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3rd International Conference on Innovations in computer Science and Software engineering, ICONICS 2022

作者： Manan, Iram Rehman, Faisal Sharif, Hanan Riaz, Naveed Atif, Muhammad Aqeel, Muhammad Khawaja Fareed University of Engineering and Information Technology Department of Information Technology Rahim Yar Khan Pakistan Lahore Leads University Department of Computer Science & Information Technology Lahore Pakistan NUST Department of Computer Science and Information Technology Islamabad Pakistan

ISBN: (纸本)9781665461412

The goal of machine learning (ML) is to develop models that automatically learn from the past without being explicitly programmed. ML has numerous applications, such as pattern recognition, forecasting upcoming trends, and judgement. It can handle massive amounts of huge vectors and tensors representing multidimensional data. To handle these processes on traditional computers, enormous time and computational resources are required. Unlike traditional computers, which use binary bits to compute, quantum computers (Q.C.) use qubits, which can simultaneously hold 0 and 1 combinations through superposition and entanglement. This makes *** an excellent choice for implementing ML algorithms because they are skilled at handling and post-processing large tensors. Although many of the models used for ML on quantum computers are based on concepts from their classical computing counterparts, the use of quantum computers has made them the better of the two. This paper assess the speed and complexity benefits of using quantum computers and gives a general overview of the state of knowledge regarding the use of ML on Q.C. © 2022 IEEE.

关键词： Quantum entanglement

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Classification of Skin Diseases in the Internet of Medical Things using Hybrid Deep Learning 2

Classification of Skin Diseases in the Internet of Medical T...

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2nd IEEE International Conference on Networks, Multimedia and information technology, NMITCON 2024

作者： Latha, Dandu Madhavi Anusha, Kondepati Samrin, Rafath Reddy, Pundru Chandra Shaker Sudhakar, Bolleddu Sathish, Goski Geethanjali College of Engineering and Technology Electronics and Communication Engineering Telangana Hyderabad India Marri Laxman Reddy Institute of Technology and Management Computer Science and Engineering Telangana Hyderabad India King Khalid University Department of Computer Science College of Computer Science Asir Abha Saudi Arabia Sr University School of Computer Science and Artificial Intelligence Telangana Warangal India Degree Lecturer of Computer Science Mjptbcwreis Telangana India Department of Information Technology Hyderabad India

ISBN: (纸本)9798350372892

When it comes to the IoMT, skin lesion examination is absolutely essential for making an accurate diagnosis. Skin lesion analysis relies heavily on computer-aided design(CAD) technologies to enhance accuracy and efficiency. Using hybrid deep learning approaches, this work focuses on segmenting and classifying skin lesions from dermoscopy images. Mask Region-based Convolutional Neural Network (MRCNN) for semantic separation and ResNet50 for lesion-detection are two state-of-the-art methodologies that are combined in this research's hybrid deep learning model. A skin lesion's exact location can be determined with the use of the MRCNN's border delineation capabilities. For comprehensive model training, we gather a large collection of dermoscopy photos that have been annotated. This dataset is used to train a hybrid deep-learning(DL) model that can capture images' nuanced representations. An accuracy rate of 95.49% in segmenting lesions into different groups demonstrates the model's capability to do so. Another significant improvement over older method is the high reliability and accuracy of skin lesion classification. After being tested on the ISIC2020 Challenge dataset, the model achieved an impressive 96.75% accuracy rate. Classification and segmentation models outperform the state-of-the-art in Internet-of-Medical-Things(IoMT). When it comes to segmenting and classifying skin lesions, this paper's hybrid deep learning approach works wonders. Outperforming the existing gold standards, the results demonstrate that the model can enhance diagnostic accuracy in an IoMT environment. © 2024 IEEE.

关键词： Convolutional neural networks

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End-to-End Quality of Service Provisioning in High Speed Networks 3

End-to-End Quality of Service Provisioning in High Speed Net...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Rao, Srikrishna B. Sathya, T. Bagade, Jayashree V. Sharma, Vishal Dhingra, Lovish Kumar, Ritesh Faculty of Engineering and Technology Department of Mechanical Engineering Karnataka Ramnagar562112 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Information Technology Pune India Vivekananda Global University Department of Mechanical Engineering Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350319125

End-to-give a fine of service (quality of service) provisioning is essential for improving the person's experience in excessive velocity networks. Quality of service provisioning is a set of strategies, methods, and strategies designed to ensure ok transport and performance of community visitors. It does so by way of deliberating first-rate-effort services, which include routing, forwarding, and mistakes-correction and using also introducing better layer services, including waft manipulation, precedence schemes, link layer offerings, and numerous exemplary carrier models like Voice over IP (VoIP), traffic engineering (TE), valuable resource Reservation Protocol (RSVP) among *** the network layer, quality of service techniques provides a manner to allocate bandwidth, regulate packet forwarding, shape site visitors, and reserve assets in excessive-speed networks. The packages of quality of service provisioning in excessive speed networks include but are not limited to assuring the non-stop shipping of bandwidth extensive real-time packages consisting of Voice over IP (VoIP) and Video streaming, granting high availability to sure assignment-essential applications, making certain a minimum fine of service (quality of service) to specific applications and supplying differentiated bandwidth for positive lessons of site visitors. Quit-to-end quality of service in high-speed networks may be done by using techniques along with weighted packet scheduling, multi-level priority queues, admission management algorithms, selectable sign and coding schemes, dual buffers, Etc. By ensuring service provisioning quality in excessive-pace networks, telecommunication service providers can offer a more significant consumer enjoy and make sure that the services they offer are up to customer expectation. © 2023 IEEE.

关键词： admission availability provisioning techniques telecommunication

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Entropy Based Feature Fusion Using Deep Learning for Waste Object Detection and Classification Model

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computer Systems Science & engineering 2023年第12期47卷 2953-2969页

作者： Ehab Bahaudien Ashary Sahar Jambi Rehab B.Ashari Mahmoud Ragab Electrical and Computer Engineering Department Faculty of EngineeringKing Abdulaziz UniversityJeddah21589Saudi Arabia Information Systems Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Mathematics Faculty of ScienceAl-Azhar UniversityNaser CityCairo11884Egypt

Object Detection is the task of localization and classification of objects in a video or *** recent times,because of its widespread applications,it has obtained more *** the modern world,waste pollution is one significant environmental *** prominence of recycling is known very well for both ecological and economic reasons,and the industry needs higher *** object detection utilizing deep learning(DL)involves training a machine-learning method to classify and detect various types of waste in videos or *** technology is utilized for several purposes recycling and sorting waste,enhancing waste management and reducing environmental *** studies of automatic waste detection are difficult to compare because of the need for benchmarks and broadly accepted standards concerning the employed data ***,this study designs an Entropy-based Feature Fusion using Deep Learning forWasteObject Detection and Classification(EFFDL-WODC)*** presented EFFDL-WODC system inherits the concepts of feature fusion and DL techniques for the effectual recognition and classification of various kinds of waste *** the presented EFFDL-WODC system,two major procedures can be contained,such as waste object detection and waste object *** object detection,the EFFDL-WODC technique uses a YOLOv7 object detector with a fusionbased backbone *** addition,entropy feature fusion-based models such as VGG-16,SqueezeNet,and NASNetmodels are ***,the EFFDL-WODC technique uses a graph convolutional network(GCN)model performed for the classification of detected waste *** performance validation of the EFFDL-WODC approach was validated on the benchmark *** comprehensive comparative results demonstrated the improved performance of the EFFDL-WODC technique over recent approaches.

关键词： Object detection object classification waste management deep learning feature fusion

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Wideband technology Design with the Novel Based Technogy : An Antenna Systems

Wideband Technology Design with the Novel Based Technogy : A...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Murugan, R. Sinha, Sanjay Kumar Savita Computer Science Department Bangalore India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Maharishi School of Engineeing & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350357769

In this work, we build and evaluate a unique wideband 8-antenna itself. Multiple-Input + Multiple-Output (MIMO) system that is optimized for the fifth generation of radios (N77/N78/N79) mobile phone applications using an analytical method. The MIMO antenna system uses a specifically designed coupled-loop antenna to accomplish its wide bandwidth while operating in the 3.3-5.0 GHz frequency range. Three separate coupling portions are included into this coupled-loop antenna, which is positioned at its center top and two sides. The coupled-loop antenna may sustain three resonance waves: 0.5?, 0.75?, + 1.0? modes because to its unique configuration. The innovation's most revolutionary characteristic is that it can excite the 0.75? methods, which has never been reported before. These three vibration modes work in concert to provide the broad bandwidth that is attained. The performance evaluation of the suggested 8x8 MIMO antenna system includes an analysis of channel capacity, antenna isolation, and envelope correlation coefficient. The antennas are manufactured and measured in physical prototypes that are placed around the edges of mobile phones and configured as a 8-antenna MIMO system. The results show excellent agreement between simulation and measuring, supporting the usefulness of the suggested MIMO antenna design. © 2023 IEEE.

关键词： 5G Antenna System Coupled-Loop Antenna Mobile Terminals and Wireless Communication technology N77/N78/N79 Bands Performance Evaluation Resonance Modes S-Parameters Wideband MIMO

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Crops Leaf Diseases Recognition:A Framework of Optimum Deep Learning Features

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computers, Materials & Continua 2023年第1期74卷 1139-1159页

作者： Shafaq Abbas Muhammad Attique Khan Majed Alhaisoni Usman Tariq Ammar Armghan Fayadh Alenezi Arnab Majumdar Orawit Thinnukool Department of Computer Science HITEC UniversityTaxilaPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia College of Computer Engineering and Science Prince Sattam Bin Abdulaziz UniversityAl-Kharaj11942Saudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySakakahSaudi Arabia Faculty of Engineering Imperial College LondonLondonSW72AZUK College of Arts Mediaand TechnologyChiang Mai UniversityChiang Mai50200Thailand

Manual diagnosis of crops diseases is not an easy process;thus,a computerized method is widely *** couple of years,advancements in the domain ofmachine learning,such as deep learning,have shown substantial ***,they still faced some challenges such as similarity in disease symptoms and irrelevant features *** this article,we proposed a new deep learning architecture with optimization algorithm for cucumber and potato leaf diseases *** proposed architecture consists of five *** the first step,data augmentation is performed to increase the numbers of training *** the second step,pre-trained DarkNet19 deep model is opted and fine-tuned that later utilized for the training of fine-tuned model through transfer *** features are extracted from the global pooling layer in the next step that is refined using Improved Cuckoo search *** best selected features are finally classified using machine learning classifiers such as SVM,and named a few more for final classification *** proposed architecture is tested using publicly available datasets–Cucumber National Dataset and Plant *** proposed architecture achieved an accuracy of 100.0%,92.9%,and 99.2%,*** with recent techniques is also performed,revealing that the proposed method achieved improved accuracy while consuming less computational time.

关键词： Crops diseases preprocessing convolutional neural network features optimization machine learning

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Optimization-Based Collision Avoidance in Underwater Wireless Sensor Network 1

Optimization-Based Collision Avoidance in Underwater Wireles...

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1st IEEE International Conference on Applied Intelligence and Sustainable Computing, ICAISC 2023

作者： Sugumaran, S. Buvaneswari, B. Senthilkumar, K.S. Jeevitha, R. Ramachandra, A.C. Vishnu Institute of Technology ECE Department Bhimavaram India Panimalar Engineering College Department of Information Technology Chennai India Sri Ramakrishna College of Arts & Science Department of Computer Applications Coimbatore India KPR Institute of Engineering and Technology Computer Science and Engineering Arasur India Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350323795

The Underwater Wireless Sensor Network (UWSN) is crucial for private, military, and commercial maritime operations, like environmental monitoring, underwater research, scientific data collection, and underwater wireless communications. The existing protocols for Terrestrial Wireless Sensor Networks (TWSNs) could be better in terms of power efficiency, reliability, and effectiveness. Due to their unique characteristics. The energy-efficient convergent depth variation routing (ECDVR) algorithm is introduced to evaluate and reduce power consumption by calculating the distance between each node point and node depth variation. This algorithm considers the two-hop neighbour depth variation when sending data to a neighbor node with a higher forward angle toward the receiver. It calculates the receive time contribution of the Adaptive Time Difference of Arrival (ATDoA). Adaptive Time Difference of Arrival (ATDoA) The arrival time of a signal makes it simple to estimate the time difference between two signals at a node. The storage node-to-receiver approach is the one that has been proposed for determining the node's remaining power for each information exchange. In the subsequent UWSN transmission, the sink allocates the node's higher power when the node reduces its power. Extending the packet's lifetime and shortening the time it takes to reach its destination boosts system performance. It outperforms the compared algorithms regarding node lifetime, dead node count, power consumption, and propagation delay. © 2023 IEEE.

关键词： Energy efficiency

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An Efficient and Low-Profile MIMO Antenna for 5G-WiFi Interference Rejection: Design and Analysis 15

An Efficient and Low-Profile MIMO Antenna for 5G-WiFi Interf...

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15th International Conference on information and Communication technology Convergence, ICTC 2024

作者： Tariq, Hassan Jafri, Mohsin Raza Khan, Abd Ullah Lee, Kyesan Shin, Hyundong Kyung Hee University Department of Electronics and Information Convergence Engineering Yongin Korea Republic of National University of Sciences and Technology Department of Computer Science Balochistan Campus Quetta Pakistan

ISBN: (纸本)9798350364637

The interference between 5G and Wi-Fi within the ultra-wideband (5.1 GHz-5.85 GHz) is a major concern for wireless communication. This overlap causes reduced data rates, increased latency, and overall diminished network efficiency. As more devices and networks use these frequencies, managing this interference becomes critical for maintaining optimal performance. Addressing the issue requires advanced antenna designs and effective spectrum management. This paper proposes a highly efficient and reconfigurable multiple input multiple output (MIMO) antenna to mitigate the effects of this interference. To achieve this, we design an array of quad-element MIMO antennae on an FR-4 substrate for the frequency range of (3.1 to 10.6) GHz. Next, we add a U-shaped notch to reject the 5 GHz band of frequencies centered at 5.5 GHz. The antenna's configuration allows it to function as both orthogonal and back-to-back structures, making it an ideal choice for MIMO-based portable devices. At the rear end of the substrate, a parasitic element in the shape of a mechanical chain strip line serves as a decoupling and isolation structure. The thickness of the strip line structure is configured to be 0.035 mm for optimal isolation, and the total dimension of the antenna is configured to be 58×58×1.6 mm2. We simulate the proposed design and find that it achieves a stable diversity gain of 10 dB, with an efficiency correlation coefficient of less than 0.01 dB. The proposed design makes it a decent contender for non-planar or compact 3-D structures. © 2024 IEEE.

关键词： Wireless local area networks (WLAN)

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Enhance the Security of Access to IoT-based Equipment in Fog

Enhance the Security of Access to IoT-based Equipment in Fog

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2023 Al-Sadiq International Conference on Communication and information technology, AICCIT 2023

作者： Zolfagharipour, Leila Kadhim, Mohammed Hayder Mandeel, Thulfiqar H. Ferdowsi University of Mashhad Department of Information Technology Mashhad Iran Jabir Ibn Hayyan for Medical and Pharmaceutical Sciences Department of Information Technology Najaf Iraq Imam Ja'afar Al-Sadiq University College of Information Technology Department of Computer Techniques Engineering Muthanna Iraq

ISBN: (纸本)9798350341881

The Internet of Things is in users' daily life/work, as a result protecting privacy and security is essential. IoT's heterogeneous, Pervasive, complicated properties make the problems of security important. Moreover, big nodes and resource limitations number make a lightweight need for algorithms of IoT security. So, attribute-based encryption (ABE) is the famous answer for the safe sharing, storage, and transfer of data in shared areas like IoT. In this paper, we propose a technique for user authentication with lightweight attribute-based encryption for IoTs in fog. With the security analysis performed, it is observed that the proposed technique prevents from the user attempting to decrypt messages that are not allowed, and thus, power dissipation and processing will be prevented for performing computational operations and processes that are spent with energy and time. Consequently, by performing this authentication before decoding, in addition to securing the security system, by removing the computational overheads required to achieve satisfaction at the requesting node, it adds the security technique performance used on the network. The results of the performance analysis show that overall, the proposed security framework has performed well. © 2023 IEEE.

关键词： Internet of things

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Improving Food Safety by IoT-based Climate Monitoring and Control Systems for Food Processing Plants

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Remote Sensing in Earth Systems Sciences 2025年第2期8卷 387-399页

作者： Kolikipogu, Ramakrishna Shivaputra Muniyandy, Elangovan Maroor, Jnaneshwar Pai Lakshmi, Gundala Venkata Rama Konduri, Bhagavan Naveenkumar, R. Department of Information Technology Chaitanya Bharathi Institute of Technology Hyderabad India Department of Electronics and Communication Engineering Dr. Ambedkar Institute of Technology Bengaluru India Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Applied Science Research Center Applied Science Private University Amman Jordan Department of Business Administration Nitte Institute of Professional Education Nitte (Deemed to Be University) Karnataka Mangaluru India Department of Computer Science and Engineering CVR College of Engineering Hyderabad India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India Department of Computer Science and Engineering Chandigarh Colleges of Engineering Chandigarh Group of Colleges Jhanjeri Punjab Mohali 140307 India

Web different IoT apps offer lot more options for every player in the meat supply chain to monitor, control, and optimize their manufacturing method. Beginning within late 2017, industrial IoF2020 program will concentrate toward massive deployments of IoT via three use cases in the meat supply chain: pig farm management, poultry chain tracking, and for livestock visibility with openness. This initiative will include eleven collaborators spanning 5 nations. Installing and integrating IoT sensors for environmental and livestock management would alleviate producers’ difficulty getting knowledge that data needed regarding continuously tracking how well they are doing. Alert detection is additionally being created, integrating multiple sources of data in order to give farmers helpful input along with communicating news with other partners. By carrying out this, preventative or remedial measures can be done for infections, swine taint, bird mortality, feed waste, the natural world, et cetera. Additionally, EPCIS-based traceability from farm to fork will be allowed to ensure customers may get precise data about the source and caliber of their livestock. Each of these three use scenarios’ existing stage in work along with future plans are expected to be discussed. IoF2020 seeks to support the digital revolution in smart farming by tackling various educational and commercial problems while also promoting its use throughout Europe. It maintains mechanical necessary degree and security against physical along with toxic contaminants during industrial butchering of chicken, a lot measures have been taken. Buyers’ worries about food safety and health are the result of eating chicken increasingly. Our authorities have begun many kinds of initiatives aimed at improving safeguards for food. Our goal is to create an apparatus that alerts the factory farms affecting potential threats for product hygiene of food. With such setup, the detector can be mounted on top of the poultry slaugh

关键词： Food safety Internet of Things Meat processing Monitoring Supply chain

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