Reviewerly/exHarmony huggingface dataset:
Structure and evolution of the Eastern part of the Southwest Indian Ridge

The structure and evolution of eastern part of the Southwest Indian ridge is discussed. Based on geological-geophysical data and cartographic materials, analysis of spatial and temporal changes of ridge morphostructure was performed. Analysis of the data made it possible to recognize the stages of ridge evolution and delineate its sections differing in tectonics, structure, morphostructural segmentation of the rift zone and the ridge flanks. It is shown that crust in the axial zone of the ridge formed under repeatedly changing spreading kinematics, degree of hotspot activity, and underlying mantle along-axis temperatures. The temporal variations in these characteristics along the rift zone are established, with consideration of their influence on its segmentation and tectonic structural features.
Semantic Correlation Based Deep Cross-Modal Hashing For Faster Retrieval

Due to growth of multi-modal data, large amount of data is being generated. Nearest Neighbor (NN) search is used to retrieve information but it suffers when there is high-dimensional data. However Approximate Nearest Neighbor (ANN) is a searching method which is extensively used by the researchers where data is represented in form of binary code using semantic hashing. Such representation reduces the storage cost and retrieval speed. In addition, deep learning has shown good performance in information retrieval which efficiently handle scalability problem. The multi-modal data has different statistical properties so there is a need to have method which finds semantic correlation between them. In this paper, experiment is performed using correlation methods like CCA, KCCA and DCCA on NMIST dataset. NMIST dataset is multi-view dataset and result proves that DCCA outperforms over CCA and KCCA by learning representations with higher correlations. However, due to flexible requirements of users, cross-modal retrieval plays very important role which works across the modalities. Traditional cross-modal hashing techniques are based on the hand-crafted features. So performance is not satisfactory as feature learning and binary code generation is independent process. In addition, traditional cross-modal hashing techniques fail to bridge the heterogeneous gap over various modalities. So many deep-based cross-modal hashing techniques were proposed which improves the performance in comparison with non-deep cross-modal techniques. Inside the paper, we presented a comprehensive survey of hashing techniques which works across the modalities.
Forensics Analysis of Typewriter and Typewritten Documents

This article reviews the forensic examination of the typewriter and typewritten documents. The main purpose of examination is to identify the source or origin of the typewritten documents or the link between two typescripts that can be vital to a court of law. Immense application of the typewriter increased the production of fraudulent documents for deceit. Typewritten documents are examined using scientific methods based on class and individual characteristics. These are physical and chemical methods of observation and comparison.
Editor’s Corner

The coronavirus has disrupted one of the foundations of our democracy—voting. Several states delayed primaries during the shut-downs. Now states are expanding, or hindering, voting options so that citizens may vote safely during this pandemic. Pew Research polled registered voters and found that 63 percent were uncomfortable voting in person because of the coronavirus outbreak. Unfortunately how citizens can vote safely during this time is falling along partisan lines.
Boosted Relief Feature Subset Selection and Heterogeneous Cross Project Defect Prediction using Firefly Particle Swarm Optimization

The exponential growth in the field of information technology, need for quality-based software development is highly demanded. The important factor to be focused during the software development is software defect detection in earlier stages. Failure to detect hidden faults will affect the effectiveness and quality of the software usage and its maintenance. In traditional software defect prediction models, projects with same metrics are involved in prediction process. In recent years, active topic is dealing with Cross Project Defect Prediction (CPDP) to predict defects on software project from other software projects dataset. Still, traditional cross project defect prediction approaches also require common metrics among the dataset of two projects for constructing the defect prediction techniques. Suppose if cross project dataset with different metrics has to be used for defect prediction then these methods become infeasible. To overcome the issues in software defect prediction using Heterogeneous cross projects dataset, this paper introduced a Boosted Relief Feature Subset Selection (BRFSS) to handle the two different projects with Heterogeneous feature sets. BRFSS employs the mapping approach to embed the data from two different domains into a comparable feature space with a lower dimension. Based on the similarity measure the difference among the mapped domains of dataset are used for prediction process. This work used five different software groups with six different datasets to perform heterogeneous cross project defect prediction using firefly particle swarm optimization. To produce optimal defect prediction in the Heterogeneous environment, the knowledge of particle swarm optimization by inducing firefly algorithm. The simulation result is compared with other standard models, the outcome of the result proved the efficiency of the prediction process while using firefly enabled particle swarm optimization.
Three Levels Dwt Watermarking Technique for Color Images and Watermarks

This paper presents a three-levels Discrete Wavelet Transform (DWT) watermarking technique for color images and watermarks. The proposed technique utilizes embedding the RGB watermark information into the Y channel of the YCbCr cover image. A pre-processor is used to convert the color watermark from RGB to a binary sequence. The pre-processed output is, then, inserted several times into the Y channel of the YCbCr cover image by changing the LL3 DWT coefficients. The robustness of the proposed scheme is verified through the ability to resist several classical attacks such as scaling, cropping, JPEG compression, median filtering and low pass filtering. In addition, the proposed scheme does not need the original host image to recover the watermark; hence, the recovery method is blind. This paper also includes a qualitative comparison between the one-level and two-levels DWT.
Using Color and Texture Feature Extraction Technique to Retrieve Image

This paper proposes a content image retrieval using the texture and the color feature of the images. Although for extraction of texture feature, the “gray level co-occurrence matrix (GLCM) algorithm” is used and for extracting color feature the color histogram is used. The presented system is tested on the WANG database that contains a thousand color images with ten different classes by the help of three various type of distances
Приложение на дигиталните технологии в обучението

Application of Digital Technologies in Training Digitization is a set of activities for the transformation of analogue information resources into digital copies using modern digital ICT technologies that respond to global “good” practices. The aim of the paper is to present the capabilities of some of the technologies for the digitization of processes in training - Augmented, Virtual and Mixed Reality. Parameters whose planning is related to conducting effective training are described.
PENINGKATAN KEMAMPUAN MEMBEDAKAN KONSEP BERAT DAN RINGAN MELALUI MEDIA TIMBANGAN KAYU

The purpose of this research is to improve the ability to distinguish the concept of weight and light learners through the medium of wooden scales, improve the quality of distinguishing concepts of weight and light and motivate the interest of learners in understanding the concept of weight and light in children aged 5-6 years even semester 2020 - 2021 through the media of wooden scales. Success indicators: contains success indicators that reference success in each action, in the form of gradations such as 80-100 (very successful), 60-79 (successful), 40-59 (sufficient), 20-39 (less successful), 0-19 (unsuccessful). If the cognitive ability measured by the minimum completion criteria can be used as a reference. Following the characteristics of class action research, the success of this action is characterized by changes in the direction of improvement related to the learning atmosphere and learning outcomes of students. The purpose of implementation in this study is to improve the ability to distinguish the concept of the light weight of children aged 5-6 years through the medium of wooden scales. The criteria for success in this class action research is the improvement of the completion of learning outcomes of children aged 5-6 years PAUD Cerdas Bangsa Jakarta 75% of the number of children and the average overall value of children is 6, then the research can be said to be successful.
Two Dimensional Path Planning with Static Polygon Obstacles Avoidance

This paper presents the designing of path planning system in an environment contains a set of static polygon obstacles localized and distributed randomly by using differential drive mobile robot. In this paper the designed algorithm (two dimensional path planning algorithm) is proposed in order of investigate the path planning of mobile robot with free collision using the visibility binary tree algorithm. The suggested algorithm is compared with the virtual circles tangents algorithm in the time of arrival and the longest of the path to the target. The aim of this paper is to get an algorithm has better performance than the other algorithms and get less time of arrival and shortest path with free collision.
PROMOTING DISTANCE E-LEARNING AND MOBILE LEARNING

It is becoming increasingly clear that the education system of our country is undergoing significant changes. It is gratifying that distance learning is widely used, along with other forms of education. It is no secret that many people use the Internet only to read the news, search for information, use e-mail or sell rumors. The possibilities of the Internet are growing day by day. A new phase of Internet use has begun, which means that the Internet has been introduced in various fields. Internet technologies: distance learning, e-libraries, telemedicine, telemetrology, e-business, e-shops, etc. Below are brief but basic descriptions of these technologies.
Outlier Detection: A Research and Modified Method using Fuzzy Clustering

Data mining is becoming increasingly popular in many application fields. Due to the advancement, Researchers show great interest to find unexpected behaviour over large amount of datasets. Outlier detection is studied extensively in data mining and developed for certain application domains, while others are generic in nature. It is one of the important and hottest topic in research which faces a series of new challenges. It occurs due to change in system behaviour, mechanical fault, human error, natural deviations and instrumental error. The purpose of this paper briefly provides a survey on outlier detection and a modified approach to detect outlier using Fuzzy clustering. Also, it provides a better understanding of different dimensions that applied in various substantive areas.
In the News

Welcome to the February 2020 issue of C&amp;RL News. Leading off the issue, Abigail Goben and Robert J. Sandusky discuss the risks and opportunities of “Open data repositories” in this month’s Scholarly Communication column.
Entropy and Fractals

The resonance stationary state of structural processes takes place under the condition of equality of degrees of corpuscular and wave interactions. The fractal structures are formed under the condition of equilibrium statistic interaction of entropic and negentropic characteristics of all particles.
Secret Image Sharing Scheme Based on Pixel Segmentation Strategy Exploiting Modification Direction (PSSEMD) with High Quality Shadows

Schemes of sharing a secret image are enhanced practically. The secret images are wrapped in cover imageon producing shadow images in this proposed scheme. In sequence,security is attained by means of methods of encryption and decryption while processing of sharing image. In the sharing step, cover image wrapped out the secret image by producing n images of shadow like cover image. This research dedicates a method of Improved Exploiting Modification Direction (IEMD) to conceal confidential data on preserving a high PSNR value. Pixel Segmentation Strategy EMD (PSSEMD) Method is used for wrapping confidential bit on all pixel cover image. the images as secret and cover are rebuilt by Shadow images. Lossless recovery of secret image is enriched by rebuilding the confidential image with lossless whereas by compressing the image before encryption and watermarking. Here Lossless image compression is done with the concern of sensitive information. Then chaotic encryption and decryption method is used for better security during image sharing process. Hence better embedding capacity and better quality in visual are attained in this proposed research results ensuring high security results in term of higher PSNR, lower MSE and higher correlation than the existing methods.
The most prevalent obstacles on the way of constructing effective teachers-students interaction and the reasons of their emersion

The possible problems of teachers-students pedagogical interaction are studied in the article.The inextricable link between pedagogical interaction and pedagogical communication, which is a part of the complex process of modern educational development, is underlined.The pedagogical heritage of the American scientist Thomas Gordon is explored, namely: his views concerning the main obstacles on the way of building effective pedagogical interaction, and the potential opportunities for overcoming them.
Publicly verifiable function secret sharing

Function secret sharing (FSS) allows a dealer to split a secret function into n sub-functions, described by n evaluation keys, such that only a combination of all of these keys could reconstruct the secret function. However, it is impossible to recover the secret correctly if there exist some sharers deviating from intended behaviours. To settle this problem, we propose a new primitive called publicly verifiable function secret sharing (PVFSS), in which any client could verify the validity of secret in constant time. Furthermore, we define three important properties: public delegation, public verification and high efficiency, which are an essential part of our scheme. Finally, we construct a PVFSS scheme for point function then we prove its security and make performance analysis in two major directions: key length and algorithm efficiency. The analysis validates that our proposed scheme is asymptotic to FSS. It would be applicable to cloud computing.
Preface

The International Scientific Conference on Electronic Devices and Control Systems (EDCS-2019) was held at Tomsk State University of Control Systems and Radioelectronics, Tomsk Russia, on November 20–22, 2019, bringing together representatives of some of the best high-tech universities, institutions, and companies. EDCS-2019 is aimed at providing platform to exchange information on advanced R&amp;D deliverables in priority fields, as well as discussing issues of modern radio electronics, theory and practice of control systems, Information security, etc., presenting new devices, engineering solutions, software and systems, and bringing together academic research and industry for development of high-tech products. EDCS-2019 covers a wide range of topics related to Radio engineering; Microwave nanoelectronics; Nanotechnology in electronics; Antennas and microwave devices; Control devices and methods; Optoelectronics and photonics; Plasma electronics; Nonlinear optics; Intelligent control systems; Information security; Information technologies in management and decision-making; Video information technologies and digital television; Robotics and mechatronics; Mathematical modeling in physical and engineering sciences. The conference was organized with the support of Ministry of Science and Higher Education of the Russian Federation, Tomsk State University of Control Systems and Radioelectronics, Administration of Tomsk region, Administration of Tomsk, Tomsk group and student branch of the IEEE, TUSUR Research Institute of Automatics and Electromechanics, Information Satellite Systems Reshetnev, Micran, Milandr, Keysight Technologies, National Instruments. Prof. Alexandre A. Shelupanov, Chair of EDCS-2019 Organizing Committee Rector of TUSUR University, Director of Institute of System Integration and Security, Chairman of Tomsk Professorate Assembly, Doctor of Engineering, Professor
Architecture Evaluation of Mobile Application: Whatsapp

Software become an unavoidable in every once life. Quality of the software is an import aspect in the software development life cycle. Quality for a software is represented in terms of functional and non-functional requirement. Software architecture is used to represent the using set of components and is connectivity as a relationship between these components. To assure the development process meet the requirement given by the user, the Software Evaluation is used. Early detection of error protect the software development producing the defect software. ATAM is the one of the method used to detect the risk, non-risk, scenarios and tradeoff in the earlier stage of development life cycle. Here in this paper security scenarios for mobile application has been elicited and compared with the scenarios extracted from the whatsapp application. Comparison shows few scenarios need to added with existing scenarios in order to improve / ensure full security for the metadata.
INFORMATION SYSTEMS OF TICKETING BUS BY ONLINE BASED ON WEB ON PO SINAR JAYA

Abstract PO Sinar Jaya is one of transportation provider companies that still develop and not yet usinginternet technology as services development to customers, the problem is they can’t see theschedule total remainder ticket directly, and company can’t give direct information to thecustomer. Systems development methods used is waterfall, waterfall consists of some stage the flowof activity that walked in one direction from the start to finish system develop project, start fromanalysis, design, code, trial, and supporting stage. According to observation that be held in POSinar Jaya Cibitung obtained complete information about procedure order the ticket during thetime, so can give the solution to information system planning order ticket bus by online. With theinformation ordering ticket bus using online system expected can help ordering ticket bus activitiesand can to increase sale volume, increase the service quality and company’s image.
Dissemination of Biomedical Cell Sheets using Reality Technology and Digital Tools

Nowadays, with the advance of biomedical and pharmaceutical technology, new treatments such as cell therapy, cell sheets, etc. all provide patients other alternatives. However, the public has little knowledge in these new technologies and they also find them difficult to understand. Hence, this paper is aimed at providing the public with state-of-the-art technological knowledge and constructing an innovative field full of diversity, entertainment, and educational meaning with the assistance of Augmented Reality (AR) and Virtual Reality (VR). Taking the cell sheets technology, a kind of cell therapy recently approved in Taiwan, as an example, we built an AR platform, and demonstrated a trailer animation, 2D animation and 3D model animation via Merge Cube. The trailer animation will portrait how the main character helps her friend, who became physically challenged in an accident, stand up again by asking a genius doctor to perform cell sheet technology. The 2D animation will be used to explain how cell sheet works and its application, while the 3D animation helps demonstrate the DNA reproduction and cell division in cell therapy. A VR field will also be set up so that players can play as the genius doctor, fight their way through the VR games, and learn more about cell sheet technology. To let the public learn more about this biotechnology knowledge, we held an exhibition to display the research results, providing them a whole new learning experience.
A Smart Home Monitoring System for Abnormal Human Activity Detection using CNN

Demonstrating human practices and movement designs for acknowledgment or location of exceptional occasion has pulled in noteworthy research enthusiasm for late years. Differing strategies that are flourish for structure smart vision frameworks went for scene comprehension and making right semantic derivation from the watched elements of moving targets. Most applications are in reconnaissance, video content recovery, and human PC interfaces. In this propose a novel strategy for irregular human action recognition in jam-packed scenes/Home. In particular, as opposed to recognizing or fragmenting people, we formulated a productive technique, called a movement impact map, for speaking to human exercises. The key element of the proposed movement impact guide is that it viably mirrors the movement qualities of the development speed, development bearing, and size of the items or subjects and their communications inside an edge succession. In this propose System developing using CNN.
Machine Learning for Data Integration in Cancer Precision Medicine: Matrix Factorization Approaches

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A cross-disciplinary investigation of multi-word expressions in the moves of research article abstracts

© 2018 Elsevier Ltd Conformity to the epistemological orientations of academic disciplines is often reflected in the ways in which knowledge is constructed and communicated through certain linguistic features in academic genres. This paper explores instances of such conformity in hard and soft science disciplines, as it is reflected in the use of recurrent word combinations in different rhetorical moves of research article abstracts. A corpus-driven approach was adopted to identify the most frequently occurring word combinations of different length in a corpus of 5910 abstracts from six disciplines. Following this, the identified sequences were classified according to their communicative functions in different moves of the abstract. A mixed-methods approach was then adopted through which the patterns of variation reflected in the use of the identified sequences were examined both quantitatively and qualitatively. It was found that members of different academic domains have different priorities for representing their research in academic abstracts.
CONNEKT: Co-Located Nearest Neighbor Search using KNN Querying with K-D Tree

Data about entities or objects associated with geographical or location information could be called as spatial data. Spatial data helps in identifying and positioning anyone or anything globally anywhere across the world. Instances of various spatial features that are closely found together are called as spatial co-located patterns. So far, the spatial co-located patterns have been used only for knowledge discovery process but it would serve a wide variety of applications if analyzed intensively. One such application is to use co-location pattern mining for a context aware based search. Hence the main aim of this work is to extend the K-Nearest Neighbor (KNN) querying to co-located instances for context aware based querying or location-based services (LBS). For the above-said purpose, co-located nearest neighbor search algorithm namely “CONNEKT” is proposed. The co-located instances are mapped onto a K-dimensional tree (K-d tree) inorder to make the querying process efficient. The algorithm is analyzed using a hypothetical data set generated through QGIS.