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Numerical Analysis of Mechanical Characteristics of Joint Structure of Steel Pipe Sheet Pile Foundation 16th

Numerical Analysis of Mechanical Characteristics of Joint St...

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16th international conference of the international Association for computer Methods and advances in Geomechanics, IACMAG 2021

作者： Miyazaki, Yusuke Sawamura, Yasuo Kusaba, Shoma Kimura, Makoto Nishihara, Tomohiko Kosaka, Takashi Hattori, Masahiro Maekawa, Kazuhiko Department of Urban Management Kyoto University C1-334 Kyoto University Katsura Campus Nishikyo-ku Kyoto615-8540 Japan Construction Unit Kansai Branch Kajima Corporation Co. Ltd 3-1 Motoakasaka 1-chome Minato-ku Tokyo107-8388 Japan Department of Civil and Earth Resources Engineering Kyoto University C1-582 Kyoto University Katsura Campus Nishikyo-ku Kyoto615-8540 Japan Construction Management Headquarters Hanshin Expressway Co. Ltd. 16-1 Shinko-cho Chuo-ku Kobe650-0041 Japan Research Section 1 Survey and Research Division Hanshin Expressway Technology Center 4-5-7 Minami-honmachi Chuo-ku Osaka541-0085 Japan

ISBN: (纸本)9783030645175

the aim of this study is to clarify the mechanical behavior of the joint parts in a steel pipe sheet pile (SPSP) foundation under horizontal loading. the foundation structure of SPSPs is constructed by coupling the joints of each SPSP in the ground with the injection of mortar into the joints. For this purpose, the mechanical behavior of the SPSP foundation should be discussed with a clear understanding of the mechanical behavior of the SPSP joints. In the design criteria under lateral loading, however, only the vertical shearing of the joint parts is considered as critical. Accordingly, the precise understanding of the lateral loading capacity of the SPSP foundation was investigated in this study through model experiments and a reproduction analysis by the 3D finite element method. Simply stated, from the lateral loading tests on the SPSP models and their reproduction analysis by a 3D FEM, it was found that the lateral loading causes vertical shear displacements of the joints of the piles arranged in parallel to the loading direction and almost no displacements of the joints of the piles arranged perpendicularly to the loading direction. © 2021, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Finite element method

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Satellite-Based Water Depth Estimation: A Review 7th

Satellite-Based Water Depth Estimation: A Review

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7th international conference on Geoinformatics in Sustainable Ecosystem and Society, GSES 2019, and 1st international conference on Geospatial Artificial Intelligence for Urban Computing, GeoAI 2019

作者： Wen, Kaixiang Li, Yong Wang, Hua Jing, Wenlong Yang, Ji Zhang, Chen Wang, Zhou Guangdong University of Technology Guangzhou510070 China Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and Application Guangzhou Institute of Geography Guangzhou510070 China State Grid Panzhihua Power Supply Company Panzhihua617000 China

ISBN: (纸本)9789811561054

this paper reviews the advances in water depth estimations from satellite images. According to the sensor type, current satellite-based water depth estimations are divided into two categories: optical-based and SAR-based (synthetic aperture radar) methods. By analyzing and discussing on the advantages and disadvantages of various methods. the following points can be summarized: First, the accuracy of optical remote sensing water depth detection method is higher than that of SAR-based models. Besides, optical-based method is simpler and less restricted than the SAR-based methods. Second, hyperspectral-based approach performed better than the multispectral optical remote sensing approaches. Since hyperspectral images provide richer spectral information than multispectral, which significantly matter in the water depth detection. third, remote sensing water depth detection method is the best way to obtain the underwater topographic features of the inaccessible waters. Finally, on the basis of summarizing the previous water depth estimation methods, the development prospects of shallow seawater deep inversion technology are discussed and analyzed. For example, the establishment of an inversion model by fusing multiple remote sensing data, and the use of artificial intelligence technology for water depth inversion. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Synthetic aperture radar

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Automated Classifier Development Process for Recognizing Book Pages from Video Frames 24th

Automated Classifier Development Process for Recognizing Boo...

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24th East-European conference on advances in Databases and Information Systems/24th international conference on theory and Practice of Digital Libraries/16th Workshop on Business Intelligence and Big Data (ADBIS/TPDL/EDA)

作者： Brzeski, Adam Cychnerski, Jan Draszawka, Karol Dziubich, Krystyna Dziubich, Tomasz Korlub, Waldemar Rosciszewski, Pawel Gdansk Univ Technol Fac Elect Telecommun & Informat Dept Comp Architecture Comp Vis & Artificial Intelligence Lab Gdansk Poland

ISBN: (纸本)9783030558130;9783030558147

One of the latest developments made by publishing companies is introducing mixed and augmented reality to their printed media (e.g. to produce augmented books). An important computer vision problem that they are facing is classification of book pages from video frames. the problem is non-trivial, especially considering that typical training data is limited to only one digital original per book page, while the trained classifier should be suitable for real-time utilization on mobile devices, where camera can be exposed to highly diverse conditions and computing resources are limited. In this paper we address this problem by proposing an automated classifier development process that allows training classification models that run real-time, with high usability, on low-end mobile devices and achieve average accuracy of 88.95% on our in-house developed test set consisting of over 20 000 frames from real videos of 5 books for children. At the same time, deployment tests reveal that the classifier development process time is reduced approximately 16-fold.

关键词： Book page classification Machine learning Business information management Convolutional neural networks computer vision

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Volkswagen Vehicle Identification via Multilayer Perceptron Trained by Improved Artificial Bee Colony Algorithm 7th

Volkswagen Vehicle Identification via Multilayer Perceptron ...

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7th international conference on Frontiers of Intelligent Computing: theory and Applications, FICTA 2018

作者： Yang, Jingyuan Wang, Lei Jiang, Qiaoyong The Faculty of Computer Science and Engineering Xi’an University of Technology Xi’an710048 China

ISBN: (纸本)9789811399190

Automatic identification of the brand of the car is difficult to accomplish because the different brands have a lot of similarities. In this work, we developed a new system of Volkswagen vehicle identification. Firstly, the original car images were preprocessed by the watershed algorithm and manual revision. Secondly, we employed the wavelet entropy (WE) to extract efficient features from the car images. thirdly, we used multilayer perceptron (MLP) as a classifier. At last, we chose the artificial bee colony (ABC) algorithm to train the MLP. the original ABC is good at exploration but poor at exploitation because of its equation system. So, we proposed a new model of the ABC called improved artificial bee colony (IABC) to balance exploration and exploitation. We used the 5 × 5-fold cross-validation for fair comparison. the experiment result showed that the overall specificity is 88.62%, the overall sensitivity is 89.16%, and the overall accuracy is 89.17%. therefore, the proposed method is effective for Volkswagen vehicle identification. the result of the IABC provides better performance than ordinary ABC. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Vehicles

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the Impact of Data Imputation and Feature Extraction on PM2.5 Forecasting Performance in Bangkok Using Long Short-Term Memory Neural Networks 20

The Impact of Data Imputation and Feature Extraction on PM2....

引用

11th international conference on advances in Information technology, IAIT 2020

作者： Rong-O, Panupong Wiwatwatana, Nuwee Master of Science in Information Technology Srinakharinwirot University Bangkok Thailand Department of Computer Science Srinakharinwirot University Bangkok Thailand

ISBN: (纸本)9781450377591

the last few years have seen a dramatic increase in PM2.5 air pollution in thailand's major cities. Various works have tried to develop efficient Long Short-Term Memory (LSTM) deep neural network models for PM2.5 concentration forecasting. However, little has been studied about the impact of data imputation and feature extraction on the model performance in this context. In this paper, we imputed missing values using Kalman Smoothing and Linearly Weighted Moving Average. We utilized the LSTM Autoencoder (LSTM AE) for feature extraction. Using the Chokchai Police station in Bangkok as a case study to predict PM2.5 in the next 24 hours, we demonstrated that the performance gain from training LSTM models with imputed data is more than 7 percent overall with respect to the root mean square error (RMSE) and more than 10 percent overall with respect to the mean absolute error (MAE). Improvement with LSTM AE varies according to time steps. Forecasting 22 to 24 hours ahead tends to favor the use of LSTM AE. © 2020 ACM.

关键词： Long short-term memory

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A Smart Green House Control and Management System Using IoT 17th

A Smart Green House Control and Management System Using IoT

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17th international conference on Information technology: New Generations, ITNG 2020

作者： Chamra, Abdallah Harmanani, Haidar Department of Computer Science and Mathematics Lebanese American University Byblos Lebanon

ISBN: (纸本)9783030430191

the Internet of things (IoT) is a new and innovative disruptive technology that has emerged over the past few years. IoT is transforming economies by connecting physical objects from smartphones and PCs to cars, vending machines and jet engines. this paper presents an IoT approach for managing greenhouses in smart cities. the proposed approach uses sensor nodes, data management, and machine learning in order to successfully control greenhouses. the system has been designed and a prototype was built using Raspberry Pi and Arduino sensors. Promising results are reported. © Springer Nature Switzerland AG 2020.

关键词： Internet of things

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A Comparative Study of Statistical and Neural Network Models for PLC Network Traffic Anomaly Detection 14th

A Comparative Study of Statistical and Neural Network Models...

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14th international conference on Dependability of computer Systems, DepCoS-RELCOMEX 2019

作者： Andrysiak, Tomasz Saganowski, Lukasz Institute of Telecommunications and Computer Science Faculty of Telecommunication Information Technology and Electrical Engineering UTP University of Science and Technology Kaliskiego 7 Bydgoszcz85-789 Poland

ISBN: (纸本)9783030195007

Protection of systems and computer networks against novel, unknown attacks is currently an intensively examined and developed domain. One of possible solutions to the problem is detection and classification of abnormal behaviors reflected in the analyzed network traffic. In the presented article we attempt to resolve the problem by anomaly detection in the analyzed network traffic described with the use of three different models. We tested two class of models which differed in prediction. the first sorts was composed of ARFIMA and Holt-Winters models which are characterized by statistical dependences. the second sorts, on the other hand, included neural network auto-regression model which are characterized by single hidden layer and lagged inputs for forecasting univariate time series. In order to detect anomalies in the network traffic we used differences between real network traffic and its estimated model. the experiment results confirmed efficiency and effectiveness of the presented method. © 2020, Springer Nature Switzerland AG.

关键词： Anomaly detection

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An Efficient Privacy-Preserving Search Technique for Encrypted Cloud Data 7th

An Efficient Privacy-Preserving Search Technique for Encrypt...

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7th international conference on Frontiers of Intelligent Computing: theory and Applications, FICTA 2018

作者： Veningston, K. Venkateswara Rao, P.V. Department of Computer Science and Engineering Madanapalle Institute of Technology & Science MadanapalleAP India

ISBN: (纸本)9789813291850

In the present scenario of data management and computing, private data has been widely outsourced into cloud storage for its ability to provide low-cost access and maintenance services offered by public clouds such as Windows Azure, Google cloud platform, Amazon S3, IBM Bluemix, and so on for flexibility and economic benefits as well. therefore, sensitive data such as Email, medical records, and other critical data assets must be kept in an encrypted form in order to preserve privacy and integrity of data. the major challenge in keeping encrypted data in cloud is that the searching process would be more complex. the data owner normally does not want the cloud provider to understand and analyze what has been done by the data owner and data user on the encrypted data in cloud storage. However, data owner and data user want to perform some computations on encrypted data such as sorting of records, splitting, searching, and ranking. this paper proposes a technique to perform search over encrypted data. When comes to performing, searching, and ranking on encrypted data, an algorithm which is mathematically strong is essential and it must be performed by the cloud provider without privacy leak. As a huge number of data users and data owners are maintaining large collection of documents in the cloud, it is essential to support multiple keyword searches in encrypted cloud data in order to present relevant documents with maximum accuracy and privacy preservation. the proposed technique for searching over encrypted data domain allows data users to search and rank according to the input query with less complexity in computation. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Cloud storage

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Open science Graphs Must Interoperate! 24th

Open Science Graphs Must Interoperate!

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作者： Aryani, Amir Fenner, Martin Manghi, Paolo Mannocci, Andrea Stocker, Markus Swinburne Univ Technol Hawthorn Vic Australia DataCite eV Hannover Germany CNR Inst Informat Sci & Technol Pisa Italy TIB Leibniz Informat Ctr Sci & Technol Hannover Germany MARUM Ctr Marine Environm Sci PANGAEA Data Publisher Earth & Environm Sci Bremen Germany

ISBN: (纸本)9783030558130;9783030558147

Open science Graphs (OSGs) are Scientific Knowledge Graphs whose intent is to improve the overall FAIRness of science, by enabling open access to graph representations of metadata about people, artefacts, institutions involved in the research lifecycle, as well as the relationships between these entities, in order to support stakeholder needs, such as discovery, reuse, reproducibility, statistics, trends, monitoring, impact, validation, and assessment. the represented information may span across entities such as research artefacts (e.g. publications, data, software, samples, instruments) and items of their content (e.g. statistical hypothesis tests reported in publications), research organisations, researchers, services, projects, and funders. OSGs include relationships between such entities and sometimes formalised (semantic) concepts characterising them, such as machine-readable concept descriptions for advanced discoverability, interoperability, and reuse. OSGs are generally valuable individually, but would greatly benefit from information exchange across their collections, thereby improving their efficacy to serve stakeholder needs. they could, therefore, reuse and exploit the data aggregation and added value that characterise each OSG, decentralising the effort and capitalising on synergies, as no one-size-fits-all solution exists. the RDA IG on Open science Graphs for FAIR Data is investigating the motivation and challenges underpinning the realisation of an Interoperability Framework for OSGs. this work describes the key motivations for i) the definition of a classification for OSGs to compare their features, identify commonalities and differences, and added value and for ii) the definition of an Interoperability Framework, specifically an information model and APIs that enable a seamless exchange of information across graphs.

关键词： Open science Research Knowledge graph Interoperability

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'Learning by Competing' Experience from Smart India Hackathon 2019 2nd

'Learning by Competing' Experience from Smart India Hackatho...

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22nd international conference on Interactive Collaborative Learning (ICL) / 48th IGIP international conference on Engineering Pedagogy - Impact of the 4th Industrial Revolution on Engineering Education

作者： Halkude, Shashikant Annarao Awasekar, Dipali Dilip Walchand Inst Technol Solapur Maharashtra India

ISBN: (纸本)9783030402747;9783030402730

In this paper, we describe the experience at Smart India Hackathon 2019, a nationwide initiative to provide students a platform to solve some of pressing problems we face in our daily lives, and thus inculcate a culture of product innovation and a mindset of problem solving. the Team 'AndroDigi' was shortlisted for Grand Finale of Smart India Hackathon 2019 which was held on 2nd and 3rd March 2019. the team built a solution for Problem Statement "App based valuation and report generation" under Aich Appraisers Auctioneers Organization. Nodal Centre for this team was Chandigarh Groups of Colleges, Landran Mohali. In this study, we analyzed student's perceptions and experience in a hackathon where they were to design a concept for an application for automation for asset valuation report generation. A team of 6 students (3 girls & 3 boys) was selected form 380 teams all over India. By collecting data through questionnaires and interviewing the participants, we applied descriptive statistics rather than exploring into inferential statistics to analyze the data due to the limited number of students. In the end, the results show that the use of hackathon helped in achieving the learning goals and inculcating problem solving mindset. the students expressed their satisfaction in the fact that it provided them with motivation to learn through practice. Also, students agreed that the event helped them to think collaboratively for refined ideas. the overwhelming satisfaction expressed by the students goes to confirm that hackathon brings out the best creative skills from people through problem-solving.

关键词： Smart India Hackathon computer science and Engineering Programming Competitive learning Open Innovation Model

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