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Trend Analysis for Retail Chain Using Statistical Analysis System 1

引用

3rd international conference on Soft computing: Theories and Applications, SoCTA 2018

作者： Ramansh, Kanwar Kalra, Parul Mehrotra, Deepti Amity University NoidaUttar Pradesh India

ISBN: (数字)9789811507519

ISBN: (纸本)9789811507502

Trend analysis is the method of analyzing or predicting the future of the goods that are available with seller. It gives the various factors affecting the performance of the store based on the past data. The research provides a detailed insight of statistics of one of the leading retail chains in London having more than 15 stores which sell laptops and accessories and investigates the current status of the company. The research aims at a thorough understanding of the customer relationship with the company. data mining has emerged as an interdisciplinary domain in the process of knowledge discovery in databases in which techniques are applied in order to extract patterns. Further, advanced approach of analytics in order to discover and communicate meaningful patterns in data has, as a result, led to drive smart decisions. This research discusses the behavior of customer with respect to different stores in three major steps;they include (i) collection of dataset, (ii) preprocessing of the dataset, and (iii) descriptive analysis. Each step plays a key role in deriving the results. The collection of data further affects the data quality. Thus, first step ensures that the data collected is relevant and least erroneous. The approach in the report has enabled and high lightened a detailed insight in understanding trends among customers (understanding trends), i.e., descriptive analysis like dependency of sales on various factors. © 2020, Springer Nature Singapore Pte Ltd.

关键词： data mining

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Optimization of Echo Parameter in intelligent Instrument Under the Condition of Numerical Stability

Optimization of Echo Parameter in Intelligent Instrument Und...

引用

international conference on Cyber Security Intelligence and analytics (CSIA)

作者： Song, Ke Sichuan Aerosp Vocat Coll Dept Elect Engn Chengdu Sichuan Peoples R China

ISBN: (纸本)9783030152352;9783030152345

The design of acquisition parameters is of great significance for intelligent instrument. In order to achieve better application of this method to formation fluid identification and reservoir evaluation, the observed echo amplitude and data kernel matrix are not affected by the diffusion coefficient and relaxation time. The FDTD method uses a set of finite difference equations to replace the Maxwell's rotation equation, that is, the solution of the differential equations is replaced by the solution of the difference equations. This substitution is meaningful only when the convergence and stability of the discrete differential equations are explained. Compared with the transmission of some broadband information, the use of a specific feature structure can increase the degree of freedom intelligent instrument, and give more detailed description of the echo parameter that can be used. By analyzing the basic principle of intelligent instrument, this paper uses the FDTD method to explain the signal of the instrument, and the simulation results are good.

关键词： Echo parameter intelligent instrument Numerical stability FDTD method

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An Improved K-means Clustering Algorithm Based on Hadoop Platform

An Improved K-means Clustering Algorithm Based on Hadoop Pla...

引用

international conference on Cyber Security Intelligence and analytics (CSIA)

作者： Hou, Xiangru Heilongjiang Int Univ Dept Informat Engn Harbin 150025 Heilongjiang Peoples R China

ISBN: (纸本)9783030152352;9783030152345

In order to solve the problem of poor clustering effect of K-means algorithm when dealing with massive high-dimensional data on Hadoop platform, and the existing improved algorithm is not conducive to parallelization. An improved K-means algorithm based on Hash is proposed on Hadoop platform. Firstly, the massive high-dimensional data is mapped to a compressed identification space, and then the clustering relationship is mined, and the initial clustering center is selected to avoid the sensitivity of the traditional K-means algorithm to randomly select the initial clustering center, and reduced the number of iterations of the K-means algorithm. Secondly, the overall parallelization of the algorithm is implemented in the framework of Map Reduce, and the degree of parallelization and execution efficiency is enhanced through the mechanisms of partition and combine. Finally, the experiments show that the algorithm not only improves the accuracy and stability of clustering, but also has a good processing speed.

关键词： Big data Hadoop K-means Clustering

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2nd international conference on Emerging Trends and Advances in Electrical Engineering and Renewable Energy, ETAEERE 2020

2nd International Conference on Emerging Trends and Advances...

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2nd international conference on Emerging Trends and Advances in Electrical Engineering and Renewable Energy, ETAEERE 2020

ISBN: (纸本)9789811586842

The proceedings contain 73 papers. The special focus in this conference is on Emerging Trends and Advances in Electrical Engineering and Renewable Energy. The topics include: Social Network Mental Disorders Detection Using Machine Learning;multi-layer Security in Cloud Storage Using Cryptography;web-Based Automatic Irrigation System;Discrete Wavelet Transform for CNN-BiLSTM-Based Violence Detection;student Location Tracking Inside College Infrastructure;finding Smelly or Non-smelly Using Injected and Revision Method;smart Bus Management and Tracking System;telemetry-Based Autonomous Drone Surveillance System;a Perceptive Fake User Detection and Visualization on Social Network;Route Search on Road Networks Using CRS;smart Fish Farming;perceptual Image Hashing Using Surf for Tampered Image Detection;diabetic Retinopathy Detection;traffic Status Update System With Trust Level Management Using Blockchain;agrochain: Ascending Blockchain Technology Towards smart Agriculture;unique and Dynamic Approach to Predict Schizophrenia Disease Using Machine Learning;live Bus Tracking System;a System for Informed Prediction of Health;a Safety Stick for Elders;intelligent Analysis for Wind Speed Forecasting Using Neural Networks;a Proficient Model for Action Detection Using Deep Belief Networks;semantic-Based Duplicate Web Page Detection;an Integrated and Dynamic Commuter Flow Forecasting System for Railways;attribute-Based data Management in Crypt Cloud;analysis on Sales Using Customer Relationship Management;Random Subspace-Based Hybridized SVM Classification for High-Dimensional data;A Unified and End-to-End Methodology for Predicting IP Address for Cloud and Edge computing;predicting the Farmland for Agriculture from the Soil Features Using data Mining;e-Commerce Site Pricing and Review Analysis;heart Disease Prediction Using Machine Learning;preface.

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Design of intelligent Manufacturing Product Identification and Detection System Based on Machine Vision

Design of Intelligent Manufacturing Product Identification a...

引用

international conference on Cyber Security Intelligence and analytics, CSIA 2020

作者： Zheng, Shandong Huizhou Economics and Polytechnic College HuizhouGuangdong516057 China

ISBN: (纸本)9783030433055

With the advent of the Industry 4.0 era, the development of smart factories and smart manufacturing industries has become the consensus of all countries. The intelligent manufacturing process is very complicated and usually consists of multiple links, each of which is completed by one or more intelligent manufacturing equipment. The environment perception and intelligent control technology of intelligent manufacturing equipment are the fundamental guarantee of adaptability, high precision and intelligent operation. It is also a technical problem that must be solved first in the development of intelligent manufacturing equipment. Based on the above background, the purpose of this article is the design of an intelligent manufacturing product recognition and detection system based on machine vision. In the context of the transition to intelligent manufacturing production mode, this paper proposes a method to directly generate matching templates using 3D models of cloud products. Second, this paper studies and compares various preprocessing algorithms such as image filtering and edge detection to determine bilateral filtering and Canny Edge detection performs image preprocessing, and then extracts contours from the processed binary image. Finally, based on the aforementioned theoretical research, a visual detection platform is built, and several products produced are matched with cloud storage data through experiments. The algorithm in this paper can meet the classification requirements of small and medium batches and customized products in flexible production lines, and realize the matching of actual product and cloud product model data. © Springer Nature Switzerland AG 2020.

关键词： Computer vision

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Social Media analytics during Pandemic for Covid19 using Topic Modeling

Social Media Analytics during Pandemic for Covid19 using Top...

引用

2020 international conference on smart Innovations in Design, Environment, Management, Planning and computing, ICSIDEMPC 2020

作者： Chakkarwar, Vrishali Tamane, Sharvari Government College of Engineering Computer Science and Engineering Department AurangabadMaharashtra India Jawaharlal Nehru Engineering College Information Technology Department AurangabadMaharashtra India

ISBN: (纸本)9781728159706

The entire world is facing the Covid19 pandemic. This pandemic has various consequences on the political, cultural, economical and social life of the community. Lockdown has affected the psychological impact on society. This is reflected in various social media sites. In such a phase social media analytics for twitter data can be useful for understanding public opinion. In this paper, we have applied the Latent Dirichlet Allocation Algorithm as a topic modeling algorithm. Topic modeling finds the main theme that pervades the large data set. Twitter media is considered as the most popular microblogging platform, hence data during this pandemic is extracted from twitter. Natural language processing Techniques applied as preprocessing and then topic modeling applied which has given satisfactory results in terms of perplexity as a performance measure. Topic extracted gives an idea of the impact of Covid19 on society through their opinion on twitter. This can be helpful for making future policies by policymakers. © 2020 IEEE.

关键词： Social networking (online)

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5th international conference on ICT for Sustainable Development, ICT4SD 2020

5th International Conference on ICT for Sustainable Developm...

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5th international conference on ICT for Sustainable Development, ICT4SD 2020

ISBN: (纸本)9789811582882

The proceedings contain 79 papers. The special focus in this conference is on ICT for Sustainable Development. The topics include: Regression Model to Estimate Effort for Software-Oriented Projects;framework for Securing IoT Ecosystem Using Blockchain: Use Cases Suggesting Theoretical Architecture;fault Exploratory data Analysis of Real-Time Marine Diesel Engine data Using R Programming;fuzzy-Based Predictive analytics for Early Detection of Disease—A Machine Learning Approach;ICT4D in Channelling Welfare Services in India: Case Study of Haqdarshak;a Low-Cost IoT-Enabled Device for Real-Time Air Quality Monitoring System;Vision-Based Driver Authentication and Alertness Detection Using HOG Feature Descriptor;toyama de Walking: Practice of Location-Based data Collection Using Augmented Reality Applications;modelling of Generation and Utilization Control for Isolated Hybrid Microgrid for Rural Electrification;A Fuzzy Time Series Prediction Model of the COVID-19 Epidemic;enhancing Trust and Immutability in Cloud Forensics;cybersecurity Attacks: Analysis of "WannaCry" Attack and Proposing Methods for Reducing or Preventing Such Attacks in Future;convolutional Neural Network and data Augmentation for Behavioral-Based Biometric User Identification;context of the Ghanaian Government: Social Media and Access to Information;new Horizons for the Application of Microalgae in the National Economy;classification of Leaves Using Convolutional Neural Network and Logistic Regression;a Multi-factorial Code Coverage Based Test Case Selection and Prioritization for Object Oriented Programs;factors Affecting the Local Governance;limiting Check Algorithm: Primality Test;Attitude of the international Students Towards Integrating ICT in Foreign Language Learning: A Case Study;emerging Trends in the Marketing of Financially Engineered Insurance Products;Pixel-Based Attack on ODENet Classifiers.

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Research on big data's prevention technology of financial systemic risk

Research on big data's prevention technology of financial sy...

引用

2020 international conference on intelligent Transportation, Big data and smart City, ICITBS 2020

作者： Zhang, Tingting Harbin Finance University Harbin City Heilongjiang Province150011 China

ISBN: (纸本)9781728166971

In order to reduce the seriousness and frequency of financial systemic risk in the new era, this paper puts forward a novel big data prevention technology of financial systemic risk. With the combination of big data technology, Internet technology and cloud computing technology, this technology can monitor the financial market in real time and guard against suspicious information. The research results show that this technology realizes the close combination of big data and the financial market, reduces the cross-infection of financial systemic risk, and improves the controllability of financial systemic risk. © 2020 IEEE.

关键词： Big data

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Privacy in the Era of 5G, IoT, Big data and Machine Learning 2

Privacy in the Era of 5G, IoT, Big Data and Machine Learning

引用

2nd IEEE international conference on Trust, Privacy and Security in intelligent Systems and Applications (TPS-ISA)

作者： Bertino, Elisa Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA

ISBN: (纸本)9781728185439

Technological advances, such as IoT devices, cyberphysical systems, smart mobile devices, cloud systems, data analytics, social networks and increased communication capabilities, are making possible to capture, quickly process and analyze huge amounts of data from which to extract information critical for many tasks, such as healthcare and cyber security. Such an intensive use of data raises however major privacy concerns, especially in the mobile application ecosystem. In this paper, we first show different examples of privacy breaches that can arise in such ecosystem. Those examples show that achieving privacy is challenging and there is no unique technique that one can use;rather one must combine different techniques depending also on the intended use of data. We then outline critical challenges towards achieving comprehensive privacy solutions.

关键词： Mobile applications cellular network protocols data privacy data transparency privacy enhancing techniques

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COVID-19: Geospatial Analysis of the Pandemic—A Case Study of Bihar State, India, Using data Derived from Remote Sensing Satellites and COVID-19 National Geoportal 9th

COVID-19: Geospatial Analysis of the Pandemic—A Case Study ...

引用

9th international conference on Frontiers in intelligent computing: Theory and Applications, FICTA 2021

作者： Kumari, Pallavi Sharma, Richa Rathore, Virendra Singh Department of Remote Sensing Birla Institute of Technology Ranchi Mesra India Birla Institute of Technology Ranchi Mesra India

ISBN: (纸本)9789811666230

The state of Bihar has a sizeable population which is spread all over the nation especially the skilled and non-skilled labourers. This populace contributes towards human resource as service providers for nation building in various sectors across the length and breadth of India. The declaration by the World Health Organization (WHO) of the spread of COVID-19 virus as a pandemic brought a nationwide lockdown from 23rd of March 2020 to curb its spread. These daily wage workers were stranded far and wide without any resources. The transport communication was also withdrawn initially against the spread. Now, as soon as the conditions became conducive for the migrant labours to return to the native state of Bihar, there was a fear for disaster due to these returning migrant labour force as they probably could become a vector for the spread of COVID-19 pandemic in the state. The state government in consonance with the Central Government formed strict protocols to be adhered to, for these returning migrants. The present paper statistically analyses the spread of this pandemic once the migrant populace began returning to their home state. It investigates whether the influx of so many humans from various parts of the country would become the hub of the spread of the virus causing infectious hot spots or not. Simultaneously, as many researchers were trying to correlate the presence of atmospheric nitrogen dioxide (NO2) with the spread of COVID-19 virus, the paper tried to relate the amount of NO2 present over the study area on the day the maximum number of cases were reported in the study area. Evaluation of atmospheric nitrogen dioxide (NO2) used for the present paper was derived from satellite data. Time series analysis of this NO2 data was done. This enabled us to identify the peak day and the day when the NO2 levels were minimum. Incidentally, the number of COVID-19 cases reported synchronized with the NO2 levels in the atmosphere. Spatial auto-correlation was performed u

关键词： Coronavirus

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