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An Empirical Brief Analysis of Novelistic Approaches for Detection Of Bone Marrow Cancer Health Monitoring Through DL MODEL 5

An Empirical Brief Analysis of Novelistic Approaches for Det...

引用

5th IEEE international conference on computing, Power, and Communication Technologies, IC2PCT 2024

作者： Reddy, Anuradha Ramaiah, V. Subba Ayyappa, R. Mohan Krishna Ghantasala, G. S. Pradeep Kurra, Mamatha Bathla, Priyanka Chitkara University Punjab India Mahatma Gandhi Institute of Technology Department of Computer Science and Engineering Hyderabad Gandipet India Alliance University Department of Computer Science and Engineering Bengaluru India Chandigarh University Mohali Punjab Gharuan India

ISBN: (纸本)9798350383522

Deep learning, with its ability to inevitably learn hierarchical depictions from multifaceted data, has shown promise in medical applications. However, tuning the hyperparameters of deep learning models is a vital task, and metaheuristic optimization techniques offer effective results. The objective is to assess their efficiency in enhancing the recital of deep learning models for bone marrow tumor prophecy. The study employs an assorted dataset, encompassing several patient attributes and medicinal gages. Through a sequence of researches, we evaluate the convergence speed, resolution excellence, and sturdiness of each metaheuristic tactic when coupled with a deep learning model. The outcomes acme the fortes and paleness of each process, providing valuable intuitions for investigators and experts in the field of medical data investigation. This study contributes to the optimization of deep learning models for bone marrow tumor prediction, targeting to advance diagnostic accurateness and sustenance healthcare authorities in making informed verdicts for persistent care. © 2024 IEEE.

关键词： Bone Marrow Cancer Prediction Deep learning model Diagnostic Accuracy Healthcare Decision Support Hyperparameter Tuning Medical Data Analysis Metaheuristic Optimization

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Application Arduino-based Unmanned Calculation System 13

Application Arduino-based Unmanned Calculation System

引用

13th international conference on Information and Communication technology convergence, ICTC 2022

作者： Kim, Junyoung Park, Beomseo Lee, Jiyoung Jang, Hyunhee Na, Woongsoo Kongju National University Department of Software Korea Republic of

ISBN: (数字)9781665499392

ISBN: (纸本)9781665499392

In this paper, we propose an application and an Arduino-based unmanned computing system that can combine applications and IoT to provide convenient services to customers. This service is implemented as a mobile application and receives member information to prevent minors from purchasing alcohol and cigarettes and provide customized product information. The application service scans the product barcode from the database and adds it to the shopping basket, comparing the weight of the product in the cart with the actual weight of the product stored in the database through Bluetooth when paying. © 2022 IEEE.

关键词： Bluetooth Databases Cameras Sensors Mobile applications Information and communication technology convergence

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Dual-Function Waveform Design via W-ADPM 30

Dual-Function Waveform Design via W-ADPM

引用

30th international conference on Mobile computing and Networking, ACM MobiCom 2024

作者： Ji, Wenshuai Liu, Tao Liu, Fan Tang, Yanqun Tian, Biao Zhang, Chudi Sun Yat-Seen University Shen Zhen China Southern University of Science and Technology Shen Zhen China Academy of Military Science Bei Jing China

ISBN: (纸本)9798400704895

This paper proposes a novel design algorithm for dual-function radar communication (DFRC) Orthogonal Frequency-Division Multiplexing (OFDM) waveform. The algorithm achieves a tradeoff between detection performance and communication bit error rate (BER) performance. Firstly, the algorithm modulates communication information on the phase of the subcarrier coefficient of OFDM waveform using M-phase-shift keying (MPSK) schemes such as Binary-PSK (BPSK). Subsequently, the waveform minimises the weighted integrated sidelobe level (WISL) of the transmit waveform and the receive mismatch filter while ensuring the BER. Additionally, constraints are placed on constant amplitude, mainlobe energy and signal-to-noise ratio (SNR) loss. To address the non-convex optimization issues arising from algorithm design, a Weight Alternating Direction Method of Penalty (W-ADPM) network-based approach simultaneously optimises the transmit waveform and receives mismatched filters. The simulation experiments demonstrate that the proposed algorithm has better convergence performance for the proposed waveform compared to the Alternating Direction Method of Multipliers (ADMM) algorithm. Besides, compared to traditional matched filters, the jointly transmitted and received mismatched filters proposed in this paper provide better WISL cross-correlation performance while ensuring the BER. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Orthogonal frequency division multiplexing

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Architectural Color Image Scale computing of Beijing Forbidden City

Architectural Color Image Scale Computing of Beijing Forbidd...

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2024 international conference on Culture-Oriented Science and technology, CoST 2024

作者： Liu, Bowen Huang, Wenli Yu, Xiumeng Ma, Zongliu Guo, Ziyi Wang, Shuang Jiang, Wei Communication University of China State Key Laboratory of Media Convergence and Communication 100024 China Communication University of China Key Laboratory of Acoustic Visual Technology and Intelligent Control System 100024 China Communication University of China Beijing Key Laboratory of Modern Entertainment Technology 100024 China

ISBN: (纸本)9798350380347

The traditional color system of Beijing Forbidden City is comprehensive and complex. The research focuses on collecting color data from the Forbidden City, analyzing subjective and objective color attributes, and compute architectural color image scale. First this research used K-means algorithm to extract the theme color cards of Beijing Forbidden City. Subsequently, single colors were extracted using the idea of community detection, and matching colors were extracted based on the thought of association rule mining. Then this research extracted objective attributes of colors and designed experiments to quantify subjective attributes. Finally, the color subjective and objective data fitting was completed. This outcome is helpful for the digital preservation of traditional colors and the advancement of color culture inheritance practices. © 2024 IEEE.

关键词： Color computer graphics

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Impact of Ant Colony Optimization on Optimal Routing for Vehicular Ad Hoc Networks 5

Impact of Ant Colony Optimization on Optimal Routing for Veh...

引用

5th IEEE international conference on Communication, computing and Industry 6.0, C2I6 2024

作者： Ramamoorthy, Raghu Velu, Anitha Appala Naidu, R China Asha Kumari, A. Angel Donny, F. Harish Kumar, M. The Oxford College of Engineering Department of Computer Science and Engineering Bengaluru India Sri Sairam College of Engineering Department of Electronics and Communication Engineering Bengaluru India Ramaiah Institute of Technology Department of Computer Science and Engineering Bengaluru India Vemana Institute of Technology Department of Artificial Intelligence & Machine Learning Bengaluru India

ISBN: (纸本)9798350379884

Using biologically inspired approaches has bonus advantages in offering optimal message distribution for vehicular ad hoc networks (VANETs). Bio-motivated approaches are motivated by the natural behavior of biological entities such as bees and insects. Ant colony optimization (ACO) is the optimal bio-inspired style, suitable for offering optimal routing in VANETs. The communication pattern of ACO and VANETs is similar, such as ants of ACO apply indirect communication among ants for the exchange of information, and VANETs require cooperative routing techniques for message exchange. The goal of the Bio-motivated approach is to attain proficient and accessible communication in a VANET, where vehicles turn as nodes and animatedly form a system to interchange information. In this context, the proposed work discusses the effectiveness and benefits of using a bio-inspired approach such as ACO for VANETs. To demonstrate ACO, a healthcare scenario is considered. In the healthcare system, efficient communication is required between emergency vehicles and hospitals to offer optimal treatment for patients. This work applies ACO to find the optimal path for sending an alarm to the nearest hospital from the emergency vehicle to arrange necessary things to treat patients. Using ACO increases the efficiency of the routing mechanism in all aspects such as throughput, overhead, data delivery, low latency, route discovery time, route repair time, convergence speed, and stagnation issue. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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Optimization of YOLO v8 Model for Forest Fire Target Detection Based on Coordinate Attention Mechanism 3

Optimization of YOLO v8 Model for Forest Fire Target Detecti...

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3rd international conference on Cloud computing, Big Data Application and Software Engineering, CBASE 2024

作者： Yang, Meng Cui, Heng Cui, Zhangyin Kuang, Shaojie Li, Zhuoshu School of Technology Beijing Forestry University Beijing10083 China

ISBN: (纸本)9798331506582

In this study, we introduced a coordinate attention mechanism based on the YOLO v8 model and optimized it to improve the performance of forest fire target detection. We conducted two sets of experiments, the first being the application of YOLO v8 basic model in forest fire target detection. The results showed that the loss values of the training and validation sets gradually decreased and tended to converge, while indicators such as precision, recall, and mean average precision (mAP) steadily improved. In the second experiment, the improved YOLO v8 model also demonstrated good training performance, with continuous reduction in loss values and convergence, as well as significant improvements in accuracy, recall, and mAP metrics. Specifically, compared to the YOLO v8 base model, the improved model improved by 0.03 in accuracy, 0.38 in recall, 0.018 in mAP50, and 0.014 in mAP50-95. This series of data indicates that our proposed optimization scheme effectively enhances the performance of the model in forest fire target detection tasks. This study not only provides a more efficient technical means for forest fire monitoring, but also offers new ideas and methods for optimizing target detection algorithms in related fields, which has important practical application value and theoretical significance. © 2024 IEEE.

关键词： Premixed flames

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Efficiency Optimization of Large-Scale Language Models Based on Deep Learning in Natural Language Processing Tasks 2

Efficiency Optimization of Large-Scale Language Models Based...

引用

2nd IEEE international conference on Sensors, Electronics and Computer Engineering, ICSECE 2024

作者： Mei, Taiyuan Zi, Yun Cheng, Xiaohan Gao, Zijun Wang, Qi Yang, Haowei Northeastern University Boston United States Georgia Institute of Technology Atlanta United States University of Houston Houston United States

ISBN: (纸本)9798350373646

The internal structure and operation mechanism of large-scale language models are analyzed theoretically, especially how Transformer and its derivative architectures can restrict computing efficiency while capturing long-term dependencies. Further, we dig deep into the efficiency bottleneck of the training phase, and evaluate in detail the contribution of adaptive optimization algorithms (such as AdamW), massively parallel computing techniques, and mixed precision training strategies to accelerate convergence and reduce memory footprint. By analyzing the mathematical principles and implementation details of these algorithms, we reveal how they effectively improve training efficiency in practice. In terms of model deployment and inference optimization, this paper systematically reviews the latest advances in model compression techniques, focusing on strategies such as quantification, pruning, and knowledge distillation. By comparing the theoretical frameworks of these techniques and their effects in different application scenarios, we demonstrate their ability to significantly reduce model size and inference delay while maintaining model prediction accuracy. In addition, this paper critically examines the limitations of current efficiency optimization methods, such as the increased risk of overfitting, the control of performance loss after compression, and the problem of algorithm generality, and proposes some prospects for future research. In conclusion, this study provides a comprehensive theoretical framework for understanding the efficiency optimization of large-scale language models. © 2024 IEEE.

关键词： Risk perception

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Research on the Human-Machine Collaborative Optimisation Algorithm for Intelligent Traffic Signal Control Systems

Research on the Human-Machine Collaborative Optimisation Alg...

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2024 international conference on computing, Robotics and System Sciences, ICRSS 2024

作者： Li, Zhuoxun Chen, Junju Wu, Kefan Wu, Zhanyi Liu, Qiqi School of Swinburne Shandong University of Science and Technology Shandong Jinan China

ISBN: (纸本)9798331511296

With the worsening of urban traffic congestion, improving traffic flow and resource utilisation efficiency has become an important challenge in the field of intelligent transportation. Traditional traffic signal control systems lack dynamic adaptability and are difficult to cope with complex and ever-changing traffic environments. To address this problem, this paper proposes a bionic ant path planning algorithm based on human-machine collaborative optimisation. The system obtains real-time road traffic data, including information such as signal status, traffic flow and obstacle distribution, through a data acquisition module, and uses an improved ant colony algorithm to achieve global path search and dynamic optimisation. At the same time, a human-machine collaborative interaction mechanism is designed to allow users to adjust path weight parameters in real time according to actual needs, enhancing the flexibility and adaptability of the system. Through simulation experiments, this paper verifies the performance of the proposed algorithm in different scenarios and compares it with traditional path planning algorithms. The results show that the ant colony algorithm based on human-machine collaborative optimisation has significant advantages in terms of convergence speed, path optimisation effect and dynamic environmental adaptability. This study provides an efficient, real-time and flexible path optimisation solution for intelligent traffic signal control systems, which can effectively improve traffic scheduling capabilities in complex dynamic environments. © 2024 IEEE.

关键词： Traffic congestion

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Research on Single Carrier Frequency Domain Equalization in Wideband High Frequency Communication System 8

Research on Single Carrier Frequency Domain Equalization in ...

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8th international conference on Intelligent computing and Signal Processing, ICSP 2023

作者： Feng, Buyi Si, Lu Yin, Hang Communication University of China Engineering Center of Digital Audio and Video Beijing China Communication University of China State Key Laboratory of Media Convergence and Communication Beijing China

ISBN: (纸本)9798350302455

In wideband high frequency communication, the signal is transmitted by ionosphere reflection, which is affected by multipath fading of the channel in the transmission process, resulting in high bit error rate and intersymbol interference(ISI). The single carrier frequency domain equalization (SC-FDE) technology adopts traditional single carrier modulation and uses orthogonal frequency division multiplexing (OFDM) for reference to equalize in frequency domain, which can effectively combat multipath fading of channels, but at the same time avoids the shortcomings of OFDM system, such as high peak-to-average ratio and sensitivity to frequency offset. This paper expounds the principle and implementation scheme of SC-FDE system, simulates and compares several main frequency domain equalization algorithms under two high frequency channel models, and gives the performance curves. © 2023 IEEE.

关键词： Bit error rate

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Enhancing DNS Attack Classification with Convolutional Neural Networks and Gated Recurrent Units 15

Enhancing DNS Attack Classification with Convolutional Neura...

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15th international conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Prasad, Sanjana Sharma, Ishu Arun, S. Department of Electronics and Communication Engineering HKBK College of Engineering Bangalore India Department of Computer Science and Engineering Lovely Professional University Punjab Phagwara India Department of Electronics and Communication Engineering CMR Institute of Technology Bangalore India

ISBN: (纸本)9798350370249

DNS attacks can be caused by various methods such as Rebinding attacks, Cryptojacking and Domain Generation Algorithm. Classifying DNS attacks in a timely manner and taking necessary action to mitigate the issue is important. This research study describes the hybrid model of Convolutional Neural Network (CNN) and Gated Recurrent Units (GRUs) that is used to improve the detection or categorization of DNS attacks. A dataset called CIRA-CIC-DoHBrw-2020 is used to train the suggested hybrid mode. According to experimental data, the LSTM prototype outperformed CNN with respect to identifying or categorizing DNS attacks. The CNN-LSTM and CNN-GRU hybrid models have the ability to improve the model's accuracy. CNN was used for feature extraction and LSTM for temporal modeling in the CNN-LSTM hybrid model. The suggested CNN-GRU hybrid model, on the other hand, obtains the greatest accuracy of 95.16%, demonstrating the efficacy of integrating GRU with CNN to effectively recognize or categorize both temporal and geographical characteristics of DNS network data. The CNN-GRU model's enhanced performance demonstrates how well merging different neural network architectures—like CNNs and GRUs—may enhance convergence and lower error rates. © 2024 IEEE.

关键词： Convolutional Neural Networks DNS Security Gated Recurrent Units Infrastructure Security Network Security Network Traffic Classification

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