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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Yeole, Prasad Labade, Yash Wabale, Nikhil Patil, Rahul Wagh, Siddhant William, P. Sanjivani College of Engineering Department of Computer Engineering India Research and Development at Sanjivani College of Engineering India

ISBN: (纸本)9798350369106

This study introduces a novel Internet of Things (IoT) assistive technology designed to increase the mobility and self-sufficiency of visually impaired people. Over 40 million individuals, including over 1.6 million children, are visually impaired in India, and getting around in daily life is still exceedingly difficult. Walking canes and other traditional aids are not always effective in identifying hazards at different heights and angles. The suggested system integrates smart shoes and spectacles with buzzers, microcontrollers, and ultrasonic sensors. The smart glasses recognise obstructions at head height by extending detection beyond the level of the shoes, which continuously monitors the ground for obstacles. The system ensures better spatial awareness by alerting users in real-time with audio when an obstacle is spotted. The IoT-enabled communication between shoes and smart glasses is a significant innovation since it enables synchronized obstacle identification and reaction. With its all-encompassing coverage, this integrated strategy enhances user mobility and safety. The system is lightweight, ergonomically sound, dependable, and made for everyday use. Future additional improvements might include GPS integration for accurate navigation and machine learning for anticipatory obstacle identification. This study demonstrates how people with visual impairments can live much better thanks to wearable Internet of Things devices. © 2024 IEEE.

关键词： Assistive technology

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Taylor jellyfish search algorithm enabled feature selection and deep learning for big data classification using mapreduce framework

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Australian Journal of Electrical and Electronics engineering 2024年第2期21卷 178-192页

作者： Kalpana, K. Sunil Vijaya Kumar, G. Madhavi, K. Research Scholar Department of Computer Science and Engineering JNTUA College of Engineering Andhra Pradesh India Nandyal Telangana India Department of CSE JNTUA College of Engineering JNTUA Ananthapuramu Andhra Pradesh India

Nowadays, the increasing growth of technology contributes various organisations to storing a huge amount of records using web servers in the form of big data. The big database possesses a vast amount of relevant and irrelevant features, and the less significant features are difficult to remove which makes the process time-consuming and more complex. Hence, this paper proposes an optimisation algorithm, named the Taylor Jellyfish Search Optimisation (TaylorJSO) for selecting the relevant features. Here, an optimisation-based deep learning approach called Taylor Jellyfish Search Optimisation-Deep Maxout Network (TaylorJSO-DMN) is introduced to classify big data more effectively by selecting optimal features. In this model, the input database is preprocessed using quantile normalisation and uses the oversampling of imbalanced classes for data augmentation. In the MapReduce framework, the selection of optimal features is performed in the mapper phase, whereas in the reducer phase, the DMN is used for the classification of big data. The DMN is trained using the introduced TaylorJSO algorithm to improve the classification performance of big data classification. Moreover, the TaylorJSO-DMN model attained greater performance with a maximum of 92.5% accuracy, 91.6% sensitivity, and 92.9% specificity than other traditional approaches. ©, Engineers Australia.

关键词： Big data

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Nonlinear Teager-Kaiser Infomax Boost Clustering Algorithm for Brain Tumor Detection Technique

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computer Systems Science & engineering 2023年第8期46卷 2589-2599页

作者： P.M.Siva Raja S.Brinthakumari K.Ramanan Computer Science and Engineering Amrita College of Engineering and TechnologyNagercoil629901India Information Technology K.C College of Engineering and Management Studies and ResearchThaneIndia Computer Science and Engineering NPR College of Engineering and TechnologyDindigul629902India

Brain tumor detection and division is a difficult tedious undertaking in clinical image *** it comes to the new technology that enables accurate identification of the mysterious tissues of the brain,magnetic resonance imaging(MRI)is a great *** is possible to alter the tumor’s size and shape at any time for any number of patients by using the Brain *** have a difficult time sorting and classifying tumors from multiple *** tumors may be accurately detected using a new approach called Nonlinear Teager-Kaiser Iterative Infomax Boost Clustering-Based Image Segmentation(NTKFIBC-IS).Teager-Kaiser filtering is used to reduce noise artifacts and improve the quality of images before they are *** clinical characteristics are then retrieved and analyzed statistically to identify brain *** use of a BraTS2015 database enables the proposed approach to be used for both qualitative and quantitative *** dataset was used to do experimental evaluations on several metrics such as peak signal-to-noise ratios,illness detection accuracy,and false-positive rates as well as disease detection time as a function of a picture *** segmentation delivers greater accuracy in detecting brain tumors with minimal time consumption and false-positive rates than current stateof-the-art approaches.

关键词： Brain tumor detection image segmentation nonlinear teager kaiser filtering

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Adaptive Window Based 3-D Feature Selection for Multispectral Image Classification Using Firefly Algorithm

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computer Systems Science & engineering 2023年第1期44卷 265-280页

作者： M.Rajakani R.J.Kavitha A.Ramachandran Full Time Research Scholar Department of Electronics and Communication EngineeringUniversity College of EngineeringPanruti607106India Department of Electronics and Communication Engineering University College of EngineeringPanruti607106India Department of Computer Science and Engineering University College of EngineeringPanruti607106India

Feature extraction is the most critical step in classification of multispectral *** classification accuracy is mainly influenced by the feature sets that are selected to classify the *** the past,handcrafted feature sets are used which are not adaptive for different image *** overcome this,an evolu-tionary learning method is developed to automatically learn the spatial-spectral features for classification.A modified Firefly Algorithm(FA)which achieves maximum classification accuracy with reduced size of feature set is proposed to gain the interest of feature selection for this *** extracting the most effi-cient features from the data set,we have used 3-D discrete wavelet transform which decompose the multispectral image in all three *** selecting spatial and spectral features we have studied three different approaches namely overlapping window(OW-3DFS),non-overlapping window(NW-3DFS)adaptive window cube(AW-3DFS)and Pixel based *** Multiclass Support Vector Machine(MSVM)is used for classification *** con-ducted on Madurai LISS IV multispectral image exploited that the adaptive win-dow approach is used to increase the classification accuracy.

关键词： Multispectral image modifiedfireﬂy algorithm 3-D feature extraction feature selection multiclass support vector machine classification

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IRS-enabled NOMA communication systems:A network architecture primer with future trends and challenges

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Digital Communications and Networks 2024年第5期10卷 1503-1528页

作者： Haleema Sadia Ahmad Kamal Hassan Ziaul Haq Abbas Ghulam Abbas Muhammad Waqas Zhu Han Faculty of Electrical Engineering and Telecommunications and Networking(TeleCoN)Research Center Ghulam Ishaq Khan Institute of Engineering and Technology(GIKI)Topi 23640Pakistan Faculty of Computer Science and Engineering GIKITopi 23640Pakistan Department of Computer Engineering College of Information TechnologyUniversity of Bahrain32028Bahrain School of Engineering Edith Cowan UniversityPerth WA6027Australia Department of Electrical and Computer Engineering University of HoustonHoustonTX 77004USA Department of Computer Science and Engineering Kyung Hee UniversitySeoul 446-701South Korea

Non-Orthogonal Multiple Access(NOMA)has already proven to be an effective multiple access scheme for5th Generation(5G)wireless *** provides improved performance in terms of system throughput,spectral efficiency,fairness,and energy efficiency(EE).However,in conventional NOMA networks,performance degradation still exists because of the stochastic behavior of wireless *** combat this challenge,the concept of Intelligent Reflecting Surface(IRS)has risen to prominence as a low-cost intelligent solution for Beyond 5G(B5G)*** this paper,a modeling primer based on the integration of these two cutting-edge technologies,i.e.,IRS and NOMA,for B5G wireless networks is *** in-depth comparative analysis of IRS-assisted Power Domain(PD)-NOMA networks is provided through 3-fold ***,a primer is presented on the system architecture of IRS-enabled multiple-configuration PD-NOMA systems,and parallels are drawn with conventional network configurations,i.e.,conventional NOMA,Orthogonal Multiple Access(OMA),and IRS-assisted OMA *** by this,a comparative analysis of these network configurations is showcased in terms of significant performance metrics,namely,individual users'achievable rate,sum rate,ergodic rate,EE,and outage ***,for multi-antenna IRS-enabled NOMA networks,we exploit the active Beamforming(BF)technique by employing a greedy algorithm using a state-of-the-art branch-reduceand-bound(BRB)*** optimality of the BRB algorithm is presented by comparing it with benchmark BF techniques,i.e.,minimum-mean-square-error,zero-forcing-BF,and ***,we present an outlook on future envisioned NOMA networks,aided by IRSs,i.e.,with a variety of potential applications for 6G wireless *** work presents a generic performance assessment toolkit for wireless networks,focusing on IRS-assisted NOMA *** comparative analysis provides a solid foundation for the dev

关键词： Intelligent reflecting surface Non-orthogonal multiple access 6G Beamforming Sum rate Energy efficiency

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Robust Resource Sharing in Network Slicing via Hypothesis Testing

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IEEE Transactions on Network and Service Management 2025年第3期22卷 2731-2746页

作者： Nikolaidis, Panagiotis Baras, John Institute for Systems Research University of Maryland at College Park Department of Electrical and Computer Engineering College ParkMD20742 United States

In network slicing, the network operator needs to satisfy the service level agreements of multiple slices at the same time and on the same physical infrastructure. To do so with reduced provisioned resources, the operator may consider resource sharing mechanisms. However, each slice then becomes susceptible to traffic surges in other slices which degrades performance isolation. To maintain both high efficiency and high isolation, we propose the introduction of hypothesis testing in resource sharing. Our approach comprises two phases. In the trial phase, the operator obtains a stochastic model for each slice that describes its normal behavior, provisions resources and then signs the service level agreements. In the regular phase, whenever there is resource contention, hypothesis testing is conducted to check which slices follow their normal behavior. Slices that fail the test are excluded from resource sharing to protect the well-behaved ones. We test our approach on a mobile traffic dataset. Results show that our approach fortifies the service level agreements against unexpected traffic patterns and achieves high efficiency via resource sharing. Overall, our approach provides an appealing tradeoff between efficiency and isolation. © 2004-2012 IEEE.

关键词： Resource management Quality of service Testing Service level agreements Network slicing Bandwidth Traffic control Costs Delays Anomaly detection

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Efficient Communication in Wireless Sensor Networks Using Optimized Energy Efficient Engroove Leach Clustering Protocol

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Tsinghua Science and Technology 2024年第4期29卷 985-1001页

作者： N.Meenakshi Sultan Ahmad A.V.Prabu J.Nageswara Rao Nashwan Adnan Othman Hikmat A.M.Abdeljaber R.Sekar Jabeen Nazeer SRM Institute of Science and Technology KattankulathurChennai 603203India Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharj 11942Saudi Arabia University Center for Research and Development(UCRD) Department of Computer Science and EngineeringChandigarh UniversityGharuanMohali 140413India Department of ECE Koneru Lakshmaiah Education FoundationVaddeswaramGuntur 522502India Department of Computer Science and Engineering Lakireddy Balireddy College of Engineering(A)NTR District 521230India Department of Computer Engineering College of EngineeringKnowledge UniversityErbil 44001Iraq Department of Computer Science Faculty of Information TechnologyApplied Science Private UniversityAmman 11937Jordan Department of Electronics and Communication Engineering(ECE) School of EngineeringPresidency UniversityBangalore 834001India

The Wireless Sensor Network(WSN)is a network that is constructed in regions that are inaccessible to human *** widespread deployment of wireless micro sensors will make it possible to conduct accurate environmental monitoring for a use in both civil and military *** make use of these data to monitor and keep track of the physical data of the surrounding environment in order to ensure the sustainability of the *** data have to be picked up by the sensor,and then sent to the sink node where they may be *** nodes of the WSNs are powered by batteries,therefore they eventually run out of *** energy restriction has an effect on the network life span and environmental *** objective of this study is to further improve the Engroove Leach(EL)protocol’s energy efficiency so that the network can operate for a very long time while consuming the least amount of *** lifespan of WSNs is being extended often using clustering and routing *** Meta Inspired Hawks Fragment Optimization(MIHFO)system,which is based on passive clustering,is used in this study to do *** cluster head is chosen based on the nodes’residual energy,distance to neighbors,distance to base station,node degree,and node *** on distance,residual energy,and node degree,an algorithm known as Heuristic Wing Antfly Optimization(HWAFO)selects the optimum path between the cluster head and Base Station(BS).They examine the number of nodes that are active,their energy consumption,and the number of data packets that the BS *** overall experimentation is carried out under the MATLAB *** the analysis,it has been discovered that the suggested approach yields noticeably superior outcomes in terms of throughput,packet delivery and drop ratio,and average energy consumption.

关键词： wireless sensor networks energy efficient engroove leach protocol meta inspired Hawks fragment optimization heuristic wing antfly optimization

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CLIP-Flow:Decoding images encoded in CLIP space

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Computational Visual Media 2024年第6期10卷 1157-1168页

作者： Hao Ma Ming Li Jingyuan Yang Or Patashnik Dani Lischinski Daniel Cohen-Or Hui Huang Visual Computing Research Center College of Computer Science and Software EngineeringShenzhen UniversityShenzhen 518060China Department of Computer Science Tel Aviv UniversityTel Aviv 6997801Israel School of Computer Science and Engineering the Hebrew University of JerusalemJerusalem 91904Israel

This study introduces CLIP-Flow,a novel network for generating images from a given image or *** effectively utilize the rich semantics contained in both modalities,we designed a semantics-guided methodology for image-and text-to-image *** particular,we adopted Contrastive Language-Image Pretraining(CLIP)as an encoder to extract semantics and StyleGAN as a decoder to generate images from such ***,to bridge the embedding space of CLIP and latent space of StyleGAN,real NVP is employed and modified with activation normalization and invertible *** the images and text in CLIP share the same representation space,text prompts can be fed directly into CLIP-Flow to achieve text-to-image *** conducted extensive experiments on several datasets to validate the effectiveness of the proposed image-to-image synthesis *** addition,we tested on the public dataset Multi-Modal CelebA-HQ,for text-to-image *** validated that our approach can generate high-quality text-matching images,and is comparable with state-of-the-art methods,both qualitatively and quantitatively.

关键词： image-to-image text-to-image contrastive language-image pretraining(CLIP) flow StyleGAN

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Tissue engineering approaches for dental pulp regeneration:The development of novel bioactive materials using pharmacological epigenetic inhibitors

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Bioactive Materials 2024年第10期40卷 182-211页

作者： Ross M.Quigley Michaela Kearney Oran D.Kennedy Henry F.Duncan Division of Restorative Dentistry&Periodontology Dublin Dental University HospitalTrinity College Dublin(TCD)University of DublinLincoln PlaceDublinIreland Department of Anatomy and Regenerative Medicine and Tissue Engineering Research GroupRoyal College of Surgeons in Ireland(RCSI)University of Medicine and Health SciencesDublinIreland The Trinity Centre for Biomedical Engineering(TCBE)and the Advanced Materials and Bioengineering Research Centre(AMBER) Royal College of Surgeons in Ireland(RCSI)and Trinity College Dublin(TCD)DublinIreland

The drive for minimally invasive endodontic treatment strategies has shifted focus from technically complex and destructive root canal treatments towards more conservative vital pulp ***,novel approaches to maintaining dental pulp vitality after disease or trauma will require the development of innovative,biologicallydriven regenerative medicine *** example,cell-homing and cell-based therapies have recently been developed in vitro and trialled in preclinical models to study dental pulp *** approaches utilise natural and synthetic scaffolds that can deliver a range of bioactive pharmacological epigenetic modulators(HDACis,DNMTis,and ncRNAs),which are cost-effective and easily applied to stimulate pulp tissue ***,many biological factors hinder the clinical development of regenerative therapies,including a lack of blood supply and poor infection control in the necrotic root canal *** challenges include a need for clinically relevant models and manufacturing challenges such as scalability,cost concerns,and regulatory *** review will describe the current state of bioactive-biomaterial/scaffold-based engineering strategies to stimulate dentine-pulp regeneration,explicitly focusing on epigenetic modulators and therapeutic pharmacological *** will highlight the components of dental pulp regenerative approaches,describe their current limitations,and offer suggestions for the effective translation of novel epigenetic-laden bioactive materials for innovative therapeutics.

关键词： Epigenetics Regenerative medicine Regenerative endodontics Biocompatible materials Tissue engineering

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Unleashing the Potential of IoT Integration for Energy Optimization in Smart Homes 3

Unleashing the Potential of IoT Integration for Energy Optim...

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3rd International Conference on Power Electronics and IoT Applications in Renewable Energy and its Control, PARC 2024

作者： Tiwari, Shivam Bhushan, Aditya Singh, Ashutosh Kumar Yadav, Rakesh Kumar United College of Engineering & Research Department of Mechanical Engineering Prayagraj India United College of Engineering & Research Department of Computer Science and Engineering Prayagraj India

ISBN: (纸本)9798350309409

This research paper explores the transformative potential of integrating Internet of Things (IoT) devices into smart home technologies, ushering in a new era of energy-efficient living. Focusing on energy optimization, the paper examines the intricate network of interconnected devices shaping efficient residential ecosystems. Beginning with an investigates specific devices such as smart thermostats and intelligent lighting systems. Through meticulous analysis of user behavior, it unveils how these devices influence and mold household energy consumption. Spotlighting data analytics, the paper reveals the power of information processing for personalized, efficient energy management. Addressing challenges like privacy and interoperability, it proposes innovative solutions for seamless IoT integration. The research concludes with an environmental assessment, emphasizing the symbiotic relationship between IoT and smart homes in fostering a sustainable and eco-friendly future. © 2024 IEEE.

关键词： Internet of things

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