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Real-Time Big Data Analysis Using Web Scraping in Apache Spark Environment: Case Study—Mobile Data Analysis from Flipkart 3rd

Real-Time Big Data Analysis Using Web Scraping in Apache Spa...

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3rd international conference on Recent Trends in Advanced Computing - Artificial Intelligence and Technologies, ICRTAC-AIT 2020

作者： Ganguly, Pushpita Parihar, Giriraj Sivagami, M. School of Computer Science and Engineering VIT University Tamil Nadu Chennai India

ISBN: (纸本)9789811664472

There are many data sources that produce sheer volumes of data, and this generated data named big data can be used for making decisions. There are lots of domains including finance, transportation, entertainment, energy, security, and emergency services rely on fast and efficient analytics based on available data to make quality decisions conveniently which is a key factor for businesses and many service industries. The big data nature requires new distributed processing approaches to extract the valuable information. Real-time sentiment analysis is one of the most demanding research areas that require powerful big data analytics tools such as Spark. This paper proposed a real-time data analysis. It first scraps data from the Web and will do real-time analysis using Spark with machine learning tools. As a case study for this real-time analysis, Flipkart mobile data is taken with the aim of doing classification of the dataset for further analysis as well as predicting the ratings of different kinds of mobile phones using machine learning modules. At last the accuracy of the implemented models is shown. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Big data

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Method of Differential-Based Remote Upgrade for ECUs on Vehicles 3

Method of Differential-Based Remote Upgrade for ECUs on Vehi...

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2021 3rd international conference on Robotics, Intelligent Control and Artificial Intelligence, ICRICA 2021

作者： Wu, Xingchen Gao, Tianyu Lee, Guodong Natl. Engineering Technology and Research Center of Railway CRRC Changchun Railway Vehicles Co. Ltd Changchun China College of Computer Science and Technology Jilin University Changchun China

In view of the problem that the current update flashing of the traditional automotive electronic control unit (ECU) software highly relies on professional maintenance personnel and external equipment, a method for ECU remote data flashing is proposed to achieve remote and efficient upgrade of ECU software. Furthermore, through the introduction of backup partitions and differential upgrade methods, the problems of lack of fault-tolerant processing, high bandwidth requirements and low efficiency in traditional ECU software update flashing are also solved. In this article, a remote update system is built, including the server-side and the vehicle, and the interface and communication protocols are defined based on HTTPS. The above methods have been verified on NXP IMX 6 platform. Associated testing of the simulation of the ECU by the STM32 and ROCKCHIP demo board has been made based on the CAN and Ethernet simulating the vehicle network architecture. By the real data catching from Ethernet and the CAN, the details of the log file of the programs' event tracking information are analyzed to obtain the experimental results. The results indicated that the incremental remote data updating system built in this article can remotely update the CAN software accurately and efficiently in all simulation tests, which proved the practicability, accuracy, and efficiency of this method. © Published under licence by IOP Publishing Ltd.

关键词： Ethernet

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A Co-caching Strategy for Edges Based on Federated Learning and Regional Prevalence 1

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3rd EAI international conference on Edge Computing and IoT, EAI ICECI 2022

作者： Zhu, Zhirong Liu, Yiwen Gao, Yanxia Wen, Wenkan Shi, Yuanquan Peng, Xiaoning School of Computer and Artificial Intelligence Huaihua University Hunan Huaihua418000 China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Hunan Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Hunan Huaihua418000 China

ISBN: (数字)9783031289903

ISBN: (纸本)9783031289897

With the rise of data storage computing and IoT technology. The increase in data volume and user demand, the accurate delivery of data and low latency during transmission become important factors that affect the end-user experience. To address this issue, previous authors have proposed the concept of edge computings. In the general environment of edge computing, reasonable scheduling of edge caches can largely achieve low latency and high efficiency, thus improving user experience. In this paper, based on existing research, we propose a combination of a joint learning framework for cache prediction based on region popularity and an edge collaborative cache value optimization method to further improve cache hit rate and cache utilization efficiency. The method obtains excellent expected results through simulation experiments. © 2023, ICST Institute for computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Edge computing

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GOSGAN: An Adaptive Atomic Force Microscope Imaging Repair Model for Cell Scanning

GOSGAN: An Adaptive Atomic Force Microscope Imaging Repair M...

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computer science and Management Technology (ICCSMT), international conference on

作者： Jingxin Li Hongmei Xu Haobo Cui Lixin Yuan International Research Centre for Nano Handling and Manufacturing of China Changchun University of Science and Technology Changchun China

In recent years, Atomic Force Microscopy (AFM) has played an irreplaceable role in cell biology as it can measure the local mechanical information of individual cells while observing the surface morphology of cells. To address the problems of long scanning time and poor image quality, this paper attempts to introduce a super-resolution method to optimize the images in order to reduce the imaging time, reduce probe loss and improve the image quality. The proposed method is based on the existing super-resolution method of generative adversarial networks and is designed to introduce a self-attentive information fusion module to enhance the organic fusion of a priori and input while improving the richness of the a priori information encapsulated in the network, and to propose GOSGAN. In addition, a large-scale data generation model and a targeted image degradation model are introduced to address the problem of difficult access to AFM data. The final experiment achieves a peak signal-to-noise ratio (PSNR) and structural similarity ratio (SSIM) of 26.8 dB and 0.92, respectively, on its own validation set.

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Panax Notoginseng Saponins Induces Apoptosis in Breast Cancer by Regulating PI3k/AKT Pathway and Suppressing Bcl-2 by Using computer science 22

Panax Notoginseng Saponins Induces Apoptosis in Breast Cance...

引用

3rd international Symposium on Artificial Intelligence for Medical sciences, ISAIMS 2022

作者： Wei, Xiaojing Department of Bioscience and Biotechnology Hunan Agriculture University China

ISBN: (纸本)9781450398442

Hypothesis: I postulate that the major function of PNS in breast cancer is to induce the apoptosis and inhibit the proliferation through activate the inhibition of P13k/AKT pathway to suppress the effect of Bcl-2 and increase the Bax and caspase-3. Purpose: Breast cancer is malignant disease for human beings. The traditional therapy is mainly resection operation. Though its effect of radical cure is high, it easily metastasizes and invades the tumor. Previous studies have shown that Panax notoginseng Saponins (PNS) has inhibitory proliferation effect and relevant function on apoptosis via PI3k/AKT/mTOR pathway. The study will investigate how PNS effects apoptosis by regulating PI3k/AKT in in vitro condition. Materials and method: The cell line which will be used is 4T1-Leu breast cancer cells. The cell proliferation will be assessed by Cell Counting Kit-8, whereas the apoptotic rate will be investigated by flow cytometry and Annexin V. The relevant proteins about PI3k/AKT/mTOR pathway and apoptosis will be assessed by western blotting. Possible results: There are five possible results in cell proliferation, five results in apoptosis and 6 results in western blot in this study, it can be aggregated to 4 results. *** can inhibit proliferation and induce apoptosis of 4T1-luc breast cancer cells by suppressing the PI3K/AKT pathway;2. PNS activates proliferation and inhibit apoptosis of 4T1-luc breast cancer cells by suppressing the PI3K/AKT/mTOR pathway. 3. PNS activates proliferation and inhibit apoptosis of 4T1-luc breast cancer cells by promoting mTOR pathway via PI3K/AKT. 4. PNS inhibit apoptosis of 4T1-luc breast cancer cells by suppressing mTOR pathway via PI3K/AKT. Conclusion: The results of the study will provide a new way to investigate the PNS in breast cancer therapy, in both apoptosis and cell signal pathway ways. © 2022 ACM.

关键词： Cell death

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Traffic Rule Violation Detection System: Deep Learning Approach 1

引用

3rd international conference on Machine Intelligence and signal processing, MISP 2021

作者： Kathane, Mandar Abhang, Shubham Jadhavar, Abhishek Joshi, Amit D. Sawant, Suraj T. Department of Computer Engineering and IT College of Engineering Maharashtra Pune India

ISBN: (数字)9789811908408

ISBN: (纸本)9789811908392

While travelling, safety is one of the most important things that should be kept in mind. Due to the negligence of people, number of road accidents continue to increase in India. To decrease the number, one of the most important things is the proper implementation of traffic rules. The proper implementation of traffic rules ensures the safety of people since traffic rules are designed for the proper flow vehicles on roads and to ensure safety. The objective of this work is to improve the implementation of traffic rules by automating the process of identification of traffic rule violators from images. The proposed methodology focuses to detect different types of traffic rule violators, the riders without helmets and bike with three people violating traffic rules. It is necessary to detect motorcycle present in an image for consideration of all these cases. The steps like helmet detection, triple seat detection and number plate detection are followed after motorcycle detection in an image. Deep learning techniques are studied and implemented for all these cases. YOLOv3 algorithm is used in the implementation of the proposed methodology. Different deep learning models are trained to detect objects. The proposed system uses three deep learning models for detection of these objects. Different models are trained for detection of different objects in the input image. The proposed work results into 88.5% mean average precision for motorcycle detection model and 91.8% for number plate detection. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image enhancement

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Design of Wechat Applet Shopping System based on Personalized Recommendation 22

Design of Wechat Applet Shopping System based on Personalize...

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3rd Asia-Pacific conference on Image processing, Electronics and computers, IPEC 2022

作者： Yang, Yuwei Gao, Jie Qiu, Jianlin School of Computer and Information Engineering Nantong Institute of Technology JiangSu NanTong China School of Electrical and Energy Engineering Nantong Institute of Technology JiangSu NanTong China

ISBN: (纸本)9781450395786

In recent years, more and more people choose to shop on the mobile terminal, which makes the functional requirements and performance complexity of the mobile terminal shopping system increasing. The traditional shopping APP is not enough to deal with the frequent changes of the shopping system. Therefore, there is an urgent need for a flexible, efficient and fast mobile shopping system. Wechat applet was born in this context. Wechat applet has the characteristics of installation free, small memory, low cost and easy extension. With the continuous growth of network information, the problem of data overload promotes the development of personalized recommendation technology. On the basis of literature research and practical research, this paper designs a wechat applet shopping system based on personalized recommendation. The system is divided into seven functional modules: user login, products information display, products classification, shopping cart, order payment, personal information management and personalized recommendation. The system adopts layered architecture design, and the module realizes the corresponding functions by calling API interface. Among them, the personalized recommendation module uses the recommendation algorithm based on collaborative filtering to analyze the user's behavior, and makes recommendations in four different scenarios. The system designed in this paper can meet the shopping needs of users, provide intimate recommendation services, improve shopping efficiency, add shopping fun, and meet the personalized life of users. © 2022 ACM.

关键词： Classification (of information)

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Time-frequency Analysis of Non-stationary signal Based on Sliding Mode Singular Spectrum Analysis and Wigner-ville Distribution

Time-frequency Analysis of Non-stationary Signal Based on Sl...

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Information science and Education (ICISE-IE), international conference on

作者： Zhe Li Shilin Sun Yichuan Wang Weiguo Dai Jiaxing Qiu Zhen Liu Naval Submarine Academy Qingdao China

In order to obtain better performance of time-frequency representation(TFR) in non-stationary signal processing using Wigner-Ville distribution(WVD), an adaptive time-frequency analysis method based on combination of sliding mode singular spectrum analysis(SM-SSA) and Wigner-Ville distribution(SM-SSA-WVD) was proposed. Through mode decomposition of original signal by SM-SSA and linear superposition of TFRs for each mode by WVD, the cross terms are effectively suppressed, which obtaining higher adaptive ability and energy concentration of WVD results comparing to the traditional WVD methods. The proposed cross-term free method is applied to analyze several kinds of simulated clean and noisy multi-component modulated signals. The TFRs of the proposed method work better in restraining the cross terms of WVD than some other adaptive decomposition methods, thus obtaining higher time-frequency resolution and noise robustness.

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Machine Learning-Based Categorization of Brain Tumor Using Image processing 3rd

Machine Learning-Based Categorization of Brain Tumor Using I...

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3rd international conference on Recent Trends in Advanced Computing - Artificial Intelligence and Technologies, ICRTAC-AIT 2020

作者： Appalaraju, Muralidhar Sivaraman, Arun Kumar Vincent, Rajiv Ilakiyaselvan, N. Rajesh, M. Maheshwari, Uma School of Computer Science and Engineering VIT University Tamil Nadu Chennai India School of Computer Science and Engineering Centre for Cyber Physical Systems VIT University Tamil Nadu Chennai India

ISBN: (纸本)9789811664472

Radiology is an enormous topic and requires extra acquaintance for accurate analysis of tumor tissue in medical sciences. In this work, a meningioma segmentation and detection approach are designed using magnetic resonance image (MRI) sequence images for defining the tumor point. This experiment is difficult for the large diversification in the existence of tumor tissues related to various inmate tissues, and in most of the cases, similarity within the normal tissues makes the task difficult. The main impartial is to categorize the brain into the presence of meningioma or not. The proposed system has Edge-based Contourlet Transformation as the main step for registration process. Then the segmentation of tumor point using region expanding segmentation for aspect extraction and two types of texture features are combined i.e., Otsu’s thresholding, k-means and local binary marking texture aspect for efficient meningioma detection and finally the classification adopting neural network method is imported out. The proposed approach implements a novel procedure that uses a backpropagation detection of meningioma from slices of scan images. The combination of GLRLM and CS-LBP features outperformed well in discriminating between normal and affected tumor tissues, and for classification, a backpropagation algorithm is used and attained better classification accuracy. The proposed algorithm is implemented using MATLAB;for various MRI sequences, the experimental results are obtained for image registration and segmentation using point of growing. The segmented images are correlated with the victims’ image database and classify it as malignant or benign using ANN classifier. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Tumors

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An Experimental Study on Extraction Method of Tobacco Color Distribution Feature 1

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3rd international conference on 3D Imaging Technologies - Multidimensional signal processing and Deep Learning, 3DIT-MSP and DL 2021

作者： Luo, Ruilin Li, Yingchun Qi, Yuecheng Zhang, Yicheng Zhang, Chunjie Yang, Dongdong Yunnan Tobacco Leaf Company Yunnan Kunming650218 China School of Information Science and Technology Yunnan Normal University Yunnan Kunming650500 China Yunnan Key Laboratory of Optoelectronic Information Technology Yunnan Kunming650500 China

ISBN: (数字)9789811924521

ISBN: (纸本)9789811924514

The color distribution of tobacco leaves is highly correlated with the grade purity of tobacco leaves, which is an important index for the sorting of primary flue-cured tobacco leaves. In this paper, the method of extracting color distribution feature from tobacco leaf image was studied experimentally. In the experiment, images of tobacco leaf were taken and collected with an industrial camera with a D65 standard light source and a white background in a dark room. Then, the green channel of images was selected, and the color values were statistically summarized. The dimensionality of color values was reduced to 8 dimensions, and then, the table of color value area was used to explain the characteristics of color. The separation algorithm of tobacco leaf and background in the image was found out by the tobacco leaf color value analysis experiment, and the image was binarized according to the threshold value. If the tobacco leaf was represented as 1 when 8 150, we can realize the separation of tobacco leaves and background. Therefore, the experiment collected the basic color distribution feature of B2F, C3F, and X2F tobacco leaves. The obtained characteristic parameters can be used for automatic evaluation of single-frame tobacco leaf grade purity by machine vision in the process of tobacco separation. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Tobacco

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