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2nd International Conference on Innovative Technology, engineering and sciences, iCITES 2020

作者： Usop, Nur Alya Afikah Hisham, Syifak Izhar Faculty of Computer Science and Software Engineering Universiti Malaysia Pahang Gambang Malaysia

ISBN: (纸本)9783030709167

Security plays an important role in many sectors and industries. Nowadays, scams and illegal movements are spreading around the world. Copyright protection for PDF documentation is one of the focus in digital watermarking. Hence, a study was conducted on the related research of digital watermarking on PDF which is text documentation. This paper shows a review of watermarking techniques, characteristics, and possibility of attacks in text document format. This paper also discusses the comparisons between the existing scheme with different domains. The results can be seen from the dominant approaches in text digital watermarking which are the structural approach and hybrid approach. Based on the experimental phase, attacks are in a few formats such as insertion attack and removal attack. These are frequently used to test the robustness of digital watermarks that are embedded into an object. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Digital watermarking

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Emergency Vehicle Navigation in Connected Autonomous Systems Using Enhanced Traffic Management System

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IEEE Internet of Things Journal 2025年第12期12卷 20670-20677页

作者： Raja, Gunasekaran Anbalagan, Sudha Gurumoorthy, Sugeerthi Jegathesan, Darshini Girivel, Niveditha Subramanian Sundaram, Varsha Mani Shanmuga Khowaja, Sunder Ali Dev, Kapal Anna University NGNLab Department of Computer Technology MIT Campus Chennai600044 India Vellore Institute of Technology Chennai Centre for Smart Grid Technologies School of Computer Science and Engineering Chennai600127 India Citicorp Services Private Ltd Software Development Chennai600113 India Dublin City University School of Computing Faculty of Engineering and Computing Glasnevin Campus DublinD09 V209 Ireland Munster Technological University Department of Computer Science Bishopstown CorkT12 P928 Ireland University of Johannesburg Department of Institute of Intelligent Systems Johannesburg2006 South Africa Chitkara University Institute of Engineering and Technology Centre for Research Impact Outcome Chitkara University Punjab Rajpura140401 India

Autonomous Vehicle (AV) usage has become predominant in the rapidly evolving landscape of urban transportation. Integrating AVs and non-AVs in the existing traffic infrastructure has significantly increased the complexity of traffic patterns. This research work primes the enhanced Traffic Management System (e-TMS), a solution implemented to expedite Emergency Vehicle (EV) travel in the context of Connected AVs (CAVs) and ensured secured communication employing Public Key Infrastructure (PKI) among the Internet of Vehicles (IoV) framework. When an EV is detected, the IoV system verifies the EV's signal using PKI, ensuring its authenticity and integrity by encrypting the communication between the EV and Road Side Units (RSUs). Further, the e-TMS activates the platooning process where CAVs in the EV's lane shift to the adjacent lanes and dynamically form platoons to create a dedicated lane for the EV. To further optimize the platooning process, an Adaptive Smart Leader Selection (ASLS) algorithm is employed to select a leader vehicle spontaneously among the AVs based on the proximity to the EV, communication reliability, and lane position. Radio Detection and Ranging devices aid this platooning process by providing distance and target velocity, which are needed to maintain the required distance between the AVs and ensure safe platoon formation. The e-TMS enhances EV response times and overall traffic flow efficiency and resulted in 27.8% increase in mean speed compared to the traditional methods. © 2014 IEEE.

关键词： Emergency vehicles

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A Mutation-Guided Assessment of Acceleration Approaches for Continuous Integration: An Empirical Study of YourBase

A Mutation-Guided Assessment of Acceleration Approaches for ...

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International Mining software Repositories, MSR

作者： Zhili Zeng Tao Xiao Maxime Lamothe Hideaki Hata Shane McIntosh Software REBELs University of Waterloo Canada Division of Information Science Nara Institute of Science and Technology Japan Department of Computer Engineering and Software Engineering Polytechnique Montréal Canada Faculty of Engineering Shinshu University Japan

ISBN: (数字)9798400705878

ISBN: (纸本)9798350363982

Continuous Integration (CI) is a popular software development practice that quickly verifies updates to codebases. To cope with the ever-increasing demand for faster software releases, CI acceleration approaches have been proposed; however, adoption of CI acceleration is not without risks. For example, CI acceleration products may mislabel change sets (e.g., a build labeled as failing that passes in an unaccelerated setting or vice versa) or produce results that are inconsistent with an unaccelerated build (e.g., the underlying reasons for failure differ between (un)accelerated builds). These inconsistencies threaten the trustworthiness of CI acceleration *** this paper, we propose an approach inspired by mutation testing to systematically evaluate the trustworthiness of CI acceleration. We apply our approach to YourBase, a program analysis-based CI acceleration product, and uncover issues that hinder its trustworthiness. First, we study how often the same build in accelerated and unaccelerated CI settings produce different mutation testing outcomes. We call mutants with different outcomes in the two settings "gap mutants". Next, we study the code locations where gap mutants appear. Finally, we inspect gap mutants to understand why acceleration causes them to survive. Our analysis of ten open-source projects uncovers 2,237 gap mutants. We find that: (1) the gap mutants account for 0.11%–23.50% of the studied mutants; (2) 88.95% of gap mutants can be mapped to specific source code functions and classes using the dependency representation of the studied CI acceleration product; and (3) 69% of gap mutants survive CI acceleration due to deterministic reasons that can be classified into six fault patterns. Our results show that even deterministic CI acceleration solutions suffer from trustworthiness limitations, and highlight the ways in which trustworthiness could be pragmatically improved.

关键词： Accelerometers Codes Source coding Life estimation software Complexity theory Reliability

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Application of Neural Networks for Network Traffic Monitoring and Analysis 8

Application of Neural Networks for Network Traffic Monitorin...

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8th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2024

作者： Kushnerov, Oleksandr Murr, Pierre Herasymov, Serhii Milevskyi, Stanislav Melnyk, Marharyta Golovashych, Sergii Sumy State University Department of Economic Cybernetics Sumy Ukraine International University of Science and Technology in Kuwait Computer Engineering Department Kuwait Kuwait 'Kharkiv polytechnic institute' Cybersecurity department National Technical University Kharkiv Ukraine Set University Department of Cyber Security and information protection Kyiv Ukraine National Technical University 'Kharkiv polytechnic institute' Department of Software Engineering and Management Intelligent Technologies Kharkiv Ukraine

ISBN: (纸本)9798350354423

Monitoring and analyzing network traffic are critically important tasks in the context of increasing cyber threats. Traditional data processing methods often struggle to handle the large volumes and complexity of modern network traffic, necessitating the use of advanced technologies such as neural networks and machine learning. This article demonstrates the application of neural networks for monitoring and analyzing network traffic, highlighting their ability to learn from large datasets to detect complex patterns and anomalies. Using TensorFlow, we developed a neural network model based on an autoencoder that effectively identifies and classifies anomalies in network traffic. The model's effectiveness was validated using a synthetic dataset from Kaggle, showing high accuracy on both training and testing data. Our approach significantly improves the efficiency and accuracy of threat detection compared to traditional methods, making it a valuable tool for enhancing cybersecurity. © 2024 IEEE.

关键词： Cyber attacks

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Intelligent Model for Optimizing Gantt Chart in the Planning Stage

Intelligent Model for Optimizing Gantt Chart in the Planning...

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International Conference on Information Technology (ICIT)

作者： Noor Bdair Wael Alzyadat Shadi AlZubi Dept of Software engineering Faculty of Science and IT Alzaytoonh University of Jordan Dept. of of Computer Science Faculty of Science and IT Alzaytoonh University of Jordan

Scheduling tasks under resource constraints is essential for project success, and this research focuses on scheduling tasks efficiently to minimize completion time. To tackle this problem, two optimization techniques are employed: Linear programming (LP) and particle swarm optimization (PSO). PSO significantly reduces the duration, leading to a reduction in project duration. But the LP algorithm does not improve the project duration. Using suitable algorithms to maximize project efficiency and success is essential for successful project management. This research provides valuable information for project managers and decision makers, highlighting the importance of utilizing suitable algorithms to maximize project efficiency and success.

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Boundary-Guided Learning for Gene Expression Prediction in Spatial Transcriptomics

Boundary-Guided Learning for Gene Expression Prediction in S...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Qu, Mingcheng Wu, Yuncong Di, Donglin Su, Anyang Su, Tonghua Song, Yang Fan, Lei Harbin Institute of Technology Faculty of Computing Harbin China Harbin Institute of Technology School of Astronautics Harbin China Space AI Li Auto Beijing China Jilin University College of Software Changchun China Computer Science and Engineering Unsw Sydney Australia

ISBN: (纸本)9798350386226

Spatial transcriptomics (ST) has emerged as an advanced technology that provides spatial context to gene expression. Recently, deep learning-based methods have shown the capability to predict gene expression from WSI data using ST data. Existing approaches typically extract features from images and the neighboring regions using pretrained models, and then develop methods to fuse this information to generate the final output. However, these methods often fail to account for the cellular structure similarity, cellular density and the interactions within the *** this paper, we propose a framework named BG-TRIPLEX, which leverages boundary information extracted from pathological images as guiding features to enhance gene expression prediction from WSIs. Specifically, our model consists of three branches: the spot, in-context and global branches. In the spot and in-context branches, boundary information, including edge and nuclei characteristics, is extracted using pretrained models. These boundary features guide the learning of cellular morphology and the characteristics of microenvironment through Multi-Head Cross-Attention. Finally, these features are integrated with global features to predict the final *** experiments were conducted on three public ST datasets. The results demonstrate that our BG-TRIPLEX consistently outperforms existing methods in terms of Pearson Correlation Coefficient (PCC). This method highlights the crucial role of boundary features in understanding the complex interactions between WSI and gene expression, offering a promising direction for future research. Codes are available at: https://***/WcloudC0416/BG-TRIPLEX © 2024 IEEE.

关键词： Gene expression

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An Approach for Early Detection of Schizophrenia

An Approach for Early Detection of Schizophrenia

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International Conference on Computing and Networking Technology (ICCNT)

作者： Sachin Paranagama Isiwara Uditha Pamodya Daundasekara Shehani Hettiarachchi Lokesha Weerasinghe Dharshana Kasthurirathna Department of Computer Science and Software Engineering Faculty Of Computing Sri Lanka Institue Of Information Technology Malabe Sri Lanka

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Schizophrenia is a chronic mental disorder with distorted thinking, hallucinations, and social difficulties. Early diagnosis is vital, but current methods are limited. This research proposes a web-based application integrating machine learning, emotion recognition, and game-based elements to track symptoms and aid in early diagnosis. Interactive exercises focus on specific symptoms like cognitive evaluation, emotional analysis, and memory assessment. By combining computer science, psychology, and machine learning, the project aims to improve early detection and ultimately enhance the quality of life for affected individuals. Key components include using Deep Convolutional Neural Network (DCNN) architecture for recognizing facial and physical expressions associated with schizophrenia with an 87% accuracy rate, and utilizing Vector Regressor (SVR) with a 93% accuracy rate, along with Vision Transformer (ViT) and Custom CNN models for cognitive assessment, achieving accuracy rates of 99% and 98%, respectively.

关键词： computer science Emotion recognition computer vision Accuracy Face recognition Psychology Machine learning Transformers Vectors Convolutional neural networks

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A Reliable and Stable V2V Routing Scheme for Warning Message Dissemination in VANETs using Bi-Directional Clustering 12

A Reliable and Stable V2V Routing Scheme for Warning Message...

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12th International Conference on Communication and Network Security, ICCNS 2022

作者： Khan, Mansoor Abbas, Ghulam Abbas, Ziaul Haq Alasmary, Hisham Tu, Shanshan Waqas, Muhammad Faculty of Computer Science and Engineering Gik Institute of Engineering and Technology Topi23640 Pakistan Faculty of Electrical Engineering Gik Institute of Engineering and Technology Topi23640 Pakistan Department of Computer Science College of Computer Science King Khalid University Information Security and Cybersecurity Unit King Khalid University Abha Saudi Arabia Faculty of Information Technology Beijing University of Technology Beijing100124 China Computer Engineering Department College of Information Technology University of Bahrain 32038 Bahrain School of Engineering Edith Cowan University PerthWA6027 Australia

ISBN: (纸本)9781450397520

Road traffic injuries cause considerable life and economic losses to individuals, their families, and nations as a whole. To avoid road accidents, Vehicular Ad-hoc Networks (VANETs) play a vital role by enhancing transportation systems to make them intelligent. To enhance road safety, emergency message dissemination schemes are indispensable in VANET-based applications. This paper proposes a routing protocol for emergency message dissemination, which uses stable clustering for the bi-directional highway scenario. To assure the long-term sustainability of a cluster, a median technique for selecting a CH is devised. Further, an extended form of the K-medoids algorithm for a new node joining a cluster is employed, which ensures that both node and cluster have the same direction for bi-directional road traffic. Simulation results reveal that the proposed protocol proffers enhanced throughput and lowers the packet loss rates and end-to-end delay compared with state-of-the-art routing schemes. © 2022 ACM.

关键词： Vehicular ad hoc networks

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Eliciting Requirements from Stakeholders’ Responses Using Natural Language Processing

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computer Modeling in engineering & sciences 2021年第4期127卷 99-116页

作者： Mohammed Lafi Bilal Hawashin Shadi AlZu’bi Department of Software Engineering Faculty of Science and Information TechnologyAl-Zaytoonah University of JordanAmman11733Jordan Department of Computer Information Systems Faculty of Science and Information TechnologyAl-Zaytoonah University of JordanAmman11733Jordan Department of Computer Science Faculty of Science and Information TechnologyAl-Zaytoonah University of JordanAmman11733Jordan

Most software systems have different stakeholders with a variety of *** process of collecting requirements from a large number of stakeholders is vital but *** propose an efficient,automatic approach to collecting requirements from different stakeholders’responses to a specific *** use natural language processing techniques to get the stakeholder response that represents most other stakeholders’*** study improves existing practices in three ways:Firstly,it reduces the human effort needed to collect the requirements;secondly,it reduces the time required to carry out this task with a large number of stakeholders;thirdly,it underlines the importance of using of data mining techniques in various software engineering *** approach uses tokenization,stop word removal,and word lemmatization to create a list of frequently accruing *** then creates a similarity matrix to calculate the score value for each response and selects the answer with the highest *** experiments show that using this approach significantly reduces the time and effort needed to collect requirements and does so with a sufficient degree of accuracy.

关键词： software requirements requirements elicitation natural language processing

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Performance Comparison of Interpolation Methods for Enriching WiFi Fingerprint Database 24

Performance Comparison of Interpolation Methods for Enrichin...

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9th International Conference on Cloud Computing and Internet of Things, CCIOT 2024

作者： Vu-Thanh, Trung He, Jing Duong-Bao, Ninh Thi, Luong Nguyen Lee, Seon-Woo Nguyen-Huu, Khanh College of Computer Science and Electronic Engineering Hunan University Changsha China Faculty of Mathematics and Informatics Dalat University Dalat Viet Nam Faculty of Information Technology Dalat University Dalat Viet Nam Division of Software Hallym University Chuncheon Korea Republic of Department of Electronics and Telecommunications Dalat University Dalat Viet Nam

ISBN: (纸本)9798400717161

Recently, WiFi Fingerprinting-based indoor positioning systems have gained significant attention due to the low cost of infrastructure deployment. In the data collection process, a higher density of reference points may lead to better positioning results. However, it makes this process time-consuming and laborious. To solve this problem, this study applies and compares different interpolation methods to enrich the fingerprint database without increasing the cost of the collection process. To evaluate the performance of the chosen methods, five interpolation methods are implemented in a multi-condition WiFi Fingerprinting dataset. Moreover, to check the robustness of the methods, different numbers of reference points are considered when creating the new interpolated fingerprint databases. According to the results, inverse distance weighting (IDW) is the most suitable interpolation method with low complexity and stable performance. The IDW-based database achieves an average interpolation error of less than 6 dBm compared to the original database. When applying this interpolated database to perform positioning tasks, it helps reduce the collection cost by 30% with slightly lower positioning results compared to the original database. This work demonstrates the feasibility of using interpolation to ease the data collection process of WiFi Fingerprinting, especially in complex and big areas such as airports or hospitals. Copyright © 2024 held by the owner/author(s). Publication rights licensed to ACM.

关键词： Wi-Fi

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