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检索条件"机构=Dept. of Computer and Electrical Engineering and Computer Science"

共 55359 条记录，以下是151-160 订阅

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Examination of PHY Layer Features in DECT-2020 and LTE-M Networks 10

Examination of PHY Layer Features in DECT-2020 and LTE-M Net...

引用

10th IEEE Information Technology International Seminar, ITIS 2024

作者： Kizilirmak, Refik Caglar Askarov, Satzhan Nazarbayev University Dept. of Electrical and Computer Engineering Astana Kazakhstan

ISBN: (纸本)9798331521295

This paper provides a comparative analysis of the physical layer (PHY) characteristics of DECT-2020 NR and LTE-M, two critical standards for IoT communication. DECT-2020 NR, developed by ETSI, is intended for industrial IoT applications and provides low-latency, reliable communication in high-density environments. In contrast, LTE-M, which is a member of the 3GPP family, is designed to provide broad coverage, energy efficiency, and mobility support for low-power devices. The study emphasizes the distinctions between the standards regarding data rates, modulation schemes, and frequency bands, displaying how each standard fulfills specific IoT requirements. Furthermore, it highlights the complementing characteristics of DECT-2020 NR and LTE-M, by providing performance insights such as bit-error rate (BER) analysis and spectral efficiency. © 2024 IEEE.

关键词： Spectrum efficiency

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Chatbot Based on Emotions Using Deep Learning 1

Chatbot Based on Emotions Using Deep Learning

引用

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

作者： Nirupa, V. Renuka, G.B. Naga Lakshmi, B. Sumanth Kumar, C.P. Rudra Sekhar Reddy, A. Paramesh, J. Dept. of Computer Science & Engineering Madanapalle India Dept. of Computer Science & Engineering Anantapur India

ISBN: (纸本)9798350328042

Human emotions are unpredictable as they change very frequently. Human emotions areinvoluntary mental states of feelings and are accompanied by physiological changes. Emotions which can be detected through the facial expressions play a major role and are very much important for non-verbal communication as they reflect on their faces. In the process of developing computer modeling of human's emotions, a lot researches have been made. Therefore, a chatbot detecting the emotions can be a better approach for detecting emotions. In this study, it demonstrate that Convolutional Neural Networks (CNNs) offer a superior method for detecting human emotions and develop a deep learning model that can accurately classify the facial expressions. The FER 2013 dataset was used in this study's training. The evaluation of the suggested approach produces pretty accurate findings, which could inspire academics to develop a Chabot model based on emotions in the future. © 2023 IEEE.

关键词： Convolutional neural networks

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Adaptive Kalman Filter Based LiDAR aided GNSS/IMU Integrated Navigation System for High-Speed Autonomous Vehicles in Challenging Environments

Adaptive Kalman Filter Based LiDAR aided GNSS/IMU Integrated...

引用

2024 International Technical Meeting of The Institute of Navigation, ITM 2024

作者： Lee, Jae-Un Won, Jong-Hoon Dept. of Electrical and Computer Engineering Inha University Korea Republic of

ISBN: (纸本)9780936406367

This paper presents an advanced localization method for autonomous vehicles using an adaptive Kalman filter integrated with LiDAR-aided GNSS/IMU systems, addressing the challenges of GNSS reliability and precision in urban high speed driving scenarios. This approach combines multiple sensors, including GNSS, IMU, and LiDAR, with adaptive estimation method to enhance the accuracy of position estimation. The adaptive Kalman filter effectively counters the limitations of GNSS by employing fault detection and exclusion and utilizing LiDAR-based localization method for real-time correction in case of GNSS errors. Experiments conducted with generated critical GNSS errors in a test vehicle driving in urban environments, demonstrate the improved reliability and accuracy in false alarm detection and position estimation of the system. This research contributes to autonomous driving technology, offering a robust solution for precise localization in dynamic urban environments, and is adaptable to a wide range of unmanned mobility systems, signifying a considerable advancement in the field of autonomous navigation. © 2024, Institute of Navigation

关键词： Autonomous vehicles

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LiDAR Point Cloud Descriptor for UAM Place Recognition with Point Cloud Map

LiDAR Point Cloud Descriptor for UAM Place Recognition with ...

引用

2024 International Technical Meeting of The Institute of Navigation, ITM 2024

作者： Im, Ji-Ung Lee, Yong-Ha Won, Jong-Hoon Dept. of Electrical and Computer Engineering Inha University Korea Republic of

ISBN: (纸本)9780936406367

Accurate localization is a critical element for the successful and safe operation of Urban Air Mobility (UAM). In this study, we present a method for UAM place recognition that utilizes point cloud map (PCM) data and a virtual LiDAR sensor model. The PCM-based approach enables the creation of a virtual descriptor database (VDD) for place recognition. To generate descriptors invariant to translation and rotation, we introduce a region of interest sampling method and a feature point detection approach, effectively minimizing altitude influence. We also outline a technique for creating translation and rotation invariant descriptors through the integration of robust feature extraction methods. Furthermore, we conduct an experiment utilizing a game engine-based UAM simulator to validate the proposed method. PCM and VDD are generated through the simulator, and a quantitative analysis of descriptors and place recognition is subsequently carried out. © 2024, Institute of Navigation

关键词： Air mobility

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UniNetProbe: A Comprehensive 5G Research Testbed Framework 29

UniNetProbe: A Comprehensive 5G Research Testbed Framework

引用

29th IEEE International Workshop on computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2024

作者： Papaioannou, P. Tziavas, G. Giannopoulos, D. Tranoris, C. Denazis, S. University of Patras Dept. of Electrical and Computer Engineering Patras Greece

ISBN: (纸本)9798350377644

A well-defined and well-designed experimentation process is crucial for meaningful research outcomes. This paper introduces a framework aimed at streamlining the experimentation process in networking testbeds, consisting of five key components: i) the experiment driver, containing available experiment tools, ii) the control tools to enhance capabilities and create complex scenarios, iii) the monitoring implementation, providing researchers with meaningful insights into gathered metrics, iv)the database component, which will be the main repository for storing experimental results and v) the analytics component, which could provide insights on patterns and hidden knowledge found in the extracted data, with the help of algorithms and artificial intelligence. The framework can be applied to various networking testbeds and is followed by descriptions of two Proof of Concepts (PoCs) demonstrating its implementation. © 2024 IEEE.

关键词： 5G mobile communication systems

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Classification and Prediction of Alzheimer's Disease using Deep Learning 7

Classification and Prediction of Alzheimer's Disease using D...

引用

7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023

作者： Brindha, D. Ebenezer, V. Selvaraj, E. Jackson Bevin Geoff, D.M. Dileep, B. Bethina Nambi, M. Thirumalai Dept. of Computer Science and Engineering Coimbatore India Dept. of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350397253

This study has proposed a novel technique for performing object detection and image classification with a Convolutional Neural Network (CNN) architecture. Nevertheless, employing a 2D CNN architecture to identify a lot of patients as AD or MCI based on 3D MR Images becomes challenging when dealing with hundreds of MRI images that are highly similar in nature. It provides a solution to this problem that streamlines the concept of classification of patients based on 3D MRI by exploiting 2D data produced by the CNN structure. In this method, 2D characteristics from MRI are extracted and then converted by using an appropriate Machine Learning (ML) algorithm for categorization. © 2023 IEEE.

关键词： Magnetic resonance imaging

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Error Analysis and Evaluation of Approximate Adder Circuits in 180nm Technology 19

Error Analysis and Evaluation of Approximate Adder Circuits ...

引用

19th Iranian Conference on Intelligent Systems, ICIS 2024

作者： Yousefnejhad, Reza Omidi, Reza University of Zanjan Dept. Electrical and Computer Engineering Zanjan Iran

ISBN: (纸本)9798331507565

The connection between approximate computations and artificial intelligence arises from employing algorithms and methodologies as exemplars for trained models across machine learning, neural networks, reinforcement learning, and various other artificial intelligence methodologies. This paper delves into the application of approximation techniques in digital adder circuits, exploring the potential benefits in terms of energy efficiency, performance enhancement, and computational speed. By examining various types of approximate adders and their implementation strategies, the study investigates the trade-off between accuracy and efficiency. The research focuses on designing adders that achieve optimal performance while minimizing hardware overhead. Through extensive error analysis, the study sheds light on the feasibility of approximation methods in practical applications, demonstrating their effectiveness in mitigating energy and performance challenges. The findings underscore the significance of approximation techniques as a viable solution for optimizing hardware design in modern computing systems. © 2024 IEEE.

关键词： Adders

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Utilizing Machine Learning for Sensor Fault Detection in Wireless Sensor Networks 26

Utilizing Machine Learning for Sensor Fault Detection in Wir...

引用

26th International Conference on Advanced Communications Technology, ICACT 2024

作者： Abdulkarim, Abubakar Ehile, Israel Ehile Kizilirmak, Refik Caglar Nazarbayev University Dept. of Electrical and Computer Engineering Astana Kazakhstan

ISBN: (纸本)9791188428120

This paper discusses the utilization of machine learning for sensor fault detection in Wireless Sensor Networks (WSNs). The WSN comprises many wireless devices with limited processing power, battery life, and memory capacity. Successfully detecting faulty sensors within a WSN can lead to increased efficiency in the fault detection system, reduced network traffic, and lower power consumption. To enhance the network management, researchers sought a technique for detecting sensor defects. In this paper, machine learning techniques are employed to address the issue of failure detection in WSNs. The utilization of machine learning techniques, specifically Kernel Support Vector Machine (SVM) and Artificial Neural Network (ANN), are demonstrated. The paper further compares the performances of the chosen machine learning algorithms in classifying sensor data as faulty or fault-free. The problem is treated as a binary classification problem. The findings of this study contribute to the development of effective fault detection systems in WSNs. © 2024 Global IT Research Institute - GIRI.

关键词： Wireless sensor networks

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Enhancing Inter-Satellite Data Relay in Dynamic Space Communication 26

Enhancing Inter-Satellite Data Relay in Dynamic Space Commun...

引用

26th International Conference on Advanced Communications Technology, ICACT 2024

作者： Kizilirmak, Refik Caglar Ehile, Israel Ehile Kabdrashev, Bekzat Khvan, Sergey Nazarbayev University Dept. of Electrical and Computer Engineering Astana Kazakhstan

ISBN: (纸本)9791188428120

In this paper, we explore the design and operations of an inter-satellite data relay network, which includes Low Earth Orbit (LEO), Medium Earth Orbit (MEO), and Geo-stationary Orbit (GEO) satellites. Due to the different orbiting speeds and dynamic behaviors of these satellite constellations, we consider Delay-Tolerant Networking (DTN) between them and implement contact graph routing (CGR) at the layer-3 and Licklider Transmission Protocol (LTP) at layer-4. We base our analysis on a realistic space scenario where satellite locations and movements over time are extracted from a real-time satellite database. We demonstrate end-to-end latency and goodput of a file transfer through the satellite network under consideration. © 2024 Global IT Research Institute - GIRI.

关键词： Delay tolerant networks

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Inexpert Sensor Fusion Using an Adaptive Kalman Filter Approach 5

Inexpert Sensor Fusion Using an Adaptive Kalman Filter Appro...

引用

5th IEEE Middle East and North Africa COMMunications Conference, MENACOMM 2025

作者： Saab, Samer Lebanese American University Dept. of Electrical and Computer Engineering Byblos Lebanon

ISBN: (数字)9798331519957

ISBN: (纸本)9798331519957

Sensor fusion in complex systems often relies on well-calibrated, expert sensors to achieve accurate and reliable outcomes. Integrating untrained or inexpert sensors into such networks poses significant challenges such as the cost associated with manually training them for the overall network objective. This paper presents an adaptive Kalman filter (AKF) approach to seamlessly incorporate an inexpert sensor into an established sensor network. By leveraging the existing trained sensors, the proposed method dynamically adjusts the inexpert sensor's parameters, enabling it to contribute effectively to the overall system. We evaluate the performance of this approach using absolute errors and Kullback-Leibler (KL) divergence. Preliminary results show that the proposed AKF achieves a KL divergence on the order of 10-4 in a binary classification task, significantly outperforming a recursive density estimation method. It is also shown that in a diverging multivariate target tracking problem, after being trained, two inexpert sensors successfully contribute to a sensor network, even after temporarily removing the expert sensor. © 2025 IEEE.

关键词： Kalman filters

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