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computing and Informatics (ICCI), International Conference on

作者： Noha Ahmed Bayomy Amira M. Idrees Ayman E. Khedr Department of Information Systems Faculty of Computers and Artificial Intelligence Helwan University Cairo Egypt Department of Information Systems Faculy of Computers and Information Technology Future University in Egypt Cairo Egypt Department of Information Systems College of Computing and Information Technology at Khulais University of Jeddah Jeddah Saudi Arabia

Nowadays, Businesses are mutating to social media platforms and websites as a new source of information and knowledge to get competitive advantages. Hence, the term NoSQL databases known as Internet era databases revealed as a solution because of raising urgency in the demand for scalability and performance. This paper presents an overview study for the evolution of databases, different forms of NoSQL databases in addition to their features, advantages and disadvantages. This paper also seeks to cover the shortage of focusing on the quality attributes based methodologies to NoSQL databases that have been largely overlooked in the previous studies and creates a brief comparison that illustrates this issue.

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Reliability of a Reconfigurable Network with Segment Switching

Reliability of a Reconfigurable Network with Segment Switchi...

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2023 Wave Electronics and its Application in information and Telecommunication systems, WECONF 2023

作者： Tu, Le Anh Bogatyrev, V.A. Abramova, E.A. ITMO University Faculty of Software Engineering and Computer Technology Saint Peterburg Russia Saint-Petersburg State University of Aerospace Instrumentation Department Information Systems Security Saint Petersburg Russia

ISBN: (纸本)9798350348293

The article proposes models of the structural reliability of a multipath routing network with the possibility of its reconfiguration when switching path segments. The models are focused on optimizing the placement of segment switching nodes, aimed at achieving maximum network performance with the option of connecting request sources to the available communication paths with servers. The study considers the options for connecting each source of requests with one of the paths or with all paths for connecting to servers. The paper shows the existence of an optimal placement of path switching nodes, in which the maximum reliability of the system is achieved. © 2023 IEEE.

关键词： Redundancy

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Bluetooth Vulnerabilities and Security

Bluetooth Vulnerabilities and Security

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Emerging Smart computing and Informatics (ESCI), Conference on

作者： Mareeswari V Vijayan R Ashish Shukla Department of Software and Systems Engineering School of Computer Science Engineering and Information Systems (SCORE) Vellore Institute of Technology (VIT) Vellore India Department of Information Technology School of Computer Science Engineering and Information Systems (SCORE) Vellore Institute of Technology (VIT) Vellore India Master of Computer Applications School of Computer Science Engineering and Information Systems (SCORE) Vellore Institute of Technology (VIT) Vellore India

ISBN: (数字)9798331515683

ISBN: (纸本)9798331515690

Bluetooth technology, which facilitates wireless communication between Billions of devices including smartphones, tablets, laptops, and Internet of Thing (IoT) devices, is a cornerstone of modern connectivity. Its importance lies in its ability to enable seamless data exchange and interaction across a wide range of applications, from personal gadgets to complex industrial systems. Despite its widespread adoption, Bluetooth is not immune to critical security vulnerabilities. Issues like Bluetooth Low Energy (BLE) vulnerabilities and denial-of-service (DoS) attacks can overwhelm devices with excessive traffic, while BLE Forced Connection can lead to unauthorized access, and eavesdropping exposes sensitive data being exchanged. We have discussed these vulnerabilities in detail, examining their mechanisms, potential impacts, and various implementation aspects. Additionally, we have added demonstrations to illustrate how these attacks can be executed and the potential consequences. To prevent these threats, we explored essential measures, including regular firmware updates, secure pairing protocols, and careful management of Bluetooth settings. Adopting best practices like disabling Bluetooth when not in use and monitoring connected devices can further enhance security, ensuring the reliable and safe operation of the vast and growing ecosystem of Bluetooth-enabled devices.

关键词： Wireless communication Ethics Protocols Ecosystems Denial-of-service attack Security Internet of Things Bluetooth Low Energy Microprogramming Guidelines

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In silico prediction methods of self-interacting proteins:an empirical and academic survey

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Frontiers of Computer Science 2023年第3期17卷 199-216页

作者： Zhanheng CHEN Zhuhong YOU Qinhu ZHANG Zhenhao GUO Siguo WANG Yanbin WANG College of Computer Science and Software Engineering Shenzhen UniversityShenzhen 518060China School of Computer Science Northwestern Polytechnical UniversityXi’an 710129China Institute of Machine Learning and Systems Biology School of Electronics and Information EngineeringTongji UniversityShanghai 201804China School of Cyber Science and Technology Zhejiang UniversityHangzhou 310058China

In silico prediction of self-interacting proteins(SIPs)has become an important part of *** is an urgent need to develop effective and reliable prediction methods to overcome the disadvantage of high cost and labor intensive in traditional biological wet-lab *** goal of our survey is to sum up a comprehensive overview of the recent literature with the computational SIPs prediction,to provide important references for actual work in the *** this review,we first describe the data required for the task of DTIs ***,some interesting feature extraction methods and computational models are presented on this topic in a timely ***,an empirical comparison is performed to demonstrate the prediction performance of some classifiers under different feature extraction and encoding ***,we conclude and highlight potential methods for further enhancement of SIPs prediction performance as well as related research directions.

关键词： proteomics self-interacting proteins feature extraction prediction model

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Reliability of Multipath Networks with Optimization of the Location of Inter-Path Communication Nodes

Reliability of Multipath Networks with Optimization of the L...

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2023 International Russian Smart Industry Conference, SmartIndustryCon 2023

作者： Bogatyrev, Vladimir A. Tu Le, Anh Abramova, Evgenia A. Saint-Petersburg State University of Aerospace Instrumentation Department Information Systems Security Saint Petersburg Russia University ITMO Faculty of Software Engineering and Computer Technology Saint Peterburg Russia

ISBN: (纸本)9781665464291

The article explores the possibility of improving the reliability of a network with multipath routing. A feature of the proposed study is the analysis of the influence of the placement of switching nodes that switch path segments on the probability of network connectivity with servers of the same type and heterogeneous in functionality. The purpose of the article is to increase the reliability of the network, taking into account the influence of the placement of communication nodes that implement the switching of route segments during reconfiguration, on the connectivity of the network with servers that are homogeneous and heterogeneous in functionality. The research involves the construction of a structural reliability model that takes into account the possibility of failures of both communication nodes and the links between them. The reliability model is built taking into account the availability of request sources with full and non-full access connections to the set of network paths. © 2023 IEEE.

关键词： Reliability

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Machine Learning Clustering Analysis Towards Educator’s Readiness to Adopt Augmented Reality as a Teaching Tool

Mendel

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Mendel 2023年第2期29卷 147-154页

作者： Sangodiah, Anbuselvan Yi, Wei Chooi Ayob, Ayu Norafida Binti Jalil, Norazira Binti A. Subramaniam, Charles Ramendran S P. R. Lirong, Gong School of Computing Faculty of Computing and Engineering Quest International University Malaysia Department of Finance Faculty of Business and Finance Universiti Tunku Abdul Rahman Malaysia Department of Information Systems Faculty of Information and Communication Technology Universiti Tunku Abdul Rahman Malaysia Department of Business and Public Administration Faculty of Business and Finance Universiti Tunku Abdul Rahman Malaysia Department of Teaching Quality Monitoring University of Sanya Hainan China

The advanced digital revolution has shifted conventional teaching and learning into digital education. In consistency with digital education, Augmented Reality (AR) applications started to shine in the education industry for their ability to create conducive teaching and learning environments, especially in remote learning during the COVID-19 pandemic. Movement Control Order (MCO) implemented in the year 2020 has led to emergency remote teaching and learning without much prepa-ration for all educators and learners. Throughout these few years, most educators got familiar with digital teaching tools and online teaching platforms. Hence, this study aims to explore educators’ readiness to adopt AR as a teaching tool in their teaching during the endemic period. A quantitative approach via questionnaire has been distributed to the Private Higher Education Institutions (PHEIs) in the states of Selangor and Kuala Lumpur. Machine learning using a clustering tech-nique was used to find patterns between the demographics of educators towards the AR perception of educators. The results revealed that educators’ perceptions of AR technology are influenced by their familiarity with it, their personal beliefs, and their attitudes toward technology. This study provides an insightful overview of the benefits of AR applications in education and the implications of the adoption of AR in Malaysian schools and educational institutions. It also highlights the importance of motivating educators and students to embrace AR as an enhancement learning tool, providing a valuable discussion for the government, learning institutions, and educators on the implementation of AR in Malaysia. © 2023, Brno University of technology. All rights reserved.

关键词： Augmented reality

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Invalidator: Automated Patch Correctness Assessment via Semantic and Syntactic Reasoning

arXiv

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arXiv 2023年

作者： Le-Cong, Thanh Luong, Duc-Minh Le, Xuan Bach D. Lo, David Tran, Nhat-Hoa Quang-Huy, Bui Huynh, Quyet-Thang School of Computing and Information Systems The University of Melbourne Australia School of Information and Communication Technology Hanoi University of Science and Technology Viet Nam School of Computing and Information Systems Singapore Management University Singapore

Automated program repair (APR) has been gaining ground recently. However, a significant challenge that still remains is patch overfitting, in which APR-generated patches plausibly pass the validation test suite but fail to generalize. A common practice to assess the correctness of APR-generated patches is to judge whether they are equivalent to ground-truth, i.e., developer-written patches, by either generating additional test cases or employing human manual inspections. The former often requires the generation of at least one test witnessing the behavioral differences between the APR-patched and developer-patched programs. Searching for the witnessing test, however, can be difficult as the search space can be enormous. Meanwhile, the latter is prone to human biases and requires repetitive and expensive manual effort. In this paper, we propose a novel technique, namely INVALIDATOR, to automatically assess the correctness of APR-generated patches via semantic and syntactic reasoning. INVALIDATOR reasons about program semantic via program invariants while it also captures program syntax via language semantic learned from large code corpus using the pre-trained language model. Given a buggy program and the developer-patched program, INVALIDATOR infers likely invariants on both programs. Then, INVALIDATOR determines that a APR-generated patch overfits if: (1) it violates correct specifications or (2) maintains errors behaviors of the original buggy program. In case our approach fails to determine an overfitting patch based on invariants, INVALIDATOR utilizes a trained model from labeled patches to assess patch correctness based on program syntax. The benefit of INVALIDATOR is three-fold. First, INVALIDATOR is able to leverage both semantic and syntactic reasoning to enhance its discriminant capability. Second, INVALIDATOR does not require new test cases to be generated but instead only relies on the current test suite and uses invariant inference to generalize the behav

关键词： Syntactics

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Imbalanced Graph Classification with Multi-scale Oversampling Graph Neural Networks

Imbalanced Graph Classification with Multi-scale Oversamplin...

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International Joint Conference on Neural Networks (IJCNN)

作者： Rongrong Ma Guansong Pang Ling Chen Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia School of Computing and Information Systems Singapore Management University Singapore

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

One main challenge in imbalanced graph classification is to learn expressive representations of the graphs in underrepresented (minority) classes. Existing generic imbalanced learning methods, such as oversampling and imbalanced learning loss functions, can be adopted for enabling graph representation learning models to cope with this challenge. However, these methods often directly operate on the graph representations, ignoring rich discriminative information within the graphs and their interactions. To tackle this issue, we introduce a novel multi-scale oversampling graph neural network (MOSGNN) that learns expressive minority graph representations based on intra- and inter-graph semantics resulting from oversampled graphs at multiple scales - subgraph, graph, and pairwise graphs. It achieves this by jointly optimizing subgraph-level, graph-level, and pairwise-graph learning tasks to learn the discriminative information embedded within and between the minority graphs. Extensive experiments on 16 imbalanced graph datasets show that MOSGNN i) significantly outperforms five state-of-the-art models, and ii) offers a generic framework, in which different advanced imbalanced learning loss functions can be easily plugged in and obtain significantly improved classification performance.

关键词： Learning systems Training Representation learning Semantics Graph neural networks

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Yolo Based License Plate Detection of Triple Riders and Violators

Yolo Based License Plate Detection of Triple Riders and Viol...

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2023 International Conference on Computer Communication and Informatics, ICCCI 2023

作者： Nandhakumar, R.G. Devi, K. Nirmala Krishnamoorthy, N. Shanthi, S. Pranesh, V.R. Nikhalyaa, S. Kongu Enginering College Perundurai Department of Computer Science and Engineering Tamilnadu Erode India Vellore Institutte of Technology School of Information and Engineering Department of Software Systems and Engineering Vellore India

ISBN: (纸本)9798350348217

Road safety is of prime importance as road accidents are among the biggest causes of deaths in the country. Road Accidents are majorly due to violators and lawbreakers of road safety rules like not wearing helmets, triple riding etc. Even though there are many smart systems to monitor these violations, it is complicated to keep a track of the data and view it efficiently anywhere. Also monitoring the permit details of other state vehicles is hard. A method was proposed to address this issue. based on Deep learning and Optical Character Recognition (OCR). Here we detect the riders not wearing helmet and triple riders using object detection by comparing YOLOv2 and YOLOv3. This simplifies the task of traffic police who can't continuously and efficiently monitor all the violators. We gathered our data from three different sources. Kaggle was used to collect the data set. A number of items can be recognized by the real-time object recognition system YOLO in a single frame. It recognizes object more precisely and faster than other recognition systems. It can predict up to 9000 classes and even unseen classes. It divides the image into m∗m matrix and each grid detects objects within itself. The trained model is tested using a test dataset set after training in order to measure the performance. For Number plate detection we use OCR based character recognition. The recognized license plate images of violators are captured and stored in a database which is then sent to the concerned department. The stored data can be easily accessed using the developed mobile app. Metrics considered for evaluation is Accuracy. The average is utilized to assess object detection models like R-CNN and YOLO. The average calculates a score by comparing the detected box to the ground-truth bounding box. The better the score, the more precise the model's detections are. When compared to YOLOv2, YOLOv3 exhibits strong performance in terms of accuracy with 95.5%. © 2023 IEEE.

关键词： Object detection

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Prerequisite Relations among Knowledge Units:A Case Study of Computer Science Domain

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Computer Modeling in Engineering & Sciences 2022年第12期133卷 639-652页

作者： Fatema Nafa Amal Babour Austin Melton Department of Computer Science Salem State UniversitySalemMA 01970USA Information Systems Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science Kent State UniversityKentOH 44240USA

The importance of prerequisites for education has recently become a promising research *** work proposes a statistical model for measuring dependencies in learning resources between knowledge *** are expected to present knowledge units in a semantically well-organized manner to facilitate students’understanding of the *** proposed model reveals how inner concepts of a knowledge unit are dependent on each other and on concepts not in the knowledge *** help understand the complexity of the inner concepts themselves,WordNet is included as an external knowledge base in *** goal is to develop a model that will enable instructors to evaluate whether or not a learning regime has hidden relationships which might hinder students’ability to understand the *** evaluation,employing three textbooks,shows that the proposed model succeeds in discovering hidden relationships among knowledge units in learning resources and in exposing the knowledge gaps in some knowledge units.

关键词： Knowledge graph text mining knowledge unit graph mining

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