Reviewerly/exHarmony huggingface dataset:
Boolean Based Mining Algorithm for Pattern Discovery Based on Human Interaction

Mining is a process that provides useful information on surfing and access pattern information based on capturing the behaviour of the user. Semantic knowledge helps to understand how the users will interact with the system. In this paper, we propose a Boolean based APriori Pattern (APP) algorithm to discover pattern based on human interaction using behavioural analysis. In the process of data mining, we have used a Boolean expression that helps to determine the pattern discovery based on the use of frequent pattern by applying association rules. The behavioural analysis is proposed based on the classification of ideas based on comments concerning positive opinion /contrary opinion during human interaction in the practical scenarios. The behavioural analysis is represented as a tree hierarchy where tree based mining is performed by the tree construction and interaction of flow patterns i.e., frequent patterns. The study shows that the successful pattern can be extracted based on the behavioural analysis of human interaction such as frequent pattern, flow interaction and relationships between the interactions.
Exploration of overlapped endogenous mineralization on the basis of paleovolcanic reconstructions

By these days issues of survey of blind and covered deposits are very actual. High affectivity of geological and prospecting abilities could be achieved only when complex studies have been done which allow to indicate structural elements of explores area and evaluate geological and geochemical potential of prospective areas. In the article the structural and geochemical criterion developed by authors is considered. Its use is preceded by definition of the structural and geological characteristic of the territory based on the method of paleovolcanic reconstruction. At the later stage areas, perspective for detection of an ore mineralization are outlined basing on localization of various type of a mineralization at specified structural units of paleovolcanic structures. Application of geochemical mapping within the perspective areas allows to estimate prospects of the areas, to allocate most perspective sites with their preliminary geochemical estimate.
Lightning Insurance: A Fast Claim, High Accuracy Insurance Platform Based on Blockchain Technology and NASNET Algorithm

Insurance is a financial instrument with a long histo-ry and conducive to social development. With the modernization process, centralized insurance companies gradually replaced mu-tual insurance, completing insurance design, insurance sales, and claims review. A large number of cases of fraudulent insurance and insurance companies delaying the application of reasonable claims, resulting in the buyer&#x0027;s distrust of the insurance company and the insurance company&#x0027;s distrust of the purchaser. Through blockchain and deep learning, this paper constructs an insurance business alliance, which links the mature and stable intelligent, discriminating scenarios into the entire insurance system, thus reducing the long redundant nuclear insurance process to the scope of machine identification and minute-level insurance. At the same time, a number of underwriting companies combined through blockchains can achieve very high accuracy rates with limited algorithm accuracy. It enhances the user experience of claimants who are in urgent need of financial assistance, thereby significantly enhancing user trust, in order to increase people&#x0027;s trust in insurance products from a macro perspective, and thus promote the popularization of insurance in China.
Practical Implementation Of The International Society For Engineering Pedagogy Curriculum In Russia

The new IGIP (International Society for Engineering Pedagogy) Curriculum was approved in 2020. It is intended for training of engineering disciplines teachers in higher education institutions. The authors present their point of view on implementing practice of the IGIP Curriculum in Russia. The article on this topic published in January 2021 includes the translation of this curriculum into Russian, and discusses various points of view on it. In the present paper, the authors consider in detail the content of the first two modules of the IGIP Curriculum in connection with the specifics of its implementation in Russia. The current situation in higher education systems in different countries is taken into account. The first module is devoted to the general problems of engineering education discussed in the world community. Its implementation aimed at the expanding general outlook of trainees and allows one to form his/her basic competencies. The second module represents the core of the IGIP Curriculum, since it sets out the didactics and the basic methods of teaching of engineering disciplines. In this regard, the module pays special attention to the modern educational technologies. This is especially true for the use of the information and communication technologies. The importance of such technologies significantly increased over the last year, when the transition to distance learning was forced. Therefore, the accumulated experience of teaching in the distance form is discussed.
Deep Learning Approaches for Speech Analysis: A Critical Insight

The main objective of speaker recognition is to identify the voice of an authenticated and authorized individual by extracting features from their voices. The number of published techniques for speaker recognition algorithms is text-dependent. On the other hand, text-independent speech recognition appears to be more advantageous since the user can freely interact with the system. Several scholars have suggested a variety of strategies for detecting speakers, although these systems were difficult and inaccurate. Relying on WOA and Bi-LSTM, this research suggested a text-independent speaker identification algorithm. In presence of various degradation and voice effects, the sample signals were obtained from a available dataset. Following that, MFCC features are extracted from these signals, but only the most important characteristics are chosen from the available features by utilizing WOA to build a single feature set. The Bi-LSTM network receives this feature set and uses it for training and testing. In the MATLAB simulation software, the proposed model’s performance is assessed and compared to that of the standard model. Various dependent factors, like accuracy, sensitivity, specificity, precision, recall, and Fscore, were used to calculate the simulated outputs. The findings showed that the suggested model is more efficient and precise at recognizing speaker voices.
Micro-architectural attacks and countermeasures on public-key implementations

Microarchitectural timing channels expose hidden hardware state though timing. We survey recent attacks that exploit microarchitectural features in shared hardware, especially as they are relevant for cloud computing. We classify types of attacks according to a taxonomy of the shared resources leveraged for such attacks. Moreover, we take a detailed look at attacks used against shared caches. We survey existing countermeasures. We finally discuss trends in the attacks, challenges to combating them, and future directions, especially with respect to hardware support.
Quantum security of AES-128 under HHL algorithm

There have been a lot of researches about algebric analysis of AES. In this paper, we turned to quantum algorithm to analyze security of AES-128 against the modified HHL algorithm, which is a quantum algorithm used to get classical solutions of multivariate equation system. We constructed two types of equation systems of AES, and solved them with several variants of HHL algorithms respectively. The resulting complexities involved the condition number are given. We analyzed the reasons for the different complexity of the two equation systems and their solution methods, and pointed out that the combination of the boolean equation system and (the improved) BoolSol is more threatening to AES. With a lower bound on the condition number presented by Ding et al., we show that, for AES-128, HHL algorithm is difficult to achieve better attack effect than Grover algorithm. Our results have some enlightening significance for analyzing the post-quantum security of AES-like block ciphers.
Anomaly Detection Method for a Local Area Network

This paper shows the development of an anomaly detection method for a local area network. This research work aims to use an unsupervised machine learning algorithm that integrates different network management tools for anomaly detection. The experiment includes the description of three essential modules: variable definition and protocol configuration, network monitoring and data collection, and fault prediction. SNMP, ICMP, and WMI communication protocols were selected to collect information about the current state of the network, and variables such as latency, packet loss, availability, traffic volume, and speed were defined. The network was polled by temperature sensors, CPU consumption, memory consumption. Network probing was done through the PRTG network monitor and access to the collected data was done through APIs, which were formatted to a template with the structure corresponding to the defined variables. In addition, a method was developed using an unsupervised machine learning algorithm in Python. The tools used for the development of this research were PRTG, Python, Pycaret Library, Collaboratory, Power BI for monitoring, development, and simulation respectively. For the analysis of the model efficiency, the parameters of accuracy (Accuracy), area under the curve (AUC), completeness (Recall), precision (Prec), F-value (F1-score), Matthews correlation coefficient (MMC) were used. The model was implemented through the Power BI tool. It was obtained as a result of measurements and simulation in different scenarios that the implementation of an anomaly detection method reduces degradation, improving the quality and availability of services offered in a local area network.
A Novel Test Scheme for Crossly-polarized Electromagnetic Wave Based on Pseudo-random Codes

With the fast growth of 5G communication, researchers have paid a lot of attention to crossly-polarized scalable channels. However, microwave anechoic chamber is almost an indispensable condition to conduct the simulation test comparisons experiment currently. In the current simulation test comparisons, the advantages of applying cross polarization from the whole system’s point of view is rarely verified. Therefore, we propose a novel test scheme for crossly-polarized electromagnetic wave based on pseudo-random codes, which concludes a pseudorandom code generation algorithm based on parallel Hash function, which makes it possible to generate pseudo-random code of specific length and an inimitable structure effectively. Multiple actual measurements are conducted in indoor and outdoor environments, and we find the scheme presented in the paper can get satisfactory results without the environment of microwave anechoic chamber, which gives a solution to the traditional method’s voracious demand of microwave anechoic chamber.
A Deep Insight in Challenges of Natural Language Processing and Usage of Deep Learning

Natural Language Processing (NLP) using the power of artificial intelligence has empowered the understanding of the language used by human. It has also enhanced the effectiveness of the communication between human and computers. The complexity and diversity of the huge datasets have raised the requirement for automatic analysis of the linguistic data by using data-driven approaches. The performance of the data-driven approaches is improved after the usage of different deep learning techniques in various application areas of NLP like Automatic Speech Recognition, POS tagging etc. The paper addresses the challenges faced in NLP and the use of deep learning techniques in different application areas of NLP.
Quotients of Bounded Natural Functors

The functorial structure of type constructors is the foundation for many definition and proof principles in higher-order logic (HOL). For example, inductive and coinductive datatypes can be built modularly from bounded natural functors (BNFs), a class of well-behaved type constructors. Composition, fixpoints, and, under certain conditions, subtypes are known to preserve the BNF structure. In this article, we tackle the preservation question for quotients, the last important principle for introducing new types in HOL. We identify sufficient conditions under which a quotient inherits the BNF structure from its underlying type. Surprisingly, lifting the structure in the obvious manner fails for some quotients, a problem that also affects the quotients of polynomial functors used in the Lean proof assistant. We provide a strictly more general lifting scheme that supports such problematic quotients. We extend the Isabelle/HOL proof assistant with a command that automates the registration of a quotient type as a BNF, reducing the proof burden on the user from the full set of BNF axioms to our inheritance conditions. We demonstrate the command's usefulness through several case studies.
Professional And Personal Development Of Teachers As Vital Resource In Changing World

The paper examines the content of self-development in the light of professional and personal development of teachers. In the modern, dynamically changing world, professional and personal development of teachers is updated with a vengeance. Not being able to change and change one’s activities following the development of technologies, information and digital means, economic and political transformations, teachers become not just ineffective, but feel fatigue and go through a professional crisis. The way transformations impact human life and health has been studied earlier in sociological sciences, proving the destructiveness of many ongoing changes. However, it is in the field of education that all social changes are most painful, and the teacher, becoming the epicenter of these changes, experiences their influence most acutely. Considering professional and personal development not only as a state task of improving competences of teaching staff, but also as a personal task of promoting one’s life resources and one’s self-efficacy, it is necessary to establish those mechanisms that trigger, initiate and ensure this process. The first step in solving this task is to figure out whether a determinant process is development or self-development. The paper aims to understand the content of both concepts and find out, through psychological and pedagogical sources, the mechanisms of self-development.
A comparative study and performance analysis of multirelational classification algorithms

Classification is one of the important tasks in data mining in which a model is generated-based on training dataset and that model is used to predict class label of unknown dataset. Many propositional classification algorithms exist to build accurate and scalable classifiers, applied to single table dataset only. Most real-world data are structured and stored in relational format and single table classification algorithms that cannot deal directly with relational data. Hence, the need for a multirelational classification algorithm that learns relational data and predicts class labels for relational tuple arises. For relational classification, various techniques are available that include flattening relational data, upgrading existing algorithm, and multiview learning. This paper presents comparative analysis of these techniques and algorithms in detail and shows that multiview-based algorithms outperform other algorithms. By implementing multiview-based algorithms it demonstrated that these algorithms achieve higher accuracy for binary class classification than multiclass classification.
Randa Abdel Salam Saad Belal A Gamification-Based Program to Enhance English Vocabulary Learning and Retention among Kindergartners

The current research investigated the effect of using a gamification-based program on enhancing English vocabulary learning and retention among kindergartners.The research participants were 60 kindergartners.They were divided into two main groups: experimental and control.30 participants of the experimental group were taught using the gamification-based program while the control group participants received regular instruction.The instruments of the research were a checklist of EFL vocabulary learning aspects and sub-aspects and an EFL vocabulary learning test.It also was used as a delayed-post test.Having administering the research instruments, the present research findings revealed that the gamification-based program proved to have a positive effect on enhancing English vocabulary learning and retention among kindergartners.
Preface

The 1 st International Conference on Science and Technology for Sustainable Industry (ICSTSI) is organized as a collaboration between The Institution of Research and Standardization of Industry Banjarbaru (Balai Riset dan Standardisasi Industri Banjarbaru) and The Chemistry Department of Lambung Mangkurat University. The theme of this conference is “Emerging Science and Technology as a Solution for Global Challenge on Research and Technology Based on Sustainable Resources” . Sustainability remains a crucial issue regarding how the industrial sectors use technology to explore and utilize resources in the era of industrial revolution 4.0. This revolution has started with the applications of advanced manufacturing and digital information technologies. The world is undergoing a fundamental transformation, which is changing the way we live, work and think. The fourth industrial revolution presents a future filled with exciting opportunities and new challenges and the potential to meet specific requirements during the COVID-19 crisis. Industry 4.0 technologies have the capability of providing better digital solutions for our daily lives during this crisis. List of Keynote Speakers, Invited Speakers, List of Committee, Conference Documentation are available in this pdf.
Spanish writing on the wall? Glorification of terrorism under Spanish law

The chapter explains that boundaries between hate speech, terrorism speech, and offensive speech are hard to draw and are not made more distinct by the application of precursor crimes which thrive on imprecision and indulgence. Cases such as rap artist, Pablo Hasél, illustrate the confusion and ill-temper on all sides. In this way, the Spanish version of the offence of glorification has, as of late, become a prominent tool for the banalisation of terrorism at a time when the domestic threat of terrorism is in decline. Therefore, the way in which the Spanish Penal Code, article 578, criminalises this offence is worthy of attention to determine what exactly is being forbidden and whether it connects to terrorism and has realistic potential to act against terrorism.
CORRECTIONAL AND DEVELOPMENTAL TRAINING OF DISABLED CHILDREN IN REMOTE CLASSES OF A SPEECH THERAPIST TEACHER

the article deals with topical issues of speech therapy support for students with disabilities in school conditions through distance learning.
Pixel Based Steganography for Secure Information Hiding

The term “steganography” is derived from the Greek words steganos, which means “verified, concealed, or guaranteed”, and graphein, which means “writing”. The primary motivation for considering steganography is to prevent unapproved individuals from obtaining disguised data. With the ultimate goal of comprehending the fundamental inspiration driving the steganography procedures, there should be no significant change in the example report. The Least Significant Bit (LSB) system, which is one of the methodologies for concealing propelled picture data, is examined in this assessment. In this evaluation, another procedure for data stowing indefinitely is proposed with the ultimate goal of limiting the progressions occurring in the spread record while hiding the data with the LSB technique and making the best cover to make it difficult to get concealed data. The RGB(Red, Green, and Blue) pixel esteem based stegnography technique is proposed in this proposition. The claim to fame of this calculation is that, unlike other stegnography calculations, we do not change the pixels unless absolutely necessary.
Forschung: Vakuum in Forschung und Praxis 1/2022

Vakuum in Forschung und PraxisVolume 34, Issue 1 p. 10-17 MagazinFree to Read Forschung: Vakuum in Forschung und Praxis 1/2022 First published: 08 February 2022 https://doi.org/10.1002/vipr.202270103AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Volume34, Issue1February/March 2022Pages 10-17 RelatedInformation
CREATIVE IMAGINATION DEVELOPMENT OF SCHOOL STUDENTS IN ROBOTICS CLASSES

The article describes the experience of developing creative imagination of school students in robotics extracurricular activities. The article presents the results of the education program based on the use of LEGO WeDo 2.0 kit that increases motivation of students to solve and make an in-depth study of high-complexity tasks and helps to build logical chains.
GEDset: Automatic Dataset Builder for Machine Translation System with Specific Reference to Gujarati-English

Datasets have been instrumental in advancing machine learning research. They are the foundation for the models we develop and implement, as well as our primary means of measuring and assessing them. Furthermore, the techniques utilized to collect, construct, and share these datasets have an impact on the sorts of problems tackled by the field as well as the methodology employed in algorithm development. This study provides method for creating a large number of new bilingual dictionaries automatically. In recent years, number of people who use the internet has exploded drastically. Because English is the most often used language on the internet, most documents are written in this language. If a user’s mother tongue is Gujarati, he or she will naturally want to access info in Gujarati if at all feasible. Our algorithm generates word translations from the source language Gujarati to the target language English. This bilingual dataset dictionary is suitable for Machine Translation (MT).
Research on the rapid discovery of information resources in the training and management of big data construction

It is the key content of the current military information system construction to quickly and accurately provide users with the required information resources from the massive military training big data. With the rapid increase of training data and the rapid expansion of the network scale, the centralized data storage and search in the past is likely to form a performance bottleneck. To this end, this paper proposes an information resource discovery method based on adaptive k-nearest neighbor clustering. This method groups data resources with similar characteristics into the same category and provides an efficient inter-class message forwarding mechanism, which can reduce the search scale of the resource discovery and the diffusion scope of resource information update, so as to improve the performance of resource discovery. The simulation results show that compared with other existing methods, the information resource discovery method proposed in this paper can not only discover resources quickly and accurately, but also adapt to the development of network scale, so it has higher resource discovery efficiency and better adaptability.