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Analysis on NSAW Reminder Based on big data Technology 2021

Analysis on NSAW Reminder Based on Big Data Technology

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2021 3rd international conference on Artificial intelligence and Advanced Manufacture

作者： Ziheng Jin The 5th Business Division Nanjing Research Institute of Electronic Engineering China

ISBN: (纸本)9781450385046

NSAWS is an intelligent and real-time large database management system. By analyzing the user identity data and access rights contained in the collected information, the NSAWS finds out the potential risks and issues an alarm notice in a timely manner. This paper mainly studies how to strengthen the prevention of network attacks in BD environment from the following aspects. This paper first introduces the common technology on the Internet in our country and its application status; secondly, it expounds the architecture, deployment mode and operation mode of the large database system based on the basic security facilities such as cloud computing platform and firewall. Then the traditional NSAWS is analyzed and the simulation platform is tested. The results show that the platform has high accuracy and stability in alerting network security hazards and can effectively protect network security.

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Artificial intelligence based Smart Cosmetics Suggestion System based on Skin Condition

Artificial Intelligence based Smart Cosmetics Suggestion Sys...

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Automation, computing and Renewable Systems (ICACRS), international conference on

作者： Kavyashree N Rama Satish K V Prasanna Rajaram Rasal Rahul Jalindar Jadhav M. Saidireddy K G Kharade Department of MCA Dr.Ambedkar Institute of Technology Bangalore Department of AIML RNS Institute of Technology Bengaluru Department of Computer Application Bharati Vidyapeeth (Deemed to be University) Yashwantrao Mohite Institute of Management Karad Department of CSE Computer Science and Engineering Koneru Lakshmaiah Education Foundation Department of Computer Science Shivaji University Kolhapur Maharashta

ISBN: (纸本)9781665460859

Today, cosmetics have a big impact on how people look. Customers can access a range of products and conduct e-commerce on the website. Choosing the best product for our skin might be challenging. It offers a prediction approach so that individuals can select the goods that are suitable for their skin type. Configuration concepts perform better than conventional methods. It uses deep learning technology to streamline the complex procedures in the IT industry for cosmetics and beauty care. Along with its clients and product offerings, the beauty sector has grown over time. With the expansion of products and consumers, selecting the right cosmetics becomes more and more important. Due to the substantial influence that cosmetics have on a person’s appearance, the client should choose the best cosmetics for themselves based on personal factors (skin type). Given that every person has a distinct type of skin, choosing cosmetics that suit the person may be difficult. The composition depends on whether the client has oily, dry, or neutral skin. Even the product the user is looking for can have an extremely difficult skin condition; AI algorithms are perfectly suited to address this problem since they can evaluate massive amounts of unstructured data and generate insightful results.

关键词： Deep learning Industries Renewable energy sources Automation Image color analysis Knowledge based systems Skin

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Logistics Network Deployment Planning under the Background of big data Technology 2021

Logistics Network Deployment Planning under the Background o...

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2021 3rd international conference on Artificial intelligence and Advanced Manufacture

作者： Xiaoxiao Wang Dalian Vocational & Technical College China

ISBN: (纸本)9781450385046

In recent years, with the rapid development of e-commerce, the technology of online shopping platform is becoming more and more mature, followed by the emergence of a large number of e-commerce platforms, such as Taobao, JD, pinduoduo, etc. Most people live a fast-paced life and have little free time. Most people prefer online shopping and then distribute the purchased goods through third-party logistics. This method is simple, convenient and fast. In recent years, the rise of modern information technologies such as Internet of things, cloud computing and big data has had a significant impact on the development and innovation of logistics industry. By building e-commerce and other information platforms based on big data, manufacturers, distributors, consumers, logistics providers and financial service providers in the supply chain can be promoted to eliminate space barriers for communication and exchange. The application of big data technology can effectively integrate e-commerce platform and urban and rural logistics system, so that their data can be shared, which is conducive to reducing their dual uncertainty and improving operation efficiency. Based on the above analysis, this paper discusses the development and planning of logistics points under the background of big data from the perspective of big data. Based on the analysis of the research situation at home and abroad, this paper makes a theoretical and systematic research on the cost design of urban logistics system. Firstly, taking Hanzhong City as an example, this paper demonstrates the applicability of the prediction method, and then puts forward the principles and principles of urban logistics design. Secondly, combined with the characteristics of the city, this paper studies the prediction method and urban logistics demand prediction model, and the overall planning route of logistics city design. Finally, the layout and design method of urban logistics service function are put forward. Experiments show

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The SMART BEAR Project: An Overview of Its Infrastructure 7th

The SMART BEAR Project: An Overview of Its Infrastructure

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7th and 8th international conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2021 and ICT4AWE 2022

作者： Su, Qiqi Peretokin, Vadim Basdekis, Ioannis Kouris, Ioannis Maggesi, Jonatan Sicuranza, Mario Acebes, Alberto Bucur, Anca Mukkala, Vinod Jaswanth Roy Pozdniakov, Konstantin Kloukinas, Christos Koutsouris, Dimitrios D. Iliadou, Elefteria Leontsinis, Ioannis Gallo, Luigi De Pietro, Giuseppe Spanoudakis, George Department of Computer Science City University of London London United Kingdom Philips Research Eindhoven Netherlands SPHYNX Technology Solutions AG Zug Switzerland Biomedical Engineering Laboratory School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Computer Science Department Università degli Studi di Milano Milan Italy Institute for High-Performance Computing and Networking National Research Council of Italy ICAR - CNR Naples Italy Atos Research and Innovation Madrid Spain 1st Otolaryngology University Department National and Kapodistrian University of Athens Athens Greece 1st Cardiology Clinic Medical School National and Kapodistrian University of Athens Athens Greece

ISBN: (纸本)9783031374951

The paper describes a cloud-based platform that utilizes Artificial intelligence (AI) and Explainable AI techniques to deliver evidence-based, personalized interventions to individuals over 65 suffering or at risk of hearing loss, cardiovascular disease, cognitive impairments, balance disorders, or mental health issues, while supporting efficient remote monitoring and clinician-driven guidance. As part of the SMART BEAR integrated project, this platform has been developed to support its large-scale clinical trials. The platform consists of a standards-based data harmonization and management layer, as well as a security component, a big data Analytics system, a Clinical Decision Support system, and a dashboard component to facilitate efficient data collection across pilot sites. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Artificial intelligence

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Airfoil Inverse Design using Conditional Generative Adversarial Networks

Airfoil Inverse Design using Conditional Generative Adversar...

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international conference on Control, Automation, Robotics and Vision (ICARCV)

作者： Xavier Tan Dai Manna Joyjit Chattoraj Liu Yong Xu Xinxing Dao My Ha Yang Feng Computing & Intelligence Department Institute of High Performance Computing A*STAR Singapore School of Informatics & IT Diploma in Big Data Analytics Temasek Polytechnic Singapore Fluid Dynamics Department Institute of High Performance Computing A*STAR Singapore

ISBN: (纸本)9781665476881

Creating an aerodynamic shape, like an airfoil wing, requires many factors to be considered, especially aerodynamic properties such as its lift-to-drag ratio (L/D). Currently, generating feasible airfoil shapes usually requires computationally expensive tools, such as Computational Fluid Dynamics (CFD). In recent years, increasing work has been directed to utilizing machine learning algorithms to synthesize accurate airfoil shapes while reducing the required computational cost. Generative Adversarial Network (GAN) is one of many algorithms to see success in airfoil shape optimization and is shown to generate good airfoils given a small set of training examples. This paper focuses on implementing a conditional GAN (cGAN) based framework with various filters for airfoil inverse design problem. By labelling the training dataset with aerodynamic characteristics separated by pre-defined thresholds to lift-to-drag ratio (L/D) and shape area, the class labels will be able to guide the network to generate different classes of airfoils influenced by these characteristics. Together with layers of Savitzky-Golay (SG) filter and B-Spline Interpolation, the developed model was shown to achieve good performance in generating new airfoils. In addition, we explored the viability of adding Wasserstein loss from Wasserstein GAN into the network architecture, forming a cWGAN-GP. Testing results showed that cWGAN-GP was able to achieve better performance for a specific airfoil class.

关键词： Training Interpolation Machine learning algorithms Shape Atmospheric modeling Computational fluid dynamics Generative adversarial networks

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Logistic Regression Model for Measuring Perception on Open and Distance Learning (ODL) during COVID-19 Pandemic based on Impeding Factors among Students

Logistic Regression Model for Measuring Perception on Open a...

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computing (ICOCO), IEEE international conference on

作者： Alia Najwa Abdul Mizan Farah Aliah Nur Mansor Nor Azura Md Ghani Adina Najwa Kamarudin Mahayaudin M. Mansor Siti Afiqah Muhamad Jamil Nurain Ibrahim College of Computing Informatics and Media Universiti Teknologi MARA Shah Alam Selangor Malaysia Department of Mathematical Sciences Faculty of Science Universiti Teknologi Malaysia Johor Bahru Malaysia Institute for Big Data Analytics and Artificial Intelligence (IBDAAI) Kompleks Al-Khawarizmi Universiti Teknologi MARA Shah Alam Selangor Malaysia

ISBN: (纸本)9781665489973

Authorities have suggested emergency remote instruction to guarantee that students are not left idle during the pandemic due to the sudden closing of educational facilities. Then for the time being, traditional methods (face-to-face) have been replaced by Open and Distance Learning (ODL). Face-to-face learning was preferred by the majority of students over online learning since students were not able transit to online learning and lacked inspiration. Hence, this study focuses on perception towards ODL during COVID-19 among statistics’ students at FSKM UiTM Shah Alam based on some impeding factors such as social issue, lecturer issue, accessibility issue, academic issue, generic skills and learner intentions. The aim of this study is to investigate the perception of statistics’ students on ODL based on impeding factors and to identify the significant impeding factors effect on statistics students’ perception on ODL. There are 160 observations that are used in this study. The methods that are being used in this study are descriptive analysis and logistic regression. Overall, from the result obtained, students’ perception on ODL are approximately to agree for social issue, academic issue and learner intentions variables. Meanwhile, the significance impeding factors in this study are social issue and learner intentions. This study may help higher education institution to improve and make a better strategy to improve the existing teaching method that have been applied by all lecturers.

关键词： COVID-19 Computer aided instruction Pandemics Computational modeling Education Logistics

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CH-Go: Online Go System Based on Chunk data Storage

CH-Go: Online Go System Based on Chunk Data Storage

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IEEE international conference on High Performance computing and Communications (HPCC)

作者： Hui Lu Chuan Li Yiming Yang Cheng Li Ashraful Islam Computer School Sichuan University Chengdu China School of Computing National University of Singapore Singapore Singapore

The training and running of an online Go system require the support of effective data management systems to deal with vast data, such as the initial Go game records, the feature data set obtained by representation learning, the experience data set of self-play, the randomly sampled Monte Carlo tree, and so on. Previous work has rarely mentioned this problem, but the ability and efficiency of data management systems determine the accuracy and speed of the Go system. To tackle this issue, we propose an online Go game system based on the chunk data storage method (CH-Go), which processes the format of 160k Go game data released by Kiseido Go Server (KGS) and designs a Go encoder with 11 planes, a parallel processor and generator for better memory performance. Specifically, we store the data in chunks, take the chunk size of 1024 as a batch, and save the features and labels of each chunk as binary files. Then a small set of data is randomly sampled each time for the neural network training, which is accessed by batch through yield method. The training part of the prototype includes three modules: supervised learning module, reinforcement learning module, and an online module. Firstly, we apply Zobrist-guided hash coding to speed up the Go board construction. Then we train a supervised learning policy network to initialize the self-play for generation of experience data with 160k Go game data released by KGS. Finally, we conduct reinforcement learning based on REINFORCE algorithm. Experiments show that the training accuracy of CH-Go in the sampled 150 games is 99.14%, and the accuracy in the test set is as high as 98.82 %. Under the condition of limited local computing power and time, we have achieved a better level of intelligence. Given the current situation that classical systems such as GOLAXY are not free and open, CH-Go has realized and maintained complete Internet openness.

关键词： Training Monte Carlo methods Smart cities Supervised learning Neural networks Games Reinforcement learning

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Proceedings - 2016 IEEE 14th international conference on Dependable, Autonomic and Secure computing, DASC 2016, 2016 IEEE 14th international conference on Pervasive intelligence and computing, PICom 2016, 2016 IEEE 2nd international conference on big data intelligence and computing, datacom 2016 and 2016 IEEE Cyber Science and Technology Congress, CyberSciTech 2016, DASC-PICom-datacom-CyberSciTech 2016

Proceedings - 2016 IEEE 14th International Conference on Dep...

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14th IEEE international conference on Dependable, Autonomic and Secure computing, DASC 2016, 14th IEEE international conference on Pervasive intelligence and computing, PICom 2016, 2nd IEEE international conference on big data intelligence and computing, datacom 2016 and 2016 IEEE Cyber Science and Technology Congress, CyberSciTech 2016, DASC-PICom-datacom-CyberSciTech 2016

ISBN: (纸本)9781509040650

The proceedings contain 149 papers. The topics discussed include: a scheme for controlling functionality of mobile device using specialized codes;a cyber voice recognition with low SNR;evaluation of network risk using attack graph based security metrics;what influence the students'learning experience? the impact of peer learning in an online environment;the design and implementation of a high-efficiency distributed web crawler;ontology modeling and application of multi-agent for negotiation system;a preliminary study of plant domain ontology;an ontology pattern for emergency event modeling;intrusion detection based on IDBM;and a MapReduce-based framework for analyzing web logs in offline streams.

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A Transparent big data Storage Facility (Demo Abstract) 5

A Transparent Big Data Storage Facility (Demo Abstract)

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5th IEEE international conference on big data intelligence and computing, datacom 2019

作者： Hsiao, Hung-Chang Lin, Chia-Wei Tsai, Chia-Ping National Cheng Kung University Department of Computer Science and Information Engineering Tainan70101 Taiwan Group Kaohsiung Taiwan Taiwan

ISBN: (纸本)9781728141176

We present an infrastructural, big data storage facility for Taiwan's semiconductor manufacturing industry. The service, named transparent data storage (TDS), has been built for operating in production systems. It evolves over time by incrementally accommodating users' requirements, and tailors to Taiwan's semiconductor manufacturing industry such as wafer fabrication foundry and IC packaging/test. Specifically, TDS is a RESTful, distributed big data storage facility. Users simply rely on TDS to access data objects stored in Hadoop with RESTful APIs. In addition, TDS is scalable and reliable. Moreover, TDS is efficient and effective by intelligently selecting either Hadoop distributed file system (HDFS) or database (HBase) for publishing data objects. This demo paper demonstrates the design and implementation features for TDS. © 2019 IEEE.

关键词： Hadoop, big data storage, Services computing

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big data Analysis and Potential Development Research of Regional Logistics Warehousing Based on Baidu Index and Warehouse in Cloud 22

Big Data Analysis and Potential Development Research of Regi...

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Proceedings of the 2022 5th international conference on Algorithms, computing and Artificial intelligence

作者： Zhe Wang Juan Huang Lijuan Xu Qiaomei Zeng Renqiang Li Shixin Li Lin Zhou School of Economics and Management Sichuan Tourism University China School of Economics and Management Sichuan Tourism University China and School of Transportation and Logistics Southwest Jiaotong University China

Based on the Baidu Index, taking "warehousing" and "warehouse" as the keywords, the Baidu search index of "warehousing" and "warehouse" nationwide is statistically analyzed. It ... 详细信息

ISBN: (纸本)9781450398336

Based on the Baidu Index, taking "warehousing" and "warehouse" as the keywords, the Baidu search index of "warehousing" and "warehouse" nationwide is statistically analyzed. It is found that the Baidu search index with "warehousing" and "warehouse" as the keywords has increased significantly before and after the epidemic, indicating that the basic role of logistics warehousing in the national economic and social development is increasingly apparent, and the corresponding demand for logistics warehousing is growing. Based on the big data of Warehouse in Cloud, the incomplete statistical analysis of "warehousing demand" by province (municipality directly under the central government) of "demand location" is similar to the analysis of the differences of different search population sources (regions and provinces) through the "population portrait" of Baidu Index. For the incomplete statistical analysis of "warehousing demand" and "warehousing supply" of cities in Sichuan and Chongqing, the correlation analysis of warehousing rent and demand area is focused on the main cities in Sichuan and Chongqing (incomplete statistics), and on this basis, the potential analysis of warehousing rent and demand area is carried out for the main cities in Sichuan and Chongqing (incomplete statistics). It is found that Chengdu and Chongqing have obvious attraction effect on logistics and warehousing in Sichuan and Chongqing. Moreover, Mianyang, Yibin, Dazhou, Luzhou, Nanchong, Deyang, Zigong and Leshan, have certain economic foundation and comparative advantages in terms of the potential of logistics warehousing rent and the potential of logistics warehousing demand area. Optimizing regional industrial layout, accelerating economic development and transportation logistics construction could play a positive role in achieving regional coordinated development. Furthermore, cultivating and strengthening regional central cities can promote regional coordinated and sustainable development.

关键词： Baidu Index

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