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data Extraction Based on Web Scrapy 11th

Data Extraction Based on Web Scrapy

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11th international conference on Innovations in Bio-Inspired computing and Applications, IBICA 2020 and 10th World Congress on Information and Communication technologies, WICT 2020

作者： Alshammari, Reem Alrashed, Rwan Almutiri, Atheer Alwalah, Mathail Al-marrai, Wadha Alqahtani, Dana Alzahrani, Amani Computer Department College of Science and Humanities in Jubail Imam Abdulrahman Bin Faisal University Jubail Industrial City Saudi Arabia

ISBN: (纸本)9783030736026

In recent years, with the growth of big data the information on the Internet is increasing rapidly, it has become important to have technologies that help the user to obtain the information efficiently and easily. Many undergraduate students buy books and school supplies through online stores such as Amazon and other websites. How to effectively obtain information from the websites. This paper implements a Python web scraper to extract the data from the target websites and store the collected data on the comma separated values file. This system aims to collect information about the products that undergraduate students need from the target websites and return them to the users with a simple page. Users can search for product that they are want to obtain information about it and the crawler crawled the following information (product name, product price, product URL) from the following online stores: Amazon, eBay, Jarir, and Extra then stored it in the comma-separated values file for information analysis. The data scraped by the crawler and saved on the comma-separated values file is 9083 records. The importance of the system lies in its effective ability to reach products fast and high efficiency and enable price comparison of similar products on different online shopping stores therefore saving the searching time. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Python

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A Review on Comparative study of 4G, 5G and 6G Networks

A Review on Comparative study of 4G, 5G and 6G Networks

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international conference on Contemporary computing and Informatics (IC3I)

作者： Pravin Ramdas Kshirsagar Dhoma Harshavardhan Reddy Mallika Dhingra Dharmesh Dhabliya Ankur Gupta Department of Artificial Intelligence G H Raisoni College of Engineering Nagpur Maharashtra India Trainee Security Analyst JunoClinic Davman Technology Services Pvt. Ltd Mumbai Maharashtra India Department of Mathematics and Statistics Manipal University Jaipur Jaipur Rajasthan India Department of Information Technology Vishwakarma Institute of Information Technology Pune Maharashtra India Department of Computer Science and Engineering Vaish College of Engineering Rohtak Haryana India

In the previous several years, wireless telecommunications technology has seen a significant change. The term “generation” in the context of wireless communication typically describes to a shift in the essential characteristics of the assistance being offered, such as transmission technologies, bit rates, frequency bands, channel frequency bandwidth, and data transfer capacity. One of the most active technological fields that is expanding too quickly is the wireless age. There is a need to implement such technologies that can be integrated and adjusted in order to produce a more advanced and unified system because there are numerous superior technologies available. In this work, we provide a summary of several wireless telecommunications technologies, in particular, 4G, 5G, and 6G Networks, and a detailed comparison between them.

关键词： Wireless communication 6G mobile communication Satellites 5G mobile communication Web and internet services Market research Telecommunications

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Hybrid Approach for Bots Detection in Social Networks Based on Topological, Textual and Statistical Features 4th

Hybrid Approach for Bots Detection in Social Networks Based ...

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4th international Scientific conference on Intelligent Information technologies for Industry (IITI)

作者： Vitkova, Lidia Kotenko, Igor Kolomeets, Maxim Tushkanova, Olga Chechulin, Andrey Russian Acad Sci St Petersburg Inst Informat & Automat 14 Th Liniya39 St Petersburg 199178 Russia

ISBN: (纸本)9783030500979

The paper presents a hybrid approach to social network analysis for obtaining information on suspicious user profiles. The offered approach is based on integration of statistical techniques, data mining and visual analysis. The advantage of the proposed approach is that it needs limited kinds of social network data ("likes" in groups and links between users) which is often in open access. The results of experiments confirming the applicability of the proposed approach are outlined.

关键词： Social network analysis Visual analysis data mining Statistics Bots detection

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Focused Stochastic Neighbor Embedding for Better Preserving Points of Interest

Focused Stochastic Neighbor Embedding for Better Preserving ...

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IEEE/ACM international Symposium on Big data computing (BDC)

作者： Rafael Baez Ramirez Sanuj Kumar Tuan M. V. Le Huiping Cao Dept. Computer Science The University of Texas at El Paso El Paso TX USA Dept. Computer Science New Mexico State University Las Cruces NM USA

Dimensionality reduction aims to find low-dimensional embeddings of high-dimensional data such that the low-dimensional representation preserves some meaningful properties of structures in the original data. When low-dimensional space is 2- or 3-dimensional, the low-dimensional embeddings can be visualized using a scatterplot map. Most of the existing methods try to preserve the local neighborhoods of all data points. However, in general, it is impossible to retain all such information for all data points in the low-dimensional space. As a result, there could be some data points whose neighborhoods are not faithfully displayed in the visualization due to information loss. If the information loss happens around a specific set of points of interest (e.g., specific patients, or proteins under observed), this may be problematic because the withdrawn insights may not be accurate for these observed data points. Therefore, in this paper, we introduce a problem called focused dimensionality reduction where given an original high-dimensional dataset and a set of points of interest, we want to find 2- or 3-dimensional embeddings of the original data such that the information loss in the local neighborhoods surrounding the points of interest is minimized as much as possible. In other words, if the information loss is inevitable, it should not happen around the points of interest. To solve the problem, we extend the stochastic neighbor embedding method and introduce a focused objective function where we put more weight on losses that involve points of interest. Experiments on real-world datasets show that our proposed method is better in preserving the local neighborhood structure of points of interest while the generated visualizations are as good as those generated by the stochastic neighbor embedding method.

关键词： Dimensionality reduction Proteins data visualization Big data Linear programming

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Designing Software Instruments for Analysis and Visualization of data Relevant to Playing Educational Video Games 4th

Designing Software Instruments for Analysis and Visualizatio...

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4th international conference on Human Interaction and Emerging technologies: Future Applications, IHIET – AI 2021

作者： Dankov, Yavor Bontchev, Boyan Faculty of Mathematics and Informatics Sofia University "St Kl. Ohridski" Sofia Bulgaria

ISBN: (纸本)9783030732707

Technology-enhanced learning applies more and more educational video games for increasing students’ motivation and engagement, for achieving better learning outcomes. This paper presents the designed functionalities of several software instruments created as analytics and visualization tools for analysing and evaluating both learning and playing outcomes of the player with different knowledge, learning goals, preferences, and learning style. This paper is based on previous publications of the authors and we step on the taxonomy of instruments for facilitated design and evaluation of video games for education (TIMED-VGE) to develop the design of the core functionalities of the software instruments for analysis and visualization of data about playing educational video games. The tools are under development within the APOGEE (smArt adaPtive videO GamEs for Education) educational game platform and will enrich its core functionalities and overall user experience by providing users with a wide range of analytics and data visualization capabilities. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Visualization

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Maximum surface settlement prediction in EPB TBM tunneling using soft computing techniques 3

Maximum surface settlement prediction in EPB TBM tunneling u...

引用

3rd international Scientific conference of Engineering sciences and advances technologies, IICESAT 2021

作者： Samadi, H. Hassanpour, J. Farrokh, E. School of Geology College of Science University of Tehran Tehran Iran Department of Mining Engineering Amirkabir University of Technology Tehran Iran

Earth pressure balance (EPB) TBMs are commonly used for soft ground tunneling in urban areas. In metro tunnels' excavation, designing a comprehensive monitoring system to control surface settlement is essential to prevent damage to surface structures. The present study aims to develop new prediction models to estimate the ground surface settlement using two soft computing techniques, SVM and ANN-MLP, and a multiple variable regression model to develop the new empirical formulas. The TBM operational parameters collected from the Tehran metro line 6, South extension (TML6-SE) project have been applied to confirm the provided models. In the data analysis process, the relationships between various parameters (torque index, thrust index, and earth pressure) and the ground surface settlement are investigated. Moreover, several statistical evaluation criteria are implemented to evaluate the performance of the developed models. The results show that the predicted values are in good agreement with the real data. The results can be used for similar ground and TBM tunneling conditions. © Published under licence by IOP Publishing Ltd.

关键词： Regression analysis

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Smart Tracker Device for Women Safety 3

Smart Tracker Device for Women Safety

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3rd international conference on advances in computing, Communication Control and Networking, ICAC3N 2021

作者： Johri, Prashant Sharma, Vishnu Gupta, Varuna Baghela, Vishwadeepak Singh Galgotias University School of Computer Science and Engineering India GCET Department of CSE Greater Noida India CHRIST University Department of Computer Science New Delhi India

ISBN: (纸本)9781665438117

Internet of Things (IoT) technologies assists by which machines, circuits, and many types of devices and interfaces communicate with one another. This IoT technology is useful for several purposes, especially in the field of Networking and Run-time data storage. Considering Women safety as our primary objective, we have used this technology and some other hardwares, including Raspberry Pi, to help the user in case of any emergency. Here also, with the help of IoT we are trying to make a device which can track the runtime location and the live, exact and efficient coordinates of the system which is in track. In the above context, in case of emergencies, it is very important to know the right place for the person to perform several important and critical actions whatsoever present at the right *** GPS coordinates can be used to solve and analyse this problem. Additionally, we intend to add a voice recorder in case the women want to record any suspicious activity or information that can be helpful in the future for evidence purposes. In this paper, IoT is acting directly by receiving a person's GPS links from his server. Furthermore, we are combining the web interface with Google Maps on a single server so that the user's location can be tracked immediately using real-time *** application can be used for wildlife, school-aged children, parent safety, and transportation services where location is a key factor. Although there are several direct and indirect usages of this project, the main use to which the project is concentrated is the use of this device to help our loved ones in the time of need. © 2021 IEEE.

关键词： Internet of things

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Private data Protection as Countermeasure Against Misuses of Medical Intelligent Technology data: a Literature Study

Private Data Protection as Countermeasure Against Misuses of...

引用

international conference on computing, Engineering, and Design (ICCED)

作者： Praseptiadi Pratama Dahlian Persadha Armi Susandi Teddy Mantoro Medical Intelligence Post-graduate Program State Intelligence College Bogor Indonesia Department of Computer Science Media-Tech Lab Sampoema University Jakarta Indonesia

ISBN: (纸本)9781665453905

Medical technologies develop along with the development of the Industrial Revolution 4.0 (I.R. 4.0). In I.R. 4.0, a collaborative ecosystem is formed between cyber technology and automation technology to be able to create "intelligent" systems to facilitate various human activities, including activities related to health. The most important thing in the system is data since it is the basis for the development of various key icons technologies in the I.R. 4.0: Cloud computing, Internet of Things (IoT), Big data, Artificial Intelligence (Al), Augmented Reality, and Cyber Security. Unfortunately, with the variety of I.R. 4.0 products, the data produced by these products is also scattered everywhere. Misuse of this scattered data—which the owner may not even know where the data are stored—can harm the individual concerned, and even the very existence of the state. Healthcare services now are undergoing Digital Transformation in which these data were needed to build high-quality services. The Health Digital Transformation strategy changes the direction of health services to be simpler and easier to use by the public, increasing efficiency, and thus providing a higher quality health service system so that it can trigger better economic growth. On the regulatory aspect, The Private data Protection Bill was proposed by the Indonesian government to protect the data of the Indonesian people. Literature studies are used to obtain knowledge between the three: technology development, digital transformation in healthcare, and private data protection. This study seeks how important private data protection regulation is to realize digitally transformed healthcare. The study conducted indicates Private data Protection Bills have the means to guarantee the rights of the data owner and prevent their data (including medical intelligence data) to be misused.

关键词： Economics Digital transformation Government Ecosystems data protection Regulation Internet of Things

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data Analysis using Robot Process Automation Study on Web Scraping using UI Path Studio

Data Analysis using Robot Process Automation Study on Web Sc...

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advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Anant Mishra Shivam Mishra N. Suresh Kumar School of Computing Science & Engineering Galgotias University Greater Noida India

Automation has been into existence since the mid Fifties but had simplest began to gain attention lately. The RPA software program makes use of existing generation’s interface to automate the human detail in the technique. So, essentially, there's no want for human intervention. web scraping is a software of robot system Automation that is used in almost all of the industries. either or not it's a e-trade internet site, commodities buying and selling web sites, or any internet site and so forth. you can scrape the information from any of them based on your hobby. Now, the problem with guide scraping by hand is that it's miles at risk of mistakes and takes numerous times. also, the facts available on websites does now not change in any respect. up to date regularly, for this reason facts saved domestically might not usually be terrible. So, industries can actually automate this mission. The main objective of the project is to save time and send the updated information to the person using RPA technology. As this COVID-19 Global Pandemic going on, we thought of creating a project around COVID-19. So, in the project we will use data Scrapping to extract Web Table (which contains COVID-19 data such as number of affected people, recovered people etc.) from web page. And, write the extracted data into Excel then we will send that excel over the email as attachment. In this project we researched how we can send data through email using RPA and extract the data from live covid_19 website. For software automation, there are many software’s that are available in market. The main RPA vendors are UiPath, Automation Anywhere, and Blue Prism. So, to complete our RPA project, we have chosen UiPath which the best in the field of automation. You should be familiar with at least one of these tools before working on the following projects. This paper aims to provide RPA reviews as technical, as well as its implementation applications.

关键词： COVID-19 Industries Automation Pandemics Web pages Closed box data mining

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Improving Medical Predictions with Label Noise Tolerant Classification

Improving Medical Predictions with Label Noise Tolerant Clas...

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advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Shivam Vernekar Arun Ayyar Arun Rajagopalan Bijendra Kumar Vivek Kumar Mishra Evive Software Analytics Pvt. Ltd. Bengaluru India Santa Fe Research Pvt Ltd Chennai India Data Science Evive Software Analytics Pvt. Ltd. Bengaluru India Electrical and Electronics Engineering Galgotia College of Engineering and Technology Greater Noida India

Supervised machine learning algorithms depend crucially on availability of a large pool of correctly labelled instances. However many real world datasets may contain noisy features and label values. This is even more problematic for medical datasets since noise can be asymmetric (class dependent) due to imprecise class definitions or subjective human biases during data collection. There is easy availability of a large pool of unlabelled instances which can’t be directly used for training, for example raw data from medical devices like fitness trackers, data from health surveys etc. Labelling them (with respect to certain task) with the help of human experts might be a time consuming and a costly process. Besides, learning algorithms trained on noisy datasets can reduce the quality of future inferences making them unsuitable for business use-cases. In this paper we propose a semi-supervised learning based approach where we combine information embedded in unlabelled and incorrectly labelled instances with a very small set of correctly labelled instances. To the best of our knowledge this is the first work based on semi-supervised learning for reducing the noise in generated predictions using imperfect datasets. It is demonstrated through extensive experimentation using a medical diagnostic diabetes dataset, that by using only a fraction of correctly labelled instances, we are able to generate high quality predictions on unseen data.

关键词： Training Medical devices Machine learning algorithms Noise reduction Semisupervised learning Diabetes Noise measurement

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