Computing最新文献_第4页

Deep learning-based classification and application test of multiple crop leaf diseases using transfer learning and the attention mechanism 利用迁移学习和注意力机制对多种作物叶片病害进行基于深度学习的分类和应用测试

IF 3.7 3区计算机科学

Computing Pub Date : 2024-07-08 DOI: 10.1007/s00607-024-01308-8

Yifu Zhang, Qian Sun, Ji Chen, Huini Zhou

{"title":"Deep learning-based classification and application test of multiple crop leaf diseases using transfer learning and the attention mechanism","authors":"Yifu Zhang, Qian Sun, Ji Chen, Huini Zhou","doi":"10.1007/s00607-024-01308-8","DOIUrl":"https://doi.org/10.1007/s00607-024-01308-8","url":null,"abstract":"Crop diseases are among the major natural disasters in agricultural production that seriously restrict the growth and development of crops, threatening food security. Timely classification, accurate identification, and the application of methods suitable for the situation can effectively prevent and control crop diseases, improving the quality of agricultural products. Considering the huge variety of crops, diseases, and differences in the characteristics of diseases during each stage, the current convolutional neural network models based on deep learning need to meet the higher requirement of classifying crop diseases accurately. It is necessary to introduce a new architecture scheme to improve the recognition effect. Therefore, in this study, we optimized the deep learning-based classification model for multiple crop leaf diseases using combined transfer learning and the attention mechanism, the modified model was deployed in the smartphone for testing. Dataset that containing 10 types of crops, 61 types of diseases, and different degrees was established, the algorithm structure based on ResNet50 was designed using transfer learning and the SE attention mechanism. The classification performances of different improvement methods were compared by model training. Result indicates that the average accuracy of the proposed TL-SE-ResNet50 model is increased by 7.7%, reaching 96.32%. The model was also integrated and implemented in the smartphone and the test result of the application reaches 94.8%, and the average response time is 882 ms. The improved model proposed has a good effect on the identification of diseases and their condition of multiple crops, and the application can meet the portable usage needs of farmers. This study can provide reference for more crop disease management research in agricultural production.","PeriodicalId":10718,"journal":{"name":"Computing","volume":"37 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141572981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A clarity and fairness aware framework for selecting workers in competitive crowdsourcing tasks 在竞争性众包任务中选择工人的清晰度和公平性意识框架

IF 3.7 3区计算机科学

Computing Pub Date : 2024-07-06 DOI: 10.1007/s00607-024-01316-8

Seyyed Javad Bozorg Zadeh Razavi, Haleh Amintoosi, Mohammad Allahbakhsh

{"title":"A clarity and fairness aware framework for selecting workers in competitive crowdsourcing tasks","authors":"Seyyed Javad Bozorg Zadeh Razavi, Haleh Amintoosi, Mohammad Allahbakhsh","doi":"10.1007/s00607-024-01316-8","DOIUrl":"https://doi.org/10.1007/s00607-024-01316-8","url":null,"abstract":"Crowdsourcing is a powerful technique for accomplishing tasks that are difficult for machines but easy for humans. However, ensuring the quality of the workers who participate in the task is a major challenge. Most of the existing studies have focused on selecting suitable workers based on their attributes and the task requirements, while neglecting the requesters’ characteristics as a key factor in the crowdsourcing process. In this paper, we address this gap by considering the requesters’ preferences and behavior in crowdsourcing systems with competition, where the requester chooses only one worker’s contribution as the final answer. A model is proposed in which the requesters’ characteristics are taken into consideration when finding suitable workers. Also, we propose new definitions for clarity and the fairness of requesters and propose models and formulations to employ them, alongside task and workers’ attributes, to find more suitable workers. We have evaluated the efficacy of our proposed model by analyzing a real-world dataset and compared it with two current state-of-the-art approaches. Our results demonstrate the superiority of our proposed method in assigning the most suitable workers.","PeriodicalId":10718,"journal":{"name":"Computing","volume":"35 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141572982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A new approach for service activation management in fog computing using Cat Swarm Optimization algorithm 使用猫群优化算法的雾计算服务激活管理新方法

IF 3.7 3区计算机科学

Computing Pub Date : 2024-07-04 DOI: 10.1007/s00607-024-01302-0

Sayed Mohsen Hashemi, Amir Sahafi, Amir Masoud Rahmani, Mahdi Bohlouli

{"title":"A new approach for service activation management in fog computing using Cat Swarm Optimization algorithm","authors":"Sayed Mohsen Hashemi, Amir Sahafi, Amir Masoud Rahmani, Mahdi Bohlouli","doi":"10.1007/s00607-024-01302-0","DOIUrl":"https://doi.org/10.1007/s00607-024-01302-0","url":null,"abstract":"Today, with the increasing expansion of IoT devices and the growing number of user requests, processing their demands in computational environments has become increasingly challenging.The large volume of user requests and the appropriate distribution of tasks among computational resources often result in disordered energy consumption and increased latency. The correct allocation of resources and reducing energy consumption in fog computing are still significant challenges in this field. Improving resource management methods can provide better services for users. In this article, with the aim of more efficient allocation of resources and service activation management, the metaheuristic algorithm CSO (Cat Swarm Optimization) is used. User requests are received by a request evaluator, prioritized, and efficiently executed using the container live migration technique on fog resources. The container live migration technique leads to the migration of services and their better placement on fog resources, avoiding unnecessary activation of physical resources. The proposed method uses a resource manager to identify and classify available resources, aiming to determine the initial capacity of physical fog resources. The performance of the proposed method has been tested and evaluated using six metaheuristic algorithms, namely Particle Swarm Optimization (PSO), Ant Colony Optimization, Grasshopper Optimization algorithm, Genetic algorithm, Cuckoo Optimization algorithm, and Gray Wolf Optimization, within iFogSim. The proposed method has shown superior efficiency in energy consumption, execution time, latency, and network lifetime compared to other algorithms.","PeriodicalId":10718,"journal":{"name":"Computing","volume":"58 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing computation reuse efficiency in ICN-based edge computing by modifying content store table structure 通过修改内容存储表结构提高基于 ICN 的边缘计算中的计算重用效率

IF 3.7 3区计算机科学

Computing Pub Date : 2024-07-03 DOI: 10.1007/s00607-024-01312-y

Atiyeh Javaheri, Ali Bohlooli, Kamal Jamshidi

{"title":"Enhancing computation reuse efficiency in ICN-based edge computing by modifying content store table structure","authors":"Atiyeh Javaheri, Ali Bohlooli, Kamal Jamshidi","doi":"10.1007/s00607-024-01312-y","DOIUrl":"https://doi.org/10.1007/s00607-024-01312-y","url":null,"abstract":"In edge computing, repetitive computations are a common occurrence. However, the traditional TCP/IP architecture used in edge computing fails to identify these repetitions, resulting in redundant computations being recomputed by edge resources. To address this issue and enhance the efficiency of edge computing, Information-Centric Networking (ICN)-based edge computing is employed. The ICN architecture leverages its forwarding and naming convention features to recognize repetitive computations and direct them to the appropriate edge resources, thereby promoting “computation reuse”. This approach significantly improves the overall effectiveness of edge computing. In the realm of edge computing, dynamically generated computations often experience prolonged response times. To establish and track connections between input requests and the edge, naming conventions become crucial. By incorporating unique IDs within these naming conventions, each computing request with identical input data is treated as distinct, rendering ICN’s aggregation feature unusable. In this study, we propose a novel approach that modifies the Content Store (CS) table, treating computing requests with the same input data and unique IDs, resulting in identical outcomes, as equivalent. The benefits of this approach include reducing distance and completion time, and increasing hit ratio, as duplicate computations are no longer routed to edge resources or utilized cache. Through simulations, we demonstrate that our method significantly enhances cache reuse compared to the default method with no reuse, achieving an average improvement of over 57%. Furthermore, the speed up ratio of enhancement amounts to 15%. Notably, our method surpasses previous approaches by exhibiting the lowest average completion time, particularly when dealing with lower request frequencies. These findings highlight the efficacy and potential of our proposed method in optimizing edge computing performance.","PeriodicalId":10718,"journal":{"name":"Computing","volume":"34 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Smart contracts auditing and multi-classification using machine learning algorithms: an efficient vulnerability detection in ethereum blockchain 使用机器学习算法进行智能合约审计和多分类：以太坊区块链中的高效漏洞检测

IF 3.7 3区计算机科学

Computing Pub Date : 2024-07-03 DOI: 10.1007/s00607-024-01314-w

Samia El Haddouti, Mohammed Khaldoune, Meryeme Ayache, Mohamed Dafir Ech-Cherif El Kettani

{"title":"Smart contracts auditing and multi-classification using machine learning algorithms: an efficient vulnerability detection in ethereum blockchain","authors":"Samia El Haddouti, Mohammed Khaldoune, Meryeme Ayache, Mohamed Dafir Ech-Cherif El Kettani","doi":"10.1007/s00607-024-01314-w","DOIUrl":"https://doi.org/10.1007/s00607-024-01314-w","url":null,"abstract":"The adoption of Smart Contracts has revolutionized industries like DeFi and supply chain management, streamlining processes and enhancing transparency. However, ensuring their security is crucial due to their unchangeable nature, which makes them vulnerable to exploitation and errors. Neglecting security can lead to severe consequences such as financial losses and reputation damage. To address this, rigorous analytical processes are needed to evaluate Smart Contract security, despite challenges like cost and complexity associated with current tools. Following an empirical examination of current tools designed to identify vulnerabilities in Smart Contracts, this paper presents a robust and promising solution based on Machine Learning algorithms. The objective is to elevate the auditing and classification of Smart Contracts, building trust and confidence in Blockchain-based applications. By automating the security auditing process, the model not only reduces manual efforts and execution time but also ensures a comprehensive analysis, uncovering even the most complex security vulnerabilities that traditional tools may miss. Overall, the evaluation demonstrates that our proposed model surpasses conventional counterparts in terms of vulnerability detection performance, achieving an accuracy exceeding 98% with optimized execution times.","PeriodicalId":10718,"journal":{"name":"Computing","volume":"28 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling end-to-end delays in TSCH wireless sensor networks using queuing theory and combinatorics 利用队列理论和组合学模拟 TSCH 无线传感器网络中的端到端延迟

IF 3.7 3区计算机科学

Computing Pub Date : 2024-07-02 DOI: 10.1007/s00607-024-01313-x

Yevhenii Shudrenko, Andreas Timm-Giel

{"title":"Modeling end-to-end delays in TSCH wireless sensor networks using queuing theory and combinatorics","authors":"Yevhenii Shudrenko, Andreas Timm-Giel","doi":"10.1007/s00607-024-01313-x","DOIUrl":"https://doi.org/10.1007/s00607-024-01313-x","url":null,"abstract":"Wireless communication offers significant advantages in terms of flexibility, coverage and maintenance compared to wired solutions and is being actively deployed in the industry. IEEE 802.15.4 standardizes the Physical and the Medium Access Control (MAC) layer for Low Power and Lossy Networks (LLNs) and features Timeslotted Channel Hopping (TSCH) for reliable, low-latency communication with scheduling capabilities. Multiple scheduling schemes were proposed to address Quality of Service (QoS) in challenging scenarios. However, most of them are evaluated through simulations and experiments, which are often time-consuming and may be difficult to reproduce. Analytical modeling of TSCH performance is lacking, as only one-hop communication with simplified traffic patterns is considered in state-of-the-art. This work proposes a new framework based on queuing theory and combinatorics to evaluate end-to-end delays in multihop TSCH networks of arbitrary topology, traffic and link conditions. The framework is validated in simulations using OMNeT++ and shows below 6% root-mean-square error (RMSE), providing quick and reliable latency estimation tool to support decision-making and enable formalized comparison of existing scheduling solutions.","PeriodicalId":10718,"journal":{"name":"Computing","volume":"14 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141516458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing virtual machine placement efficiency in cloud data centers: a hybrid approach using multi-objective reinforcement learning and clustering strategies 提高云数据中心的虚拟机放置效率：使用多目标强化学习和聚类策略的混合方法

IF 3.7 3区计算机科学

Computing Pub Date : 2024-07-02 DOI: 10.1007/s00607-024-01311-z

Arezoo Ghasemi, Abolfazl Toroghi Haghighat, Amin Keshavarzi

{"title":"Enhancing virtual machine placement efficiency in cloud data centers: a hybrid approach using multi-objective reinforcement learning and clustering strategies","authors":"Arezoo Ghasemi, Abolfazl Toroghi Haghighat, Amin Keshavarzi","doi":"10.1007/s00607-024-01311-z","DOIUrl":"https://doi.org/10.1007/s00607-024-01311-z","url":null,"abstract":"Deploying virtual machines poses a significant challenge for cloud data centers, requiring careful consideration of various objectives such as minimizing energy consumption, resource wastage, ensuring load balancing, and meeting service level agreements. While researchers have explored multi-objective methods to tackle virtual machine placement, evaluating potential solutions remains complex in such scenarios. In this paper, we introduce two novel multi-objective algorithms tailored to address this challenge. The VMPMFuzzyORL method employs reinforcement learning for virtual machine placement, with candidate solutions assessed using a fuzzy system. While practical, incorporating fuzzy systems introduces notable runtime overhead. To mitigate this, we propose MRRL, an alternative approach involving initial virtual machine clustering using the k-means algorithm, followed by optimized placement utilizing a customized reinforcement learning strategy with multiple reward signals. Extensive simulations highlight the significant advantages of these approaches over existing techniques, particularly energy efficiency, resource utilization, load balancing, and overall execution time.","PeriodicalId":10718,"journal":{"name":"Computing","volume":"2 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141516489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Packet header-based reweight-long short term memory (Rew-LSTM) method for encrypted network traffic classification 用于加密网络流量分类的基于数据包头的加权长时短记忆（Rew-LSTM）方法

IF 3.7 3区计算机科学

Computing Pub Date : 2024-07-02 DOI: 10.1007/s00607-024-01306-w

Jiangang Hou, Xin Li, Hongji Xu, Chun Wang, Lizhen Cui, Zhi Liu, Changzhen Hu

引用次数: 0

Back-and-Forth (BaF): a new greedy algorithm for geometric path planning of unmanned aerial vehicles 往返算法（BaF）：一种用于无人飞行器几何路径规划的新贪婪算法

IF 3.7 3区计算机科学

Computing Pub Date : 2024-07-01 DOI: 10.1007/s00607-024-01309-7

Selcuk Aslan

{"title":"Back-and-Forth (BaF): a new greedy algorithm for geometric path planning of unmanned aerial vehicles","authors":"Selcuk Aslan","doi":"10.1007/s00607-024-01309-7","DOIUrl":"https://doi.org/10.1007/s00607-024-01309-7","url":null,"abstract":"The autonomous task success of an unmanned aerial vehiclel (UAV) or its military specialization called the unmanned combat aerial vehicle (UCAV) has a direct relationship with the planned path. However, planning a path for a UAV or UCAV system requires solving a challenging problem optimally by considering the different objectives about the enemy threats protecting the battlefield, fuel consumption or battery usage and kinematic constraints on the turning maneuvers. Because of the increasing demands to the UAV systems and game-changing roles played by them, developing new and versatile path planning algorithms become more critical and urgent. In this study, a greedy algorithm named as the Back-and-Forth (BaF) was designed and introduced for solving the path planning problem. The BaF algorithm gets its name from the main strategy where a heuristic approach is responsible to generate two predecessor paths, one of which is calculated from the start point to the target point, while the other is calculated in the reverse direction, and combines the generated paths for utilizing their advantageous line segments when obtaining more safe, short and maneuverable path candidates. The performance of the BaF was investigated over three battlefield scenarios and twelve test cases belonging to them. Moreover, the BaF was integrated into the workflow of a well-known meta-heuristic, artificial bee colony (ABC) algorithm, and detailed experiments were also carried out for evaluating the possible contribution of the BaF on the path planning capabilities of another technique. The results of the experiments showed that the BaF algorithm is able to plan at least promising or generally better paths with the exact consistency than other tested meta-heuristic techniques and runs nine or more times faster as validated through the comparison between the BaF and ABC algorithms. The results of the experiments further proved that the integration of the BaF boosts the performance of the ABC and helps it to outperform all of fifteen competitors for nine of twelve test cases.","PeriodicalId":10718,"journal":{"name":"Computing","volume":"80 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141509693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AI enabled: a novel IoT-based fake currency detection using millimeter wave (mmWave) sensor 启用人工智能：使用毫米波 (mmWave) 传感器进行基于物联网的新型假币检测

IF 3.7 3区计算机科学

Computing Pub Date : 2024-06-27 DOI: 10.1007/s00607-024-01300-2

Fahim Niaz, Jian Zhang, Muhammad Khalid, Kashif Naseer Qureshi, Yang Zheng, Muhammad Younas, Naveed Imran

引用次数: 0