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International Conference on Machine Learning and Big Data Analytics, ICMLBDA 2023

作者： Dekka, Satish Raju, K. Narasimha Sai, D. Manendra Pallavi, M. Sambana, Bosubabu JNTU-GV Andhra Pradesh Vizianagaram India Andhra University Andhra Pradesh Visakhapatnam India Department of Computer Science and Engineering Vignan’s Institute of Engineering for Women Visakhapatnam JNTU-GV Andhra Pradesh Vizianagaram India Department of Data Science School of Computing Mohan Babu University Andhra Pradesh Tirupathi India

ISBN: (纸本)9783031513374

One of the most important and complex issues in the IoT context is energy usage. Because the many nodes utilized in IoT contexts are energy-constrained and must operate for long periods of time without human interaction, their batteries quickly run out of power. As a result, nodes must manage their energy effectively. Sensing, communicating, and processing are regarded as the primary functions of IoT sensors. IoT connectivity uses more energy at the node level than at other times. The main motto of this study is to reduce energy consumption and lengthen network life. Although routing also has a major impact on energy usage, the first one deals with employing an energy model, and the second one deals with selecting an effective routing protocol. When picking a protocol, various other performance indicators such as throughput, delay, packet delivery ratio, and packet loss are also considered. The Network Simulator 3 is used as a tool for testing these strategies (NS3). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Energy Model Green IoT Green networks MANET NS3 Routing

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Distributed robust fuzzy control for mixed-order multi-agent systems ensuring global consensus

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science China Technological sciences 2025年

作者： Xiaoli YANG Jiaxi CHEN Xinbo GAO Shuzhi Sam GE Key Laboratory of Intelligent Analysis and Decision on Complex Systems School of Mathematics and StatisticsChongqing University of Posts and Telecommunications School of Mathematics and Statistics Xidian University School of Computer Science and Technology Chongqing University of Posts and Telecommunications Department of Electrical and Computer Engineering National University of Singapore

This study investigates the global consensus problem of mixed-order multi-agent systems. Firstly, a control strategy based on switching functions is proposed to ensure the effective operation of fuzzy control in the fuzzy region. Secondly, the differential equation model satisfying the global Lipschitz condition is extended, and a more universal model framework is constructed. Furthermore, online learning laws with time-varying σ-modifications are introduced to effectively guarantee the global asymptotic convergence of the closed-loop multi-agent systems. Finally, the effectiveness of the proposed algorithm is validated through designed simulation experiments.

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From Vision to Motion: Translating Large-Scale Knowledge for Data-Scarce IMU Applications

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IEEE Transactions on Mobile computing 2025年

作者： Yoon, Hyungjun Cha, Hyeongheon Nguyen, Hoang C. Gong, Taesik Lee, Sung-Ju KAIST School of Electrical Engineering Korea Republic of Stony Brook University Department of Computer Science NY United States UNIST Department of Computer Science and Engineering Artificial Intelligence Graduate School Korea Republic of

Pre-training representations acquired via self-supervised learning could achieve high accuracy on even tasks with small training data. Unlike in vision and natural language processing domains, pre-training for IMU-based applications is challenging, as there are few public datasets with sufficient size and diversity to learn generalizable representations. To overcome this problem, we propose IMG2IMU that adapts pre-trained representation from large-scale images to diverse IMU sensing tasks. We convert the sensor data into visually interpretable spectrograms for the model to utilize the knowledge gained from vision. We further present a sensor-aware pre-training method for images that enables models to acquire particularly impactful knowledge for IMU sensing applications. This involves using contrastive learning on our augmentation set customized for the properties of sensor data. Our evaluation with four different IMU sensing tasks shows that IMG2IMU outperforms the baselines pre-trained on sensor data by an average of 9.6%p F1-score, illustrating that vision knowledge can be usefully incorporated into IMU sensing applications where only limited training data is available. © 2002-2012 IEEE.

关键词： Contrastive Learning

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Formal Analysis of electrical Circuit Network Topologies Using Theorem Proving

Formal Analysis of Electrical Circuit Network Topologies Usi...

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Annual IEEE Systems Conference

作者： Kubra Aksoy Adnan Rashid Osman Hasan Sofiène Tahar Department of Electrical and Computer Engineering Concordia University Montreal Quebec Canada School of Electrical Engineering and Computer Science National University of Science and Technology Islamabad Pakistan

ISBN: (数字)9798331508180

ISBN: (纸本)9798331508197

electrical circuit networks consist of various electrical components connected in different arrangements that are used to process electrical signals, such as voltages and currents. Moreover, they are widely used in many engineering and physical systems, such as control, embedded and communication systems. In this work, we propose to use higher-order-logic theorem proving for formally analyzing electrical circuit networks using network topology matrices. In particular, we formalize in the Is-abellelHOL theorem prover incidence and circuit (loop) matrices, which are widely used topology matrices. Our formalization is based on modeling the system as a network using the notion of directed graphs that are algebraically represented by matrices. Next, we use this formalization to formally analyze various network topologies, such as Δ- $Y$ and ∏ - $L$ topologies, where we perform Kirchhoff's current and voltage laws based analysis in a generic way.

关键词： Network topology Communication systems Directed graphs Bridge circuits Network analyzers Control systems Matrices Libraries Topology Integrated circuit modeling

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Support Vector Machine Based Handwritten Hindi Character Recognition and Summarization

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computer Systems science & engineering 2022年第10期43卷 397-412页

作者： Sunil Dhankhar Mukesh Kumar Gupta Fida Hussain Memon Surbhi Bhatia Pankaj Dadheech Arwa Mashat Department of Computer Science&Engineering Swami Keshvanand Institute of TechnologyManagement&GramothanJaipurRajasthan302017India Department of Electrical Engineering Sukkur IBA UniversityPakistan Department of Mechatronics Engineering Jeju National UniversityJeju63243Korea Department of Information Systems College of Computer Science and Information TechnologyKing Faisal UniversitySaudi Arabia Faculty of Computing&Information Technology King Abdulaziz UniversityRabigh21911Saudi Arabia

In today’s digital era,the text may be in form of *** research aims to deal with the problem by recognizing such text and utilizing the support vector machine(SVM).A lot of work has been done on the English language for handwritten character recognition but very less work on the under-resourced Hindi language.A method is developed for identifying Hindi language characters that use morphology,edge detection,histograms of oriented gradients(HOG),and SVM classes for summary *** rank employs the summary to extract essential phrases based on paragraph position,phrase position,numerical data,inverted comma,sentence length,and keywords *** primary goal of the SVM optimization function is to reduce the number of features by eliminating unnecessary and redundant *** second goal is to maintain or improve the classification system’s *** experiment included news articles from various genres,such as Bollywood,politics,and *** proposed method’s accuracy for Hindi character recognition is 96.97%,which is good compared with baseline approaches,and system-generated summaries are compared to human *** evaluated results show a precision of 72%at a compression ratio of 50%and a precision of 60%at a compression ratio of 25%,in comparison to state-of-the-art methods,this is a decent result.

关键词： Support vector machine(SVM) optimization precision Hindi character recognition optical character recognition(OCR) automatic summarization and compression ratio

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Development and Control of Quadrotors Using Constrained Model Predictive Control in a Co-Simulation Environment

Development and Control of Quadrotors Using Constrained Mode...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Long, Sian Zhao, Na Qin, Chaojun Luo, Yudong He, Zhipeng Shen, Yantao Dalian Maritime University Department of Computer Science and Technology Liaoning Dalian116026 China School of Mechatronical Engineering Beijing Institute of Technology Beijing100081 China University of Nevada Department of Electrical and Biomedical Engineering RenoNV89557 United States

ISBN: (纸本)9781665481090

Model Predictive Control (MPC) is commonly used to solve flight control problems in quadrotors due to its ability to handle multivariate and practical constraints. Considering its computational problem, which may lead to untimely control signal updates and thus affect flight stability, we adopt cascade control, where an MPC controller is used for attitude control in the inner loop, and a PD controller is used for position control in the outer loop to reduce the computational load. In the inner loop, physical constraints are considered, and an augmented MPC is constructed to reduce the steady-state error. Finally, we build a co-simulation environment based on Matlab and Coppeliasim to verify the proposed control scheme. © 2024 IEEE.

关键词： Predictive control systems

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Screening and Characterization of Aroma and Flavor-Producing Bacteria and Yeast from Traditional Fermented Food and Beverages of Northeast, India 2nd

Screening and Characterization of Aroma and Flavor-Producing...

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2nd NIELIT's International Conference on Communication, Electronics and Digital Technologies, NICEDT 2024

作者： Borthakur, Debashree Barlaskar, Esha Medhi, Smriti Priya Sharma, Bipin Kumar Department of Microbiology Tripura University Tripura India Department of Bio Sciences Assam Don Bosco University Assam Guwahati India School of Electronics Electrical Engineering and Computer Science Queen’s University Belfast Northern Ireland Belfast United Kingdom Department of Computer Science and Engineering Assam Don Bosco University Assam Guwahati India

ISBN: (纸本)9789819736003

Fermented foods in India are diverse and play a significant role in the country's culinary traditions. These foods are often categorized based on their base material and include a variety of items with reported medicinal properties. Some examples of these fermented foods are: Dahi, Gundruk, Sinki, Inziangsang, Iromba, etc. While there were initially limited reports on the extraction of lactic acid bacteria (LAB) from Indian fermented dishes, the growing awareness toward the health benefits associated with LAB has spurred increased research in this domain. LAB are known for their probiotic properties, promoting gut health and overall well-being. The increasing interest in the health benefits attributed to lactic acid bacteria (LAB) offers a valuable opportunity for food microbiologists to delve deeper into the study and exploration of fermented foods. In the current study, bacteria and yeast were isolated from the different traditional fermented foods of northeast, and their potential of flavor production was studied. These isolated strains were used to check the potential of undergoing fermentation and flavor production by inoculating the isolated strains in the raw milk for the development of novel probiotic products. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Yeast

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UAV-mounted Intelligent Reflecting Surface (IRS) MISO Communications

UAV-mounted Intelligent Reflecting Surface (IRS) MISO Commun...

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2022 International Conference on Networking and Network Applications, NaNA 2022

作者： Li, Kaixin Zhao, Ke Khan, Muhammad Fawad Ho, Pin-Han Peng, Limei School of Computer Science and Engineering Kyungpook National University Deagu Korea Republic of University of Waterloo Department of Electrical and Computer Engineering WaterlooON Canada

ISBN: (数字)9781665461313

ISBN: (纸本)9781665461313

This paper proposes using the unmanned aerial vehicle (UAV)-mounted intelligent reflecting surface (IRS) as a flying relay to enable the communication between the base station (BS) and suburb access points (APs). Since the UAV flight endurance is mainly affected by the weight of the IRS mounted on it, it is significant to reduce the IRS weight by minimizing the number of its reflecting elements. Regarding this, we propose an Optimized Phase Shift (OPS) algorithm to adjust the phase shift of the IRS reflecting elements, aiming to minimize the number of IRS reflecting elements required to successfully serve the APs while satisfying the signal-to-noise ratio (SNR) requirement. © 2022 IEEE.

关键词： Signal to noise ratio

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An Investigation into Spectral Efficiency Enhancement of Fiber-Optic Communication via High-Speed Spectrum Management 2

An Investigation into Spectral Efficiency Enhancement of Fib...

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2nd IEEE International Conference on Futuristic Technologies, INCOFT 2023

作者： Singh, Khushboo Lalitha, Sai Ravivarman, G. Sasirekha, R. Shinde, Swapnil K. Singh, Akhilendra Pratap Vivekananda Global University Department of Computer Science & Engineering Jaipur India Department of Computer Science and Information Technology Karnataka Bangalore India Department of Electrical and Electronics Engineering Karpagam Academy of Higher Education Coimbatore641021 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350308846

This research appears into the effectiveness of high-pace spectrum management as a way to beautify the spectral performance of fiber-optic conversation. that is finished by means of forecasting a dynamic optical visitors arrival pattern to reduce carrier-degree blocking off opportunity, and with the aid of allocating the maximum green bandwidth to every request based totally on a non-blocking priority-based totally scheduling algorithm. This study assesses the overall performance of modern-day systems, analyzes their shortcomings, and uses experimental consequences to evaluate their effectiveness for improving spectral efficiency. The findings endorse that there's ability for improvement in spectral efficiency with excessive-speed spectrum control. © 2023 IEEE.

关键词： Control Efficiency Excessive Improvement Spectrum

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Unifying Generation and Prediction on Graphs with Latent Graph Diffusion 38

Unifying Generation and Prediction on Graphs with Latent Gra...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Zhou, Cai Wang, Xiyuan Zhang, Muhan Department of Automation Tsinghua University China Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology United States Institute for Artificial Intelligence Peking University China School of Intelligence Science and Technology Peking University China

In this paper, we propose the first framework that enables solving graph learning tasks of all levels (node, edge and graph) and all types (generation, regression and classification) using one formulation. We first formulate prediction tasks including regression and classification into a generic (conditional) generation framework, which enables diffusion models to perform deterministic tasks with provable guarantees. We then propose Latent Graph Diffusion (LGD), a generative model that can generate node, edge, and graph-level features of all categories simultaneously. We achieve this goal by embedding the graph structures and features into a latent space leveraging a powerful encoder and decoder, then training a diffusion model in the latent space. LGD is also capable of conditional generation through a specifically designed cross-attention mechanism. Leveraging LGD and the "all tasks as generation" formulation, our framework is capable of solving graph tasks of various levels and types. We verify the effectiveness of our framework with extensive experiments, where our models achieve state-of-the-art or highly competitive results across a wide range of generation and regression tasks. © 2024 Neural information processing systems foundation. All rights reserved.

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