检索结果-内蒙古大学图书馆

Optimizing land mine detection across diverse mining environments: A hyperspectral data approach with regression models

引用

International Journal of Intelligent Networks 2024年第1期5卷 351-363页

作者： Anand, R. Andrew, J. Makki, Ihab Department of Electrical and Electronics Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India Department of Computer Science and Engineering Manipal Institute of Technology Manipal Academy of Higher Education Manipal Karnataka 576104 India Department of Nouvelle Aquitaine France

The detection of landmines, namely anti-tank mines, explosive devices, and unexploded ordnance, is a formidable obstacle for the global community. The visible consequences of unobserved explosives in communities affected by war are characterized by significant devastation and human suffering. In order to effectively tackle this matter, it is imperative to use proactive strategies that focus on the identification and mitigation of these perilous substances prior to their potential infliction of harm. Nevertheless, the majority of current solutions exhibit significant deficiencies, such as exorbitant expenses, inefficiencies, and apprehensions over accuracy. These drawbacks are further compounded by the inherent trade-offs that exist between these elements, where improvements in one area often come at the expense of another. Contrarily, recent breakthroughs in the areas of deep learning, unmanned aerial vehicles, and sensor technologies are being recognized as potentially transformative elements in the domain of landmine identification and removal. This paper presents a thorough examination of recent scholarly investigations that integrate computerized technology in the field of landmine detection. To the extent of our current understanding, there has been no prior investigation that has thoroughly examined this particular domain. The main aim of this study is to investigate the incorporation of machine learning based regression methods in the field of landmine detection. The study specifically emphasizes the identification and resolution of existing issues that hinder the development of efficient automated solutions, hence enhancing performance optimization. The Sum of Sine Curve Fit Regression Model is proposed and proved a powerful and adaptable tool for extracting relevant information from this hyperspectral images. © 2024 The Authors

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

Integrating big data and blockchain to manage energy smart grids—TOTEM framework

引用

Blockchain(Research and Applications) 2022年第3期3卷 36-45页

作者： Dhanya Therese Jose Jørgen Holme Antorweep Chakravorty Chunming Rong Department of Computer Science Electrical Engineering University of Stavanger4036StavangerNorway

The demand for electricity is increasing exponentially day by day,especially with the arrival of electric *** the smart community neighborhood project,electricity should be produced at the household or community level and sold or bought according to the *** the actors can produce,sell,and buy according to the demands,thus the name *** solutions can contribute to this in several ways,such as machine learning for analyzing the household data for customer demand and peak hours for the usage of electricity,blockchain as a trustworthy platform for selling or buying,data hub,and ensuring data security and privacy of ***:Token for controlled computation is a framework that allows users to analyze the data without moving the data from the data owner's *** also ensures the data security and privacy of the ***,in this article,we will show the importance of the TOTEM architecture in the EnergiX project and how the extended version of TOTEM can be efficiently merged with the demands of the current and similar projects.

关键词： Blockchain Big data analytic Hyperledger fabric Hadoop Map Reduce Docker PIVT

来源：评论

学校读者我要写书评

暂无评论

A fire management intelligent system for the Brazilian cerrado biome based on a deep learning two phase detection method

引用

Journal of Reliable Intelligent Environments 2025年第1期11卷 1-18页

作者： Borges, Natalia Fonseca, Lívia Barreto, Priscila Solis Alchieri, Eduardo Caetano, Marcos Fagundes Resende, Paulo Brandão, Leonardo Vieira, Lucas Department of Electrical Engineering University of Brasilia DF Brasília Brazil Department of Computer Science University of Brasilia DF Brasília Brazil GigaCandanga Association DF Brasília Brazil

The implementation of smoke and fire detection systems based on image processing and machine learning still present research challenges for certain biomes, such as the cerrado where video-based fire smoke detection using cameras could be more efficient than sensor-based systems. This work presents the SEMFOGO-DF fire monitoring system, a solution composed of a distributed processing architecture and a deep-learning computer vision algorithm for smoke detection and emergency alert generation. The solution performs smoke detection on image sequences using a two-phase algorithm. The first phase analyzes image sequences and classifies regions of the image with a high probability of fire and in the second phase, a smoke classification is conducted on a zoomed image. Experimental results show that the two-phase algorithm can consistently reduce the number of false alerts generated by the first phase alone, with a relatively low reduction in the detection rate. The development of the solution also allowed the creation of two novel datasets. The first dataset consists of image sequences of the cerrado biome, annotated with smoke contours. The second dataset includes zoomed images of the cerrado landscape, annotated with labels indicating smoke and non-smoke occurrences. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Intelligent systems

来源：评论

学校读者我要写书评

暂无评论

A Bilayered Decomposition Technique for Handling Complex Constrained Multi-Objective Optimization Problems

A Bilayered Decomposition Technique for Handling Complex Con...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Yasuda, Yusuke Tamura, Kenichi Yasuda, Keiichiro Tokyo Metropolitan University Department of Electrical Engineering and Computer Science Tokyo191-0065 Japan

ISBN: (纸本)9781665410205

Constrained multi-objective optimization problems (CMOPs) are prevalent in real-world applications, dealing with multi-objective and constraint functions. Multiobjective evolutionary algorithm based on decomposition with differential evolution (MOEA/D-DE) has proven effective for unconstrained multi-objective optimization problems with complex Pareto front (PF). However, in CMOPs, the conflicting nature between objectives and constraints often makes it challenging to appropriately manage constraints while ensuring convergence, diversity, and feasibility of the solution set towards the PF. To address this issue, this paper proposes a bilayered decomposition technique. The proposed algorithm treats constraints as an additional objective function, separately decomposing the objective space and the constraint violation space. This method allows for the simultaneous attainment of convergence, diversity, and feasibility in the solution set while efficiently exploring the PF. Experimental results demonstrate that, within the MOEA/D-DE framework, our algorithm efficiently navigates complex PFs on challenging problems such as LIR-CMOPs and DAS-CMOPs, matching the performance of state-of-the-art constrained multi-objective evolutionary algorithms. © 2024 IEEE.

关键词： Constrained optimization

来源：评论

学校读者我要写书评

暂无评论

Developing a Smart Drip Infusion System to Elevate Precision in Healthcare 4

Developing a Smart Drip Infusion System to Elevate Precision...

引用

4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： Molefinyane, Sefemo Yahya, Abid Hamsadhwani, V. Rohini, R. Samikannu, Ravi Begam, K.Maruliya Botswana International University of Science and Technology Department of Electrical and Communications Systems Engineering Palapye Botswana Periyar Maniammai Institute of Science and Technology Department of Electrical and Electronics Engineering Thanjavur India Vivekanandha College of Engineering for Women Department of Computer Science and Engineering Tiruchengode India Saveetha School of Engineering Saveetha Institute of Medical and Technology Science Department of Computer Science and Communications Engineering Tiruchengode India

ISBN: (纸本)9798331529635

Intravenous (IV) therapy is a critical component of modern healthcare, yet traditional IV systems are prone to human errors, manual adjustments, and limited monitoring capabilities, which can jeopardize patient safety and hinder healthcare efficiency. This paper presents the development of the Smartdrip IV Infusion System, a sophisticated and automated solution that integrates advanced sensors, control algorithms, and intuitive user interfaces to address these limitations. The Smartdrip system minimizes human intervention, provides real-time monitoring, and automates fluid administration with enhanced precision and safety features. The system demonstrates high reliability through simulation and prototype testing in detecting anomalies, issuing alerts, and ensuring accurate infusion rates, thereby improving patient outcomes and reducing healthcare provider workload. The results validate the Smartdrip system as a transformative approach to optimizing IV therapy in diverse clinical settings. © 2024 IEEE.

关键词： Automated Infusion System Drip Rate Monitoring Healthcare Automation Intravenous Therapy Patient

来源：评论

学校读者我要写书评

暂无评论

Ph.D. Project: A Compiler-Driven Approach to HW/SW Co-Design of Deep-Learning Accelerators 32

Ph.D. Project: A Compiler-Driven Approach to HW/SW Co-Design...

引用

32nd IEEE Annual International Symposium on Field-programmable Custom Computing Machines, FCCM 2024

作者： Kamucheka, Tendayi Andrews, David University of Arkansas Department of Electrical Engineering and Computer Science FayettevilleAR72701 United States

ISBN: (纸本)9798350372434

This work introduces SPAR, a compiler framework based on MLIR, tailored for deep learning inference applications. Alongside SPAR, we present SPAR HL, an extensible Instruction Set Architecture (ISA) designed to seamlessly interface custom FPGA-based accelerators with the SPAR compiler. Historically, custom accelerators on FPGA have posed a challenge as a compiler target. Prior compiler initiatives have addressed this issue by generating application-specific hardware during compilation, necessitating expertise across both application and hardware domains. In response, we offer an alternative approach by proposing an ISA as a unified compiler target and hardware interface for custom accelerators. Furthermore, we introduce a compiler capable of translating high-level machine learning models encoded in ONNX into code compatible with our proposed ISA, thus enabling efficient deployment on FPGA-based custom accelerators. © 2024 IEEE.

关键词： program compilers

来源：评论

学校读者我要写书评

暂无评论

Robust Indoor Positioning of Automated Guided Vehicles in Internet of Things Networks With Deep Convolution Neural Network Considering Adversarial Attacks

引用

IEEE Transactions on Vehicular Technology 2024年第6期73卷 7748-7757页

作者： Elsisi, Mahmoud Rusidi, Akhmad Lutfi Tran, Minh-Quang Su, Chun-Lien Ali, Mahmoud N. National Kaohsiung University of Science and Technology Department of Electrical Engineering Kaohsiung807618 Taiwan Cairo11629 Egypt National Taiwan University of Science and Technology Department of Electronic and Computer Engineering Taipei106 Taiwan Tuetech University Department of Mechanical Engineering Thai Nguyen250000 Viet Nam

The effectiveness of positioning techniques that utilize the receiver signal strength (RSS) is highly dependent on the instability of the received signal strength indicator (RSSI). Up to now, there is no strategy that effectively lowers the influence of such instability on the accuracy of positioning. Moreover, recent studies showed that indoor positioning techniques are vulnerable to noise in RSSI data and cyber-attacks, which make them more expensive. In this study, a new Internet of Things (IoT) paradigm is proposed for the indoor positioning of automated guided vehicles (AGVs) using a deep convolution neural network (CNN). The proposed method handles signal processing by converting the RSSI signal into an image. In which, the 1-D RSSI signal is converted into 2-D image data in order to generate the new features based on continuous wavelet transform (CWT), and then the proposed deep CNN is implemented for the indoor positioning system. The test results show that the proposed model can outperform other state-of-the-art positioning techniques with small position errors. Furthermore, the robustness of the proposed model is validated against various adversarial attacks. In addition, the proposed method can have a lower impact on RSSI change compared with other methods. © 1967-2012 IEEE.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Design of a Standalone Hybrid Renewable Energy System - A Hospital in Lafayette, Indiana, USA 5

Design of a Standalone Hybrid Renewable Energy System - A Ho...

引用

5th IEEE International Conference on Communication, Computing and Industry 6.0, C2I6 2024

作者： Thapa, Samir Asrari, Arash Naderi, Ehsan Fajri, Poria Purdue University Northwest Department of Electrical and Computer Engineering HammondIN United States Arkansas State University College of Engineering and Computer Science Department of Electrical Engineering JonesboroAR United States University of Nevada Department of Electrical and Biomedical Engineering RenoNV United States

ISBN: (纸本)9798350379884

This paper presents the design of a standalone hybrid renewable energy system (HRES) for a hospital in Lafayette, Indiana, USA, to enhance energy reliability and reduce costs. The proposed system integrates photovoltaic (PV) panels, wind turbines, batteries, and a backup diesel generator. Using Hybrid Optimization Model for Electric Renewables (HOMER) software, the system is optimized for cost-effectiveness and sustainability, while electrical Transient Analyzer program (ETAP) software is employed to ensure a safe operation under varying conditions. Results verify that the developed HRES meets the hospital's energy needs, significantly reduces operational costs, and minimizes carbon emissions, offering a sustainable model for healthcare facilities. © 2024 IEEE.

关键词： Windmill

来源：评论

学校读者我要写书评

暂无评论

An Improved High Gain Continuous Input Current Quadratic Boost Converter for Next-Generation Sustainable Energy Application

引用

IEEE Transactions on Circuits and Systems II: Express Briefs 2024年第5期71卷 2839-2843页

作者： Liu, Hwa-Dong Jana, Anindya Sundar Lin, Chang-Hua National Taiwan Normal University Undergraduate Program of Vehicle and Energy Engineering Taipei106 Taiwan University of Notre Dame Department of Electrical Engineering South BendIN46556 United States National Taiwan University of Science and Technology Department of Electrical Engineering Taipei106 Taiwan

With the rapid transformation from fossil fuel-based energy systems to renewable-based energy systems the application of a high gain boost DC-DC converter is becoming the main attraction due to its wide range of numerous applications. This specific study presents an improved high gain non isolated quadratic boost DC-DC converter (QBC) with voltage gain three times of the quadratic boost converter. The proposed non-isolated category topology is the modified version of the quadratic boost converter where the 2nd inductor of the QBC is replaced by a voltage multiplier cell (VMC) and a switch capacitor network is integrated with the VMC to increase the voltage gain as well as to reduce the switch's voltage stress. Moreover, the continuous input current and common ground feature of this proposed circuit configuration have shaped its potential application by making it advantageous over other non-isolated based high gain boost converters. To support its feasibility a rated power of 150 W prototype is developed after validating the results by Plecs software. The voltage gain offered by this proposed circuit configuration is justified by experimental results and the software simulation. A comprehensive analysis and components design is also formulated and documented in this brief. © 2004-2012 IEEE.

关键词： Boost converter

来源：评论

学校读者我要写书评

暂无评论

Cultural Heritage Monitoring and Predictive Maintenance using Internet of Things: Assessment and Future Aspects

引用

Journal of Mobile Multimedia 2024年第6期20卷 1211-1250页

作者： Um-E-habiba Shaikh, Faisal Karim Chowdhry, Bhawani Shankar Department of Computer Science Shaheed Zulfikar Ali Bhutto Institute of Science and Technology Hyderabad Pakistan Telecommunication Engineering Department Mehran University of Engineering and Technology Jamshoro Pakistan Faculty of Electrical Electronics and Computer Engineering Mehran University of Engineering and Technology Jamshoro Pakistan

This study presents a detailed survey on the use of the Internet of Things (IoT) for predictive maintenance and monitoring of cultural heritage, focusing on museums and exhibitions. The integration of IoT in these fields offers significant potential for optimizing maintenance and supervision of heritage resources while also enhancing maintenance strategies. This review examines the application of IoT devices, data analysis, and predictive algorithms in monitoring the state of heritage resources to improve tourist experiences and conserve cultural resources. Key enabling technologies can enable adaptive interactions and engagement with enhanced navigation. Visualization technologies are also common, offering hands-on displays. The study also emphasizes the value of accessibility and interactivity, providing personalization and content sharing features. Several initiatives prioritize the delivery of digital content through mobile applications, internet browsers, and downloadable *** study examines how IoT-enabled predictive maintenance systems can recognize potential hazards, like resource decay or environmental dangers, enabling immediate action. This survey also highlights trends, challenges, and future research in IoT and cultural heritage monitoring. © 2025 River Publishers.

关键词： heritage monitoring IoTs predictive maintenance trends

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：