Reviewerly/exHarmony huggingface dataset:
Effect of Amplification on Microwave Based Quantum Radar Systems

Quantum radar systems have an important advantages compared to the classical radar systems especially in a highly noisy environment. The superiority of the quantum radar comes from the quantum mechanical phenomenon named as entanglement. These quantum radar systems have been also studied experimentally on both optical and microwave domains. Amplifiers are the necessary part of both classical and quantum radar systems. In this paper, the effect of phase-sensitive amplification has been simulated in microwave based quantum radar systems. Apart from the studies from the literature symmetric and asymmetric amplification for both transmitted and retained signals have been simulated in this analysis.
Multi-domain Value Block Enhancement Algorithm Fused with Genetic Algorithm

In order to solve the problems of the low-illuminance image with low contrast and blurred details, this paper design the multi-domain value block enhancement algorithm fused with genetic algorithm. The algorithm first searches for the optimal segmentation threshold of the brightness channel of the input image through genetic algorithm. Then, according to the obtained threshold, the brightness channel is divided into multiple subgraphs with different exposure levels. Next, all subgraphs are assessed by the multi-threshold block enhancement method, and the brightness of each subgraph is adjusted according to the assessment. After that the multi-scale fusion method is used to fuse the details of the input image into the brightness-enhanced image. Finally, the output image with normal brightness and rich details is reconstructed. This paper selects the enhancement algorithm proposed in the past three years for comparison experiments. The results show that the low-illuminance image is enhanced by the algorithm in this paper. Its entropy increases by 66.2%, enhancement by entropy increases by 94.7%, and average gradient increases by 97.2%. The increase of each index of the image enhanced by the algorithm in this paper is greater than that of other comparison methods, which proves that the algorithm in this paper has better performance.
Utilizing Dinesh Verma Transformation (DVT) and Differential Equations in a Cryptography Model

The ever-expanding area of cryptography fostered the development of numerous cryptographic models utilizing a variety of mathematical and logical methodologies, and integral transformations were no exception. This paper proposes a cryptographic model based on the application of the Dinesh Verma integral Transformation (DVT) to the series produced by the production of a general polynomial P(t) of degree n with the Taylor series to increase the complexity of the resulting ciphertext, and in which key elements required for encryption and decryption are transmitted over channels of various security measurements to complicate the attacker's work in gathering the required information.
Review on Advantages of Blue Eyes Technology

Blue eyes technology going to lead the life in near future. This technology works on the concept of artificial intelligence. Its purpose is that computer can work like human. A lot of research work is going on it and IBM research team has already come with this blue eye technology in which a computer can sense human feelings and behaviour and understand it. The purpose of this technology is that it gives human power and abilities to computer so that computer can interact with human similar to that way one human interact with another through speech, facial expressions and touch. All humans understands each other’s feeling and emotions just by reading the facial expressions. This blue eyes technology going to create a computer that can have a human abilities like recognising the facial expressions and understand it and give the result accordingly. Some electronics gadgets are used in blue eyes technology which can sense and control human feelings and emotions. The proper hardware and software are loaded on this system. This technology can be applied everywhere where permanent operator attention required. In this technology, the meaning of blue is Bluetooth connection, eyes means eye movement and technology means techniques. Blue eyes system contains two devices, one is Data Acquisition System (DAU) and other is Central System Unit (CSU) which are connected by Bluetooth. The function of Data acquisition systems is to receive information from the sensor and send it via Bluetooth and also the message from CSU to operator. The CSU gives visualization interface by buffering incoming sensor data.
Text Tone Determination Using Fuzzy Logic

Abstract The study proposes the text tone detection system based on sentiment dictionaries and fuzzy rules. Computer analysis of texts from different sources has been performed in emotional categories: anger, anticipation, disgust, fear, joy, sadness, surprise and trust. A synonym dictionary has been used to expand the vocabulary. To increase the accuracy and validity of sentiment analysis, the authors of the study have used coefficients that take into account different emotional loads of words of various parts of speech and the action of intensifying or softening adverbs. A quantitative value of the text tone has been obtained as a result of an aggregation of normalized data on all emotional categories by the fuzzy inference methods. It has been found that emotional words have a greater impact on the text tone value in the case of analysis of short messages. The proposed approach makes it possible to contribute to all emotional categories in the final text evaluation.
China’s data-orienting personal information protection during combating the epidemic

COVID-19 came suddenly. China has controlled this epidemic in a certain degree by means of digitized epidemic prevention. This kind of means is like a double-edged sword, which eases major public health events, but threatens personal information security. The legislation of personal information protection went through several discussions in China until this issue resurfaced during the recent COVID-19 pandemic, and on August 20, 2021 China passed The Personal Information Protection Law and began implementing it in November of the same year. This research focus on the outstanding personal information issues in the process of digitized epidemic prevention and hopes to improve the protection system of personal information by combing the deficiencies in legislation.
Total Prediction Decision Support System Bakery and Cake Production Using Mamdani Fuzzy Method

The decision support system for predicting the amount of bakery and cake production using the fuzzy mamdani method is one of the processes for determining the prediction of the amount of bakery and cake production for the next month so that the desired production amount is according to needs. Neko-Neko Bakery &amp; Cake so far in predicting the amount of production where the demand for bakery and cake is sometimes not fulfilled considering that the available bakery and cake production is not sufficient because the bakery and cake supplies in the production section do not meet and vice versa, namely the amount of production sometimes experiences excess in production. production so that it is not in accordance with demand, then there is often an error in predicting the amount of production in producing bakery and cake because the number of bakery and cake productions produced is not really needed while bakery and cake which are often needed are not produced since so far the Neko-Neko Bakery and Cake in Prediction data collection on the number of bakery and cake productions only relies on the Microsoft Office Excel application system where the data that is processed or processed is sometimes double in value. The method used in the decision support system to predict the amount of bakery and cake production is fuzzy mamdani. Mamdani fuzzy method is one method that has a simple structure and easy to understand. Mamdani fuzzy logic uses MIN-MAX or max-product operations with a predetermined set of rules, namely the previous IF…AND…THEN. Based on the application of this mamdani fuzzy method in predicting the amount of bakery and cake production, it can be stated that it is very feasible to apply to Neko-Neko Bakery &amp; Cake. This decision support system was built using the PHP programming language and MySQL database.
THE METHOD OF EXTRACTING THE STEGANOGRAPHY WATERMARKS BY KEY USING HAAR WAVELETS

This article describes a method for applying an encoded digital steganographic watermark to a digital image and its subsequent extraction using Haar wavelets. The method of applying a digital steganographic watermark by key, and highlighting this sign with a key, is considered. The relevance of this method of applying and highlighting a digital steganographic watermark is considered. A few words describe the method of splitting a signal into sub-signals using the Haar algorithm and how it is applicable in the context of digital images. The results of checking the application of a digital watermark for resistance to various transformations are presented, such as: blurring with a 3×3, 5×5 core, jpeg compression with a compression ratio of 50 and 70 %, deleting the 1 LSB, 2 and 4 LSBs. Corresponding images are presented that illustrate the results of tests for resistance to conversion of a digital steganographic watermark. A small, illustrative and easy to implement example of applying a digital steganographic watermark, as well as its extraction using a previously created key using simple coding, which consists in the fact that the columns of pixels of the original image are shifted by a certain number of positions, is presented. Also, the article provides a brief description of the LSB algorithm and considers the main advantages and disadvantages of the algorithm developed and presented in this article with the standard LSB algorithm. In conclusion, the corresponding conclusions were drawn about the applicability of the developed algorithm, about its shortcomings and advantages, described in this article.
Development of depth map from stereo images using sum of absolute differences and edge filters

This article proposes a framework for the depth map reconstruction using stereo images. Fundamentally, this map provides an important information which commonly used in essential applications such as autonomous vehicle navigation, drone’s navigation and 3D surface reconstruction. To develop an accurate depth map, the framework must be robust against the challenging regions of low texture, plain color and repetitive pattern on the input stereo image. The development of this map requires several stages which starts with matching cost calculation, cost aggregation, optimization and refinement stage. Hence, this work develops a framework with sum of absolute difference (SAD) and the combination of two edge preserving filters to increase the robustness against the challenging regions. The SAD convolves using block matching technique to increase the efficiency of matching process on the low texture and plain color regions. Moreover, two edge preserving filters will increase the accuracy on the repetitive pattern region. The results show that the proposed method is accurate and capable to work with the challenging regions. The results are provided by the Middlebury standard dataset. The framework is also efficiently and can be applied on the 3D surface reconstruction. Moreover, this work is greatly competitive with previously available methods.
Node Classification in Attributed Multiplex Networks Using Random Walk and Graph Convolutional Networks

Node classification, as a central task in the graph data analysis, has been studied extensively with network embedding technique for single-layer graph network. However, there are some obstacles when extending the single-layer network embedding technique to the attributed multiplex network. The classification of a given node in the attributed multiplex network must consider the network structure in different dimensions, as well as rich node attributes, and correlations among the different dimensions. Moreover, the distance node context information of a given node in each dimension will also affect the classification of the given node. In this study, a novel network embedding approach for the node classification of attributed multiplex networks using random walk and graph convolutional networks (AMRG) is proposed. A random walk network embedding technique was used to extract distant node information and the results are considered as pre-trained node features to be concatenated with the original node features inputted into the graph convolutional networks (GCNs) to learn node representations for each dimension. Besides, the consensus regularization is introduced to capture the similarities among different dimensions, and the learnable neural network parameters of GCNs for different dimensions are also constrained by the regularization mechanism to improve the correlations. As well as an attention mechanism is explored to infer the importance for a given node in different dimensions. Extensive experiments demonstrated that our proposed technique outperforms many competitive baselines on several real-world multiplex network datasets.
Methodology for assessing the quality of educational services in higher education

The article examines the criteria and indicators for assessing the quality of educational services. The coverage of the topic of this article passes through the prism of factors related to the assessment of educational services quality, which allowed the authors to identify current methodological problems, as well as to emphasize the importance of using an integrated approach in studying the issues of providing educational services. The authors identify criteria and indicators for assessing of educational services. The authors developed the composite coefficient of educational services quality. The practical implementation of the proposals prepared by the authors determines the prerequisites for the development of a methodology for assessing educational services quality, which will allow for an objective assessment and, as a result, take the necessary measures to improve the quality of educational services on the part of the educational organization.
Variable Selection Technique for Solar Global Irradiance Prediction

Sun’s energy is variable and intermittent by nature and has straight influence on output yielded by photo voltaic (PV) systems. Solar global irradiance prediction is crucial for conducting various research projects in emerging field of renewable energy sources (RESs). Selecting the most significant input variables that influence the solar irradiance prediction is important as it can reduce computational time and burden, enhance the prediction accuracy, increase the convergence speed and simplify the structure of the model. This work has been aimed at finding input variables that affect the prediction of solar global irradiance the most based on backward elimination technique integrated with Pearson correlation coefficient approach. 14 input variables—3 geographical variables, 9 meteorological and 2 calendar variables have been considered for the analysis. Feed forward neural network (FFD) technique has been trained on 25 different climatic regions of India and has been used to predict irradiance for Chandigarh, India. The proposed approach has yielded that surface pressure (SP), wind speed (WS), year (Y) are the most insignificant variables, whereas Clearness Index (CI), maximum temperature (MaT) are most influential ones.
Big Data–Based Frameworks and Machine Learning

The optical character recognition (OCR) system is implemented for the classification of text and language retrieval systems. Due to the complexity in the text style and the higher number of connected components OCR has failed to classify and retrieve many regional languages like Telugu. Thus, to overcome these problems, retrieval of a word image system is developed using intelligence-based Telugu word image retrieval (TWIR) system. This paper presented a work to retrieve Telugu word images using a DeepCluster-based or multilayered deep learning convolution neural network (DL-CNN). Then, a deep learning-based model is used for extraction of relevant features of Telugu word images using AlexNet and the procedure named as DeepCluster. Thus, by using the DeepCluster method various logy grammar rules of Telugu scripts will be perfectly analysed. Thus, the TWIR system will be effectively used for the retrieval of Telugu words and useful in all real-time applications such as Telugu web browsing and Telugu speech analysis. The proposed DeepCluster model gives outstanding simulation results compared to the state-of-the-art approaches for both average precision (mAP) and mean average recall (mAR) metrics.
Association Rule Mining on Spambase Dataset using Tanagra

There is huge amount of data being generated every minute on internet. This data is of no use until we cannot extract useful information from it. Data mining is the process of extracting useful information or knowledge from this huge amount of data that can be further used for various purposes. Discovering Association rules is one of the most important tasks among all other data mining tasks. Association rules contain the rules in the form of IF then THAN form. The leftmost part of the rule i.e. IF is called as the Antecedent which defines the condition and the rightmost part i.e. ELSE is called as the Consequent which defines the result. In this paper, we present the overview and comparison of Apriori, Apriori PT and Frequent Itemsets algorithm of association component in Tanagra Tool. We analyzed the performance based on the execution time and memory used for different number of instances, support and Rule Length in Spambase Dataset. The results show that when we increase the support value the Apriori PT takes the less execution time and Apriori takes less memory space. When numbers of instances are reduced Frequent Itemsets outperforms well both in case of memory and execution time. When rule length is increased the Apriori algorithm performs better than Apriori PT and Frequent Itemsets.
Peer review declaration

The present document contains details on the procedure for reviewing the materials of the third International Scientific and Practical Conference MATHEMATICAL MODELING, PROGRAMMING AND APPLIED MATHEMATICS 2021. • The type of peer review is double blind peer review. • All the submitted materials, timely received by the conference e-mail conf-ieis@novsu.ru, were considered by the program organizing committee. The program committee identified the reviewers who received the authors’ articles through the conference email. Each article was submitted to two independent peer reviewers with a scientific degree who did not know the name of the author (or the names of authors) of the article being reviewed. All articles submitted for consideration have passed the peer review procedure in accordance with the standards of editorial ethics, with international practice of editing, reviewing, publishing and authorship of scientific publications and the recommendations of the Committee on Publication Ethics –COPE. Plagiarism, improper borrowing, attempts to circumvent plagiarism detection, verbatim copying and paraphrasing of one’s own work (self-plagiarism) without proper justification, copyright infringement is considered unacceptable practices. All articles that have passed the peer review procedure are original works that have not been previously published in other publications in their current or similar form; they have not been reviewed in other editions. Materials of low scientific level are not accepted for publication. • The number of applications received is 105, of which 59 were accepted for work, the acceptance rate (number of applications accepted / number of applications received X 100) was 56%. • Average number of reviews per paper - 1,6. • The total number of reviewers involved is 40 experts in this particular subject area. • Additional information on the process of consideration of materials: only applications, the authors of which had corrected the substantiated comments of the reviewers, were accepted; the articles that received a negative review from the reviewer were excluded from the conference materials. The conference materials submission control system is presented on the official conference website at https://www.novsu.ru/dept/515278/i.454744/?id=1759423. • For inquiries please contact Dr. Oxana Fikhtner, Head of Academic Publishing Development centre of NovSU (Oxana.Fikhtner@novsu.ru).
Evaluating the Implementation of Distributed Ledger Technology for the Licensing and Regulation of Nuclear Power Plants

Abstract The approval process from the U.S. Nuclear Regulatory Commission (NRC) for nuclear power plants is sequential. It involves several government bodies such as the Advisory Committee on Reactor Safeguards (ACRS), public meetings, and hearings. If the submissions made to the NRC do not contain enough information to meet the regulation requirements, the NRC issues a Request for Additional Information (RAI). Thus, the licensee has to go through a paperwork-intensive process that involves multiple regulatory agencies for the various licensing requirements. Moreover, sending applications to the NRC is limited to using an electronic submission generation tool called the Packing Slip Wizard (PSW). This paper presents a methodology to implement Distributed Ledger Technology (DLT) to address the need for a real-time, digitized documentation platform in the nuclear power industry’s licensing and regulation process. The evaluation of DLT’s implementation resulted in the formulation of a methodology to accept submissions from an applicant on a web application and storing the received data on a distributed ledger. The presented method offers a real-time submission of the available information of an application. It facilitates the NRC with a real-time feedback capability expediting the review process. RAI’s can be reduced in number by ensuring that the NRC’s information requirements are defined as smart contracts.
ICTs - An Efficient Tools for Entrepreneurs Amongst the Nigerian Youths.

Information and Communications Technology (ICT) is an umbrella term that includes any communication device encompassing: Computers and network, hardware and software, smart phones, satellites system, radio and television and so on, as well as the various services and application associated with them. Undoubtedly ICT is the greatest achievement of the 21st Century. It is believed that ICT have the potential to help the young graduates/ youths develop various skills including entrepreneurial skills. In Nigeria a considerable part of young graduates/youths remains unemployed; a possible solution for this problem might be self-employment. ICT skills which the young generation are very much familiar with can contribute to the development of an entrepreneurial career. This study tries to define those ICT tools mostly used by the graduates/youths and how possibly best they can be used to generate income and employ others. The paper concludes that the need for ICT in our daily life is imperative and cannot be overemphasized, hence the need to sieze the opportunity in order to generate income and employment. However the studys recommends among others that; an ICT skill based acquisition centres should be established by the government and other relevant stakeholders in order to equip the young Nigerian graduates/youths with the necessary skills they need to be self-employed. Keywords: ICT, Entrepreneurship, Youths, Nigeria, Graduates, Unemployment