检索结果-内蒙古大学图书馆

International Conference on Inventive Computation Technologies (ICICT)

作者： J. Seetha Senthil Kumar S Nruthya K Nynalasetti Kondala Kameswara Rao D. Leela Rani Department of Computer science and Business Systems Panimalar Engineering College Chennai India Department of Mechanical Engineering R.M.K College of Engineering and Technology Thiruvallur India Department of Civil Engineering Indian Institute of Science Bengaluru India Department of Computer Science and Engineering Sagi Rama Krishnam Raju Engineering College Bhimavaram India Department of Electronics and Communication Sree Vidyanikethan Engineering College Tirupati India

The utilisation of sensor networks in agriculture monitoring is the invention that benefits Indians the most. Given that agriculture is the primary source of revenue, it is essential to boost production while decreasing expenses, inputs of time, and labour. Information gathered from agricultural areas is stored in a database, which may be monitored via the Internet of Things (IoT). Connecting Raspberry Pi with IoT and sensors to increase agricultural activity productivity is the challenging task in the Farm Management System for secure agriculture. Temperature, humidity, soil moisture content, and any field fires are tracked as a challenge's outcome. Specifications like temperature, moisture content, and fire are currently detected manually in farm systems. This technique automates the completion of watering. It used to lighten the workload for farmers. Any type of crop productivity is feasible. This method's drawbacks include an increase in labour costs, increased time requirements, and the inability to do continuous monitoring.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Automated Colorectal Polyps Detection from Endoscopic Images using MultiResUNet Framework with Attention Guided Segmentation

引用

Human-Centric Intelligent systems 2024年第2期4卷 299-315页

作者： Ahamed, Md. Faysal Islam, Md. Rabiul Nahiduzzaman, Md. Chowdhury, Muhammad E. H. Alqahtani, Abdulrahman Murugappan, M. Department of Computer Science & Engineering Rajshahi University of Engineering & Technology Rajshahi Bangladesh Department of Electrical & Computer Engineering Rajshahi University of Engineering & Technology Rajshahi Bangladesh Department of Electrical Engineering Qatar University Doha Qatar Department of Biomedical Technology College of Applied Medical Sciences Al-Kharj Prince Sattam Bin Abdulaziz University Al-Kharj Saudi Arabia Department of Medical Equipment Technology College of Applied Medical Science Majmaah University Majmaah City Saudi Arabia Intelligent Signal Processing (ISP) Research Lab Department of Electronics and Communication Engineering Kuwait College of Science and Technology Doha Kuwait Department of Electronics and Communication Engineering Vels Institute of Sciences Technology and Advanced Studies Chennai India DCenter for Unmanned Autonomous Systems (CoEUAS) Universiti Malaysia Perlis Perlis Malaysia

The early detection of colorectal polyps is crucial for the reduction of mortality rates. However, manually identifying polyps is time-consuming and expensive, increasing the risk of missing them. Our paper aims to address this issue by presenting an automated segmentation approach for colorectal polyps. This paper proposes a method that combines a skip connection with hybrid attention guidance (AG) using attention guidance (AG) and residual path frameworks to identify salient features. Furthermore, we augment test samples using original, horizontal flip, and vertical flip transformations to enhance model robustness through Test Time Augmentation (TTA). The model was trained with Kvasir-seg samples and evaluated on Kvasir-seg and CVC-ClinicDB datasets to gauge generalizability. A significant accuracy (0.9546), a Dice Similarity Coefficient (DSC) of 0.8557, a Cross-section over Union (IoU) of 0.8824, a Recall (0.8221), a Precision (0.8922), an area under Receiver Operating Characteristics (ROC-AUC) of 0.9454, and an area under Precision-Recall (AUC-PR) of 0.8717 were achieved without TTA. Through TTA integration, accuracy (0.9993), DSC (0.8663), IoU (0.8277), Recall (0.8060), Precision (0.9364), and ROC-AUC (0.9587) have been improved. A comparison of our framework with state-of-the-art models demonstrated its effectiveness and segmentation capabilities. Additionally, the proposed model contains only 0.47 million parameters and a weight size of 6.71 MB, illustrating its potential for clinical diagnostics. A computer-aided diagnosis (CAD) system improves patient outcomes by detecting colorectal polyps early and improving segmentation accuracy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Optimizing Controller Tuning using Bio-Inspired Algorithms for Robot Path Tracking 3

Optimizing Controller Tuning using Bio-Inspired Algorithms f...

引用

3rd International Conference on Sentiment Analysis and Deep Learning, ICSADL 2024

作者： Rani, Taneti Lilly Deepa, S. Joon, Rakesh Kumar Jayaseelan, P. Soudagar, Manzoore Elahi M. Dhanraj, Joshuva Arockia Jawaharlal Nehru Technological University College of Engineering Kakinada University College of Engineering in JNTU Department of Civil Engineering Andhra Pradesh Kakinada533003 India RMD Engineering College Department of Computer Science and Business Systems Tamil Nadu Kavarapettai601206 India Ganga Institute of Technology and Management Department of Electronics and Communication Engineering Haryana Kablana124104 India Achariya College of Engineering Technology Department of Mechanical Engineering Puducherry605110 India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of VLSI Microelectronics Tamil Nadu Chennai602105 India Chandigarh University Punjab Mohali140413 India

ISBN: (纸本)9798350396157

In the field of industrial and commercial robotics, there has been a recent boom in research towards the navigation of wheel-based mobile robots. There are numerous aspects of this complex problem that need fixing, including issues with sensory data gathering and processing, trajectory planning, and controlling motion. In the field of motion control, creating reliable trajectory controllers is the highest priority. This study improves the Proportional-Integral-Derivative (PID) controller using Ant Colony Optimization (ACO) and Cat Swarm Optimization (CSO) to get the best possible trajectory tracking. The kinematics of a two-wheeled mobile robot serve as the foundation for its mathematical model. The user-specified reference trajectory is given to the robot. The conventional PID, ACO-PID, and CSO-PID controller's trajectory tracking capacity are evaluated using the metrics. The performance metrics such as the Integral of Squared Error (ISE), Integral of Absolute Error (IAE), and Integral of Time-weighted Absolute Error (ITAE) are taken. According to the simulation results, the CSO-PID controller beats the conventional PID and ACO-PID controllers in terms of error metrics. This discovery highlights the effectiveness of using CSO-PID to improve the trajectory-Tracking performance of mobile robots. © 2024 IEEE.

关键词： Three term control systems

来源：评论

学校读者我要写书评

暂无评论

Development of an Artificial Intelligence-based Prediction System for Short-term Solar Power Generation

Development of an Artificial Intelligence-based Prediction S...

引用

2025 IEEE International Conference on Consumer Electronics, ICCE 2025

作者： Kang, Minseok Choi, Suhyeon Kim, Woohyun Kim, Jaehyeon Cho, Seokheon Department of Computer Science Yonsei University Seoul Korea Republic of Department of Management Information Systems Kyonggi University Suwon Korea Republic of Department of Information and Communication Chosun University Gwangju Korea Republic of Department of Business Chosun University Gwangju Korea Republic of Qualcomm Institute University of California La Jolla San Diego United States

ISBN: (纸本)9798331521165

The increased occurrence of extreme weather events is closely related to global warming caused by excessive fossil fuel consumption. This has resulted in significant global interest in renewable energy sources, especially solar power, which is showing rapid growth worldwide. However, the excessive and disorganized utilization of solar power systems can cause instability of the existing power system because of a continuous time varying output of solar power systems. Hence, it is crucial to accurately predict the solar power generation for a stable energy supply to the traditional electricity system. This study aims to provide a short-term solar power generation prediction model based on various Artificial Intelligence algorithms and improve its performance. The Multiple Linear Regression, Random Forest Regression, Multi-Layer Perceptron and Long Short-Term Memory algorithms were utilized for a solar power generation prediction model. Also, solar power-related data measured every 15 minutes and hourly meteorological data were used to train and evaluate our proposed prediction models. Several datasets generated by the feature selection process and the addition of the historical solar power-related data as well as the historical weather data were used to enhance a short-term solar power generation prediction model. The comparison of performance results showed that the Multi-Layer Perceptron algorithm-based prediction model using the solar power-related data and the weather data as well as their past data outperforms by achieving the highest value of R-squared (R2) but the lowest value of the Root Mean Squared Error. An architecture of an Artificial Intelligence-based solar power prediction system embedded with this optimal short-term solar power prediction model is proposed. © 2025 IEEE.

关键词： Solar fuels

来源：评论

学校读者我要写书评

暂无评论

Cloud Computing based Smart Traffic Management System with Priority Switching for Health Care Services

Cloud Computing based Smart Traffic Management System with P...

引用

Applied Artificial Intelligence and Computing (ICAAIC), International Conference on

作者： X.S. Asha Shiny D. Ravikumar A. Chinnasamy S. Hemavathi Department of Computer Science and Engineering Nalla Malla Reddy Engineering College (Autonomous Institution) Hyderabad Telangana India Department of Electronics and Communication Engineering Kings Engineering College Chennai Tamil Nadu India Department of Data Science and Business Systems School of Computing SRM Institute of Science and Technology Chennai Tamil Nadu India Department of Computer Science Engineering Sri Sairam Engineering College Chennai Tamil Nadu India

Regular cities can be transformed into intelligent structures by leveraging information and communication technologies. Innovative city development could be significantly impacted by the Internet of Things paradigm, commonly called cloud computing. All urban locations have a lot of traffic. In this study, Internet-of- Things (IoT) based system is proposed for health care services to organize and to establish the traffic signaling and pick up a route under which road congestion can be administrated. Vehicle accident contraventions are identified by the traffic officers using an online service that is hierarchically carefully monitored or constrained. However, the suggested approach is generic and may be utilized in any major metropolis without losing its generality. Traffic lights linked to cameras in metropolitan areas can be upgraded by connecting to IoT. During a pandemic, this approach is precious. The police can easily regulate traffic from their homes using their cell phones and identify defaulters. The suggested technique aids in the separation of ambulance and rescue engines from ordinary traffic.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A New Look for Outage and Ergodic Improvements in Coordinated IoT Paradigms with Hybrid Multiple Access

引用

IEEE Transactions on Vehicular Technology 2025年

作者： Vu, Thai-Hoc Le, Anh-Tu Huynh-The, Thien da Costa, Daniel Benevides Kim, Sunghwan Kyonggi University School of Electronic Engineering Korea Republic of VSB-Technical University of Ostrava Faculty of Electrical Engineering and Computer Science 17. Listopadu 2172/15 Ostrava708 00 Czech Republic Ho Chi Minh City University of Technology and Education Department of Computer and Communications Engineering Viet Nam Interdisciplinary Research Center for Communication Systems and Sensing Department of Electrical Engineering Dhahran31261 Saudi Arabia

As spectrum utilization becomes increasingly scarce due to the exponential growth of intelligent connected devices in the Internet of Things (IoT), developing efficient communication protocols with simultaneous improvements in energy and spectrum usage is critical in response to the demands of cost-effective IoT devices. In this work, we propose a hybrid orthogonal and non-orthogonal multiple-access protocol in coordinated direct uplink/downlink and relay transmission for low-cost IoT paradigms, where a source node engages in direct transmission with proximate IoT users and relies on a relay node for distant connections. This protocol offers a successive interference cancellation–free approach and does not require any channel disparity for power allocation. Exact and asymptotic analytical expressions for the outage probability (OP) and ergodic capacity (EC) are derived. Numerical results demonstrate that the proposed protocol significantly improves OP–by 8 folds for the respective proximate users while maintaining the same OP for distant users over classical coordinated non-orthogonal multiple access–and delivers superior EC performance for proximate IoT users at low to moderate signal-to-noise ratios (SNRs) and distant users at most SNR. Moreover, critical tasks for minimizing the maximal OP and maximizing the ergodic sum capacity have been undertaken to achieve outage fairness and enhance the overall system's capacity. These non-convex problems are efficiently addressed by applying the analytical asymptotic-inspired alternative optimization. © 1967-2012 IEEE.

关键词： Signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

Flexible Measurement Testbed for Evaluating Time-Sensitive Networking in Industrial Automation Applications

Flexible Measurement Testbed for Evaluating Time-Sensitive N...

引用

IEEE Conference on Network Softwarization (NetSoft)

作者： Stefan Senk Marian Ulbricht Javier Acevedo Giang T. Nguyen Patrick Seeling Frank H. P. Fitzek Deutsche Telekom Chair of Communication Networks TU Dresden Haptic Communication Systems TU Dresden Centre for Tactile Internet with Human-in-the-Loop (CeTI) Department of Computer Science Central Michigan University

ISBN: (数字)9781665406949

ISBN: (纸本)9781665406956

Deterministic communications are required for industrial environments, yet their realization is a challenging task. Time-Sensitive Networking (TSN) is intended to enable deterministic communication over inexpensive Ethernet networks. Standardized by the IEEE TSN working group, TSN enables precise control of time synchronization, traffic shaping, reliability enhancements, and network administration to answer the demands of industrial control applications. Subsequently, there is a significant need to enable turnkey research and implementation efforts. However, a current lack of open-sourced testbed implementations to investigate and study the behavior of TSN network devices limits verification to simulation and theoretical models. We introduce a publicly available, flexible, and open-sourced measurement testbed for evaluating TSN in the context of industrial automation applications to address the need to perform real-world measurements. In this contribution, we describe our testbed combining Commercial-Off-The-Shelf (COTS) hardware and existing open-source tools as a platform for in-depth evaluation of TSN devices. Providing detailed TSN backgrounds, we describe an in-depth performance analysis for our implementation. For a common Tactile Internet scenario, we observe an accuracy of close to 5 ns achievable with our publicly available COTS setup.

关键词： Performance evaluation Automation Turnkey project Current measurement Hardware Behavioral sciences Software measurement

来源：评论

学校读者我要写书评

暂无评论

Building Highly Maintainable Software for Energy Automation systems using Abstraction Layering

Building Highly Maintainable Software for Energy Automation ...

引用

Annual Conference of Industrial Electronics Society

作者： Arsalan Liaqat Max Somerville Matthew M. Y. Kuo John Spray Chen-Wei Yang Roopak Sinha Computer Science and Software Engineering Department Auckland University of Technology Auckland New Zealand Software Engineering Consultant Auckland New Zealand Dependable Communication and Computation Systems Lulea University of Technology Sweden School of Information Technology Deakin University Melbourne Australia

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

In smaller components of industrial or energy automation systems, such as device controllers of Protection and Control (PAC) systems in smart grids, controller functionality is tightly coupled with the physical device or sensor capabilities. At this level, software is small and therefore easy to maintain and test. However, when multiple controllers are interconnected and higher-level functionality is added, software applications grow exponentially, and ensuring maintainability becomes proportionally challenging. In this paper, we extend the IEC 61499 reference architecture used to develop industrial automation software with the principles of Abstraction Layered Architecture (ALA) that has shown up to 400% improvements in industrial software maintainability. We show that even a light application of abstraction layering on the top, application-level of IEC 61499 applications makes them significantly more readable and slightly more maintainable. More concrete gains in maintainability are expected when abstraction layering is integrated into lower layers.

关键词： Industrial electronics Automation Buildings computer architecture Control systems Software Picture archiving and communication systems Smart grids Protection IEC Standards

来源：评论

学校读者我要写书评

暂无评论

An Evaluation of Lightweight Deep Learning Techniques in Medical Imaging for High Precision COVID-19 Diagnostics

arXiv

引用

arXiv 2023年

作者： Ukwandu, Ogechukwu Hindy, Hanan Ukwandu, Elochukwu Department of Computer Communication and Information Systems School of Engineering and Built Environment Glasgow Caledonian University School of Computer Science and Informatics Cardiff University United Kingdom Computer Science Department Faculty of Computer and Information Sciences Ain Shams University Cairo11566 Egypt Department of Applied Computing and Engineering Cardiff School of Technologies Cardiff Metropolitan University CardiffCF5 2YB United Kingdom

Timely and rapid diagnoses are core to informing on optimum interventions that curb the spread of COVID-19. The use of medical images such as chest X-rays and CTs has been advocated to supplement the Reverse-Transcription Polymerase Chain Reaction (RT-PCR) test, which in turn has stimulated the application of deep learning techniques in the development of automated systems for the detection of infections. Decision support systems relax the challenges inherent to the physical examination of images, which is both time consuming and requires interpretation by highly trained clinicians. A review of relevant reported studies to date shows that most deep learning algorithms utilised approaches are not amenable to implementation on resource-constrained devices. Given the rate of infections is increasing, rapid, trusted diagnoses are a central tool in the management of the spread, mandating a need for a low-cost and mobile point-of-care detection systems, especially for middle- and low-income nations. The paper presents the development and evaluation of the performance of lightweight deep learning technique for the detection of COVID-19 using the MobileNetV2 model. Results demonstrate that the performance of the lightweight deep learning model is competitive with respect to heavyweight models but delivers a significant increase in the efficiency of deployment, notably in the lowering of the cost and memory requirements of computing resources. © 2023, CC BY-NC-SA.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

On-chip metamaterial-enabled high-order mode-division multiplexing

引用

Advanced Photonics 2023年第5期5卷 106-113页

作者： Yu He Xingfeng Li Yong Zhang Shaohua An Hongwei Wang Zhen Wang Haoshuo Chen Yetian Huang Hanzi Huang Nicolas KFontaine Roland Ryf Yuhan Du Lu Sun Xingchen Ji Xuhan Guo Yingxiong Song Qianwu Zhang Yikai Su Shanghai Jiao Tong University Department of Electronic EngineeringState Key Laboratory of Advanced Optical Communication Systems and NetworksShanghaiChina Nokia Bell Labs Murray HillNew JerseyUnited States Shanghai University Key Laboratory of Specialty Fiber Optics and Optical Access NetworksJoint International Research Laboratory of Specialty Fiber Optics and Advanced CommunicationShanghaiChina Shanghai Jiao Tong University School of Electronic Information and Electrical EngineeringJohn Hopcroft Center for Computer ScienceShanghaiChina

Mode-division multiplexing(MDM)technology enables high-bandwidth data transmission using orthogonal waveguide modes to construct parallel data ***,few demonstrations have been realized for generating and supporting high-order modes,mainly due to the intrinsic large material groupvelocity dispersion(GVD),which make it challenging to selectively couple different-order spatial *** show the feasibility of on-chip GVD engineering by introducing a gradient-index metamaterial structure,which enables a robust and fully scalable MDM *** demonstrate a record-high-order MDM device that supports TE_(0)–TE_(15)modes simultaneously.40-GBaud 16-ary quadrature amplitude modulation signals encoded on 16 mode channels contribute to a 2.162 Tbit∕s net data rate,which is the highest data rate ever reported for an on-chip single-wavelength *** method can effectively expand the number of channels provided by MDM technology and promote the emerging research fields with great demand for parallelism,such as high-capacity optical interconnects,high-dimensional quantum communications,and large-scale neural networks.

关键词： integrated photonics metamaterial mode-division multiplexing subwavelength grating

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：