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29th International Symposium on Algorithms and Computation, ISAAC 2018

作者： Ficker, Annette M.C. Erlebach, Thomas Mihalák, Matúš Spieksma, Frits C.R. Faculty of Economics and Business KU Leuven Leuven Belgium Department of Informatics University of Leicester Leicester United Kingdom Department of Data Science and Knowledge Engineering Maastricht University Maastricht Netherlands Department of Mathematics and Computer Science Eindhoven University of Technology Eindhoven Netherlands

ISBN: (纸本)9783959770941

Consider a problem where 4k given vectors need to be partitioned into k clusters of four vectors each. A cluster of four vectors is called a quad, and the cost of a quad is the sum of the component-wise maxima of the four vectors in the quad. The problem is to partition the given 4k vectors into k quads with minimum total cost. We analyze a straightforward matching-based algorithm and prove that this algorithm is a23 -approximation algorithm for this problem. We further analyze the performance of this algorithm on a hierarchy of special cases of the problem and prove that, in one particular case, the algorithm is a54 -approximation algorithm. Our analysis is tight in all cases except one. © Annette M. C. Ficker, Thomas Erlebach, Matúš Mihalák, and Frits C. R. Spieksma;licensed under Creative Commons License CC-BY

关键词： Approximation algorithms

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Web-based Teamwork: Distributed Software Development Course under Covid-19

Web-based Teamwork: Distributed Software Development Course ...

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International Conference on computer science & Education (ICCSE)

作者： Rui ZHANG Pedro Mestre Carlos Serodio Marília Prada Wenjuan GAO College of Computer Science and Technology Jilin University Key Lab of Symbolic Computation and Knowledge Engineering Chinese Ministry of Education Changchun China Centro Algoritmi University of Minho Guimaraes Portugal CITAB University of Tras-os-Montes and Alto Douro Vila Real Portugal Department of Social and Organizational Psychology Instituto Universitário de Lisboa (ISCTE-IUL) Lisboa Portugal Library of Changchun University Changchun China

ISBN: (数字)9781728172675

ISBN: (纸本)9781728172682

In a increasingly globalized world, it is very important to help students to acquire the hard and soft skills needed to cope with the challenges they will face when working in such environments. However, even though students find this subject interesting and volunteer for it, it is hard, even impossible to teach college students such a distributed fashion of teamwork. In this paper, a case study is provided to illustrate the methodology and experiences of a joint course, distributed software development, of multiple universities from Asia, Europe, North and South Americas. The results show that student can get the spirit, effective communication for such web-based teamwork environment and achieve software project development. The recent developments because of the Covid-19 pandemic are the facts that now students have to cooperate remotely with each other not only across continents but also inside their own city or country. It has increased the awareness of the need for this kind of training and effectively improved the interactions between team elements in different countries and improved the students' feeling of belonging to their team.

关键词： Software Software engineering Games Faces Teamwork Electronic mail Tools

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Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy

arXiv

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arXiv 2020年

作者： Ali, Sharib Dmitrieva, Mariia Ghatwary, Noha Bano, Sophia Polat, Gorkem Temizel, Alptekin Krenzer, Adrian Hekalo, Amar Guo, Yun Bo Matuszewski, Bogdan Gridach, Mourad Voiculescu, Irina Yoganand, Vishnusai Chavan, Arnav Raj, Aryan Nguyen, Nhan T. Tran, Dat Q. Huynh, Le Duy Boutry, Nicolas Rezvy, Shahadate Chen, Haijian Choi, Yoon Ho Subramanian, Anand Balasubramanian, Velmurugan Gao, Xiaohong W. Hu, Hongyu Liao, Yusheng Stoyanov, Danail Daul, Christian Realdon, Stefano Cannizzaro, Renato Lamarque, Dominique Tran-Nguyen, Terry Bailey, Adam Braden, Barbara East, James Rittscher, Jens Institute of Biomedical Engineering and Big Data Institute Old Road Campus University of Oxford Oxford United Kingdom Translational Gastroenterology Unit Experimental Medicine Div. John Radcliffe Hospital University of Oxford Oxford United Kingdom Oxford NIHR Biomedical Research Centre Oxford United Kingdom Université de Versailles St-Quentin en Yvelines Hôpital Ambroise Paré France Instituto Onclologico Veneto IOV-IRCCS Padova Italy CRO Centro Riferimento Oncologico IRCCS Aviano Italy Computer Engineering Department Arab Academy for Science and Technology Alexandria Egypt Department of Computer Science University College London London United Kingdom CRAN UMR 7039 University of Lorraine CNRS Nancy France Graduate School of Informatics Middle East Technical University Ankara Turkey Department of Artificial Intelligence and Knowledge Systems University of Würzburg Germany School of Engineering University of Central Lancashire United Kingdom Department of Computer Science University of Oxford United Kingdom Mimyk Medical Simulations Pvt Ltd Indian Institute of Science Bengaluru India Dhanbad India Hanoi Viet Nam Le Kremlin-BicêtreF-94270 France School of Science and Technology Middlesex University London United Kingdom Department of Computer Science School of Informatics Xiamen University China Sungkyunkwan University Seoul Korea Republic of Claritrics India Pvt Ltd Chennai India School of Medical Science and Technology Indian Institute of Technology KharagpurWest Bengal India Shanghai Jiaotong University Shanghai China Ibn Zohr University Computer Science HIT Agadir Morocco

The Endoscopy computer Vision Challenge (EndoCV) is a crowd-sourcing initiative to address eminent problems in developing reliable computer aided detection and diagnosis endoscopy systems and suggest a pathway for clinical translation of technologies. Whilst endoscopy is a widely used diagnostic and treatment tool for hollow-organs, there are several core challenges often faced by endoscopists, mainly: 1) presence of multi-class artefacts that hinder their visual interpretation, and 2) difficulty in identifying subtle precancerous precursors and cancer abnormalities. Artefacts often affect the robustness of deep learning methods applied to the gastrointestinal tract organs as they can be confused with tissue of interest. EndoCV2020 challenges are designed to address research questions in these remits. In this paper, we present a summary of methods developed by the top 17 teams and provide an objective comparison of state-of-the-art methods and methods designed by the participants for two sub-challenges: i) artefact detection and segmentation (EAD2020), and ii) disease detection and segmentation (EDD2020). Multi-center, multi-organ, multi-class, and multi-modal clinical endoscopy datasets were compiled for both EAD2020 and EDD2020 sub-challenges. The out-of-sample generalization ability of detection algorithms was also evaluated. Whilst most teams focused on accuracy improvements, only a few methods hold credibility for clinical usability. The best performing teams provided solutions to tackle class imbalance, and variabilities in size, origin, modality and occurrences by exploring data augmentation, data fusion, and optimal class thresholding techniques. © 2020, CC BY-NC-SA.

关键词： Endoscopy

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Infants' pain recognition based on facial expression: Dynamic hybrid descriptions

Infants' pain recognition based on facial expression: Dynami...

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作者： Zhi, Ruicong Zamzmi, Ghada Goldgof, Dmitry Ashmeade, Terri Li, Tingting Sun, Yu School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083 China Department of Computer Science and Engineering University of South Florida TampaFL33620 United States College of Medicine Pediatrics University of South Florida TampaFL33620 United States

The accurate assessment of infants' pain is important for understanding their medical conditions and developing suitable treatment. Pediatric studies reported that the inadequate treatment of infants' pain might cause various neuroanatomical and psychological problems. The fact that infants can not communicate verbally motivates increasing interests to develop automatic pain assessment system that provides continuous and accurate pain assessment. In this paper, we propose a new set of pain facial activity features to describe the infants' facial expression of pain. Both dynamic facial texture feature and dynamic geometric feature are extracted from video sequences and utilized to classify facial expression of infants as pain or no pain. For the dynamic analysis of facial expression, we construct spatiotemporal domain representation for texture features and time series representation (i.e. time series of frame-level features) for geometric features. Multiple facial features are combined through both feature fusion and decision fusion schemes to evaluate their effectiveness in infants' pain assessment. Experiments are conducted on the video acquired from NICU infants, and the best accuracy of the proposed pain assessment approaches is 95.6%. Moreover, we find that although decision fusion does not perform better than that of feature fusion, the False Negative Rate of decision fusion (6.2%) is much lower than that of feature fusion (25%). © Copyright 2018 The Institute of Electronics Information and Communication Engineers.

关键词： Time series

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Mining and linking open economic data from governmental communities 14th

Mining and linking open economic data from governmental comm...

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14th IFIP WG 2.13 International Conference on Open Source Systems, OSS 2018

作者： Vafopoulos, Michalis Rallis, Stylianos Anagnostopoulos, Ioannis Peristeras, Vassilios Negkas, Dimitrios Skaros, Ilias Tzani, Aggelos Software and Knowledge Engineering Laboratory IIT NCSR-"Demokritos" Athens Greece School of Engineering Department of Production and Management Engineering Democritus University of Thrace Xanthi Greece School of Sciences Department of Computer Science and Biomedical Informatics University of Thessaly Lamia Greece School of Science and Technology International Hellenic University Thessaloniki Greece

ISBN: (纸本)9783319923741

In this paper, we propose a model conceptualization (Linked Open Economy - LOE) capable of exploiting the massive amount and variety of open economic data that are gradually becoming available by governments and open source communities. The main aim is to unleash the power of open data and open source systems and create a common ground to serve as a catalyst in providing more efficient answers in important economic activities. © 2018, IFIP International Federation for Information Processing.

关键词： Open Data

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Work in Progress – Establishing a Master Program in Cyber Physical Systems: Basic Findings and Future Perspectives

Work in Progress – Establishing a Master Program in Cyber P...

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International Conference on Promising Electronic Technologies (ICPET)

作者： Isam Ishaq Rashid Jayousi Salaheddin Odeh Ezzaldeen Edwan Asmaa Shaheen Mohamed Elnaggar Ahmed Elagha Samy Salamah Christian Weber Hasan Abu Rasheed Raimund Kirner Martina Doolan Hamidreza Ahmadian Roman Obermaisser Dhiah el Diehn I. Abou-Tair Ala Khalifeh Sahel Alouneh Zaid Alhalhouli Khalid Alemerien Faiez Gargouri Bassem Bouaziz Nadia Aloui Mohammad Saleh Computer Engineering and Science Departments Al-Quds University Jerusalem Palestine Engineering Program and Computer Department Palestine Technical College - Deir El-Balah Deir El-Balah Palestine Institute of Knowledge Based Systems & Knowledge Management University of Siegen Siegen Germany University of Siegen Siegen Germany School of Engineering and Computer Science University of Hertfordshire Hatfield UK Chair of Embedded Systems University of Siegen Siegen Germany German Jordanian University Amman Jordan School of Electrical Engineering and Information Technology German Jordanian University Amman Jordan Computer and Information Technology Department Tafila Technical University Tafila Jordan Higher Institute of Computer Science and Multimedia University of Sfax Sfax Tunisia Higher Institute of Applied Sciences and Technology of Mateur University of Carthage Mateure Tunisia KTH Royal Institute of Technology Stockholm Sweden

This paper reports on the basic findings and future perspectives of a capacity building project funded by the European Union. The International Master of science on Cyber Physical Systems (MS@CPS) is a collaborative project that aims to establish a master program in cyber physical systems (CPS). A consortium composed of nine partners proposed the project. Three partners are European and from Germany, UK and Sweden; while the other six partners are from the South Mediterranean region and include: Palestine, Jordan and Tunisia. The consortium is led by the University of Siegen in Germany who also manages the implementation of the work packages. CPS is an emerging engineering subject with significant economic and societal implications, which motivated the consortium to propose the establishment of a master program to offer educational and training opportunities at graduate level in the fields of CPS. In this paper, CPS as a field of study is presented with an emphasis on its importance, especially with regard to meeting local needs. A brief description of the project is presented in conjunction with the methodology for developing the courses and their learning outcomes.

关键词： computer science Internet of Things Industries knowledge engineering Embedded systems Europe Collaboration

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computer and network security

arXiv

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arXiv 2020年

作者： Sen, Jaydip Mehtab, Sidra Sone, Michael Ekonde Jyothsna, Veeramreddy Prasad, Koneti Munivara Singh, Rajeev Sharma, Teek Parval Noskov, Anton Velásquez, Ignacio Caro, Angélica Rodríguez, Alfonso Fatayer, Tamer S.A. Mulani, Altaf O. Mane, Pradeep B. Chitrakar, Roshan Bhusal, Roshan Maharjan, Prajwol School of Computing and Analytics NSHM Knowledge Campus Kolkata India College of Technology University of Buea Buea Cameroon Sree Vidyanikethan Engineering College Tirupati India Chadalawada Ramanamma Engineering College Tirupati India G.B. Pant University of Agriculture and Technology PantnagarUttarakhand India National Institute of Technology HamirpurHimachal Pradesh India Yaroslavl State Technical University Yaroslavl Russia Computer Science and Information Technologies Department University of Bío-Bío Chillán Chile Computer Science and Information Technology Al-Aqsa University Gaza Palestine AISSMS Institute of Information Technology PuneMaharashtra India Nepal Open University Nepal Nepal College of Information Technology Nepal

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Performance Analysis of Machine Learning Algorithms for Gender Classification

Performance Analysis of Machine Learning Algorithms for Gend...

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International Conference on Inventive Communication and Computational Technologies (ICICCT)

作者： Laxmi Narayana Pondhu Govardhani Kummari Department of Computer Science and Engineering Rajiv Gandhi University of Knowledge Technologies Basar India Department of Computer Science and Engineering Kodada Institute of Technology and Science for Women Kodada India

We have various machine algorithms for gender classification but choosing best one is important task. For selecting best algorithm we conducted experimental study on machine learning algorithms for gender classification. In this experimental study of machine learning algorithms, we analyzed performance of various algorithms for gender classification using voice dataset. From this study we concluded that SVM and ANN are giving best results. After tuning parameters ANN outperforms SVM giving accuracy 99.87% on test data.

关键词： Frequency measurement Support vector machines Machine learning algorithms Artificial neural networks Acoustics Machine learning Classification algorithms

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Collective fast delivery by energy-efficient agents

arXiv

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arXiv 2018年

作者： Bärtschi, Andreas Graf, Daniel Mihalák, Matúš ETH Zürich Department of Computer Science Switzerland Department of Data Science and Knowledge Engineering Maastricht University Netherlands

We consider k mobile agents initially located at distinct nodes of an undirected graph (on n nodes, with edge lengths). The agents have to deliver a single item from a given source node s to a given target node t. The agents can move along the edges of the graph, starting at time 0, with respect to the following: Each agent i has a weight ωithat defines the rate of energy consumption while travelling a distance in the graph, and a velocity νiwith which it can move. We are interested in schedules (operating the k agents) that result in a small delivery time Τ (time when the item arrives at t), and small total energy consumption ϵ. Concretely, we ask for a schedule that: either (i) Minimizes Τ, (ii) Minimizes lexicographically (Τ, ϵ) (prioritizing fast delivery), or (iii) Minimizes ϵ · Τ + (1 - ϵ) · ϵ, for a given ϵ ∈ (0, 1). We show that (i) is solvable in polynomial time, and show that (ii) is polynomial-time solvable for uniform velocities and solvable in time O(n + k log k) for arbitrary velocities on paths, but in general is NP-hard even on planar graphs. As a corollary of our hardness result, (iii) is NP-hard, too. We show that there is a 3-approximation algorithm for (iii) using a single agent. Copyright © 2018, The Authors. All rights reserved.

关键词： Mobile agents

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A study of lexical ambiguity in large forum discussions for multidisciplinary knowledge engineering 13

A study of lexical ambiguity in large forum discussions for ...

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13th International Conference on knowledge, Information and Creativity Support Systems, KICSS 2018

作者： Takhom, Akkharawoot Boonkwan, Prachya Ulrich Hoppe, H. Ikeda, Mitsuru Usanavasin, Sasiporn Supnithi, Thepchai Japan Advanced Institute of Science and Technology School of Knowledge Science Nomi Japan School of Information Computer and Communication Technology Sirindhorn International Institute of Technology Thammasat University Pathum Thani Thailand Language and Semantic Technology Laboratory National Electronics and Computer Technology Center Pathum Thani Thailand Department of Computer Science and Applied Cognitive Science Faculty of Engineering University of Duisburg-Essen Duisburg Germany

ISBN: (纸本)9781728101613

Lexical ambiguity is a challenging issue in multidisciplinary knowledge engineering due to the tendency that lexical terms can be used among different domains with different specific meanings. Particularly in large forum discussions, such ambiguous cross-disciplinary terms hard to be identified and detected by the discussion participants because domain expertise from several relevant fields is required to detect those terms and discover the actual divergence of interpretation. Having many ambiguous terms in the discussion context will result in gradual misunderstanding and delayed knowledge construction. We studied the effects of data sizes and morphological analysis in discovering ambiguous cross-disciplinary terms in large forum discussions. Our findings are twofold. First, it is more likely to discover cross-disciplinary terms as forum discussions deepen. This correlates with domain experts' tendency to use general terms in metaphorically describing domain-specific concepts, therefore causing lexical ambiguity. Second, we found that lemmatization outperforms stemming in forming more understandable key terms. This is because lemmatization eliminates only inflectional affixes and keeps derivational affixes. On the other hand, stemming eliminates both types of affixes, causing semantic bleaching. © 2018 IEEE.

关键词： knowledge engineering

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