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Finding a Minimum Distance Between Two Smooth Curves in 3D Space 2nd

Finding a Minimum Distance Between Two Smooth Curves in 3D S...

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2nd International Conference on information Technologies and Their Applications

作者： Abbasov, Majid Polyakova, Lyudmila St Petersburg State Univ 7-9Univ Nab St Petersburg 199034 Russia

ISBN: (纸本)9783031734199;9783031734205

This study investigates the problem of determining the minimum distance between two smooth 3D curves. We propose its solution on the basis of the newly formulated idea of Charged Balls Method. The main idea behind this method is the physical model which tends to the solution of the original problem. We can derive equations of motion for the system and apply the difference scheme for the solution of the obtained ordinary differential equations. This is the way we get an iterative algorithm for the initial problem. We employ Lyapunov theory of stability to prove the convergence of the proposed method. More specifically, the Barbashin-Krasovskii theorem on asymptotic stability is employed. The convergence rate of the algorithm is analyzed and the corresponding results are presented. We provide a number of numerical examples to demonstrate its work. These examples acknowledge the effectiveness of the method and stresses that the choice of the parameters one may significantly affect the convergence rate.

关键词： Minimal Distance Charged Balls Method Mathematical Programming Lyapunov's Second Method LaSalle's Invariance Principle Computational Geometry

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JSMBox-A Runtime Monitoring Framework for Analyzing and Classifying Malicious JavaScript 33rd

JSMBox-A Runtime Monitoring Framework for Analyzing and Clas...

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33rd International Conference on Software and Data Engineering

作者： Phung, Phu H. Varghese, Allen Wang, Bojue Zhao, Yu Yu, Chong Univ Dayton Dept Comp Sci Intelligent Syst Secur Lab 300 Coll Pk Ave Dayton OH 45469 USA Univ Cincinnati Dept Comp Sci 2901 Woodside Dr Cincinnati OH 45221 USA Univ Cincinnati Dept Elect & Comp Engn Cincinnati OH USA

ISBN: (纸本)9783031752001;9783031752018

In recent years, there has been a notable increase in the prevalence of malicious websites, leading to a majority of cyber-attacks and data breaches. Malicious websites often incorporate JavaScript code to execute attacks on web browsers. Despite existing methodologies documented in the literature, the analysis and detection of malicious JavaScript pose significant challenges due to the dynamic nature of JavaScript and the use of advanced evasion techniques. These challenges motivate the need for an innovative and efficient approach to comprehensively analyze the code to identify its malicious intent. In this paper, we introduce a monitoring approach for analyzing JavaScript code, which can capture all of the code's features at runtime. Our method leverages the security reference monitor technique to mediate JavaScript security-sensitive executions, including function calls and property accesses. Therefore, the proposed method can capture behaviors at runtime regardless of how the code is written, even with recent advanced evasion techniques like WebAssembly diversification. We have implemented our approach as a JavaScript dynamic analysis framework called JSMBox in aChromium-based browser extension. Our experiments demonstrated that JSMBox is capable of effectively countering sophisticated evasion techniques found in modern malicious JavaScript code, including WebAssembly diversification. We have also evaluated the framework's ability to classify malicious behaviors based on a large-scale raw dataset comprising about 20,000 malicious and benign webpages. Our developed tool automatically launches the browser to execute these webpages, records JavaScript code execution events, and captures their execution frequency as extracted features. We have tested the extracted dataset with various machine-learning models, yielding promising experimental results that confirm the effectiveness of our approach and achieve a high accuracy rate.

关键词： JavaScript Dynamic Analysis Runtime Monitoring Maliciousness Classification

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A Novel Approach of SHA-3-512bits Using Keccak Technique Based on Sponge Function Implementation on FPGA 5th

A Novel Approach of SHA-3-512bits Using Keccak Technique Bas...

引用

5th International Conference on Computing science, Communication and Security

作者： Lakshmi, K. Janshi Sreenivasulu, G. Sri Venkateswara Univ Coll Engn Dept Elect & Commun Engn Tirupati Andhra Pradesh India

ISBN: (纸本)9783031751691;9783031751707

SHA-3-512bits offers stronger cryptographic security than SHA1, SHA 2, and *** paper describes a SHA-3-512bits hash function utilizing the Sponge-based Keccak Algorithm. Four alternate messages digest lengths of 512 bits, 384 bits, 256 bits, and 224 bits are allowed by the SHA3 hash algorithm, depending on the hash function in use. The SHA3-512 function operates on a single instance, processing input messages at a rate of 72 bytes per 1096 cycles at 316.25 MHz and a 1600 bits data path with a round-iterative structure. The SHA-3-512bits is verified by VIVADO 2017.2 version software with hardware implementation on FPGA ARTIX-7 device. The proposed method consumed power is 192.334W and occupied an area of 2493 LUTs, Flip-Flops 1876 and IOB's 17.65% of ARTIX-7 FPGA device and became cost-effective device used ARTEX-7.

关键词： Cryptography Security SHA-3-512 Keccak Sponge function VIVADO FPGA Artix-7

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DRLN: Disentangled Representation Learning Network for Multimodal Sentiment Analysis 5th

DRLN: Disentangled Representation Learning Network for Multi...

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5th International Conference on Neural Computing for Advanced Applications (NCAA)

作者： Hou, Jingming Omar, Nazlia Tiun, Sabrina Saad, Saidah He, Qian Univ Kebangsaan Malaysia Fac Informat Sci & Technol Ctr Artificial Intelligence Technol Bangi 43650 Selangor Malaysia Guilin Univ Elect Technol State & Local Joint Engn Res Ctr Satellite Nav & Guangxi Key Lab Cryptog & Informat Secur Guilin Peoples R China

ISBN: (纸本)9789819770069;9789819770076

Multimodal sentiment analysis (MSA) involves the analysis of human emotions by integrating emotional features from text, audio, and visual modalities. Previously, a considerable amount of research had commonly focused on fusing these three modalities equally, neglecting the importance of text modality and the influence of modal heterogeneity on fusion. To address this issue, we propose the Disentangled Representation Learning Network (DRLN) which decomposes representations from different modalities into separate sub-spaces centered around text modality to capture similarity and dissimilarity features among modalities. Meanwhile, we utilize contrastive learning loss and reconstruction loss to better learn representations within each sub-space. Finally, extensive experiments on two benchmark datasets demonstrate that our model outperforms state-of-the-art methods on various metrics.

关键词： Multimodal Sentiment Analysis Multimodal Representation Learning Contrastive Learning Text-Centric

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Assessing Consumers' Embrace of the Internet of Things 5th

Assessing Consumers' Embrace of the Internet of Things

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5th 5th Olympus - International Conference on Supply Chain

作者： Kostas, Tassis Dimitris, Folinas Maria, Argyropoulou Rachel, Argyropoulou Soheila, Nemati Hellen Open Univ Patras Greece Int Hellen Univ Thermi Greece Brunel Univ London Uxbridge Middx England Hellen Army Acad Attica Greece

ISBN: (纸本)9783031693502;9783031693519

This research provides the results of an empirical study among Greek consumers on their perception and adoption of Internet of Things (IoT) applications in everyday life. The theoretical framework is based on the Technology Acceptance Model (TAM) to investigate consumers' intention to use IoT applications. The empirical data of this study came from a sample of 814 consumers in Greece via an online survey. The research findings suggest that attitude toward IoT is primarily determined by individuals' innovativeness and only secondarily by the perceived usefulness of the technology. Moreover, future use of IoT depends mainly on performance expectancy. It appears that the success of IoT products depends on appealing to individuals with high perceived technology usefulness, high self-efficacy, and high personal innovativeness. Such consumers are more likely to have high expectations of IoT offerings and consequently intend to use them.

关键词： Internet of Things Industry 4.0 Technology Acceptance Model Consumer Behaviors Behavioral Intention

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Camera-Based ASL Alphabet Recognition Using Hand Landmark Features 1

引用

15th Indian Conference on Human-computer Interaction Design and Research

作者： Chakravarty, Anwesha Choudhary, Ayesha Jawaharlal Nehru Univ New Delhi 110067 India

ISBN: (数字)9783031808326

ISBN: (纸本)9783031808319;9783031808326

Sign language is the fundamental mode of communication for people with hearing and speaking disabilities worldwide. The goal of automating sign language understanding is to establish inclusive visual communication to facilitate conversations between sign language users and the wider community. This paper deals with the problem of understanding ASL alphabet gestures and proposes a two-stage deep learning and computer vision-based framework for ASL alphabet recognition and classification into 26 distinct classes. Existing systems struggle with variations in signer appearance, complex backgrounds and limited high-quality data. The proposed method attempts to address these challenges by experimenting with features and classification techniques and uses a learning-based automatic annotation method for labelling data. This work contributes to the ongoing effort of building automated camera-based systems for inclusive communication that can potentially revolutionize visual communication.

关键词： Sign Language Recognition ASL Keypoint Extraction

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Predictive Analytics in Weather Forecasting Using Machine Learning and Deep Learning 4th

Predictive Analytics in Weather Forecasting Using Machine Le...

引用

4th International Conference on Artificial Intelligence and Knowledge Processing

作者： Pantola, Deepika Gupta, Madhuri Agarwal, Mahim Bohra, Rupal Rawat, Kritika Bennett Univ Sch Comp Sci Engn & Technol Greater Noida India

ISBN: (纸本)9783031734762;9783031734779

Climate and weather patterns have a significant influence on many aspects of our lives, including infrastructure planning, emergency preparedness, agriculture, and electricity use. It is not just a scientific endeavor but also a practical imperative to comprehend and accurately predict temperature swings in the context of Helsinki, which is a city known for its dramatic seasonal adjustments. Major weather forecasting centers use numerical weather prediction models that operate on many supercomputers to solve difficult nonlinear mathematical equations simultaneously. These models offer medium-range weather forecasts, with a grid length of 10-20 km, every 6 h to 18h. Nonetheless, agriculture and emergency preparations frequently rely on higher-resolution regional forecasting models to provide them with more precise short- to medium-range projections. This study aims to conduct time series analysis and weather forecasting for Helsinki using facts from 2015 to 2019, utilizing models such as ARIMA, SARIMAX, LSTM, and GARCH. The experimental results based on MAE, MSE, RMSE, R2 score and MAPE, show that the SARIMAX has better performance, which makes it the preferred choice for handling the temporal and geographical intricacies of Helsinki's weather patterns.

关键词： ARIMA weather forecasting LSTM time series SARIMAX

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A Strategy-Proof and Collusion-Proof Peer Grading Mechanism 1st

A Strategy-Proof and Collusion-Proof Peer Grading Mechanism

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1st International Workshop on Mechanism Design in Social Networks

作者： Li, Bin Du, Xiaoyu Nanjing Univ Sci & Technol Nanjing Peoples R China

ISBN: (纸本)9789819602131;9789819602148

The practice of grading candidates according to their performance is widespread and of utmost importance, where the key is to assess each candidate's performance with reliable information. This paper aims to investigate peer grading in scenarios with ground truths, where there is an unknown ground truth represented by a real number for each candidate's performance. The final grade assigned to each candidate is determined by the assessments, which are assumed as unbiased estimators of the candidate's ground truth, made by both the experts and the candidates. We are interested in peer grading mechanisms that not only provide unbiased grades but are also resistant to strategic behaviors such as unilateral strategy deviation and collusion, which poses a challenging task in peer mechanism design. Generally, we make two contributions to the study of peer grading. First, we establish the impossibility of designing non-trivial grading mechanisms when the number of candidates is less than three. Second, we propose a practical and non-trivial grading mechanism, called the mean externality mechanism, for settings with at least three candidates, which is proved to be unbiased, strategy-proof and collusion-proof.

关键词： Peer grading Strategy-Proofness Collusion-Proofness

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Privacy Preserving Enablers for Data Space Ecosystems 1st

Privacy Preserving Enablers for Data Space Ecosystems

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1st Global Internet of Things and Edge Computing Summit

作者： Borgonos Garcia, Natalia Hernandez Padilla, Maria Skarmeta Gomez, Antonio Fernando Univ Murcia Murcia Spain

ISBN: (纸本)9783031785719;9783031785726

Data Spaces are ecosystems designed to allow multiple organizations or companies to share data in a secure manner. Despite the potential of these technologies, they encounter a number of challenges and privacy issues that limit their use. Privacy Preserving Enablers are mechanisms developed to tackle these difficulties, ensuring data integrity and access control. This paper aims to analyze the role of some Privacy Preserving Enablers and its integration with Connectors in the context of Data Spaces. The research will focus on key enablers, including a Self-Sovereign Identity with Zero-Knowledge Proof, which is a privacy preserving approach that allows users to verify their identity and attributes without the need to disclose underlying data, ensuring their privacy. Additionally, the usage of Sticky Policies instantiated through Attribute-Based Encryption attaches control policies into the encrypted data in order to have an attribute-based access control, enhancing its security. The application of Policies Enforcement assure the consistent application of policies and the maintenance of the security within the Data Space.

关键词： Data Spaces Privacy Preserving Enablers Self-Sovereign Identity Sticky Policies Policy Enforcement

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Neural Network-Based Vehicular Channel Estimation Performance: Effect of Noise in the Training Set 5th

Neural Network-Based Vehicular Channel Estimation Performanc...

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5th Southern African Conference for Artificial Intelligence Research

作者： Ngorima, Simbarashe Aldrin Helberg, Albert S. J. Davel, Marelie H. Northwest Univ Fac Engn Potchefstroom South Africa Ctr Artificial Intelligence Res Cape Town South Africa Natl Inst Theoret & Computat Sci Stellenbosch South Africa

ISBN: (纸本)9783031782541;9783031782558

Vehicular communication systems face significant challenges due to high mobility and rapidly changing environments, which affect the channel over which the signals travel. To address these challenges, neural network (NN)-based channel estimation methods have been suggested. These methods are primarily trained on high signal-to-noise ratio (SNR) with the assumption that training a NN in less noisy conditions can result in good generalisation. This study examines the effectiveness of training NN-based channel estimators on mixed SNR datasets compared to training solely on high SNR datasets, as seen in several related works. Estimators evaluated in this work include an architecture that uses convolutional layers and self-attention mechanisms;a method that employs temporal convolutional networks and data pilot-aided estimation;two methods that combine classical methods with multilayer perceptrons;and the current state-of-the-art model that combines Long-Short-Term Memory networks with data pilot-aided and temporal averaging methods as post processing. Our results indicate that using only high SNR data for training is not always optimal, and the SNR range in the training dataset should be treated as a hyperparameter that can be adjusted for better performance. This is illustrated by the better performance of some models in low SNR conditions when trained on the mixed SNR dataset, as opposed to when trained exclusively on high SNR data.

关键词： Channel estimation deep learning neural networks CNN-Transformer IEEE 802.11p vehicular channels

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