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Empirical techniques for effort estimation in designing effective ML models

International Journal of computers and Applications 2025年第2期47卷 226-234页

作者： Padmanabha Reddy, Y.C.A. Kosuru, Sai Sathwik Sirisalla, Nageswara Rao Vivekananda, G.N. Perala, Venkata Akanksha Department of Artificial Intelligence and Machine Learning Chaitanya Bharati Institute of Technology Telangana Hyderabad India Department of CSE B V Raju Institute of Technology Telangana Narsapur India Department of Computer Science and Engineering K.S.R.M. College of Engineering AP Kadapa India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

Machine Learning Research often involves the use of diverse libraries, modules, and pseudocodes for data processing, cleaning, filtering, pattern recognition, and computer intelligence. Quantization of Effort Required for the above cumulative processes is rarely discussed in the existing works and The time to reach the desired level of the model's functionality is essential to gauge the environment training for the model training and pre-deployment testing. In this study, we empirically defined the manual-cum-computational effort required for the model development in terms of 2-time factors: time-to-live (time until 1st code modification) and time-for-modification (time between 2 codebase changes) taken together in a mathematical model to compute Effort Factor(quantitative measure of determining effort needed to design ML algorithms). The study is novel in terms of how the effort required to create ML models is calculated with a particular focus on the manual effort direction. The results and the findings obtained can be used for determining the total time needed to synthesize ML models and frameworks in terms of code change cycles and implementation strategies marking a 25% performance increase in the current method above the Standard Pipeline. © 2025 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Pipeline codes

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Halo reduction multi-exposure image fusion technique

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Multimedia Tools and Applications 2025年第13期84卷 12347-12370页

作者： Sharif, Rizwan Amin, Benish Sukhia, Komal Nain Department of Electrical Engineering Institute of Space Technology Islamabad Pakistan Department of Computer Science Institute of Space Technology Islamabad Pakistan

Multi-exposure image fusion (MEF) involves combining images captured at different exposure levels to create a single, well-exposed fused image. MEF has a wide range of applications, including low light, low contrast, night photography, medical imaging, and remote sensing. However, MEF methods often face issues like artifacts, halos around edges, color inconsistencies, noise amplification, and difficulty in preserving fine details. Moreover, assessing the quality of fused images objectively is complex due to the subjective nature of human perception. Solving the challenges is essential to developing efficient MEF techniques that produce high-quality results across various scenarios. The proposed technique introduces an approach to handling halo artifacts and implementing MEF. The Dense Scale-Invariant Feature Transform (DSIFT) is used to capture vital information about image brightness, texture, and edges from source images. Three weight maps are computed from the local mean, signal strength, and the global gradient for initial weight estimation. The local mean represents the brightness of specific image areas, signal strength preserves essential details like textures and edges while reducing image noise, and global gradient helps identify regions with significant pixel value shifts across multiple exposure images. The weight maps are then combined using a weighted average and a Gaussian smoothing filter is applied to reduce inherent noise and discontinuities in the original weights. Subsequently, pyramid decomposition is performed to generate a fused image. The efficiency of the proposed method is extensively tested on challenging multi-exposure image sequences. The results of the proposed approach demonstrate its superiority in both subjective evaluation and objective metrics like the MEF-Structural Similarity Index (MEF-SSIM), Natural Image Quality Evaluator (NIQE) and Gradient based performance measure (QAB/f). © The Author(s), under exclusive licence to Springer

关键词： Image fusion

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Towards secure and resilient unmanned aerial vehicles swarm network based on blockchain

IET Blockchain

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IET Blockchain 2024年第S1期4卷 483-493页

作者： Zhou, Xin Yang, Lin Linru, M.A. He, Huasen Academy of Military Science Institute of Systems Engineering Beijing Beijing China University of Science and Technology Institute of Advanced Technology Hefei Hefei China

Blockchain, as an emerging technology, has found diverse applications in solving trust issues in multi-party cooperation. The field of Unmanned Aerial Vehicle (UAV) swarm networks is no exception, as UAVs are susceptible to attacks from malicious counterparts due to limited computing and storage resources. In this paper, the authors present an adaptive networking mechanism for UAVs based on blockchain technology, which incorporates three key technologies. Utilizing Global Unique Identifier (GUID) and block storage, UAVs can achieve rapid identity authentication and efficient swarm switching. By evaluating node participation in block consensus, malicious nodes within the UAV swarm can be accurately identified. Additionally, routing learning based on node security attributes and link quality ensures secure and efficient data transmission. Simulation test results demonstrate the practicality and applicability of the proposed blockchain-based adaptive networking mechanism for UAV swarm networks. © 2023 The Author(s). IET Blockchain published by John Wiley & Sons Ltd on behalf of The Institution of engineering and technology.

关键词： Unmanned aerial vehicles (UAV)

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Research on facial expression recognition based on multimodal data fusion and neural network

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International Journal of Wireless and Mobile Computing 2024年第1期27卷 47-55页

作者： Han, Yi Wang, Xubin Lu, Zhengyu School of Mechanical Science and Engineering Huazhong University of Science and Technology Hubei Wuhan China Anyang Institute of Technology Department of Computer Science and Information Engineering Henan Province Anyang China School of Computer Science and Information Engineering Shanghai Institute of Technology FengXian District Shanghai China

Facial expression recognition is a challenging task when neural network is applied to pattern recognition. Most of the current recognition research is based on single source facial data, which generally has the disadvantages of low accuracy and low robustness. In this paper, a neural network algorithm of facial expression recognition based on multimodal data fusion is proposed. The algorithm is based on the multimodal data, and it takes the facial image, the histogram of oriented gradient of the image and the facial landmarks as the input, and establishes Convolutional Neural Network (CNN) designed to extract features from facial image, neural network designed to extract features from facial Landmarks and Neural Network (LNN) designed to extract features from Histogram of gradient (HNN), three sub-neural networks to extract data features, using multimodal data feature fusion mechanism to improve the accuracy of facial expression recognition. Experimental results show that, the algorithm has a great improvement in accuracy, robustness and detection speed. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Data fusion

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A user-adaptive privacy-preserving authentication of IoMT using zero knowledge proofs with ECC

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Multimedia Tools and Applications 2025年 1-32页

作者： Misra, Garima Hazela, Bramah Chaurasia, Brijesh Kumar Department of Computer Science and Engineering Amity School of Engineering and Technology Lucknow Amity University Uttar Pradesh India Department of Computer Science & Engineering Pranveer Singh Institute of Technology Utter Pradesh Kanpur India

The Internet of Things (IoT) has developed into a crucial component for meeting the connection needs of the current smart healthcare systems. The Internet of Medical Things (IoMT) consists of medical devices that are connected to patients in order to sense their medical parameters and exchange that information with healthcare professionals so they can deliver remote healthcare services. The need to protect the patient’s private information from being misused makes IoMT security an urgent issue that merits further study. Elliptic Curve cryptography (ECC), a popular substitute for traditional public key encryption like RSA, has several advantages. ECC is a prime contender for implementation on constrained devices with confined memory and speed, as well as wireless communication protocols that use low power like IoMT environment. The economic complexity of the current security protocols makes them inappropriate, hence new security protocols must be developed for resource-constrained and diverse IoT networks. This work suggests an authenticated key agreement protocol for the IoMT that is based on elliptic curve encryption based zero-knowledge proof (ZKP) protocols. The proposed mechanism completes in order of milliseconds up to 300 ms for 160 bits. The research will include the comparison between computational delays in traditional protocols and ZKP-ECC protocol. This paper provides a protocol to obtain privacy of data in IoMT environment on the basis of zero knowledge phenomenon and anonymous communication by ZKP-ECC. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Authentication Protocol

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Realizing the potential of Internet of Things (IoT) in Industrial applications

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Discover Internet of Things 2025年第1期5卷 1-16页

作者： Rathi, Bharat Thapaswi, S. Kambhampati, Meghana Jain, Vineet Akshay, P. Pandey, Trilok Nath Pradhan, Sunil Kumar School of Electronics Engineering Vellore Institute of Technology Chennai600127 India School of Computer Science and Engineering Vellore Institute of Technology Chennai600127 India

The Internet of Things (IoT), which enables seamless connectivity and effective data exchange between physical items and digital systems, has completely changed the way we interact with our surroundings. This study evaluates IoT applications in healthcare, transportation, agriculture, and smart cities, highlighting advancements, opportunities, and challenges. Using a systematic literature review and case study analysis, it identifies essential IoT components, including sensors, communication protocols, data analytics, and security methods. Key findings demonstrate IoT's potential to enhance healthcare through real-time monitoring and cost reduction, optimize transportation systems for resource efficiency, improve agricultural productivity via precision farming, and enable sustainable urban development in smart cities. However, challenges like data privacy, interoperability, and scalability remain critical barriers to widespread adoption. This study underscores the need for interdisciplinary collaboration among researchers, policymakers, and industry stakeholders to address these challenges and unlock IoT's full potential. It provides actionable insights and future directions for realizing a connected, efficient, and sustainable IoT-driven future. © The Author(s) 2025.

关键词： Precision agriculture

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Analytical Formulation and Numerical Investigation of Electromechanical Dynamics in Circular Biconvex Diaphragm Capacitive Pressure Sensor

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IEEE Sensors Journal 2025年第11期25卷 18867-18875页

作者： Rukshana Bi, Gajula Motwani, Mayank Jindal, Sumit Kumar Vellore Institute of Technology School of Electronics Engineering Vellore632014 India Vellore Institute of Technology School of Computer Science and Engineering Vellore632014 India

Capacitive pressure sensors (CPSs) have attracted considerable interest due to their high sensitivity, low energy consumption, and potential for miniaturization, making them suitable for applications in automotive systems, consumer electronics, and industrial automation. The conventional designs of CPSs often face challenges such as limited sensitivity, mechanical instability, and difficulties in achieving increased sensitivity. This study presents a biconvex diaphragm using silicon, featuring a gradual thickness variation, with a maximum thickness at the center. This article offers a mathematical analysis of the sensor, featuring step-by-step derivations for parameters such as the maximum thickness of the diaphragm, working range, capacitance, and capacitive sensitivity. Finally, curves of capacitance and capacitive sensitivity with pressure are obtained in MATLAB, and the results are compared with those of prior works. The proposed sensor shows a more than threefold increase in capacitance and a nearly double improvement in capacitive sensitivity compared to the highest previously reported double touch mode capacitive pressure sensor (DTMCPS). The deflection of the diaphragm is obtained using COMSOL. © 2001-2012 IEEE.

关键词： MATLAB

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Automatic Sentimental Analysis by Firefly with Levy and Multilayer Perceptron

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computer systems science & engineering 2023年第9期46卷 2797-2808页

作者： D.Elangovan V.Subedha School of Computing Computer Science and EngineeringSathyabama Institute of Science and TechnologyChennai600118India Computer Science and Engineering Panimalar Institute of TechnologyChennai600069India

The field of sentiment analysis(SA)has grown in tandem with the aid of social networking platforms to exchange opinions and *** people share their views and ideas around the world through social media like Facebook and *** goal of opinion mining,commonly referred to as sentiment analysis,is to categorise and forecast a target’s *** on if they provide a positive or negative perspective on a given topic,text documents or sentences can be *** compared to sentiment analysis,text categorization may appear to be a simple process,but number of challenges have prompted numerous studies in this area.A feature selection-based classification algorithm in conjunction with the firefly with levy and multilayer perceptron(MLP)techniques has been proposed as a way to automate sentiment analysis(SA).In this study,online product reviews can be enhanced by integrating classification and feature *** firefly(FF)algorithm was used to extract features from online product reviews,and a multi-layer perceptron was used to classify sentiment(MLP).The experiment employs two datasets,and the results are assessed using a variety of *** account of these tests,it is possible to conclude that the FFL-MLP algorithm has the better classification performance for Canon(98%accuracy)and iPod(99%accuracy).

关键词： Firefly algorithm feature selection feature extraction multi-layer perceptron automatic sentiment analysis

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Research on lightweight pavement disease detection model based on YOLOv7

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Journal of Intelligent and Fuzzy systems 2024年第4期46卷 10573-10589页

作者： Wang, Chishe Li, Jun Wang, Jie Zhao, Weikang School of Computer Science and Engineering Anhui University of Science and Technology Huainan China Jinling Institute of Technology Nanjing China

Rapid urbanization has made road construction and maintenance imperative, but detecting road diseases has been time-consuming with limited accuracy. To overcome these challenges, we propose an efficient YOLOv7 road disease detection model. Our approach involves integrating MobilieNetV3 as the backbone feature extraction network to reduce the network's parameters and computational requirements. Additionally, we introduce the BRA attention module into the spatial pyramid pooling module to eliminate redundant information and enhance the network's feature representation capability. Moreover, we utilize the F-ReLU activation function in the backbone network, expanding the convolutional layers' receptive field range. To optimize the model's boundary loss, we employ the Wise-IoU loss function, which places more emphasis on the quality of ordinary samples and enhances the overall performance and generalization ability of the network. Experimental results demonstrate that our improved detection algorithm achieves a higher recall rate and mean average precision (mAP) on the public dataset (RDD) and the NJdata dataset in Nanjing's urban area. Specifically, compared to YOLOv7, our model increases the recall rate and mAP on RDD by 3.3% and 2.6%, respectively. On the NJdata dataset, our model improves the recall rate and mAP by 1.9% and 1.3%, respectively. Furthermore, our model reduces parameter and computational requirements by 30% and 22.5%, respectively, striking a balance between detection accuracy and speed. In conclusion, our road disease detection model presents an effective solution to address the challenges associated with road disease detection in urban areas. It offers improved accuracy, efficiency, and generalization capabilities compared to existing models. © 2024 - IOS Press. All rights reserved.

关键词： Roads and streets

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Improved Symbiotic organisms search for path planning of unmanned combat aerial vehicles

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Journal of Ambient Intelligence and Humanized Computing 2023年第4期14卷 4289-4311页

作者： Rajmohan, Shathanaa Ramasubramanian, N. Computer Science and Engineering Indian Institute of Information Technology Chittoor Sri City India Computer Science and Engineering National Institute of Technology Tiruchirappalli India

Unmanned Combat Aerial Vehicles (UCAVs) are becoming a critical part of the military to automate complex missions with minimum risk and increased efficiency. Path planning is a necessary routine for UCAVs to guide them from the initial position to a pre − determined target. The focus of this work is to devise an algorithm to automatically plan the path for UCAVs in a 3D environment that is hostile and contains obstacles. In this work, an improved symbiotic organisms search algorithm with a novel adaptive peaking mechanism is proposed for 3D path planning. The new algorithm has been designed so that the search environment can be efficiently explored and to ensure quick convergence. The performance of the proposed algorithm is analysed with respect to the UCAV path planning and the results and statistical analysis show that the proposed algorithm outperforms other existing algorithms and also achieves an 11% speedup in exploration time. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Motion planning

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