Reviewerly/exHarmony huggingface dataset:
The Analysis and Optimization of CNN Hyperparameters with Fuzzy Tree Model for Image Classification

The meaningful performance of convolutional neural network (CNN) has enabled the solution of various state-of-the-art problems.Although CNNs achieve satisfactory results in computer-vision problems, they still have some difficulties.As the designed CNN models are deepened to achieve much better accuracy, computational cost and complexity increase.It is significant to train CNNs with suitable topology and training hyperparameters that include initial learning rate, minibatch size, epoch number, filter size, number of filters, etc. because the initialization of hyperparameters affects classification results.On the other hand, it is not possible to make a definite inference for the hyperparameter initialization and there is uncertainty.This study is carried out to model uncertainty using fuzzy inference system (FIS).The designed fuzzy model provides estimation of classification result depending on CNN topology and training hyperparameters.GoogleNet and Inceptionv3 that contain inception-modules, ShuffleNet that contains shuffleblocks, DenseNet201 that contains dense-blocks, EfficientNet, ResNet18, ResNet50, ResNet101, and MobileNetv2 that contain residual-blocks, and InceptionResNetv2 that includes both inception-modules and residual-blocks were evaluated as CNN models.Test sample dataset was obtained by training CNN models with various training hyperparameter combinations.CNN models were trained on Animal Diagnostics Lab (ADL) which is a histopathological dataset includes healthy and inflamed kidney, lung, and spleen images.A new FIS tree model that is more computationally efficient and easier to understand than a single FIS was designed and classification accuracy prediction of CNN models depending on hyperparameter combinations was performed.The best, the worst, and the average classification accuracies obtained with CNN models that use best training hyperparameter set are 97.70%,93.60%, and 96.30%, respectively.Moreover, Cifar10 and Cifar100 benchmark datasets were experimented to reveal true capability and limitations of the proposed approach.Experimental results indicate that the designed FIS tree model provides a successful hyperparameter evaluation mechanism with an average RMSE value of 1.2652.
Design of Takagi–Sugeno fuzzy systems by learning from examples in case a number of available data is not sufficient

The paper describes a solution of a problem of developing of fuzzy rules compliant with the Takagi-Sugeno approach where a number of available examples (observations) is not sufficient.Modeling of fuzzy premises and generating functions describing a dependence of a result variable on antecedents are described.In our original approach a problem of identification of membership functions of variables com-posing premises and a problem of consequent parameters identification are solved.For the first one, we used a simple technique based on individual judgements of experts.The second one is solved with a linear programming method.In particular, our approach to formulate the consequent parameter identification problem allows using of an extremely effective T-S method when a data-driven approach cannot be applied.In the paper we present a description of our methods and results of simulations of accuracy of the proposed approach, based on commonly known benchmarks.The achieved accuracy of classification is sufficient for the most of decision-making systems of an expert nature.
MODERNIZATION OF DEMONSTRATION PHYSICAL EXPERIMENT AS A MEANS OF FORMATION OF DIGITAL COMPETENCE OF LEARNERS AND STUDENTS

The conditions and initiatives for the formation of digital competence, which are part of the reform of Ukrainian education, are analyzed. The possibilities of digital laboratory complexes as an effective tool for the formation of digital competence of students and pupils are identified. It is emphasized that the cost of such equipment is quite high, so the actual and effective alternative is to upgrade existing laboratory equipment with modern digital software and hardware components. The analysis of researches of domestic and foreign scientists is carried out, which gives grounds to assert that the problems of formation of digital competence can be formed, in particular in the process of modernization and use of the updated educational experiment in physics. The problems of effective methods of updating the educational physical experiment and its promotion of the development of information and digital competence of students and pupils are clarified. A modernized experimental setup for studying pendulum oscillations is described. The main characteristics and features of equipment manufacturing are considered, in particular the use of Arduino platform, means of microelectronic circuitry and three - dimensional prototyping. Practical recommendations for the use of the complex in a training experiment in physics are offered. The approbation of the complex in the educational process and research work was carried out, which confirmed the effectiveness of the use of modernized equipment as a tool for the formation of information and digital competence of pupils and students.
Do Children With Developmental Language Disorder Activate Scene Knowledge to Guide Visual Attention? Effect of Object-Scene Inconsistencies on Gaze Allocation

Our visual environment is highly predictable in terms of where and in which locations objects can be found. Based on visual experience, children extract rules about visual scene configurations, allowing them to generate scene knowledge. Similarly, children extract the linguistic rules from relatively predictable linguistic contexts. It has been proposed that the capacity of extracting rules from both domains might share some underlying cognitive mechanisms. In the present study, we investigated the link between language and scene knowledge development. To do so, we assessed whether preschool children (age range = 5;4-6;6) with Developmental Language Disorder (DLD), who present several difficulties in the linguistic domain, are equally attracted to object-scene inconsistencies in a visual free-viewing task in comparison with age-matched children with Typical Language Development (TLD). All children explored visual scenes containing semantic (e.g., soap on a breakfast table), syntactic (e.g., bread on the chair back), or both inconsistencies (e.g., soap on the chair back). Since scene knowledge interacts with image properties (i.e., saliency) to guide gaze allocation during visual exploration from the early stages of development, we also included the objects' saliency rank in the analysis. The results showed that children with DLD were less attracted to semantic and syntactic inconsistencies than children with TLD. In addition, saliency modulated syntactic effect only in the group of children with TLD. Our findings indicate that children with DLD do not activate scene knowledge to guide visual attention as efficiently as children with TLD, especially at the syntactic level, suggesting a link between scene knowledge and language development.
Acoustic Feature Extraction and Optimized Neural Network Based Classification for Speaker Recognition

Identifying the person from his or her voice characteristics is an essential trait for human interaction. Automatic speaker recognition (ASR) systems are developed to find the identity of the speaker in the field of forensics, business interactions and law enforcement. It can be achieved by extracting prosodic, linguistic, and acoustic speech characteristics. Furthermore optimized neural network based approaches are reviewed to classify the extracted features. In this paper, literatures are surveyed on recognition of speaker through the neural network using an optimization algorithm that has developed from the previous years for ASR systems. We deliberate different characteristics of ASR arrangements, containing features, neural network based classification, performance metrics and standard evaluation data sets. ASR system is discussed in two parts. The first part illustrates different feature extraction techniques and the second part involves the classification approaches which identify the speaker. We accomplish this evaluation through a comparative analysis of various recognition of speaker approaches and compare the results of the same.
Evaluation of Research, Journals, and Universities in Iraq and the Kurdistan Region According to the Scimago Classification of Administration and Economics Specializations: A Comparative Study with Neighboring Countries

The aim of study is to determine the level of researchers, the quality of published research, and the quality of journals in the fields of administration and economics, using indicators from the Scimago journal and country Rank (SJR) and the Scimago Institutions Rankings (SIR), which is based on the Scopus database of the Dutch publishing house Elsevier for Iraq in comparison to neighboring countries (Turkey, Iran, Saudi Arabia, Kuwait, Jordan and Syria) in terms of the number of published research, total citations, citations per publication which reflects the quality of scientific research and refereed scientific journals for three different time periods, including for a period of ( 24) years over the period and for a period of ( 18) years after the year ( 2002) and for the year (2020) only, and the number of academic journals and universities classified for the year (2021) for Iraq using the descriptive and quantitative method of academic journals over the period .The study concludes that, except in Syria, research output, academic journals, and universities in Iraq and the Kurdistan Region fall behind neighboring nations.Also, this study suggests that higher education and educational authorities should update regulations and directions to motivate Iraqi researchers and universities to publish according to prominent databases such as Scopus.
Quantonomics: Economy of Quantum Computers and Quantum Communications, Quantum Technologies, and Quantum Communications with the usage of Data Protection Systems based on Principles of Quantum Cryptography and Steganography

Intensive development of the quantum communications and quantum technologies in the world form new directions of the scientific researching and transform world economy, forming as the one of priority directions quantonomics. In the article are discussed the components of the economy of the quantum computers and quantum calculations, quantum technologies and quantum communications with the usage of data protection systems, based on principles of quantum cryptography and steganography.
Smart learning technology for computer programming driven by research related to COVID-19

The restrictions imposed by COVID-19 have significantly affected the reorganization of educational processes, including the process of computer programming learning in higher education. The work experiences in teaching programming languages in higher education have served as an idea for the development of smart learning technology, as a complement to the pre-existing ecosystem for digital learning, in particular C++ programming, in higher education. This paper aims to present the realization of smart learning technology, describes its use and provides information about the level of acceptance of higher education students. The opinions and experiences of the students who used the technology, during the summer semester of 2020, were obtained through an anonymous questionnaire, prepared by the author of the paper. The results were obtained during implementation of the curriculum in advanced C++ programming in the Faculty of ICТ. The results show the potential for wider application of this Smart Learning technology, especially in technical areas. Keywords: C++; covid19; programming; smart learning, technology
SECURING IOT WITH BLOCKCHAIN

Abstract. IoT is becoming ubiquitous in industry, homes, cities, literally in every aspect of our daily lives. Securing IoT-based systems is difficult because of deficiencies in the very nature of IoT devices such as limited battery power, processing, and storage, etc. Blockchain is a new approach used to securely record transactions and offers potential solutions to computer and internet security issues such as confidentiality, integrity, availability, authentication, authorization, and accountability. Blockchain, as a decentralized ledger consisting of interconnected blocks, can remedy most of the security deficiencies of heavily IoT based systems. The Hyperledger Fabric blockchain network used in this study provides confidentiality, data integrity, authentication, and data security for data obtained from IoT devices. Widely used IoT data transfer MQTT protocol is included in the proposed approach. The approach is demonstrated in a simple demo Hyperledger network with simulated IoT devices. The proposed approach is discussed in terms of network security dimensions. Based on the features of the Hyperledger Blockchain network, it is displayed that the IoT security deficiencies can largely be remedied with the proposed approach.
A Model for Detecting Accounting Frauds by using Machine Learning

This paper aims to develop a machine learning model that enables to predict signs of financial statement frauds by combining the domain knowledge of machine learning and accounting.Inputs of this model is a published dataset of financial statements, and outputs involve the conclusions whether the predicted financial statements indicate the signs of financial statement frauds or not.Currently, XGBoost is recognized as one of the most popular classification methods with fast performance, flexibility, and scalability.However, its default properties are not suitable for fraudulent detecting of imbalanced datasets.To overcome this drawback, this research introduces a new machine learning model based on XGBoost technique, called f(raud)-XGBoost.The proposed model not only inherits XGBoost advantages but also enables it to detect financial statement frauds.We apply the Area Under the Receiver Operating Characteristics Curve and NDCG@k to perform the evaluation process.The experimental results show that the new model performs slightly better than three existing models including logistic regression model that is based on financial ratios, Support-vector-machine model, and RUSBoost model.
Research on the Construction of a Talent Training Mode for Artificial Intelligence Specialty in Local Colleges and Universities

In order to serve the local economic development, this study investigates the demand for local talents and analyzes the characteristics of the talent training in artificial intelligence in local colleges and universities. Subsequently, the talent training objectives of artificial intelligence specialty have been formulated, and a curriculum system that integrates the industry and education has been constructed in hope to continuously provide high-quality talents in artificial intelligence for the society.
Standpoint Logic: Multi-Perspective Knowledge Representation

Ontologies and knowledge bases encode, to a certain extent, the standpoints or perspectives of their creators. As differences and conflicts between standpoints should be expected in multi-agent scenarios, this will pose challenges for shared creation and usage of knowledge sources. Our work pursues the idea that, in some cases, a framework that can handle diverse and possibly conflicting standpoints is more useful and versatile than forcing their unification, and avoids common compromises required for their merge. Moreover, in analogy to the notion of family resemblance concepts, we propose that a collection of standpoints can provide a simpler yet more faithful and nuanced representation of some domains. To this end, we present standpoint logic, a multi-modal framework that is suitable for expressing information with semantically heterogeneous vocabularies, where a standpoint is a partial and acceptable interpretation of the domain. Standpoints can be organised hierarchically and combined, and complex correspondences can be established between them. We provide a formal syntax and semantics, outline the complexity for the propositional case, and explore the representational capacities of the framework in relation to standard techniques in ontology integration, with some examples in the Bio-Ontology domain.
Matrix Based Single Authority Electronic Voting Schemes

The developments of electronic communication have made the world in to a global village and provide the opportunity for interactive communication with distant people with in short duration. Cost, time and energy are saved by the digital technologies like electronic commerce, electronic voting and so
Unfolding #Anonymous on Twitter

This paper presents a comprehensive empirical investigation of the range of actors, issues and sub-groups related to the hashtag Anonymous on Twitter between 2012 and 2015. Complementing existing studies that have provided in-depth accounts of Anonymous from a specific point of view, this research provides an overview of the network related to the discursive construction of Anonymous on Twitter from a synoptic standpoint. In particular, the analysis covers three dimensions: the structure and dynamics of the #Anonymous interaction network; the range of issues that Anonymous has been associated with; and the relation between Anonymous and its offshoots. This research provides a descriptive characterization of the topological and semantic complexity of Anonymous and invites to reflect on the simplifications that our vocabulary and methods entail vis a vis the complexity of digital entities delimited by and individuated through hashtags.
Concept Libraries for Repeatable and Reusable Research: Qualitative Study Exploring the Needs of Users

Big data research in the field of health sciences is hindered by a lack of agreement on how to identify and define different conditions and their medications. This means that researchers and health professionals often have different phenotype definitions for the same condition. This lack of agreement makes it difficult to compare different study findings and hinders the ability to conduct repeatable and reusable research.This study aims to examine the requirements of various users, such as researchers, clinicians, machine learning experts, and managers, in the development of a data portal for phenotypes (a concept library).This was a qualitative study using interviews and focus group discussion. One-to-one interviews were conducted with researchers, clinicians, machine learning experts, and senior research managers in health data science (N=6) to explore their specific needs in the development of a concept library. In addition, a focus group discussion with researchers (N=14) working with the Secured Anonymized Information Linkage databank, a national eHealth data linkage infrastructure, was held to perform a SWOT (strengths, weaknesses, opportunities, and threats) analysis for the phenotyping system and the proposed concept library. The interviews and focus group discussion were transcribed verbatim, and 2 thematic analyses were performed.Most of the participants thought that the prototype concept library would be a very helpful resource for conducting repeatable research, but they specified that many requirements are needed before its development. Although all the participants stated that they were aware of some existing concept libraries, most of them expressed negative perceptions about them. The participants mentioned several facilitators that would stimulate them to share their work and reuse the work of others, and they pointed out several barriers that could inhibit them from sharing their work and reusing the work of others. The participants suggested some developments that they would like to see to improve reproducible research output using routine data.The study indicated that most interviewees valued a concept library for phenotypes. However, only half of the participants felt that they would contribute by providing definitions for the concept library, and they reported many barriers regarding sharing their work on a publicly accessible platform. Analysis of interviews and the focus group discussion revealed that different stakeholders have different requirements, facilitators, barriers, and concerns about a prototype concept library.
The Development of Innovative Activities in High Edsucation

Changes in modern high education of the Russian Federation have occurred within recent years. They were caused by new demands of the state and society as well as innovations in economy. In modern higher education there is a need for the development of innovation and its continuous improvement. In modern realities, each higher education institution faced a task that is extremely difficult to solve. It consists in the development and implementation of the latest innovative information and educational environment. The electronic environment of a high educational institution expands educational opportunities, raises the level of educational services, therefore today the issue of the development of electronic activities in an educational institution is so urgent. The purpose of the article is to develop a question concerning introduction of e-learning in high education. For this purpose, a model of methodological support of innovation activity in electronic environment was developed. It allows increasing the level of electronic environment development and the quality of students’ education in general. Based on it, we have developed recommendations for the introduction of e-education in high education.Experimental verification of the model methodological support of innovative activities in electronic environment showed that the willingness of teachers to use electronic environment has increased significantly. The research can be used in the further development of higher education electronic environment.
Summary and Outlook

SummaryWe are at the end of our journey—at least for now. So let us recap briefly: Our universe is old and cold and was created from a hot Big Bang about 14 billion years ago. Since then, it has been expanding. With the help of particle physics and cosmology, it is possible to reconstruct the universe from about 10−10 s after the Big Bang. A quantum gravity, such as string theory, is necessary to describe the Big Bang itself. String theory is still not sufficantly well understood, but already suggests interesting properties, e.g. additional space dimensions and parallel universes.
Pengembangan Media Pembelajaran Berbasis Aplikasi Game dalam Pembelajaran Bahasa Indonesia pada Siswa Kelas XI

The aims of this study are to (1) describe the development of game media in Indonesian language learning; (2) reveal the level of interest in using game media in an effective learning process requires media in Indonesian language learning; and (3) knowing the level of effectiveness of using game media in learning Indonesian. This research is development research, with data collection steps according to the development model according to Borg &amp; Gall. The stages taken in this research are limited to seven stages, namely research and information collecting, planning, developing the preliminary form of product, preliminary field testing, main product revision, main field testing, and operational product revision. The results of the research show that: (1) the development of learning media based on Android games with the support of the Netbeans 12.4 product oracle software; (2) students have a positive attitude towards the product by 81% in the "very interesting" category; (3) the level of effectiveness of using game media in learning Indonesian is 82% or very effective. Based on the results of these studies, it can be concluded that web-based games can be used to support learning media for high school students.