检索结果-内蒙古大学图书馆

Editorial: Recent advances in image fusion and quality improvement for cyber-physical systems, volume II

Frontiers in Neurorobotics 2024年 18卷 1422982页

作者： Jin, Xin Lee, Shin-Jye Wozniak, Michal Jiang, Qian School of Software Yunnan University Yunnan Kunming China Department of Systems and Computer Networks Faculty of Information and Communication Technology Wroclaw University of Science and Technology Wroclaw Poland Institute of Management of Technology National Yang Ming Chiao Tung University Hsinchu Taiwan

Multi-source visual information fusion and quality improvement can help the robotic system to perceive the real world. Image fusion is a computational technique fusing multisource images from multiple sensors into a synthesized image that provides a comprehensive or reliable description. Quality improvement techniques can be used to address the challenge of low-quality image analysis tasks [1][2][3][4][5][6]. At present, a lot of brain-inspired algorithm methods (or models) are aggressively proposed to accomplish these two tasks, and the artificial neural network has become one of the most popular techniques in processing image fusion and quality improvement techniques in this decade, especially deep convolutional neural networks [4][5][6][7][8]. This is an exciting research field for the research community of image fusion, and many interesting issues remain to be explored, such as deep few-shot learning, unsupervised learning, application of embodied neural systems, and industrial *** to develop a sound biological neural network and embedded system to extract the multiple features of source images are two key questions that need to be addressed in the fields of image fusion and quality improvement. Hence, studies in this field can be divided into two aspects: new end-to-end neural network models for merging constituent parts during the image fusion process and the embodiment of artificial neural networks for image processing systems. In addition, current booming techniques, including deep neural systems and embodied artificial intelligence systems, are considered potential future trends for reinforcing image fusion performance and quality *** paper of Zhang et al. introduces a palmprint recognition method based on a gating mechanism and adaptive feature fusion. They propose a new network structure, GLGAnet, for extracting local and global features of palmprints. The method incorporates a gating mechanism to control features extracted by dee

关键词： artificial neural networks embedded learning system feature extraction image quality improvement image fusion robot vision

来源：评论

学校读者我要写书评

暂无评论

Effect of Electron Thermal Conductivity on Resonant Plasmonic Detection in Terahertz Hot-Electron Bolometers Based on Metal/Black-AsP/Graphene FETs

引用

Physical Review Applied 2023年第6期19卷 064033-064033页

作者： V. Ryzhii C. Tang T. Otsuji M. Ryzhii V. Mitin M.S. Shur Research Institute of Electrical Communication Tohoku University Sendai 980-8577 Japan Department of Computer Science and Engineering University of Aizu Aizu-Wakamatsu 965-8580 Japan Department of Electrical Engineering University at Buffalo SUNY Buffalo New York 14260 USA Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy New York 12180 USA

We analyze the operation of terahertz (THz) bolometric detectors based on field-effect transistor (FET) structures with graphene channels (GCs) and black-phosphorus and black-arsenic gate barrier layers (BLs). Such GC FETs use two-dimensional electron gas (2DEG) heating by the incident THz radiation leading to the thermionic emission of hot electrons from the GC via the BL into the gate. Due to the excitation of plasmonic oscillations in the GC by THz signals, the GC FET detector response can be pronouncedly resonant, leading to elevated values of the detector responsivity. The lateral thermal conductivity of the 2DEG and its Peltier cooling can markedly affect the GC FET responsivity, in particular its spectral characteristics. These effects should be considered for the optimization of GC FET detectors.

关键词： Optoelectronics Plasmonics Field-effect transistors Graphene Phosphorene Bolometers Terahertz techniques

来源：评论

学校读者我要写书评

暂无评论

COVID-19: Update, Forecast and Assistant-An Interactive Web Portal to Provide Real-Time Information and Forecast COVID-19 Cases in Bangladesh

COVID-19: Update, Forecast and Assistant-An Interactive Web ...

引用

2021 International Conference on Information and communication Technology for Sustainable Development, ICICT4SD 2021

作者： Satu, Md Shahriare Rahman, Md Khalilur Rony, Maksud Alam Shovon, Ahmedur Rahman Adnan, Md Jane Alam Howlader, Koushik Chandra Kaiser, M Shamim Department of Management Information Systems Noakhali Science and Technology University Bangladesh Department of Information and Communication Engineering Noakhali Science and Technology University Bangladesh Department of Computer Science and Telecommunication Noakhali Science and Technology University Bangladesh Institute of Information Technology Jahangirnagar University Bangladesh

ISBN: (纸本)9781665414609

Since December 2019, Novel coronavirus disease has been shown an extensive impact on social, mental, personal, and economic fields throughout the world. In this pandemic situation, people are worried and interested to know what is going on in the upcoming days. Therefore, it is very important to provide relevant information about how many people are affected and will infect in near future. Moreover, they need to know how to spread different symptoms and prevention steps of this disease. Hence, we developed an informative and prediction-based web portal named COVID-19: Update, Forecast and Assistant which provides real-Time information on COVID-19 cases in Bangladesh and worldwide. In this model, we also provide a machine learning-based short-Term forecasting web tool that is used to predict infectious and fatality cases in an upcoming couple of days. Also, we provide precaution steps against coronavirus, emergency contacts of testing, and treatment centers for individuals. © 2021 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Improved Adaptive Fairness-Indexed Technique for Congestion Control in Underwater Networks

Improved Adaptive Fairness-Indexed Technique for Congestion ...

引用

communication, Control and Intelligent systems (CCIS)

作者： Balaji Vijayan V K S Manojee Mohammed Ibrahim M Nivethitha R Thamaraimanalan T Ranjithkumar M Department of Information Science and Engineering HKBK College of Engineering Bengaluru Karnataka India Department of Information Technology Kongunadu College of Engineering and Technology Trichy Tamilnadu India Department of Computer Science and Engineering Sona College of Technology Salem Tamilnadu India Department of Computer Science and Engineering K.S.R. College of Engineering Thiruchengode Tamilnadu India Department of Electronics and Communication Engineering Sri Eshwar College of Engineering Coimbatore Tamilnadu India Department of Computer Science and Business Systems Knowledge Institute of Technology Salem Tamilnadu India

ISBN: (数字)9798331528201

ISBN: (纸本)9798331528218

In underwater acoustic sensor networks (UASNs), effective congestion control is essential for ensuring reliable data transmission and resource efficiency, especially in the face of challenging environmental factors such as water velocity, pressure, temperature, and salinity. This paper introduces a novel Adaptive Fairness-Indexed Congestion Control (AFICC) mechanism that employs Q-learning to dynamically adjust transmission rates among nodes, ensuring equitable resource distribution and minimizing congestion. Our simulations, conducted with 100 nodes at depths of up to 1000 meters, reveal that AFICC significantly outperforms two existing algorithms: Rate-Based Congestion Control (RBCC) and Energy-Aware Congestion Control (EACC). Specifically, AFICC achieved a Packet Delivery Ratio (PDR) of 93%, compared to 85% for RBCC and 80% for EACC. Additionally, the End-to-End Delay was reduced to an average of 150 milliseconds with AFICC, while RBCC and EACC recorded delays of 220 milliseconds and 210 milliseconds, respectively. AFICC also demonstrated a 25% improvement in Energy Efficiency over EACC and maintained a Jain’s Fairness Index of 0.92, surpassing the 0.82 and 0.78 indices achieved by RBCC and EACC, respectively. These results confirm that AFICC offers a robust framework for congestion control in UASNs, effectively adapting to fluctuating underwater conditions while ensuring reliable communication and equitable resource allocation.

关键词： Q-learning Salinity (geophysical) Dynamic scheduling Energy efficiency Delays Temperature control Resource management Reliability Underwater acoustics Water resources

来源：评论

学校读者我要写书评

暂无评论

From Rule-Based Models to Deep Learning Transformers Architectures for Natural Language Processing and Sign Language Translation systems: Survey, Taxonomy and Performance Evaluation

arXiv

引用

arXiv 2024年

作者： Shahin, Nada Ismail, Leila Intelligent Distributed Computing and Systems Lab Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University United Arab Emirates Emirates Center for Mobility Research United Arab Emirates University Abu Dhabi United Arab Emirates

With the growing Deaf and Hard of Hearing population worldwide and the persistent shortage of certified sign language interpreters, there is a pressing need for an efficient, signs-driven, integrated end-to-end translation system, from sign to gloss to text and vice-versa. There has been a wealth of research on machine translations and related reviews. However, there are few works on sign language machine translation considering the particularity of the language being continuous and dynamic. This paper aims to address this void, providing a retrospective analysis of the temporal evolution of sign language machine translation algorithms and a taxonomy of the Transformers architectures, the most used approach in language translation. We also present the requirements of a real-time Quality-of-Service sign language machine translation system underpinned by accurate deep learning algorithms. We propose future research directions for sign language translation *** Codes I.2, I.2.7, I.4, I.4.9 © 2024, CC BY.

关键词： Neural machine translation

来源：评论

学校读者我要写书评

暂无评论

A Fast and Effective Multiple Kernel Clustering Method on Incomplete Data

引用

computers, Materials & Continua 2021年第4期67卷 267-284页

作者： Lingyun Xiang Guohan Zhao Qian Li Gwang-Jun Kim Osama Alfarraj Amr Tolba Changsha Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation School of Computer and Communication EngineeringChangsha University of Science and TechnologyChangsha410114China Hunan Key Laboratory of Smart Roadway and Cooperative Vehicle-Infrastructure Systems Changsha University of Science and TechnologyChangsha410114China Faculty of Engineering and Information Technology Global Big Data Technologies CentreUniversity of Technology SydneyUltimoNSW2007Australia Department of Computer Engineering Chonnam National UniversityGwangju61186Korea Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Department of Mathematics and Computer Science Faculty of ScienceMenoua UniversityShebin-El-kom32511Egyp

Multiple kernel clustering is an unsupervised data analysis method that has been used in various scenarios where data is easy to be collected but hard to be ***,multiple kernel clustering for incomplete data is a critical yet challenging *** the existing absent multiple kernel clustering methods have achieved remarkable performance on this task,they may fail when data has a high value-missing rate,and they may easily fall into a local *** address these problems,in this paper,we propose an absent multiple kernel clustering(AMKC)method on incomplete *** AMKC method rst clusters the initialized incomplete ***,it constructs a new multiple-kernel-based data space,referred to as K-space,from multiple sources to learn kernel combination ***,it seamlessly integrates an incomplete-kernel-imputation objective,a multiple-kernel-learning objective,and a kernel-clustering objective in order to achieve absent multiple kernel *** three stages in this process are carried out simultaneously until the convergence condition is *** on six datasets with various characteristics demonstrate that the kernel imputation and clustering performance of the proposed method is signicantly better than state-of-the-art ***,the proposed method gains fast convergence speed.

关键词： Multiple kernel clustering absent-kernel imputation incomplete data kernel k-means clustering

来源：评论

学校读者我要写书评

暂无评论

Using IoT-Based Mobile Application to Build Smart Parking System

Using IoT-Based Mobile Application to Build Smart Parking Sy...

引用

International Conference on Computing, Engineering, and Design (ICCED)

作者： Zainab S. Attarbashi Tharshaan A-L Thamodharan Mustafa Ali Abuzaraida Saman Iftikhar Noof Abdulaziz Alansari Atikah Balqis Binti Basri Dini Oktarina Dwi Handayani Department of Computer Science Faculty of Information & Communication Technology International Islamic University Malaysia Selangor Malaysia School of Computing Universiti Utara Malaysia Sintok Malaysia Computer Science Department Faculty of Information Technology Misurata University Libya Faculty of Computer Studies Arab Open University Saudi Arabia Department of Information Systems Faculty of Information & Communication Technology International Islamic University Malaysia Selangor Malaysia

The idea of using the current technologies to build more sustainable smart cities has gained great popularity. One of attractive fields is Internet of Things applications to control vehicle traffic and parking which reduce energy consumption in smart cities. This paper presents an android mobile application system that allows users to check the availability and location of parking spots by using their smartphones. Main tools used for this project are the Arduino UNO and mobile application running with Android. Sensors were used to sense if the spot is empty, and then send that info to the mobile application. As the empty place is discovered to be vacant it is distinguished utilizing ultrasonic sensors which report it further. The system would not help the user to book parking spot but would show the availability of parking spot to reduce the searching time. This Smart Parking System is a basic prototype which can be improved later for real system by connecting the system to a GPS-based application which will direct the user to the spot itself and it can further be improved by using artificial intelligence to highlight different spots to different users.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Method for preserving privacy in wearable IoT devices by extending security using fog computing

Method for preserving privacy in wearable IoT devices by ext...

引用

Emerging Trends in Industry 4.0 (ETI 4.0)

作者： P. Sathyaraj Mukesh Singh P. Umaeswari Mahesh Kumar A S Vipul Vekariya Ramya Maranan Department of Electronics and Communication Engineering R.M.K. College of Engineering and Technology Puduvoyal Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Department of Computer Science And Business Systems R.M.K Engineering College Kavaraipettai Thiruvallur Tamil Nadu India Department of Electronics and Communication Engineering PES College of Engineering Mandya Karnataka India Department of Computer Science and Engineering Parul Institute of Engineering and Technology Parul University Gujarat India Department of Research and Innovation Saveetha School of Engineering SIMATS Chennai Tamil Nadu India

ISBN: (数字)9798350373783

ISBN: (纸本)9798350373790

The overarching objective has been achieved through the development of a method enabling the extension of Fog Computing (FC) to facilitate the transport and encryption of sensitive data from wearable devices. The study presents a method leveraging Fog Computing (FC) to transport and encrypt sensitive data from wearable devices, effectively mitigating privacy risks. Through comprehensive tests, NFC emerges as the optimal technology for data transport, while the DHEC algorithm is identified as the best encryption method for securing data between FC and the cloud. Real-world simulations validate the proposed approach, demonstrating its feasibility and effectiveness. The MyNFC app facilitates secure data transmission to AWS, with ServerNFC successfully decrypting data. The AES algorithm exhibited an average CPU usage of 31.8375, with low energy consumption and an average execution time of 26.404 seconds. For the RSA algorithm, the average CPU usage was 33.5875, also with low energy consumption, and an average execution time of 27.8 seconds. The DHEC algorithm showed an average CPU usage of 33.25, with low energy consumption, and an average execution time of 26.711 seconds. Lastly, the HJP algorithm displayed an average CPU usage of 32.375, with low energy consumption, and an average execution time of 30.163 seconds. Overall, the study highlights the ability of FC to safeguard information against interception, endorsing the proposed method’s security and scalability.

关键词： Energy consumption Data privacy Technological innovation Scalability Encryption Internet of Things Data communication

来源：评论

学校读者我要写书评

暂无评论

Modulation Recognition of the OFDM Signals in the UAV-RIS Based AI-enabled 6G Network for Smart Agriculture

Modulation Recognition of the OFDM Signals in the UAV-RIS Ba...

引用

International Bhurban Conference on Applied sciences & Technology, IBCAST

作者： Adil Sheraz Muhammad Farrukh Shahid Zuhaib Ashfaq Khan Tariq Jamil. S. Khanzada Department of Computer Science FAST-NUCES Karachi Pakistan Department of Electronic and Communication Engineering (ECE) School of Architecture Technology and Engineering (ATE) University of Brighton UK Department of Information Systems Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia Computer Systems Engineering Department Mehran UET Jamshoro Pakistan

ISBN: (数字)9798350308259

ISBN: (纸本)9798350308266

The integration of artificial intelligence (AI) and 6G networks aims to enhance agricultural applications by enabling adaptive and efficient communication systems. Fusing the potential and strengths of machine learning (ML) technology and the high-speed, low-latency communication capabilities of 6G networks, we can create intelligent farming systems that can enhance productivity, reduce resource wastage, and ensure sustainable agricultural practices. To tackle resource wastage and power efficiency of 6G-enabled devices, we present an AI-based solution that utilizes pre-trained Deep Learning (DL) models to classify Orthogonal Frequency Division Multiplexing (OFDM) modulated Quadrature Amplitude Modulation (QAM) signals. The proposed approach involves recognizing signals based on the classification results at the receiving nodes, prompting them to switch their radio modulation schemes to options such as 4-QAM, 16-QAM, and 64-QAM. Taking advantage of DL models for QAM classification and dynamically adjusting modulation schemes, the proposed solution can optimize resource utilization, improve data transmission quality, and enhance overall network performance in agricultural applications. We used pre-trained ResNet50, MobileNetV2, and a scratch CNN model. Our results show that pretrained models performed better than scratch CNN models and demonstrate the feasibility of using pretrained DL models for modulation scheme classification, offering promising opportunities for the development of adaptive and intelligent agricultural systems.

关键词： 6G mobile communication Smart agriculture Adaptation models Adaptive systems Quadrature amplitude modulation OFDM Modulation Switches Resource management Residual neural networks

来源：评论

学校读者我要写书评

暂无评论

Security Analysis of Private Intellectual Property

Security Analysis of Private Intellectual Property

引用

2021 International Conference on Engineering Management of communication and Technology, EMCTECH 2021

作者： Dhoot, Anshita Zong, Boyang Saeed, Muhammad Salman Singh, Karan School of Computer & Systems Sciences Jawaharlal Nehru University New Delhi India Department of Computer Science & Technology Qilu University of Technology Shandong China Department of Information & Communication Engineering Islamia University of Bahawalpur Punjab Pakistan

ISBN: (纸本)9781665416115

Intellectual Property Rights (IPR) results from years of research and wisdom by property owners, and it plays an increasingly important role in promoting economic development, technological progress, and cultural prosperity. Thus, we need to strengthen the degree of protection of IPR. However, as internet technology continues to open up the market for IPR, the ease of network operation has led to infringement of IPR in some cases. Intellectual property infringement has occurred in some cases. Also, Internet development's concealed and rapid nature has led to the fact that IPR infringers cannot be easily detected. This paper addresses how to protect the rights and interests of IPR holders in the context of the rapid development of the internet. This paper explains the IPR and proposes an algorithm to enhance security for a better security model to protect IPR. This proposes optimization techniques to detect intruder attacks for securing IPR, by using support vector machines (SVM), it provides better results to secure public and private intellectual data by optimizing technologies. © 2021 IEEE.

关键词： Intellectual property

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：