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A Cascaded Design of Best Features Selection for Fruit Diseases Recognition

computers, Materials & Continua 2022年第1期70卷 1491-1507页

作者： Faiz Ali Shah Muhammad Attique Khan Muhammad Sharif Usman Tariq Aimal Khan Seifedine Kadry Orawit Thinnukool Department of Computer Science COMSATS University IslamabadWah Campus47080Pakistan Department of Computer Science HITEC University TaxilaTaxila47040Pakistan College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia National University of Science and Technology Islamabad IslamabadPakistan Faculty of Applied Computing and Technology Noroff University CollegeKristiansandNorway Research Group of Embedded Systems and Mobile Application in Health Science College of ArtsMedia and TechnologyChiang Mai UniversityChiang Mai50200Thailand

Fruit diseases seriously affect the production of the agricultural sector,which builds financial pressure on the country’s *** manual inspection of fruit diseases is a chaotic process that is both time and cost-consuming since it involves an accurate manual inspection by an ***,it is essential that an automated computerised approach is developed to recognise fruit diseases based on leaf *** to the literature,many automated methods have been developed for the recognition of fruit diseases at the early ***,these techniques still face some challenges,such as the similar symptoms of different fruit diseases and the selection of irrelevant *** processing and deep learning techniques have been extremely successful in the last decade,but there is still room for improvement due to these ***,we propose a novel computerised approach in this work using deep learning and featuring an ant colony optimisation(ACO)based *** proposed method consists of four fundamental steps:data augmentation to solve the imbalanced dataset,fine-tuned pretrained deep learning models(NasNetMobile andMobileNet-V2),the fusion of extracted deep features using matrix length,and finally,a selection of the best features using a hybrid ACO and a Neighbourhood Component Analysis(NCA).The best-selected features were eventually passed to many classifiers for final *** experimental process involved an augmented dataset and achieved an average accuracy of 99.7%.Comparison with existing techniques showed that the proposed method was effective.

关键词： Fruits diseases data augmentation deep learning features fusion feature selection

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Advancing Sustainable Energy: Analyzing Stochastic Algorithms and Q-Learning for Wind Farm Layout Optimization

Advancing Sustainable Energy: Analyzing Stochastic Algorithm...

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Artificial Intelligence, Robotics and Control (AIRC), International Conference on

作者： Mohamed Elsheikh Amr Yonis Jessica Magdy Omar M. Shehata Computer Science Department Faculty of Media Engineering and Technology German University in Cairo Egypt Mechatronics Engineering Department Faculty of Engineering and Materials Science German University in Cairo Egypt Multi-Robot Systems (MRS) Research Group Cairo Egypt

ISBN: (数字)9798350385076

ISBN: (纸本)9798350385083

This paper presents a comprehensive study on the optimization of wind farm layouts, a critical aspect of enhancing the efficiency and effectiveness of wind energy production. We delve into various optimization techniques, including Simulated Annealing, Genetic Algorithm, Particle Swarm Optimization, Moth Flame Optimization, and Deep Q-Learning. Each optimization technique is explored through a series of case studies, where different configurations and parameters are applied to assess their effectiveness in optimizing wind farm layouts. These techniques are evaluated based on criteria such as computational complexity, optimality of solutions, and repeatability of results. The paper's findings offer insightful comparisons and analyses of each technique, providing an understanding of their respective strengths and limitations in the context of wind farm layout optimization.

关键词： Machine learning algorithms Runtime Wind energy Computational modeling Layout Wind farms Prediction algorithms

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Energy-Efficient Operation of Train Platoons in Urban Rail Transit systems: An MIP Approach 43

Energy-Efficient Operation of Train Platoons in Urban Rail T...

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43rd Chinese Control Conference, CCC 2024

作者： Li, Haodong Yin, Jiateng Tang, Tao D'Ariano, Andrea You, Mengxing Beijing Jiaotong University State Key Laboratory of Advanced Rail Autonomous Operation Beijing100044 China Beijing Jiaotong University School of Systems Science Beijing100044 China RomaTre Universily Computer Science and Aeronautical Technologies Engineering Department of Civi Rome0018511 Italy Nanchang Rail Transit Group CO. Ltd Jiangxi330038 China

ISBN: (纸本)9789887581581

Train platooning, which allows multiple train units to be virtually coupled into a platoon with very short following distances, has become an emerging technology in railway industry. Our study investigates the energy-efficient operation of train platoons to reduce the energy consumption of trains while satisfying time-varying passenger demands in practice. We develop a mixed integer programming (MIP) model to optimize the timetable, running speed and coupling strategies of trains. Considering that the small-size train platoons consume much less energy but can serve fewer passengers, our model involves bi-objectives, i.e., to minimize the passenger waiting time and to minimize the overall energy consumption of trains. We also construct a series of model constraints to limit the movement of trains as well as the time-dependent flows of passengers, since a part of passengers during the peak period may have to wait for a longer time due to the capacity limitation of different sizes of trains. Finally, we conduct real-world case studies on the Beijing subway Yizhuang line to verify the effectiveness of our approach. The results indicate that the energy-efficient operation of train platoons can achieve a better trade-off between service quality and system energy consumption. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Energy efficiency

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A Machine Learning Approach for High Resolution Fractional Vegetation Cover Estimation Using Planet Cubesat and RGB Drone Data Fusion

A Machine Learning Approach for High Resolution Fractional V...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Jacob Nesslage Brittany Lopez Barreto Adam Weingram Erin Hestir Environmental Systems Graduate Group University of California Merced Department of Civil and Environmental Engineering University of California Merced Department of Electrical Engineering and Computer Science University of California Merced

High resolution fractional vegetation cover (HR-FVC) is important for many applications, including precision agriculture, forestry, and conservation. For land managers, HR-FVC is most useful when the data can be produced quickly with minimal effort. In this study, we perform data fusion of RGB drone data and multispectral cubesat data for synthetic daily HR-FVC estimation. First, binary classification of 10cm resolution drone data was used to identify vegetation. An AdaBoost model (Accuracy = 0.868, F1-score = 0.840) was selected for further analysis. HR-FVC training data was then produced from drone vegetation maps by calculating the FVC in a 3m pixel – Planet SuperDove resolution, resulting in 238,270 training points. A random forest regression model was used to predict HR-FVC from Planet SuperDove data. The final model’s performance is comparable to similar studies (R 2 = 0.720, RMSE = 0.213), suggesting the methodology could be viable for applications requiring daily HR-FVC datasets.

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Estimating Complexity for Perception-based ADAS in Unstructured Road Environments

Estimating Complexity for Perception-based ADAS in Unstructu...

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IEEE Symposium on Intelligent Vehicle

作者： Imane Taourarti Ayesha Choudhary Vivek Kumar Paswan Aditya Kumar Arunkumar Ramaswamy Javier Ibanez-Guzman Bruno Monsuez Adriana Tapus Autonomous Systems and Robotics Lab/U2IS Computer Science and System Engineering (U2IS) ENSTA Paris Institut Polytechnique de Paris France Research Department Renault Group France School of Computer and Systems Sciences Jawaharlal Nehru University New Delhi India

ISBN: (数字)9798350348811

ISBN: (纸本)9798350348828

Advanced Driver Assistance systems (ADAS) are rapidly becoming a standard feature in modern road vehicles, enhancing safety and driver comfort. As ADAS adoption expands across diverse geographical and cultural regions, the performance of camera-based perception systems may vary significantly due to environmental and expected social behaviour of the different actors. This paper explores the referred factors and evaluates the traffic environment complexity for vehicles with different levels of automation. In particular, we propose a novel modeling and quantitative assessment approach for environment complexity. Specifically, we compare a perception model trained on United States dataset with a dataset from India, a nation characterized by unique traffic patterns, signage conventions, and cultural norms to assess its performance variation, and to lay the basis for proposing influencing factors of traffic environment complexity. We establish a scheme of referential and additional static factors and based on an expert evaluation, environment complexity is established. The effectiveness of the proposed approach is testified by naturalistic driving data. These findings pave the way for future research in intelligent driving and emphasize the importance of addressing cultural nuances as vehicle automation levels increase.

关键词： Measurement Automation Roads Road vehicles Globalization Complexity theory Safety

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Model-Based Design of a Collaborative Human-Robot Workspace

Model-Based Design of a Collaborative Human-Robot Workspace

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Rifa Rahmayanti Juan C. Alvarez Diego Alvarez Antonio M. López Department of Electrical Electronic Computer and Systems Engineering Multisensor Systems and Robotics Group (SiMuR) University of Oviedo Gijón Spain

ISBN: (数字)9781728188591

ISBN: (纸本)9781665406802

This paper presents a complete design and validation of a specific case of a Human-Robot collaborative workspace consisting of a robot arm and a human operator working in a pick & place task in close proximity. The human motion monitoring is made with IMU-based wearables and optical markers, and the robot motion planning method considers safety distance criteria as prescribed in ISO/TS 15066. This case study is meant to illustrate the design of collaborative environments by using the Model-based Design approach. The goal is to systematically address the problems of safety assurance and performance optimization, allowing the use of optimization and machine learning approaches.

关键词： Wearable computers Collaboration Machine learning Manipulators Safety Planning Task analysis

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Attention Model-Driven Maddpg Algorithm for Delay and Cost Aware Placement of Service Function Chains in 5g

SSRN

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SSRN 2024年

作者： Munshi, Joy Sultana, Sumaya Hassan, M.D. Jahid Roy, Palash Razzaque, M.D. Abdur Alkhamees, Bader Fahad Uddin, M.D. Zia Hassan, Mohammad Mehedi Department of Computer Science and Engineering Green University of Bangladesh Narayanganj Dhaka 1461 Bangladesh Green Networking Research Group Department of Computer Science and Engineering University of Dhaka Bangladesh Department of Information Systems College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia Sintef Digital Oslo Norway

The rapidly expanding applications of 5G networks necessitate strategic placement of Virtual Network Functions (VNFs) within Service Function Chains (SFCs) to minimize placement costs while delivering real-time services to users. The dual objectives of this efficient placement strategy are to simultaneously reduce resource usage costs and application service delays in the 5G network. Previous studies have limitations, typically constrained by fixed resource costs or by adopting a greedy approach for resource selection from nearby nodes. In this paper, we introduce a multi-objective linear programming (MOLP) based optimization framework designed for the placement of VNFs in SFC requests, considering a real-time pricing scheme of the resources and the demands of user applications. This framework allows for the analysis of the boundary performances regarding cost and delay, facilitating a balanced trade-off between the two. Given that this problem is proven to be NP-hard in large networks, we have also developed a Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm, which leverages an attention model-based approach for the placement of SFC VNFs. This method focuses on neighboring nodes to help agents reduce the complexity of the solution and effectively capture the dynamic nature of the network environment. Simulation experiments demonstrate that our proposed system model surpasses existing state-of-the-art approaches in terms of resource placement cost and service latency. © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

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SID: Service Identification and Discovery Framework for Decentralised Supply Chains

SID: Service Identification and Discovery Framework for Dece...

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Software Services engineering (SSE) IEEE International Conference on

作者： Hang Zhao Helen Paik Qin Wang Shining Chen School of Computer Science and Engineering The University of New South Wales Sydney Australia Software Systems Group CSIRO Data61 Sydney Australia

The traditional decentralised supply chains are facing challenges to meet the increasing demands for openness, transparency, trust and efficiency. As a result, blockchain-based decentralised supply chains are emerging. However, how to identify and discover various services in a decentralised supply chain remains an unsolved issue. This paper presents a new framework for modelling and discovering services in decentralised supply chain systems. In the framework, W3C Decentralised Identifier (DID) is adopted to describe service attributes to meet different business and technical requirements for a supply chain service. While blockchain is used for publishing and storing DID, a graphic-database-based service repository is proposed to organize these DID strings in a natural way as a graph for better service discovery. An Ethereum-based prototype is implemented as a proof of concept to demonstrate its feasibility and usefulness.

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A Review of Pseudonym Change Strategies for Location Privacy Preservation Schemes in Vehicular Networks

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ACM Computing Surveys 2025年第8期57卷 1-37页

作者： Benarous, Leila Zeadally, Sherali Boudjit, Saadi Mellouk, Abdelhamid Department of Computer science Amar Telidji University of Laghouat Laghouat Algeria LISSI-Tinc-NET Laboratory University of Paris-Est Creteil Créteil France College of Communication and Information University of Kentucky Lexington United States Department of Electronic Engineering Kyung Hee University Seoul Korea Republic of Litis Lab Intelligent Transportation Systems Group University of Rouen Normandy Mont-Saint-Aignan France Lissi Laboratory Department of Networks and Telecom University Paris-Est Créteil Val de Marne Créteil France

Location privacy protection in vehicular networks has been a primary priority to ensure because of its direct impact on human physical safety. Leakage and violation of road users' location privacy may be perilous beyond simple curiosity as it may scale to cyberstalking and tracking. This may lead to road users being subjected to mental and physical distress, from blackmailing to targeted advertising, and trap planning. The results of tracking may be fatal to road users. Over the past 17 years, researchers have been actively investigating location privacy protection mechanisms for vehicular networks. Numerous research results have been published that examined the use of pseudonym change strategies, which have been considered as the most appropriate solution that maintains the tradeoff between ease of application, good protection level, and the correct functionality of the network. We evaluate, classify, and analyze pseudonym change strategies aimed at location privacy preserving solutions for vehicular networks and discuss their performance. We also review the simulation tools used for evaluating pseudonym change techniques used in location privacy preserving solutions for the vehicular environment. The results of this survey will help researchers in this field to develop more robust, efficient, and cost-effective location privacy protection schemes in the future. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Differential privacy

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Designing and simulating IoT environments by using a model-driven approach*

Designing and simulating IoT environments by using a model-d...

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Iberian Conference on Information systems and Technologies (CISTI)

作者： José A. Barriga Pedro J. Clemente Department of Computer and Telematic Systems Engineering Quercus Software Engineering Group Universidad de Extremadura C&#x00E1 ceres Spain

Developing, deploying and testing IoT projects require high investments on devices, fog nodes, cloud nodes, analytic nodes, hardware and software. However, in order to decrease the cost associated to develop and test the IoT system it can be previously simulated. In this regard, designing IoT simulation environments has been tackled focusing on low level aspects such as networks, motes and so on more than focusing on the high level concepts related to IoT environments. Model-driven development aims to develop the software systems from domain models which capture at high level the domain concepts and relationships, generating from them the software artefacts by using code-generators. In this paper, a model-driven development approach is applied to define, generate code and deploy IoT systems simulations. The IoT simulation environment generated from each model includes the sensors, actuators, fog nodes, cloud nodes and analytical characteristics. Additionally, a case study, focused on an Industrial IoT environment is presented to show the simulation expressiveness.

关键词： Analytical models Codes Focusing computer architecture Sensor phenomena and characterization Software systems systems simulation

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