Reviewerly/exHarmony huggingface dataset:
Image Super-resolution Reconstruction Based on Adaptive Fractional Order

The reconstruction of super-resolution images from low-resolution images is essentially a morbid invers problem , which can often be dealt with by adding regular terms. In this paper, using the traditional total variational method for reference, fractional total variational regularities and fractional fidelity terms are added to the model to constrain the solution space, and an adaptive fractional order function based on local variance is proposed. In addition, the Fourier transform is used to calculate in the frequency domain, which reduces the computational complexity. The experimental results show that the image reconstruction model proposed in this paper can reconstruct the texture details and edges more clearly, and at the same magnification, the values of peak signal to noise ration (PSNR) and structural similarity index measure(SSIM) are higher than those of the comparison methods.
Research and Analysis of Software Defect Measurement Elements Based on Analytic Hierarchy Process

Abstract It is not convenient for the general software quality evaluation system to be directly and quickly applied to the software quality evaluation to be tested. Therefore, this paper proposes a method suitable for the analysis of factors affecting software quality based on analytic hierarchy process. The analytic hierarchy process is used as the main framework, the distribution of the software’s own properties and accumulated test findings as input,the constructed defect weight ratio is used as the judgment matrix, Then do the hierarchical analysis. Through the analytic hierarchy process to analyse the weight of the factors of the software itself, test organizations can quickly make a fuzzy assessment of software quality, and provides the reference basis for the reasonable allocation of test resources.
Evaluation and Search for Points to be Improved in the Fisheries and Marine Skill Learning Support System Using Text Mining

We developed a fishery and marine skill learning support system as a self-training teaching material. In this study, we evaluated the usefulness of the proposed system by using text mining and searched for the points to be improved in this system. Using this system, we conducted a survey among the students of a fisheries high school using an evaluation sheet with free-form answering. From the results, we extracted five points, namely “learning method using this system”, “video operation and technology confirmation”, “promotion of understanding by this system”, “skill learning at home”, and “fun to learn fisheries skills”. Among these five points, “promotion of understanding by this system”, in which an understanding of the skill is promoted through explanations of skill and skill videos, was evaluated positively. It was also found that a review is effective in utilizing this system. As a point to be improved, it was found that narration should be provided along with the presentation of the subtitles.
KPDR : An Effective Method of Privacy Protection

To solve the problem of user privacy disclosure caused by attacks on anonymous areas in spatial generalization privacy protection methods, a K and P Dirichlet Retrieval (KPDR) method based on k-anonymity mechanism is proposed. First, the Dirichlet graph model is introduced, the same kind of information points is analyzed by using the characteristics of Dirichlet graph, and the anonymous set of users is generated and sent to LBS server. Second, the relationship matrix is generated, and the proximity relationship between the user position and the target information point is obtained by calculation. Then, the private information retrieval model is applied to ensure the privacy of users’ target information points. Finally, the experimental results show that the KPDR method not only satisfies the diversity of <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <mi>l</mi> <mfenced open="(" close=")" separators="|"> <mrow> <mn>3</mn> <mo>/</mo> <mn>4</mn> </mrow> </mfenced> </math> , but also increases the anonymous space, reduces the communication overhead, ensures the anonymous success rate of users, and effectively prevents the disclosure of user privacy.
A Database Collusion Detection and Measurement Based on Bloom Filter

In the era of rapid development of information technology brings about the protection of digital products. In order to solve the problem of traditional anti-collusion fingerprint code is difficult to detect multi-user collusion attacks, this paper proposes a method of detecting collusive users by storing the embedded attribute values of database as user characteristics. In order to further measure the collusion rate of user data, the characteristic weight value of user is included in the leaking database. The position of any embedded digital watermarking technology is taken as the feature, and the features of high efficiency and small storage of the bloom filter-is used to extract the features in the database at high speed. This paper uses a low distortion database watermarking algorithm to embed the watermark. The experimental results show that the embedded database has little distortion and can extract watermark accurately. In the case of collusion attack, this method can accurately detect collusion users and estimate the collusion rate.
Design of ideal secret sharing based on new results on representable quadripartite matroids

With the rapid development of the next generation of mobile networks and communications (5G networks), group-oriented applications show the great potential ability in 5G and multipartite group communications occur frequently in a single network, where a multipartite access structure is denied to be a collection of the subsets of users who may come from different parts of the network such that only users in an authorized subset of users can use their shares to build up a group key for a secure group communication. Most existing group key establishment schemes based on a secret sharing target on building up a group key for a threshold access structure and need to compute a t-degree interpolating polynomial in order to encrypt and decrypt the secret group key. This approach is not suitable and inefficient in terms of computational complexity for multipartite group environments which need to realize the multipartite access structures. In this paper, we study the characterization of ideal access structures related to representable multipartite matroids. By employing some existing results, such as the well-known connection between ideal secret sharing and matroids, the recent discovery of ideal multipartite access structures, and the connection between multipartite matroids and discrete polymatroids, we obtain the characterization of a family of representable multipartite matroids, including a sufficient condition for an access structure to be ideal. Based on this result, we provide a complete characterization of representable quadripartite matroids, showing that these access structures related to representable quadripartite matroids are the ideal ones. From these ideal access structures, we can then construct ideal secret sharing schemes for multipartite group communications. Our results are attractive for efficient and secure multi-group-oriented applications.
Robust Face Recognition via Multi-scale Contextual Information Ensemble Learning

The study of robust face recognition has always gained much attention and has been widely applied to many social and public safety protection fields. Image patch based methods have achieved much more attractive performance. Especially, multi-scale patch based methods take the impact of different scales of the image patch into consideration. However, these methods ignore a fact that different parts of the face image contain different contextual semantic information which may be useful for the recognition task. To this end, in this study, we presented a robust face recognition approach by fully utilizing the multi-scale contextual information. Different from previous patch based methods, in our method, we select several patches around the test patch with a certain step in each window. Then the concatenated patch set is linearly represented over the corresponding patch sets on the training samples. By this consideration, the contextual topology can provide complementary contributions to the recognition, especially when the test faces have occlusions. Also, the multi-scale ensemble learning scheme is exploited to further enhance the recognition performance. Our extensive experiments have validated the superiority of our proposed approach over some state-of-the-art patch based robust face recognition approaches.
A Novel Attention Model of Deep Learning in Image Classification

As the neural network becomes more and more complex, a large number of parameters are to be adjusted and more unrelated information will be generated, which is more time-consuming in model training and affects the model performance. The attention mechanic is often used to address this problem in the literature. However, the current attention models only consider the correlation within the pixel domain and channel domain individually, and the computational complexity is comparatively high. This paper proposes a new type of attention module called Pixel-wise And Channel-wise attention (PAC attention module for short) in which the hybrid correlation between the pixel and channel domain is also considered. Without increasing the number of parameters, this module can be used to calculate the correlation of the convolution feature map at any position in any layer of the convolutional neural network to achieve end-to-end training. In the experiments, the proposed PAC attention module is used in typical network structures in deep learning and has been compared to current models on some benchmark big datasets.
Optimized Design of Worm Gear and Worm Drive of a Certain Shipborne Antiriot Launcher Based on MATLAB

Worm gear and worm drive mechanism is widely used in mechanical drive. In traditional design, the valuation trial method is generally used, and then the design scheme is checked to verify whether the design parameters are within the performance range for the given conditions. In a sense, the design parameter values obtained by this method are not the most reasonable and economical. Under the premise of systematic study of the possible failure forms and design criteria of worm gear and worm drive, design criteria and use of materials, we determine the optimization design objectives, design variables and constraints, and use the MATLAB optimization toolbox to complete the optimized design of worm gear and worm drive. We finally obtain the optimization results and compare them with the original design data. The optimization results show that MATLAB can significantly improve the analysis efficiency and quality of worm drive design, which will reduce the cost.
Vietnamese Speech Synthesis with End-to-End Model and Text Normalization

Speech synthesis systems are now getting smarter and more natural thanks to the power of deep neural networks. However, each language has a different phonological and contextual characteristics, we have conducted experiments, statistics, and applied Vietnamese phonetics to improve speech synthesis systems based on Tacotron2 neural networks. Our methods achieve the accuracy of 97% in text normalization task, and the synthesized speeches with a MOS score of 3.97, asymptotic to 4.43 of the voices that are directly recorded. We also provide a library for standardizing Vietnamese text called Vinorm and a package that converts text into a phonetic format called Viphoneme, which is used as an input for end-to-end neural networks, make the synthesis process faster, more intelligent and natural than using character inputs.
Maximum Likelihood Method in Targets Tracking with Complete Information

In this paper, multiple targets need to be tracked and the appearance of targets are no different. The research is based on two pictures: one is the initial picture and the other one is the end picture. There are multiple targets in both initial picture and end picture. The correspondence between the targets in initial picture and the targets in end picture has been studied.
Entity Hierarchical Clustering Method Based on Multi-channel and T-SNE Dimension Reduction

Named entity clustering is a basic work in the field of natural language processing, which is helpful to excavate the implicit relationship between entities. Most of the existing clustering algorithms are unable to combine various features of entities and have some problems such as poor hierarchical clustering analysis. Based on this, this paper proposes a multi-channel dimensionless entity clustering method and carries out experimental verification. A multi-channel framework is constructed, and channels based on knowledge graph, language model and statistics are respectively set up to express the features of entities in objective knowledge, co-existing relationship and different texts. Network embedding method, BERT model and automatic coding machine are respectively used to convert the entities into vector forms. The t-SNE algorithm is used to reduce the dimension and map it to the two-dimensional space, so that it can be expressed visually in the low-dimensional space. An improved hierarchical clustering method is proposed to cluster entities in two-dimensional space and construct hierarchical clustering trees. Experiments show that the F1 value of this algorithm can reach 78.72% at most under the test set. At the same time, through analysis, the algorithm has a strong ability of expansion and generalization.
Geology and Gold Mineralization of Lower Carboniferous Deposits of the Kommercheskoye Deposit (Kumak Ore Field)

The work considers a promising object—the Kommercheskoye deposit in the black shales of the Kumak ore field. The main ore-bearing structures are two meridional zones of the East Anikhov faults, into which quartz veins penetrate and where fracture metamorphism, metasomatism, and mineralization are intensely manifested. Significant concentrations of gold are confined to intercalation bundles of metamorphosed primary terrigenous and clay rocks, which are now transformed into a diverse composition of micaceous-quartz and quartz-micaceous chlorinated schists. The prevailing importance among them is occupied by the most favorable for mineralization carbonaceous micaceous carbonate-quartz siltstone shales, and shields for ore-bearing solutions are clays and limestones. More gold concentrations are expected at deeper horizons of the Kommercheskoye deposit, less susceptible to weathering.
FEATURES OF PRACTICAL STUDENTS' TRAINING IN OLEXIY HRYHOROVYCH MOROZ'S SCIENTIFIC AND PEDAGOGICAL RESEARCH

The article deals with the scientific and pedagogical heritage of Moroz Oleksiy Hrygorovych, the issue of the importance of out-ofclass modern students' work, the concepts and content of their individual work, pedagogical conditions of ensuring the individual educational activity of students of third level educational institutions. The article analyzes Oleksiy's Hrygorovych Moroz scientific and pedagogical heritage. It emphasizes the importance of effective organization and pedagogical conditions for providing individual student's work. It is concluded, that: – in conditions of students' creative cognitive activity intensification during the educational process individual work can not only be reduced to the implementation of normative home assignment; – students' independence and creative activity are to be started not in the audience when listening to and acquiring lectures but when preparing for them in the laboratory, library, during practice in school etc. According to O.H. Moroz, this activity, with the transfer of students to senior courses, should assume the nature of research; – with the material for independent study, the modern student is more motivated to perform creative research tasks, like preparation of papers, abstracts, research of school experience, presentation at student scientific conferences, preparation for colloquiums, writing of coursework, graduation works to further studying the problematic topics of lectures. Such individual and practical activity will be more pedagogically effective for the professional competence formation of a future specialist. Moroz also emphasized the importance of systematic and continuous nature of individual student work, which can be ensured not by increasing time for work but by its more rational distribution between subjects, according to the semester schedule, taking into account the significance of their specifics.
Orthogonal projections for image quality analyses applied to MRI

Abstract Measuring digital image quality is of importance in numerous applied research fields, such as image acquisition, image processing or image reconstruction. Subjective evaluation, i.e. assessment by human beings, is often too time‐consuming, expensive and inconsistent in complicated tasks such as medical imaging. In order to better understand the relation between objective image quality assessment measures, we compare a selection in an experimental setup. It is well known that L 2 error estimation, i.e. computing the mean squared error (MSE) between two images, does not correspond well to the perceptual evaluation by the human visual system. Here, we illustrate on the example of MRI data the interaction of the MSE with the signal to noise ratio (SNR), the variance and subjective evaluation. We use random coverings of the space of orthogonal projections for coil combination to enable a comprehensive correlation analysis.
Fast Discontinuity-Aware Subpixel Correspondence in Structured Light

Structured light-based 3D scanning presents various challenges. While robustness to indirect illumination has been the subject of recent research, little has been said about discontinuities. This paper proposes a new discontinuity-aware algorithm for estimating structured light correspondences with subpixel accuracy. The algorithm is not only robust to common structured light problems, such as indirect lighting effects, but also identifies discontinuities explicitly. This results in a significant reduction of reconstruction artifacts at objects borders, an omnipresent problem of structured light methods, especially those relying on direct decoding. Our method is faster than previously proposed robust subpixel methods, has been tested on synthetic as well as real data and shows a significant improvement on measurement at discontinuities when compared with other state-of-the-art methods.
The Effect of Innovative Contracts on the Business Behaviors in the Context of IoT

Digital transformation using emerging technologies such as internet of things (IoT) is transforming the way business is conducted within industrial value chains. Consequently, business model innovation and the transition to networked business model are required. Yet, many gaps are being researched to analyze how industrial companies can leverage digital transformation to transform their business models to achieve sustainability benefits. Typically, issues related to value creation and the delivery of business models require more clarification. It is also important to recognize how these components integrate to the sustainability of industrial initiatives. The main objective of this chapter is to pave the way for business behaviors associated with internet of things environment and the related innovative contracts. The discussions and conclusions discussed here will help organizations to establish a long-term, complex relationships with their suppliers, customers, and other value chain actors.
Implementation of Dual Image Watermarking for Copyright Protection

In this paper, a copyright protection scheme for images has been developed through dual watermarking method. Here, the watermark, i.e., the copyright information has been embedded visibly and invisibly into the cover image. The visible watermark enhances robustness against signal processing attacks, whereas the invisible watermark is used to prevent different types of malpractices. The proposed scheme has completely been developed in spatial domain, and thus, the system complexity is very low. The system proficiency has been evaluated in terms of the three major qualities: imperceptibility, robustness, and data hiding capacity. The output results, being compared with some other existing methods, confirm the efficacy of the proposed scheme.
Research on Application of 3D Laser Point Cloud Technology in 3D Geographic Location Information Modeling of Electric Power

Three-dimensional laser scanning technology is a new surveying and mapping technology, also known as “real scene replication technology”, which can completely and accurately reconstruct scanned objects and quickly obtain original surveying and mapping data. Multi-site cloud data registration is an important link in 3D laser scanning data processing. The seven-parameter registration model based on control points with the same name is an algorithm model with high accuracy. Through piecewise low-order interpolation method, the curve smoothing processing of empty area model is realized, and then combined with the existing hierarchical detail model algorithm, the 3D model file of power equipment is loaded and rendered in the 3D scene. The purpose of this paper is to provide reference for the subsequent construction of power 3D geographic information platform.
A Multi-layer Cryptosystem for Secure Data Transmission using PRNG

Nowadays the usage of the Internet is developing day by day. One of the largest uses of the internet is to transfer data from different sources to different states. During data transfer over the internet, a major issues arises with data protection. When transferring data over the internet with security that is called data security. Two techniques are used in data protection. Cryptography and Steganography. In our proposed system Cryptography and Steganography are combine used for making the data more secure. The basic function of Cryptography is encryption and decryption. Here, the message is encrypted more than 4 Times. Basically in Cryptography method the secret message are encrypted with an encryption key. The sender uses the encryption key for sending a message. On the other hand, the receiver should know the encryption key for decrypting the message to get the original data. Instantly Steganography is the way to hides secret data using digital media cover such as Audio, Image and Video and Text. In our proposed system, Color Image has been used for embedding the secrete message. In the proposed technique mostly used random binary digit from multiple pixel instead of LSB technique after converting the stego image into a binary form. Before embedding the secret message the Robust Cryptography Algorithm Advanced Encryption Standard (AES) & Pseudorandom Number Generator (PRNG) has been used to encrypting the secret message and secure the confidential data from the unauthorized access.