检索结果-内蒙古大学图书馆

26th International Conference on computer and Information Technology, ICCIT 2023

作者： Bin Habib, Al Zadid Sultan Islam, Md. Ekramul Bin Syed, Md Asif Ahamed, Md Younus Tasnim, Tanpia West Virginia University Lane Department of Computer Science and Electrical Engineering MorgantownWV26506 United States Stamford University Bangladesh Department of Computer Science & Engineering Dhaka1217 Bangladesh West Virginia University Department of Industrial and Management Systems Engineering MorgantownWV26506 United States Green University of Bangladesh Department of Computer Science and Engineering Dhaka1461 Bangladesh

ISBN: (纸本)9798350359015

Pediatric bone age prediction is a crucial task in clinical practice that can help diagnose endocrine disorders and provide insight into a child's growth and development. However, conventional bone age prediction methods are often labor-intensive and require specialized radiological expertise. This paper presents a Deep Learning (DL)-based approach to pediatric bone age prediction using EfficientNet with Additive Attention, a state-of-the-art neural network architecture for image classification and regression tasks. The method utilizes over 12,000 X-ray images from the RSNA bone age dataset. It involves image preprocessing, transforming them into three-channel images, and training a Convolutional Neural Network (CNN) to automatically learn the features of hand bone images. This approach provides a more effective and accurate solution for predicting bone age, which is critical in diagnosing pediatric endocrine diseases. This work uses two variations of the EfficientNet model (B0 and B4), where EfficientNetB4 is also finetuned with the Additive Attention mechanism. These three models predict the age for the original age, and their comparison is shown in curves. The predicted ages depict that in most cases, EfficientNetB4 and EfficientNetB4 with Additive Attention (EN-AA) successfully predicted the bone ages more accurately regarding the original age, and their performance was better than the EfficientNetB0. Specific performance metrics are provided to underscore this improvement. Learning curves for training and validation loss confirm effective learning without overfitting or underfitting, further validating our approach's efficacy in pediatric endocrine disease diagnosis. © 2023 IEEE.

关键词： Additive Attention Deep Learning EfficientNet Image Regression Pediatrics RSNA Bone Age

来源：评论

学校读者我要写书评

暂无评论

Conductive Atomic Force Microscopy to Shed New Light on Surface electrical Trees

Conductive Atomic Force Microscopy to Shed New Light on Surf...

引用

2024 IEEE Conference on electrical Insulation and Dielectric Phenomena, CEIDP 2024

作者： Davis-Amendola, Kerry L. Ortiz-Flores, Luis A. Abu Hurayra Lizu, K.M. Huey, Bryan Cao, Yang Electrical Insulation Research Center Institute of Materials Science University of Connecticut United States Materials Science and Engineering University of Connecticut United States Electrical and Computer Engineering University of Connecticut 25 King Hill Road StorrsCT06268 United States

ISBN: (纸本)9798350366679

Greenhouse gas emission reduction is underway worldwide to mitigate the effects of global warming. Among the new initiatives, electrification of passenger airplanes could yield enormous economic and environmental benefits although a few key technology barriers remain. One main challenge is related to the insulation system. This is because insulation systems required for electric aircraft will need to withstand higher local electric fields and higher temperatures. Unfortunately, all polymeric insulation systems are subject to an aging degradation mechanism called electrical treeing, which can lead to electrical breakdown. The defect is exacerbated in areas of local high field, making it a crucial issue to understand in aircraft insulation. While this mode of tree-aging has been studied for centuries, the mechanism has been debated in the literature. Using new characterization techniques to shed new light on parts of the electrical treeing mechanism is key to new understanding that can lead to mitigation solution. One such new characterization technique is conductive atomic force microscopy (c-AFM). By using a conductive tip on the AFM, the electrical tree can be studied with respect to the electrical conductance of the interior walls and their speculated contribution to electrical tree propagation. This work used c-AFM to study an electrical tree on the surface of an insulation material to establish a baseline procedure in using this technique to study the walls of electrical trees. It was found that the c-AFM can provide conductivity results within and around an electrical tree. © 2024 IEEE.

关键词： Emission control

来源：评论

学校读者我要写书评

暂无评论

RAPUF: A Novel Integration of Reversible Logic and Arbiter Physical Unclonable Functions for Enhancing IoT Security

RAPUF: A Novel Integration of Reversible Logic and Arbiter P...

引用

2024 International Conference on Artificial Intelligence, computer, Data sciences, and Applications, ACDSA 2024

作者： Rizk, Dominick Rizk, Frederic Rizk, Patrick Rizk, Rodrigue The Catholic University of America Dept. of Electrical Engineering and Computer Science WashingtonDC United States University of Louisiana at Lafayette The Center for Advanced Computer Studies LafayetteLA United States University of Quebec at Trois-Rivières Dept. of Mechanical Engineering Drummondville Canada University of South Dakota Dept. of Computer Science VermillionSD United States

ISBN: (纸本)9798350394528

The Internet of Things (IoT) devices' proliferation underscores the critical importance of fortifying nanoscale circuit security against evolving cyber threats. This paper introduces an unprecedented paradigm to enhance IoT security through the synergistic integration of reversible logic gates and Arbiter Physical Unclonable Functions (APUFs). Reversible logic, known for its theoretical efficiency and energy conservation, is coupled with APUFs, leveraging their unique ability to exploit nanoscale manufacturing variations for robust hardware security. The novel integration is specifically tailored to address the distinctive security challenges prevalent in IoT ecosystems. The proposed methodology encompasses designing and implementing a secure nanoscale circuit system, tailored to the resource constraints of IoT devices. Through an exhaustive literature review, we establish the significance of reversible logic and APUFs in the broader context of nanoscale circuit design and IoT security. The experimental results demonstrate not only the feasibility of the integrated approach but also its effectiveness in fortifying IoT devices against unauthorized access and data breaches. This research contributes a fresh perspective to the field of IoT security, presenting a novel solution that combines energy-efficient reversible logic with the intrinsic security features of APUFs. The outcomes of this work hold promise for advancing the security paradigm of IoT devices ensuring their resilience against emerging threats in the ever-evolving landscape of cybersecurity and contributing significantly to the evolving field of quantum-enhanced IoT security. © 2024 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Price-Discrimination Game for Distributed Resource Management in Federated Learning

IEEE Networking Letters

引用

IEEE Networking Letters 2024年第2期6卷 124-128页

作者： Zhang, Han Yang, Halvin Zhang, Guopeng China University of Mining and Technology School of Computer Science and Technology Xuzhou221116 China University College London Department of Electronic and Electrical Engineering LondonWC1E 7JE United Kingdom

In federated learning (FL) systems, the parameter server (PS) and clients form a monopolistic market, where the number of PS is far less than the number of clients. To improve the performance of FL and reduce the cost to incentive clients, this letter suggests distinguishing the pricing of FL services provided by different clients, rather than applying the same pricing to them. The price is differentiated based on the performance improvements brought to FL by clients and their heterogeneity in computing and communication capabilities. To this end, a price-discrimination game (PDG) is formulated to comprehensively address the distributed resource management problems in FL, including multi-objective trade-off, client selection, and incentive mechanism. As the PDG includes a mixed-integer nonlinear programming problem, a distributed semi-heuristic algorithm with low computational complexity and low communication overhead is designed to solve the Nash equilibrium (NE) of the PDG. The simulation result verifies that the NE achieves a good tradeoff between the training loss, training time, and the cost of motivating clients to participate in FL. © 2019 IEEE.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

Hybrid of Distributed Cumulative Histograms and Classification Model for Attack Detection

引用

computer Systems science & engineering 2023年第5期45卷 2235-2247页

作者： Mostafa Nassar Anas M.Ali Walid El-Shafai Adel Saleeb Fathi E.Abd El-Samie Naglaa F.Soliman Hussah Nasser AlEisa Hossam Eldin H.Ahmed Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Alexandria Higher Institute of Engineering&Technology(AIET) AlexandriaEgypt Department of Computer Science Security Engineering LaboratoryPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Traditional security systems are exposed to many various attacks,which represents a major challenge for the spread of the Internet in the *** techniques have been suggested for detecting attacks using machine learning and deep *** significant advantage of deep learning is that it is highly efficient,but it needs a large training time with a lot of ***,in this paper,we present a new feature reduction strategy based on Distributed Cumulative Histograms(DCH)to distinguish between dataset features to locate the most effective *** histograms assess the dataset instance patterns of the applied features to identify the most effective attributes that can significantly impact the classification *** different models for detecting attacks using Convolutional Neural Network(CNN)and Long Short-Term Memory Network(LSTM)are also *** accuracy test of attack detection using the hybrid model was 98.96%on the UNSW-NP15 *** proposed model is compared with wrapper-based and filter-based Feature Selection(FS)*** proposed model reduced classification time and increased detection accuracy.

关键词： Feature selection DCH LSTM CNN security systems

来源：评论

学校读者我要写书评

暂无评论

Prediction of IDC Breast Cancer by the Application of Transfer Learning with an Ensemble Method 2

Prediction of IDC Breast Cancer by the Application of Transf...

引用

2nd International Conference on Information and Communication Technology for Sustainable Development, ICICT4SD 2023

作者： Hossain, M. Iffat Billa, Arefa Karim, Md. Ebtidaul BJIT Ltd. Dhaka Bangladesh Florida State University Department of Electrical and Computer Engineering Tallahassee United States Northeastern University Department of Computer Science Boston United States

ISBN: (纸本)9798350358667

Cancer mainly is the result of uncontrollable changes in genes. Hence breast cancer is a result of the unstoppable growth of breast cells. A common type of breast cancer is Invasive Ductal Carcinoma (IDC) also popular as Infiltrating Carcinoma. Detection of IDC is necessary and precise identification is expected. If the diagnosis is accurate then the patient will be able to get the necessary treatment needed. For the detection of IDC positive or negative, our proposed methodology employs transfer learning by using ResNet-50, Inception V2, and EfficientNet deep learning models with an ensemble method. The dataset used here consisted of 162 whole-mount slide images of Breast Cancer specimens. From that, 277,524 patches of size 50 × 50 were extracted (198,738 IDC negative and 78,786 IDC positive). This dataset contains a huge number of histopathology images and is passed through the models for training, testing, and validation. In the training section, 10-fold cross-validation was used. This method gives better performance than any single method as it uses an ensemble method with all three mentioned models. The accuracy of separate models is compared with the ensemble methods result. Having made the ensemble approach, we got an accuracy of 94.047% which is higher than the models performing separately. Moreover, the other performance parameters also showed improvement in the ensemble approach. With this satisfactory result, this approach can be of great use in detecting IDC breast cancer. © 2023 IEEE.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

A GPGPU-Based Algorithm Acceleration System for ECG Signal Processing 7

A GPGPU-Based Algorithm Acceleration System for ECG Signal P...

引用

7th International Conference on Algorithms, Computing and Artificial Intelligence, ACAI 2024

作者： Huang, Tianyu Wang, Zhijiong Hu, Guannan Pun, Sio Hang Li, Hung Chun Vai, Mang I Science and Technology Research Institute Lingyange Semiconductor Incorporated University of Macau Joint Laboratory of Zhuhai UM Department of Electrical and Computer Engineering China Science and Technology Research Institute Lingyange Semiconductor Incorporated University of Macau Joint Laboratory of Zhuhai UM Lingyange Semiconductor Incorporated Department of Electrical and Computer Engineering China Science and Technology Research Institute Lingyange Semiconductor Incorporated Joint Laboratory of Zhuhai UM Lingyange Semiconductor Incorporated Zhuhai China Institute of Microelectronics Science and Technology Research Institute Lingyange Semiconductor Incorporated University of Macau Joint Laboratory of Zhuhai UM Department of Electrical and Computer Engineering China

ISBN: (纸本)9798331529314

Electrocardiogram (ECG) is an important non-invasive technique for diagnosing cardiovascular diseases (CVD). After acquiring the patients' raw ECG signal data, signal processing is essential for the diagnosis. Conventional ECG signal processing is usually performed serially, which takes a long time to process signals with large amounts of data. In this study, we have proposed a GPGPU-based algorithm acceleration system to improve the efficiency of ECG signal processing. This system utilizes OpenCL for parallel algorithm development on GPGPU. GPGPU executes certain steps in the QRS complex detection algorithm via parallel computing, thereby accelerating the algorithmic process. Experimental results showed that the system achieved a speedup of 1.279 compared to serial computing when processing 39 ECG signal sequences in parallel. In addition, our system has been equipped with a progressive transmission mechanism and a function that intelligently determines whether an algorithm can be accelerated. These features make this system practical not only in biomedical signal processing but also in engineering and research fields with large amounts of data. © 2024 IEEE.

关键词： Noninvasive medical procedures

来源：评论

学校读者我要写书评

暂无评论

Design of Intelligent Solar Cooling System with IoT Monitoring 3rd

Design of Intelligent Solar Cooling System with IoT Monitori...

引用

3rd International Conference on Emerging Electronics and Automation, E2A 2023

作者： Kushagra, C. Kirtimaan, S. Rushit, P. Jane Joshita, K. Divya Navamani, J. Lavanya, A. Department of Computer Science Engineering SRM Institute of Science and Technology Tamil Nadu Kattankulathur India Department of Electronics and Instrumentation Engineering SRM Institute of Science and Technology Tamil Nadu Kattankulathur India Department of Electrical and Electronics Engineering SRM Institute of Science and Technology Tamil Nadu Kattankulathur India

ISBN: (纸本)9789819730896

Currently, IoT rules many unmanned applications to improve supervision and productivity. The proposed work concentrates on the need for a cooling system for solar Photovoltaic (PV) panels to enhance its efficiency. An increase in temperature will reduce the efficiency of the solar panel. The cooling system should be monitored, automated, and controlled without human intervention. This is achieved by developing a web App by which the cooling system can be controlled automatically. DHT11–Temperature and Humidity Sensor is used to monitor the temperature of the panel. If the module temperature increases more than 35 °C to 60 °C, the sensor sends the signal to the actuator to cool the PV panel, which will increase the output power. This technique is proposed for solar rooftop home applications where the grey water can be treated and used for cooling the solar panel rather than using fresh, clean water. Finally, a web-interface is done to cool the solar panel with water pumping through the tubes below the panel. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Cooling IoT Solar Temperature Web interface

来源：评论

学校读者我要写书评

暂无评论

Exploring the concept of multi-modality using grounding dino with evaluation of its performance in the context of different types and complexity of input text prompts

Exploring the concept of multi-modality using grounding dino...

引用

2024 International Conference on Smart Devices, ICSD 2024

作者： Rahim, Abdul Singh, Amanjot Sharma, Ankur Garg, Rachit Ravisankar, Ch Yamsani, Nagendar Malla Reddy Engineering College for Women Department of ECE Hyderabad India Lovely Professional University School of Electronics and Electrical Engineering Punjab Phagwara India Institute of Technology and Science Mohan Nagar Ghaziabad India Lovely Professional University School of Computer Science and Engineering Punjab Phagwara India SR University School of Computer Science and Artificial Intelligence Warangal India

ISBN: (纸本)9798350394412

We have known artificial intelligence, deep learning models can be trained with a certain type of input format to perform a task e.g., OCR models takes input in the form of image to read the text characters from the image, a weather prediction model can take weather data like wind speed, moisture, etc. as an input which is in text format to predict future weather data. But the multi-modality concept which is comparatively newer in the market paves the way for models to be built which can take more than one type of inputs e.g., text and audio, text and image, etc. In the same concept one of the popular architectures is specially designed for detection of any hindrance, model grounding dino about which we will be discussing in this setting. It is a zero-shot object detection model which can perform inference just by taking a text prompt input from the user describing what they want the model to detect in the provided image. In this study, we will be discussing about its capabilities, architecture and also its performance. We will be testing and quantifying its performance using standard self-created input text prompts with variations including description of the object, complexity of the object, etc. on a standard image. © 2024 IEEE.

关键词： Zero-shot learning

来源：评论

学校读者我要写书评

暂无评论

Low-Cost Hardware Platform for Testing ML-Based Edge Power Grid Oscillation Detectors 10

Low-Cost Hardware Platform for Testing ML-Based Edge Power G...

引用

10th Workshop on Modelling and Simulation of Cyber-Physical Energy Systems, MSCPES 2022

作者： Dorado-Rojas, Sergio A. Xu, Shunyao Vanfretti, Luigi Olvera, Galilea Ayachi, M. Ilies I. Ahmed, Shehab Rensselaer Polytechnic Institute Electrical Computer and Systems Engineering Troy United States King Abdullah University of Science and Technology Electrical and Computer Engineering Thuwal Saudi Arabia

ISBN: (纸本)9781665468657

This paper introduces a low-cost hardware testing platform designed to investigate the performance of a Machine Learning (ML)-based edge application developed to detect forced oscillations in power grids. The core of the ML application lies in a Convolutional Neural Network (CNN) model deployed on an ML edge device (NVIDIA Jetson TX2). The proposed platform consists of a method for real-time signal emulation using the WaveForms Software Development Kit (SDK) that defines low-voltage signals generated by Digilent's Analog Discovery Board. The output of the signal generator is read by the Jetson board using an Analog-to-Digital Converter (ADC). Our experiments compare the performance of different ADCs when performing inference with the same CNN model. Additionally, we give an overview of the communication scheme that allows experiment automation, which is particularly useful when experiment design is time-consuming and laborious. © 2022 IEEE.

关键词： Data acquisition

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：