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1st IEEE International Conference on Industrial Cyber-Physical Systems, ICPS 2018

作者： Zenkert, Johannes Dornhofer, Mareike Weber, Christian Ngoukam, Charly Fathi, Madjid University of Siegen Institute of Knowledge Based Systems and Knowledge Management Department of Electrical Engineering and Computer Science Germany

ISBN: (纸本)9781538665312

A smart city is a modern and visionary approach for a city to provide intelligent and smart urban services by using information and communication technologies (ICT). The Internet of Things (IoT), emerging through intelligent networking and sensing technologies, is seen as the data-driven enabler for smart cities with current and future infrastructures. The Open Data Aarhus datasets have been created from sensor data in the city Aarhus in Denmark. This paper presents how big data technologies in the context of smart cities are used to implement a framework with a prototype R Shiny application to analyze road traffic and pollution data to make a step towards smart mobility. The main objective of the approach is the calculation and visualization of the least polluted route from a chosen start to an end point by applying an algorithm utilizing the MapReduce framework running on a Hadoop cluster. © 2018 IEEE.

关键词： MapReduce

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Bayesian heatmaps: Probabilistic classification with multiple unreliable information sources

arXiv

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arXiv 2019年

作者： Simpson, Edwin Reece, Steven Roberts, Stephen J. Ubiquitous Knowledge Processing Lab Department of Computer Science Technische Universität Darmstadt Department of Engineering Science University of Oxford

Unstructured data from diverse sources, such as social media and aerial imagery, can provide valuable up-to-date information for intelligent situation assessment. Mining these different information sources could bring major benefits to applications such as situation awareness in disaster zones and mapping the spread of diseases. Such applications depend on classifying the situation across a region of interest, which can be depicted as a spatial "heatmap". Annotating unstructured data using crowdsourcing or automated classifiers produces individual classifications at sparse locations that typically contain many errors. We propose a novel Bayesian approach that models the relevance, error rates and bias of each information source, enabling us to learn a spatial Gaussian Process classifier by aggregating data from multiple sources with varying reliability and relevance. Our method does not require gold-labelled data and can make predictions at any location in an area of interest given only sparse observations. We show empirically that our approach can handle noisy and biased data sources, and that simultaneously inferring reliability and transferring information between neighbouring reports leads to more accurate predictions. We demonstrate our method on two real-world problems from disaster response, showing how our approach reduces the amount of crowdsourced data required and can be used to generate valuable heatmap visualisations from SMS messages and satellite images. Copyright © 2019, The Authors. All rights reserved.

关键词： Crowdsourcing

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Face Recognition System Using Local Features Fusion for Multi-Masks

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Journal of Physics: Conference Series 2021年第1期2107卷

作者： Mustafa Zuhaer Nayef Al-Dabagh Muhammad Imran Ahmad Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Perlis Malaysia Department of Computer Science College of Science Knowledge University Kirkuk Road 44001 Erbil Iraq

Face recognition is a relatively novel research field, and its application is closely related to numerous other areas. Moreover, it is emerging as a critical research theme due to its broad range of applications. Thus, many face recognition methods use a variety of feature extraction approaches. Nonetheless, the issue continues to be challenging, particularly identifying non-biological entities. This paper proposes an extended descriptor for local features of an effectual facial recognition system using a local directional pattern operator. This technique combines the Frei-Chen and Robinson masks' strengths by fusion of the directional features of LDP for these two masks; this elicits a robust feature extraction method for distinguishing faces. Experimental results using the Yale database show that the extended descriptor considerably improved recognition rate and better performance than traditional local feature descriptors.

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SHREC'19 track: Extended 2D scene image-based 3D scene retrieval 12

SHREC'19 track: Extended 2D scene image-based 3D scene retri...

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12th Eurographics Workshop on 3D Object Retrieval, 3DOR 2019, in conjunction with the 40th Annual Conference of the European Association for computer Graphics, EG 2019

作者： Abdul-Rashid, Hameed Yuan, Juefei Li, Bo Lu, Yijuan Schreck, Tobias Bui, Ngoc-Minh Do, Trong-Le Holenderski, Mike Jarnikov, Dmitri Le, Khiem T. Menkovski, Vlado Nguyen, Khac-Tuan Nguyen, Thanh-An Nguyen, Vinh-Tiep Ninh, Tu V. Rey, Perez Tran, Minh-Triet Wang, Tianyang School of Computer Science and Computer Engineering University of Southern Mississippi United States Department of Computer Science Texas State University United States Institue of Computer Graphics and Knowledge Visualization Graz University of Technology Austria Faculty of Information Technology Vietnam National University Ho Chi Minh City Viet Nam Software Engineering Lab Vietnam National University Ho Chi Minh City Viet Nam Department of Mathematics and Computer Science Eindhoven University of Technology Netherlands University of Information Technology Vietnam National University Ho Chi Minh City Viet Nam Department of Computer Science and Information Technology Austin Peay State University United States

ISBN: (纸本)9783038680772

In the months following our SHREC 2018 - 2D Scene Image-Based 3D Scene Retrieval (SceneIBR2018) track, we have extended the number of the scene categories from the initial 10 classes in the SceneIBR2018 benchmark to 30 classes, resulting in a new benchmark SceneIBR2019 which has 30,000 scene images and 3,000 3D scene models. For that reason, we seek to further evaluate the performance of existing and new 2D scene image-based 3D scene retrieval algorithms using this extended and more comprehensive new benchmark. Three groups from the Netherlands, The United States and Vietnam participated and collectively submitted eight runs. This report documents the evaluation of each method based on seven performance metrics, offers an in-depth discussion as well as analysis on the methods employed and discusses future directions that have the potential to address this task. Again, deep learning techniques have demonstrated notable performance in terms of both accuracy and scalability when applied to this exigent retrieval task. To further enrich the current state of 3D scene understanding and retrieval, our evaluation toolkit, all participating methods' results and the comprehensive 2D/3D benchmark have all been made publicly available. © 2019 The Author(s)

关键词： Three dimensional computer graphics

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Applications of Game Theory in Vehicular Networks: A Survey

arXiv

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arXiv 2021年

作者： Sun, Zemin Liu, Yanheng Wang, Jian Li, Guofa Anil, Carie Li, Keqiang Guo, Xinyu Sun, Geng Tian, Daxin Cao, Dongpu College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China Institute of Human Factors and Ergonomics College of Mechatronics and Control Engineering Shenzhen University Guangdong Shenzhen518060 China School of Computer Science and Engineering VIT-AP Andhra Pradesh Amaravati522237 India College of Engineering Nanjing Agricultural University Nanjing210031 China State Key Laboratory of Automotive Safety and Energy Department of Automotive Engineering Tsinghua University Beijing100084 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University Beijing100191 China Waterloo Cognitive Autonomous Driving Lab University of Waterloo N2L 3G1 Canada

In the Internet of things (IoT) era, vehicles and other intelligent components in an intelligent transportation system (ITS) are connected, forming vehicular networks (VNs) that provide efficient and safe traffic and ubiquitous access to various applications. However, as the number of nodes in an ITS increases, it is challenging to satisfy a varied and large number of service requests with different quality of service (QoS) and security requirements in highly dynamic VNs. Intelligent nodes in VNs can compete or cooperate for limited network resources to achieve the objective for either an individual or a group. Game theory (GT), a theoretical framework designed for strategic interactions among rational decision makers sharing scarce resources, can be used to model and analyze individual or group behaviors of communicating entities in VNs. This paper primarily surveys the recent developments of GT in solving various challenges of VNs. This survey starts with an introduction to the background of VNs. A review of GT models studied in the VNs is then introduced, including the basic concepts, classifications, and applicable vehicular issues. After discussing the requirements of VNs and the motivation of using GT, a comprehensive literature review on GT applications in dealing with the challenges of current VNs is provided. Furthermore, recent contributions of GT to VNs that are integrated with diverse emerging 5G technologies are surveyed. Finally, the lessons learned are given, and several key research challenges and possible solutions of applying GT in VNs are outlined. Copyright © 2021, The Authors. All rights reserved.

关键词： Quality of service

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Competence assessment as an expert system for human resource management: A mathematical approach

arXiv

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arXiv 2020年

作者： Bohlouli, Mahdi Mittas, Nikolaos Kakarontzas, George Theodosiou, Theodosios Angelis, Lefteris Fathi, Madjid Institute of Knowledge Based Systems University of Siegen Hoelderlinstr. 3 Siegen57076 Germany Department of Informatics Aristotle University of Thessaloniki Thessaloniki54124 Greece Department of Computer Science and Engineering T.E.I. of Thessaly Larissa41110 Greece

Efficient human resource management needs accurate assessment and representation of available competences as well as effective mapping of required competences for specific jobs and positions. In this regard, appropriate definition and identification of competence gaps express differences between acquired and required competences. Using a detailed quantification scheme together with a mathematical approach is a way to support accurate competence analytics, which can be applied in a wide variety of sectors and fields. This article describes the combined use of software technologies and mathematical and statistical methods for assessing and analyzing competences in human resource information systems. Based on a standard competence model, which is called a Professional, Innovative and Social competence tree, the proposed framework offers flexible tools to experts in real enterprise environments, either for evaluation of employees towards an optimal job assignment and vocational training or for recruitment processes. The system has been tested with real human resource data sets in the frame of the European project called ComProFITS. Copyright © 2020, The Authors. All rights reserved.

关键词： Human resource management

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Warburg Effects in Cancer and Normal Proliferating Cells:Two Tales of the Same Name

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Genomics, Proteomics & Bioinformatics 2019年第3期17卷 273-286页

作者： Huiyan Sun Liang Chen Sha Cao Yanchun Liang Ying Xu The China-Japan Union Hospital Jilin UniversityChangchun 130033China MOE Key Laboratory of Symbolic Computation and Knowledge Engineering College of Computer Science and TechnologyJilin UniversityChangchun 130012China Computational Systems Biology Lab Department of Biochemistry and Molecular Biology and Institute of BioinformaticsUniversity of GeorgiaAthensGA 30602USA Faculty of Health Sciences University of MacaoTaipaMacao SAR 999078China Department of Biostatistics School of MedicineIndiana UniversityIndianapolisIN 46202USA Zhuhai Laboratory of MOE Key Laboratory of Symbolic Computation and Knowledge Engineering Zhuhai College of Jilin UniversityZhuhai 519041China

It has been observed that both cancer tissue cells and normal proliferating cells(NPCs)have the Warburg *** goal here is to demonstrate that they do this for different *** accomplish this,we have analyzed the transcriptomic data of over 7000 cancer and control tissues of 14 cancer types in TCGA and data of five NPC types in *** analyses reveal that NPCs accumulate large quantities of ATPs produced by the respiration process before starting the Warburg effect,to raise the intracellular pH from 6.8 to 7.2 and to prepare for cell division *** cell cycle starts,the cells start to rely on glycolysis for ATP generation followed by ATP hydrolysis and lactic acid release,to maintain the elevated intracellular pH as needed by cell division since together the three processes are pH *** cells go back to the normal respirationbased ATP production once the cell division phase *** comparison,cancer cells have reached their intracellular pH at 7.4 from top down as multiple acid-loading transporters are up-regulated and most acid-extruding ones except for lactic acid exporters are *** cells use continuous glycolysis for ATP production as way to acidify the intracellular space since the lactic acid secretion is decoupled from glycolysis-based ATP generation and is pH balanced by increased expressions of acid-loading ***-expression analyses suggest that lactic acid secretion is regulated by external,non-pH related ***,our data strongly suggest that the two cell types have the Warburg effect for very different reasons.

关键词： Cancer Warburg effect Fenton reaction Cell proliferation pH homeostasis

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Design of a Daily Brief Business Report Generator based on Web Scraping with KNN Algorithm

Design of a Daily Brief Business Report Generator based on W...

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作者： Gang Lin Yanchun Liang Xiaoyang Fu Guangshun Chen Shaocan Cai Zhuhai Laboratory of Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Department of Computer Science and TechnologySchool of Computer Science Department of Computer Science and Technology School of Computer ScienceZhuhai College of Jilin University

In order to generate a report for an enterprise where there is neither the API supporting from their existing website systems nor the granted database access rights approval,a daily business report generator system based on web scraping with k nearest neighbor(kNN)classification algorithm is proposed in this *** covers the web crawler technology that is to access existing website system and extract business *** k NN algorithm is applied to identify the verification code on the login page,and the brief daily report generating in a spreadsheet style *** with some OCR engine for image recognition,the system in Python can automatically generate the brief daily business reports by the kNN algorithm,which is better than some library with default training set on validating the verification code.

关键词： image Design of a Daily Brief Business Report Generator based on Web Scraping with KNN Algorithm Web KNN

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A new and more informative subtyping scheme for breast cancer based on co-expression of metabolic genes

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Genes & Diseases 2025年

作者： Chongren Pei Yuzhe Zhang Jun Xiao Qing He Wenyong Zhang Ying Xu Systems Biology Lab for Metabolic Reprogramming Department of Human Cell Biology and Genetics School of Medicine Southern University of Science and Technology Shenzhen Guangdong 518055 China The First Laboratory of Cancer Institute The First Hospital of China Medical University Shenyang Liaoning 110001 China Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University Changchun Jilin 130012 China The Third People's Hospital of Shenzhen Shenzhen Guangdong 518112 China School of Medicine Southern University of Science and Technology Shenzhen Guangdong 518055 China

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Sentilyzer: Aspect-oriented sentiment analysis of product reviews

Sentilyzer: Aspect-oriented sentiment analysis of product re...

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2018 International Conference on Computational science and Computational Intelligence, CSCI 2018

作者： Wladislav, Schulz Johannes, Zenkert Christian, Weber Andre, Klahold Madjid, Fathi Department of Electrical Engineering and Computer Science Institute of Knowledge Based Systems and Knowledge Management University of Siegen Siegen Germany

ISBN: (纸本)9781728113609

Aspect-oriented sentiment analysis is used in particular on textual product reviews to identify positive or negative product characteristics. This information is beneficial not only for customers related to purchasing decisions, but also used by manufacturers to improve their products. In this short paper, we introduce Sentilyzer, a system which performs state-of-the-art aspect-oriented sentiment analysis based on automatically generated category-specific sentiment and aspect dictionaries from Amazon product reviews. © 2018 IEEE.

关键词： Sentiment analysis

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