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Metrics Evaluation of Bell Pepper Disease Classification Using Deep Convolutional Neural Network (DCNN) 1

2nd International Conference on Women Researchers in Electronics and Computing, WREC 2023

作者： Sowmiya, K. Thenmozhi, M. Department of Computer Science and Engineering SRM Institute of Science and Technology Kattankulathur Chennai India Department of Networking and Communications SRM Institute of Science and Technology Kattankulathur Chennai India

ISBN: (数字)9789819970773

ISBN: (纸本)9789819970766

Crop disease is one of the major issues in agricultural fields. It reduces the food production process and produces a huge economic loss for farmers in agricultural lands. Deep learning models are built for detecting and identifying diseases at an early stage to help the farmers and provide food security. In this paper, transfer learning approach is used to identify and classify the diseased portion of leaves in farming lands. The benchmark dataset was taken from the Internet (Kaggle) for bell pepper leaf for identifying the diseases such as pepper leaf spot, mosaic virus, blight, damping off disease, verticillium wilt, blossom end rot, yellowing leaves, curling leaves, and healthy leaves. Ten pre-trained models are built for recognizing diseases and compared to obtain better accuracy. Adam optimizer and binary cross-entropy is used in the model for calculating loss function. In this paper, experimental results are presented on bell pepper diseases for MobileNetV2 with better accuracy of 99.42%. The various performance metrics such as accuracy, precision, recall and F1-score, ROC curve are used to determine the accuracy of the model. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Crops

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An Explainable Deep Learning Framework for Multi-Class Skin Lesion Classification While Resolving Class Imbalance 2

An Explainable Deep Learning Framework for Multi-Class Skin ...

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2nd International Conference on Power, Electrical, Electronics and Industrial Applications, PEEIACON 2024

作者： Jahan, Israt Efat, Anwar Hossain Hasan, S. M. Mahedy Faruk, Md. Farukuzzaman Srizon, Azmain Yakin Hossain, Md. Rakib Al Mamun, Md. Rajshahi University of Engineering & Technology Department of Computer Science & Engineering Rajshahi6204 Bangladesh Rajshahi University of Engineering & Technology Department of Electronics & Telecommunication Engineering Rajshahi6204 Bangladesh

ISBN: (纸本)9798331517984

Skin lesions are indicative of various skin diseases, including serious conditions like melanoma, which can be life-threatening if not detected early. Automated systems for analyzing dermatoscopic images have shown promise in improving diagnostic accuracy. However, many existing studies rely on pre-trained convolutional neural network (CNN) architectures without customization, leading to potential biases and suboptimal performance. In this study, we propose a customized DenseNet121 architecture tailored for skin lesion classification. We address class imbalance issues through data augmentation and fine-tune the model to extract fine-grained features. Our method surpasses other cutting-edge models in terms of accuracy, precision, recall, specificity, sensitivity, and root mean square (ROC) values. Furthermore, we utilise Gradient-weighted Class Activation Mapping (Grad-CAM) to visually represent the decision-making process of the model. The next study will prioritise the validation of the model using a wide range of datasets and the integration of lesion-related information to enhance its performance. © 2024 IEEE.

关键词： Convolutional neural networks

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"I Have to Use My Son's QR Code to Run the Business": Unpacking Senior Street Vendors' Challenges in Mobile Money Collection in China

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Proceedings of the ACM on Human-computer Interaction 2023年第CSCW1期7卷 1-28页

作者： He, Changyang He, Lu Lu, Zhicong Li, Bo Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong Department of Informatics University of California Irvine United States Department of Computer Science City University of Hong Kong Hong Kong Hong Kong

Mobile payment systems have become an infrastructural component in citizens' socio-economic life in China. The rapid shift to a cashless society demands vendors of all ages to quickly adapt themselves to the ubiquitous mobile payment era. However, how this trend may impact senior vendors, a group that typically uses less technology, remains unknown despite its significance in inclusive mobile payment design. This work aims to address this gap by investigating the challenges and strategies of senior vendors in mobile payment adoption. Particularly, we focus on a traditional low-resource setting with a large volume of senior vendors: street vending. We conduct a qualitative study incorporating field observations on 33 senior street vendors and semi-structured interviews with 15 of them (aged 53-78), and take Moneywork as an analytical lens to unpack their challenges in physical and social interactions. We find that senior street vendors are a group passively adopting mobile payments due to business requirements instead of recognizing their advantages. Vendors with relatively low digital literacy have to take an alternative method - using family members' QR codes - to run the business as family-dependent money receivers. With limited considerations for senior vendors' situational vulnerabilities, unexpected difficulties of payment confirmation emerge during transactions, such as reduced confirmation efficacy under noisy surroundings and degraded hearing. Transaction security issues also appear when mobile payment-based frauds target both confirmation interfaces (e.g., fake sounds of successful payment) and trust systems (e.g., showing half-done proof to flee without paying) in street vending. Finally, we raise a less visible yet critical concern of family-dependent vendors on the lost money freedom when their income flows into their families' wallets. We propose design implications for mobile payment systems to support more secure, efficient and accessible money collec

关键词： Electronic money

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Design of Fuzzy Logic Control Framework for QoS Routing in MANET

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Intelligent Automation & Soft Computing 2023年第3期35卷 3479-3499页

作者： M.Vargheese S.Vanithamani D.Stalin David Ganga Rama Koteswara Rao Department of Computer Science and Engineering PSN College of Engineering and TechnologyTirunelveli627152Tamil NaduIndia Department of Master of Computer Applications M.Kumarasamy College of EngineeringKarur639113Tamil NaduIndia Department of Information Technology Veltech Multitech Dr.Rangarajan Dr.Sakunthala Engineering CollegeChennai600062Tamil NaduIndia Department of Computer Science and Information Technology Koneru Lakshmaiah Education FoundationVaddeswaram522502Andhra PradeshIndia

Wireless networks with no infrastructure arise as a result of multiple wireless devices working *** Mobile Ad hoc Network(MANET)is a system for connecting independently located Mobile Nodes(MNs)via wireless links.A MANET is self-conﬁguring in telecommunications,while MN produces non-infrastructure networks that are entirely *** the MAC and routing layers of MANETs take into account issues related to Quality of Service(QoS).When culling a line of optical discernment communication,MANET can be an effective and cost-saving route cull *** maintain QoS,however,more or fewer challenges must be *** paper proposes a Fuzzy Logic Control(FLC)methodology for specifying a probabilistic QoS guaranteed for *** framework uses network node mobility to establish the probabil-istic quality of *** Logic(FL)implementations were added to Network Simulator-3(NS-3)and used with the proposed FLC framework for *** have found that for a given node’s mobility,the path’s bandwidth decreases with time,hop count,and *** is resolutely based on this fuzzy rule that the priority index for a packet is ***,by avoiding sending pack-ets(PKT)out of source networks when there are no beneﬁcial routes,bandwidth is not *** FLC outperforms the scheduling methods with a wide range of *** improve QoS within MANETs,it is therefore recommended that FLC is used to synchronize ***,using these performance metrics,the QoS-responsible routing can opt for more stable *** on network simulation,it is evident that incorporating QoS into routing protocols is meant to improve traf-ﬁc performance,in particular authentic-time trafﬁc.

关键词： MANET quality of service fuzzy logic mobile node network trafﬁc

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Dynamic Trust Management and AI-Based Multi-Factor Authentication for 6G Machine Type Communications 1

Dynamic Trust Management and AI-Based Multi-Factor Authentic...

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1st International Conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Sinha, Garima Agarwal, Ankita Faculty of Engineering and Technology Department of Computer Science Engineering Ramnagar District Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798331518578

New security concerns about the transmission of sensitive data over enormous networks of linked devices have arisen with the advent of the 6G era and the broad adoption of massive machine-type communication (MTC). The authors of this paper provide a fresh strategy for MFA and dynamic trust management in 6G networks that make use of AI to solve these issues and improve MTC security. This study presents a novel approach to behavioural profiling that takes into account the strengths and weaknesses of machine-type devices. It was necessary to create simulated data to represent many situations due to the wide range of possible network circumstances, device characteristics, ambient variables, applications load of work, and security needs. The efficacy of the suggested remedy was evaluated during six simulation cycles. The findings showed that the framework can adapt to changing network circumstances and device behaviours, with stability demonstrated across many situations. The accuracy rates for implementing MFA ranged from 0.49 to 0.57. This MFA and AI-driven dynamic trust management framework has great potential to improve 6G network MTC security;its adaptability and resilience provide a solid basis for meeting the security concerns that will inevitably arise in the future of 6G networks. To maximize performance and assure successful deployment, more modifications and real-life testing are suggested. © 2025 IEEE.

关键词： Authentication Protocol

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An Enhanced Feature-Based Hybrid Approach for Adversarial PDF Malware Detection 6

An Enhanced Feature-Based Hybrid Approach for Adversarial PD...

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6th International Conference on Electrical engineering and Information and Communication technology, ICEEICT 2024

作者： Hossain, G.M. Sakhawat Deb, Kaushik Sarker, Iqbal H. Chittagong University of Engineering and Technology Department of Computer Science and Engineering Chattogram4349 Bangladesh Rangamati Science and Technology University Department of Computer Science and Engineering Rangamati4500 Bangladesh Centre for Securing Digital Futures Edith Cowan University PerthWA6027 Australia

ISBN: (纸本)9798350385779

Cyber scammers frequently use PDF (Portable Document Format) files to install malicious code and infect consumers' systems. Standard remedies and techniques for identifying adversarial PDF malware are often insufficient to stop it completely. This is because adversarial PDF malware is flexible and doesn't depend on a single set of features. Therefore, this study focuses on efficiently detecting adversarial PDF malware to mitigate the existing challenges. Inspection of adversarial PDF files introduced a flag feature set of 13 freshly discovered flag features. These were combined with the standard feature set to develop an efficient, enhanced feature set. Furthermore, a hybrid approach PDFMALDET consisting of a Random Forest classifier and a Deep Neural Network of just two hidden layers was proposed for adversarial PDF malware detection. The recommended model was executed using the standard, flag, and enhanced feature sets to assess the proposed model's effectiveness. The findings revealed that the suggested approach outperformed various baseline machine learning classifiers by yielding an accuracy of 99.57% on the enhanced feature set. Moreover, the proposed hybrid model performed better than several state-of-the-art works for detecting adversarial PDF malware. © 2024 IEEE.

关键词： Malware

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Seer: Accelerating Block chain Transaction Execution by Fine-Grained Branch Prediction 51st

Seer: Accelerating Block chain Transaction Execution by Fine...

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51st International Conference on Very Large Data Bases, VLDB 2025

作者： Zhang, Shijie Cheng, Ru Liu, Xinpeng Xiao, Jiang Jin, Hai Li, Bo National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong

Increasingly popular decentralized applications (dApps) with complex application logic incur significant overhead for executing smart contract transactions, which greatly limits public block chain performance. Pre-executing transactions off the critical path can mitigate substantial I/O and computation costs during execution. However, pre-execution does not yield any state transitions, rendering the system state inconsistent with actual execution. This inconsistency can lead to deviations in pre-execution paths when processing smart contracts with multiple state-related branches, thus diminishing pre-execution effectiveness. In this paper, we develop Seer, a novel public block chain execution engine that incorporates fine-grained branch prediction to fully exploit pre-execution effectiveness. Seerpredicts state-related branches using a two-level prediction approach, reducing inconsistent execution paths more efficiently than executing all possible branches. To enable effective reuse of pre execution results, Seer employs checkpoint-based fast-path execution, enhancing transaction execution for both successful and unsuccessful predictions. Evaluations with realistic block chain workloads demonstrate that Seer delivers an average of 27.7× transaction-level speedup and an overall 20.6× speedup in the execution phase over vanilla Ethereum, outperforming existing block chain execution acceleration solutions. © 2025, VLDB Endowment, All rights reserved.

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Fixed-time-synchronized control: a system-dimension-categorized approach

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science China(Information sciences) 2023年第7期66卷 177-194页

作者： Wanyue JIANG Shuzhi Sam GE Dongyu LI Institute for Future & Shandong Key Laboratory of Industrial Control Technology School of Automation Qingdao University Department of Electrical and Computer Engineering National University of Singapore School of Cyber Science and Technology Beihang University Shanghai Institute of Satellite Engineering

This study addresses the fixed-time-synchronized control problem of perturbed multi-input multioutput(MIMO) systems. In the task of fixed-time-synchronized control, different dimensions of the output signal in MIMO systems are required to reach the desired value simultaneously within a fixed time *** MIMO system is categorized into two cases: the input-dimension-dominant and the state-dimensiondominant cases. The classification is defined according to the dimension of system signals and, more importantly, the capability of converging at the same time. For each kind of MIMO system, sufficient Lyapunov conditions for fixed-time-synchronized convergence are explored, and the corresponding robust sliding mode controllers are designed. Moreover, perturbations are compensated using the super-twisting technique. The brake control of the vertical takeoff and landing aircraft is considered to verify the proposed method for the input-dimension-dominant case, which shows the essential advantages of decreasing the energy consumption and the output trajectory length. Furthermore, comparative numerical simulations are performed to show the semi-time-synchronized property for the state-dimension-dominant case.

关键词： fixed-time-synchronized convergence sliding mode control perturbed MIMO systems

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Evaluating Service Life of Metal Processing Machinery: An Intelligent Monitoring Perspective

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Mobile Networks and Applications 2024年第3期29卷 935-946页

作者： Wang, Hsiao-Yu Hung, Ching-Hua Chen, Cheng-Hui Department of Mechanical Engineering National Yang Ming Chiao Tung University Hsinchu City300093 Taiwan Department of Computer Science and Information Engineering National Chin-Yi University of Technology Taichung411030 Taiwan

This investigation addresses a range of critical challenges within the domain of mechanical engineering and anticipates their potential impacts. The study’s goals include developing methods for detecting tool breakage in integrated milling-turning machines, evaluating the service life of punching machine components, and determining the durability of molds in forging equipment, alongside other complex issues. The primary aim is to devise a specialized equipment health diagnostic system, designed for complex industrial environments. Industry consultation has revealed that effective monitoring strategies and threshold values must be tailored to the specific characteristics of each piece of equipment and their respective sectors. Despite the metal processing industry lagging roughly a decade behind the semiconductor sector in adopting intelligent monitoring systems, it encounters similar hurdles. These include shrinking labor demographics necessitating increased reliance on shift-based external labor, higher turnover rates impacting the retention of skilled workers for essential tasks such as tool replacements and machinery maintenance. Furthermore, there is a pressing need to maintain traceability for the usage history of molds and punching heads, especially to meet aerospace industry regulations. In response, the sector aims to accomplish two primary goals for its critical production machinery: firstly, to implement diagnostic tools for evaluating the wear and overall quality of tools and molds;secondly, to shift from time-based to condition-based maintenance protocols, adaptable to the frequent mold changes required for varied product fabrication. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Empirical mode decomposition

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Medical Image Analysis Using Soft Computing Feature Selection and Classification of Skin Cancer 1

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International Conference on Modern Electronics Devices and Communication Systems, MEDCOM 2021

作者： Saraswat, Birendra Kumar Srivastava, Shipra Singh, Samender Takuli, Arun Kumar Saxena, Aditya Department of Computer Science and Engineering G.L.A. University Mathura India Department of Information Technology Greater Noida Institute of Technology Greater Noida India Department of Computer Science and Engineering Jaypee Institute of Information Technology Noida India Department of Computer Science and Engineering Hi-Tech Institute of Engineering and Technology Ghaziabad India

ISBN: (数字)9789811963834

ISBN: (纸本)9789811963827

Adaptive resonance theory ARTI neural network (unsupervised learning) is being implemented for the classification of feature values with the objective of carrying out a comparative study with the performance of other technique including multi-layer feed forward network transform (supervised learning). A neural network is applied for the detection/identification of melanoma skin cancer. The images were collected from melanoma database is first processed and some distinguishable features were extracted by a MATLAB GUI. Two classes of the images were used: (a) benign, (b) malignant. A collection of interpreted binary input data, which is digitized from analog data after normalization is, then clustered adaptively with neural network ART-1. The goal of the project is to classify the feature dataset using supervised and unsupervised neural networks. To collect the feature set 1 implemented MATLAB image processing toolbox to create my own MATLAB functions. I created my own ARTI codes in MATLAB 701 (AKTI) to analysis which features are giving better efficiency using different vigilance parameter. Along with these supervised and unsupervised classification and pattern recognition, I am also trying to classify my own data-set of extracted features on Weka machine learning benchmarking software which is nothing but implements machine learning algorithms in JAVA. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Supervised learning

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