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"Hand Model" - A Static Sinhala Sign Language Translation Using Media-Pipe and SVM Compared with Hybrid Model of KNN, SVM and Random Forest Algorithms 5

"Hand Model" - A Static Sinhala Sign Language Translation Us...

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5th International Conference on Advancements in Computing, ICAC 2023

作者： Gedaragoda, G.H.M.S.C. Wijesinghe, W.R.S. Abeywickrama, T.R. Lokuliyana, Shashika Mahaadikara, Hansika Sri Lanka Institute of Information Technology Faculty of Computing Department of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798350358131

The study of sign language recognition has been a thriving area of research for nearly twenty years. SSL translation using computer vision relies on extensive training using large number of images or video sequences. Yet, it poses a challenge for languages with limited resources, like Sinhala Sign Language. Due to the absence of accessible datasets for such investigations and lack of SSL recognition systems for real-time scenarios, the authors of this research have developed a completed system that consist of three components which are, static sign recognition, dynamic sign recognition and natural language processing to output a meaningful sentence. This paper describes the models and the results which are developed for static sign recognition. The final model for the Sinhala Static recognition has developed using media-pipe and SVM algorithm. And to compare the results and performance authors have used CNN, SVM, KNN and Random-forest algorithms to compare the results and performance. In this research, authors have made a valuable contribution by introducing a new dataset and developing a system for translating static SSL that gives 99.67% of accuracy and best performance when compared to the other two models and algorithms described in this paper. © 2023 IEEE.

关键词： Support vector machines

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Adaptive Hybrid Filtering & Damping Control for Grid-Following MMC

Adaptive Hybrid Filtering & Damping Control for Grid-Followi...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Huang, Pengxiang Vanfretti, Luigi Rensselaer Polytechnic Institute Depart. Electrical Computer and Systems Engineering TroyNY12180 United States

ISBN: (纸本)9798350316445

Oscillation events between grid-following MMC (GFL-MMC) and ac systems in the medium-/high-frequency (MF/HF) range have been widely reported over recent years. To address this issue, this paper proposes an adaptive hybrid filtering and damping (AHFD) control design method to address oscillation issues within the MF/HF range. When lowpass filters with proposed designs are placed into control loops, the negative damping region in the HF range of MMC is eliminated, effectively limiting the potential oscillations to the MF range. In addition, based on online resonance detection, an active narrowband damper is automatically configured to add and adjust positive damping to MMC at the system resonance frequency in the MF range. Both the damper gain and damping range of this narrowband damper are autonomously adjusted through an adaptive tuning unit, thereby eliminating the need for prior knowledge of the MMC's physical characteristics (i.e., its model parameters) for damper design and tuning. Electromagnetic Transient (EMT) simulation results validate the efficacy of the proposed AHFD control method in a power system involving GFL-MMC and long overhead transmission. © 2023 IEEE.

关键词： adaptive control high-frequency resonance medium-frequency resonance modular multilevel converter (MMC) oscillation

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Innovative Data Encryption Techniques using AI for Wireless Sensor Actuator Network Security 2

Innovative Data Encryption Techniques using AI for Wireless ...

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2nd International Conference on Distributed Computing and Optimization Techniques, ICDCOT 2024

作者： Dharmateja, M. Rama, Prabha K.P. Asha, N. Nithya, P. Lalitha, S. Manojkumar, P. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Chennai India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore India Arunai Engineering College Department of Computer Science and Engineering Tamil Nadu Tiruvannamalai India Bannari Amman Institute of Technology Department of Electrical and Electronics Engineering Tamil Nadu Sathyamangalam India

ISBN: (纸本)9798350382952

Wireless Sensor Actuator Networks (WSANs) are sensitive to cyber threats due to present static encryption techniques. Adaptive security methods are required in WSAN settings to reduce evolving dangers and maintain data integrity. The paper introduces a novel method for encrypting WSAN data using AI and machine learning. Long Short-Term Memory (LSTM) networks process data, Genetic Algorithms (GAs) optimize encryption, and Isolation Forests detect threats in real-time. The proposed system achieved remarkable performance, with scores of 98% data integrity, 96% error repair, and 95% threat detection accuracy. Encryption rates reach their max at 200 Mbps, with optimal resource usage (30% CPU, 25% RAM) and a 5% false positive rate. The proposed AI-driven security architecture improves data integrity, encryption speed, and overall security efficacy in WSANs, surpassing existing methods. The paper overcomes the limitations of static encryption methods and proposes a proactive protection mechanism against developing cyber threats, making a substantial contribution to WSAN security improvement. © 2024 IEEE.

关键词： Cryptography

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A Novel Approach for Hashtag Topic Classification with Multimodal Features and VLMs

A Novel Approach for Hashtag Topic Classification with Multi...

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2024 International Conference on Horizons of Information Technology and engineering, HITE 2024

作者： Zafar, Hafiza Tayyaba Tahir, Bilal Mehmood, Muhammad Amir University of Engineering and Technology Al-Khawarizmi Institute of Computer Science Lahore54890 Pakistan Islamic University of Madinah Associated with Faculty of Computer and Information Systems Madinah42351 Saudi Arabia

ISBN: (纸本)9798331516055

The rapid expansion of Instagram content marked by a large volume of photos and comments demands effective methods for discovering topics. While hashtags facilitate the grouping of posts, categorizing these hashtags into specific topics is challenging task due to the multimodal and noisy nature of content on the platform. In this paper, we introduce a novel approach that leverages multimodal features and Vision-Language Models (VLMs) for the topic classification of hashtags. To achieve this, we develop a dataset InstaHash which includes 464 hashtags and 12,345 posts spanning five topic categories: army, politics, sports, judiciary, and religion. We extract text features using the TF-IDF algorithm and visual features using HSV, SIFT, ResNet50, and VGG16 algorithms. Additionally, we introduce 34 binary features derived from the VLM of LLAVA through prompt engineering. These prompt engineering features examine the six aspects of images such as people, symbols and objects, buildings, events, uniforms, and embedded text. We train four classifiers of Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), and Convolutional Neural Network (CNN) for topic classification of hashtags. Our analysis reveals that combining text and visual features yields an accuracy of 0.89 for topic classification with the CNN classifier. However, by incorporating additional prompt features into the model, we achieve the highest accuracy of 0.96. Moreover, we notice that prompt features related to aspects of people and symbols are the most important features for the topic classification of hashtags. © 2024 IEEE.

关键词： Visual languages

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Optimized Design Methodology in Inductive Power Transfer systems Applied to Electric Vehicle Charging 8

Optimized Design Methodology in Inductive Power Transfer Sys...

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8th Southern Power Electronics Conference and the 17th Brazilian Power Electronics Conference, SPEC / COBEP 2023

作者： Viera, Leonardo A. Brum Pascoal, Pedro Gelati Rech, Cassiano RS Santa Maria Brazil Inesc Tec - Institute of Systems and Computer Engineering Technology and Science Porto Portugal

ISBN: (纸本)9798350321128

Technologies related to the transportation electrification have been gaining attention in recent years. One technology that stands out is wireless charging, which still presents numerous challenges in terms of design and optimization of parameters. This article proposes a design methodology for optimizing the performance of an inductive power transfer (IPT) for wireless charging of electric vehicles, taking into account operating limits. The proposed methodology uses a PSO (Particle Swarm Optimization) algorithm to find the design variables that maximize the eficiency. The methodology and the development of a 3.6 kW experimental setup are presented, resulting in a power transfer efficiency of 89.4 %. © 2023 IEEE.

关键词： Electric Vehicle Inductive Power Transfer (IPT) Optimization Design Particle Swarm Optimization (PSO) Wireless Charger Wireless Power Transfer (WPT)

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Deployment Architectures of MQTT Brokers in Event-Driven Industrial Internet of Things 50

Deployment Architectures of MQTT Brokers in Event-Driven Ind...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Amiri, Amirali Just, Valentin Steindl, Gernot Nastic, Stefan Kastner, Wolfgang Gorton, Ian Institute of Computer Engineering TU Wien Vienna Austria Distributed Systems Group TU Wien Vienna Austria Khoury College of Computer Sciences Northeastern University Seattle United States

ISBN: (纸本)9781665464543

The Industrial Internet of Things (IIoT) involves various standards, protocols, and tools, requiring extensive expertise for system design. The traditional automation pyramid limits scalability due to tightly-coupled components. Integrating IIoT data in the cloud through event-driven communication, like MQTT brokers, provides loose coupling. This integration also aids in resource monitoring and planning, enhancing IIoT application performance. Despite many IIoT architecture studies, there is a lack of empirical comparisons of MQTT broker deployment strategies. This paper examines an edge-cloud aggregation scenario, where IIoT device requests are aggregated at the edge and fog services before being transmitted to the cloud. We study four MQTT deployment architectures and compare the results empirically. We use an Arduino Opta as an IIoT device. Also, we use software-based load generation to support replicability of our experiment and reproducibility of our results. Findings indicate that a central broker on a dedicated virtual machine gives 13.8% improvements of the mean response time compared to the shared deployment of MQTT broker and device gateways. Our results offer insights into effective deployment strategies. © 2024 IEEE.

关键词： Industrial internet of things (IIoT)

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Post-operative Smart Healthcare Kit

Post-operative Smart Healthcare Kit

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International Conference on Smart systems and Wireless Communication, SSWC 2024

作者： Kanchana Devi, V. Umamaheswari, E. Gao, Xiao-Ghi Rathinavel, Nirupama School of Computer Science and Engineering Vellore Institute of Technology Chennai India Centre for Cyber Physical Systems Vellore Institute of Technology Chennai India University of Eastern Finland Kuopio Finland

ISBN: (纸本)9789819613472

The Internet of Things is becoming an increasingly important tool for the healthcare sector. It is utilized in common healthcare settings, such as smart watches and oxygen monitors, as well as in hospitals for anything from routine checks to critical care units. One of the most crucial hospital departments is post-operative care, where patients are monitored to make sure they are getting better. Here, a constant watch is kept on the patient’s vital signs and the associated organs to detect any anomalies that might develop following the treatment. Utilizing IoT in post-operative treatment will guarantee patient contentment. This is ensured by the Post-Operative Smart Healthcare Kit (POSHK), presented in this paper, furnished with several sensors, including heartbeat, oxygen and carbon dioxide sensors, blood pressure, room, and patient temperature sensors, and more. During discharge, data is gathered and analyzed to look at possible future recovery trends. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electrotherapeutics

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Mitigation of MMC High-Frequency Oscillations by Wideband Passivation 4

Mitigation of MMC High-Frequency Oscillations by Wideband Pa...

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4th Annual IEEE Kansas Power and Energy Conference, KPEC 2023

作者： Huang, Pengxiang Vanfretti, Luigi Rensselaer Polytechnic Institute Depart. Electrical Computer and Systems Engineering TroyNY12180 United States

ISBN: (纸本)9798350335408

Modular multilevel converters are known to develop high-frequency oscillations (HFOs) with the power system they are connected to, and the root cause is that the system resonance frequencies fall into the delay-induced non-passive region of MMCs. To damp such oscillations, this paper presents a wideband passivation method that can shape the MMC impedance to become completely passive above 100 Hz. This work involves a systematic design approach for using voltage feedforward for passivizing an MMC inverter impedance, and using current feedforward for passivizing MMC rectifier impedance. The effectiveness of the proposed wideband passivation method is verified first by frequency-domain analysis and then validated via EMT simulations. © 2023 IEEE.

关键词： Frequency domain analysis

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Survey on digital twins for Internet of Vehicles:Fundamentals,challenges,and opportunities

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Digital Communications and Networks 2024年第2期10卷 237-247页

作者： Jiajie Guo Muhammad Bilal Yuying Qiu Cheng Qian Xiaolong Xu Kim-Kwang Raymond Choo School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China Department of Computer Engineering Hankuk University of Foreign StudiesGyeonggi-do17035South Korea Jiangsu Hydraulic Research Institute Nanjing210044China Department of Information Systems and Cyber Security University of Texas at San AntonioSan AntonioTX78249-0631USA

As autonomous vehicles and the other supporting infrastructures(e.g.,smart cities and intelligent transportation systems)become more commonplace,the Internet of Vehicles(IoV)is getting increasingly *** have been attempts to utilize Digital Twins(DTs)to facilitate the design,evaluation,and deployment of IoV-based systems,for example by supporting high-fidelity modeling,real-time monitoring,and advanced predictive ***,the literature review undertaken in this paper suggests that integrating DTs into IoV-based system design and deployment remains an understudied *** addition,this paper explains how DTs can benefit IoV system designers and implementers,as well as describes several challenges and opportunities for future researchers.

关键词： Internet of vehicles Digital twin Simulation Traffic systems

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Voltage Relaxation Pattern Recognition for Efficient Sorting of Healthy Cells for Second-Life Applications of Retired Electric Vehicle Batteries 25

Voltage Relaxation Pattern Recognition for Efficient Sorting...

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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Samanta, Akash Karnehm, Dominic Neve, Antje Williamson, Sheldon Ontario Tech University Electrical Computer And Software Engineering Oshawa Canada Institute Of Intelligent Distributed Systems University Of The Bundeswehr Munich Neubiberg Germany

ISBN: (纸本)9798350340266

First-generation electric vehicle (EV) batteries are now retiring from their first life with 70-80%of their initial capacity and are becoming available in the market. To harness the remaining capacity of retired batteries before they reach the end of their life, researchers have proposed various methods, including backup and emergency power supplies for homes, grid-tied stationary energy storage, and storage for renewable energy applications. These applications are collectively termed second-life applications. The first step in utilizing these retired batteries is the selection of healthy cells, as cells in an EV battery pack do not degrade evenly. State-of-the-art cell selection and sorting techniques are either ineffective for industrial-grade applications or highly time-consuming processes. Therefore, this paper proposes a charging voltage relaxation pattern recognition method to efficiently sort healthy cells, powered by data-driven machine learning algorithms. A wide range of battery cycling data collected under different ambient and charging conditions is used for training, testing, and validating the proposed sorting strategy. Furthermore, a comparative analysis is conducted to demonstrate the effectiveness of the proposed strategy compared to state-of-the-art methods. © 2024 IEEE.

关键词： Battery management systems

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