Reviewerly/exHarmony huggingface dataset:
Italian Sign Project 1.0.1 By Scan720 [1.36.X]

Changes v1.0.1 Completely rework of all signs (with the old Format) Compatible With Southern Region Now! Reworks at A4 (Verona-Venezia) Some Bugs ...
Outlier-Robust Learning of Ising Models Under Dobrushin's Condition

We study the problem of learning Ising models satisfying Dobrushin'scondition in the outlier-robust setting where a constant fraction ofthe samples are adversarially corrupted. Our main result is to providethe first computationally efficient robust learning algorithm for thisproblem with near-optimal error guarantees. Our algorithm can be seenas a special case of an algorithm for robustly learning a distributionfrom a general exponential family. To prove its correctness forIsing models, we establish new anti-concentration results for degree-2 polynomials of Ising models that may be of independent interest.
LibGuides: Grade 1 Library Guide, PXES: 3 Rs

Materials to help support Grade 1 literacy units, including Small Moments, . . . . .(to be completed as the 2020-21 School Year progresses)
The Economics of Cyber Crime

Digital technologies are creating more value and thus becoming more attractive to cyber criminals. Gary Becker provides a philosophy for understanding crimes from an economic perspective, but criminal behavior and potential policies against it differ in the context of a digital economy. Criminals with economic incentives are expected to hack digital systems and ask for a ransom to not disturb those compromised. We model the interactions between attackers and defenders with a dynamic Bayesian game. There are two processes. The first is the attackers' learning about the distribution of the defenders' level of defense, and the second is the attackers' reputation building based on being honest after being paid. The attackers' dynamic decision is captured by a bandit process. The defenders' behavior exerts externalities on themselves by influencing the attackers' behavior. We explore policies that could enhance social welfare through moderating these externalities.
Paired discrete competition with a free route choice

The paper considers the problem of optimizing the operation schedule for multiprocessor systems. The solution to this problem involves the formation of a rigid work schedule, which determines the rhythm of the processes, but in practice the functioning of systems is influenced by many side factors that make the intervals of work execution random. In the work, a semi-Markov model of the formation of a stochastic schedule in conditions of pair competition is constructed. It is shown that if during the functioning of the system it is possible to execute the items of the schedule in an arbitrary order, then the evolution of the semi-Markov process follows the Hamiltonian path. It is proved that all possible realizations of Hamiltonian paths form a complete group of incompatible events. It is noted that, due to the imposition of restrictions on the nature of evolution, the evolution process is not strictly semi-Markov, and therefore a method of forming a strictly semi-Markov process with a tree structure from the primary model is proposed. Dependences are obtained for calculating the distribution densities and the probabilities of switching from states of a semi-Markov process to conjugate states, as well as the time of walking from the starting to absorbing states. Using the concept of paired discrete competition and a distributed penalty, the effectiveness of the choice of a Hamiltonian path by one of the subjects is estimated, taking into account the fact that the algorithm of his opponent’s behavior is known up to the construction of a semi-Markov model.
Course Learning Materials Application For Computer Science Students

This project was centered on “Android Based Course Learning Materials Application (Courseware) for computer science students”. The current process of learning is being done manually and due to this procedure the learning process is slow and not encouraging. An Android will be developed to computerize the manual way of learning in order to check this problem. The problems were identified after series of interviews and examination of documents after which analysis was made and a computerized procedure recommended. This work also aimed to use the mobile phones and other handheld devices as e-learning pedagogical tools in order to enhance technology-enabled interactive learning. This project work made use of data collected from the university, materials and journals from various authors and an android application was developed to effectively achieve the aims of this project. The new system was designed using Extended Markup Language (XML), Java JDK, and SDK (Software Development Kit). These languages and platform were chosen because of their easy syntax and features for developing android based applications.
Research Guides: Introduction to eBooks: Frequently Asked Questions

This guide includes links to the Carl B.'s eBook collections and answers to eBook frequently asked questions.
Provision of mathematical prerequisites to students in humanities at the Federal University of Yakutia

The purpose of the research is to reveal the problems of studying mathematics by students of the humanities and specialties, using the example of students of the Faculty of Philology and the Institute of Foreign Philology and Regional Studies of the Ammosov North-Eastern Federal University and describe the experience of teaching mathematics, contributing to the formation of general cultural competencies focused on the use of mathematical methods in professional activities. A sociological study was carried out in the form of a written survey of students and conversations with teachers of the Faculty of Philology and the Institute of Foreign Philology and Regional Studies, covering 114 students and 4 teachers. Based on the results of the study, the authors summed up the possibility of spreading this experience, using the proposed educational and methodological complex in other humanitarian areas and specialties.
Study of Quantum Cryptography with a Thorlabs Teaching Apparatus

A pseudo-quantum system consisting of laser diodes, wave retarders, beamsplitters, and photodetectors was employed to study encryption of data through binary transmission. The Jones vectors for each optical element can be represented in matrix notation and operated on through linear algebra computation. The laser diodes emit polarized photon pulses which can be represented by 2 x 1 matrices which are treated as transmitted bits. Because of the inherent randomness of polarized photons through a beamsplitter any intermediate detection and subsequent transmission of bits by a third party can immediately be detected. In this study, a total error rate of 25% was calculated for a 20-bit key and 52-bit protocol when the transmitted signal was intercepted in agreement with theory.
Residual Network of Residual Network: A New Deep Learning Modality to Improve Human Activity Recognition by Using Smart Sensors Exposed to Unwanted Shocks

Background and Objective: Recently, smartphones have been vastly utilized in monitoring the daily activities of people to check their health. The main challenge in this procedure is to distinguish similar activities based on signals recorded by using sensors mounted on smartphones and smartwatches.Although deep learning approaches have better addressed the above challenge than alternative methods, their performance may be severely degraded, especially when the mounted sensors receive disturbed signals due to smartphones and smartwatches not being in a fixed position.Methods: In this article, a new deep learning structure is introduced to recognize challenging human activities by using smartphones and smartwatches, even when the recorded signals are noisy due to the sensors being unstable. In the proposed structure, the residual network of residual network (i.e. ROR) is engaged as a new concept inside the deep learning architecture, which provides greater stability against either disturbed or noisy signals.Results: The performance of the proposed method is evaluated on recorded signals from smartphones and smartwatches and compared with the state of art techniques containing deep learning and classic (non-deep) schemes. The obtained results show that the proposed method may improve the recognition parameters at least 1.79 percent against deep alternatives in distinguishing challenging activities (i.e. downstairs and upstairs). These superiorities reach at least 32.86 percent for classic methods, which are applied on the same data. Conclusions: The effectiveness of the architecture in recognizing either challenging or non-challenging activities in the presence of unwanted cell phone shocks demonstrates its potential to be used as a mobile application for human activity recognition.
THE PRINCIPLE OF UNITY OF SENSUALLY-EMPIRICAL AND CONCEPTUAL COGNITION AS A MEANS OF DEVELOPMENT CREATIVITY OF TEACHERS AND STUDENTS

The article proves that the unity of sensory-empirical and conceptual knowledge, expressed in their interpenetration into each other, is the most important means of developing the creativity of teachers and students. Sensory cognition in the broad sense of the word is understood as sensory (sensitive) cognition in the form of sensations, perceptions and representations and sensory-emotional. The opposite of sensory cognition is rational cognition, which in thinking reflects what is given in sensory cognition. If sensory images are verbalized at an ordinary level, then there is a rational everyday consciousness, if on the basis of certain theoretical concepts, then there is empirical knowledge. The opposite of sensory-empirical cognition is conceptual cognition in the form of a unity of theoretical, normative-evaluative and project cognition. In the pedagogical literature, the term “sensory-empirical knowledge” is not used. Instead, the term “visualization” is used, which is identical to the term “sensory cognition”. But in the pedagogical process empirical knowledge is also used as a visualization. Therefore, the basis for clarity is the last. Visibility in educational activities provides: 1) students’ understanding of the meaning of abstract knowledge; 2) their understanding of the personal meaning of scientific knowledge; 3) the formation of skills to use scientific knowledge as methods of their activities; 4) control by teachers and students of the degree of assimilation of conceptual knowledge and the ability to use them; 5) and most importantly – the development of the creativity of teachers and students. If the knowledge acquired by students meets these requirements, then it is “living knowledge”, if it does not correspond, then it is “dead knowledge”. In the scientific activities of teachers and students, the development of creativity is ensured primarily by the unity of empirical and theoretical knowledge, as well as by the unity of sensory-empirical, evaluative and project knowledge when assessing scientific activity and developing recommendations for practice. In university practice, the development of students’ creativity is ensured by diagnosing the “place” of practice by the student, developing a project of the labor process and implementing it through self-government on the basis of the project.
SIJELLO' TO MAMPU LEGEND’S PICTURE STORYBOOK DESIGN TO TEACH ETHICS FOR CHILDREN

In Bone Regency, South of Sulawesi, there is a historical site called Goa Mampu.There is a legend about the origin of Goa called to Mampu Overall, this legend contained decisive messages about the attitude of responsibility towards our ownself words. Children are still categorized in the phase of learning. This condition can be used to teach children about good ethics. Using the message contained in the legend of to Mampu, can teach the children about good ethics.The method that uses in the picture storybook is the design method that was developed by Bruce Archer, where the problem issue will lead to the acquisition of appropriate data, then the analysis of the data is to get the right solution. The techniques that use to obtain all data are observation, interviews, and document data. Using these techniques, then the data obtained is analyzed using the 5W+1H analysis method (What, Where, Who, When, Why, and How). The design strategy that uses in the picture storybook of Sijello' to legend is to use a picture storybook as the media that dominate by colorful illustrations rather than the text. The design uses cartoon-style illustrations that seem funny and cute. The colors in the picture books have a warm and soft atmosphere with primary and secondary colors. The language for the story is also simpler to make children easily understand the story. This language is also needed to be accompanied by using handwriting typography with sans serif typefaces for easy to read.
Resource Management Technology and Application of Remote Network Education Based on Metadata

Abstract Based on the effective solution to the problem of poor supply and application of digital education resources. Aiming at the digital basic education resources involved in the field of basic education, this paper uses the methods of investigation and research, demand analysis, metadata model design, system design, practice verification, etc., based on the metadata system and web service of digital basic education resources We have completed the business process analysis of the shared service system, the overall design of the sharing platform, the design of the three-tier metadata structure, the collation and aggregation of digital resources, the realization and verification of platform technology. From the compilation, supplement and description of resource metadata specification, to the clustering, integration and cataloging of digital resources, and then to the realization of retrieval and service interface, this paper focuses on the effective integration of high-quality digital basic education resources in the process of network sharing. Through the establishment of a relatively complete set of digital education resources integration, convergence engineering methodology, to provide the best solution for teachers in the application of resources, maximize support for teachers’ work efficiency, and promote the improvement of curriculum teaching level.
A Survey Paper on Breast Cancer Detection using Big data

Breast malignancy is the second reason for death among ladies. Early recognition followed by proper malignant growth treatment can lessen the savage danger. It is a genetic sickness and doesn't result from a solitary reason. The analysis of malignancy begins with a biopsy. A computer-aided diagnosis (CAD) framework dependent on mammograms empowers early bosom malignant growth location, finding, and treatment. Be that as it may, the precision of existing CAD frameworks remains unsatisfactory[2]. Different techniques are utilized to identify and perceive malignant growth cells, from minute pictures and mammography to ultrasonography and magnetic resonance images (MRI). In the current examination, Extreme Learning Machine (ELM) order was performed for 9 highlights dependent on picture division in the Breast Cancer Wisconsin (Diagnostic) informational index in the UC Irvine Machine Learning Repository information base. Enormous Data innovation is utilized to examine these datasets in an information base for exact investigation and location of amiable and threatening bosom masses. Broad trials show the precision and efciency of our proposed mass recognition and bosom malignancy classication technique. With the sheer size of information accessible today, large information brings huge chances and extraordinary potential for different areas; then again, it likewise presents exceptional difficulties to outfitting information and information[3].
Large Scale Efficient Clustering Using DBSCAN and Ensemble Techniques

Data clustering techniques are unsupervised machine learning techniques used in the field of data mining. Different clustering technique operate and perform differently based on the characteristics of input dataset. DBSCAN is a popular clustering technique with great ability to cluster datasets of arbitrary shapes and different sizes and densities using the principle of density estimation and noise removal. Density based clustering has proven to be very efficient and has found numerous applications across several domains. But DBSCAN does not perform well with clusters of similar densities and has a worst case run-time complexity of O(n^2) for high dimensional data. In this paper we try to overcome the drawbacks by developing SuperCube based Accelerated Density Based Spatial Clustering algorithm that detects the clusters by performing a dimensionality reduction that is, transforming high dimensional complex data into a lower dimensionality data and uses a unique combination of a virtual grid and employs representative points which reduces the time complexity to O (n log n). Results from the experiments with Datasets of varying sizes and dimensions are presented which proves that the proposed algorithm performs with greater accuracy and effectiveness.
Library Guides: Cyber Security: Online videos - Lynda.com

This guide provides links to Australian and international standards and regulations relevant to cyber security.
Epistemological-Methodological and Applied Aspects of Georg Brutian’s Philosophy

The article presents a number of key episodes and elaborations of the philosophical legacy of the famous Armenian philosopher of the 20th-21st centuries Georg Abel Brutian, each of which is a valuable contribution to the treasury of world philosophical thought. In particular, the paper deliberates on the epistemological-methodological and applied aspects of the concept of polylogic, transformational logic as a non-classical logical value system, the principle of linguistic complementarity. The paper analyzes the main achievements of the famous thinker in the field of study of the semantic theory of knowledge, logical principles of translation art, issues of argumentation theory, methodological bases of Armenology, their methodological significance in the context of further development of science.
Box Office Success Prediction Through Artificial Neural Network and Machine Learning Algorithm

In this study, a comparison is made between Artificial Neural Network Algorithm and Machine Learning Algorithm of Support Vector Machine by considering pre-release and pre plus post release features of a movie for predicting a movie to a particular success class. These success classes includes Flop/Disaster, Average, Hit, Super-Hit and Block-Buster of a movie. Our best performing model from Artificial Neural Network and Support Vector Machine is able to give better performance in order to predict any particular movie to specific success class of a movie for both the cases of prerelease as well as pre plus post release features of a movie.
Smart Home Setup Based on Service Design

The aim of this paper is to analyze the existing smart home setup problems and propose the solution of the problem based on the service design. Smart home is developing towards whole-house smart home, which makes the setup more complex. In order to improve user experience, some smart home enterprises are beginning to deploy services to help users to set up. This paper analyzes the pain points of the typical setup process of smart home through user testing, which includes eye tracking experiments and post-test interviews. In the future, AI technology may be a good way to solve these pain points. After discussing service design theory, this paper presents a service system to help users easily set up a smart home that meets their family needs. In conclusion, making full use of service design to improve user experience is an effective direction to promote the smart home industry.
InfoGuides: Research Support: Research Impact & Analysis

Information about library services that support faculty research. Covers services such as issuing DOIs, repository and publishing services for sharing and archiving research, metadata, data management, ORCID, biosketches, copyright and Creative Commons.
Classifying Urdu Verbs Using Rule Based Approach

To make dictionaries complete and to keep their size restricted, there is an approach in the linguistic world to equip these dictionaries with morphological information. This module of morphological information is usually known as a morphological analyzer or morphological classifier, which normally contains the complete possible linguistic information about each word for that particular language and it also describes the rules of derivations from the root of a word and its various inflections, respectively. In this work, a classifier for Urdu verbs (CUV) is proposed which is still a challenging research issue, as Urdu is a language of high inflection and derivation. The available stemmers for Urdu do not provide enough information about inflectional and derivational forms of words. Also, morphological classifiers available for Urdu are not worthy of handling various problems and delivering results that prune errors. In our work, a rule based CUV is designed which is able to classify 63 forms of Urdu verbs successfully out of 66. Available Urdu language processing tools are very rare compared to other higher inflectional languages such as German, Turkish, etc., which have competitive morphological classifiers. However, the studies related to Urdu verb morphological classification are identified and a comparative study is presented in this article. In short, this work is a positive contribution to the community, and it provides sufficient information with promising results specifically on inflectional and derivational forms of Urdu verbs.
Reasoning on with Defeasibility in ASP

Reasoning on defeasible knowledge is a topic of interest in the area of description logics, as it is related to the need of representing exceptional instances in knowledge bases. In this direction, in our previous works we presented a framework for representing (contextualized) OWL RL knowledge bases with a notion of justified exceptions on defeasible axioms: reasoning in such framework is realized by a translation into ASP programs. The resulting reasoning process for OWL RL, however, introduces a complex encoding in order to capture reasoning on the negative information needed for reasoning on exceptions. In this paper, we apply the justified exception approach to knowledge bases in $\textit{DL-Lite}_{\cal R}$, i.e., the language underlying OWL QL. We provide a definition for $\textit{DL-Lite}_{\cal R}$ knowledge bases with defeasible axioms and study their semantic and computational properties. In particular, we study the effects of exceptions over unnamed individuals. The limited form of $\textit{DL-Lite}_{\cal R}$ axioms allows us to formulate a simpler ASP encoding, where reasoning on negative information is managed by direct rules. The resulting materialization method gives rise to a complete reasoning procedure for instance checking in $\textit{DL-Lite}_{\cal R}$ with defeasible axioms. Under consideration in Theory and Practice of Logic Programming (TPLP).