检索结果-内蒙古大学图书馆

Smart Electronics and Communication (ICOSEC), International Conference on

作者： Helina Rajini Suresh R. Neelaveni Bonda Kiran Kumar R. Arunadevi Indhumathi G M Varun Department of ECE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tamilnadu India Department of CSE SRM institute of science and technology Chennai Tamilnadu India KL School of Architecture KL Deemed to be University Andhrapradesh India Department of Computer Science and Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai Tamilnadu India Department of ECE Rajalakshmi Engineering College Chennai Tamilnadu India Department of ECE Saveetha Engineering College Chennai Tamilnadu India

The proliferation of IoT devices is primarily responsible for the data deluge that has engulfed multiple industries. Nevertheless, due to the high dimensionality and complexity of IoT data streams, anomaly detection remains a significant challenge. This suggests that an unsupervised deep learning strategy could be used to identify anomalies in IoT data streams. Instead of relying on labeled data, this method employs deep neural networks, which can be trained to recognize anomalies and comprehend complex patterns. Experiments are conducted on a real-world IoT dataset to evaluate the efficacy and accuracy of the proposed method. The results demonstrate its proficiency in detecting anomalies in IoT data streams, paving the way for a safer, more reliable Internet of Things. Using unsupervised deep learning techniques, the method provides a practicable solution to the age-old problem of IoT anomaly identification.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Evaluating Large Language Models on Spatial Tasks: A Multi-Task Benchmarking Study

arXiv

引用

arXiv 2024年

作者： Xu, Liuchang Zhao, Shuo Lin, Qingming Chen, Luyao Luo, Qianqian Wu, Sensen Ye, Xinyue Feng, Hailin Du, Zhenhong School of Mathematics and Computer Science Zhejiang Agriculture and Forestry University Hangzhou311300 China School of Earth Sciences Zhejiang University Hangzhou310058 China Department of Landscape Architecture and Urban Planning Center for Geospatial Sciences Applications and Technology Texas A&M University College StationTX77843 United States Financial Big Data Research Institute Sunyard Technology Co. Ltd Hangzhou310053 China

The advent of large language models such as ChatGPT, Gemini, and others has underscored the importance of evaluating their diverse capabilities, ranging from natural language understanding to code generation. However, their performance on spatial tasks has not been comprehensively assessed. This study addresses this gap by introducing a novel multi-task spatial evaluation dataset, designed to systematically explore and compare the performance of several advanced models on spatial tasks. The dataset encompasses twelve distinct task types, including spatial understanding and simple route planning, each with verified, accurate answers. We evaluated multiple models, including OpenAI’s gpt-3.5-turbo, gpt-4-turbo, gpt-4o, ZhipuAI’s glm-4, Anthropic’s claude-3-sonnet-20240229, and MoonShot’s moonshot-v1-8k, through a two-phase testing approach. Initially, we conducted zero-shot testing, followed by categorizing the dataset by difficulty and performing prompt tuning tests. Results indicate that gpt-4o achieved the highest overall accuracy in the first phase, with an average of 71.3%. Although moonshotv1-8k slightly underperformed overall, it surpassed gpt-4o in place name recognition tasks. The study also highlights the impact of prompt strategies on model performance in specific tasks. For example, the Chain-of-Thought (CoT) strategy increased gpt-4o’s accuracy in simple route planning from 12.4% to 87.5%, while a one-shot strategy enhanced moonshot-v1-8k’s accuracy in mapping tasks from 10.1% to 76.3%. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

Pathways for Efficient Transition into Net Zero Energy Buildings (Nzeb) in Sub-Saharan Africa. Case Study: Cameroon, Senegal, and Côte D’Ivoire

SSRN

引用

SSRN 2023年

作者： Umaru Mohammed, Bongwirnso Wiysahnyuy, Yufenyuy Severine Ashraf, Noman Mempouo, Blaise Mengata, Ghislain Mengounou Department of Building Engineering College of Architecture and Planning Imam Abdulrahman Bin Faisal University Dammam31451 Saudi Arabia Laboratory of Computer Science Engineering and Automation University of Douala Cameroon Smart Green Shift Ltd Rotherham United Kingdom Laboratory of Technology and Applied Sciences University of Douala Cameroon

The combustion of fossil fuels to generate electricity to meet up with high energy demands of buildings, increases pollution;deteriorating the environment and accelerating climate change. The idea of net zero energy buildings (nZEB) was developed to reduce building energy use and pollution. However, there are still many obstacles to implementing the nZEB idea, notably in sub-Saharan Africa, where energy consumption and pollutant emissions from buildings are particularly high. This article focuses on Cameroon, Senegal, and Côte d'Ivoire and proposes guidelines for making a smooth transition to nZEB in sub-Saharan Africa, as are examples of strategies that might be used to minimize energy consumption in buildings and pollution. The path has been shown to consist of the following steps: conducting a baseline assessment;creating building energy codes and standards;conducting a stakeholder analysis;carrying out capacity building and awareness-raising;setting up financing mechanisms and incentives;creating a strong supply chain;setting up a monitoring and evaluation framework;piloting nZEB projects;disseminating best practices;and scaling up adoption. With this plan in place, sub-Saharan Africa can make the most of its resources while preserving the environment as it makes the move to nZEB © 2023, The Authors. All rights reserved.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

Reliable Multihop Routing and Congestion Aware Chicken Swarm Optimization in Vehicular Ad-Hoc Network

Reliable Multihop Routing and Congestion Aware Chicken Swarm...

引用

Integrated Circuits and Communication Systems (ICICACS), IEEE International Conference on

作者： Cuddapah Anitha Dalia Al-Tarazi GD. Vignesh A. Vinotha Vasuki Jayant Giri M. Dinesh Department of Computer Science and Engineering School of Computing Mohan Babu University Erstwhile Sree Vidyanikethan Engineering College Tirupati India Department of Architecture Engineering Faculty of Engineering Zarqa university Zarqa Jordan College of Engineering University of Business and Technology Jeddah Saudi Arabia Department of Electronics and Communication Engineering St. Joseph's College of Engineering Chennai India Department of Computer Science and Engineering J.P. College of Engineering Tenkasi India Department of Mechanical Engineering Yeshwantrao Chavan College of Engineering Nagpur India Division of Research and Development Lovely Professional University Phagwara India Department of VLSI Microelectronics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Chennai India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

Background: Vehicular Ad Hoc Networks (VANETs) play a crucial role in intelligent transportation by facilitating communication between vehicles and vehicles with infrastructure-based models. They encounter problems such as significant movement, overcrowding, and loss of data. This research presents a novel deep reinforcement learning-based resource allocation and congestion optimization (DRLRCO) framework aimed at improving communication efficiency and high reliability using an effective learning process. Method Used: The DRLRCO framework employs agent-based learning to ensure precise data transmission, AdMAC Protocol for dynamic packet delivery, and Congestion-Aware Chicken Swarm Optimization (CSO) to enhance network performance. Result: The DRLRCO framework surpasses reinforcement learning models for comprehensive testing. Significant enhancements involve improved accuracy, reduced data loss, minimized overhead, increased throughput, and shorter average delays for real-time communication. Conclusion: The DRLRCO framework successfully tackles congestion and data loss in vehicular communication. Future studies might involve Artificial Intelligence (AI) for traffic forecasting, experimentation among high-speed vehicles and investigating blockchain for enhanced security.

关键词： Vehicular ad hoc networks Routing Throughput Synchronization Resource management Dedicated short range communication Particle swarm optimization Artificial intelligence Vehicle dynamics Testing

来源：评论

学校读者我要写书评

暂无评论

STRUCTURE-ORIENTED PROGRESSIVE LOW-RANK IMAGE RESTORATION FOR DEFENDING ADVERSARIAL ATTACKS

STRUCTURE-ORIENTED PROGRESSIVE LOW-RANK IMAGE RESTORATION FO...

引用

2021 IEEE International Conference on Multimedia and Expo, ICME 2021

作者： Zhao, Zhiqun Wang, Hengyou Sun, Hao Cao, Wenming He, Zhihai Department of Electrical Engineering and Computer Science University of Missouri ColumbiaMO65211 United States School of Science Beijing University of Civil Engineering and Architecture Beijing100044 China Guangdong Multimedia Information Service Engineering Technology Research Center Shenzhen University Shenzhen518060 China

ISBN: (纸本)9781665438643

Deep neural networks recognize objects by analyzing local image details and summarizing their information along the inference layers to derive the final decision. Because of this, they are prone to adversarial attacks. On the other hand, human eyes recognize objects based on their global structures and semantic cues, instead of local image textures. In this work, we propose to develop a structure-oriented progressive low-rank image completion method to remove unneeded texture details from the input images and shift the bias of deep neural networks towards global object structures and semantic cues. We formulate the problem into a low-rank matrix completion problem with progressively smoothed rank functions to avoid local minimums. Our experimental results demonstrate the proposed method is able to successfully remove the insignificant local image details while preserving important global object structures. © 2021 IEEE computer Society. All rights reserved.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Twin-Array Quasi FSS Reflector with Dual Band Cross-Dipole for 5G Base Station Antenna Application

Twin-Array Quasi FSS Reflector with Dual Band Cross-Dipole f...

引用

Conference on Power, Energy and Innovations (ICPEI)

作者： Ian Jerome Q. Santos Maleeya Tangjitjetsada Paitoon Rakluea Norakamon Wongsin Chawalit Rakluea Chatree Mahatthanajatuphat Nonchanutt Chudpooti Tawan Thianthong Department of Electronics and Telecommunication Engineering Faculty of Engineering Rajamangala University of Technology Thanyaburi Thanyaburi Pathum Thani Thailand Department of Electronics and Telecommunication Engineering Faculty of Engineering and Architecture Rajamangala University of Technology Suvarnabhumi Nonthaburi Thailand Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Wongsawang Bangsue Bangkok Thailand Department of Industrial Physics and Medical Instrumentation Faculty of Applied Science King Mongkut’s University of Technology North Bnagkok Wongsawang Bangsue Bangkok Thailand Siam Airport Ground Service Co. Ltd. Don Mueang Bangkok Thailand

This article provides an explanation of the use of a Twin-Array Quasi Frequency Selective Surface (FSS) Reflector with Dual Band Cross-Dipole for antenna applications in 5G base stations. The base material employed in this study is FR4 sheet, which has a dielectric constant (ε r ) of 4.3. The antenna obtained has dimensions of 100x100 mm 2 and functions throughout the frequency spectrum spanning from 730 to 860 MHz, 1700 to 2130 MHz. The primary benefits of this antenna design are its lightweight structural composition, compatibility with the frequency range of 730–860 MHz, and discernible performance attributes. The CST Studio Suite software was used to conduct a simulation of the antenna’s performance. The antenna has an operating frequency range of 730–860 MHz and 1700–2130 MHz, enabling it to support a unidirectional wave propagation pattern that is suitable for the implementation of a 5G mobile communication base station.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Stock optimization Approach for Inventory Management 3

A Hybrid Stock optimization Approach for Inventory Managemen...

引用

3rd International Congress on Human-computer Interaction, Optimization and Robotic Applications, HORA 2021

作者： Cimen, Egemen Berki Kurban, Ilknur Selmanoglu, Ozgur Sahin, Murat Kilinc, Deniz Data Science Eldor Corporation Izmir Turkey Software Development Eldor Corporation Izmir Turkey Technology Eldor Corporation Izmir Turkey Data Science Kalybe.AI Izmir Turkey Bakirçay University Computer Engineering Department of Faculty of Engineering and Architecture Izmir Turkey

ISBN: (纸本)9781665440585

Modern world is rapidly evolving around knowledge and business that know how to use knowledge shows superiority. Thus, smart decision making becomes vital for the modern business world to achieve sustainability in life and business. Especially, with a world of scarce resources, utilizing knowledge would play critical not only today but also for future. Moreover, using knowledge is inevitable in supply chain and inventory management must be supported with smart algorithms and modern heuristics to avoid excessive inventory while fighting with stockout. Therefore, this study explores the opportunity for inventory planning with heuristics and tailored techniques as well as how to hybridize modern heuristics and tailored techniques. In this study, inventory optimization experiments are proposed to model spare part inventory management and find the best way to determine reorder amount to deal with shortage and excessive inventory. Four heuristics which are i) basic golden ratio, ii) simulated annealing, iii) statistical rule-based heuristic and iv) hybrid algorithm of simulated annealing and statistical rule-based heuristic are evaluated on existing spare part dataset with an example from real-life part supplier named Eldor. In this test case, 400 products are analyzed, and best reorder points and amounts are selected with the help of heuristics. Heuristics' main structures and parameters are adjusted for the problem's need and improvement on quality of results. Parameters are determined according to trial and error with experts' guidance on heuristics. The best result suggests 8% improvement on cost and 37% improvement on inventory load could achieve with the help of heuristics. These solutions are usable against even hard constraints like shortage. © 2021 IEEE.

关键词： Simulated annealing

来源：评论

学校读者我要写书评

暂无评论

Reducing Operational Expenses of Lorawan-Based Solutions that Connect Urban and Rural Areas

SSRN

引用

SSRN 2022年

作者： Finochietto, José Mariano Santos, Rodrigo Ochoa, Sergio F. Meseguer, Roc GIDI Department of Information Technology Universidad Nacional de Mar del Plata Mar del Plata7600 Argentina Department of Electrical and Computers Universidad Nacional del Sur CONICET Bahía Blanca8000 Argentina Department of Computer Science Universidad de Chile Santiago8370456 Chile Department of Computer Architecture Universitat Politècnica de Catalunya Barcelona08034 Spain

LoRaWAN has become the most widely used Low Power Wide Area Network technology to implement monitoring solutions based on the Internet of Remote Things (IoRT) paradigm. Typically, these solutions interconnect remote sensing areas and data processing infrastructure located in urban centers. The operation expenses of these solutions depend mainly on the traffic sent through the network backhaul;i.e., the link that connects the remote sensing area and urban area where the data is processed and stored. This service is provided by telecommunication companies and represents the main operation cost of IoRT solutions. These expenses usually limit the affordability of IoRT-based systems in developing countries, and also in scenarios where the operational cost is an issue to address. This paper presents an extension to the LoRaWAN protocol, named Node Aware-LoRaWAN (NA-LoRaWAN), that reduces the traffic in backhaul, decreasing thus the operation expenses of IoRT-based systems. In order to evaluate the performance of NA-LoRaWAN, it was compared to a regular LoRaWAN implementation. Depending on the network scenario, the proposed extension reduces the traffic through the backhaul in the range of 12-34 %. This opens several possibilities to use it in application domains with low operational budget, and reduce expenses in already implemented systems. © 2022, The Authors. All rights reserved.

关键词： Remote sensing

来源：评论

学校读者我要写书评

暂无评论

A Resource-Friendly Authentication Protocol for UAV-Based Massive Crowd Management Systems

引用

Security and Communication Networks 2021年第1期2021卷

作者： Alzahrani, Bander A. Barnawi, Ahmed Chaudhry, Shehzad Ashraf Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia Department of Computer Engineering Faculty of Engineering and Architecture Istanbul Gelisim University Istanbul Turkey

As a part of the smart city revolution, crowd management is an emerging trend and it can enhance the quality of life. Unmanned ariel vehicles (UAVs) can help in making the crowd management process more efficient and more accurate. UAVs can monitor and collect environmental-related surveillance data and share real-time information with each other and with the decision makers. However, the battery-operated UAVs communicate over the open public channel making the privacy and security of the UAVs a crucial element in mission-critical applications. The weaknesses of the existing scheme pave the way to design a new lightweight authentication scheme for UAV environments. In this article, we present a symmetric key primitive-based scheme and provide authentication among a user and a UAV through an intermediate control center. Due to usage of symmetric key and elliptic curve cryptography, the proposed scheme fulfils the performance requirements of the UAVs. The security of the proposed scheme is substantiated through BAN logic, along with a discussion on security features extended by the proposed scheme. The performance and security comparisons show that the proposed scheme provides adequate security and efficiency and can be practically deployed in real UAV environments. © 2021 Bander A. Alzahrani et al.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

Redefining Neural architecture Search of Heterogeneous Multi-Network Models by Characterizing Variation Operators and Model Components

arXiv

引用

arXiv 2021年

作者： Garciarena, Unai Santana, Roberto Mendiburu, Alexander The Department of Computer Science and Artificial Intelligence University of the Basque Country UPV/EHU Donostia20018 Spain The Department of Computer Architecture and Technology University of the Basque Country UPV/EHU Donostia20018 Spain

With neural architecture search methods gaining ground on manually designed deep neural networks -even more rapidly as model sophistication escalates-, the research trend shifts towards arranging different and often increasingly complex neural architecture search spaces. In this conjuncture, delineating algorithms which can efficiently explore these search spaces can result in a significant improvement over currently used methods, which, in general, randomly select the structural variation operator, hoping for a performance gain. In this paper, we investigate the effect of different variation operators in a complex domain, that of multi-network heterogeneous neural models. These models have an extensive and complex search space of structures as they require multiple sub-networks within the general model in order to answer to different output types. From that investigation, we extract a set of general guidelines, whose application is not limited to that particular type of model, and are useful to determine the direction in which an architecture optimization method could find the largest improvement. To deduce the set of guidelines, we characterize both the variation operators, according to their effect on the complexity and performance of the model;and the models, relying on diverse metrics which estimate the quality of the different parts composing *** Codes 68T07 © 2021, CC BY-SA.

关键词： Deep neural networks

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：