it possible to assess plausibility and similarity based on the limited amount of information available. Under observation is the assessing the plausibility of occurrence of armed conflict. The data this study is based on is limited periodically and regionally: starting from the end of World War II, until the year 2008. Developments and situations will be treated as algebraic systems.
Corpus Construction and Annotation Challenge for Language Identification and Sentiment Analysis

Corpora construction is an indispensable task in many natural language processing (NLP) domains. Thus, this paper aims to construct a linguistic resource that covers two NLP domains simultaneously, namely language identification, that distinguishes Moroccan Dialectal Arabic from Modern Standard Arabic, and sentiment analysis. It presents the construction concept, defines data sources, explains the annotation process and describes corpus characteristics. All along the paper, the description is enhanced by statistics and vivid examples. Moreover, the paper studies either language identification or sentiment analysis specificities separately.
Functional Regularization for Representation Learning: A Unified Theoretical Perspective

Unsupervised and self-supervised learning approaches have become a crucial tool to learn representations for downstream prediction tasks. While these approaches are widely used in practice and achieve impressive empirical gains, their theoretical understanding largely lags behind. Towards bridging this gap, we present a unifying perspective where several such approaches can be viewed as imposing a regularization on the representation via a learnable function using unlabeled data. We propose a discriminative theoretical framework for analyzing the sample complexity of these approaches, which generalizes the framework of (Balcan and Blum, 2010) to allow learnable regularization functions. Our sample complexity bounds show that, with carefully chosen hypothesis classes to exploit the structure in the data, these learnable regularization functions can prune the hypothesis space, and help reduce the amount of labeled data needed. We then provide two concrete examples of functional regularization, one using auto-encoders and the other using masked self-supervision, and apply our framework to quantify the reduction in the sample complexity bound of labeled data. We also provide complementary empirical results to support our analysis.
PROSPECTS FOR INTEGRATING ARTIFICIAL INTELLIGENCE AND NEW DIGITAL TECHNOLOGIES INTO TERTIARY EDUCATION

The paper focuses on the issue of implementing Artificial Intelligence (AI) and online educational technologies into the sphere of higher education. Today AI is gradually penetrating into such spheres of human activity as medicine, business, science, journalism, entertainment, etc. The use of AI-driven programs and digital technologies is also observed in such conservative area of our life as education and the potential of AI to disrupt the educational sector is immense. Online educational platforms involve blended learning that promises to enhance education at all levels, especially by providing adaptive teaching. The key challenge is to best integrate human interaction and face-to-face learning with the latest digital educational technologies and resources. The topic is extremely relevant as today we should find new approaches to education in order to improve its quality and accessibility. Blended learning, based on the use of the latest digital technologies, is designed to solve these problems.Since the main purpose of the given research is to discuss the prospects for the introduction of digital educational technologies and online resources into the modern system of tertiary education, first, the author considers promising areas of AI application in education; then studies the current state of affairs in this field, names specific examples of existing digital programs, provides some information on the principles of operation and capabilities of such electronic platforms as Coursera and Moodle; conducts a survey among undergraduates in order to determine the attitude of students to the use of online platforms and identify their effectiveness in foreign language teaching; and finally considers the advantages and disadvantages of the new educational technology and identifies possible threat or benefit to the teaching profession.The data obtained as a result of an empirical study confirm the assumption that the use of online educational resources enhances motivation and cognitive activity of students, improves their self-study skills, provides an individualization of the learning process, and, on the whole, helps to have a thorough grasp of the subject.In conclusion, the author states that despite the fact that the scope of the use of online platforms and state-of-the-art technologies in the field of education is extensive, the truth is that none of these computer programs is remotely intelligent in the way that a human being is and none of the electronic educational resources can replace the process of cooperation between a student and a teacher. Therefore, all projects for the implementation of AI and digital educational resources into the modern system of higher education currently do not pose a direct threat to the profession of a teacher.
Designing Contextually: An Investigation of Design-Based Research to Promote Situated Irish Language Identity through Virtual Reality

The Irish language is a minority language within the island of Ireland with only 5% of speakers using it daily outside the education system. This paper presents the results of the third case study in a mixed methods design-based research experiment with the aim of improving the situated Irish language identity of Irish language learners. A situated virtual reality game was designed by the researchers in order to improve Irish language identity among its players. We outline the design decisions of the game along with the results of a five-week study with a context group of Irish language learners. Data gathered through the iterative process of the design based research cycles has informed the design decisions of the study. The study evaluates the change in attitudes, ideal self and vocabulary retention as a result of interaction with the virtual reality game.
THE ROLE OF THE DIGITAL TRANSFORMATION FOR THE IMPROVEMENT OF THE UNIVERSITY EDUCATION AND THE IMPORTANCE OF THE IT LEADERSHIP FOR THE SUCCESSFUL RE-ENGINEERING OF THE LEARNING PROCESS

THE ROLE OF THE DIGITAL TRANSFORMATION FOR THE IMPROVEMENT OF THE UNIVERSITY EDUCATION AND THE IMPORTANCE OF THE IT LEADERSHIP FOR THE SUCCESSFUL RE-ENGINEERING OF THE LEARNING PROCESS
NL2Code: A Corpus and Semantic Parser for Natural Language to Code

In this work, we present a new method of semantic analysis and data allowing the automatic generation of source code from specifications and descriptions written in natural languages (NL2Code). Our long-term goal is to allow any user to create an application from a specification describing the need for a complete system. It involves the realization of a study, the design and the implementation of an intelligent system allowing the automatic generation of a computer project by answering the needs of the user (skeleton, configuration, scripts of initialization, ...) expressed in natural language. We are taking a first step in this area by providing a new dataset specific to our Novelis company and putting in place an approach that allows the machine to understand the user’s need, expressed in natural language in a specific area.
Analysis of data mining method for short-term wind measurement of wind farm based on multi-technology fusion

Aiming at the problems of poor noise reduction effect of current methods for short-term wind measurement data, poor fitting between wind measurement values and real values, and long running time of the methods, a data mining method for short-term wind measurement of wind farm based on multi-technology fusion is proposed. The anomaly points in the short-term wind data are found and corrected. The short-term wind data are de-noised by wavelet decomposition and normalised. The short-term wind speed measurement of wind farms at each time is carried out, and the short-term wind measurement data mining of wind farms is finally realised. The experimental results show that the proposed method has better noise reduction effect for short-term wind measurement data, the fitting degree between wind measurement value and real value is higher, and the running time of the method is shorter. All the above results verify the effectiveness of the proposed method.
Author Correction: Analog Coding in Emerging Memory Systems

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Human Pose Estimation Applying ANN While RGB-D Cameras Video Handling

In the paper we try to solve the problem of online human pose estimation. All over the world security systems of railway stations, airports and other facilities have control points. Control points are equipped with cameras and other devices for automated data acquisition. One of the tasks within security providing is to recognize the position of body parts of the human, passing the control point. In this paper, a method, based on the use of artificial neural networks. The features of the practical implementation of the proposed approach are described.
Research on the Innovative Talents in “Double First-Class” Universities under Artificial Intelligence Technology

Abstract With the continuous integration of artificial intelligence technology and management disciplines, the emergence of new technologies and new concepts put forward new requirements for the cultivation of cross-disciplinary talents in management disciplines. At the same time, strengthening the development of cross-disciplinary integration is also a vital part of the “Double First-Class” universities construction. This article points out that the application direction of artificial intelligence technology in innovative talents of management discipline can be divided into three levels: computational intelligence, perceptual intelligence, and cognitive intelligence. Based on the three levels, formulated innovative talents in the management discipline cross-cultivation model that integrates innovation quality orientation, innovation performance orientation and innovation contribution orientation, designed a talent training operation mechanism based on multi-subject collaboration, facing the new education ecology in the era of artificial intelligence.
Web Based Online Inventory Information System

Abstract This study aims to show the use of a web-based online inventory system to maximize human performance in the work process in companies. This study used descriptive method by reading related literatures. From this research, show about web-based online inventory system is an innovation in facilitating the management of goods, helping to make complicated things easier, this is good news for large companies in running their businesses, no wonder many companies are using online inventory systems to help work. Companies that use online inventory systems are competing in developing their existing inventory systems so they can better support the company’s work.
Students’ perceptions of using padlet as a learning tool for English writing / Mohd Zaidi Mahmud

The introduction of Padlet as a learning tool has changed the traditional method of teachingfrom teacher-centered to student-centered. This can be seen in the classes where the lecturershave integrated Padlet in their teaching, particularly in English writing class. In this study,Padlet was used as a tool or platform for learning English writing. The aim of this study is toinvestigate the students’ perceptions of the usage of Padlet in learning English writing in theEnglish as Second Language (ESL) tertiary classroom. A total of 60 students from one privatecollege in Penang were asked to complete a survey questionnaire, and 6 of them wereinterviewed to gather feedback on their perceptions of using Padlet as a learning tool forEnglish writing. The survey results showed that Padlet is a good learning tool for collegestudents with a mean score of 3.503 (S.D=0.476). The interview analysis showed clearer results.Based on the focus group interview, the students think that Padlet could not assist them to learnEnglish writing, as Padlet only accommodate simple English activities. They have suggested thatby adding advanced English programs and activities into Padlet, it will help them to improve thelearning process of English writing.
Prevention and Analysing on Cross Site Scripting

Nowadays web application is highly demandable in different criteria based on their e-commerce setup which give assurance in security to lots of customers. If an applications contains small flaw of susceptibilities on it, Attackers had accidental to steal their credential password accidentally same way, Cross site scripting is a procedures where malicious code are to be exploit by an attackers to Grab the credential information of a user’s it may within your web application or within a server side database its allow us by injecting malicious JavaScript when code wasn’t sanitized for a web applications This study discusses about Cross site attack and its taxonomy, In addition to that the paper presents the XSS attack apparatuses, Analysis and preclude from XSS forgery.
Multiple Criteria Fake Reviews Detection Based on Spammers’ Indicators Within the Belief Function Theory

E-reputation becomes one of the most important keys of success for companies and brands. It is mainly based on the online reviews which significantly influence consumer purchase decisions. Therefore, in order to mislead and artificially manipulate costumers’ perceptions about products or services, some dealers rely on spammers who post fake reviews to exaggerate the advantages of their products and defame rival’s reputation. Hence, fake reviews detection becomes an essential task to protect online reviews, maintain readers’ confidence and to ensure companies fair competition. In this way, we propose a new method based on both the reviews given to multiple evaluation criteria and the reviewers’ behaviors to spot spam reviews. This approach deals with uncertainty in the different inputs thanks to the belief function theory. Our method shows its performance in fake reviews detection while testing with two large real-world review data-sets from Yelp.com .
The Psychological Characteristics of the Formation of Elementary Mathematical Operations in Children

Children’s general orientation to the world of mathematics is largely a function of the initial concepts and operations they master. This orientation, in turn, has an important influence on children’s further mathematical development. Identifying the concepts and skills with which the study of mathematics in school should begin is, therefore, of considerable importance in the improvement of mathematical instruction because these concepts and the operations connected with them form the foundation for the structure of the entire academic discipline. In our view, many difficulties in teaching mathematics in schools 1 arise from the fact that neither the content of elementary mathematical concepts nor the methods of introducing them in instruction have yet been subjected to careful psychological investigation.
Energy-saving Design of the Enclosure Structure of Teaching Buildings in Severe Cold Areas

Abstract In recent years, the energy saving issue in public educational places has attracted more and more attention from scholars in the society, especially the energy-saving design and construction of teaching buildings in severe cold areas have received widespread attention from scholars from all walks of life. In this paper, it will further analyze the energy-saving design of the enclosure structure of teaching buildings in severe cold areas, aiming to further improve the energy-saving design level of public buildings, so that construction projects can better serve education fields.
Blind restoration of atmospheric turbulence degraded images by sparse prior model

Blind image deconvolution is one method of restoring both kernel and real sharp image only from degraded images, due to its illness, image priors are necessarily applied to constrain the solution. Given the fact that traditional image gradient l2 and l1 norm priors cannot describe the gradient distribution of natural images, in this paper, the image sparse prior is applied to the restoration of single-frame atmospheric turbulence degraded images. Kernel estimation is performed first, followed by non-blind restoration and the split Bregman algorithm is used to solve the non-convex cost function. Simulation results show that compared with total variation priori, sparse priori is better at kernel estimation, producing sharp edges and removal of ringing, etc., which reducing the kernel estimation error and improving restoration quality. Finally, the real turbulence-degraded images are restored.