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A Novel Model for Driver Lane Change Prediction in Cooperatice Adaptive Cruise Control Systems

A Novel Model for Driver Lane Change Prediction in Cooperati...

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2023 International Symposium on Signals, Circuits and Systems, ISSCS 2023

作者： Qasemabadi, Armin Nejadhossein Mozaffari, Saeed Rezaei, Mahdi Ahmadi, Majid Alirezaee, Shahpour University of Windsor Electrical and Computer Engineering Department Windsor Canada University of Windsor Mechanical Automotive and Material Engineering Department Windsor Canada Institute for Transport Studies University of Leeds United Kingdom

ISBN: (纸本)9798350342031

Accurate lane change prediction can reduce potential accidents and contribute to higher road safety. Adaptive cruise control (ACC), lane departure avoidance (LDA), and lane keeping assistance (LKA) are some conventional modules in advanced driver assistance systems (ADAS). Thanks to vehicle-to-vehicle communication (V2V), vehicles can share traffic information with surrounding vehicles, enabling cooperative adaptive cruise control (CACC). While ACC relies on the vehicle's sensors to obtain the position and velocity of the leading vehicle, CACC also has access to the acceleration of multiple vehicles through V2V communication. This paper compares the type of information (position, velocity, acceleration) and the number of surrounding vehicles for driver lane change prediction. We trained an LSTM (Long Short-Term Memory) on the HighD dataset to predict lane change intention. Results indicate a significant improvement in accuracy with an increase in the number of surrounding vehicles and the information received from them. Specifically, the proposed model can predict the ego vehicle lane change with 59.15% and 92.43% accuracy in ACC and CACC scenarios, respectively. © 2023 IEEE.

关键词： Adaptive cruise control

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A multi-modal approach for identifying schizophrenia using cross-modal attention

A multi-modal approach for identifying schizophrenia using c...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Gowtham Premananth Yashish M. Siriwarden Philip Resnik Carol Espy-Wilson Department of Electrical and Computer Engineering University of Maryland College Park Maryland USA Institute for Advanced Computer Studies University of Maryland College Park Maryland USA

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

This study focuses on how different modalities of human communication can be used to distinguish between healthy controls and subjects with schizophrenia who exhibit strong positive symptoms. We developed a multi-modal schizophrenia classification system using audio, video, and text. Facial action units and vocal tract variables were extracted as low-level features from video and audio respectively, which were then used to compute high-level coordination features that served as the inputs from the audio and video modalities. Context-independent text embeddings extracted from transcriptions of speech were used as the input for the text modality. The multi-modal system is developed by fusing a segment-to-session-level classifier for video and audio modalities with a text model based on a Hierarchical Attention Network (HAN), with cross-modal attention. The proposed multi-modal system outperforms the previous state-of-the-art multi-modal system by 8.53% in the weighted average F1 score.

关键词： Biological system modeling Computational modeling Feature extraction engineering in medicine and biology Audio-visual systems

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Node Mobility and Encounter Rate Metrics to Enhance Stability in MANET 2

Node Mobility and Encounter Rate Metrics to Enhance Stabilit...

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2nd International Conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023

作者： Rajaram, Gnanajeyaraman Archana Vishveswari, R.S. Deepa, R. Packialatha, A. Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Applied Machine Learning Tamil Nadu Chennai India Varuvan Vadivelan Institute of Technology Department of Computer Science and Engineering Tamil Nadu Dharmapuri India Vels Institute of Science Technology & Advanced Studies Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350325799

Mobile Ad hoc Networks (MANETs) have been broadly functional in a wide variety of scenarios, for example, in disaster recovery, health care, video conferencing, and battlefield transmissions. MANET is an independent and peer-to-peer network which builds a chain of nodes to enable data transmission from sender to receiver. Hop count is measured as the most significant metric in MANET. Though several metrics have been introduced as the replacement for the hop count metric, there is a need for outperformance in mobile scenarios. The node mobility will affect the link stability, and it creates congestion. To solve these issues, a Node Mobility and Encounter Rate metrics (NMER) to enhance the stability of the network. It selects the route based on the node mobility and Encounter Rate (ER) metrics. The congestion ingredient measures the congestion level in the MANET. The objective of this route has the least cost for forward data packets and minimizes congestion. The NMER approach simulation results demonstrate that the NMER approach minimizes the packet loss ratio and reduces the network delay. © 2023 IEEE.

关键词： Mobile ad hoc networks

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Smart and advanced electrical Skills: Identifying Current Gaps and Emerging Trends 5

Smart and Advanced Electrical Skills: Identifying Current Ga...

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5th IEEE International Conference on Communications, Information, Electronic and Energy Systems, CIEES 2024

作者： Karapidakis, Emmanuel Markaki, Marini Apostolakis, Spyridon Canizes, Bruno Androulakis, Radamanthys Castro, Fabio Hellenic Mediterranean University Electrical and Computer Engineering Department Heraklion Greece Polytechnic Institute of Porto GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Porto Portugal ECTE GECAD - Research Group on Research Department Rethymno Greece

ISBN: (纸本)9798350352863

With the rise of smart buildings, new expertise gaps and security vulnerabilities are emerging, necessitating a comprehensive understanding of their current state and proactive future planning to address these challenges. Such identification is crucial for mapping the pathway towards vocational modernization (keeping up with trends and goal alignment). To assess these gaps, this paper explores the extensive literature that draws on workshops, expert interviews, and research to identify emerging roles and training needs across seven countries: Greece, Spain, Portugal, Italy, North Macedonia, Germany, and the Netherlands. In particular, it examines the validity of its findings in critical areas such as security, privacy, and the integration of smart grids with energy markets. Additionally, the paper highlights future skills gaps emerging from advancements in IoT, automation, and renewable energy technologies. It emphasizes the growing demand for specialized electrical expertise to optimize energy production, integrate monitoring and storage systems, and manage electric vehicle charging and energy communities effectively. In conclusion, the study identifies critical gaps in expertise and training needed to keep up with the rapid evolution of smart building technologies. Emerging trends highlight the demand for interdisciplinary skills, particularly in IoT, automation, and renewable energy. As these fields advance, expertise in cybersecurity, energy management, and smart grid integration will be crucial, emphasizing the need for proactive workforce development and planning. The findings can be used to inform and direct policymakers towards the smooth reexamination of vocational training. © 2024 IEEE.

关键词： Power grids

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Detection of Anomaly Detection with high dimensional data using volume and velocity aspects 5

Detection of Anomaly Detection with high dimensional data us...

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5th International Conference on Information Management and Machine Intelligence, ICIMMI 2023

作者： Chakraborty, Koushik Tata, Ravi Kumar Mahajan, Rashima Dudeja, Deepak Ramkumar, R. Gupta, Upasana Adamas University Kolkata India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram India Department of Computer Science and Engineering Manav Rachna International Institute of Research and Studies Faridabad India Department of Computer Science and Engineering MMEC MMDU Mullana Ambala India Department of Electrical and Electronics Engineering School of Engineering and Technology Dhanalakshmi Srinivasan University Tamilnadu Tiruchirapalli India Department of Computer Science & Engineering BBD University Lucknow India

ISBN: (纸本)9798400709418

Now a days detection of various anomalies finds all the unexpected events in the computing information over the internet are defined as anomalous events or inconsistency events. While detecting the various inconsistencies will help in getting the useful computing information system. Inconsistency type locations and exception investigation is the way of information mining prepared for recognizing information focuses that drop exterior anomaly. While doing so a standard is set up to anticipated design in a dataset. This location preparation is crucial since peculiarities like these are frequently a marker of bizarre behavior, such as potential false endeavors, security breaches, or cyber security interruptions. Organizations use information mining methods to identify inconsistencies and screen information points inputs and outputs moving over their IT framework and frameworks. On a very basic level, peculiarity discovery makes a difference organization address security spill, dodge information introduction, and set cautions against unordinary behavior that goes astray from the built-up design. This research paper deals with various techniques and ways for several anomalies inside the information. The finding of the research is how to detect the anomalies. © 2023 ACM.

关键词： Data mining

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Augmenting EHR Systems by Utilizing Blockchain Technology with unique Aadhar Identity System 2

Augmenting EHR Systems by Utilizing Blockchain Technology wi...

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2nd International Conference Computational and Characterization Techniques in engineering and Sciences, IC3TES 2024

作者： Joshi, Rahul Pandey, Krishna Kumari, Suman Gupta, Shashi Kant Mohanty, Mitali Salau, Ayodeji Olalekan Manav Rachna International Institute of Research & Studies Department of Journalism & Mass Communication Smeh Haryana India Independent Researcher Haryana India Eudoxia Research University Computer Science and Engineering New CastleDE United States Afe Babalola University Department of Electrical/Electronics and Computer Engineering Ado-Ekiti Nigeria

ISBN: (纸本)9798350364699

Currently, digital technologies are progressing swiftly in the modern era. Virtually every sector has reaped the rewards of this continuous transformation. The proposal to digitize medical records in the health industry was made several decades ago. Several wealthy nations have effectively embraced and executed Electronic Health Record (EHR) systems. India, along with other developing nations, continues to primarily depend on medical records that are documented on paper. Despite the existence of multiple electronic medical record management systems, they need help with interoperability, timely access, and storage. The existing systems need to be more robust in communicating and tracking medical records due to inadequate infrastructure and architecture. The COVID-19 pandemic underscored the imperative for an improved EHR (Electronic Health Record) system. The current system has two significant drawbacks: a lack of interoperability, resulting in delays in sharing of information, and a lack of standards, leading to compromised quality of data when shared. In order to address these problems, it is necessary to implement a comprehensive electronic health record system throughout the country. Another problem that arises is the need for a widely available UPI. In India, the 2nd most populous country globally, Aadhar is the optimal choice for UPI, as it can facilitate the establishment of a national Electronic Health Record system. This paper introduces a framework for an EHR system that is interoperable, standardized, and unified. The system is built on blockchain technology and utilizes Aadhar as UPI. Utilizing blockchain as the foundation of this approach offers several benefits compared to a cloud-based system, including decentralization, enhanced immutability, traceability, and security. © 2024 IEEE.

关键词： Electronic health record

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Investigating Blockchain Security Mechanisms for Tamper-Proof Data Storage 2

Investigating Blockchain Security Mechanisms for Tamper-Proo...

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2nd IEEE International Conference on Communication, Security and Artificial Intelligence, ICCSAI 2023

作者： Thilakavathy, P. Jayachitra, S. Aeron, Anurag Kumar, Narendra Ali, Syed Sumera Malathy, M. Computer Science and Engineering Vels Institute of Science Technology and Advanced Studies Chennai India Psna College of Engineering and Technology Department of Ece Tamilnadu Dindigul India School of Computing Dit University Dehradun Computer Science and Engineering India Amity University Department of Computer Science and Engineering Jharkhand Ranchi India Csmss Chh Shahu College of Engineering Electronics and Computer Engineering Department Maharashtra Aurangabad India Vel Tech High Tech Dr Rangarajan Dr Sakunthala Engineering College Department of Computer Science and Engineering Chennai Avadi India

ISBN: (纸本)9798350369960

Across a wide range of sectors, blockchain technology has emerged as a game-changing option for secure data storage. This research dives into the mechanisms that enable blockchain to protect data integrity and immutability. This research investigates how blockchain technology reduces the chances of data tampering and unauthorized adjustments by examining its underlying concepts and features, such as decentralization, cryptography, consensus procedures, and immutability. Blockchain networks are decentralized, so they don't rely on any one entity to function. This eliminates one potential point of failure or manipulation. Data is protected from tampering and disclosure thanks to the use of hash functions and digital signatures, two examples of strong cryptographic algorithms. By confirming and agreeing on transactions, consensus methods like Proof of Work (PoW) and Proof of Stake (PoS) keep the blockchain ledger up-to-date and accurate. By linking blocks together and recording timestamps, blockchain makes it practically impossible to alter data after it has been recorded. The distributed ledger's availability to the public and ease of use encourage accountability and deter dishonest participants. Smart contracts eliminate the need for third parties by automating operations based on predetermined rules that cannot be altered after they have been created. This study also delves into blockchain fork resistance, incentives for truthful involvement, and other network security measures. It also covers the security implications of both permissioned and permissionless blockchains. Blockchain technology provides strong security procedures, but it has several drawbacks that must be taken into account. These include issues with scalability and the possibility of security flaws in smart contracts. Therefore, securing security and performance requires cautiously considering particular use case needs and picking the right blockchain platform and configuration. For blockchain networ

关键词： Blockchain Consensus Algorithms Cryptography Immutable Ledger

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Human-machine Hierarchical Networks for Decision Making under Byzantine Attacks 57

Human-machine Hierarchical Networks for Decision Making unde...

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57th Annual Conference on Information Sciences and Systems, CISS 2023

作者： Quan, Chen Geng, Baocheng Han, Yunghsiang S. Varshney, Pramod K. Syracuse University Department of Electrical Engineering and Computer Science Syracuse United States University of Alabama at Birmingham Department of Computer Science Alabama United States Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen China

ISBN: (纸本)9781665451819

This paper proposes a belief-updating scheme in a human-machine collaborative decision-making network to com-bat Byzantine attacks. A hierarchical framework is used to realize the network where local decisions from physical sensors act as reference decisions to improve the quality of human sensor decisions. During the decision-making process, the belief that each physical sensor is malicious is updated. The case when humans have side information available is investigated, and its impact is analyzed. Simulation results substantiate that the proposed scheme can significantly improve the quality of human sensor decisions, even when most physical sensors are malicious. Moreover, the performance of the proposed method does not necessarily depend on the knowledge of the actual fraction of malicious physical sensors. Consequently, the proposed scheme can effectively defend against Byzantine attacks and improve the quality of human sensors' decisions so that the performance of the human-machine collaborative system is enhanced. © 2023 IEEE.

关键词： Decision making

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Crowd-Counting of Images in Rainy Weather Based on GAN-U-Net Model and Multi-column CNN Counting Approaches 3

Crowd-Counting of Images in Rainy Weather Based on GAN-U-Net...

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3rd IEEE International Conference on Electronic engineering, ICEEM 2023

作者： Saad, Rasha A. Abd El-Samie, Fathi E. Abdel-Azim, Mohammed El-Hoseny, Heba M. Obour Higher Institute for Engineering and Technology Department of Electronics and Electrical Communications Egypt Menoufia University Faculty of Electronic Engineering Department of Electronics and Electrical Communications Egypt Mansoura University Faculty of Engineering Department of Electronics and Electrical Communications Egypt The Higher Future Institute for Specialized Technological Studies Department of Computer Science Egypt

ISBN: (纸本)9798350323511

A count of crowds tries to determine the total number of persons in crowded places in order to avoid disruption of the safety system and maintain crowd safety. Accurate estimation of the size of crowds is a challenging process because of numerous challenges like occlusion, complicated backgrounds, varying sizes, uneven distribution, alteration of lighting, and adaptable weather. In this study, we propose a solution to two crowd counting challenges: poor weather such as rain and image scaling. We investigate crowd counting in the rainy Shanghai-Tec images. We adopt the GAN-U-Net de-raining model and the SAS-Net [1] and SGA-Net [2] crowd-counting models in our study. © 2023 IEEE.

关键词： computer vision

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CNN-LSTM: Development of Offline Signature Authentication 1

CNN-LSTM: Development of Offline Signature Authentication

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1st IEEE International Conference on Emerging Research in Computational Science, ICERCS 2023

作者： Ganapathy, Revathy Lingeshwaran, D. Suthanthiradevi, P. Harish Kumar, M.V. Vels Insitute of Science Technology and Advanced Studies Department of Computer Science and Engineering Chennai India Srm Institute of Science and Technology Department of Data Science and Business Systems Chennai India

ISBN: (纸本)9798350359756

Offline Signature Authentication is a critical task in the field of document authentication, and its accuracy is essential for ensuring security while transactions. This research proposes two approaches: Initially Pre-trained CNN models are used to extract features from signature images, which are then combined with handcrafted features such as HOG and some other geometric features of signature. Such combined features are passed to bidirectional LSTM model in which drop out layer undergoes classification which differentiate real and forgery signature. The proposed system has potential applications in document authentication and security, subsequently combination of CNN models and additional features provides more comprehensive representation of signature images resulting in improved accuracy. Three signature datasets are utilized namely GDPS, CEDAR, and BHSig-Bengali each with varying signature styles and image quality. Our experimental outcomes reveal that Bidirectional Convolutional LSTM along with handcraft features attained maximum accuracy in offline signature verification system. © 2023 IEEE.

关键词： Long short-term memory

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