Reviewerly/exHarmony huggingface dataset:
Efficient protocols for private wildcards pattern matching

A wildcard character in a pattern adds an additional feature in the field of pattern matching. In this paper, we consider two problems of secure pattern matching (SPM) with wildcards: (i) SPM with repetitive wildcards (SPM-RW) and (ii) SPM with compound wildcards (SPM-CW). Here we consider that a type of wildcard characters “*” is used to represent gaps in the pattern for the first problem of SPM with wildcards. Usually, a wildcard character “*” is used to replace with zero or more letters in the text for the pattern matching problem. Yasuda et al. (ACISP 2014) proposed a protocol with an existing data packing method for secure wildcards pattern matching using symmetric somewhat homomorphic encryption (SwHE) in the semi-honest model in which a wildcard character in the pattern is replaced with just one letter in the text. Furthermore, we enhance their work to replace a wildcard with any sequence of letters in the text then propose SPM-RW protocols by using the symmetric and public-key SwHE schemes in the semi-honest model. Also, we propose a packing method that improves the number of homomorphic multiplications by a factor of k compared to a naive usage of Yasuda et al.’s method to solve the SPM-RW problem in which k is the number of sub-patterns. Next, we consider the SPM-CW problem for processing private database queries, which allows a few types of wildcards (“$”, “*”, and “!”) to appear in the pattern. To solve this problem, we propose an SPM-CW protocol using a double-query technique with public-key SwHE encryption in the semi-honest model. Our experiments exhibit the practicality of the new protocols for SPM-RW and SPM-CW, which outperforms state-of-the-art.
PROBLEMS AND SOLUTIONS FOR ENSURING INFORMATION SECURITY OF ELECTRONIC LIBRARIES

Information technologies development has led to intensification of distant information exchange, sharp increase in the speed of data retrieval, storage and processing of large amounts of information. At the same time, just these opportunities gave rise to such problems as unauthorized access to information resources, threat to the library resources security, need to ensure the users’ personal information protection. Extension in the volume and value of information scientific- technical and educational resources leads to an increase in the threats of unauthorized access to them. This requires the creation of reliable means of protecting information sources.
Blockchain Security Using Secure Multi-Party Computation

In secure multi-party computation (SMC), multiple distributed parties jointly carry out the computation over their confidential data without compromising data security and privacy. It is a new emerging cryptographic technique used in huge applications such as electronic auction bidding, electronic voting, protecting personal information, secure transaction processing, privacy preserving data mining, and privacy preserving cooperative control of connected autonomous vehicles. This chapter presents two model paradigms of SMC (i.e., ideal model prototype and real model prototype). It also deals with the type and applications of adversaries, properties, and the techniques of SMC. The three prime types of SMC techniques such as randomization, cryptographic techniques using oblivious transfer, and anonymization methods are discussed and illustrated by protective procedures with suitable examples. Finally, autonomous vehicle interaction leveraged with blockchain technology to store and use vehicle data without any human interaction is also discussed.
Performance-based Comparative Analysis of Open Source Vulnerability Testing Tools for Web Database Applications

In the last two decades, with the increase of information communications technology, the cybersecurity threats to web-based data-bases have seen exponential growth. Though the web database resources are tested for possible cyber threat vulnerabilities, it is challenging to identify the security weak points and back-doors of web database and applications to achieve data confidentiality and integrity. The vulnerability testing tools are used to find specific vulnerabilities on software or applications. This paper studies, analyses and compares the open-source vulnerability testing tools, SQLMAP and JSQL, for web database applications. A set of dummy URLs are introduced to evaluate the penetrating ability of both tools, and an analysis is presented to aid the users to choose a suitable tool based on security requirements.
EnTrace: Achieving Enhanced Traceability in Self-Aware Computing Systems

The evaluation and validation of self-aware computing systems is still a challenging task. Traceability of the behavior makes sure that a running system is behaving as defined at design time, which is important for developers as well as system administrators. In this work, we coin the term “enhanced traceability” for self-aware computing systems based on explainable artificial intelligence, data visualization, and human-computer interaction research. We present EnTrace, a reusable and open source platform that provides enhanced traceability capabilities for self-aware computing systems. EnTrace visualizes the current state of a self-aware computing system and enables users to comprehend the influence of adaptations on functional constraints and non-functional goals. We evaluate EnTrace qualitatively and quantitatively to show its features, its support for distributed and decentralized target systems, as well as its responsiveness.
MODERN LIBRARY IN THE CONTEXT OF DOCUMENTARY– INFORMATION APPROACH

The results of the analysis of the documentary – information approach heuristic potential in the study of modern library are presented. The modern library documentary- information form of organizing information process is modelled. The differences between it and proto- documentary and post-documentary forms of information process are indicated. Attention is focused on the library as a social institution that maintains the necessary level of confidence in the information it provides.
Restoration of Motion Blurred Image based on Improved Inverse Filtering Model

Aiming at the demand of deblurring motion blurred images, a motion blurred image restoration method based on improved inverse filtering model is designed. Preprocess the blurred image; analyze the cause of the motion blurred image, introduce Radon transform and Sobel operator to estimate the displacement angle and displacement distance of the pixel; reconstruct the inverse filter model, add the restoration transfer function, and realize the motion blur image recovery. By comparing with the classic restoration algorithm, it turns out that the image restoration restoration model in this article is more effective.
CENTER OF INTERNATIONAL AND INTERETHNIC COOPERATION OF SPSTL SB RAS

The article describes the project of creating in the SPSTL SB RAS the Center for International and Interethnic Cooperation for to maintain and expand relations with foreign library and information establishments. It presents the first results of the work and states plans for its further development.
Intelligent system for university legal education based on machine learning

University legal education is of great significance to the personal development and social stability of college students. At present, there are certain problems in the traditional teaching system, which has led to inefficient university legal education. In order to improve the legal teaching effect of the university, based on machine learning and neural networks, this paper integrates and optimizes the original hardware and software and operation process, and further highlights the functions of interconnection and sharing, automatic sensing, real-time recording, interactive feedback, dynamic supervision, and intelligent analysis, which greatly facilitates the evaluation of teaching at all levels. In particular, this study uses big data technology to conduct an intelligent analysis of data completeness, multimedia application rate, system execution, and average test scores, and scientifically evaluates the implementation of basic-level education systems and the effectiveness of education, which can effectively solve the problems of quantitative formalization and qualitative subjectivity of current education evaluation from a technical level. In addition, this study designs a control experiment to analyze the system performance. The research results show that the model proposed in this paper has a certain effect.
ANALYSIS OF REQUIREMENTS FOR CONSTRUCTING THE SCIENTIFIC INFORMATION SYSTEM PROTOTYPE

The article describes technological approaches used to create distributed information systems supporting scientific research. Architectural solutions intended to create such systems and principles for integrating these systems with external sources are considered. Functional requirements for the model of scientific information system (SIS), conditioned, firstly, by the researchers’ information needs, and secondly, by the necessity to ensure a reliable and longterm storage of information, are determined. Rules for presenting and transforming metadata are examined.
A hybrid eye movement feature recognition of classroom students based on machine learning

Online classroom teaching is difficult to identify students’ learning status in real time. Therefore, we need to combine intelligent image recognition technology to analyze student status through eye movement features. This study solves the problem of inaccurate positioning of the initial position of the shape model in the process of eyelid matching through machine learning. Moreover, this study improves the algorithm and uses the AK-EYE model based on the combination of ASM algorithm and Kalman filtering to establish a local feature model for each feature point. According to the gray information in the normal direction of the feature point, the local gray information is modeled. After training through the sample set to obtain the state model, the target eye can be searched, and the pose parameters can be determined. Finally, this study designs a control experiment to analyze the performance of the model proposed in this study. The research shows that the algorithm proposed in this paper has a high recognition accuracy and has a practical basis, which can be used as one of the subsequent classroom teaching system algorithms.
Fractal-interpolation of seismic traces using vertical scale factor with residual behavior

The inaccessibility of the terrain causes an irregular spatial seismic sampling, leading to poor reliability in the images of the subsoil generated by the processing algorithms; an accurate reconstruction of regular data is therefore crucial. This paper presents a fractal reconstruction method based on the self-similarity fractal property of the seismic data, on local and global scales. The method interpolates non-collected samples on the basis of the vertical scale factor value, thus making a solution possible to a system of coupled equations. However, tests with synthetic data show errors, with a tendency related to the scale factor. To reduce the imbalance, this approach takes into account the behavior of the discrepancy between the expected and the estimated values. The method applied to synthetic and real data sampled irregularly indicates that the fine structure of the seismic data can be quickly and accurately reconstructed using the localized fractal approach. The interpolation method can be fruitful in other fields where data need to be reconstructed from data sets not suitably sampled.
Swift UI and Their Integration to MapKit Technology as a Framework for Representing Spatial Information in Mobile Applications

Mobile applications are becoming as complex as the kind of problems we need to solve. A normal GIS application needs to incorporate elements such as artificial intelligence more specifically, pattern recognition or machine learning, relational or non-relational databases, spatial representation, and reasoning. In addition to that, it is necessary to design and develop a mobile application to integrate all these elements. After analysis, planning, and design a company will require to develop a full team of engineers to accomplish an application. On the other hand, universities and other organizations, have additional interests. It is necessary to develop a mobile application to test a hypothesis before a large development project. The necessity is to use a technology that permits the integration of advanced technologies and programming tools in a manageable sense. Companies such as Google and Apple are reducing the gap of learning knowledge. They are developing new technologies. For example, Apple presented in 2019 at WWDC2019 and WWDC2020 a novelty technology called SwiftUI, which aims to reduce the complexity of developing a mobile application and allowing us to integrate technology such as Mapkit to represent spatial information. This work presents the advantages of using SwiftUI to integrate Mapkit as a spatial representation framework to ease the development of GIS mobile development. And focus on the problem solution, such as spatial representation and reasoning, robot planning, content image retrieval, etc.
Custom Walk-in Closet

Custom Walk-in Closet Leads For Closet designer and Professional Organizer Generation of Exclusive Custom Walk-in Closet leads is both an art and a ...
Automatic grading of admitted patients using genetic algorithm

The current application of intelligent algorithms has achieved certain applications in smart medical, but its application in the automatic grading of admitted patients is in a blank, which makes it difficult to allocate hospital resources effectively. In order to improve the efficiency and accuracy of automatic classification of patients admitted to hospital, this study builds the corresponding genetic algorithm operator based on genetic algorithm. At the same time, this paper uses the random method to generate the initial population and uses the inversion mutation operator to perform the mutation operation. In addition, this article combines image processing to automatically classify patient types and patient levels. Finally, this paper uses the data collection method to verify the model and input the data into the research model. The research shows that the model proposed in this paper has certain effects, which can realize the automatic grading of patients admitted, and can provide theoretical reference for subsequent related research.
Web Masquerade Based on the MAC Addresses : How to change the web contents without changing the corresponding uniform resource locators

Web masquerade is defined as the network skill enabling to display various kinds of web contents on the monitors without changing URLs which are input into the web browsers. It is well known that there is a method of web masquerade which can change the web contents according to a change of the switchport to which a personal computer is directly connected. In this paper, we introduce another method of web masquerade which can change the web contents according to a change of the MAC address attached to a personal computer. In other words, we introduce the new system playing the role at the datalink layer which is analogous to the role being played by the vlan membership policy system at the network layer.
Factors Shaping Information Security Culture in an Internal IT Department

Companies are exposed to the risk of falling victim to cyber attacks every day and therefore invest in optimizing their information security (IS) level. In addition to technological investments, the focus is now increasingly on employees, as their attitude and behavior has a significant influence on the IS level of a company. There is already extensive research on the influencing factors and the establishment of an IS culture in companies. However, little attention has been paid to the group of IT employees, although it has been proven that their attitude, behavior and judgment regarding cyber attacks and IS in general differ from non-IT employees. Even within an IT department, one can expect to see different degrees of these factors, as a distinction must be made between IS employees and employees with traditional IT functions (software development, server operation, etc.).Based on 25 recent IS studies, a literature review has identified four factors that influence the IS attitude and behavior of employees in an internal IT department and thus have an impact on the IS culture. These four components are IT tools, IS skill, appreciation and sub-cultures.The results show that more qualitative research with a focus on employees of an IT department is necessary to advance the findings in the area of IS culture. In addition, CIOs and CISOs benefit from the results, as they specify fields of action that can be tested and optimized in their own organizations.
A Case Study Into the Effects of Implementing Web-Based Instructional Technology in a Primary School Classroom in Trinidad and Tobago

Redesigning teaching for the 21st century in Trinidad and Tobago involves several mechanisms to be put in place to ensure our students are equipped with competencies and skills to lead a sustainable life. One such mechanism is the implementation of computer and web-based technologies in the public primary school classroom. Traditionally, computers are not used within the classroom for learning; neither are computing nor Information Communication Technology (ICT) taught as subject areas. The case study presented in this chapter explores the effects of implementing web-based technology into classroom instruction. Specifically, it was implemented into the Language Arts classroom to help students to develop grammar skills in their writing tasks. The research found three effects: 1) an established technological infrastructure needs to be in place for successful implementation, 2) the role of technology on student learning, and 3) the influence of technology on student behavior in the classroom.
Exploring Parameter Sharing Techniques for Cross-Lingual and Cross-Task Supervision

Many languages still lack the annotated training data needed for supervised learning. This issue is often addressed by using auxiliary supervision and the so called transfer learning. In this work we focus on the problem of combining two types of auxiliary supervision – cross-lingual and cross-task. Previous work has shown promising results for this combination. Here, we aim to explore various advanced parameter sharing techniques to improve the results. We propose three distinct techniques with various properties and evaluate their performance on four Indo-European languages and four distinct NLP tasks (dependency parsing, language modeling, named entity recognition and part-of-speech tagging). We conclude that the proposed techniques significantly improve the performance for zero-shot learning.
Efficient destriping of remote sensing images using an oriented super-Gaussian filter

Satellite imagery provides information crucial for remote sensing applications. However, the images themselves can suffer from systematic and random artefacts which reduce the utility and accuracy of datasets. In particular, radiometric miscalibration due to temporal variation of the detector response may result in stripe noise. We report a method for suppressing striping in remote sensing images by use of a Fourier filter shaped like a superGaussian function. In comparison to both established ‘traditional’ and deep-learning-based destriping techniques, our method demonstrates superior destriping performance for both remote sensing images with native striping as well as those with stripes added to them. Our method simultaneously meets the three criteria of fidelity, speed and flexibility, enabling an efficient improvement in the radiometric accuracy of images from a wide range of satellite sources.
Instance Explainable Multi-instance Learning for ROI of Various Data

Estimating the Region of Interest (ROI) for images is a classic problem in the field of computer vision. In a broader sense, the object of ROI estimation can be generalized to the bag containing multiple data instances, i.e., identify the instances that probably arouse our interest. Under the circumstance without instance labels, generalized ROI estimation problem can be addressed in the framework of Multi-Instance Learning (MIL). MIL is a variation of supervised learning where a bag containing multiple instances is assigned a single class label. Though the success in bag-level classification, when bags contain a large number of instances, existing works ignore instance-level interpretation which is the key to ROI estimation. In this paper we propose an instance explainable MIL method to solve the problem. We devise a generalized permutation-invariant operator with the idea of utility and show that the interpretation issues can be addressed by including a family of utility functions in the space of instance embedding. Following this route, we propose a novel Permutation-Invariant Operator to improve the instance-level interpretability of MIL as well as the overall performance. We also point out that existing approaches can be regarded as a special case of our framework and qualitatively analyze the superiority of our work. Furthermore we give a criterion to measure the linear separability in the instance embedding space. We conduct extensive evaluations on both classic MIL benchmarks and a real-life histopathology dataset. Experimental results show that our method achieves a significant improvement in the performance of both instance-level ROI estimation and bag-level classification compared to state-of-the-art methods.
Decoding CNN based Object Classifier Using Visualization

This paper investigates how working of Convolutional Neural Network (CNN) can be explained through visualization in the context of machine perception of autonomous vehicles. We visualize what type of features are extracted in different convolution layers of CNN that helps to understand how CNN gradually increases spatial information in every layer. Thus, it concentrates on region of interests in every transformation. Visualizing heat map of activation helps us to understand how CNN classifies and localizes different objects in image. This study also helps us to reason behind low accuracy of a model helps to increase trust on object detection module.
Research on the design method of servo position loop parameters of shipborne TT&amp;C radar

This paper systematically analyzes the servo position loop and its control object of the shipboard TT & C radar system from the practical engineering application. The selection and parameter design of the position loop regulator are deeply studied. The method flow and computer realization scheme of the parameter design of the servo position loop are proposed, which provides theoretical support and practical feasibility for the design and improvement of the servo position loop of the shipboard TT & C radar system Scheme.
How Do Negative Emotions Influence on the Conceptual Models Verification?

The present live study is proposed with the objective of investigating the influence of negative emotions (i.e., stress) in the efficiency for verifying conceptual models. To conduct this study, we use a Model-driven Testing tool, named CoSTest, and our own version of stress detector within a competition setting. The experiment design, overview of the empirical procedure, instrumentation and potential threats are presented in the proposal.