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A Multiple-Replica Provable data Possession Algorithm Based on Branch Authentication Tree

A Multiple-Replica Provable Data Possession Algorithm Based ...

引用

IEEE international conference on Software engineering and Service Sciences (ICSESS)

作者： Sichen Dong Jian Jiao Shuyu Li School of Computer Science Shaanxi Normal University Xi'an China

the following topics are dealt with: learning (artificial intelligence); neural nets; feature extraction; pattern classification; convolutional neural nets; computer network security; security of data; recurrent neura... 详细信息

ISBN: (数字)9781728165790

ISBN: (纸本)9781728165806

关键词： Heuristic algorithms data integrity conferences Software algorithms Authentication Security Software engineering

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Orchids Classification Using Spatial Transformer Network with Adaptive Scaling 1

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20th international conference on intelligent data engineering and automated learning (IDEAL)

作者： Sarachai, Watcharin Bootkrajang, Jakramate Chaijaruwanich, Jeerayut Somhom, Samerkae Chiang Mai Univ Dept Comp Sci Chiang Mai Thailand

ISBN: (数字)9783030336073

ISBN: (纸本)9783030336073;9783030336066

the orchids families are large, diverse flowering plants in the tropical areas. It is a challenging task to classify orchid species from images. In this paper, we proposed an adaptive classification model of the orchid images by using a Deep Convolutional Neural Network (D-CNN). the first part of the model improved the quality of input feature maps using an adaptive Spatial Transformer Network (STN) module by performing a spatial transformation to warp an input image which was split into different locations and scales. We applied D-CNN to extract the image features from the previous step and warp into four branches. then, we concatenated the feature channels and reduced the dimension by an estimation block. Finally, the feature maps would be forwarded to the prediction network layers to predict the orchid species. We verified the efficiency of the proposed method by conducting experiments on our data set of 52 classes of orchid flowers, containing 3,559 samples. Our results achieved an average of 93.32% classification accuracy, which is higher than the existing D-CNN models.

关键词： Orchids images Classification Deep learning

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threat Identification in Humanitarian Demining Using Machine learning and Spectroscopic Metal Detection 20th

Threat Identification in Humanitarian Demining Using Machine...

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20th international conference on intelligent data engineering and automated learning (IDEAL)

作者： van Verre, Wouter Ozdeger, Toykan Gupta, Ananya Podd, Frank J. W. Peyton, Anthony J. Univ Manchester Oxford Rd Manchester M13 9PL Lancs England

ISBN: (纸本)9783030336073;9783030336066

the detection of buried minimum-metal anti-personnel landmines is a time-consuming problem, due to the high false alarm rate (FAR) arising from metallic clutter typically found in minefields. Magnetic induction spectroscopy (MIS) offers a potential way to reduce the FAR by classifying the metallic objects into threat and non-threat categories, based on their spectroscopic signatures. A new algorithm for threat identification for MIS sensors, based on a fully-connected artificial neural network (ANN), is proposed in this paper, and compared against a classifier based on Support Vector Machines (SVM). the results demonstrate that MIS is a potentially viable option for the reduction of false alarms in humanitarian demining. It is also shown that the ANN outperforms the SVM-based approach for threat objects containing minimal amounts of metal.

关键词： Magnetic induction spectroscopy Machine learning Landmine detection

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Multimodal Web Based Video Annotator with Real-Time Human Pose Estimation 20th

Multimodal Web Based Video Annotator with Real-Time Human Po...

引用

20th international conference on intelligent data engineering and automated learning (IDEAL)

作者： Rodrigues, Rui Madeira, Rui Neves Correia, Nuno Fernandes, Carla Ribeiro, Sara Polytech Inst ESTSetubal Sustain RD Ctr Setubal Portugal NOVA Univ Lisboa FCT DI NOVA LINCS Lisbon Portugal NOVA Univ Lisboa FCSH ICNOVA Lisbon Portugal

ISBN: (纸本)9783030336172;9783030336165

this paper presents a multi-platform Web-based video annotator to support multimodal annotation that can be applied to several working areas, such as dance rehearsals, among others. the CultureMoves' "Motion-Notes" Annotator was designed to assist the creative and exploratory processes of both professional and amateur users, working with a digital device for personal annotations. this prototype is being developed for any device capable of running in a modern Web browser. It is a real-time multimodal video annotator based on keyboard, touch and voice inputs. Five different ways of adding annotations have been already implemented: voice, draw, text, web URL, and mark annotations. Pose estimation functionality uses machine learning techniques to identify a person skeleton in the video frames, which gives the user another resource to identify possible annotations.

关键词： Multimodal video annotations Real-time human pose estimation Machine learning for creativity

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Dual learning in the Bachelor's Degree in Automotive engineering at the Faculty of engineering of Vitoria-Gasteiz: Quality Requirements 13th

Dual Learning in the Bachelor's Degree in Automotive Enginee...

引用

Int Joint Conf of the 13th Int Conf on Soft Comp Models in Ind and Environm Applicat (SOCO) / 11th Int Conf on Computat Intelligence in Secur for Informat Syst (CISIS) / 9th Int Conf on European Transnat Educ (ICEUTE)

作者： Mesanza-Moraza, Amaia Tazo-Herran, Inmaculada Antonio Ramos-Hernanz, Jose Delgado, Ruperta Sancho-Saiz, Javier Manuel Lopez-Guede, Jose Apinaniz, Estibaliz Basque Country Univ UPV EHU Fac Engn Vitoria Gasteiz C Nieves Cano 12 Vitoria 01006 Spain

ISBN: (纸本)9783319941202;9783319941196

Since 2017-2018 academic year, the Bachelor's Degree in Auto-motive engineering has been implemented at the Faculty of engineering of Vitoria-Gasteiz (Basque Country University, UPV/EHU) in dual format, based on the complementarity of the University and company learning environments. With this type of education the aim is to achieve greater motivation of the students and facilitate the work insertion by having greater contact with companies. In this way, companies are fully integrated with the agents who are responsible for the education of university students. the teaching institutions need to accredit Bachelor's degrees or itineraries that are taught using this training format (dual training). In order to get this purpose, the university institutions adapt their studies in dual format to the quality requirements proposed by the state quality agencies of the university systems, based on objective evaluation criteria.

关键词： Quality Internship Company Dual learning Accreditation

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Industrial intelligent Optimization System Based on Industrial Internet Platform

Industrial Intelligent Optimization System Based on Industri...

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IEEE international conference on Software engineering and Service Sciences (ICSESS)

作者： Qingchun Wang Ge Ma Sijia He Qiyang Huang Weixi Gu China Academy of Industrial Internet China

ISBN: (数字)9781728165790

ISBN: (纸本)9781728165806

the concept of “Industrial Internet” was first proposed by General Electric in 2012. As a new infrastructure of the fourth industrial revolution, Industrial Internet has become a significant technique to realize digital transformation of industrial economy. the Industrial Internet platform is a service system based on massive data collection, aggregation and analysis, which is oriented to the needs of digitalization, networking and intellectualization of manufacturing industry. In order to solve the problems of current backward industrial data, improve the ability of data acquisition and deal with the industrial interconnection platform, the industrial intelligent optimization system generates the product services required by industrial enterprises and realizes the goal of industrial optimization.

关键词： Manufacturing industries data collection Tools Internet Manufacturing Optimization Software engineering

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Deep RL-based Trajectory Planning for AoI Minimization in UAV-assisted IoT 11

Deep RL-based Trajectory Planning for AoI Minimization in UA...

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11th IEEE international conference on Wireless Communications and Signal Processing (WCSP)

作者： Zhou, Conghao He, Hongli Yang, Peng Lyu, Feng Wu, Wen Cheng, Nan Shen, Xuemin (Sherman) Univ Waterloo Dept Elect & Comp Engn Waterloo ON Canada Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou Peoples R China Xidian Univ Sch Telecommun Xian Peoples R China

ISBN: (纸本)9781728135557

Due to the flexibility and low deployment cost, unmanned aerial vehicles (UAVs) have been widely used to assist cellular networks in providing extended coverage for Internet of things (IoT) networks. Existing throughput or delay-based UAV trajectory planning methods cannot meet the requirement of collecting fresh information from IoT devices. In this paper, by taking age-of-information (AoI) as a measure of information freshness, we investigate AoI-based UAV trajectory planning for fresh data collection. To model the complicated association and interaction pattern between UAV and IoT devices, the UAV trajectory planning problem is formulated as a Markov decision process (MDP) to capture the dynamics of UAV locations. As network topology and traffic generation pattern are unknown ahead, we propose an AoI-based trajectory planning (A-TP) algorithm using deep reinforcement learning (RL) technique. To accelerate the learning process during online decision making, the off-line pre-training of deep neural networks is performed. Extensive simulation results demonstrate that the proposed algorithm can significantly reduce the AoI of collected IoT data, as compared to other benchmark approaches.

关键词： Internet of things age-of-information unmanned aerial vehicle trajectory planning deep reinforcement learning

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Modeling data Driven Interactions on Property Graph 1

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20th international conference on intelligent data engineering and automated learning (IDEAL)

作者： Pongpech, Worapol Alex NIDA Business Analyt & Data Sci Grad Program Fac Appl Stat Bangkok 10240 Thailand

ISBN: (数字)9783030336073

ISBN: (纸本)9783030336073;9783030336066

data Driven Transformation is a process where an organization transforms its infrastructure, strategies, operational methods, technologies, or organizational culture to facilitate and encourage data driven decision-making behaviors. We defined a data driven network as group/groups of people in an organization network working on common projects where making data driven decisions is necessary in the project. One important problem in data driven transformation is how to understand data driven behaviors in the network. Ability to model and compute on a DDIG is crucial for understanding data driven network behaviors. To this end, we modeled a data driven network as a property graph, in which nodes represent users, projects, or data sources and edges represent interactions between them. We termed this data Driven Interactions Graph and modeled on the Neo4j graph platform. A graph model framework to represent data driven interactions such that a number of network properties can be computed from the proposed graph is introduced. Finally, we discussed data utilization and data collaboration behaviors of the social working network.

关键词： data Driven Transformation Collaboration Utilization Property graph Social network analysis Clustering Communities Neo4j

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A methodology on interpretable novelty detection 11

A methodology on interpretable novelty detection

引用

11th international conference on Structural Dynamics, EURODYN 2020

作者： Movsessian, A. Garcia Cava, D. Tcherniak, D. Janeliukstis, R. School of Engineering Institute for Infrastructure and Environment University of Edinburgh Alexander Graham Bell Building Thomas Bayes Road EdinburghEH9 3FG United Kingdom Bruel & Kjær Sound and Vibration Measurements Skodsborgvej 307 Nærum2085 Denmark Department of Wind Energy Technical University of Denmark Frederiksborgvej 399 Roskilde4000 Denmark

ISBN: (纸本)9786188507203

Vibration-based Structural Health Monitoring (VSHM) systems continuously gather data from an array of sensors mounted on a structure. Features are constructed from the data measured. the aim is to monitor the vibration responses in the search for changes that may hint to damage. the continuous data acquisition generates high-dimensional feature spaces that require data-Driven approaches to make inferences concerning the integrity of the structure. In recent years, machine learning has played an increasingly important role in VSHM. data-driven algorithms have been successfully used to construct models capable of detecting anomalies such as damage in the features derived from the vibration signals. Mahalanobis Distance based novelty detection is a common used method to detect damage. Yet, the resulting models have been labelled "black box models" given that they lack interpretability. this becomes a relevant challenge in the presence of high-dimensional feature spaces. Using machine learning algorithms that can be interpreted would enable a more reliable novelty detection process, building trust in these methods and easing the decision-making process. Decision Trees (DT) is a widely used interpretable machine learning algorithm. the hierarchical structure of this algorithm enables the prioritisation of features that are used as predictors in the damage detection models. Furthermore, the nature of the algorithm enables the user to track the decisions and understand the classification process in detail. In this paper, we introduce the complementary use of so-called "black box models" and DT for novelty detection. the proposed damage detection approach is tested on an experimental setup with a 14.3m wind turbine blade (WTB) equipped with 24 accelerometers. A pseudo-damage was simulated by adding masses to several locations of the WTB. the pseudo-damage was detected by means of a semisupervised novelty-detection. the novelties were later studied in detail with decision-tr

关键词： Decision trees

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Generating education in-game data: the case of an ancient theatre serious game 11

Generating education in-game data: The case of an ancient th...

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11th international conference on Computer Supported Education, CSEDU 2019

作者： Vidakis, Nikolas Barianos, Anastasios Kristofer Trampas, Apostolos Marios Papadakis, Stamatios Kalogiannakis, Michail Vassilakis, Kostas Department of Informatics Engineering Technological Educational Institute of Crete Heraklion Crete Greece Department of Preschool Education Faculty of Education University of Crete Greece Department of Electronic Engineering Technological Educational Institute of Crete Heraklion Crete Greece

ISBN: (纸本)9789897583674

learning Analytics have become an indispensable element of education, as digital mediums are increasingly used within formal and informal education. Integrating specifications for learning analytics in non-traditional educational mediums, such as serious games, has not yet reached the level of development necessary to fulfil their potential. though much research has been conducted on the issue of managing and extracting value from learning analytics, the importance of specifications, methods and decisions for the initial creation of such data has been somewhat overlooked. To this end, we have developed a custom library that implements the Experience API specification within the Unity 3D game engine. In this paper, we present this library, as well as a representative scenario illustrating the procedure of generating and recording data. through this work we aim to expand the reach of learning analytics into serious games, facilitate the generation of such data in commercially popular development tools and identify significant events, with educational value, to be recorded. Copyright © 2019 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.

关键词： Serious games

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