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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Yun-Chi Chen Tung Chao Wimaya Nitya Phandita Tzu-Yu Sun Huai-Zhi Wang Yi-Hsien Hsieh Le-Yin Hsu Che Lin Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University (NTU) Taipei Taiwan College of Bioresources and Agriculture NTU Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan Graduate Institute of Communication Engineering NTU Taipei Taiwan Data Science Degree Program NTU Taipei Taiwan Department of Electrical Engineering NTU Taipei Taiwan Center for Advanced Computing and Imaging in Biomedicine NTU Taipei Taiwan Smart Medicine and Health Informatics Program NTU Taipei Taiwan

ISBN: (数字)9798331518622

ISBN: (纸本)9798331518639

Microsatellite instability (MSI) is a pivotal genetic marker influencing the efficacy of immunotherapy in colorectal cancer. Traditional MSI examination often requires additional genetic or immunohistochemical tests, whereas histology images, widely available in colorectal cancer diagnosis, offer a valuable alternative for MSI prediction. Although Transformer-based models have demonstrated promising outcomes in predicting MSI from histology images, they are hampered by traditional local attention mechanisms that struggle to capture long-range interdependencies and establish a comprehensive global receptive field. In this study, we introduce DiNAT-MSI, a novel framework for histology-based MSI prediction that incorporates the Dilated Neighborhood Attention Transformer (DiNAT). This model enhances global context recognition and substantially expands receptive fields, all without additional computational burden. Our results demonstrate that DiNAT-MSI achieves a superior patientwise AUROC compared to ResNet18 and Swin Transformer, along with commendable explainability. Our work not only illustrates a more accessible diagnostic tool for leveraging histological data but also underscores the potential of Transformerbased models with sophisticated attention designs in advancing precision medicine for colorectal cancer patients.

关键词： Attention mechanisms Histopathology Computational modeling Precision medicine Small satellites Immunotherapy Colorectal cancer Predictive models Transformers Genetics

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Sensory Perception of Haptic Rendering in Surgical Simulation

Sensory Perception of Haptic Rendering in Surgical Simulatio...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Rohit Kaushik Rachit Sachdeva Chirag Vashisht Krishan Kant Choudhary CS and Mathematics Department Data Analytics Program University of Illinois Springfield USA Electronics and Communication Engineering Department Dr. Akhilesh Das Gupta Institute of Technology and Management New Delhi India Information Technology and Engineering Department Dr. Akhilesh Das Gupta Institute of Technology and Management New Delhi India

The essential ideas behind haptic technology, including haptic interface and haptic rendering methods, as well as its application to surgical simulation, medical education, and other diverse topics, are presented in this paper. In empirical psychology and physiology, this refers to the sense of contact. The process of analyzing and developing capabilities in response to user interactions with virtual entities is elaborated as haptic rendering. Haptic may indicate haptic transmission, haptic perception, and haptic technology. Humans and other animals can respond to one another by using their feelings through haptic technology. Haptic perception is the process of recognizing objects through *** implies tactile response, which means it delivers feedback in the state of sensation as we may sense the material properties and motions of virtual objects devised by a computer. The use of haptic technology in the medical profession has proven extremely beneficial, and it has a wide range of applications in many different industries. Providing effective exchange via virtual reality helps to ease the surgeon’s obligations. Amplify a person’s experience in the virtual environment. The haptics ability ranges from computer graphics to psychophysics, cognitive science, and neurosciences.

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Fast RTL Implementation of A∗ Path Planning Algorithm

Fast RTL Implementation of A∗ Path Planning Algorithm

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2021 International Conference on Microelectronics, ICM 2021

作者： Osama, Adham Mostafa, Ahmed Mamdouh, Eslam Gamal, Mohamed Imam, Usama Taha, Mohamed Khalil, Ahmed Ahmed, Islam Mostafa, Hassan Cairo University Electronics and Communication Engineering Department Giza12613 Egypt Siemens EDA IC Verification Solutions Cairo Egypt University of Science and Technology Nanotechnology and Nanoelectronics Program Zewail City of Science and Technology October Gardens 6th of October Giza12578 Egypt

ISBN: (纸本)9781665408394

The conventional A∗ algorithm consumes a lot of time due to its large number of iterations. In every iteration, the memory is accessed for multiple data structures, functions are evaluated then sorted into queues which makes it sometimes not suitable for real-time applications. This paper proposes a fast implementation for the A∗ algorithm to meet requirements of real-time applications. The proposed implementation uses parallelism and caching to achieve better performance. We used Register Transfer Level (RTL) simulation and formal verification to do functional verification of the implemented *** design is implemented on Xilinx Virtex-7 to be evaluated. Experiments prove that this implementation achieves 100 times enhancement for low obstacle maps and 50 times for high ones relative to software implementation. The design is suitable for real-time applications. © 2021 IEEE.

关键词： Formal verification

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Optimization of the Weapon Target Assignment Problem with Metaheuristic Algorithms in the Electronic Warfare Battlefield

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SSRN 2023年

作者： Ozden, Semih Arslan, Elvan Banu National Defence University Alparslan Defence Sciences and National Security Institute Electronic Warfare Program Ankara Turkey National Defence University Turkish Military Academy Department of Electronics and Communication Engineering Ankara Turkey Devlet Mah. Kara Harp Okulu Harp Okulu Cad. Cankaya Ankara Turkey

One of the most critical elements of electronic warfare is the repression, squelching, and suppression of the electronic communication systems of the adversary. Knowing the properties of the systems in the inventory and evaluating them accordingly plays an important role in the success of the jamming process. In this study, it is aimed to find the best jammer positions for suppressing radios operating in the 300 – 500 MHz band, according to the previously determined criteria. In this position finding problem, it is assumed that there is a tactical field where electronic listening is done and the artifacts of the targets are detected. Particle Swarm Optimization (PSO) and Symbiotic Organism Search (SOS) algorithms, which have been used most recently and have many advantages, have been preferred in solving the problem. PSO, which has a simple mathematical calculation advantage, and SOS, which requires a small amount of hyper-parameter, have been tested for this problem. The cost function of the problem is J/S value (Eq. 3) that represents white noise jamming to suppress counterpart communication. According to the results obtained, the effectiveness of suppressants in the positions obtained with SOS was generally higher than the effectiveness of PSO. In some scenarios, even if they had approximately the same suppression efficiency value, the SOS offered a faster solution in each case in terms of computation time. Looking at the results for all scenarios and targets, SOS achieved an average suppression effectiveness of more than 50% compared to PSO. © 2023, The Authors. All rights reserved.

关键词： Particle swarm optimization (PSO)

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A Novel Hybrid Framework for Energy-Efficient Clustering and Routing in Heterogeneous IoT-Driven Wireless Sensor Networks

A Novel Hybrid Framework for Energy-Efficient Clustering and...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Gopal Kumar Gupta Arpit Jain Khemraj Sharma P. M. Ashok Kumar Shubhi Gupta Sheenu Agarwal Symbiosis Institute Of Technology Nagpur Campus Symbiosis International (Deemed University) Pune India Department of Computer Science Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram AP India Department of Business Administration Doctoral Program in Management Sciences NANHUA UNIVERSITY Dalin Chiayi R.O.C Department of Computer Science and Engineering Amity University Greater Noida Uttar Pradesh India Department of Electronics and Communication Engineering Uttarakhand Technical University Dehradun U.K. India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

Smart computing has been particularly notable in the development of wireless sensor networks (WSNs), which have many applications. Battery-powered, self-configuring sensor nodes are the basis of these networks. Energy and resources are limited when it comes to sensors. Unbalanced nodes in the network consume more power, which adversely affects the network’s lifespan. An improved energy-efficient cluster-based routing protocol for heterogeneous wireless sensor networks (WSNs) based on the Internet of Things is proposed in this study. Several performance metrics were used to evaluate the proposed model’s effectiveness, including energy efficiency, alive nodes, dead nodes, network lifetime, and residual energy. The results of the comparison were compared with existing methodologies, such as LEACH, PSO, and hybrid PSO. The proposed approach outperforms the existing model by a substantial margin in networks with 50 and 100 nodes, according to the simulation results.

关键词： Wireless communication Measurement Wireless sensor networks Simulation Heuristic algorithms Routing Energy efficiency Routing protocols Internet of Things Informatics

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Mathematical modelling and optimization of parameters for Al-Si-Fe aluminum alloy reinforced by Al 2 O 3 and graphite particles using Taguchi method

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Materials Today: Proceedings 2021年 44卷 979-986页

作者： Robale Dinsa Daba Devendra Kumar Sinha Habtamu Beri Satyam Shivam Gautam Gulam Mohammed Sayeed Ahmed Ram Sewak Singh Program of Mechanical Design and Manufacturing Engineering School of Mechanical Chemical and Materials Engineering ASTU ADAMA Ethiopia Department of Mechanical Engineering North Eastern Regional Institute of Science and Technology Itanagar India Department of Electronics and Communication School of Electrical Engineering and Computing ASTU ADAMA Ethiopia

In the present scenario the aluminum and its alloys are preferred due to requirement of lightweight high strength material. The present research article interrogates experimentally the study of actual density and porosity using powder metallurgy method. The experimental design is done using Taguchi L 16 orthogonal array. Actual density and porosity has been analyzed based on ‘smaller is best’ basis. Actual density and porosity are calculated using Archimedes principle. The leverage of four levels and five process parameters such as weight percentage of Al 2 O 3 , weight percentage of graphite, compaction pressure, compaction time and milling time are considered. Results reveal that Al 2 O 3 weight percentage has the highest leverage on density followed by compaction time and graphite weight percentage.

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Hot Carrier Injection Reliability of Fabricated N- and P-Type Multi FinFETs with Different TiN Stacks

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ECS Journal of Solid State Science and Technology 2023年第3期12卷 035007-035007页

作者： Chen, Yu-Lin Yeh, Wen-Kuan Hsu, Heng-Tung Chen, Ke-Horng Lin, Wen-Chin Yu, Tien-Han Chou, Hung-Ting Godwin Raj, D. Godfrey, D. International College of Semiconductor Technology National Yang Ming Chiao Tung University Taiwan Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Taiwan National Applied Research Laboratories Taiwan Institute of Microelectronics National Cheng Kung University Taiwan National Chung-Shan Institute of Science and Technology Taoyuan Taiwan Dept of ECE Amal Jyothi College of Engineering Kerala India Dept of Electronics and Communication Engineering Dayananda Sagar University Bengaluru India

Device degradation due to hot carrier injection (HCI) in multi-fin 20 nm and 10 nm N- and P-type FinFET devices are thoroughly analyzed. To further understand the HCI reliability of the four FinFET devices, the device is fabricated with a standard Vt base and low Vt base gate stacks with different work functions. It is evident that: (i) The standard Vt device sustains lower effective stress bias due to the difference in threshold voltage, resulting in a more stable threshold voltage than the low Vt base device, and (ii) the transconductance of the single N- and P-type FinFET is more severely degraded than the multi-fin N- and P-type FinFET, mainly because multi N- and P-type Finfet has coupe effect, which effectively reduces the impact of HCI. © 2023 The Electrochemical Society ("ECS"). Published on behalf of ECS by IOP Publishing Limited

关键词： FinFET

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Deep Learning in Smart Healthcare: A GAN-based Approach for Imbalanced Alzheimer's Disease Classification

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Procedia Computer Science 2024年 241卷 146-153页

作者： Hina Tufail Abdul Ahad Ira Puspitasari Ibraheem Shayea Paulo Jorge Coelho Ivan Miguel Pires Department of Computer Science University of Management and Technology Sialkot Pakistan Information System Study Program Faculty of Science and Technology Universitas Airlangga School of Software Northwestern Polytechnical University Xian Shaanxi P.R. China Department of Electronics and Communication Engineering Istanbul Technical University(ITU) Turkey Polytechnic University of Leiria Leiria Portugal Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra) Coimbra Portugal Instituto de Telecomunicações Escola Superior de Tecnologia e Gestão de Águeda Universidade de Aveiro Águeda Portugal

Alzheimer's disease (AD) is a type of dementia that leads to memory loss and impairment, which afects patients’ lives badly. It is not curable yet, but its progression can be slowed down if detected at earlier stages. In this research study, we propose a transfer learning-based convolutional neural network (CNN) model to classify magnetic resonance imaging (MRI) into one of four stages of Alzheimer's disease. One of the major limitations of the deep learning-based classification model is the non-availability of healthcare datasets related to AD. The widely used Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset has a major class imbalance issue. We propose a generative adversarial network (GAN) based data augmentation technique to overcome the data imbalance. This promotes the investigation of applying GANs to generate synthetic samples for minority classes in Alzheimer's disease datasets to enhance classification performance. The results show the progression in the overall classification process of AD.

关键词： Alzheimer disease (AD) Deep learning Convolutional Neural Network (CNN) Computer-aided diagnosis (CAD)

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Structural, morphological and optical properties of barium doped bismuth ferrite thin films deposited by spray pyrolysis

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Materials Today: Proceedings 2021年 35卷 440-444页

作者： Charishma V. Veena Devi Shastrimath Raghavendra Bairy M.S. Murari A. Jayarama Richard Pinto Department of Electronics and Communication Engineering NMAM Institute of Technology Nitte Karkala 574110 India Department of Physics NMAM Institute of Technology Nitte Karkala 574110 India DST PURSE Program Mangalore University Mangalagangothri 574199 India Department of Physics Alva’s Institute of Engineering and Technology Moodbidri 574225 India Department of Electronics and Communication Engineering Alva’s Institute of Engineering and Technology Moodbidri 574225 India

In the area of material science and technology, fabrication and characterization of nano-materials play an important role since it leads to the development of devices with interesting performance and potential applications in electronics, magnetics, optics, and photonics. Among the materials perovskite materials are gaining prominence. In this investigation, thin films of bismuth ferrite have been prepared and the impact of co–substitution of barium on their structural, morphological and optical properties have been studied. The spray pyrolysis procedure was used to prepare the thin films of bismuth ferrite with medium thickness by doping barium with concentrations of 1%, 3%, 5% and 10%. Various characterization techniques were employed to study the films. The presence of barium, bismuth and iron in the samples was confirmed by EDAX spectra. X-Ray diffraction studies confirmed the polycrystalline nature of the films having a rhombohedrally distorted pervoskite crystal structure fitting to space group R3c. The Scherrer rule was applied to obtain the crystallite size which was found to be small. Surface morphology studies carried out using field emission scanning electron microscopy revealed that the grain size and roughness of the films are modified with increase in doping concentration. The measurement results of optical absorption showed an increase in optical band gap with doping with barium. The results of structural, morphological and optical parameters with the increasing doping concentration indicate that these films are promising candidate for applications in opto-electronics, photovoltaics and gas sensors.

关键词： Morphology Spray pyrolysis Perovskite Optical properties Photoluminescence

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Exploring Regression and Classification in Big Data with Deep Learning

Exploring Regression and Classification in Big Data with Dee...

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International Conference on Power Energy, Environment and Intelligent Control (PEEIC)

作者： Ravindra Pandey Aruna Sri Rongali S. Gopinath Nilesh Anute Forda Nama Sachin Pund Department - Management Hult International Business School Doctoral Information Technology/Information Technology Emphasis/Information Technology University of The Cumberlands US Department of Electronics And Communication Engineering Karpagam Institute of Technology Coimbatore Management ASM's Institute of Business Management and Research Pune Department of Informatics Doctoral Program of Environtmental Science University of Lampung Bandar Lampung Department of Industrial Engineering Shri Ramdeobaba College of Engineering and Management Nagpur Maharashtra India

Deep gaining knowledge is a synthetic intelligence approach used to recognize complex facts. It uses many facts to recognize the complicated relationships between various factors. With deep learning, models can be built which might be capable of understanding the complicated patterns within big datasets. In this paper, we can explore using deep mastering in regression and type tasks on large datasets. In particular, we can use deep learning strategies to build a regression model that predicts a target value primarily based on the functions in a massive dataset and a classification version that can classify an object into one of the many classes of an extensive dataset. We can then discuss the overall performance of the fashions in comparison to standard models and talk about capability areas for development. Moreover, we will analyze the scalability of deep mastering strategies used on large datasets and discuss exceptional practices for building deep mastering fashions on massive datasets. Finally, we will summarize our findings and offer our conclusions approximately the use of deep studying in regression and type obligations on large datasets.

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