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A semi-supervised deep neuro-fuzzy iterative learning system for automatic segmentation of hippocampus brain MRI

Mathematical Biosciences and engineering 2024年第12期21卷 7830-7853页

作者： Nisha, M. Kannan, T. Sivasankari, K. Department of Computer Science and Engineering Akshaya College of Engineering and Technology Tamil Nadu Coimbatore India Department of Mechanical Engineering Amrita College of Engineering and Technology Tamil Nadu Nagercoil India Department of Electronics and Engineering Akshaya College of Engineering and Technology Tamil Nadu Coimbatore India

The hippocampus is a small, yet intricate seahorse-shaped tiny structure located deep within the brain’s medial temporal lobe. It is a crucial component of the limbic system, which is responsible for regulating emotions, memory, and spatial navigation. This research focuses on automatic hippocampus segmentation from Magnetic Resonance (MR) images of a human head with high accuracy and fewer false positive and false negative rates. This segmentation technique is significantly faster than the manual segmentation methods used in clinics. Unlike the existing approaches such as UNet and Convolutional Neural Networks (CNN), the proposed algorithm generates an image that is similar to a real image by learning the distribution much more quickly by the semi-supervised iterative learning algorithm of the Deep Neuro-Fuzzy (DNF) technique. To assess its effectiveness, the proposed segmentation technique was evaluated on a large dataset of 18,900 images from Kaggle, and the results were compared with those of existing methods. Based on the analysis of results reported in the experimental section, the proposed scheme in the Semi-Supervised Deep Neuro-Fuzzy Iterative Learning System (SS-DNFIL) achieved a 0.97 Dice coefficient, a 0.93 Jaccard coefficient, a 0.95 sensitivity (true positive rate), a 0.97 specificity (true negative rate), a false positive value of 0.09 and a 0.08 false negative value when compared to existing approaches. Thus, the proposed segmentation techniques outperform the existing techniques and produce the desired result so that an accurate diagnosis is made at the earliest stage to save human lives and to increase their life span. © 2024 the Author(s),

关键词： Convolutional neural networks

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Efficient resource allocation for D2D-enabled social IoT networks:A tripartite and time-scale optimization approach

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Intelligent and Converged Networks 2024年第4期5卷 380-401页

作者： Saurabh Chandra Rajeev Arya Maheshwari Prasad Singh Department of Electronics&Communication Engineering National Institute of Technology PatnaPatna 800005India Department of Computer Science and Engineering National Institute of Technology PatnaPatna 800005India

In the densification of Device-to-Device(D2D)-enabled Social Internet of Things(SIoT)networks,improper allocation of resources can lead to high interference,increased signaling overhead,latency,and disruption of Channel State Information(CSI).In this paper,we formulate the problem of sum throughput maximization as a Mixed Integer Non-Linear Programming(MINLP)*** problem is solved in two stages:a tripartite graph-based resource allocation stage and a time-scale optimization *** proposed approach prioritizes maintaining Quality of Service(QoS)and resource allocation to minimize power consumption while maximizing sum *** results demonstrate the superiority of the proposed algorithm over standard benchmark *** of the proposed algorithm using performance parameters such as sum throughput shows improvements ranging from 17%to 93%.Additionally,the average time to deliver resources to CSI users is minimized by 60.83%through optimal power *** approach ensures QoS requirements are met,reduces system signaling overhead,and significantly increases D2D sum throughput compared to the state-of-the-art *** proposed methodology may be well-suited to address the challenges SIoT applications,such as home automation and higher education systems.

关键词： Device-to-Device(D2D)communication Social Internet of Things(SIoT) resource allocation Quality of Service(QoS) tripartite graph time scale

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New Antenna Array Beamforming Techniques Based on Hybrid Convolution/Genetic Algorithm for 5G and Beyond Communications

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computer Modeling in engineering & Sciences 2024年第3期138卷 2749-2767页

作者： Shimaa M.Amer Ashraf A.M.Khalaf Amr H.Hussein Salman A.Alqahtani Mostafa H.Dahshan Hossam M.Kassem Electronics and Communications Engineering Department Higher Institute of Engineering and TechnologyKafr ElsheikhEgypt Electronics and Electrical Communications Engineering Department Faculty of EngineeringMinia UniversityMiniaEgypt Electronics and Electrical Communications Engineering Department Faculty of EngineeringTanta UniversityTantaEgypt Electronics and Electrical Communications Engineering Department Faculty of EngineeringHorus University EgyptNew DamiettaEgypt Department of Computer Engineering College of computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia School of Computing Mathematics and EngineeringCharles Sturt UniversityBathurstNSW2795Australia

Side lobe level reduction(SLL)of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service(QOS)in recent and future wireless communication systems starting from 5G up to ***,it improves the array gain and directivity,increasing the detection range and angular resolution of radar *** study proposes two highly efficient SLL reduction *** techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm(GA)to develop the Conv/GA andDConv/GA,*** convolution process determines the element’s excitations while the GA optimizes the element *** M elements linear antenna array(LAA),the convolution of the excitation coefficients vector by itself provides a new vector of excitations of length N=(2M−1).This new vector is divided into three different sets of excitations including the odd excitations,even excitations,and middle excitations of lengths M,M−1,andM,*** the same element spacing as the original LAA is used,it is noticed that the odd and even excitations provide a much lower SLL than that of the LAA but with amuch wider half-power beamwidth(HPBW).While the middle excitations give the same HPBWas the original LAA with a relatively higher *** the increased HPBWof the odd and even excitations,the element spacing is optimized using the ***,the synthesized arrays have the same HPBW as the original LAA with a two-fold reduction in the ***,for extreme SLL reduction,the DConv/GA is *** this technique,the same procedure of the aforementioned Conv/GA technique is performed on the resultant even and odd excitation *** provides a relatively wider HPBWthan the original LAA with about quad-fold reduction in the SLL.

关键词： Array synthesis convolution process genetic algorithm(GA) half power beamwidth(HPBW) linear antenna array(LAA) side lobe level(SLL) quality of service(QOS)

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Utilization of Two Cross Two Switch for Bitonic Sorting Circuit

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Micro and Nanosystems 2025年第1期17卷 45-57页

作者： Bhattacharjee, Subhasree Sarkar, Soumyadip Das, Kunal Sadhu, Arindam Sarkar, Bikramjit Department of Computer Application Narula Institute of Technology Kolkata India Department of Computer Science Acharya Prafulla Chandra College Kolkata India Department of Electronics & Communication Engineering Greater Kolkata College of Engineering and Management West Bengal India Department of Computer Science & Engineering JIS College of Engineering West Bengal India

Background: The synthesis of reversible logic has gained prominence as a crucial research area, particularly in the context of post-CMOS computing devices, notably quantum computing. Objective: To implement the bitonic sorting circuit, 2x2 switch, is used. The overarching objective of implementing a reversible sorting circuit is to mitigate power consumption while promising secure communication. The successful implementation of the bitonic sorting circuit utilizing the proposed 2x2 switch is validated through simulations conducted in IBM Qiskit. Methods: This study begins by employing the control swap gate to implement a 2x2 switch, aimed at enabling concurrent computing operations within multiprocessor systems to enhance throughput. Subsequently, following the successful implementation of the 2x2 switch, the study proceeds to design a bitonic sorting circuit. Results: Bitonic sort using a 2x2 switch on the IBM Quantum Experience (IBMQ) platform via the QISKit SDK in Python 3.6. Specifically, Qiskit v0.29.0 is utilized, with OpenQASM. OpenQASM serves as the quantum assembly and instruction language. Conclusion: This work presents a methodology for constructing a 2x2 switch, utilizing a reversible control swap gate as its core component. Additionally, it demonstrates the intricate development and implementation of a bitonic sorting circuit, capitalizing on this innovative switch architecture. © 2025 Bentham Science Publishers.

关键词： Quantum computers

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Modulated advancements in semiconductor-based nanomaterials for environmental solutions

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Nanotechnology for Environmental engineering 2024年第4期9卷 525-537页

作者： Tirmare, Aarti Hemant Gowda V, Dankan Dhabarde, Rupali J Tirmare, Hemant Appa Kale, Satish Bapuso Suryawanshi, Varsha Amol Kumar N, Anil Department of Electronics and Telecommunications Engineering Bharati Vidyapeeth’s college of Engineering Maharashtra Kolhapur416013 India Department of Electronics and Communication Engineering BMS Institute of Technology and Management Bangalore Karnataka560064 India Department of Computer Science and Technology Department of Technology Shivaji University Kolhapur Maharashtra Kolhapur416008 India Department of Computer Science and Technology Department of Technology Shivaji University Kolhapur Maharashtra Kolhapur416004 India Department of Mechanical Engineering Department of Technology Shivaji University Kolhapur Maharashtra Kolhapur416004 India Maharashtra Kolhapur India Department of Electronics and Communication Engineering School of Engineering Mohan Babu University Andhra Pradesh Tirupati India

This research explores significant advancements in semiconductor-based nanomaterials and their crucial applications in addressing environmental challenges. Highlighted for their expansive surface area, chemical stability, and adaptable electrical and optical properties, these nanomaterials present innovative solutions for pressing environmental issues. The paper details novel synthesis methods enhancing these materials’ effectiveness in environmental applications, including pollution remediation, sustainable energy production, and the development of environmental monitoring tools. Key findings include the discovery of advanced techniques for fabricating nanoscale semiconductor components, improving the efficiency of photocatalytic degradation of pollutants, energy conversion, and sensor sensitivity. Additionally, this study investigates the integration of semiconductor nanomaterials with biocompatible polymers and metals, aiming to enhance their operational stability and longevity in environmental applications. The outcomes contribute to the advancement of nanotechnology in environmental conservation, offering insights into the development of eco-friendly materials and innovative strategies for environmental protection. This work underscores the potential of semiconductor-based nanomaterials to revolutionize the field of environmental solutions, presenting a promising avenue for future research and application in sustainable technologies. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Nanostructured materials

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Container Based Nomadic Vehicular Cloud Using Cell Transmission Model

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computer Systems Science & engineering 2023年第1期44卷 423-440页

作者： Devakirubai Navulkumar Menakadevi Thangavelu Department of Computer Science and Engineering Jayam College of Engineering and TechnologyDharmapuri636813India Department of Electronics and Communication Engineering Adhiyaman College of EngineeringHosur635109India

Nomadic Vehicular Cloud(NVC)is envisaged in this *** predo-minant aspects of NVC is,it moves along with the vehicle that initiates it and functions only with the resources of moving vehicles on the heavy traffic road without relying on any of the static infrastructure and NVC decides the initiation time of container migration using cell transmission model(CTM).Containers are used in the place of Virtual Machines(VM),as containers’features are very apt to NVC’s dynamic *** specifications of 5G NR V2X PC5 interface are applied to NVC,for the feature of not relying on the network ***-days,the peak traffic on the road and the bottlenecks due to it are inevitable,which are seen here as the benefits for VC in terms of resource availability and residual in-network *** speed range of high-end vehicles poses the issue of dis-connectivity among VC participants,that results the container migration *** the entire VC participants are on the move,to maintain proximity of the containers hosted by them,estimating their movements plays a vital *** infer the vehicle movements on the road stretch and initiate the container migration prior enough to avoid the migration failure due to vehicles dynamicity,this paper proposes to apply the CTM to the container based and 5G NR V2X enabled *** simulation results show that there is a significant increase in the success rate of vehicular cloud in terms of successful container migrations.

关键词： Vehicular cloud container migration cell transmission model 5G NR V2X PC5 interface

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Impact of Different Integration Times on Distributions of Rain Rates for Predictions of Rain Attenuation

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Progress in Electromagnetics Research C 2025年 154卷 229-238页

作者： Hassan, Mohammad Rofiqul Rafiqul, Islam Md. Habaebi, Mohamed Hadi Suriza, Ahmad Zabidi Badron, Khairayu Budalal, Asma Ali Mahfuz, Md. Mahmudul Hasan Department of Electrical and Computer Engineering Faculty of Engineering International Islamic University Malaysia Jalan Gombak Kuala Lumpur53100 Malaysia College of Electrical and Electronics Technology Benghazi Libya Department of Electrical and Computer Engineering Concordia University Canada

All wireless communication systems are moving towards higher and higher frequencies day by day which are severely attenuated by rains in outdoor environment. To design a reliable RF system, an accurate prediction method of rain attenuation is established and used globally based on local rain intensity measurement. Required rain intensity used for attenuation prediction is generally measured at a point with 1-min integration time or converted from higher integration time to 1-min. Recent measurements of rain intensity with a 10-second integration time indicate that intensity is not uniform over a 1-minute duration. Consequently, the statistics of rain intensity distribution and attenuation predictions are influenced by measurements with integration times shorter than 1 minute. It has been established that an integration time of 0.01% provides the optimal fit for actual rain rate data. This paper presents the rain intensity distributions from data measured with 2-min, 1-min, 30-sec, 20-sec, and 10-sec integration times, and it has impact on rain rate distributions as well as rain attenuation predictions. © 2025, Electromagnetics Academy. All rights reserved.

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Improved Load-Balanced Clustering for Energy-Aware Routing(ILBC-EAR)in WSNs

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computer Systems Science & engineering 2023年第1期44卷 99-112页

作者： D.Loganathan M.Balasubramani R.Sabitha S.Karthik Department of Electronics and Communication Engineering Info Institute of EngineeringCoimbatore641107India Department of Computer Science and Engineering SNS College of TechnologyCoimbatore641035India

Sensors are considered as important elements of electronic *** many applications and service,Wireless Sensor Networks(WSNs)are involved in significant data sharing that are delivered to the sink node in energy efficient man-ner using multi-hop ***,the major challenge in WSN is the nodes are having limited battery resources,it is important to monitor the consumption rate of energy is very much ***,reducing energy con-sumption can increase the network lifetime in effective *** that,clustering methods are widely used for optimizing the rate of energy consumption among the sensor *** that concern,this paper involves in deriving a novel model called Improved Load-Balanced Clustering for Energy-Aware Routing(ILBC-EAR),which mainly concentrates on optimal energy utilization with load-balanced process among cluster heads and member *** providing equal rate of energy consumption among nodes,the dimensions of framed clusters are ***,the model develops a Finest Routing Scheme based on Load-Balanced Clustering to transmit the sensed information to the sink or base *** evaluation results depict that the derived energy aware model attains higher rate of life time than other works and also achieves balanced energy rate among head ***,the model also provides higher throughput and minimal delay in delivering data packets.

关键词： Wireless sensor networks energy consumption load balanced clustering finest routing

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A two-stage CNN model for the classification and severity analysis of retinal and choroidal diseases in OCT images

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International Journal of Intelligent Networks 2024年第1期5卷 10-18页

作者： George, Neetha Shine, Linu N, Ambily Abraham, Bejoy Ramachandran, Sivakumar Department of Electronics and Communication Engineering Rajiv Gandhi Institute of Technology Kottayam Kerala India Department of Electronics and Communication Engineering College of Engineering Trivandrum Kerala India Department of Electronics and Communication Engineering Government Engineering College Idukki Kerala India Department of Computer Science and Engineering College of Engineering Muttathara Kerala Thiruvananthapuram India Department of Electronics and Communication Engineering Government Engineering College Wayanad Kerala India

The advancements in medical imaging techniques have brought exponential increase in the quantity and complexity of data which often require human expertise for interpretation and decision making. However, in real-world clinical settings, there is often a shortage of experts available for timely diagnosis and triage. An automated diagnostic technique aids clinicians in the precise diagnosis and effective management of diseases. In this article, a two-stage classification model using convolutional neural network (CNN) is proposed for the classification and severity analysis of retinal and choroidal diseases in optical coherence tomography (OCT) images. The proposed model can identify abnormal conditions such as Pachychoroid disorders, macular edema, and Drusen. The images are initially classified into four categories-healthy, Drusen, Pachychoroid and macular edema classes. The severity of Pachychoroid conditions, including central serous chorioretinopathy, polypoid choroidal vasculopathy, and choroidal neovascularization, is subsequently determined through a second-level classification. A modified version of the VGG16 architecture is used for the initial classification. A fine-tuned CNN with the same architecture is then employed to determine the severity of Pachychoroid diseases. Further, we make use of the UNet architecture for assessing the severity of macular edema. The proposed hybrid approach for classification and analysis achieved promising results, demonstrating consistency on par with human experts in diagnosing and grading ocular diseases. © 2024

关键词： Optical tomography

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Air quality and dust level monitoring systems in hospitals using IoT

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Discover Internet of Things 2025年第1期5卷 1-18页

作者： Parkavi, A. Sowmya, B.J. Alex, Sini Anna Supreeth, S. Shruthi, G. Rohith, S. Chatterjee, Sudipta Lingaraj, K. Department of Computer Science and Engineering Ramaiah Institute of Technology Bengaluru560054 India Department of Artificial Intelligence and Data Science Ramaiah Institute of Technology Bengaluru560054 India Ramaiah Institute of Technology Bengaluru560054 India School of Computer Science and Engineering REVA University Bengaluru560064 India Department of Electronics and Communication Engineering Nagarjuna College of Engineering and Technology Bengaluru562164 India Department of Electronics and Communication Engineering Brainware University Barasat West Bengal Kolkata700125 India Department of Computer Science and Engineering Rao Bahadur Y. Mahabaleswarappa Engineering College Bellary583104 India

This system provides a comprehensive overview of hospital environments by tracking air quality, dust, temperature, and humidity simultaneously, offering a more complete picture of indoor conditions than systems that focus on fewer parameters. The use of IoT technology enables real-time monitoring and alerts, allowing hospital staff to respond immediately to any issues. Additionally, predictive analytics anticipate future changes, giving staff time to take preventive measures. The integration with a mobile app and cloud-based data storage ensures easy access to data, convenient monitoring, and the ability to scale the system across multiple hospital facilities, catering specifically to the unique needs of different healthcare environments. © The Author(s) 2025.

关键词： Indoor air pollution

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