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Deep Learning Based Signal Detection for Quadrature Spatial Modulation System

China Communications 2024年第10期21卷 78-85页

作者： Shu Dingyun Peng Yuyang Yue Ming Fawaz AL-Hazemi Mohammad Meraj Mirza School of Computer Science and Engineering Macao University of Science and TechnologyMacaoChina Department of Computer and Network Engineering University of JeddahSaudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia

With the development of communication systems, modulation methods are becoming more and more diverse. Among them, quadrature spatial modulation(QSM) is considered as one method with less capacity and high efficiency. In QSM, the traditional signal detection methods sometimes are unable to meet the actual requirement of low complexity of the system. Therefore, this paper proposes a signal detection scheme for QSM systems using deep learning to solve the complexity problem. Results from the simulations show that the bit error rate performance of the proposed deep learning-based detector is better than that of the zero-forcing(ZF) and minimum mean square error(MMSE) detectors, and similar to the maximum likelihood(ML) detector. Moreover, the proposed method requires less processing time than ZF, MMSE,and ML.

关键词： bit error rate complexity deep learning quadrature spatial modulation

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Predicting from a Different Perspective: A Re-ranking Model for Inductive Knowledge Graph Completion 21st

Predicting from a Different Perspective: A Re-ranking Mode...

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21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024

作者： Iwamoto, Yuki Kaneiwa, Ken Department of Computer Network Engineering Graduate School of Informatics and Engineering The University of Electro-Communications Tokyo Japan

ISBN: (纸本)9789819601240

Rule-induction models have demonstrated great power in the inductive setting of knowledge graph completion. In this setting, the models are tested on a knowledge graph entirely composed of unseen entities. These models learn relation patterns as rules by utilizing subgraphs. Providing the same inputs with different rules leads to differences in the model’s predictions. In this paper, we focus on the behavior of such models. We propose a re-ranking-based model called ReDistLP (Re-ranking with a Distinct Model for Link Prediction). This model enhances the effectiveness of re-ranking by leveraging the difference in the predictions between the initial retriever and the re-ranker. ReDistLP outperforms the state-of-the-art methods in 2 out of 3 benchmarks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Knowledge graph

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Baby Suffocation Prediction System 2

Baby Suffocation Prediction System

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2nd International Conference on Advanced Innovations in Smart Cities, ICAISC 2025

作者： Atwah, Rasha Jamal Alharthi, Mashael Alharbi, Lamees Bashnini, Jana Al-Sharif, Nujoud College of Computer Science and Engineering University of Jeddah Department of Computer and Network Engineering Jeddah Saudi Arabia

ISBN: (纸本)9798331506995

The number of suffocation cases among babies during their sleeping is increased due to the presence of blankets and sheets. Therefore, it is crucial to have a reliable system that can monitor babies during bedtime. In order to ensure the safety of children, we have developed an AI-based comprehensive smart system that provides real-time monitoring to predict suffocation incidents as soon as possible. The proposed system offers babies protection by promoting suffocation prediction within an appropriate time frame. The system is built based on the BlazeFace detection model to monitor the baby and send notifications and sound alarms if the baby's face is covered or missing for a certain amount of time. The notification is sent through the mobile application to alert the baby's parents or caregivers if there is a suffocation case that may occur. Additionally, an audible alarm is activated to grab the attention of the child's parents or caregivers and ensure quick intervention. We conducted an experiment to assess the system's effectiveness, and the prototype shows adequate accuracy and quick response. There is still space for further development, which we suggest as future work. © 2025 IEEE.

关键词： Interactive computer systems

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Smart Visual Pollution Detection System 2

Smart Visual Pollution Detection System

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2nd International Conference on Advanced Innovations in Smart Cities, ICAISC 2025

作者： Alsolami, Rothana Atwah, Rasha Alajlani, Ranad Alhajaili, Sara College of Computer Science and Engineering University of Jeddah Department of Computer and Network Engineering Jeddah Saudi Arabia

ISBN: (纸本)9798331506995

As Saudi Arabia moves forward with its Vision 2030 initiative to improve the quality of life and services for its people, visual pollution continues to have a negative impact on the environment. However, assessing and addressing visual pollution in cities remains a challenging task due to its subjective nature and complexity. One of the main challenges is the lack of powerful and reliable intelligent systems for detecting visual pollution. To tackle this issue, we have invested our efforts in developing a cost-effective intelligent system using advanced technologies like the Internet of Things (IoT) and computer vision. This system will help detect and monitor visual pollution, including items such as water cans, paper, and plastic cups. Our smart system uses sensors like cameras to collect data and then analyzes it to display the information on a user-friendly control panel for administrators to monitor the area under study. The system has been successfully tested under various scenarios and has shown promising accuracy rates, reaching up to 87% in detecting recyclable materials. We believe that there are numerous opportunities to further enhance the performance of future designs. © 2025 IEEE.

关键词： Detection Internet of Things (IoT) Smart Cities Visual Pollution

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Enhancing Security and Flexibility in Smart Locker Systems: A Multi-Authentication Approach with IoT Integration 21

Enhancing Security and Flexibility in Smart Locker Systems: ...

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21st International Learning and Technology Conference, L and T 2024

作者： Balfaqih, Mohammed University of Jeddah Department of Computer and Network Engineering Jeddah Saudi Arabia

ISBN: (纸本)9798350393569

The past decade has witnessed the widespread integration of the Internet of Things (IoT) in the evolution of smart locker systems. However, many existing systems rely on a single authentication method, limiting their adaptability. These systems fail to account for potential unavailability of the chosen authentication method due to issues such as lost access cards, damaged cameras, or malfunctioning devices. Furthermore, the vulnerability of relying on a single authentication method, without considering dual-authentication approaches, poses a security risk, as unauthorized access could occur through eavesdropping or code interception. This paper addresses these shortcomings by introducing a smart locker system that incorporates multiple authentication methods, including dual authentication (utilizing both phone number and One Time Password (OTP)), fingerprint recognition, face recognition, and emergency code. Leveraging IoT technology, the system offers a range of authorization methods to grant access permission. The dual authentication method serves as the foundational security layer, significantly enhancing the locker's overall security. The system is developed, implemented, and rigorously evaluated under various scenarios. The outcomes demonstrate superior performance compared to existing systems, particularly in terms of accuracy and flexibility. © 2024 IEEE.

关键词： Internet of things

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Enhancing the Reliability of NR-V2X Sidelink Broadcast through Relay 29

Enhancing the Reliability of NR-V2X Sidelink Broadcast throu...

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29th IEEE Asia Pacific Conference on Communications, APCC 2024

作者： Aoki, Shiro Tang, Suhua The University of Electro-Communications Department of Computer and Network Engineering Tokyo Japan

ISBN: (纸本)9798331517816

NR-V2X sidelink (SL) broadcast is used for the real-time exchange of position and other information between adjacent vehicles. However, its reliability degrades much in non-line-of-sight environments, where Blind ReTransmission (BReTX) does not work well. Relay can effectively address this issue, and a relaybased SL broadcast method was proposed in previous work. However, in this method, each vehicle must detect communication Link Quality (LQ) and exchange LQ Indicators (LQIs) with its neighbors to select a proper relay, which causes much overhead. This paper aims to improve the relay-based SL broadcast from two aspects. (i) To reduce the overhead, we suggest aggregating LQIs per direction, making the overhead of sharing LQIs irrelevant to the number of vehicles. (ii) To further improve reliability, we use an explicit ACK to deal with the potential failure of the transmission from the source vehicle to the relay. Using explicit ACKs allows the source vehicle to retransmit the packet until the relay vehicle correctly receives it, after which the relay vehicle handles the remaining retransmissions. Simulation results confirm that the proposed method, RReTX-ACK, improves the packet dissemination rate by approximately 8.30% within a 200 m distance from the source vehicle in an intersection scenario, compared to BReTX without using relay vehicles. © 2024 IEEE.

关键词： Magnetic levitation vehicles

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Design of Miniature Automatic Driving Vehicle Controlled by Camera Image Processing

Design of Miniature Automatic Driving Vehicle Controlled by ...

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2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Kojima, Akira Hiroshima City University Department of Computer and Network Engineering Hiroshima Japan

ISBN: (纸本)9798350324136

We are developing a miniature self-driving car for the design contest at ICCE2024, which will be driven automatically by image processing of camera images. Our implementation uses a AMD/Xilinx SoC FPGA as the central controller. The hardware of the programmable logic part of the SoC FPGA is used for object detection in the camera image and PWM control of the motors. Other processes are software-controlled by the processor of the SoC FPGA. © 2024 IEEE.

关键词： Autonomous driving DPU Object detection Real-Time image processing SoC FPGA

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A Base Station Deployment Algorithm for Wireless Positioning Considering Dynamic Obstacles

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computers, Materials & Continua 2025年第3期82卷 4573-4591页

作者： Aiguo Li Yunfei Jia Department of Network Engineering Xi’an University of Science and TechnologyXi’an710600China College of Computer Science and Technology Xi’an University of Science and TechnologyXi’an710600China

In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of *** studies focus on optimizing base station deployment under the assumption of static obstacles,aiming to maximize the perception coverage of wireless RF(Radio Frequency)signals and reduce positioning blind ***,in practical security systems,obstacles are subject to change,necessitating the consideration of base station deployment in dynamic ***,research in this area still needs to be *** paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm(DIE-BDA)to address this *** algorithm considers the dynamic alterations in obstacle locations within the designated *** determines the requisite number of base stations,the requisite time,and the area’s practical and overall signal coverage *** experimental results demonstrate that the algorithm can calculate the deployment strategy in 0.12 s following a change in obstacle *** results show that the algorithm in this paper requires 0.12 s to compute the deployment strategy after the positions of obstacles *** 13 base stations,it achieves an effective coverage rate of 93.5%and an overall coverage rate of 97.75%.The algorithm can rapidly compute a revised deployment strategy in response to changes in obstacle positions within security systems,thereby ensuring the efficacy of signal coverage.

关键词： Wireless positioning base station deployment dynamic obstacles dynamic obstacle wireless positioning

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Using dummy data for RFID tag and reader authentication

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Digital Communications and networks 2022年第5期8卷 804-813页

作者： Baha’A.Alsaify Dale R.Thompson Abdallah Alma'aitah Jia Di Department of Network Engineering and Security Jordan University of Science and TechnologyIrbid21163Jordan Computer Science and Computer Engineering Department University of ArkansasFayetteville72701ARUSA

Radio-Frequency IDentification(RFID)technology is an essential enabler of a multitude of intelligent *** robust authentication of RFID system components is critical in providing trustworthy data delivery from/to *** this paper,we propose an authentication protocol based on monitoring the transmissions between readers and tags in the *** proposed authentication scheme is based on injecting decoys within the exchanged communications(between RFID readers and tags)and is used in the authentication ***,the proposed authentication scheme is mathematically modeled and validated using extensive *** simulations results show that the proposed scheme provides a 100%confidence level in the authentication of tags and detection of compromised readers.

关键词： RFID Authentication Dummy data Security Decoys

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A Literature Review on Model Conversion, Inference, and Learning Strategies in EdgeML with TinyML Deployment

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computers, Materials & Continua 2025年第4期83卷 13-64页

作者： Muhammad Arif Muhammad Rashid Department of Computer Science and Artificial Intelligence Umm Al-Qura UniversityMakkah Al-Mukarama21955Saudi Arabia Department of Computer and Network Engineering Umm Al-Qura UniversityMakkah Al-Mukarama21955Saudi Arabia

Edge Machine Learning(EdgeML)and Tiny Machine Learning(TinyML)are fast-growing fields that bring machine learning to resource-constrained devices,allowing real-time data processing and decision-making at the network’s ***,the complexity of model conversion techniques,diverse inference mechanisms,and varied learning strategies make designing and deploying these models ***,deploying TinyML models on resource-constrained hardware with specific software frameworks has broadened EdgeML’s applications across various *** factors underscore the necessity for a comprehensive literature review,as current reviews do not systematically encompass the most recent findings on these ***,it provides a comprehensive overview of state-of-the-art techniques in model conversion,inference mechanisms,learning strategies within EdgeML,and deploying these models on resource-constrained edge devices using *** identifies 90 research articles published between 2018 and 2025,categorizing them into two main areas:(1)model conversion,inference,and learning strategies in EdgeML and(2)deploying TinyML models on resource-constrained hardware using specific software *** the first category,the synthesis of selected research articles compares and critically reviews various model conversion techniques,inference mechanisms,and learning *** the second category,the synthesis identifies and elaborates on major development boards,software frameworks,sensors,and algorithms used in various applications across six major *** a result,this article provides valuable insights for researchers,practitioners,and *** assists them in choosing suitable model conversion techniques,inference mechanisms,learning strategies,hardware development boards,software frameworks,sensors,and algorithms tailored to their specific needs and applications across various sectors.

关键词： Edge machine learning tiny machine learning model compression inference learning algorithms

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