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5th International Conference on Electronics and Sustainable communication systems, ICESC 2024

作者： Revathy, G. Maheswari, P. Uma Madhavi, S. Vijay Anand, P. Begum, R. Vajubunnisa Jasmin, H. Department of Computer Science and Engineering Chennai India K. Ramakrishnan College of Engineering Department of Computer Science and Business Systems Trichy India Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College Department of Information Technology Chennai India Cmr Institute of Technology Department of Artificial Intelligence and Data Science Bengaluru India Justice Basheer Ahmed Sayeed College for Women Affiliated by University of Madras Department of Electronics and Communication Science Teynampet Chennai India

ISBN: (纸本)9798350379945

Ovarian cancer is the fifth most common cause of death from cancer in women. This is mainly because it is often diagnosed at a late stage, as the earliest symptoms are unclear and inconsistent. Existing diagnostic techniques, such as biomarkers, biopsies, and imaging tests, have notable drawbacks such as reliance on subjective interpretation, inconsistency across different observers, and time-consuming testing procedures. This research study introduces an innovative deep learning framework that employs a convolutional neural network (CNN) algorithm to accurately predict and diagnose ovarian cancer, thereby overcoming the existing constraints. The CNN was trained using a dataset of histopathology images. The dataset was partitioned into test and training subsets to enhance the model's performance. The algorithm demonstrated an impressive accuracy rate of 96%, successfully detecting 97.12% of malignant instances and precisely categorizing 95.02% of healthy cells. This method effectively mitigates the challenges related to human expert evaluation, including elevated rates of misclassification and variability across different observers, while also reducing the time required for analysis. The results underscore the capability of this CNN-based technique to offer a more precise, effective, and dependable strategy for forecasting and detecting ovarian cancer. Subsequent investigations will prioritize the integration of new breakthroughs in deep learning to further amplify the efficacy of the suggested approach. © 2024 IEEE.

关键词： Lung cancer

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AI-Powered Precision: Revolutionizing Skin Cancer Detection with Advanced Machine Learning 6

AI-Powered Precision: Revolutionizing Skin Cancer Detection ...

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6th IEEE Novel Intelligent and Leading Emerging sciences Conference, NILES 2024

作者： Abd-Elaziz, Mariam M. Elshafie, Basma M. Abdullah, Hagar Gerges, Karen Y. Ghanem, Ingy A. Fouad, Khaled M. El-Ghamry, Amir Moawad, Ibrahim F. El-Metwally, Sara New Mansoura University Faculty of Computer Science and Engineering Dakahlia Egypt Mansoura University New Mansoura University Faculty of Engineering Computer and Communication Program Faculty of Computer Science and Engineering Egypt Benha University Information Systems Faculty of Computers and Artificial Intelligence Egypt Mansoura University New Mansoura University Faculty of Computer and Information Sciences Faculty of Computer Science and Engineering Egypt School of Engineering and Computer Science University of Hertfordshire Gaf Egypt Ain Shams University Faculty of Computer and Information Sciences Cairo Egypt College of Computer Science and Engineering Taibah University Department of Artificial Intelligence Medina42353 Saudi Arabia

ISBN: (纸本)9798350378511

Skin cancer's increasing incidence rates necessitate advanced diagnostic tools. This research uses MobileNet architecture to develop an enhanced system for skin cancer detection. MobileNet's efficient CNN architecture, combined with Keras for model lifecycle management and TensorFlow for real-time inference, forms the foundation of this study. Using 10,015 dermatoscopic pictures from seven different classifications of skin cancer in the HAM10000 dataset, the methodology includes several key stages: image preprocessing to correct illumination and adjust resolution, data augmentation to balance the dataset, and model training using Transfer Learning. The MobileNet model was trained over 50 epochs with a comprehensive architecture incorporating multiple specialized layers. By combining large-scale data analysis and adaptive learning, this methodology demonstrates The revolutionary possibilities of AI and ML in improving skin cancer diagnostics and public health outcomes. Keywords Skin Cancer Detection, Dermatoscopic Images, Machine Learning, Deep Learning © 2024 IEEE.

关键词： Adversarial machine learning

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Alternating Minimization Schemes for Computing Rate-Distortion-Perception Functions with f-Divergence Perception Constraints

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arXiv 2024年

作者： Serra, Giuseppe Stavrou, Photios A. Kountouris, Marios Communication Systems Department EURECOM Sophia-Antipolis France Department of Computer Science and Artificial Intelligence University of Granada Spain

We study the computation of the rate-distortion-perception function (RDPF) for discrete memoryless sources subject to a single-letter average distortion constraint and a perception constraint that belongs to the family of f -divergences. In this setting, the RDPF forms a convex programming problem for which we characterize the optimal parametric solutions. We employ the developed solutions in an alternating minimization scheme, namely Optimal Alternating Minimization (OAM), for which we provide convergence guarantees. Nevertheless, the OAM scheme does not lead to a direct implementation of a generalized Blahut-Arimoto (BA) type of algorithm due to the presence of implicit equations in the structure of the iteration. To overcome this difficulty, we propose two alternative minimization approaches whose applicability depends on the smoothness of the used perception metric: a Newton-based Alternating Minimization (NAM) scheme, relying on Newton’s root-finding method for the approximation of the optimal iteration solution, and a Relaxed Alternating Minimization (RAM) scheme, based on a relaxation of the OAM iterates. Both schemes are shown, via the derivation of necessary and sufficient conditions, to guarantee convergence to a globally optimal solution. We also provide sufficient conditions on the distortion and the perception constraints which guarantee that the proposed algorithms converge exponentially fast in the number of iteration steps. We corroborate our theoretical results with numerical simulations and draw connections with existing results. © 2024, CC BY.

关键词： Convex optimization

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A flexible capacitive photoreceptor for the biomimetic retina

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Light(science & Applications) 2022年第1期11卷 38-49页

作者： Mani Teja Vijjapu Mohammed E.Fouda Agamyrat Agambayev Chun Hong Kang Chun-Ho Lin Boon S.Ooi Jr-Hau He Ahmed M.Eltawil Khaled N.Salama Sensors lab Advanced Membranes and Porous Materials CenterComputerElectrical and Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Communication and Computing Systems Lab ComputerElectrical and Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Department of Electrical Engineering and Computer Science University of California-IrvineIrvineCA 92612USA Department of Electrical Computer and Energy EngineeringArizona State UniversityTempeAZUSA Computer Electrical and Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Department of Materials Science and Engineering City University of Hong KongHong Kong SARChina

Neuromorphic vision sensors have been extremely beneficial in developing energy-efficient intelligent systems for robotics and privacy-preserving security *** is a dire need for devices to mimic the retina's photoreceptors that encode the light illumination into a sequence of spikes to develop such ***,we develop a hybrid perovskite-based flexible photoreceptor whose capacitance changes proportionally to the light intensity mimicking the retina's rod cells,paving the way for developing an efficient artificial retina *** proposed device constitutes a hybrid nanocomposite of perovskites(methyl-ammonium lead bromide)and the ferroelectric terpolymer(polyvinylidene fluoride trifluoroethylene-chlorofluoroethylene).A metal-insulator-metal type capacitor with the prepared composite exhibits the unique and photosensitive capacitive behavior at various light intensities in the visible light *** proposed photoreceptor mimics the spectral sensitivity curve of human photopic *** hybrid nanocomposite is stable in ambient air for 129 weeks,with no observable degradation of the composite due to the encapsulation of hybrid perovskites in the hydrophobic *** functionality of the proposed photoreceptor to recognize handwritten digits(MNIST)dataset using an unsupervised trained spiking neural network with 72.05%recognition accuracy is *** demonstration proves the potential of the proposed sensor for neuromorphic vision applications.

关键词： perovskite illumination preserving

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A Question of Trust: Old and New Metrics for the Reliable Assessment of Trustworthy AI

A Question of Trust: Old and New Metrics for the Reliable As...

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16th International Joint Conference on Biomedical Engineering systems and Technologies, BIOSTEC 2023

作者： Campagner, Andrea Angius, Riccardo Cabitza, Federico IRCCS Ospedale Galeazzi-Sant’Ambrogio Milan Italy University of Padova Padua Italy Department of Computer Science Systems and Communication University of Milano-Bicocca Milan Italy

This work contributes to the evaluation of the quality of decision support systems constructed with Machine Learning (ML) techniques in Medical Artificial Intelligence (MAI). In particular, we propose and discuss metrics that complement and go beyond traditional assessment practices based on the evaluation of accuracy, by focusing on two different dimensions related to the trustworthiness of a MAI system: reputation/ability, which relates to the accuracy or predictive ability of the system itself;and expertise/source reliability, which relates instead to the trustworthiness of the data which have been used to construct the MAI system. Then, we will discuss some previous, but so far mostly neglected, proposals as well novel metrics, visualizations and procedures for the sound evaluation of a MAI system's trustworthiness, by focusing on six different concepts: advice accuracy, advice reliability, pragmatic utility, advice value, decision benefit and potential robustness. Finally, we will illustrate the application of the proposed concepts through two realistic medical case studies. © 2023 by SCITEPRESS – science and Technology Publications, Lda.

关键词： Adversarial machine learning

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Artificial Intelligence For Realtime Face Recognition Attendance Using College Classrooms and Buses

Artificial Intelligence For Realtime Face Recognition Attend...

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2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Ahila, A. Hosanna Princye, P. Poonguzhali, A. Kavivendhan Deepa, M. Arthy, A. Saravanakumar, R. Sri Sairam College of Engineering Department of Electronics and Communication Engineering Anekal Bangalore India Francis Xavier Engineering College Department of Computer Science and Business Systems Tamil Nadu Tirunelveli India Iconix Software Solution Software Analyst Tamil Nadu Tirunelveli India

ISBN: (纸本)9798350378092

Teachers take attendance by having pupils sign in or check-in classes and transportation. Student absences often result from individual mistakes. This article examines a technology that records data from classroom photographs of every student's face. This research uses an Adaptive Boost Classifier, Random Forest (RF), and Deep Convolutional Neural Networks (DCNNs). The model performs well on the DCNN model with 88 and 92% accuracy and on the ResNet50 pre-trained model with 97.21% accuracy. After detecting each student's face, they recorded their present status in an Excel document. It kept the best system implementation approach based on performance. © 2024 IEEE.

关键词： Convolutional neural networks

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Design and Development of an Ontology Driven Search Engine for a Mobile Cloud Asynchronous Remote Learning Platform 13

Design and Development of an Ontology Driven Search Engine f...

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13th Annual IEEE Global Humanitarian Technology Conference, GHTC 2023

作者： Cruz, X.M. Honrado, J.L. Coronel, A. Libatique, N.J. Tangonan, G. Ateneo de Manila University Ateneo Innovation Center Quezon City Philippines Ateneo de Manila University Department of Information Systems and Computer Science Quezon City Philippines Ateneo de Manila University Department of Electronics Computer and Communication Engineering Department Quezon City Philippines

ISBN: (纸本)9798350321326

In the face of a global pandemic, the digital divide has become apparent especially in bandwidth-constrained countries. As contactless remote services have become increasingly necessary in the face of limited human mobility, remote learning has become the norm. To support remote learning, the research team developed a resilient asynchronous remote learning and content distribution platform as a digital library. Collaborating with corresponding stakeholders, the scope of content for the initial iterations of the platform was curated to accommodate resources for STEM educational *** the initial feedback for the prototype, there is a need for a consolidated means of retrieving information and resources across content channels while adhering to the prescribed Philippine K-12 curriculum. As such, the researcher proposes an implementation of an ontology-driven search engine deployed on the remote learning platform. The search engine will use an ontology encompassing the K-12 curriculum and an index of curated content across the educational content-hosting services within the digital library. This study develops a system to reliably retrieve and recommend contextually relevant results with the use of semantic web annotations and semantic information retrieval techniques to improve upon classical information retrieval. © 2023 IEEE.

关键词： COVID-19

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Optimal Resource Allocation for NOMA Wireless Networks

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computers, Materials & Continua 2023年第2期74卷 3249-3261页

作者： Fahad R.Albogamy M.A.Aiyashi Fazirul Hisyam Hashim Imran Khan Bong Jun Choi Turabah University College Computer Sciences ProgramTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Mathematics Jazan UniversityJazanP.O.Box 218Saudi Arabia Department of Computer and Communication Systems Engineering Faculty of EngineeringUniversiti Putra Malaysia(UPM)43400SerdangMalaysia Department of Electrical Engineering University of Engineering and Technology PeshawarP.O.Box 814Pakistan School of Computer Science and Engineering Soongsil UniversitySeoulKorea

The non-orthogonal multiple access(NOMA)method is a novel multiple access technique that aims to increase spectral efficiency(SE)and accommodate enormous user ***-user signals are superimposed and transmitted in the power domain at the transmitting end by actively implementing controllable interference information,and multi-user detection algorithms,such as successive interference cancellation(SIC),are performed at the receiving end to demodulate the necessary user *** its basic signal waveform,like LTE baseline,could be based on orthogonal frequency division multiple access(OFDMA)or discrete Fourier transform(DFT)-spread OFDM,NOMA superimposes numerous users in the power *** contrast to the orthogonal transmission method,the nonorthogonal method can achieve higher spectrum ***,it will increase the complexity of its *** power allocation techniques will have a direct impact on the system’s *** a result,in order to boost the system capacity,an efficient power allocation mechanism must be *** research developed an efficient technique based on conjugate gradient to solve the problem of downlink power *** major goal is to maximize the users’maximum weighted sum *** suggested algorithm’s most notable feature is that it converges to the global optimal *** compared to existing methods,simulation results reveal that the suggested technique has a better power allocation capability.

关键词： Non-orthogonalmultiple access wireless networks power domain 5G networks

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Efficient UAV Routing Strategies for Wireless Sensor Network Data Retrieval

Efficient UAV Routing Strategies for Wireless Sensor Network...

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

作者： Ahmed, Amjed Abbas Al-Sharhanee, Kareem Ali Malalah Najim, Ali Hamza Alheeti, Khattab M. Ali Satar, Nurhizam Safie Mohd Hashim, Aisha Hassan Abdallah Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq College of Engineering Techniques Department of Communication Technical Engineering Al-Farahidi University Baghdad10011 Iraq Department of Computer Technical Al-Diwaniyah Iraq College of Computer and Information Technology University of Anbar Computer Networking Systems Department Anbar Iraq Center for Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

WSNs are applied in many disciplines where certain conditions require the ability to adapt to network sink mobility and changes in the dynamics of the area coverage. To meet these needs, it is necessary to develop integrated systems where the ''terrestrial' systems and the Unmanned Aerial Vehicles (UAVs)' collect data from sensors efficiently. Planning of UAV trajectories is another challenging issue if many WSN nodes are randomly deployed. This challenge has a big impact on the overall effectiveness of the system. This paper presents a novel approach for reducing the traveled distance of unscrewed aerial vehicles (UAVs) to improve the data collection efficiency in WSNs with poor node density. Yet the method that has been developed is aimed at increasing 'the efficiency and efficacy of data collection... with the assistance of Unmanned Aerial Vehicles (UAVs)' which means this work reveals practical application solutions. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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An Intelligent Voice-Recognition Wheelchair System for Disabled Persons

An Intelligent Voice-Recognition Wheelchair System for Disab...

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2023 International Conference on Sustainable Computing and Smart systems, ICSCSS 2023

作者： Kalpana, A.V. Venkataramanan, V. Charulatha, G. Geetha, G. Srm Institute of Science and Technology Department of Data Science and Business Systems Tamil Nadu Chennai India D.J Sanghvi College of Engineering Department of Electronics and Communication Engineering Maharashtra Mumbai India Peri Institute of Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India B v Raju Institute of Technology Department of Computer Science Engineering Telangana Hyderabad India

ISBN: (纸本)9798350333602

This study illustrates the creation of an intelligent voice-recognition wheelchair for disabled persons who cannot manually man-oeuvre their wheelchairs. Using voice recognition, the patient operates the wheelchair, and a GPS device included in the wheelchair can track the patient's position and communicate the data to a Smartphone. To carry out the people's orders, the voice module V3 records and can recognize the patient's voice. This module converts the voice commands into letters, subsequently transmitted to the Wi-Fi module to operate the wheelchair. The Wi-Fi module sends commands to the motor drive for the wheels. In addition, three levels of motor speed adjustment are available: low, medium, and high. This device also utilizes an Infrared sensor to automatically identify obstacles, allowing the patient's family members to know exactly where they are. Disabled People can be used this device, which simultaneously provides a voice-controlled wheelchair, obstacle detection, motor speed control, and patient GPS tracking via mobile phone;it will be a successful solution for disabled people across the world. © 2023 IEEE.

关键词： Wheelchairs

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