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Adventitia Segmentation on Superficial Femoral Artery Optical Coherence Tomography Images 24

Adventitia Segmentation on Superficial Femoral Artery Optica...

引用

24th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2024

作者： Anić, Miloš Nikopoulos, Sotirios Siaravas, Konstantinos Katsouras, Christos S. Potsika, Vassiliki Filipović, Nenad Fotiadis, Dimitrios I. University of Ioannina MedLab Ioannina Greece Medical School Dept. of Cardiology Ioannina Greece Medical School Michaelidion Cardiac Center Dept. of Cardiology Ioannina Greece University of Ioannina Unit of Medical Technology and Intelligent Information Systems Dept. of Materials Science and Engineering Ioannina Greece University of Kragujevac BioIRC Kragujevac Serbia University of Ioannina Biomedical Research Institute FORTH Unit of Medical Technology and Intelligent Information Systems Dept. of Materials Science and Engineering Ioannina Greece

ISBN: (纸本)9798331518622

Atherosclerotic disease on peripheral arteries, commonly known as peripheral artery disease represents accumulation of cholesterol in peripheral arteries. It causes the formation of different types of depositions called plaques which cause thickening of the arterial walls resulting in reduced blood flow to lower extremities, in case of femoral arteries, upper extremities, in case of brachial artery or brain in case of carotid artery. Current research shows that approximately 8.5 million Americans, aged over 40 years, are affected by peripheral artery disease while one fourth of them falls into a severe category. For these reasons, an early detection of the disease is important. In order to detect the disease, arteries need to be imaged properly. In the recent years, an increase of optical coherence imaging has occurred due to the ease of use and the ability to detect tissue morphology which is extremely important for the detection of the disease. From the tissue morphology, it is of most importance to observe the tissue between lumen and intimal layer of the artery, since the majority of the plaques form in that region, but it is also important to observe the region between intima and adventitia (the outer wall of the artery) since the plaque can penetrate the intimal layer as well. In this paper, a deterministic approach for the detection of the adventitia is described based on the previously detected intimal layer of the artery. The proposed method is evaluated on optical coherence tomography images from 8 specimens of porcine femoral arteries. The results show that the detection of adventitia is possible on this image modality with Dice coefficient 0.9805 and Hausdorff distance 0.1 mm. © 2024 IEEE.

关键词： Optical coherence tomography

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Refreshable Braille Display: A Review of Existing Technologies and a Proposed Method

Refreshable Braille Display: A Review of Existing Technologi...

引用

Power, Electrical, and Electronics and Industrial Applications (PEEIACON), IEEE International Conference on

作者： Md Asraful Alam Nayan Chandra Roy Durjoy Kumar Paul Nazifa Fairuz Zuthi Dept. of Mechanical Engineering Rajshahi University of Engineering & Technology Rajshahi Bangladesh

ISBN: (数字)9798331517984

ISBN: (纸本)9798331517991

The world is currently undergoing the fourth Industrial Revolution (4IR), in which information plays a crucial role in everyday life. However, those with visual impairments are unable to access information by visual means. Approximately 237 million individuals worldwide suffer from vision impairment. The Refreshable Braille Display (RBD) is considered the most advanced and significant instructional tool for the visually impaired (VI), garnering interest from scientists and researchers worldwide. There are numerous technologies available to actuate the RBD. A comprehensive and meticulous examination of the existing technologies is necessary to make the proper choice of actuating technology in relevant applications. This paper aims to categorize the published articles based on the different types of actuation technologies that exist, and to examine each technology in terms of its benefits, drawbacks, and technical and economic parameters such as cost, power consumption, frequency, durability, etc. The analysis demonstrated that the electromagnetic actuation method is the most suitable approach from both an economic and technical standpoint. The authors proposed a RBD that utilizes the electromagnetic actuation approach. This method involves the use of a permanent magnet, electromagnet, and a cam in each braille pin. The proposed method is anticipated to fulfill all the necessary criteria and specifications of a braille display. The authors have already finished creating the computer-aided design (CAD) model of the proposed approach.

关键词： Braille Solid modeling Visualization Design automation Costs Reviews Computational modeling Visual impairment Electromagnetics Pupils

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Active RIS-Aided Terahertz Communications with Phase Error and Beam Misalignment 15

Active RIS-Aided Terahertz Communications with Phase Error a...

引用

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

作者： Khalid, Waqas Yu, Heejung Ali, Farman Huang, Huiping Institute of Industrial Technology Korea University Sejong Korea Republic of Korea University Dept. of Elec. & Inform. Eng. Sejong Korea Republic of School of Convergence Sungkyunkwan University Dept. of Applied Ai Seoul Korea Republic of Chalmers University of Technology Dept. of Electrical Engineering Sweden

ISBN: (纸本)9798350364637

Terahertz (THz) communications will be pivotal in sixth-generation (6G) wireless networks, offering significantly wider bandwidths and higher data rates. However, the unique propagation characteristics of the THz frequency band, such as high path loss and sensitivity to blockages, pose substantial challenges. Reconfigurable intelligent surfaces (RISs) present a promising solution for enhancing THz communications by dynamically shaping the propagation environment to address these issues. Active RISs, in particular, can amplify reflected signals, effectively mitigating the multiplicative fading effects in RIS-aided links. Given the highly directional nature of THz signals, beam misalignment is a significant concern, while discrete phase shifting is more practical for real-world RIS deployment compared to continuous adjustments. This paper investigates the performance of active-RIS-aided THz communication systems, focusing on discrete phase shifts and beam misalignment. An expression for the ergodic capacity is derived, incorporating critical system parameters to assess performance. Numerical results offer insights into optimizing active-RIS-aided THz communication systems. © 2024 IEEE.

关键词： Interlocking signals

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Predicting Metabolic Reactions with a Molecular Transformer for Drug Design Optimization 21

Predicting Metabolic Reactions with a Molecular Transformer ...

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21st IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2024

作者： Multari, Silvia Özçelik, Riza Mazzolari, Angelica Nobile, Marco Salvatore Grisoni, Francesca Ca' Foscari University of Venice Dept. of Molecular Sciences and Nanosystems Venice Italy Eindhoven University of Technology Dept. of Biomedical Engineering Eindhoven Netherlands University of Milan Dept. of Pharmaceutical Sciences Milan Italy Ca' Foscari University of Venice Dept. of Environmental Sciences Informatics and Statistics Venice Italy

ISBN: (纸本)9798350356632

Metabolism prediction is a crucial step of drug development, as the biotransformations a drug candidate undergoes inside the human body can affect the clinical outcome. Computer-aided drug design has been extensively employed to speed up the process and enhance its efficiency and effectiveness, but among the investigated areas, metabolism has received less attention. This project aimed at leveraging machine learning to analyze large metabolic datasets, make predictions, and recognize patterns, in order to fill this knowledge gap and enhance our understanding of metabolism and its impact on drug development. To achieve this goal, we developed a Deep Learning model for metabolism prediction using natural language processing techniques trained on molecular string representations, i.e., Simplified Molecular Input Line Entry systems (SMILES) strings. To this end, we employ a Molecular Transformer, because of its ability to capture sequential and contextual information within strings (in this case, SMILES) enabling the learning of complex relationships. The transformer was trained using a high-quality dataset, MetaQSAR, from which we derived approximately 100000 instances of metabolic reactions. In this work, we investigate whether the Transformer architecture bears the potential to learn a mapping between the input molecular structures and their corresponding metabolites, in order to expedite drug discovery and improve patient safety. © 2024 IEEE.

关键词： Deep learning

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Optimizing Power Quality varify on UPQC and Soft Computing Approaches

Optimizing Power Quality varify on UPQC and Soft Computing A...

引用

Green Industrial Electronics and Sustainable Technologies (GIEST), IEEE International Conference on

作者： Sadasiva Behera Gayatri Bhagat Singh Barar Deepak Sharma Dept. of Electrical Engineering Meerut Institute of Engineering and Technology Meerut India

ISBN: (数字)9798331540142

ISBN: (纸本)9798331540159

One of the most critical challenges in today’s rapidly expanding electrical world is maintaining power quality, efficiently distributing electricity without significant losses is difficult, and it's crucial to ensure that the quality of power remains within acceptable limits. The versatile dual control methodology of the Unified Power Quality Conditioner (UPQC) offers an effective solution to manage power distribution and address power quality issues. UPQC compensates for both current and voltage irregularities in reactive loads while also eliminating harmonics in the load current under distorted supply conditions. This project explores various techniques to enhance power efficiency, starting with the use of a UPQC integrated with a PID controller to address power efficiency challenges. To further improve power quality, an advanced solution using a UPQC with an ANFIS controller has been implemented, significantly enhancing performance.

关键词： Renewable energy sources Power quality Power distribution Power system harmonics Harmonic analysis Harmonic distortion Smart grids Power system reliability Reliability MATLAB

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Secret Key Generation using Genetic Algorithm for the Hybrid Blowfish Encryption and Substitution Ciphers 2

Secret Key Generation using Genetic Algorithm for the Hybrid...

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2nd International Conference on Computer Science, engineering and Applications, ICCSEA 2022

作者： Rao, Shirole Rashmi Prakash Jyothi, K. Nmam Institute of Technology Dept. of Information Science & Engineering Nitte Karnataka India Jnnce Dept. of Information Science & Engineering Shimoga Karnataka India

ISBN: (数字)9781665458344

ISBN: (纸本)9781665458344

Today security and privacy of user from unauthorized access, corruption, or theft is becoming more crucial requirement due to increased use of internet and communication networks. To protect data effectively, there is a need to know about the different security mechanisms. The proposed work presents a novel approach of cryptography discipline. In this approach data privacy is achieved using genetic algorithm, symmetric encryption and the substitution cipher. Implemented model may be used in the medical fields, military applications, forensic science, e-commerce etc. where there is a great exchange of sensitive data. Key point of the proposed method is the use of genetic algorithm for the key generation. Real time clock values are used to generate the keys. Parallel programming is achieved by having two threads for execution. Blowfish algorithm is executed by one thread and substitution cipher method is executed by another thread. Performance analysis is done by observing file accuracy and execution time of the proposed technique and the traditional blowfish technique. Result shows that blowfish technique with the substitution cipher gives better file accuracy in minimum execution time. © 2022 IEEE.

关键词： Genetic algorithms

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Wafer Surface Semiconductor Defect Classification Using Convolution Neural Network Based Improved Faster R-CNN 2

Wafer Surface Semiconductor Defect Classification Using Conv...

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2nd International Conference on Data Science and Information system, ICDSIS 2024

作者： Babu, Praveenkumar Habelalmateen, Mohammed I. Srikanteswara, Ramya Reddy, R. Archana Purushotham, N. Srm Institute Of Science And Technology Department Of Electronics And Communication Engineering Chennai Ramapuram India The Islamic University College Of Technical Engineering Department Of Computers Techniques Engineering Najaf Iraq Nitte Meenakshi Institute Of Technology Department Of Computer Science And Engineering Bengaluru India Sr University School Of Computer Science And Engineering Telangana Warangal India Mohan Babu University School Of Computing Dept. Of Cse Tirupati India

ISBN: (纸本)9798350381665

Defect classification helps ensure the quality and reliability of semiconductor devices. Even a minor defect can lead to significant performance issues or failures in electronic components. Moreover, a recurring issue in this field is the identification of minute fault patterns, frequently measuring just a few μ m in size, and pixels among enormous volumes of high-resolution imaging. In this paper, proposed the improved Faster Region-Based Convolutional Neural Network (R-CNN) by utilizing the Res2Net model can assign the backbone of the proposed model. The model can train and validating on WM811 K dataset. The dataset contains imbalance classes in the presented categories. Initially the data-augmentation technique is employed to create the synthetic data, and it solve the classes imbalance issue. Subsequently Build the Convolutional Neural Network (CNN) foe classify the categories of the defects by using the extracted features. The Res2Net is effectively extract the various features and the feature pyramid network is used to fuse the extracted information. The proposed method is evaluated and compared with various existing methods and metrices such as Accuracy of 97.86 %, precision of 96.50%, Recall of 96.80% and F1-score of 97.85% and the methods are namely Deep Convolutional Neural Network for Wafer Defect Identification (DCNN-WDI), ShuffleNet-v2-CNN and Transfer Learning Using Faster R-CNN. © 2024 IEEE.

关键词： Convolutional neural networks

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Breast Cancer Image Classification Using External Attention Multilayer Perceptron-Based Transformer

Breast Cancer Image Classification Using External Attention ...

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International Conference on Advancement in Electrical and Electronic engineering (ICAEEE)

作者： Shemonti Barua Md Saiful Islam Dept. of Electronics and Telecommunication Engineering Chittagong University of Engineering and Technology Bangladesh

ISBN: (数字)9798350388282

ISBN: (纸本)9798350388299

The prevalence of breast cancer has led to increased interest in its classification among healthcare scholars. Deep learning techniques and self-attention-based transformers have gained popularity in breast image analysis. However, self-attention’s quadratic complexity limits its capacity and interpretability, disregarding sample-to-sample association. To address this issue, a study introduces a novel attention mechanism called External Attention Multi-Layer Perceptron (EAMLP). EAMLP utilizes two external, tiny, learnable, shared retention units implemented with linear and normalization layers. By leveraging the linear complexity of external attention, this approach reduces operational complexity while considering all data point connections. The study evaluates the proposed model’s effectiveness using two publicly available datasets: Breast Histopathology Images and the BreakHis dataset. The model’s performance is assessed using different image sizes and numbers of dense layers. Additionally, a self-attention-based transformer is experimentally tested for comparison. The results demonstrate that the proposed model achieves a maximum accuracy of 95.73%.

关键词： Accuracy Sensitivity Histopathology Noise reduction Transformers Feature extraction Nonhomogeneous media

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High-Speed Secure Vanity Address Generator for User Convenience in Blockchain Networks 5

High-Speed Secure Vanity Address Generator for User Convenie...

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5th International Conference on Blockchain Computing and Applications, BCCA 2023

作者： Islam, Md. Mainul Islam, Md. Kamrul Hammoudeh, Mohammad Texas A&M University Dept. of Computer Science and Engineering College Station United States Shahjalal University of Science and Technology Dept. of Electrical and Electronic Engineering Sylhet Bangladesh King Fahd University of Petroleum and Minerals Dept. of Information and Computer Science Dhahran Saudi Arabia

ISBN: (纸本)9798350339239

Generating a vanity address (VA) for user convenience in blockchain networks is a memoryless brute-force exercise that involves testing millions of probable private keys. It requires a high-speed processor to compute millions of public keys and corresponding addresses in a short time. In this paper, we propose a novel split-key-multiplicative online VA generator for crypto wallet that provides faster VA generation compared with the existing vanity pools. The proposed approach is capable of improving the speed (in keys per second) of conventional VA generation by 2-7 times without reconfiguring the processor. We also propose a high-speed offline VA generator that offers blockchain users the ability to create a VA with a random vanity word using a low-performance processor without reliance on a vanity pool. To the best of our knowledge, this is the first research paper on VA generation in blockchain networks. © 2023 IEEE.

关键词： Blockchain

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Deep Learning Technique for Real-Time Forest Fire Detection from Video Streams 11

Deep Learning Technique for Real-Time Forest Fire Detection ...

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11th International Conference on Intelligent systems and Embedded Design, ISED 2023

作者： Gupta, Nidhi Chakravarty, Sujata Dash, Satyabrata Centurion University of Technology & Management Dept. of Computer Science & Engineering Odisha India Gandhi Institute of Technology & Management Gitam Deemed to Be University Dep. of Computer Science and Engineering Andhra Pradesh India

ISBN: (纸本)9798350318159

Forest fires are currently the most common issue that we are dealing with. The resources that have been lost are irreplaceable. Forest fires are uncontrollable fires that occur in nature as a result of human involvement or any other natural event. Forest fires can be so large that putting them out takes a long time. Contrasting with previous years, there has been a striking surge in the frequency of forest fires. Changes in climatic conditions are the key factor affecting the scope of forest fires. Long dry spells in the spring and summer make the woodlands particularly vulnerable. The extent of forest fires is mostly determined by weather conditions such as precipitation and wind, as well as the terrain's architecture. Long dry spells in the spring and summer make the woodlands particularly vulnerable. The extent of forest fires is mostly determined by weather conditions such as precipitation and wind, as well as the terrain's architecture. The incorporation of a Video Fire Detection model significantly enhances the efficiency of fire detection systems, particularly in large spaces. Establishing a video fire detection system involves focusing on spatial, spectral, and temporal indicators, as well as flame picture segmentation, recognition, tracking, and prediction. Analytical techniques, specifically utilizing ResNet50 and VGG16 models, can be applied to identify pool fire images through these segmentation processes, contributing to more robust fire detection capabilities. © 2023 IEEE.

关键词： Fires

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