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Joint Angular-Frequency Power Spectrum Sensing Based on K-Means Clustering

Joint Angular-Frequency Power Spectrum Sensing Based on K-Me...

引用

2023 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications technology, IAICT 2023

作者： Jati, Ahmad Nugroho Wibowo, Sigit Basuki Ariananda, Dyonisius Dony Universitas Gadjah Mada Dept. Electrical Engineering and Information Technology Indonesia

ISBN: (纸本)9798350313635

The critical component in the cognitive radio (CR) network is spectrum sensing (SS) used to locate the accessible spectrum and to minimize interference with the licensed users (LUs). The CR SS could take into account the direction-of-arrival (DoA) of signals sent by LUs from the perspective of a secondary user (SU) to further improve the spectrum utility. This prevents the SU to interfere the LU signals by occupying a frequency band that the LU is currently using but aiming its transmission at a specific angle away from the LU. We use a uniform linear array, sample the signal received by each antenna, compute the correlation between samples, apply classical beamforming, and compute the discrete Fourier transform to reconstruct the complete two-dimensional angular-frequency power spectrum. In order to determine whether LUs or other SUs are currently occupying a certain frequency band or not, we use K-means clustering to compute the detection threshold. Numerical studies are carried out to demonstrate that the threshold based on the K-means clustering is applicable to detect signals from LUs based on the result of frequency and DoA power SS. © 2023 IEEE.

关键词： Cognitive radio

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Text to Photo-Realistic Image Synthesis using Generative Adversarial Networks 2

Text to Photo-Realistic Image Synthesis using Generative Adv...

引用

2nd IEEE International Conference on Futuristic Technologies, INCOFT 2023

作者： Rao, Abhishek S. Bhandarkar, P Adokshaj Devanand, Padmashali Akshay Shankar, Pratheek Shanti, Srinivas Karthik Pai, B.H. Nmam Institute of Technology Dept. of Information Science & Engineering Nitte India

ISBN: (纸本)9798350308846

Innovative design patterns have traditionally been constrained by time-consuming and expertise-intensive methods, limiting diversity and creativity in design. To overcome these challenges, our research focuses on revolutionizing the design process by leveraging Generative Adversarial Networks (GANs). Our goal is to offer an affordable and cutting-edge solution that enables the creation of unique design patterns based on user input text. By harnessing the power of GANs, we can generate high-resolution images, reducing the reliance on expensive designers and fostering creativity and idea generation in the design sector. Our methodology involves building upon a diverse dataset of sunflower images and associated text data borrowed from the Oxford-102 flowers dataset. We meticulously collect, clean, and normalize this dataset to ensure optimal training. U sing an encoder-decoder architecture, we train a GAN -based generative model to produce remarkable sunflower patterns. To enhance usability, we have developed a user-friendly graphical user interface (GUI) that allows users to input text and receive corresponding sunflower images seamlessly. Our current model has exhibited promising results, achieving an inception score of 3.45 ± 0.05 in generating sunflower patterns. These outcomes demonstrate the feasibility of our approach, which not only reduces design costs but also fosters innovation and ingenuity within the industry. By making this solution publicly accessible, we aim to support local businesses and individuals with limited finances in creating distinctive design patterns. © 2023 IEEE.

关键词： deep learning generative adversarial networks inception score text to image Synthesis text-conditioned auxiliary classifier

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Drones in Forest Fire Mitigation

Drones in Forest Fire Mitigation

引用

2023 International Conference on Electrical, Computer, Communications and Mechatronics engineering, ICECCME 2023

作者： Nayak, Vaishnavi Y. Rao, Vaishnavi G. Jagruthi, H. Bnm Institute of Technology Dept. Information Science and Engineering Bengaluru India

ISBN: (纸本)9798350322972

The proposed system in this paper utilizes drones and Convolutional Neural Networks (CNN) for fire detection. Traditional smoke sensors can be slow and cost-inefficient, making them less suitable for early fire detection. The authors analyze the scope of CNN and related methodologies for detecting fire and propose a novel system that uses optical cameras mounted on drones to detect and identify forest fire threats in real-time. The system also aims to notify interested parties and authorities by providing alerts and important information such as the specific location and environmental conditions. The use of drones equipped with optical cameras is an innovative approach to early fire detection. The ability of drones to capture images and transmit them in real-time enables the detection and identification of forest fires as they occur. The use of CNN allows for the efficient and accurate analysis of the captured images, resulting in a reliable detection system. Additionally, the system can send alerts to authorities and interested parties, allowing for timely and appropriate action to be taken. Overall, the proposed system has the potential to revolutionize early fire detection and response. The use of modern technology such as drones and CNN can greatly improve the efficiency and accuracy of fire detection, ultimately leading to a safer and more secure environment. © 2023 IEEE.

关键词： Deforestation

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A Novel Phase Generation Mechanism for PAPR Reduction in SLM-based OFDM Systems 23

A Novel Phase Generation Mechanism for PAPR Reduction in SLM...

引用

11th International Conference on Computer and Communications Management, ICCCM 2023

作者： Yang, Chih-Yao Chu, Hung-Chi Liang, Hsin-Ying Dept. of Information and Communication Engineering Chaoyang University of Technology Taichung Taiwan

ISBN: (纸本)9798400707735

Orthogonal frequency division multiplexing (OFDM) is a widely used digital modulation technique in wireless communication systems. However, its high peak-to-average power ratio (PAPR) may cause nonlinear distortion during transmission. Selective mapping (SLM) is a popular technique to reduce PAPR by generating multiple candidate signals for phase perturbation and selecting the one with the smallest PAPR. However, the traditional SLM technology uses a random phase generation mechanism, lacks systematic design, and has high circuit complexity. Furthermore, generating multiple candidate signals requires inverse fast Fourier transform (IFFT), resulting in increased computational complexity. To address these issues, this paper proposes a system design of a phase generation mechanism using randomly sorted Walsh-Hadamard matrices, and introduces a phase picking mechanism to reduce computational complexity. The simulation results show that the recommended method achieves a similar improved PAPR performance as traditional SLM technology when the selection mechanism is not used. However, when the recommended method incorporates the selection mechanism, it achieves a sub-optimal improved PAPR performance. It is worth noting that this paper considers the number of Inverse Fast Fourier Transform (IFFT) operations, and with the addition of the selection mechanism, the number of operations is significantly reduced by about 35%. This reduction in operations greatly reduces the overall computational complexity. These findings highlight the systematic and efficient nature of the proposed phase generation method in SLM-based OFDM systems, effectively reducing computational complexity while significantly reducing PAPR. © 2023 ACM.

关键词： Peak to average power ratio

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Capacitive Wireless Power Transfer Independent of Load Impedance Fluctuation with Transfer Distance

Capacitive Wireless Power Transfer Independent of Load Imped...

引用

2023 IEEE/MTT-S International Microwave Symposium, IMS 2023

作者： Naka, Yasumasa Ishiwata, Akihiko Tamura, Masaya Toyohashi University of Technology Dept. of Electrical and Electronic Information Engineering Japan

ISBN: (纸本)9798350347647

The transfer distance variation of a coupler is a significant issue for capacitive wireless power transfer (WPT). This paper presents a capacitive WPT system independent of load impedance fluctuation with the transfer distance for underwater drones operating in freshwater. A capacitive coupler with opposite feeding is the primary design element. Maximum efficiency and stable power transmission are provided that a phase difference between the feeding point and the coupler electrode edge becomes p/2, and an unloaded Q-factor of surrounded dielectric is large, such as freshwater. Furthermore, the constant-current output inverter suppresses input power to the coupler at a distance where the efficiency drops, automatically reducing electricity waste. Finally, their prototypes are demonstrated at a transfer distance of 20, 50, and 100 mm in tap water. © 2023 IEEE.

关键词： Energy transfer

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A Comprehensive Analysis on 5G, IoT and Its Impact on Agriculture and Healthcare 2

A Comprehensive Analysis on 5G, IoT and Its Impact on Agricu...

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2nd International Conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023

作者： Jape, Shraddha Dattatray Mungase, Kaveri Vitthal Thite, Vaishnavi Bhausaheb Jadhav, Devyani Sanjivani College of Engineering Dept. Information Technology Maharashtra Kopargaon India

ISBN: (纸本)9798350325799

The advent of fifth-generation (5G) wireless technology, coupled with the Internet of Things (IoT), has revolutionized various industries, including agriculture and healthcare. This research paper provides a comprehensive review of the applications of 5G and IoT in these sectors, highlighting the transformative potential and benefits they offer. In agriculture, 5G and IoT have facilitated the development of smart farming systems that enable precise and data-driven decision-making. Through the integration of sensors, drones, and autonomous machinery, farmers can monitor crop health, soil conditions, and climate parameters in real-time. This information can be analyzed to optimize irrigation, fertilization, and pest control, leading to enhanced crop yields, reduced resource consumption, and increased sustainability. In the healthcare sector, 5G and IoT have discovered patient care and management. By connecting medical devices, wearables, and health monitoring systems, healthcare professionals can remotely monitor patients' vital signs, detect anomalies, and provide timely interventions. Moreover, 5G enables the transmission of large volumes of medical data, such as high-resolution images and real-time video consultations, facilitating telemedicine and remote surgeries. This has proven invaluable in providing healthcare services in underserved areas and improving overall patient outcomes. The findings of this research highlight the transformative impact of 5G and IoT in agriculture and healthcare, emphasizing their potential to address critical challenges faced by these sectors. © 2023 IEEE.

关键词： Internet of things

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Constructing Phase Generation Mechanism based on Recursive Structure for PAPR Reduction in SLM-OFDM Systems 23

Constructing Phase Generation Mechanism based on Recursive S...

引用

11th International Conference on Computer and Communications Management, ICCCM 2023

作者： Meng, Po-Lin Chu, Hung-Chi Liang, Hsin-Ying Dept. of Information and Communication Engineering Chaoyang University of Technology Taichung Taiwan

ISBN: (纸本)9798400707735

Selective Mapping (SLM) is a popular technique used to reduce the Peak-to-Average Power Ratio (PAPR) in Orthogonal Frequency Division Multiplexing (OFDM) systems. Recently, Ali et al. proposed a systematically structured phase generation mechanism and applied it to the SLM scheme to generate scrambling phase sequences, known as PRS-SLM. PRS-SLM primarily utilizes a seed matrix for recursive construction to generate the scrambling phase sequences required for the SLM scheme. Although PRS-SLM can improve the circuit complexity of the phase generation mechanism in SLM, the optimal design of the seed matrix and its recursive construction to achieve better PAPR reduction performance in SLM remains an unresolved issue. Therefore, this paper proposes four recursive construction methods for generating scrambling phase sequences, and simulation results show that the proposed methods not only retain a systematic structure design but also achieve similar PAPR reduction performance as traditional SLM. © 2023 ACM.

关键词： Peak to average power ratio

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Multi-Objective Cooperative control of Vehicle Platoon Based on Fuzzy MPC 26

Multi-Objective Cooperative Control of Vehicle Platoon Based...

引用

26th International Conference on Industrial technology, ICIT 2025

作者： Zhu, Wanying Yin, Yunfei Xu, Zhanguo Wei, Yuanlong Zeng, Shenjun Harbin Institute of Technology Dept. of Traffic Information and Control Engineering Harbin China Jilin University Dept. of Traffic Information and Control Engineering Changchun China

ISBN: (纸本)9798331521950

To simultaneously optimize multiple performances of the cooperative adaptive cruise control (CACC) system, a fuzzy MPC control strategy is proposed to achieve multi-objective cooperative control for electric vehicle platoons. The longitudinal kinematic analysis of the vehicle platoon is conducted to establish the platoon model. Based on the analysis of system performance, safety, comfort, and following performance are selected as the system's performance indexes, and a comprehensive performance function for the MPC is constructed. Fuzzy control theory is employed to optimize the weight parameters, enabling the CACC system to adapt to different conditions. The effectiveness and reliability of the fuzzy MPC control strategy are verified through co-simulation using Carsim and Simulink. © 2025 IEEE.

关键词： control system analysis

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Tourist Place Classification Using Topic Modeling Algorithms 56

Tourist Place Classification Using Topic Modeling Algorithms

引用

56th International Carnahan Conference on Security technology, ICCST 2023

作者： Wadhe, Apeksha Arun Suratkar, Shraddha S. Vjti Mumbai Dept. of Computer Engineering & Information Technology 400019 India

ISBN: (纸本)9798350315875

Today social media is one of the most powerful and popular tool which is expanding rapidly in the world. Many tourism websites publish tourist places data for describing places in the form of Description. Over this data, Analysis can be performed and meaningful insights can be drawn. By analyzing this data we can find the subject or topic discussed in Description. By performing topic modeling over these data we can predict the category of tourist place. Also topic Modeling can help to cluster textual content into groups as per the subject of the text. In research study, Comparative analysis of topic modeling algorithms has been performed which will find a category of tourist places. Tourist place description blog data was gathered from tourism websites. Using tourist place Description dataset, comparative study of Topic modeling algorithms i.e. LDA Variational Inference(VI) algorithm and LDA Gibbs Sampling(GS) algorithm has been performed. Results of experiments has been analyzed with performance evaluation using various factors such as coherence score, perplexity, training execution time and accuracy percentage. LDA Gibbs Sampling(GS) algorithm outperforms LDA Variational Inference (VI) algorithm in terms of coherence score, perplexity, accuracy percentage. Whereas, LDA Variational Inference(VI) algorithm requires less execution time as compared to the LDA Gibbs Sampling(GS) algorithm © 2023 IEEE.

关键词： Websites

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Enhancing Colorectal Cancer Histological Image Classification Using Transfer Learning and ResNet50 CNN Model 5

Enhancing Colorectal Cancer Histological Image Classificatio...

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5th IEEE Eurasia Conference on Biomedical engineering, Healthcare and Sustainability, ECBIOS 2023

作者： Peng, Chun-Cheng Lee, Bing-Rong Chaoyang University of Technology Dept. of Information and Communication Engineering Taichung Taiwan

ISBN: (纸本)9798350320978

Medical image analysis is crucial in healthcare research. The convolutional neural network (CNN) has great potential in improving the precision and speed of medical diagnosis. In medical diagnostics, CNNs have displayed promising results, indicating their capability to enhance the accuracy and efficiency of the diagnostic process, accurately classifying complex medical images remains challenging. Colorectal cancer, a significant cause of global mortality, emphasizes the need for early detection and diagnosis to ensure successful treatment. We develop a new method combining transfer learning and a ResNet50 CNN model with the Adam optimizer to increase the accuracy in the classification of the histopathology images of colorectal cancer. The experimental results demonstrated outstanding performance with an accuracy of 99.99% in training and an accuracy of 99.77% in validation which were excellent performance on widely recognized evaluation metrics. In conclusion, the proposed method surpasses other related studies using CNN models for histopathology image classification. It provides a practical solution to further improve the classification performance of colorectal cancer histopathology images. The study result shows the efficacy of transfer learning in the analysis of medical images. Moreover, the proposed approach outperforms existing methods in medical image analysis, underscoring its potential to empower medical professionals in enhancing diagnostic capabilities and making more informed clinical decisions for patients. © 2023 IEEE.

关键词： Convolutional neural networks

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