Reviewerly/exHarmony huggingface dataset:
An Embedded CNN Design for Edge Devices Based on Logarithmic Computing

In this paper, we propose a very compact embedded CNN processor design that can easily fit into edge devices based on a modified logarithmic computing method using very low bit-width representation. For Yolov2, our processing circuit takes only 0.15 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> using TSMC 40 nm cell library. The key idea is to apply low bit-width logarithmic representation and devise a unified, reusable CNN computing kernel that can significantly reduce computing resources. The proposed approach has been extensively evaluated on many popular image classification CNN models (AlexNet, VGG16, and ResNet-18/34) and object detection models (Yolov4). The hardware-implemented results show that our design achieves 20x performance improvement while consumes only minimal computing and storage resources, yet attains very high accuracy. The design is thoroughly verified on FPGAs, and the SoC integration is underway with promising results. With extremely efficient resource and energy usage, our design is excellent for edge computing purposes.
DPCat: Specification for an Interoperable and Machine-Readable Data Processing Catalogue Based on GDPR

The GDPR requires Data Controllers and Data Protection Officers (DPO) to maintain a Register of Processing Activities (ROPA) as part of overseeing the organisation’s compliance processes. The ROPA must include information from heterogeneous sources such as (internal) departments with varying IT systems and (external) data processors. Current practices use spreadsheets or proprietary systems that lack machine-readability and interoperability, presenting barriers to automation. We propose the Data Processing Catalogue (DPCat) for the representation, collection and transfer of ROPA information, as catalogues in a machine-readable and interoperable manner. DPCat is based on the Data Catalog Vocabulary (DCAT) and its extension DCAT Application Profile for data portals in Europe (DCAT-AP), and the Data Privacy Vocabulary (DPV). It represents a comprehensive semantic model developed from GDPR’s Article and an analysis of the 17 ROPA templates from EU Data Protection Authorities (DPA). To demonstrate the practicality and feasibility of DPCat, we present the European Data Protection Supervisor’s (EDPS) ROPA documents using DPCat, verify them with SHACL to ensure the correctness of information based on legal and contextual requirements, and produce reports and ROPA documents based on DPA templates using SPARQL. DPCat supports a data governance process for data processing compliance to harmonise inputs from heterogeneous sources to produce dynamic documentation that can accommodate differences in regulatory approaches across DPAs and ease investigative burdens toward efficient enforcement.
Digesting smart contracts in Ethereum blockchain networks

Blockchain relies on a peer-to-peer trusted model over a transparent publicly-available distributed ledger. Much has been said about this particular definition, about the technology, its benefits, potential for new market niches, and revolutionary possibilities. Functional aspects are typically put forward, whereas non-functional sides like performance issues and, above all, security threats are left in a second line. The excitement on this technology yields most of the literature to report success cases and final results. However, there are fewer works focusing on practical technology revisions that provide the insights into blockchain fundamental technology. To effectively widespread this technology it is needed to digest the basic tools that enable the creation of a blockchain application and that enable one to join a particular blockchain network of her/his interest. This paper describes and analyzes, from a practical point of view, the implementation of Solidity smart contracts and their deployment on an Ethereum blockchain network. Moreover, it discusses in the end limitations of the technology as far as its security issues is concerned.
Intelligent Web Mining Techniques using Semantic Web

The Evolution of Web over the years has made a significant progress on how the information is organized and stored, as the complexity of the data stored and retrieved increases it becomes mandatory to upgrade the methodology involved in achieving them. During web Access it becomes essential to determine the nature of the user so as to understand his preferences in order to generate a customized look and feel of the website and there by offering him a Personalized web surfing experience. The primary Stage of a customized web access is in determining what the user wants from the web via a proper semantic Query Methodology which represents what user need rather than content prevailing in the web for request Query. When the user request is understood, the next task would to categorize the possible results in response to the query depending upon relevance. Furthermore, the process would be to categorize user data according different aspects to create web personalization. This takes the web to next level with web usage prediction using Web log files there by creating a New Customized web for every one with the major focus to represent what matters to the users.
Optimization of chamfer masks using Farey sequences and kernel dimensionality

Farey sequences have captured the attention of several researchers because of their wide applications in polygonal approximation, generation of Ford circles, and shape analysis. In this work, we extend the applications of these sequences to optimize chamfer masks for computation of distance maps in images. Compared with previous methods, the proposed method can more effectively generate optimal weights from larger chamfer masks without considering multiple and rather complex defining variables of the masks. Furthermore, our work demonstrates the relationship between size of the chamfer kernel, Farey sequence, and optimal weights of the chamfer mask. This interesting relationship, which may be useful in various image processing and computer vision tasks, has never been revealed by any other previous study. Results from the current research may advance our understanding on the applications of Farey sequences in computational geometry and vision-related tasks. To allow reproducibility of the results, implementation codes and datasets can be accessed in the public repository at https://www.mathworks.com/matlabcentral/fileexchange/71652-optimization-of-chamfer-masks .
Mathematical Model Construction of Network Computer Test Automation System for College English Teaching

Networked education represents a development direction of educational reform, has become a feature of modern education, and has formed a new impetus to the development of education. The change from paper-and-pencil examinations to computer network-based machine examinations is not only a reform of the content and form of the University English Level 4 and 6 examinations, but also a reflection of the reform of the comprehensive assessment system and teaching philosophy of University English teaching. Promoting the development and construction of online college English examination systems in universities, applying machine examinations to various types of tests and formal examinations for college English teaching, and updating the college English question bank through continuous accumulation of professional teachers will have very high research value and practical value in improving the quality of examinations and promoting the standardization of college English examinations. In order to show the individualized chemistry report simultaneously, it is necessary to further ask relevant subject experts, educational measurement experts, and front-line teachers to expand the question attributes; that is, the question attributes extend to module specific knowledge points, cognitive levels, and information literacy ability levels, while most of the pages are combined with Ajax technology to reduce hardware resource dependency and optimize software performance. The paper analyzes the requirements analysis and overall design of the online college English examination system, including the design objectives, design principles, functional design, core algorithm design, architecture design, database design, and security design. The main functions of the online college English examination system, such as personal information management, question bank information management, test paper grouping management, online examination management, paper marking management, and system setting management, are discussed in detail. The main functions of the system, such as personal information management, question bank information management, test paper grouping management, online test management, mark and approve management, and system setting management, are discussed in detail, and the performance test and some function test of the system are also briefly discussed. The whole research process involves the identification of test questions and their attributes in the construction of the question bank, the construction of the adaptive test system, the comprehensive analysis of the mock test results, and the thinking about the application of the high school adaptive academic level test.
Analysis on the Development of Cloud Security using Privacy Attribute Data Sharing

The data sharing is a helpful and financial assistance provided by CC. Information substance security also rises out of it since the information is moved to some cloud workers. To ensure the sensitive and important data; different procedures are utilized to improve access manage on collective information. Here strategies, Cipher text-policyattribute based encryption (CP-ABE) might create it very helpful and safe. The conventionalCP-ABE concentrates on information privacy only; whereas client's personal security protection is a significant problem as of now. CP-ABE byhidden access (HA) strategy makes sure information privacy and ensures that client's protection isn't exposed also. Nevertheless, the vast majority of the current plans are ineffectivein correspondence overhead and calculation cost. In addition, the vast majority of thismechanism takes no thought regardingabilityauthenticationor issue of security spillescapein abilityverificationstage. To handle the issues referenced over, a security protectsCP-ABE methodby proficient influenceauthenticationis presented in this manuscript. Furthermore, its privacy keys accomplish consistent size. In the meantime, the suggestedplan accomplishes the specific safetyin decisional n-BDHE issue and decisional direct presumption. The computational outcomes affirm the benefits of introduced method.
Infinite Fuzzy Restricted Boltzmann Machines for the Enhancement of Fuzzy Neural Networks

Nowadays, fuzzy restricted Boltzmann machines (FRBMs) enjoy wide attention in deep learning and fuzzy systems. As a fuzzy neural network, FRBM is the extension of the classic RBM. However, FRBM has inherent defects because it relies heavily on the size of hidden units for feature extraction. In this paper, a novel infinite FRBM (IFRBM) is proposed by extending the hidden units from fixed parameters to infinite ones. The structure of the FRBM is further improved guaranteed by a novel infinite energy function without specifying the hidden elements. Specifically, the proposed model can increase generated hidden units adaptively during training when encountering different training data. Comparative experiments demonstrate that our IFRBM can obtain competitive performance than the state-of-the-art model in terms of feature extraction and image classification. Besides, the proposed model tends to more concise network structure while not requiring the tuning of hidden hyper-parameter or additional expert experience.
Analysis of Web Usage Mining Using Various Fuzzy Techniques and Cluster Validity Index

The internet is a large source of information and there is a vast growth in the degree of information each moment. The large number of web users are also increasing every day. To decrease web users browsing time, a lot of studies are going on. In Web usage mining technique mining strategies are performed in a proxy server dataset to detect the behavior of web users. Clustering plays a key role in a large scale of applications like web log dataset investigation, CRM, advertising and marketing, scientific diagnostics, computational biology, and lots of others. Clustering is the set of related data items. The key issue for clustering is a few sorts of measures that can decide whether two objects are relative or distinctive. This paper describes various validity measures including partition coefficient and partition entropy. Experiments perform for the various fuzzy clustering techniques such as Fuzzy C-Means, Fuzzy Possibilistic C-Means and Modified Fuzzy Possibilistic C-Means Clustering. These methods are developed and examined for proxy log dataset. Finally algorithms experimental outcomes are analyzed. Experiential result precisely denote that the clusters formed using proposed MFPCM method is much better in terms of various validity parameter compared with k-Means, Fuzzy C-Means, Fuzzy Possibilistic C-Means and Modified Fuzzy Possibilistic C-Means Clustering algorithms.
Problems of Matrix Structures in the Components of Modern Computer Systems

This paper is devoted to the features of matrix schemes, which have a significant impact on the capabilities of modern computer systems, creating tangible problems for them. One of the main characteristics of modern computers is their productivity in terms of cost. This characteristic is considered taking into account the using rate of computer resources, including matrix elements. Another characteristic associated with the energy efficiency of matrix circuits is especially important for mobile and other autonomous systems, as well as energy-intensive structures, including data centers. The next problem is related to the influence of matrix structures on functional safety, which is supported by computer systems in the field of critical applications. The involvement of matrix structures in the problem of hidden faults is investigated. The results of experiments evaluating the energy consumption of matrix structures and the manifestation of hidden faults, as well as the reduction of negatives during matrix reduction using the example of iterative array multipliers, are discussed.
Radio frequency fingerprint recognition based on deep transfer learning

Radio frequency (RF) fingerprint refers to the inevitable subtle defects in the hardware circuit of radio transmitter, which are reflected in the signal waveform transmitted by it. Therefore, the wireless device can be uniquely identified by analyzing the received signal waveform. Due to the advantages of multidimensional mapping of convolutional neural network (CNN), it can automatically extract signal features and transmitter nonlinear features, which can not be extracted by traditional low-dimensional algorithms. Therefore, it is very important to design a deep neural network with reasonable structure and high recognition accuracy. Taking the in phase and quadrature (I & Q) time domain signals of eight radiation sources of the same model as the input samples, the fine features of IQ time domain signals are extracted by designing six deep learning radiation source individual recognition algorithms with different structures to realize the identification of RF fingerprint. Besides, the change of wireless channel probably weakens the identification robustness of RF fingerprint. Thus, a deep transfer learning algorithm is proposed to cross train and test the I & Q data collected at different times, which solves the problem of poor robustness.
Evaluation Index System of Economic and Social Development Pilot Area Based on Spatial Network Structure Analysis

In order to improve the evaluation effect of the economic and social development pioneer area, this paper constructs the evaluation index system of the economic and social development pioneer area based on the spatial network structure analysis method and obtains an intelligent analysis system. Moreover, from the perspective of economic development information flow, this paper uses information flow direction analysis method and advantage flow analysis method to discuss the structural characteristics of urban economic development network in the economic belt, providing new methods and perspectives for the study of urban economic development flow. In addition, this paper attempts to propose a universal method for quantitative research on the "flow space" structure of urban economic development as the forward-looking content of urban economic development. According to the simulation test results, it can be seen that the evaluation index system of the economic and social development pilot area based on the analysis of the spatial network structure proposed in this paper has a good effect.
Development of Technical University Students’ Foreign Language Creativity in Distance Learning

It is proved the need to develop the creative component of foreign language education in a technical university. Forming and development of students' creative thinking when solving professionally significant cases as well as the development of creative activity are the key factors in the entry of students into the professional sphere of interlanguage and intercultural communication. Based on the system and situational analysis of the main digital tools used in educational practice, they have been identified effective mechanisms for ensuring creative activity in the process of intercultural communication of engineering areas students.
Application of intelligent algorithm in face texture extraction

In this paper, 45 male faces and 45 female faces were collected to evaluate the texture of human face, gray level cooccurrence Matrix (GLCM) was used to extract the texture features of male and female faces, such as energy, contrast, correlation and entropy. T test was performed with SPSS17.0 software, and the results were compared and analyzed, the experimental results show that there are statistical differences between men and women in the four features. Based on the analysis of texture and pore depth, Pearson Correlation Coefficient is 0.9795, and the correlation between pore depth and texture is very strong.
Sustainable Communications in the Digital Media Area: Measurement Criteria and Indicators

The appearance of certain factors that distort the message, violate its integrity and the possibility of perception by others, indicates the entropy of the communication system in digital media communication systems, the manifestation of which can lead to the curtailment of communication processes. In information theory, entropy is understood as a measure of the uncertainty of an experience (test), which is invariant as such. It was Claude Shannon who first began to use the knowledge of entropy gained in thermodynamics and statistical physics in his research on the amount of information. From the point of view of the socio-political context, entropy should be understood as an increase in the disunity of communication participants, expressed in the absence of a clear formulation of collective needs and interests in the communication process, the general atomization of civil society and, consequently, the low level of political activity of the majority of its members, or vice versa, lead to protests and conflicts in the media area. These circumstances indicate the uncertainty of the results of the communicative process and lead to instability of communication in the media environment.The interaction of individuals in media communication is possible only through the act of reaching mutual understanding. Mutual understanding processes are aimed at reaching agreement, which depends on the rationally motivated approval of a particular statement. In this case, in order to comprehend the main problems of the study, the theoretical concept of Yu.Habermas, devoted to the analysis of communicative action, and for which undistorted communication is important, communication without coercion. It is in the communicative interaction that the German scientist sees the main way that makes it possible to understand how society can influence itself, political power, the institutional design of the political system as a whole, how to lead to a certain state of stability of communication processes.L.N. Timofeeva, analyzing the postulates of Yu. Habermas points out that the communicative process should be aimed at creating an orderly normative system of stable interpersonal relations and a stable personality structure capable of coexistence in the socio-political space [1]. Therefore, in the article the author attempts to systematize the main criteria and indicators for measuring the stability of communication in the media area.
Image Recognition, Classification and Analysis Using Convolutional Neural Networks

This paper presents a comprehensive discussion and analysis of the various architectures of Convolutional Neural Networks for image classification. This paper intends to implement and analyze the performance of AlexNet, VGG16, VGG19 and ResNet50 as Image Classifiers on the dataset CIFAR10. Accuracy, Loss and Confusion Matrix were used as metrics to analyze the performance.
Adaptive Bandwidth Prediction and Smoothing Glitches in Low-Latency Live Streaming

HTTP adaptive streaming (HAS) technologies such as dynamic adaptive streaming over HTTP (DASH) and common media application format (CMAF) are now used extensively to deliver live streaming services to large numbers of viewers. However, in dynamic networks, inaccurate bandwidth prediction may result in the wrong request of bitrate, and short-term network fluctuations may produce glitches, causing unnecessary bitrate switching, thereby degrading clients' Quality of Experience (QoE). To tackle this, we propose adaptive bandwidth prediction and smoothing glitches in low-latency live streaming (called APSG) in this article. Concretely, firstly, the size of random bandwidth fluctuations is exploited as the weight of exponentially weighted moving average (EWMA) for adaptive bandwidth prediction; in addition to bandwidth prediction and buffer occupancy, glitches phenomena under a stable network environment are taken into account to enhance the viewing experience of clients. Finally, experimental results show that compared to traditional ABR algorithms under a stable network environment, APSG could reduce the number of bitrate switches and latency by up to 72.6% and 27.3%, respectively; under a dynamic network environment, APSG could reduce the number of bitrate switches and latency by up to 53.8% and 23.6%, respectively.
Optimal simulation and experimental research on the operation system of dumper of the stemming production line

Abstract In order to further improve the running speed and stability of the feed truck in the mud production line, optimization simulation and experimental research on the running system of the feed truck were carried out. First, based on the analysis of the operating system of the material truck, Then, according to the experimental plan, an optimization experiment on the project site was carried out, and it was confirmed in a quantitative form that the operating efficiency and stability of the optimized truck operating system have been significantly improved. Finally, the experimental results are applied and analyzed, and a mathematical model that can be used in actual engineering is obtained, so as to reflect the actual engineering application value.