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检索条件"任意字段=Proceedings of the 2023 5th International Conference on Big Data Engineering and Technology"

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Detection of Breast Cancer Based on Fuzzy Logic 5

Detection of Breast Cancer Based on Fuzzy Logic

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5th international conference on Advancement in data Science, E-Learning and Information Systems, ICADEIS 2023

作者： Neelima, G. Kanchanamala, P. Misra, Alok Nugraha, Ryan Adhitya Vignan's Institute of Information Technology Duvvada CSE Dept Gajuwaka A.P. Visakhapatnam India GMR Institute of Technology Dept of IT AP Rajam India Chitkara University Institute of Engineering and Technology Punjab India Telkom University Information System Departement Bandung Indonesia

ISBN: (纸本)9798350303414

the most dangerous illnesses in medical history are said to include breast cancer. People die more frequently because breast cancer, one of the leading causes of death worldwide, is more common. However, early detection of this cancer helps to save lives. this is complicated because mammography detection is difficult in many ways. A system for early detection and diagnosis of breast cancer is being developed for physicians using Machine Learning (ML) techniques, which has the potential to significantly improve survival rate of patients. Using machine learning algorithms, fuzzy-based breast cancer detection is demonstrated in this analysis. this analysis proposes two machine learning methods for the Wisconsin (Diagnostic) data Set: the Support Vector Machine (SVM) and Decision Tree (DT) algorithms. In consideration of the parameters of precision, accuracy, specificity, and recall, the combined model outperforms other individual Machine Learning models. Fuzzy based SVM and DT classification technique efficiently detects the breast cancer diseases with high Accuracy as 98.2%, Precision, 97.6%, Recall 96.5% and Specificity 97.8%. © 2023 IEEE.

关键词： Decision trees

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Visual Odometry Based on Camera Motion and Bidirectional Long Short-Term Memory Network 5

Visual Odometry Based on Camera Motion and Bidirectional Lon...

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5th international conference on Computer Information Science and Application technology, CISAT 2022

作者： Zhao, Zhangzhen Xing, Bin Song, Tao Liu, Yi Chen, Bin Chongqing Key Laboratory of Optical Fiber Sensing and Photoelectric Detection Chongqing University of Technology Chongqing400054 China Chongqing Industrial Big Data Innovation Center Co. Ltd Chongqing400708 China Chongqing Jiuzhou Star Navigation Equipment Co. Ltd Chongqing400037 China

ISBN: (纸本)9781510660076

Most of the deep learning-based visual odometers have defects such as being unable to effectively learn camera motion information directly from RGB images, and low pose accuracy in the face of vehicle turning, high-speed driving and other scenes with dramatic changes in motion. Aiming at the above problems, this paper proposes a monocular visual odometry method that combines the camera's own motion estimation and a bidirectional long-short-term memory network. Firstly, a camera motion based on a gated recurrent convolutional neural network is proposed by introducing a 4D correlation volume of pixel pairs. Feature extraction algorithm to extract the motion features of adjacent frames of the camera;then, a monocular visual odometry combining motion features and bidirectional long-short-term memory network is proposed. By learning the geometric motion relationship between adjacent frames before and after, more accurate six-degree-of-freedom camera pose information can be obtained. Comparative experiments on the KITTI dataset show that the proposed algorithm can estimate the pose with higher accuracy. © 2022 SPIE.

关键词： Motion estimation

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Effective Method for Cancer Diagnosis Employing Deep Learning Algorithms 5

Effective Method for Cancer Diagnosis Employing Deep Learnin...

引用

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

作者： Borah, Nayana Agrawal, Trapty Ali, K. Shoukath School of Sciences Department of Life Sciences Karnataka India Maharishi University of Information Technology Maharishi School of Engineering & Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India

ISBN: (纸本)9798350383522

Leading sources of death and morbidity, lung and colon cancers sometimes develop simultaneously and pose serious risks to people's health. Early discovery is essential for successful therapy, but the procedure for conducting a histopathological analysis may be laborious and complicated. Deep learning (DL) approaches have become important technologies that allow for more efficient examination of a greater number of patients. Previous studies have typically used individual DL models, which require more computation for feature extraction and analysis. However, based on several mild DL models, this study provides a modification framework for the early detection of lung and colorectal cancer. this innovative framework combines several reduction techniques that improve data representation. the reduced features generated by FHWT are fused to the three DL models using a discrete wavelet transform (DWT). In addition, all three DL models combine features of PCA. Finally, four different machine learning techniques are applied to feature reductions from PCA and FHWT-DWT algorithms, yielding an impressive accuracy rate of 99.6%.the results of these algorithms, based on DL on lighter models, shows that this is more effective than the previous methods In complex cases. this framework demonstrates the power of reductionist and adaptive approaches, resulting in better data interpretation and diagnostic methods. © 2024 IEEE.

关键词： Classification accuracy Colon cancer Diagnosis DWT Feature reduction FHWT Lightweight deep learning models Lung cancer Machine learning PCA Transformation methods

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An Inverted S-Shaped Microstrip Antenna for 5G Millimeter-wave Applications 12

An Inverted S-Shaped Microstrip Antenna for 5G Millimeter-wa...

引用

12th IEEE international conference on Communication Systems and Network Technologies, CSNT 2023

作者： Jain, Rachit Mishra, Deeksha Singhal, P.K. thakare, Vandana Vikas Institute of Technology &management Department of Electronics and Communication M.P Gwalior India Madhav Institute of Technology & Science Department of Electronics Engineering M.P Gwalior India

ISBN: (纸本)9781665462617

the evolution of Fifth Generation (5G) mobile communication systems is driven by the need to support high data rates, which are essential for various applications such as streaming video, virtual reality, and the internet of things. this paper presents a new compact antenna design for 5G wireless devices. this design's aim is to create a compact, antenna solution having a great performance for 5G mobile networks that can effectively support the high data rate requirements of the 5G systems. Initially, the main focus was in terms of design that operates at 28 GHz, & 38 GHz which is a key frequency of 5G band for 5G application. the antenna was created and optimized to work for this frequency band and to meet the specifications required for 5G applications. the proposed antenna's simulation analysis shows that it has multiband characteristics and a return loss of -17.3dB in the 28 GHz band and -21.11dB in the 38 GHz band, which can be used as a framework for future 5G system development. © 2023 IEEE.

关键词： 5G mobile communication systems

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the Application of 5G Wireless Communication in Maritime Environment 5

The Application of 5G Wireless Communication in Maritime Env...

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5th international conference on Maritime Autonomous Surface Ships, ICMASS 2023

作者： Wu, Jianming Yang, Kun Zeng, Hao Zhang, Shuo Ding, Jianjun Jiang, Xue Key Laboratory of Oceanographic Big Data Mining Application of Zhejiang Province Zhejiang Ocean University Zhoushan316022 China Department of Naval Architecture and Marine Engineering Zhejiang Ocean University 1st Haidanan Road Zhoushan316000 China

Recently, 5G wireless communication have been rapidly adopted for maritime applications. As a result, significant progress has been made in the ocean digitalization. 5G features with low latency, high reliability, and a large bandwidth, which satisfies the requirements of maritime applications. Due to significant differences between land and marine radio propagation environments, the maritime communication encounters a large challenge for providing maritime users with reliable data communication service. In order to solve the abovementioned challenge, we designed a maritime 5G terminal and tested it on an unmanned surface vehicle (USV) in the Lanyue Lake of Zhejiang Ocean University. the test data were collected, and the corresponding data analysis are presented, which includes signal strength, signal reception quality, upload and download data rate. the received signal level (RSL) and transmission data rate obtained by the maritime 5G terminals demonstrate great potential of meeting the communication requirements of the maritime users. It is also can be found that the RSL and the data transmission rate of the maritime 5G can be used for the remote control of the unmanned ships, with the signal strength at sea up to -89.45 dBm, and maximum rate up to 226 Mbps. © 2023 Institute of Physics Publishing. All rights reserved.

关键词： Reception quality

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Hybrid Forecasting Model in Used Car Price Forecasting Based on Stochastic Algorithm 5

Hybrid Forecasting Model in Used Car Price Forecasting Based...

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5th international conference on Computer Information Science and Artificial Intelligence, CISAI 2022

作者： Xu, Lili Tian, Cong Liu, LinHui School of Modern Manufacturing Engineering Heilongjiang University of Technology Heilongjiang Jixi158100 China School of Electrical and Information Engineering Heilongjiang University of Technology Heilongjiang Jixi158100 China

ISBN: (纸本)9781510662520

With the quiet change of people's consumption habits, the used car market has been unprecedentedly prosperous and developed. However, the current second-hand car market does not have a unified price evaluation standard, which leads to frequent occurrences of wanton price listings and excessively low or high transaction prices, which create great obstacles to the transaction process and seriously affect the health and order of the second-hand car market development. this paper selects 13 index variables that affect the price of used cars, and analyzes the correlation between each index and the current price of used cars. through the random forest prediction model, GBDT prediction model and SVM prediction model proposed in this paper, the used car prices are predicted and compared. It is hoped that the research in this paper will have important significance for promoting the standardization of car pricing in the used car market. © 2023 SPIE.

关键词： Stochastic systems

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Research on the Optimal Layout of Large Chicken Coop Chicken Rack Based on Ventilation Airflow Organization 5

Research on the Optimal Layout of Large Chicken Coop Chicken...

引用

2023 5th international conference on Modeling, Simulation, Optimization and Algorithm, ICMSOA 2023

作者： Wu, Shuyang Shi, Zhigang Qu, Zhiguang Gao, Xinming School of Environmental and Municipal Engineering Qingdao University of Technology Shandong Province Qingdao China Qingdao Tengyuan Design Office Co. Ltd Shandong Province Qingdao China Shandong Xinde Technology Co. Ltd Shandong Province Yantai City China

To address the challenges associated with airflow organization in chicken coops within the Chinese poultry industry, this study conducted on-site measurements and utilized Computational Fluid Dynamics (CFD) simulations. the validity of the simulation results was confirmed through root mean square error analysis in comparison to experimental data. Subsequently, the study assessed the influence of different chicken rack arrangements within the coops, both when wet curtains were closed and opened. the findings reveal that, when wet curtains are closed, the internal coop layout significantly impacts chicken welfare, especially concerning layout changes relative to coop length. When wet curtains are open, the impact of coop layout and a 10-meter reduction in coop length on chickens is approximately equivalent. the arrangement of chicken racks within the coop has a profound effect on airflow organization. therefore, when designing coops, careful attention to chicken rack placement is essential to ensure proper airflow organization. © Published under licence by IOP Publishing Ltd.

关键词： Mean square error

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Brain Tumor Identification and Classification Using Enhanced Convolution Neural Network 5

Brain Tumor Identification and Classification Using Enhanced...

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5th international conference on Inventive Research in Computing Applications, ICIRCA 2023

作者： Raju, J. Anand, Krteen Krishna Kumar, D. Sivaganesan, D. Psg Institue of Technology and Applied Research Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350321425

Brain tumor identification and classification play a crucial role in medical imaging. Accurately identifying tumors is a challenging task that often requires highly skilled and experienced doctors. Manual identification is prone to errors, leading to the need for automated solutions. this study aims to utilize advancements in Machine Learning (ML) and Artificial Intelligence (AI) to develop an automated brain tumor identification and classification system. the primary objective is to predict the type of tumor accurately. this study employs a deep neural network architectures specifically Convolutional Neural Network (CNN) and other pre trained deep learning models to find the optimal solution that provides a high degree of accuracy in detecting cancerous cells in the brain. In this study, advanced ML and AI techniques are used to perform brain tumor classification. the study utilizes various deep CNN architectures and methods like random cropping to improve training accuracies. Proposed CNN 7x7 model demonstrates remarkable performance in accurately classifying brain tumors. It achieves a high degree of accuracy in detecting the presence of cancerous cells, surpassing manual identification methods and the accuracies of other pre trained models. the automated brain tumor classification system presented in this study has the potential to streamline the diagnosis and treatment process, significantly reducing the reliance on healthcare systems. By reducing the cost and time required for brain tumor diagnosis, it improves patient access to care. Future research can further enhance the proposed methodology and its applications in medical diagnosis. © 2023 IEEE.

关键词： Medical imaging

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Machine Learning and Deep Learning Algorithms for Network data Analytics Function in 5G Cellular Networks 6

Machine Learning and Deep Learning Algorithms for Network Da...

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6th international conference on Inventive Computation Technologies, ICICT 2023

作者： Pavani, Ale Kathirvel, A. Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India

ISBN: (纸本)9798350398496

Machine learning and deep learning algorithms have the potential to revolutionize network data analytics in 5G cellular networks. With the increase in the number of connected devices and the explosion of data generated by these devices, traditional methods of network data analytics are becoming increasingly inadequate. However, this function faces several challenges, including managing massive amounts of data, processing data in real-time, addressing privacy concerns, integrating with other network systems, and requiring skilled professionals. Overcoming these challenges will enable the network data analytics function to achieve its objectives and improve the overall performance and reliability of 5G cellular networks. Machine learning and deep learning algorithms enable the automatic identification of patterns and insights in large volumes of data, thereby facilitating real-time decision-making and proactive network management. these algorithms can be used for a wide range of network data analytics functions, including network optimization, anomaly detection, prediction of network failures, and dynamic spectrum management. Deep learning algorithms have shown significant promise in processing unstructured network data such as network logs, video, and images. As the 5G network continues to grow and evolve, the use of machine learning and deep learning algorithms in network data analytics is likely to become increasingly essential for ensuring network efficiency, reliability, and security. © 2023 IEEE.

关键词： 5G mobile communication systems

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Design and Simulation of a Highly Efficient SnSe Solar Cell with CuI as an HTL by SCAPS-1D 5

Design and Simulation of a Highly Efficient SnSe Solar Cell ...

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5th IEEE international conference on Telecommunications and Photonics, ICTP 2023

作者： Khan, Tanvir Mahtab Khatun, Most. Marzia Khatun, Habiba Hosen, Adnan Al Ahmed, Sheikh Rashel Electronic and Communication Engineering Pabna University of Science and Technology Department of Electrical Pabna6600 Bangladesh

ISBN: (纸本)9798350393477

In the present article, a semiconducting tin selenide (SnSe) absorber-based novel heterostructure device of FTO/CdS/SnSe/CuI/Ni is modeled by exploiting SCAPS-1D program. Herein, the copper iodide (CuI) as a hole transport layer (HTL) is employed at the rear of SnSe active material and rear metal electrode. the SCAPS-1D program is also exploited to evaluate the photovoltaic (PV) output parameters of the suggested new solar device. It is discovered that that p+ type CuI as an HTL confirms modest band structure at the SnSe/CuI junction, thus minimizing the carrier recombination at rear contact. As a result, the open circuit voltage (Voc) is increased up to 0.86 V for the cell with an HTL. Also, the efficiency is increased from 17.58% to 24.57% after adding the CuI HTL in the anticipated SnSe-based PV device. Furthermore, the PV performances of the designed device employing an HTL have been analyzed by the thickness, carrier density, defect level, and operating temperature. these outputs intimate that the CuI can be introduced as a promising HTL material for the developing inexpensive and high-efficiency SnSe-based PV devices. © 2023 IEEE.

关键词： Copper compounds

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