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共 5927 条记录，以下是181-190 订阅

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Deep Learning for Tea Leaf Disease Detection: Comparing VGG16, Vision Transformer, EfficientNetB3, and Xception 15

Deep Learning for Tea Leaf Disease Detection: Comparing VGG1...

引用

15th international conference on computing communication and networking Technologies, ICCCNT 2024

作者： Ayon, Rokonozzaman Mojumdar, Mayen Uddin Mubin, Arif Shahriar Chakraborty, Narayan Ranjan Hridoy, Al-Amin Gazi Md. Jahidul, Islam Dept. of Computer Science & Engineering Daffodil International University Dhaka Bangladesh

ISBN: (纸本)9798350370249

The need for efficient disease management in crop production is highlighted by the economic relevance of agriculture. Various leaf diseases cause major losses for tea, a staple product in many places. In this paper, a deep learning-based method is provided for the automated identification of illnesses affecting tea leaves. Using the unique architectural benefits of four models: VGG16, ViT (Vision Transformer), EfficientNetB3, and Xception, their performance is examined. Each model's accuracy and effectiveness in classifying diseases are evaluated by conducting a thorough series of experiments on a dataset of photos of tea leaves. The results show that ViT and VGG16 perform better than expected, with accuracies of 96.09% and 98.29%, respectively. These results highlight the effectiveness of transformer-based designs and conventional CNN in the identification of tea leaf disease. Our research also demonstrates how deep learning approaches can improve agricultural practices by enabling early and accurate disease identification, which would facilitate proactive disease control tactics and increase crop output. ©2024 IEEE.

关键词： Plant diseases

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Integrating Software-Defined networking and Fog computing for a Novel Routing Protocol in Vehicular Ad-Hoc Networks 7

Integrating Software-Defined Networking and Fog Computing fo...

引用

7th international conference on Advanced communication Technologies and networking, CommNet 2024

作者： Darabkh, Khalid A. Al-Mistarihi, Mamoun F. Odat, Bayan Abdallah The University of Jordan School of Engineering Computer Engineering Department Amman11942 Jordan Jordan University of Science and Technology Faculty of Engineering Electrical Engineering Department P.O. Box 3030 Irbid22110 Jordan

ISBN: (纸本)9798350367027

This study presents an intelligent strategy designed to enhance the efficacy of routing in VANETs. In particular, this work presents a new clustering approach for Cluster Head (CH) selection based on a weighted formula. Our protocol's objectives are to create clusters and allocate C H to each of them. In our protocol, three significant parameters are involved in C H selection process, including vehicle speed, average vehicle distance among other vehicles, and vehicle LifeTime (LT). By considering vehicle speed, the protocol enhances route stability and dependability while the average distance of a vehicle among other vehicles mitigates long-distance communications. Interestingly, the vehicle LT greatly minimizes the control overhead. Furthermore, for improved programmability and scalability, our approach incorporates novel technologies like Software Defined Network (SDN) and Fog computing (FC) for location awareness. Proper network simulations are performed to test the performance of our proposed protocol, and considerable increases in terms of throughput are achieved over those of our protocol's counterparts. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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Advancing Droop control Dynamics for Equilibrium in Decentralized Microgrids: A Strategy for Enhanced Power Distribution

Advancing Droop Control Dynamics for Equilibrium in Decentra...

引用

2024 international conference on advances in computing, communication, Electrical, and Smart Systems, iCACCESS 2024

作者： Islam, Riadul Kabir, Shaharier Hossain, Md Imran Hannan, Nasif Islam, Md Ashikul Shufian, Abu Lamar University Dept. of Electrical Engineering TX United States American International University-Bangladesh Dept. of Eee Dhaka Bangladesh Eastern University Dept.of Eee Dhaka Bangladesh

ISBN: (纸本)9798350350289

Variations in feeder impedances among Distributed Generators (DGs) within a microgrid lead to inaccuracies in reactive power distribution. Additionally, significant fluctuations in load and diverse droop characteristics among DGs cause fluctuations in the inverter's voltage and frequency, thereby impacting both reactive and active power sharing. The generalized droop control strategy struggles to efficiently distribute both reactive and active power loads among the distributed generators. This paper introduces a decentralized enhanced droop-based control method aimed at improving the equitable distribution of both active and reactive power within an isolated micro grid utilizing inverters. The research then proceeds into enhancing droop control to achieve better optimization and incorporating additional mechanisms to distribute voltage, power, and frequency more effectively among different energy sources. A microgrid consisting of three DGs and three loads is simulated using the MATLAB/Simulink environment, and the proposed control strategy is validated through this simulation. The outcomes offer valuable understanding on addressing challenges related to voltage, power, and frequency imbalances, thereby improving the stability of Microgrids (MGs), and ensuring dependable operation of decentralized energy systems. © 2024 IEEE.

关键词： Reactive power

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Comparison between Direct Torque control based on Space Vector Modulation with Conventional Direct Torque control Technique for Speed control of Three-phase Induction Motor 4

Comparison between Direct Torque Control based on Space Vect...

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4th international conference on advances in Electrical, computing, communication and Sustainable Technologies, ICAECT 2024

作者： Suman, Neha Prasad, Upendra Kumar, Rahul Bit Sindri Department of Electrical Engineering Dhanbad India

ISBN: (纸本)9798350343670

This paper represents comparative performance analysis between switching table based direct torque control (ST-DTC) and direct torque control with space vector modulation (DTC-SVM) for different torque and speed pattern for three-phase induction motor. One of the modern control methods used to regulate AC motor speed is DTC. Basically, DTC is control scheme which directly control the stator flux and torque. Conventional DTC uses switching table for selection of voltage vector. In conventional DTC there is some disadvantages like high torque ripple, machine vibration and noise which are overcome in DTC-SVM technique. In DTC-SVM technique space vector modulation used to improve efficiency of motor by selecting the appropriate voltage vector. Two-level inverter is used for both DTC and DTC-SVM technique. Moreover, in DTCSVM technique have many more advantages like low ripple torque in transient state, lower current distortion, lower switching losses etc. Both the proposed techniques are implemented using MATLAB/ SIMULINK software. DTC-SVM technique provide better results as compare to ST-DTC technique. © 2024 IEEE.

关键词： Direct Torque control Induction Motor Space Vector Modulation Switching Table Two-level Inverter

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Design and control of Swerve Drive Robot Using Kinematic Model 14

Design and Control of Swerve Drive Robot Using Kinematic Mod...

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14th international conference on computing communication and networking Technologies, ICCCNT 2023

作者： Khairnar, Kunal Gavani, Madhukar Nalawade, Satyajeet Department of Automobile Engineering Pune India Department of Computer Engineering Pune India Department of Instrumentation and Control Engineering Pune India

ISBN: (纸本)9798350335095

Nowadays, wheeled mobile robots is an expanding field of scientific research and growing applications in both industrial and non-industrial fields. They are extensively used in surveillance, industrial automation, and transportation task. This paper describes the design and control of the Swerve drive robot with a kinematic model. In this swerve drive, all four swerve modules are operated independently, which provides greater agility and minimal steering hysteresis over the conventional holonomic drive. In Swerve drive, each swerve module is driven by a gear-train and steered by belt drive with the help of a BLDC motor. Each motor has an in-built hall sensor and acts as a feedback element for the PID controller. © 2023 IEEE.

关键词： controllers

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Finite-time Fault-Tolerant Time-Varying Elliptical Formation control of Heterogeneous Multi-agent System for Collaborative Wildfire Monitoring 4

Finite-time Fault-Tolerant Time-Varying Elliptical Formation...

引用

4th international conference on advances in Electrical, computing, communication and Sustainable Technologies, ICAECT 2024

作者： Mawanza, Joewell T. Agee, John T. Bhero, Ernest University of KwaZulu Natal Department of Electrical Engineering Durban4041 South Africa

ISBN: (纸本)9798350343670

Combating wildfires is an inherently perilous occupation, presenting firefighters with numerous risks. One critical responsibility of firefighters is to monitor the progression of fire borders and identify areas prone to further spread. Insufficient understanding of fire spread often results in accidents. The utilization of an air-ground heterogeneous multiple agent system (HMAS), comprising Uncrewed Aerial Vehicles (UAVs) and Uncrewed Ground Vehicles (UGVs), for wildfire surveillance holds immense potential as it can replace humans in hazardous fire tracking tasks, leading to a significant reduction in operational expenses. In this article, we propose a finite-time fault-tolerant elliptical formation control algorithm for an air-ground HMAS, assigned to collaboratively monitor the spreading of wildfires in an elliptical pattern. During the fire monitoring mission, the HMAS encounters communication link and actuator faults. The control algorithm incorporates a High-Order Super-Twist Observer (HOSTO) to estimate the multi-source disturbances, including actuator faults and external disturbances, as well as the Nonlinear Fractional-Order Terminal Sliding Mode (NFTSM) method, featuring a novel sliding surface with an exponential variable. The proposed control algorithm ensures that all agents actively monitor the elliptical wildfire, and the cooperative tracking error converges to zero within a finite time. Comparative simulation results are presented to illustrate the effectiveness of the proposed control scheme. © 2024 IEEE.

关键词： communication link fault fault-tolerant control finite-time control time-varying formation control

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Load Frequency control Scheme controller Design for Isolated and Conventional Two Area Power Systems 4

Load Frequency Control Scheme Controller Design for Isolated...

引用

4th international conference on advances in Electrical, computing, communication and Sustainable Technologies, ICAECT 2024

作者： Soni, Mukesh Mittal, Amit Soomar, Arsalan Muhammad Sahoo, Pooja Markam, Karuna Singh, Shweta Dr. D.Y. Patil Vidyapeeth School of Science and Technology Pune India Dept. of Allied Sciences Bhimtal India GdanskUniversity of Technology Electrical and Control Engineering Gdansk Poland Madhav Institute of Tech. and Science Dept. of Electronics Engineering Gwalior India Ies College of Technology Department of Electronic and Comm. Bhopal India

ISBN: (纸本)9798350343670

The adaptive optimal control approach for the isolated and interconnected power systems, AGC scheme using PI technique is presented in this research. Due to the policy evaluation and policy improvement phases, which analyze and update the cost and control policy, the PI approach can provide adaptive optimal control without using all system states. This is possible through policy evaluation and improvement. An adaptive optimal control strategy based on the PI methodology may be model-free. To complete this work, a comparison of the PI-based and LQR-based schemes efficiency is needed. The adaptive optimum control approach's efficiency has also been studied following several parameter change scenarios. Simulations show that the PI-based adaptive optimum control approach surpasses the LQR-based framework in effectiveness © 2024 IEEE.

关键词： AGC LFC Linear Quadratic Regulator (LQR) LQR Optimal control Power Systems

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Preventing Accident Through Blockchain and IoT 15

Preventing Accident Through Blockchain and IoT

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15th international conference on computing communication and networking Technologies, ICCCNT 2024

作者： Sriram, Suthir Sonar, Pradip Sah Nivethitha, V. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350370249

In today's changing world, the rise in car accidents and deaths on the road is an outcome of increasing traffic and population growth. The World Health Organization (WHO) states that a concerning 1.35 million lives are lost each year due to road accidents with factors like alcohol use, reckless driving and speeding playing roles. To make matters worse a significant 55 percent of road fatalities remain unreported leading to delays in emergency responses and sadly more deaths. To solve this issue, an effective solution emerges through the merging of the Internet of Things (IoT) and blockchain technologies. The proposed system for warning about car collisions combines an Arduino controller with sensors such as accelerometers and vibration sensors. These sensors quickly identify dangers activating the emergency system that uses GPS to pinpoint locations and a GSM module to communicate with emergency services. Immediate alerts are then sent out to designated contacts for help. By incorporating technology into the mix, the efficiency of emergency alerts is further boosted by ensuring communication between vehicles and medical facilities. This integration promotes trust and transparency through encrypted data sharing and verification methods thereby enhancing the reliability of the system. This novel approach significantly reduces fatalities by creating a transparent environment, for emergency assistance. Moreover, the system's cost and easy availability make it suitable for use in all types of vehicles irrespective of their brand or design. Choosing this budget option has promise not just in lowering the number of deaths but also, in improving overall road safety worldwide. © 2024 IEEE.

关键词： Budget control

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Predictive Analytics for Agricultural Futures: Modelling and Forecasting Net Exports of Commodities 1

Predictive Analytics for Agricultural Futures: Modelling and...

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1st IEEE international conference on Electronics, computing, communication and control Technology, ICECCC 2024

作者： Ayineni, Kaarthik Sai Charan Pranav, Pasumarthi Madhava Venkata Vijay Vasanth, A. SRM Institute of Science and Technology Department of Networking and Communications Kattankulathur India

ISBN: (纸本)9798350371802

Agricultural futures markets play a pivotal role in global trade, enabling producers, consumers, and investors to manage risks and capitalize on market opportunities. Accurate prediction of future exports is crucial for informed decision-making in this domain. In this research, we present a comparative analysis of several forecasting algorithms applied to 'Agricultural Commodities Futures Data' sourced from Kaggle. The aim is to predict net exports for the next five years based on the selected commodity. We employ a range of models including Integrated Autoregressive Moving Average (ARIMA), Seasonal Autoregressive Integrate Moving-Average with Exogenous Regressors (SARIMAX), Long Short-Term Memory (LSTM) Least Absolute Shrinkage and Selection Operator (LASSO), Random Forest, and Local regression using LOESS combined with seasonal-trend decomposition. Through a Streamlit application, users can interactively input commodity names and receive forecasts generated by the various models. © 2024 IEEE.

关键词： Predictive analytics

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Automatic Creation of Ontologies and Rules from ML Models for Access control in IoT 15

Automatic Creation of Ontologies and Rules from ML Models fo...

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15th international conference on computing communication and networking Technologies, ICCCNT 2024

作者： Tyagi, Surendra Jinwala, Devesh C. Bhattacharjee, Subhasis Computer Science & Engineering Indian Institute of Technology Jammu India Computer Science & Engineering S. V. National Institute of Technology Surat India

ISBN: (纸本)9798350370249

Ontologies have been increasingly used in designing access control policies in Internet of Things (IoT) systems. Machine Learning (ML) has been extensively used to identify patterns from existing data. Trained ML models can be used on end devices for applying access control for resources and users. However it is unreasonable to deploy ML models into the low-powered and mostly hand-held IoT devices. This paper demonstrates an attempt to exploit the power of ML for generating access control rules. We propose algorithms for generating Ontologies and policy rules from trained ML models. Motivated by their simple design, low or almost no requirement for data preprocessing, no requirement for scaling/normalization of data, simple, intuitive design, and most essentially an inherent ability to optimize, by handling irrelevant features through pruning, we use Decision Trees (DT) for the classification in the proposed approach. For smart home dataset, we show in this paper, automatic creation of Ontologies and policy rules from trained DT models. The resulting Ontologies and Semantic Web Rule Language (SWRL) rules are then deployed into an Ontological framework (Protege) and tested for consistency using a Reasoner. Our approach demonstrates a significant improvement in the efficiency of rule generation and offers a promising direction towards designing automated access control systems. In Protege, we achieve 100% consistency in deployment and testing of the generated access control policies by firing queries. We obtain exactly the same accuracy from Protege queries as we get from ML model. We also propose pruning on DT as a fall-back method for IoT devices with limited computing and memory resources that can handle only limited number of policy rules. The proposed method creates a deployable access control system in a few minutes without any human intervention. Our experiment shows a turnaround time of 5 minutes for the Smart Home dataset. ©2024 IEEE.

关键词： Decision trees

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