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Performance analysis of BDS-3 pseudo-range single point positioning model under environment of woods

Performance analysis of BDS-3 pseudo-range single point posi...

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2023 International conference on Intelligent systems, Communications, and computer Networks, ISCCN 2023

作者： Zhou, Mingduan Cui, Likun Xu, Xiang Ji, Xu Bai, Yansong School of Geomatics and Urban Spatial Informatics Beijing University of Civil Engineering and Architecture Beijing102616 China

ISBN: (纸本)9781510666238

With the successful global networking of Beidou satellite navigation system, Beidou system has been able to provide allweather navigation, positioning and timing services to users worldwide. In order to compare and analyze the positioning performance of BDS-3 with GPS and their combinations under observation environment of woods, based on the unified GPS/BDS-3 combined positioning spatio-Temporal datum, a GPS/BDS-3 combined pseudo-range single-point positioning observation model is established, the positioning solution results are solved by the least squares method, and the SPP data processing software (LsmSPP) is developed based on Visual Studio 2022 platform using C/C++ programming language. The experimental results show that the BDS-3 system is better than the GPS system in tracking satellites under observation environment of woods, and the BDS-3 pseudo-range single-point positioning accuracy is better than 2.50m in the E direction, 2.15m in the N direction, and 5.98m in the vertical direction, which is slightly worse than the GPS/BDS-3 combined positioning accuracy in the E and N directions, but slightly better than the dual-system combined positioning accuracy in the vertical direction, and the positioning accuracy of BDS-3 system is better than that of GPS system in all directions. © 2023 SPIE.

关键词： Global positioning system

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IoT-Based System for Monitoring Energy Consumption in Smart Cities

IoT-Based System for Monitoring Energy Consumption in Smart ...

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2023 International conference on Electrical, computer, Communications and Mechatronics engineering, ICECCME 2023

作者： Onay, Aytun Turkish Aeronautical Association University Department of Software Engineering Ankara Turkey Inovasyon Muhendislik Ltd. Sti Department of R and D Eskisehir Turkey

ISBN: (纸本)9798350322972

In this work, an efficient energy monitoring system based on the Internet of Things (IoT) has been designed to monitor energy and power consumption in real-time for buildings in the city. It is important to make people aware of their behavior as energy consumers, which gives rise to reducing energy consumption to a considerable extent. The developed system provides dynamic monitoring of energy data and searches the energy to determine future energy management solutions for a city. The system is powered by Fiware, which provides a set of context data management standards that enable the creation of smart solutions. The connection between the end devices and the gateway is performed via the Bluetooth 5 protocol. The cost of the developed system, which contains sensors, devices, and a sensor communication network connecting the system to the platform, is less than 10.000 euros per building with 50 flats in the city. ICT monitors have been used to display a city's energy use. IoT devices collect and exchange data via embedded sensors, and they can connect with dashboards, many entities, and remote devices. This study indicates the significance of energy monitoring systems and constructs a solution to monitor power and energy consumption. The monitoring system can be integrated into Smart Cities. © 2023 IEEE.

关键词： Internet of things

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Cognitive Effort in Interaction with software systems for Self-regulation - An Eye-Tracking Study 20th

Cognitive Effort in Interaction with Software Systems for Se...

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20th International conference on engineering Psychology and Cognitive Ergonomics (EPCE) Held as Part of the 25th International conference on Human-computer Interaction (HCII)

作者： Drzyzga, Gilbert Harder, Thorleif Janneck, Monique TH Lubeck Inst Interact Syst Lubeck Germany

ISBN: (纸本)9783031353918;9783031353925

The importance of digital degree programs has grown increasingly in recent years, due in part to their ability to provide a personalized learning experience for students. However, degree programs in this format have higher dropout rates than traditional degree programs. In the process of a user-centered design approach, a dashboard for the online degree programs of a university network is developed to provide information and recommendations about the learning process based on descriptive analysis and machine learning (ML) methods. For this purpose, ML models are developed, trained and evaluated. The goal of the dashboard is to promote self-regulation among students and reduce dropout rates. It will be set up as a plug-in through the learning management system (LMS) Moodle exclusively for students. In order to understand which aspects are important for users in relation to the cognitive processes involved in interacting with the dashboard, an eye-tracking study was conducted using the thinking aloud technique. The goal of the study was to investigate which cognitive demands are set for the users when interacting with the prototype and how the automatically generated information is perceived. When integrating the LD into the LMS, care should be taken to ensure that all content is realized in an understandable and easy-to-follow manner, due to the fact that otherwise the effort required to focus on the content elements of the LD could become greater - and with it the cognitive requirements.

关键词： Higher Education Learning-Management-System Learners Dashboard Self-regulation Motivation Structuring of Feedback Usability User Experience

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A Domain-Aware Federated Learning Study for CNC Tool Wear Estimation 20th

A Domain-Aware Federated Learning Study for CNC Tool Wear E...

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20th International conference on Mobile Web and Intelligent Information systems, MobiWIS 2024

作者： Kaleli, Inci Sila Unal, Perin Deveci, Bilgin Umut Albayrak, Ozlem Ozbayoglu, Ahmet Murat Department of Industrial Engineering Department of Computer Engineering TOBB ETU Ankara Turkey Department of Research and Development TEKNOPAR Ankara Turkey Department of Software Engineering TEDU Ankara Turkey

ISBN: (纸本)9783031680045

This study proposes a cutting tool condition monitoring platform for CNC machines used in metal part manufacturing to estimate tool wear values. The PHM 2010 Dataset, along with operational and situational data from CNC machines and sensors, were analyzed using artificial intelligence algorithms to support total equipment performance with current tool wear values. The innovation lies in developing an artificial intelligence application that incorporates the Federated Learning method with artificial neural networks. This application is among the first to monitor machine cutting tools using Federated Learning. An efficient and accurate predictive tool wear estimation method is presented through the application of Federated Learning with Long-Short Term Memory models. This novel approach holds great potential for industrial applications, optimizing CNC cutting processes and reducing operational costs through enhanced tool wear prediction. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Predictive maintenance

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Blockchain-Based Multi-Cloud Data Storage System Disaster Recovery

Blockchain-Based Multi-Cloud Data Storage System Disaster Re...

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2023 IEEE International conference on systems, Man, and Cybernetics, SMC 2023

作者： Wang, Feiyu Zhou, Jian-Tao College of Computer Science Inner Mongolia University Inner Mongolia Hohhot China Engineering Research Center of Ecological Big Data Ministry of Education Natl. Loc. Jt. Eng. Research Center of Intelligent Information Processing Technology for Mongolian Inner Mongolia Engineering Laboratory for Cloud Computing and Service Software Inner Mongolia Key Laboratory of Social Computing and Data Processing Inner Mongolia Engineering Laboratory for Big Data Analysis Technology China

ISBN: (纸本)9798350337020

Cloud storage services have been used by most businesses and individual users. However, data loss, service interruptions and cyber attacks often lead to cloud storage services not being provided properly, and these incidents have caused financial losses to users. Second, traditional and single-cloud model disaster recovery services are no longer suitable for the current complex cloud storage systems. Therefore, a scheme to provide disaster recovery for cloud storage services in a multi-cloud storage environment is needed in real production. In this paper, we propose a disaster recovery scheme based on blockchain technology. The proposed scheme outlined in this study aims to address the issue of data availability within the cloud storage landscape. The proposed scheme achieves this goal by dividing data into hot and cold categories, verifying the integrity of copy data via blockchain technology, and utilizing blockchain networks to manage multi-cloud storage systems. Experimental findings demonstrate that the proposed scheme yields superior results in terms of computation and time overheads. © 2023 IEEE.

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Deep Learning Model for Intrusion Detection in SDN Networks 1

Deep Learning Model for Intrusion Detection in SDN Networks

引用

1st International conference on Optimization Techniques for Learning, ICOTL 2023

作者： Jyothsna, V. Sandhya, E. Swetha, Thammisetty Lokesh Kumar Reddy, P. Jyothsna, B. Bhasha, P. Mohan Babu University Erstwhile Sree Vidyanikethan Engineering College Dept. of Data Science Tirupati India Madanapalle India Madanapalle India Tirupati India Viswam Engineering College Department of Cse Madanapalle India Mohan Babu University Erstwhile Sree Vidyanikethan Engineering College Department of Data Science Tirupati India

ISBN: (纸本)9798350328042

Network security has grown in importance as computer network technology has progressed. Today networking technologies are vulnerable to a variety of security risks, and intrusion detection has emerged as a key tool for identifying network attacks. The architecture of software-Defined Networks (SDN) is utilized to offer network monitoring and function observation. In order to protect computer networks and systems, IDS serves a crucial role. In order to keep the SDN's security at a high level, an IDS is typically created to monitor the SDN's normal traffic. A SDN network's different security threats can be detected and managed using a number of strategies. For the purpose to identify the attacks, we combine LSTM with a deep convolution neural network (Deep CNN) driven by Grey Wolf Optimization (GWO). Effective intrusion detection requires a CNN feature extraction procedure, deep LSTM is used to detect network intrusion, and a deep CNN-LSTM is trained with a specially devised optimization strategy to improve detection performance. © 2023 IEEE.

关键词： Long short-term memory

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The Design and Implementation of a Control computer Based-on FPGA Core

The Design and Implementation of a Control Computer Based-on...

引用

Automation, Robotics and computer engineering (ICARCE), International conference on

作者： Chuanfei Qiu Chunting Zhang Quanzhi Zhou Xiaofang Lou Junyong Liu Hao Yang Ordnance NCO Academy Arm Engineering University of PLA Wuhan China

ISBN: (数字)9798331529505

ISBN: (纸本)9798331529512

According to the requirement of the system operation, a control computer monitors and controls a large number of key nodes, synthesizes a variety of excitation signals, obtains the angular state of the rotating mechanism, controls its rotation to the specified position. Based on an FPGA (Field-Programmable Gate Array) core, this paper develops a signal synthesizing module, a digital axis-angle conversion module and a W5500 Ethernet interface using a SOPC system that can be tailored and configured flexibly. It integrates the customed logic IPs into the SOPC (System-on-a-Programmable Chip) system of the Nios II architecture. The software system coordinates the operation of all modules. Finally, the control computer synthetically implements all its functions.

关键词： systems operation Robot kinematics Ethernet software systems Control systems Table lookup Logic IP networks Signal synthesis Field programmable gate arrays

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Development of Boost Converter System with Solar Charging Controller for Electrical Equipment 8

Development of Boost Converter System with Solar Charging Co...

引用

8th IEEE International conference on engineering Technologies and Applied Sciences, ICETAS 2023

作者： Ibrahim, Babul Salam Soomro, Dur Muhammad Sundarajoo, Sharman Shahirin, Mohd Fakhrul Gulf University for Science & Technology Electrical and Computer Engineering Department Kuwait Universiti Tun Hussein Onn Malaysia Faculty of Electrical and Electronic Engineering Johor Malaysia

ISBN: (纸本)9798350327090

There are numerous DC to DC energy alteration utilizations where the origin voltage needs to be transformed to a larger resulting voltage. Boost converters utilization includes energy equipment for semiconductor manufacturing supplies, ultrasound instruments, X-ray devices, solar systems, and mercury ion motors. Notably, this type of converter is used to step up the photovoltaic generator's voltage to the required load voltage in solar systems. Hence, this study's principal interest is to form and compose a boost converter and a solar charging controller circuit. This system aims to change the uncontrolled input of DC to a regulated output of DC with the wanted level of voltage. There are three critical procedures involved to produce a boost converter. The first process was to design. Next was to simulate, and the final process was to construct the boost converter and a solar charging controller circuit. The operational frequency was configured at 20 kHz, and a duty cycle of 50% was employed. In this study, the OrCAD PSpice, Multisim, and Proteus software environments were used to simulate the develop the circuit to obtain results. Every parameter value was obtained from the hardware. The values obtained were compared with the calculation, simulation, and hardware results from the boost converter circuit as a validation procedure. © 2023 IEEE.

关键词： Boost converter

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Design Matrix Factorization and Knowledge-Guided Clustering for Trust-Aware Cross-Domain Recommendation systems

Design Matrix Factorization and Knowledge-Guided Clustering ...

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software engineering and computer Science (CSECS), International conference on

作者： Jiaqi Chang Fusheng Yu School of Mathematical Sciences Beijing Normal University Beijing People's Republic of China

ISBN: (数字)9798331522216

ISBN: (纸本)9798331522223

The core challenge in designing an algorithm for trust-aware cross-domain recommendation systems lies in effectively integrating ratings from all domains (target-domain and source-domains) and trust relationships to improve recommendation performance in the target-domain. These systems involve two types of information fusion: intra-domain information fusion, which integrates intra-domain trust relationships and ratings within each domain (target-domain or source-domain), and cross-domain information fusion, which fuses information from all domains through inter-domain trust relationships as a bridge. The existing algorithms are limited in that they only address either intra-domain information fusion or cross-domain information fusion, failing to comprehensively utilize both intra-domain and inter-domain trust relationships for integrating information from all domains. To address this limitation, we propose a novel approach that combines inter-domain information fusion and cross-domain information fusion. Based on this approach, we design a matrix factorization and knowledge-guided clustering based trust-aware cross-domain collaborative filtering algorithm (MFKC _ TCCFA). Experimental results on a dataset show that MFKC_TCCFA outperforms existing state-of-the-art algorithms.

关键词： computer science Social networking (online) Fuses Collaborative filtering Soft sensors software algorithms Semantics Clustering algorithms Recommender systems software engineering

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A Survey on the Applications of Frontier AI, Foundation Models, and Large Language Models to Intelligent Transportation systems 5

A Survey on the Applications of Frontier AI, Foundation Mode...

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5th International conference on computer and Applications, ICCA 2023

作者： Shoaib, Mohamed R. Emara, Heba M. Zhao, Jun Nanyang Technological University School of Computer Science and Engineering Singapore Pyramids Higher Institute for Engineering and Technology Giza Governorate Egypt

ISBN: (纸本)9798350303254

This survey paper explores the transformative influence of frontier AI, foundation models, and Large Language Models (LLMs) in the realm of Intelligent Transportation systems (ITS), emphasizing their integral role in advancing transportation intelligence, optimizing traffic management, and contributing to the realization of smart cities. Frontier AI refers to the forefront of AI technology, encompassing the latest advancements, innovations, and experimental techniques in the field, especially AI foundation models and LLMs. Foundation models, like GPT-4, are large, general-purpose AI models that provide a base for a wide range of applications. They are characterized by their versatility and scalability. LLMs are obtained from fine-tuning foundation models with a specific focus on processing and generating natural language. They excel in tasks like language understanding, text generation, translation, and summarization. By leveraging vast textual data, including traffic reports and social media interactions, LLMs extract critical insights, fostering the evolution of ITS. The survey navigates the dynamic synergy between LLMs and ITS, delving into applications in traffic management, integration into autonomous vehicles, and their role in shaping smart cities. It provides insights into ongoing research, innovations, and emerging trends, aiming to inspire collaboration at the intersection of language, intelligence, and mobility for safer, more efficient, and sustainable transportation systems. The paper further surveys interactions between LLMs and various aspects of ITS, exploring roles in traffic management, facilitating autonomous vehicles, and contributing to smart city development, while addressing challenges brought by frontier AI and foundation models. This paper offers valuable inspiration for future research and innovation in the transformative domain of intelligent transportation. © 2023 IEEE.

关键词： Intelligent systems

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