Reviewerly/exHarmony huggingface dataset:
Differential evolution with dynamic neighbourhood learning strategy-based mutation operators

As the core operator of differential evolution (DE), mutation is crucial for guiding the search. However, in most DE algorithms, the parents in the mutation operator are randomly selected from the current population, which may lead to DE being slow to exploit solutions when facing complex problems. In this study, a dynamic neighbourhood learning (DNL) strategy is proposed for DE to alleviate this drawback. The new proposed DE framework is named DE with DNL-based mutation operators (DNL-DE). Unlike the original DE algorithms, DNL-DE uses DNL to dynamically construct neighbourhood for each individual during the evolutionary process and intelligently select parents for mutation from the defined neighbourhood. In this way, the neighbourhood information can be effectively utilised to improve the performance of DE. Furthermore, two instantiations of DNL-DE with different parent selection methods are presented. To evaluate the effectiveness of the proposed algorithm, DNL-DE is applied to the original DE algorithms, as well as several advanced DE variants. The experimental results demonstrate the high performance of DNL-DE when compared with other DE algorithms.
Analysis of Convolution Neural Network Architectures and Their Applications in Industry 4.0

Convolution neural networks (CNNs) have shown extraordinary performance in the fields of computer vision and image processing. This is because the incredible ability of CNNs to automatically learn feature representation for a particular domain has given them an edge over the traditional computer vision methodologies, which heavily depended on human annotations for feature extraction. The shift of focus from traditional methods to CNN-based methodology has resulted in immense architectural innovations over the course of time. Choosing a proper CNN architecture is an extremely vital step towards solving a critical problem. We have done a thorough literature survey of various CNN architectures developed over time. This chapter acts as a convenient and comprehensive solution for CNN advancements over time, the major architectural improvements in each architecture, and what improvements they brought. Such innovations have enabled a smooth transition into Industry 4.0, which is heavily dependent on task automation through deep learning and computer vision. In this chapter, we have covered major CNN architectural innovations, a brief description about their constituent blocks, structural description, and limitations, and provided use cases that pertain to Industry 4.0.
An Novel Framework For Content Based Image Retrieval With Quality Assessment System using Optimal Deep Convolution Neural Network

Content based image retrieval (CBIR) models become popular for retrieving images connected to the query image (QI) from massive dataset. Feature extraction process in CBIR plays a vital role as it affects the system’s performance. This paper is focused on the design of deep learning (DL) model for feature extraction based CBIR model. The presented model utilizes a ResNet50 with co-occurrence matrix (RCM) model for CBIR. Here, the ResNet50 model is applied for feature extraction of the QI. Then, the extracted features are placed in the feature repository as a feature vector. The RCM model computes the feature vector for every input image and compares it with the features present in the repository. Then, the images with maximum resemblance will be retrieved from the dataset. In addition, the resemblance between the feature vectors is determined by the use of co-occurrence matrix subtraction process. Besides, structural similarity (SSIM) measure is applied for the validation of the similarity among the images. A comprehensive results analysis takes place by the use of Corel 10K dataset. The experimental outcome indicated the superiority of the RCM model with respect to precision, recall and SSIM.
Parsing and Creating XML Documents with DOM

SAX can parse XML documents but cannot create them. In contrast, DOM can parse and create XML documents. Chapter 3 introduces you to DOM.
Open Street Map for crime and place

This chapter provides a framework to approach and meaningfully interpret open data. The chapter also offers a practical hands-on guide to demonstrate how to access, wrangle, and analyse different sources of open data in R in order to draw conclusions about crime and place.
Classification of histogram-valued data with support histogram machines

The current large amounts of data and advanced technologies have produced new types of complex data, such as histogram-valued data. The paper focuses on classification problems when predictors are observed as or aggregated into histograms. Because conventional classification methods take vectors as input, a natural approach converts histograms into vector-valued data using summary values, such as the mean or median. However, this approach forgoes the distributional information available in histograms. To address this issue, we propose a margin-based classifier called support histogram machine (SHM) for histogram-valued data. We adopt the support vector machine framework and the Wasserstein-Kantorovich metric to measure distances between histograms. The proposed optimization problem is solved by a dual approach. We then test the proposed SHM via simulated and real examples and demonstrate its superior performance to summary-value-based methods.
Digital Forensics: Where Are We?

Digital Foensics is a branch of Forensic Sciences that involves the recovery of materials in digital devices, e.g. computers, mobile phones and storage devices. Fast and continuous advances in digital techniques and devices are happening. On the other hand, the forensic tools to track these technologies are short lagged. This mini-review discusses the issue and its consequences and recommendations for covering the gap between the two.
Protected Health Care Application In Cloud using Ciphertext-Policy Attribute-Based Encryption And Hierarchical Attribute-Based Encryption

Cloud computing is becoming an emerging paradigm to tenuously store and Share the data for users. A personal health record (PHR) could be a health record during which the patient keeps health data and other information associated with the patient's care. There is a great challenge of privacy and confidentiality once patient shares their records of the commercial cloud servers, that results in less secure. In view of the above, this paper proposes a technique which combines attribute based access control model with an expansion of ciphertext-policy attribute-set-based encryption (ASBE) and Hierarchical Attribute-based Encryption allows to store the sanitized data securely in the cloud system and also the original data may be retrieved from the sanitized data with the help of the key provided by the data owner. The experimentation is carried out on the data sets and it provides superior performance efficient and accurate results. PHR system categorizes the users to multi security domains so as to scale back key management quality.
2018 4th International Conference on Environmental Science and Material Application

The organizing committee of ESMA 2018 is proud to present the proceedings of the 2018 4th International Conference on Environmental Science and Material Application (ESMA 2018: http://www.icesma.org/), held in Xi'an, China from 15 to 16 December, 2018. We warmly welcome prospected authors submit new research papers to ESMA 2018, and share the valuable experiences with the scientist and scholars around the world.
An Efficient Hardware Implementation of Finite Field Inversion for Elliptic Curve Cryptography

The modular inversion operation is an essential hardware design for computing speed when we use it in cryptography applications. Through this work, we present a FSM based design methodology to achieve speed, area and high-performance modular binary inversion algorithm over 256-bit prime field. The proposed architecture implemented using Xilinx Virtex-7 FPGA device, it achieves 37% reduction in area-delay product and 15% and 16% of improvement in speed and throughput respectively, when compared with existing designs. Also, ASIC based implementation is done using TSMC 65nm CMOS technology, the synthesis results achieved the maximum operating clock frequency is 833 MHz and throughput of 626Mbps, which makes it suitable for speed-critical cryptoapplications.
Reduction o f Time f or Speech Recognition System b y Shrinking Adaptive Layer s o f ADAG f or Real Time System u sing ADAT SVM

Recently speech recognition becomes very major area for large vocabulary real time applications. In the existing work research was formulated for large number of words spoken by same speaker using Adaptive Directed Acyclic Graph (ADAG) with support vector machines. In today’s era the emphasis is given to processing large vocabulary data process and recognition. In existing system, when spoken words are recognizing by number of adaptive layers causes increase in testing time for recognition of data occur. The aim of the proposed Reduced Adaptive Directed Acyclic technique (RADAT) is to develop a system to recognize test word in less amount of time than existing System [1]. In our current system it is possible to remove unnecessary finding distance of test word with number of times with training word. The proposed RADAT system handles this by applying reduction in number of adaptive layers to recognize any testing word and which result reduction in time. The experiment results of current system reduce time complexity without loss of recognition accuracy for any data of speaker dependent system. The results are obtained for various dataset like large vocabulary speech record as well for small size data to large vocabulary dataset. In our paper we use same feature extracted samples for training and testing. This method is work for various speech dataset like machine operation command in English or required language to operate computer system in real time application as well applied for offline application such as start, logoff, login, notepad, open, close, shutdown etc [5].
Fire Detection System Using Android-Based Microcontroller

The Fire Detection System can be supported by Internet of Things technology, e.g. a Microcontroller device which is used to control the related devices. In this study, android-Based fire detection system was designed in which the house owner can always monitor the condition of the house all the times and accessing the information about their house when a fire occurs until the fire suppression process is complete. Information of the house condition will be displayed on the Blynk application which is located in the kitchen area and is connected to several supporting sensors. The design of a Fire Detection System Using an Android-Based Microcontroller is divided into several stages, namely: (1) Requirement Identification; (2) Requirement Analysis;(3) Hardware Design; (4) The software design (Arduino IDE 1.8.5 and Blynk). The testing results showed that the android-based Fire Detection System Using Microcontroller was able to provide information to residents of the house in the real-time.
On the conceptual and terminological apparatus of didactics within the digital age.

The article is devoted to the up-to-date issue on how to develop the conceptual and terminological apparatus of higher education didactics. The purpose of the article is clarify the interpretation of new terms and concepts (digitalization of education, digital education, digital learning, digital didactics, blended learning, etc.), the emergence of which is due to the era of education digitalization. As a research method, the authors used a theoretical analysis of the conceptual and terminological apparatus of didactics, generalization, comparison, interpretation. The research results are as follows: 1) the concepts "digitalization of education", "digitalization of the education system" and "digital learning" are given; 2) authors determined their place in the system of closely established terms and concepts; 3) they made a conclusion about the boundaries in using the term “digital pedagogy” and “digital didactics”; 4) the identified the main features, the role and place of the concept of "blended learning" in the system of didactic knowledge. The research results contribute to the development of the conceptual and terminological apparatus of didactics. They can be useful both for educational researchers and for practicing educators, as they clarify a whole range of new terms and concepts
A word-frequency-preserving steganographic method based on synonym substitution

Text steganography is a widely used technique to protect communication privacy yet it suffers from a variety challenges. One of these challenge is synonym substitution-based method, which may change the statistical characteristics of the content. For example, the word frequency may be changed, which may be easily detected by steganalysis. In order to overcome this disadvantage, this paper proposes a synonym substitution-based steganographic method taking the word frequency into account. This method dynamically divides the synonyms appearing in the text into groups, and substitutes some synonyms to alter the positions of the relative low frequency synonyms in each group to encode the secret information. By maintaining the number of relative low frequency synonyms across the substitutions, it preserves some characteristics of the synonyms with various frequencies in the stego and the original cover texts. The experimental results illustrate that the proposed method can effectively resist the attack from the detection using relative frequency analysis of synonyms.
Predictive structure or paradigm size? Investigating the effects of i-complexity and e-complexity on the learnability of morphological systems

Research on cross-linguistic differences in morphological paradigms reveals a wide range of variation on many dimensions, including the number of categories expressed, the number of unique forms, and the number of inflectional classes. However, in an influential paper, Ackerman &amp;amp; Malouf (2013) argue that there is one dimension on which languages do not differ widely: in predictive structure. Predictive structure in a paradigm describes the extent to which forms predict each other, called i-complexity. Ackerman &amp;amp; Malouf (2013) show that although languages differ according to measure of surface paradigm complexity, called e-complexity, they tend to have low i-complexity. They conclude that morphological paradigms have evolved under a pressure for low i-complexity, such that even paradigms with very high e-complexity are relatively easy to learn so long as they have low i-complexity. While this would potentially explain why languages are able to maintain large paradigms, recent work by Johnson et al. (submitted) suggests that both neural networks and human learners may actually be more sensitive to e-complexity than i-complexity. Here we will build on this work, reporting a series of experiments under more realistic learning conditions which confirm that indeed, across a range of paradigms that vary in either e- or i-complexity, neural networks (LSTMs) are sensitive to both, but show a larger effect of e-complexity (and other measures associated with size and diversity of forms). In human learners, we fail to find any effect of i-complexity at all. Further, analysis of a large number of randomly generated paradigms show that e- and i-complexity are negatively correlated: paradigms with high e-complexity necessarily show low i-complexity. These findings suggest that the observations made by Ackerman &amp;amp; Malouf (2013) for natural language paradigms may stem from the nature of these measures rather than learning pressures specially attuned to i-complexity.
Preface Annual Conference on Computer Science and Engineering Technology (AC2SET) 2020

Forum Kerjasama Pendidikan Tinggi, Sekolah Tinggi Ilmu Manajemen Sukma, Universitas Budi Darma organized Workshop scientific writing in conjunction with Annual Conference on Computer Science and Engineering Technology (AC2SET) 2020 on 23 September 2020 in Medan, North Sumatera, Indonesia. The AC2SET 2020 is a part of FKPT conference that aims to exchange knowledge and research finding among academicians, researchers, professionals, policy makers, and postgraduate students. The Awareness to increase the number of publications on the results of research that has been done, deserves appreciation by all parties. Because of that, Forum Kerjasama Pendidikan Tinggi provide motivation and space for researcher to disseminate their research and accommodate the result of research that has been done. Annual Conference on Computer Science and Engineering Technology (AC2SET) 2020 , is another International Conference held by Forum Kerjasama Pendidikan Tinggi. AC2SET 2020 was chosen to be implemented virtually, this is because the cov-19 pandemic is still spreading. The conference was perform using zoom. The AC2SET 2020 event is virtually implemented with a model that all invited speakers are given time to present their material for 30 minutes every invited speaker and after that a question and answer is carried out with the participants with a direct questioning system, through chat forums and Q&amp;A forums provided by the zoom application. Overall, the conference took 4.5 hours the number of participants who joined the zoom room was recorded at 491 participants. Participants came from 13 countries, namely Indonesia, Malaysia, Iraq, Vietnam, Thailand, Morocco, India, Iran, Philippine, Ghana, Oman, Nigeria, UAE. Participants from Indonesia came from 14 Provinces from 33 Provinces. List of Organizing Committee and Editors are available in this pdf.
Societal Pressures, Safety, and Online Labeling - Investigating LGBTQ Self-Identification in an Online Space

When and how to come out are difficult choices. In this research, we examine one form of disclosure: the inclusion of an LGBTQ keyword in one's online social media profile. We construct daily time series of the prevalence of American Twitter users whose self-descriptions contain LGBTQ keywords. Further, we construct daily time series of inferred Add and Delete events - i.e. we make best estimates for how many users per day make an edit to include a previously absent word or remove a word previously present. These we compare to relevant annual and one-time events such as LGBTQ Pride Month and the date of the Pulse Nightclub shooting. We confirm two pre-registered hypotheses and explore several others.
Refinement

As a technical term in Computer Science, “refinement” is understood as a relation between systems (programs, channels. . . ) that, in its most austere form, is simply preservation of properties.
SPECIFICS OF CREATIVE ACTIVITY OF A TEACHER-PSYCHOLOGIST IN THE CONDITIONS OF INTEGRATED TRAINING

The article presents the features of psychological and pedagogical support in the conditions of integrated learning. The role of a teacher - psychologist in the design and organization of psychological and pedagogical support of the educational process is considered. The main directions of psychological and pedagogical support for the development of professional competence of a teacher, the specifics of his creative activity are formulated. The main conditions for the effectiveness of programs of psychological and pedagogical support are considered. At the present stage of development in the Republic of Kazakhstan, there are deep socio-economic transformations that require new approaches to the system of vocational education. The First President of the Republic of Kazakhstan Elbasy N. A. Nazarbayev pays attention to the development of science and education in the program "100 concrete steps" in five institutional reforms. Special emphasis is placed on improving the competitiveness of graduates and the growth of the educational sector. The article considers the theoretical features of the priority tasks of higher education, strengthening the resource base, expanding the practical component of scientific and educational activities, investments in the preservation and development of human capital, which is the main priority of the State program for the development of education of the Republic of Kazakhstan for 2011 – 2020. The paper describes the need for specialists who can productively organize interaction and relationship in the "person-to-person" system. In these conditions, the problems of training specialists in the so-called "helping professions" (psychologists, social workers, etc.) become urgent. The article describes the current socio-economic situation in Kazakhstan, which also determines the order for specialists of this profile who have the qualities and skills of activity in this field, which requires the modernization of training students in the relevant specialties of the higher education system. Both domestic and foreign experts are increasingly calling the XXI century the century of "man". The article considers that in modern socio-economic conditions, the problem of developing creative abilities remains one of the most important problems of human society. It is particularly relevant in modern society, because education as a resource of science, technology and art is undergoing radical changes today, due to the need for continuous adaptation to rapidly changing dynamic socio-economic conditions. In addition, the paper describes the fact that this is due to the constantly increasing volume of information, which is forced to operate a modern specialist in any field, and the process of integrating the Sciences, which requires a person not only extensive knowledge, but also a higher creative level of thinking development.
Patrick Wilson

During 1965-2001, Patrick Wilson brought the acuity of a professional philosopher to library and information science (LIS) and became a major theorist in many aspects of knowledge organization (KO). This article, an extensive critical introduction to his thought, reflects the view that much of his work is of permanent value. He can be read for well-informed critiques of the instruments by which writings are organized for retrieval-the bibliographical side of KO. He can also be read for shrewd accounts of personal knowledge and behavior with respect to societal information systems-the social-epistemological side of KO. Indeed, in his work the two sides converge. One of his themes is the preferability of human consultants over bibliographies and catalogs for answering questions. He thus writes at length about the social organization of possible consultants and their degrees of cognitive authority in communicating what they know. Another theme is the desirability of indexing writings not only by subject but also by their possible utility in helping individuals. For that, however, he saw little hope. A third theme is ideal information systems. Broadly, he can be read for his clarifications of concepts on both sides of KO, such as bibliographical control, relevance, subject indeterminacy, information needs, information overload, librarians’ roles, and LIS as a field.