检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Gil, Sinhué García Díaz, Luis Llana Jarabo, José Ignacio Requeno Dept. of Information Systems and Computing Faculty of Computer Engineering Complutense University of Madrid Madrid Spain

Quantum computing has been on the rise in recent years, evidenced by a surge in publications on quantum software engineering and testing. Progress in quantum hardware has also been notable, with the introduction of impressive systems like Condor boasting 1121 qubits, and IBM Quantum System Two, which employs three 133-qubit Heron processors. As this technology edges closer to practical application, ensuring the efficacy of our software becomes imperative. Mutation testing, a well-established technique in classical computing, emerges as a valuable approach in this context. In our paper, we aim to introduce QCRMut, a mutation tool tailored for quantum programs, leveraging the inherent Quantum Circuit structure. We propose a randomised approach compared to previous works with exhaustive creation processes and the capability for marking immutable positions within the circuit. These features facilitate the preservation of program structure, which is crucial for future applications such as metamorphic testing. © 2024, CC BY-NC-SA.

关键词： Application programs

来源：评论

学校读者我要写书评

暂无评论

Passing Practice Support for Soccer Players Using First-Person Videos

Passing Practice Support for Soccer Players Using First-Pers...

引用

International Symposium on Soft Computing and Intelligent systems (SCIS)

作者： Nobuyuki Umezu Yuya Imada Dept. of Computer and Information Sciences Ibaraki University Hitachi Japan Dept. of Mechanical Systems Engineering Ibaraki University Hitachi Japan

ISBN: (数字)9798350373332

ISBN: (纸本)9798350373349

We propose a novel visualization system to enhance soccer passing practice by providing potential pass courses and their scores. The proposed system is based on a first-person video footage captured during soccer play and extracts frames for pass-course suggestions using the rate of ground-surface pixels in the frame and dept. estimation. Possible pass courses were scored according to their direction and distance to the closest player. To validate the proposed method's effectiveness, we conducted a series of experiments involving 17 participants, comprising 12 museum visitors and five university students. The estimated score of visualized pass courses using the proposed method was generally successful, whereas some pass courses received lower scores from participants owing to limitations in the system's ability to accurately detect the color of players' uniforms, which affected the overall evaluation of certain passing options.

关键词： Visualization Color Museums Sports

来源：评论

学校读者我要写书评

暂无评论

Transformer-Based Ensemble Model for Binary and Multiclass Oral Cancer Segmentation

Transformer-Based Ensemble Model for Binary and Multiclass O...

引用

International Conference on Electrical, computer and Communication engineering (ECCE)

作者： Amira Hossain Anamul Sakib Al Shahriar Uddin Khondakar Pranta Jesika Debnath Md Tanvir Rahman Tarafder Sazzadul Islam Shamim Forhad Md. Redwan Ahmed Rezaul Haque Shafiur Rahman Dept. of Computer Science Westcliff University Irvine CA USA Dept. of Business Administration International American University CA USA Dept. of Computer Science Wright State University Dayton OH USA Dept. of Information Technology Westcliff University Irvine California Dept. of Computer Science and Engineering BRAC University Dhaka Bangladesh Dept. of Electrical and Electronics Engineering American International University Bangladesh Dept. of Computer Science and Engineering East West University Dhaka Bangladesh Dept. of Software Engineering Daffodil International University Dhaka Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

Early and accurate segmentation of oral cancer is essential for timely diagnosis and treatment. Traditional methods like visual inspections and biopsies are often subjective and costly, which can hinder early detection. To improve segmentation accuracy for binary and multiclass classification, we propose a transformer-based ensemble model that combines Vision Transformer (ViT), Data-efficient Image Transformer (DeiT), Swin Transformer, and BEiT. This ensemble utilizes self-attention mechanisms for better feature extraction and spatial representation. Our study employs two datasets: the MOD dataset (463 images of oral diseases) and a histopathological dataset (1,224 images of oral squamous cell carcinoma and normal epithelium). We applied extensive preprocessing and augmentation techniques, such as grayscale conversion, binary thresholding, and Contrast Limited Adaptive Histogram Equalization (CLAHE), to enhance image quality and model generalization. The performance evaluation showed that our ensemble model outperformed individual architectures, achieving an Intersection over Union (IoU) of 0.9601 and a Dice Coefficient of 0.9598 for binary segmentation, and IoU of 0.9587 and Dice Coefficient of 0.9575 for multiclass segmentation. A comparative analysis with state-of-the-art models confirmed the effectiveness of our approach. These results demonstrate the potential of transformer-based ensemble learning for oral cancer diagnosis, presenting a scalable tool for clinical applications. Future work will focus on expanding dataset diversity, optimizing computational efficiency, and integrating real-time inference for improved usability in healthcare.

关键词： Image segmentation computer vision Adaptation models Visualization Accuracy Computational modeling Transformers Cancer detection Real-time systems Cancer

来源：评论

学校读者我要写书评

暂无评论

Classification of Subtypes of Acute Lymphoblastic Leukemia Using Feature Fusion from Blood Smear Images

Classification of Subtypes of Acute Lymphoblastic Leukemia U...

引用

Computational Intelligence Approaches and Applications (ICCIAA), International Conference on

作者： Ghazala Alhadi Eljadi Ahmed Lawgali Salwa Elakeili dept. Computer Sciences Faculty of Information Technology University of Benghazi Beghazi Libya dept. Software Engineering Faculty of Information Technology University of Benghazi Beghazi Libya

ISBN: (数字)9798331523657

ISBN: (纸本)9798331523664

Early detection of Acute Lymphoblastic Leukemia (ALL) is vital for providing appropriate treatment, which requires accurate diagnosis to identify the types of the disease. Therefore, this study focuses on evaluating the performance of deep learning models in classifying different types of leukemia using three pre-trained CNN models: MobileNet V2, DenseNet201, and EfficientNet, to extract deep features. These features are then combined into a single set. An information exchange technique was used to select the best features after merging, and SMOTEENN was employed to address feature imbalance. The results showed that combining features extracted by the pre-trained CNN models achieved high accuracy and reliability, reaching 99.66%, enhancing the performance in accurately and quickly classifying patients. This approach not only improves diagnostic accuracy but also contributes to accelerating the decision-making process for treatment, enabling doctors to better tailor therapies and thereby improve patient outcomes. The findings underscore the importance of ongoing research in this field and provide future recommendations for enhancing performance and increasing classification accuracy in similar medical applications.

关键词： Support vector machines Accuracy Merging Leukemia Medical treatment Feature extraction Convolutional neural networks Reliability Blood Medical diagnostic imaging

来源：评论

学校读者我要写书评

暂无评论

Email Armour: A Multi-Layered Email Defense Solution

Email Armour: A Multi-Layered Email Defense Solution

引用

International Conference on Information Technology Research (ICITR)

作者： K.T.A.U Lakmal L.M.C Perera S.P.K Padmika S.P.A De Silva Dinithi Pandithage Deemantha Siriwardana Dept. computer systems engineering Sri Lanka institute of information technology Malabe Sri Lanka

ISBN: (数字)9798331511425

ISBN: (纸本)9798331511432

Phishing and spam emails are evolving threats in today's digital landscape, posing significant risks to small and medium-sized businesses (SMBs). Despite the growing demand for email security solutions, SMBs often face barriers such as high costs and complexity. To address this gap, this study introduces a cost-effective, multi-layered email security solution leveraging machine learning. The proposed system comprises four core components: (1) spam detection using natural language processing (NLP) to analyze email content, (2) phishing URL and QR code detection by identifying malicious patterns and attributes, (3) attachment security analysis to detect malware and harmful scripts, and (4) suspicious URL detection focusing on JavaScript obfuscation. The model was trained and validated on publicly available datasets, achieving an overall accuracy of 85% and demonstrating effectiveness in identifying diverse email threats. Designed as an email client, this tool empowers SMBs to secure communication with an accessible and robust defense against email-based attacks

关键词： Uniform resource locators Unsolicited e-mail Phishing Focusing Machine learning QR codes Natural language processing Malware Security Information technology

来源：评论

学校读者我要写书评

暂无评论

Dantalion: Digital Twinning the Computing Continuum

Dantalion: Digital Twinning the Computing Continuum

引用

2023 IEEE Globecom Workshops, GC Wkshps 2023

作者： Laso, Sergio Martín, Luis Herrera, Juan Luis Galán-Jiménez, Jaime Berrocal, Javier Murillo, Juan M. Cáceres Spain University of Extremadura Dept. of Computer Systems and Telematics Engineering Spain University of Bologna Dipartamento di Informatica Scienza e Ingegneria Italy Cáceres Spain

ISBN: (纸本)9798350370218

Thanks to the Internet of Things (IoT) paradigm, it is now possible to develop computer applications that automate real, intensive processes, by processing sensor information using techniques such as artificial intelligence or computer vision. Nonetheless, due to the criticality of the processes they automate, intensive IoT applications have very strict Quality of Service (QoS) requirements to function properly, motivating their deployment throughout the Computing Continuum to optimize the obtained QoS. Evaluating and guaranteeing the QoS of this application can be a challenging endeavor, as current QoS evaluation tools are unable to predict future changes to the real world, evaluate multiple adaption alternatives, or act accordingly. To fulfill these needs, in this paper, we present the evolution of a Computing Continuum emulator towards Dantalion, a complete Digital Twin for the Computing Continuum. © 2023 IEEE.

关键词： Computing Continuum Digital Twin In-ternet of Things Quality of Service

来源：评论

学校读者我要写书评

暂无评论

Saw-YOLOv5: Scale-Aware YOLOv5 for Object Detection in Aerial Images 5

Saw-YOLOv5: Scale-Aware YOLOv5 for Object Detection in Aeria...

引用

5th International Congress on Human-computer Interaction, Optimization and Robotic Applications, HORA 2023

作者： Doruk, Abdullah Enes Algul, Mucteba Akyurek, Feyzullah Alpaydm, Osman Kursat Uslu, Fatmatulzehra Zyeǧin University Dept. of Artificial Intelligence Eng. Istanbul Turkey Yildiz Technical University Dept. of Electronics and Communication Eng. Istanbul Turkey Bursa Technical University Dept. of Electrical and Electronics Eng. Bursa Turkey Yildiz Technical University Dept. of Smart Transportation Systems Eng. Istanbul Turkey Department of Software Engineering Faculty of Engineering and Natural Sciences Gumushane University Trabzon Trabzon Turkey

ISBN: (纸本)9798350337525

The detection of objects in aerial images is impor-tant for many real world problems related to military defense, transportation, and etc. However, this is a challenging task as a result of the presence of various scales of objects in the same image, the large variety of contexts across aerial images, various brightness levels due to image acquisition at different times of the day and so on. To address these challenges, this paper introduces Saw-YOLOv5 for object detection in aerial images. Saw-YOLOv5 is a deep network based on YOLOv5, which was proposed for object detection in natural images. Saw-YOLOv5 extends YOLOv5 with the addition of several attention modules in its design. The results of our experiments, conducted on the aerial dataset delivered by the Turkey Technology Team for the Artificial Intelligence in Transportation Competition, showed that Saw-YOLOv5 outperforms previous methods, particularly for pedestrian detection, by yielding a mean mAP of 80.23% over all objects. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based Energy Efficiency Maximization in Massive MIMO-NOMA Networks With Multiple RISs

Deep Learning-Based Energy Efficiency Maximization in Massiv...

引用

International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Ridho Hendra Yoga Perdana Toan-Van Nguyen Yushintia Pramitarini Beongku An Dept. of Software and Communications Engineering in Graduate School Hongik University Republic of Korea Department of Electrical and Computer Engineering San Diego State University San Diego CA USA Dept. of Software and Communications Engineering Hongik University Republic of Korea

In this paper, we study a deep learning (DL)-based energy efficiency maximization (EEM) problem in massive multiple-input multiple-output (MIMO)-non-orthogonal multiple access (NOMA) networks with multiple reconfigurable intelligent surfaces (RISs). These RISs are deployed randomly at the edge of the near radius to assist the base station (BS) in communicating with near and far users. We formulate the problem of jointly optimizing the precoding matrix and phase shift of the RISs to maximize the overall energy efficiency subject to the quality-of-service of each user, phase shift of RISs, and power budget of the BS constraints. To address this challenging non-convex problem with mixed-integer constraints, the original problem is decoupled into phase shift and beamforming sub-problems, then addressed them separately. We introduce the bisection search algorithm to address the challenge of the phase shifts optimization problem. For the beamforming optimization, it is transformed into an equivalent non-convex problem but with a more tractable form. Then, we propose an iterative algorithm based on the inner approximation method for its solution. To support real-time optimization, we design a deep learning framework to predict optimal solutions of phase shifts at RISs and precoding matrix under different parameter settings. Simulation results show that the proposed DL-based approach can predict the optimal solution with high accuracy in a short time compared to the conventional approach. Additionally, the effect of the maximum power budget at the base station, the number of RISs, and BS's antennas are evaluated thoroughly.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Wide-Band Signal Generation Using Egyptian Fractions and Application to Instantaneous Impedance Measurements

引用

IEEE Sensors Journal 2025年第11期25卷 19555-19562页

作者： Majzoub, Sohaib Allagui, Anis Elwakil, Ahmed S. Zhang, Di University of Sharjah Depts. of Electrical Eng. and Computer Eng PO Box 27272 Sharjah United Arab Emirates University of Sharjah Dept. of Sustainable and Renewable Energy Eng PO Box Sharjah27272 United Arab Emirates Florida International University Dept. of Mechanical and Materials Eng MiamiFL33174 United States University of Sharjah Dept. of Electrical Eng P.O. Box 27272 Sharjah United Arab Emirates Nile University Nanoelectronics Integrated Systems Center Cairo Egypt University of Calgary Dept. of Electrical and Software Eng AB Canada

In this work, we investigate the use of Egyptian fractions to construct wide-band signals with a near-flat power spectrum. In particular, it is well-known that wide-band signals can be obtained by using composite multi-sine signals. However, the choice of the frequencies and/or phase shifts in these sinusoids is critical in order to approach a flat power spectrum with a low crest factor. A number of known methods, such as using Rudin-Shapiro polynomials or random phases, have been employed in this problem. However, the use of Egyptian fractions has not been explored yet;despite being easier to generate and implement. Here, we construct multi-sine signals (in the form of a voltage) based on different Egyptian fraction sequences and use them to measure the linear time-invariant impedance of an RC circuit and then the instantaneous impedance of nonlinear time-varying solar cell. Two methods are used to generate these signals: (i) the Egyptian fraction sequences are assigned to the phase angles or (ii) they are used to set the values of the angular frequencies. The accuracy of measurements is assessed via comparison with the standard sine-sweep method using a research-grade Biologic VSP-300 electrochemical station showing acceptable results. © 2001-2012 IEEE.

关键词： Sheet resistance

来源：评论

学校读者我要写书评

暂无评论

A Study on a Personalized Robot Golf Trainer System with Multi-Persona and Ethical Guidelines for Robots

A Study on a Personalized Robot Golf Trainer System with Mul...

引用

International Conference on Electronics, Information and Communications (ICEIC)

作者： Younglim Choi BoJeong Park JongWoo Kim SeoYeong Mun Hyunseok Kim dept. of Software Innovation Center Dong-A University Busan South Korea dept. of Electronic Engineering Dong-A University Busan South Korea dept. of Mechanical Engineering Dong-A University Busan South Korea dept. of Computer Engineering Dong-A University Busan South Korea

ISBN: (数字)9798331510756

ISBN: (纸本)9798331510763

This paper proposes a multi-persona and robot ethics system for a personalized robot golf trainer. The system combines a wheeled mobile robot without arms and GolfPoseNet for analyzing golf postures and integrates a MediaPipe Pose-based user command recognition system to enhance the golf learning experience. To improve the learning process for users of all ages, the system incorporates a multipersona approach. It features custom training designed according to the Robot Service Personality (RSP) model developed by the author, with interaction styles tailored to each service personality type. Additionally, the system optimizes feedback style and training speed based on each user's preferences and learning style, resulting in a highly personalized experience. In an outdoor golf setting, the system aims to support efficient learning by utilizing both an external camera and the robot's camera for accurate posture analysis, offering real-time feedback. Furthermore, by integrating robot ethics, the system ensures user privacy and safety while fostering trust in AI robots. This study provides foundational insights into the potential for personalized AI service robot development in golf posture analysis and human-robot interaction, serving as groundwork for future system advancements.

关键词： Training Ethics Service robots Robot vision systems Human-robot interaction Manipulators Cameras Mobile robots Artificial intelligence Robots

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：