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BrainTract: segmentation of white matter fiber tractography and analysis of structural connectivity using hybrid convolutional neural network

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Neuroscience 2025年 580卷 218-230页

作者： Puranam Revanth Kumar B Shilpa Rajesh Kumar Jha Department of Electronics and Communication Engineering Faculty of Science and Technology (IcfaiTech) ICFAI Foundation for Higher Education Hyderabad India Department of Artificial Intelligence and Machine Learning School of Engineering Malla Reddy University Hyderabad India. Electronic address: revanth123451.rk@***. Department of Computer Science and Engineering AVN Institute of Engineering and Technology Hyderabad India. Department of Electronics and Communication Engineering Faculty of Science and Technology (IcfaiTech) ICFAI Foundation for Higher Education Hyderabad India.

Tractography uses diffusion Magnetic Resonance Imaging (dMRI) to noninvasively reconstruct brain white matter (WM) tracts, with Convolutional Neural Network (CNNs) like U-Net significantly advancing accuracy in medical image segmentation. This work proposes a metaheuristic optimization algorithm-based CNN architecture. This architecture combines the Inception-ResNet-V2 module and the densely connecting convolutional module (DI) into the Spatial Attention U-Net (SAU-Net) architecture for segmenting WM fiber tracts and analyzing the brain's structural connectivity. The proposed network model (DISAU-Net) consists of the following parts are; First, the Inception-ResNet-V2 block is used to replace the standard convolutional layers and expand the network's width; Second, the Dense-Inception block is used to extract features and deepen the network without the need for any additional parameters; Third, the down-sampling block is used to speed up training by decreasing the size of feature maps, and the up-sampling block is used to increase the maps' resolution. In addition, the parameter existing in the classifiers is randomly selected with the Gray Wolf Optimization (GWO) technique to boost the performance of the CNN architecture. We validated our method by segmenting WM tracts on dMRI scans of 280 subjects from the human connectome project (HCP) database. The proposed method is far more efficient than current methods. It offers unprecedented quantitative evaluation with high tract segmentation consistency, achieving accuracy of 97.10%, dice score of 96.88%, recall 95.74%, f1-score 94.79% for fiber tracts. The results showed that the proposed method is a potential approach for segmenting WM fiber tracts and analyzing the brain's structural connectivity.

关键词： DenseNet Diffusion magnetic resonance imaging Grey wolf optimization Spatial Attention U-Net White matter tract segmentation

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Incorporating Extended Reality technology for Delivering computer Aided Design and Visualisation Modules 14

Incorporating Extended Reality Technology for Delivering Com...

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14th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2022

作者： Vichare, Parag Cano, Michele Dahal, Keshav Siewierski, Tomasz Gilardi, Marco University of the West of Scotland PaisleyPA1 2BE United Kingdom Lodz University of Technology Faculty of Electrical Electronic Computer and Control Engineering Lodz90-537 Poland

ISBN: (纸本)9781665493345

The basic requirement in curriculum design is to review and constructively align programme modules with state-of-the art and trends in the subject area. Extended reality (XR), an umbrella term for emerging technologies such as augmented reality (AR), mixed reality (MR) and virtual reality (VR), is becoming a prominent aspect of design and visualization for architecture, engineering, and construction (AEC) industry. engineering programmes are primary feeders for the AEC industry, delivery of CAD and visualisation modules provide wider opportunities for adapting such emerging technologies in the subject area, as well as use of these technologies for developing novel pedagogical practices. This paper provides a rational behind revising traditional CAD and visualisation modules designed for engineering undergraduate programmes, and constructively incorporate XR within programme modules. A critical literature review is provided on XR subject area as well as XR based pedagogical practices. This review identifies elements of XR as a subject area that can be incorporated in AEC programmes. It also highlights academic and operational considerations in adapting XR technology for delivering CAD and visualisation modules. Similar approach is extended to evaluate integration of XR technologies for Electrical and Power engineering Programmes. © 2022 IEEE.

关键词： computer aided design

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Sentiment Analysis Using Machine Learning and Deep Learning Models

Sentiment Analysis Using Machine Learning and Deep Learning ...

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Machine Learning and Applied Network Technologies (ICMLANT), IEEE International Conference on

作者： Hoang-Dieu Vu Quang-Tu Pham Vijender Kumar Solanki Trong-Minh Hoang Due-Tan Tran Faculty of Electrical and Electronic Engineering Phenikaa University Hanoi Vietnam Department of Computer Science and Enginnering Stanley College Of Engineering & Technology For Women Hyderabad TG India Posts and Telecommunications Institute of Technology Hanoi Vietnam

ISBN: (数字)9798350389180

ISBN: (纸本)9798350389197

This study investigates sentiment analysis method-ologies using two distinct datasets: the IMDb Movie Reviews corpus and a novel Financial Sentiment dataset. Employing a comprehensive approach, the research integrates traditional Machine Learning algorithms and Deep Learning models to analyze and interpret sentiments. The preprocessing phase incor-porates techniques such as punctuation removal, text lowercasing, and specialized considerations for financial symbols. Machine Learning models, including Logistic Regression and Random Forest, are applied to the IMDb dataset, with Naive Bayes demonstrating superior performance at 89% accuracy. The Deep Learning model achieves 82% accuracy on the testing set. In the Financial Sentiment dataset, Naive Bayes emerges as the optimal model, despite reduced overall performance due to dataset limitations and imbalance. This research contributes valuable insights into sentiment analysis methodologies, offering a nuanced understanding of model performance across diverse datasets and enhancing our comprehension of sentiment classification in various contexts.

关键词： Deep learning Analytical models Sentiment analysis Logistic regression Machine learning algorithms Accuracy Reviews Symbols Bayes methods Testing

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Modeling and Analysis of Electrical Circuit Connections in the Piezoelectric Cantilever Array for Vibration Energy Harvester

Modeling and Analysis of Electrical Circuit Connections in t...

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International Conference on Environment and Electrical engineering (EEEIC)

作者： Li Wah Thong Swee Leong Kok Roszaidi Ramlan Faculty of Engineering and Technology Multimedia University Melaka Malaysia Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka Melaka Malaysia Faculty of Mechanical Engineering Universiti Teknikal Malaysia Melaka Melaka Malaysia

The use of energy-efficient and environmentally-friendly low-power sensors technologies has impacted the advancement of vibration energy harvesting systems. The standard piezoelectric cantilever beam has numerous limitations, such as a limited operating range and decreased output power due to mismatch of operating frequency and its surrounding frequencies. A broadband approach to energy harvesting is crucial for capturing electrical energy from random ambient vibrations. In this study, a model of the piezoelectric energy harvesters is established to assess the effectiveness of a multi-cantilever system. This research explores the impact of two distinct electrical connection configurations for the cantilevers, specifically series and parallel circuit arrangements, on boosting the power output and expanding the bandwidth. An array consisting of four similar piezoelectric cantilevers with different resonant frequencies were positioned alongside each other to function as a system for producing electrical output across a frequency range between 100Hz to 400Hz. The bandwidth of the multi-cantilever system was effectively expanded from 100Hz to 200 Hz for a 4-beam system, which is twice its original single cantilever output for both the series and parallel configurations. The peak output voltage of the system is also notably higher, at least a two-fold increase over the individual cantilever beams.

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Improving Subset Linear Discriminant Analysis Algorithm Using Overlapping Clustering

Improving Subset Linear Discriminant Analysis Algorithm Usin...

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

作者： Mandeel, Thulfiqar H. Ahmad, Muhammad Imran Khalid, Noor Aldeen A. Hassan, Mustafa Hamid Kadhim, Mohammed Hayder Imam Ja'afar Al-Sadiq University College of Information Technology Department of Computer Techniques Engineering Muthanna Iraq Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Perlis Malaysia Bilad Alrafidain University College Department of Medical Instruments Engineering Techniques Diyala Iraq Imam Ja'afar Al-Sadiq University College of Information Technology Muthanna Iraq Jabir Ibn Hayyan for Medical and Pharmaceutical Sciences Department of Information Technology Najaf Iraq

ISBN: (纸本)9798350341881

In recent years, there have been many proposals to improve the performance of traditional linear discriminant analysis (LDA). One of these is subset-improving linear discriminant analysis (S-LDA), which is based on clustering the whole set of classes into subsets and performing the LDA locally on these subsets. However, this algorithm suffers from an improper mapping of the classes to the corresponding subset during the testing procedure due to the inevitable discrepancy between the images used for training and those for testing. This discrepancy is caused either by spatial distortion or noise. The wrong mapping is severe when the number of data samples is small which is a common scenario in biometric datasets. In this paper, overlapping clustering is proposed for class clustering, to overcome the aforementioned problem. The proposed algorithm outperforms the S-LDA by 35.4% in mapping accuracy when using the PolyU palmprint database, 36.96%, resp. 33.92% when using left resp. Right palm images from the IIT Delhi Touchless Palmprint Database. © 2023 IEEE.

关键词： Mapping

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Energy Efficiency Maximization for Relay-aided Wireless Powered Mobile Edge Computing

TechRxiv

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TechRxiv 2023年

作者： Wu, Tongyu He, Huaiwen Shen, Hong School of Computer University of Electronic Science and Technology of China Zhongshan Institute China Computer Science and Engineering School University of Electronic Science and Technology of China China Faculty of Applied Sciences Macao Polytechnic University China

Mobile edge computing (MEC) integrated with radio frequency-based wireless power transfer (WPT) has became a promising trend to shorten task delay and achieve sustainable operations of computing system, as it continuously provides energy to wireless devices (WDs) and allows computation tasks offloading to a powerful edge server nearby. Furthermore, introducing the relay technique to WPT-MEC system could improve offloading capability and energy efficiency, especially when the condition of the wireless channels between server and WDs is poor. In this paper, we seek to maximize the energy efficiency (EE) for a multiuser relay-aided MEC network powered by WPT, where binary offloading policy is followed in WDs and partial offloading policy is adopted in the relay. We aim to jointly optimize the relay’s computing configurations, wireless charge time fraction and WDs offloading strategy, that faces great challenge due to the strong coupling of multi-user computing mode selection and hybrid offloading model among WDs and relay. To tackle the problem, we formulated it as a mixed integer nonlinear programming (MINLP) problem and design an iterative algorithm based on Dinkelbach’s method and alternating direction method of multipliers (ADMM) decomposition technique to solve it. We first transform the original fractional programming problem into a more tractable problem in a subtraction form based on Dinkelbach’s method. Then according to ADMM technique, we decompose the multi-user offloading problem into multiple subproblems which can be solved in a distributed model. For an iterative calculating step, we propose a Bi-Search algorithm for CPU frequency and transmission power optimization and a DAI-Based algorithm to choose the time fraction of wireless power charging. The simulation results show that our proposed algorithm convergence fast and derive a 15% higher energy efficiency than other benchmark methods. © 2023, CC BY-NC-SA.

关键词： Mobile edge computing

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Distributed Fixed-Time Algorithms for Time-Varying Constrained Optimization Problems

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年

作者： He, Xing Li, Yue Zhang, Meng Huang, Tingwen Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Chongqing400715 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

In this paper, the distributed form of the zeroing neural network for solving time-varying optimal problems is put forward. Compared with traditional centralized algorithms, distributed algorithms possess better privacy and scalability. This paper initially proposes a centralized time-varying optimisation algorithm with fixed-time convergence and certain robustness, which is based on the integration-enhanced zeroing neural network. Subsequently, the algorithm is enhanced, and two distributed algorithms are designed separately. Both of these two algorithms have a fixed convergence time and certain robustness. Additionally, this paper utilizes the penalty function approach to handle time-varying optimization problems with inequality constraints, thereby making the algorithm more widely applicable. The effectiveness of the algorithm is verified through several numerical examples, and the applicability of the algorithm is demonstrated by solving the package-level state-of-charge balancing problem. © 2020 IEEE.

关键词： Optimization algorithms

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The Response of EEG Signal on Brain Relaxation Meditation Using Different Type of Zikr

The Response of EEG Signal on Brain Relaxation Meditation Us...

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2021 International Conference on Biomedical engineering, ICoBE 2021

作者： Razak, N.N. Abd Sidek, K.A. Alaa, K.Y.D. Nasir, N.F. Mohd Department of Electrical and Computer Engineering Kulliyyah of Engineering International Islamic University Malaysia Department of Computer Engineering College of Computer Science and Engineering University of Ha’il Saudi Arabia Biomedical Electronic Engineering Programme Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Malaysia

Depression and stress are increasingly prevalent in today’s society, owing to people's hectic, competitive, and demanding lifestyles. These illnesses had become very common, particularly among young and middle-aged people, and suicidal ideation had been identified as one of the leading causes of death by the World Health Organization (WHO). Nature sound (sound of downpours or beach) has been linked to depression and anxiety in neurology research, and it has been shown to be an alternative to alleviate anxiety. The electroencephalogram (EEG) waveform has been discovered to possess the potential in identifying information from the brain signal as well as data from the past via Bluetooth communication. The waveform use in the study are the result of a few experiments. In this study, EEG data were collected from eight subjects, four males and four females, in between the age of 20 to 30 years old and in good health, using the BrainLink device. The participants were asked to listen to two playlists of zikr, Allah, Ya Allah, and SubhanAllah, during the experiments. To smooth the signal, the Butterworth filter was used. Later, the extracted features were Alpha, Beta, and Delta waves, which were segmented based on the filtered signal. To complete the decision-making stage, the average value of amplitude differences and the p-value test were performed in the final phase. Based on the results of the experiments, it is clear that zikr is dominant in Delta wave. In terms of data hypothesis analysis, the results of both experiment were differentiated to determine which brain signal was dominant, and p-value testing was performed. Furthermore, this research is an alternative to current methods because it suggest that zikr has the tendency to alter a person's brain state to be either in a relaxed or calm mode regardless of the type of zikr recitation. As an outcome, the study recommends the relationship of the reaction of EEG signal on brain relaxation with different types of zikr

关键词： Electroencephalography

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Design of an electronically Controlled Biquadratic Filter Using Commercial ICs

Design of an Electronically Controlled Biquadratic Filter Us...

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International Electrical engineering Congress (iEECON)

作者： Somkid Ritnathikul Danupat Duangmalai Khanittha Kaewdang Settasuk Kwuanphet Thanawat Chalermpong Koson Pitaksuttayaprot Department of Computer Engineering Faculty of Agricultural and IndustrialTechnology Phetchabun Rajabhat University Phetchabun Thailand Department of Electrical and Electronic Engineering Faculty of Engineering Ubon Ratchathani University Ubon Ratchathani Thailand Department of Electrical Engineering Faculty of Industrial Technology Nakhon Phanom University Nakhon Phanom Thailand Department of Electronics and Automation Systems Engineering Faculty of Agricultural and Industrial Technology Phetchabun Rajabhat University Phetchabun Thailand

ISBN: (数字)9798331543952

ISBN: (纸本)9798331543969

This paper presents an electronically controlled biquadratic filter designed for precise frequency selection in applications such as audio processing, telecommunications, and cochlear implants. The design utilizes AD830, AD844, and LM13700 integrated circuits, facilitating high-pass, band-pass, and low-pass responses with improved stability and real-time tunability. PSPICE simulations validate the filter's adaptability and performance, demonstrating its effectiveness in dynamic environments and its suitability for high-frequency applications requiring flexible frequency control. The results indicate a calculated pole frequency of 2.23 MHz, while simulations yield a slightly lower value of 2.0 MHz, affirming the design's practical viability and alignment with theoretical expectations.

关键词： Band-pass filters Performance evaluation Adaptation models Low-pass filters SPICE Stability analysis Real-time systems Telecommunications Integrated circuit modeling Frequency control

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Optimizing Scattering Area of ZnO Nanostructures on Glass Substrates Platform for Sensing

Optimizing Scattering Area of ZnO Nanostructures on Glass Su...

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IEEE International Conference on Sensors and Nanotechnology

作者： Marlina Jahava Mohd Hafiz Jali Md. Ashadi Md Johari Mohd Adili Norashikin Haziezol Helmi Mohd Yusof Aminah Ahmad Faculty of Electrical Engineering Universiti Teknikal Malaysia Melaka Malacca Malaysia Faculty of Information Technology and Computer Engineering Universiti Teknikal Malaysia Melaka Malacca Malaysia Faculty of Electronic Engineering and Computer Engineering Universiti Teknikal Malaysia Melaka Malacca Malaysia Faculty of Electrical and Electronics Engineering Technology Universiti Teknikal Malaysia Melaka Malacca Malaysia

This paper presents an optimization of scattering area on a glass substrate platform for a proposed sensing method. The glass substrate was coated with sensitive nanomaterial, which is Zinc Oxide (ZnO) nanorods. The hydrothermal technique was employed to fabricate the ZnO nanorods on microscope glass substrates of varying areas. The samples undergo exposure to various levels of RI solution, ranging from 0% to 100% concentration. This was performed to examine several performance parameters, including the scattering coefficient, and sensing performance factor that generated by the proposed sensor. The growth area of 0.022m2 demonstrated the most favorable samples with respect to the concentration level. It exhibited normalized scattering coefficient (α) and normalized sensing performance factor (ɣ) close to 1 which is desirable in this study.

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