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检索条件"任意字段=8th IEEE International Enterprise Distributed Object Computing Conference"

共 1278 条记录，以下是271-280 订阅

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A Week of Playing with Code, the object-Oriented Way 8th

A Week of Playing with Code, the Object-Oriented Way

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8th international conference in Methodologies and Intelligent Systems for Technology Enhanced Learning (MIS4TEL)

作者： Tomaiuolo, Michele Angiani, Giulio Ferrari, Alberto Mordonini, Monica Poggi, Agostino Univ Parma Dept Engn & Architecture Parma Italy

ISBN: (纸本)9783319988726;9783319988719

this work presents the results of some summer stages for high school students, for the first introduction to computational thinking and programming. Differently from other approaches, our experiences are characterized by: (i) a full week of lessons and exercises, for gradually developing a small but complete and original project, (ii) an objects-early methodology, (iii) the choice of a dynamic videogame as the main programming project, and (iv) the availability of few small and focused examples, as source files, for students to start building their own application. At the end, the students' anonymous opinions about the stage, and their own projects, were collected and analyzed, for improving future similar activities.

关键词： Computer games Computational thinking Computer science education Computer programming Python

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Staticslam: A dynamic object-free accurate SLAM system 8

Staticslam: A dynamic object-free accurate SLAM system

引用

8th international conference on computing and Pattern Recognition, ICCPR 2019

作者： Du, Haibin Wang, Jianming Sun, Yukuan School of Computer Science and Technology Tiangong University Tianjin China Center for Engineering Internship and Training Tiangong University Tianjin China

ISBN: (纸本)9781450376570

Localization and mapping in the real scene where movable objects exist is a challenging task, however, most SLAM approaches generally assume that the scene is static. this assumption leads to building a map with movable objects, causing the localization to fail. We propose MODS, a movable object discrimination strategy which generates a knowledge base containing different attributes of an object, classify the object according to various attributes in the knowledge base, and take different measures for different categories. By using MODS, lidar data can be used in a selective manner to avoid data redundancy and reduce the probability of localization failure. We implement a complete SLAM system based on MODS, verify the influence of movable objects on SLAM with KITTI dataset, and also estimate our SLAM system. the qualitative experimental results show that our SLAM system can effectively eliminate the influence of movable objects on mapping and localization. Moreover, the quantitative experiment results show that the time required for localization was reduced by 16.0% on average compared with the state-of-the-art, while the loop-closure can still be correctly detected. © 2019 Association for computing Machinery.

关键词： Mapping

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A Big Data Platform for Industrial enterprise Asset Value Enablers 15th

A Big Data Platform for Industrial Enterprise Asset Value En...

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15th international conference on distributed computing and Artificial Intelligence (DCAI)

作者： Canito, Alda Fernandes, Marta Conceicao, Luis Praca, Isabel Marreiros, Goreti Polytech Porto GECAD Res Grp Intelligent Engn & Comp Adv Innovat Porto Portugal

ISBN: (纸本)9783319946498;9783319946481

the growing ubiquity of IoT, along with bigger steps towards full digitalization in the manufacturing industry, makes it easier to constantly monitor equipment activity and implement predictive maintenance approaches. Big Data solutions are best suited to process the large amounts of data generated through monitorization - additionally, they also allow for processing of unstructured data, such as documents used in not fully-digitalized processes. this paper describes the creation of a small Hadoop cluster, without high-availability, its integration in the InValue architecture and the processes through which it was populated with historical data from a relational warehouse. the degree of parallelization on the data ingestion tasks and its effect on performance were evaluated for the different kinds of datasets that are currently being used for batch data processing.

关键词： Predictive maintenance Big data architecture Hadoop ecosystem Data ingestion Data processing

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A Probabilistic enterprise Architecture Model Evolution 22

A Probabilistic Enterprise Architecture Model Evolution

引用

22nd ieee international enterprise distributed object computing conference (ieee EDOC)

作者： Hacks, Simon Lichter, Horst Rhein Westfal TH Aachen Res Grp Software Construct Aachen Germany

ISBN: (纸本)9781538641392

enterprise Architecture (EA) is a widely accepted means to ease the alignment of IS projects with enterprise-wide objectives. One central artifact of EA are EA models, which provide a holistic view on the organization and support EA's stakeholder to create added value. As EA collects its data from different sources, the data can be contradictory. this work contributes to existing research by proposing a novel approach to deal with contradictory data without solving the thereby caused conflicts. In order to achieve this objective, we refine the Predictive, Probabilistic Architecture Modeling Framework (P2AMF) introduced by Johnson et al., which already incorporates a way to represent uncertainty regarding the existence of modelled entities. To make our technique usable, we generalize P2AMF from its UML/OCL notation to a graph presentation in order to apply it to EA models notated in arbitrary notations like ArchiMate. Furthermore, we add alternative scenarios in different versions along a time series to meet the requirements of a distributed EA evolution. To show the applicability of our approach, we developed a proof of concept prototype by implementing the proposed calculations and guidelines on a Neo4j graph database. Last, we argue that our approach meets the stated requirements of a distributed EA evolution.

关键词： enterprise Architecture Management Probabilistic Modelling Quality Management

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Fire Detection Using DCNN for Assisting Visually Impaired People in IoT Service Environment 15th

Fire Detection Using DCNN for Assisting Visually Impaired Pe...

引用

15th international conference on distributed computing and Artificial Intelligence (DCAI)

作者： Kong, Borasy Lim, Kuoysuong Kwon, Jangwoo Inha Univ Dept Comp Engn Incheon 22201 South Korea

ISBN: (纸本)9783319946498;9783319946481

In an emergency, such as fire in a building, visually impaired people are prone to danger more than non-impaired people, for they cannot be aware of it quickly. Current fire detection methods such as smoke detector is very slow and unreliable. But by using vision sensor instead, fire can be proven to be detected much faster as shown in our experiments. Previous studies have applied various image processing and machine learning techniques to detect fire, but they usually don't generalize well because those techniques use hand-crafted features. With the recent advancements in the field of deep learning, this research can be conducted to help solve the problem by using deep learning-based object detector to detect fire. Such approach can learn features automatically, so they can usually generalize well to various scenes. We introduced two object detection models (R1 and R2) with slightly different model's complexity. R1 can detect fire at 90% average precision and 85% recall at 33 FPS, while R2 has 90% average precision and 61% recall at 50 FPS. the reason why we introduced two models is because we want to have a benchmark comparison as no other research on fire detection with similar techniques exists. We also want to give two model choices when we wish to integrate the model into an IoT platform.

关键词： object detection Deep convolutional neural network Tensorflow Darkflow

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A Systematic Literature Review of the Mobile Application for object Recognition for Visually Impaired People

A Systematic Literature Review of the Mobile Application for...

引用

international conference on Information Technology and Multimedia (ICIM)

作者： Zulfadhlina Amira Nor Hisham Masyura Ahmad Faudzi Azimah Abdul Ghapar Fiza Abdul Rahim College of Computing and Informatics Universiti Tenaga Nasional Malaysia Institute of Informatics and Computing in Energy Universiti Tenaga Nasional Malaysia

ISBN: (数字)9781728173108

ISBN: (纸本)9781728173115

Nowadays, mobile applications or also known as mobile apps are one of the most important sources of communication and gives a lot of benefits to a person. Mobile technology advancements have brought an excessive change in people's daily lifestyles which has led to high demand for developing software that can give benefit to a person that runs on a mobile device. Mobile apps are represented visually on a smartphone, which it is not user-friendly for visually impaired people. the number of visually impaired people are growing in each of the countries in the world. Most technologies are being developed to help people with visual impairment because they still have difficulties in using assistive technologies. this systematic literature review attempts to provide findings on the project for visually impaired people to recognize objects using their smartphones. Systematic Literature Review (SLR) method was used to collect and review the current state of analysis concerning object recognition for visually impaired people on mobile platforms. Overall, this research covered articles published in three databases which are ScienceDirect, ieee Xplore and Google Scholar and the articles selected are between 2013 until 2019. this paper is based on the Kitchenham methodology where the keyword search and exclusion criteria to select the articles about the topic were used. After reading the total of 371 titles of articles based on keywords, 323 abstracts were examined thoroughly. then, 21 full-text articles were chosen for the final review. the findings show the techniques, tools used and methods on how the system was implemented to recognize object.

关键词： Visualization Systematics Bibliographies Tools Mobile applications object recognition Testing

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A comparative study of security features provided by different cloud services to enterprises 8

A comparative study of security features provided by differe...

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8th ieee international conference on Cloud computing, Data Science and Engineering (Confluence) / Global Technology, Innovation and Enterpreneurship Summit

作者： Sirohi, Vansh Jain, Tanya Arora, Rachita Munjal, Puja Jagannath Int Management Sch Dept Informat Technol New Delhi 110070 India

ISBN: (纸本)9781538617199

Cloud computing is a rapidly growing technology which offers enterprises to outsource their data and software to the cloud server while enabling them to respond to the changes occurring in technology and operational environment. Organizations are expected to pay as per their use while utilizing the service offered by cloud service providers (CSP). But the main concern while outsourcing their data to the CSP is security which needs to be addressed since their data will be processed by the third party cloud. this paper presents comparison of the services provided by three renowned CSP. Also this research study facilitates an enterprise to choose the best CSP based on the most important security parameter.

关键词： cloud computing security enterprise cloud service providers (CSP)

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Intent-based object Grasping by a Robot using Deep Learning 8

Intent-based Object Grasping by a Robot using Deep Learning

引用

ieee 8th international Advance computing conference (IACC)

作者： Zunjani, Faheem Hassan Sen, Souvik Shekhar, Himanshu Powale, Aditya Godnaik, Debadutta Nandi, G. C. Indian Inst Informat Technol Robot & Machine Learning Lab Allahabad Uttar Pradesh India

ISBN: (纸本)9781538666784

A robot needs to predict an ideal rectangle for optimal object grasping based on the intent for that grasp. Mask Regional - Convolutional Neural Network (Detectron) can be used to generate the object mask and for object detection and a Convolutional Neural Network (CNN) can be used for ideal grasp rectangle prediction according to the supplied intent, as described in this paper. the masked image obtained from Detectron along with the metadata of the intent type has been fed to the Fully-Connected layers of the CNN which would generate the desired optimal rectangle for the specific intent and object. Before settling for a CNN for optimal rectangle prediction, conventional Neural Networks with different hidden layers have been tried and the accuracy achieved was low. A CNN has then been developed and tested with different layers and sizes of pool and strides to settle on the final CNN model that has been discussed here. the optimal predicted rectangle is then fed to a robot, ROS simulation of Baxter robot in this case, to perform the actual grasping of the object at the predicted location.

关键词： robotics deep learning object grasping convolutional neural network

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Message from the TEAR 2018 Workshop Chairs 22

Message from the TEAR 2018 Workshop Chairs

引用

22nd ieee international enterprise distributed object computing conference Workshops, EDOCW 2018

作者： Franke, Ulrik Buschle, Markus Jung, Jürgen Sweden Zeb.consulting Sweden Frankfurt University of Applied Sciences Germany

this paper gives a brief overview of the 13th Workshop on Trends in enterprise Architecture Research (TEAR) organized in conjunction with EDOC 2018. the paper introduces the Workshop research topics and presents the a... 详细信息

ISBN: (纸本)9781538641415

关键词： enterprise Architecture enterprise Architecture Management

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Mobile Application: Mobile Assistance for Visually Impaired People - Speech Interface System (SIS)

Mobile Application: Mobile Assistance for Visually Impaired ...

引用

international conference on Information Technology and Multimedia (ICIM)

作者： Abdul Majid Norkhalid Masyura Ahmad Faudzi Azimah Abdul Ghapar Fiza Abdul Rahim College of Computing and Informatics Universiti Tenaga Nasional Malaysia Institute of Informatics and Computing in Energy Universiti Tenaga Nasional Malaysia

ISBN: (数字)9781728173108

ISBN: (纸本)9781728173115

the evolution of technology has been made to bring the most benefits to human-being on communication and to facilitate their day-to-day activities. Technologies contribution, such as mobile application, has been proved to have a high capability to cater to the needs of a person with disabilities. the usage of smartphone is limited for visually impaired(VI) community as most of the currently available mobile application are not user-friendly for people with vision disability. Although smartphones nowadays are offering accessibility services such as TalkBack for Android and VoiceOver for iOS, these accessibilities provide fewer functions on navigating the VI community. A speech interface system(SIS) in mobile application combined with object and distance detection could help the VI community to navigate to their destination only with the use of a smartphone. this Systematic Literature Review (SLR) provide our findings on the present study of speech recognition projects and the requirement issues of speech recognition in mobile application platform throughout supporting VI people. three journal databases (Google Scholar, ieee Explore and Science Direct) has been searching throughout this SLR with articles ranging from the year of 2013-2019. A result of 136 article titles, abstracts of 73 articles were examined, 35 full-text articles were selected for final review. A total of 19 articles are analyzed. the purpose of the SLR is to collect the technique, evaluation methods and the validation of the projects.

关键词： Systematics Navigation Databases Bibliographies Speech recognition Distance measurement Mobile applications

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