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ACKNOWLEDGMENTS We would like to acknowledge the support granted by CAPES process AEX 4982/12-6. REFERENCES [1] T. Conte, J. Massollar, E. Mendes and G. Travassos, “Web usability inspection technique based on d esign perspectives,” IET Software, Volume 3, Issue 2, 2009. [2] A. Fernandez, E. Insfran and S. Abrahao, “Usability evaluation methods for the Web: A systematic mapping study,” Information and Software Technology, Volume 53, Issue 8, 2011. [3] J. Fons, V. Pelechano, O. Pastor, P. Valderas, and V. Torres, “Applying the OOWS model-driven approach for developing Web applications: The internet movie database case study,” In: G. Rossi, D. Schwabe, L. Olsina and O. Pastor, Web Engineering: Modeling and Implementing Web Applications, Springer, 2008. [4] E. Insfran and A. Fernandez, “A Systematic Review of Usability Evaluation in Web Development,” Proc. Second International Workshop on Web Usability and Accessibility, New Zealand, 2008, pp. 81-91. [5] International Organization for Standardization, ISO/IEC 9241-11: Ergonomic Requirements for Office work with Visual Display Terminals (VDTs) – Part 11: Guidance on Usability, 1998. [6] M. Matera, F. Rizzo and G. Carughi, “Web Usability: Principles and Evaluation Methods,” In: E. Mendes and N. Mosley, N, Web Engineering, Springer, 2006. [7] E. Mendes, N. Mosley and S. Counsell, “The Need for Web Engineering: An Introduction. Web Engineering,” In: E. Mendes and N. Mosley, Web Engineering, Springer, 2006. [8] J. Nielsen, “Finding usability problems through heuristic evaluation,” Proc. CHI’92, UK, 1992, pp. 373-380. [9] J. Offutt, “Quality attributes of Web software applications,” IEEE Software: Special Issue on Software Engineering of Internet Software, Volume 19, Issue 2, 2002. [10] L. Olsina, G. Covella and G. Rossi, “Web Quality,” In: E. Mendes and N. Mosley, Web Engineering, Springer, 2006. [11] P. Polson, C. Lewis, J. Rieman and C. Wharton, “Cognitive walkthroughs: a method for theory-based evaluation of user interfaces,” International Journal of Man-Machine Studies, Volume 36, Issue 5, 1992. [12] L. Rivero and T. Conte, “Characterizing Usability Inspection Methods through the Analysis of a Systematic Mapping Study Extension,” Proc. IX Experimental Software Engineering Latin Workshop, Argentina, 2012. [13] L. Rivero and T. Conte, “Web DUE technique: Usability Verification Items per Web Page Zone,” Technical Report RT-USES-2012-001, 2012. Available at: http://www.dcc.ufam.edu.br/uses/index.php/ publicacoes/cat_view/69-relatorios-tecnicos. [14] H. Rocha and M. Baranauska, “Design and Evaluation of Human Computer Interfaces,” (Book), Nied, 2003. (in Portuguese) [15] Z. Zhang, V. Basili and B. Shneiderman, “Perspective-based Usability Inspection: An Empirical Validation of Efficacy,” Empirical Software Engineering, Volume 4, Issue 1, 1999. SELECTED PRIMARY STUDIES LIST [S01] M. Allen, L. Currie, S. Patel and J. Cimino, “Heuristic evaluation of paper-based Web pages: A simplified inspection usability methodology,” Journal of Biomedical Informatics, Volume 39, Issue 4, 2006. [S02] D. Alonso-Rios, I. Vazquez, E. Rey, V. Bonillo and B. Del Rio, “An HTML analyzer for the study of Web usability,” Proc. IEEE International Conference on Systems, Man and Cybernetics, USA, 2009, pp. 1224-1229. [S03] C. Ardito, R. Lanzilotti, P. Buono, and A. Piccinno, “A tool to support usability inspection,” Proc. Working Conference on Advanced Visual Interfaces, Italy, 2006, pp. 278-281. [S04] R. Atterer and A. Schmidt, “Adding Usability to Web Engineering Models and Tools,” Proc. 5th International Conference on Web Engineering, Australia, 2005, pp. 36-41. [S05] A. Basu, “Context-driven assessment of commercial Web sites,” Proc. 36th Annual Hawaii International Conference on System Sciences, USA, 2003, pp. 8-15. [S06] M. Blackmon, P. Polson, M. Kitajima and C. Lewis, “Cognitive walkthrough for the Web,” Proc. SIGCHI Conference on Human Factors in Computing Systems, USA, 2002, pp. 463-470. [S07] M. Blackmon, M. Kitajima and P. Polson, “Repairing usability problems identified by the cognitive walkthrough for the Web,” Proc. SIGCHI Conference on Human Factors in Computing Systems, USA, 2003, pp. 497- 504. [S08] M. Blackmon, M. Kitajima and P. Polson, “Tool for accurately predicting Website navigation problems, non-problems, problem severity, and effectiveness of repairs,” Proc. SIGCHI Conference on Human Factors in Computing Systems, USA, 2005, pp. 31-40. [S09] D. Bolchini and F. Garzotto, “Quality of Web Usability Evaluation Methods: An Empirical Study on MiLE+,” Proc. International Workshop on Web Usability and Accessibility, France, 2007, pp. 481-492. [S10] C. Burton and L. Johnston, “Will World Wide Web user interfaces be usable?,” Proc. Computer Human Interaction Conference, Australia, 1998, pp. 39-44. [S11] J. Chattratichart and J. Brodie, “Applying user testing data to UEM performance metrics,” Proc. of the Conference on Human Factors in Computing Systems, Austria, 2004, pp. 1119-1122. [S12] T. Conte, J. Massollar, E. Mendes and G. Travassos, “Web usability inspection technique based on design perspectives,” IET Software, Volume 3, Issue 2, 2009. [S13] M. Costabile and M. Matera, “Guidelines for hypermedia usability inspection,” IEEE Multimedia, Volume 8, Issue 1, 2001. [S14] L. Filgueiras, S. Martins, C. Tambascia, and R. Duarte, “Recoverability Walkthrough: An Alternative to Evaluate Digital Inclusion Interfaces,” Proc. Latin American Web Congress, Mexico, 2009, pp. 71-76. [S15] P. Fraternali, and M. Tisi, “Identifying Cultural Markers for Web Application Design Targeted to a M ulti-Cultural Audience,” Proc. 8th International Conference on Web Engineering, USA, 2008, pp. 231-239. [S16] Y. Habuchi, M. Kitajima and H. Takeuchi, “Comparison of eye movements in searching for easyto-find and hard-to-find information in a hierarchically organized information structure,” Proc. Symposium on Eye Tracking Research & Applications, USA, 2008, pp. 131-134. [S17] S. Kirmani, “Heuristic Evaluation Quality Score (HEQS): Defining Heuristic Expertise,” Journal of Usability Studies, Volume 4, Issue 1, 2008. [S18] F. Molina and A. Toval, “Integrating usability requirements that can be evaluated in design time into Model Driven Engineering of Web Information Systems,” Advances in Engineering Software, Volume 40, Issue 12, 2009. [S19] M. Moraga, C. Calero and M. Piattini, “Ontology driven definition of a usability model for second generation portals,” Proc. 1st International Workshop on Methods, Architectures & Technologies for e-Service Engineering, USA, 2006. [S20] A. Oztekin, A. Nikov and S. Zaim, “UWIS: An assessment methodology for usability of Web-based information systems,” Journal of Systems and Software, Volume 8, Issue 12, 2009. [S21] L. Paganelli and F. Paterno, “Automatic reconstruction of the underlying interaction design of Web applications,” Proc. 14th International Conference on Software Engineering and Knowledge Engineering, Italy, 2002, pp.439-445. [S22] P. Paolini, “Hypermedia, the Web and Usability issues,” Proc. IEEE International Conference on Multimedia Computing and Systems, Italy, 1999, pp. 111-115. [S23] O. Signore, “A comprehensive model for Web sites quality,” Proc. 7th IEEE International Symposium on Web Site Evolution, Hungary, 2005, pp. 30-36. [S24] A. Thompson and E. Kemp, “Web 2.0: extending the framework for heuristic evaluation,” Proc. 10th International Conference NZ Chapter of the ACM’s Special Interest Group on Human-Computer Interaction, New Zeland, 2009, pp. 29-36. [S25] L. Triacca, A. Inversini and D. Bolchini, “Evaluating Web usability with MiLE+,” Proc. 7th IEEE International Symposium on Web Site Evolution, Hungary, 2005, pp. 22-29. [S26] J. Vanderdonckt, A. Beirekdar, and M. Noirhomme-Fraiture, “Automated Evaluation of Web Usability and Accessibility by Guideline Review,” Proc. 4th International Conference on Web Engineering, Munich, 2004, pp. 28-30. 587
Improving a Web Usability Inspection Technique through an Observational Study Priscila Fernandes, Tayana Conte Grupo de Usabilidade e Engenharia de Software (USES) Universidade Federal do Amazonas Manaus, Brazil {priscila.fernandes, tayana}@icomp.ufam.edu.br Bruno Bonifácio Nokia Institute of Technology - INdT Manaus, Brazil {bruno.bonifacio}@indt.org.br Abstract— Given the growth in the usage of Web Applications, the usability of these applications has become a key success factor. Several technologies have been developed to evaluate and improve this quality factor. However, the usability inspections results still depend on the inspector’s experience. We have proposed a Web usability inspection approach, called WE-QT (Web Evaluation – Question Technique), a question based technique that aims to reduce the difficulties of inspectors with little knowledge of usability. We are following an experimentation-based methodology to support its development and improvement. This paper presents an observational study, aimed at eliciting how inspectors apply the WE-QT technique. We discuss the quantitative and qualitative results and their impact on improving the WE-QT. Results indicated that our technique assists novice inspectors uncovering usability problems effectively; despite qualitative data indicate the need for improvement. Keywords – web application, usability evaluation, inspection technique; observarional study; qualitative analysis I. INTRODUCTION The increasing popularity of Web applications has allowed an intensive use of these applications in current society [1]. The success of Web applications can be determined by two features: their fast evolution and their usability [2]. Usability is considered to be one of the most important quality factors for Web applications, along with others such as reliability and security [3]. The acceptability of Web applications relies strictly on the usability of the applications [4]. Web applications with poor usability will be quickly replaced by other ones more usable, as soon as its existence becomes known to the target audience [5]. Still, users often face errors while using these applications, caused by the not intuitive interfaces [6]. Therefore, improving usability of Web application can substantially minimize the users’ interaction difficulty and improve the quality of these applications [7]. The challenge of developing Web applications with more intuitive interface has made the usability evaluation of these applications an important research area. Several methodologies to ensure a good usability specific for Web applications have been proposed, some of them based on user testing and others based on inspections performed by experts [8]. However, usability evaluations on Web development processes are often avoided by developers or companies due to their lack of experience in the field. Despite the high demand for usability evaluations of Web applications, developing methods to assist novice inspectors detecting defects without compromising the inspection result is not a simple task. According to Conte et al. [9], inspectors’ skills such as experience on usability and inspection can affect the outcome of the inspection. For this reason, we have proposed a new usability inspection technique, called WE-QT (Web Evaluation Question-Technique) [10]. The WE-QT technique was specifically tailored for usability evaluation of Web applications for novice evaluators. It uses a question based approach to guide the inspectors uncovering usability problems. The main goal of our solution is to minimize the difficulties and efforts of software developers with little knowledge in usability when executing inspections. To support the development and validation of the WE-QT technique, we adopted the experimental methodology presented in [11]. This methodology comprises four stages: 1) feasibility studies to determine the usage possibility of the technology; 2) observational studies to improve the understanding of the technology, that aims to answer the question “Do the steps of the process make sense?”; 3) case studies in real lifecycle to characterize the technology application during a real lifecycle, and; 4) case studies in industry to identify if technology application fits into the industrial setting. Following this methodology, Fernandes et al. [10] presented an overview of the development of our technique and the feasibility study results, including discussions on how the methodology guided this phase of its development. This paper describes the conducted observational study, aimed at eliciting how inspectors apply the WE-QT technique. We analyzed the qualitative data using coding procedures [12]. We discuss the results of the quantitative and qualitative data analyses and their impact in the improvement of the WE-QT technique. The results show that our technique assists novice inspector detecting usability defects effectively. The remainder of this paper is structured as follows: Section 2 presents some background information on Web usability evaluation. Section 3 pr esents our technique, as th e results of a feasibility study aimed at improving the technique. In Section 4, the observational study to evaluate our technique 588
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SEKE San Francisco Bay July 1-3 201
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Copyright © 2012 by Knowledge Syst
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The 24 th International Conference
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Zhenyu Chen, Nanjing University, Ch
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Riccardo Martoglia, University of M
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Evaluating the Cost-Effectiveness o
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Computer Forensics: Toward the Cons
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Modeling Bridging KDM and ASTM for
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A Mapping Study on Software Product
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A proposal for the improvement of t
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Panel on Future Trends of Software
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een available for analysis. Social
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Now we assume is given, we first pr
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“iphone” and “blackberry” a
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nique estimate the impact set based
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Figure 1. An example to illustrate
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trategy, the results should support
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Figure 1. System Architecture would
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Figure 2. Sequence Diagram of Train
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deployed on Android phone and runs
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the ontology information is only us
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engineer and achieving requirements
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elicitation and the act ivities con
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original User’s Discourse / Speec
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II. RELATED WORK Business processes
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test, we did not find any significa
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the model checkers SPIN [8] and NuS
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allow for the presentation of syste
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the requirement or design phases sh
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using the CR estimates against the
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Data Set TABLE II. DATA SETS Artifa
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Figure 4. Relative Error in the Est
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Take basic requirements from user a
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sent Semantic Web Ontologies. It co
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and the risk level. Existing assess
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diagram could give developers an in
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Figure 2. Co
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• Sensor(Lexical): at the top and
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An Overview of the RSLingo Approach
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Figure 2. Overview of the RSLingo a
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DETECTING EMERGENT BEHAVIOR IN DIST
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Definition 2: For a set of MSCs M,
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Stability of Filter-Based Feature S
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MI KS GM AUC PRC S2N RUS35 RUS50 RO
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Cloud Application Resource Mapping
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An Empirical Study of Software Metr
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TABLE I SOFTWARE DATASETS CHARACTER
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1) Classifiers: In this study, soft
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Progressive Clustering with Learned
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IV. DATA SOURCES We have been worki
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meta-data we assign to indicate sig
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Multi-Objective Optimization of Fuz
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uilding FNNs that satisfy different
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VI. EXPERIMENTAL RESULTS The presen
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Generating Performance Test Scripts
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test duration(s) for the scenario(s
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which are composed by the name and
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A Catalog of Patterns for Concept L
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assisted solution for lattice analy
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Client-Side Rendering Mechanism: A
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JavaScript code directly within the
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[9] but no validation is provided i
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Recommender systems are usually cla
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such as one week and gradually dete
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•
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Enforcing Contracts for Aspect-orie
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Table 1. Behavioral Rules in LSD [9
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1 public privileged aspect Update {
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Towards More Generic Aspect-Oriente
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Aspect-Orientation in the Developme
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Table II SELECTED PRIMARY STUDIES #
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Evaluating Open Source Reverse Engi
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Some tools may perform the needed f
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Coordination Model to Support Visua
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this CMV approach we employee three
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colored according to the Gradient T
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Improving Program Comprehension in
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An Approach for Software Component
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properties. In particular, the foll
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Conference Dataset Anatomy Dataset
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equipment maintenance node may cont
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Online Anomaly Detection for Compon
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undle which is responsible for pars
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An Exploratory Study of One-Use and
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subject also caused outliers for re
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Choosing licenses in free open sour
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that holds a model of each software
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Online Probability Application Char
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TABLE II THE PARAMETERS FOR THE HAR
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[10] N. Gunther, “Hit-and-run tac
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Section 5 d iscusses some related w
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model and the analysis results. The
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tree view of UML model, as show in
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II. BACKGROUND In this section, we
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Algorithm 2 MarkStatements function
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(a) printtok (b) printtok2 (c) sche
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Gupta extended HGS and proposed the
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manage intellectual knowledge with
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D. Manage Training When any trainin
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B. Trace Semantics of DAP Fig. 1. A
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executing a continuous transition,
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4.4. An Illustrative Example Now le
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Evolutionary Learning and Fuzzy Log
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As described in the previous sectio
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the ontology hierarchy; learning a
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three different learning techniques
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TABLE IX. USING SVM FOR LEARNING tr
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Siemens set contains seven C progra
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esults. To be more specific, they w
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(a) Volatility (b) Complexity (c) R
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integrate the test results. • Aut
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No tify the cloud controller to get
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of execution-data classification. T
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anches is more applicable than the
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Patient Doctor Doctor Patient Direc
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satisfies R( D) R( C) S 1. Compa
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sequence. Each t i θ i in the firi
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SAMAT -AToolforSoftware Architectur
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Figure 4. The SAM Hierarchical Mode
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High-level Petri net Place Place Ty
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access control exists, the action i
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Connectors for Secure Software Arch
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anAsynchronousCustomer InterfaceCon
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How Social Network APIs Have Ended
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users can control the reach of thei
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Computer Forensics: Toward the Cons
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In 2009, Cohen et al. in [4] have o
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dcterms:contributor, dcterms:creato
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A Holistic Approach to Software Tra
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Figure 1. Figure 1 shows an overvie
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B. Case study in a proprietary proj
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Pointcut Design with AODL Saqib iqb
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system attributes, methods and exec
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Feature modeling and Verification b
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Ontology-based Representation of Si
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Automatic Generation of Architectur
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different from replacing it, we dec
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Using FCA-based Change Impact Analy
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Figure 3. The PF and PTS results fo
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Forecasting Fault Events in Power D
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which the airport data did not cont
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classified. Recall is the probabili
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Testing Interoperability Security P
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Objective Figure 4. Testing
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A New Approach to Evaluate Path Fea
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k v ( df i ) 0 , it means that the
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Model & Method Feasibility Evaluati
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Structural Testing for Multithreade
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adequate to another criterion. This
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A Tiny Specification Metalanguage W
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derivation dependencies. The third
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model extension as proposed in [6].
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Figure 1. The process for engineeri
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Figure 4. The abstractions extracte
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way to detect something which could
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Algorithm 1: Algorithm to recursive
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obtain the input of experts on desi
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A. Pattern Reuse In patterns reuse
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IV. SCATTER In order to enhance pat
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These latter would be clustered acc
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described or even r etrieved, thus
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DC2AP Element and their Application
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21. Consequences Example of use DC2
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Legacy2Cloud logic. In this scope,
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2.3.1 Complementarity of MDD techno
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3.2.2 EAggregateRelationship The EA
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cess. The proposal follows the ADM
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II. OVERVIEW OF MODAL TRANSITION SY
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(1) V □ (A) ⊆ V □ (B), V ♦
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Suppose P = 〈S P , SP i , AI P ,
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Adaptive software should basically
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A. Step S1 - Define the Business Pr
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Page 577 and 578: the project. This achievement has t
Page 579 and 580: proposed in this work requires the
Page 581 and 582: FTS is an important research area,
Page 583 and 584: C. Dependent Variables and Measures
Page 585 and 586: D. Conclusion Validity Conclusion v
Page 587 and 588: evaluation of team productivity, qu
Page 589 and 590: Figure 3: Process Fragment Example
Page 591 and 592: complexity issues traditionally inv
Page 593 and 594: Fig. 1: Swing Framework Class Diagr
Page 595 and 596: ize:Class”, with an empty precond
Page 597 and 598: Fig. 11: Overwritten Method Fig. 12
Page 599 and 600: Investigating the use of Bayesian n
Page 601 and 602: process for the network. Thus, this
Page 603 and 604: Reuse of Experiences Applied to Req
Page 605 and 606: Step 1: To start the process, the u
Page 607 and 608: Specification of Safety Critical Sy
Page 609 and 610: current belief of agents in order t
Page 611 and 612: Using the Results from a Systematic
Page 613 and 614: obtained from the categorization of
Page 615: that automatically presents the usa
Page 619 and 620: Following the experimental methodol
Page 621 and 622: About the category “Improvements
Page 623 and 624: Identification Guidelines for the D
Page 625 and 626: created according to the preview re
Page 627 and 628: In our analysis, the “Government
Page 629 and 630: In the following, we present the re
Page 631 and 632: USE SCENARIO The application Vuelos
Page 633 and 634: [8] Mayhew, D., “The Usability En
Page 635 and 636: Interaction State Set Structure Dat
Page 637 and 638: B. Component Model Fig. 2 show s th
Page 639 and 640: As a continuation of our research w
Page 641 and 642: PROMETHEE methods [3] belong to a f
Page 643 and 644: comparison rule, a value of 1/9 is
Page 645 and 646: TABLE V: Supermatrix for the exampl
Page 647 and 648: for knowledge sharing. Based on str
Page 649 and 650: y applying hash functions to its su
Page 651 and 652: Empirical Validation of Variability
Page 653 and 654: III. EXPERIMENTAL STUDY In this sec
Page 655 and 656: Table III SPEARMAN’S CORRELATION
Page 657 and 658: A Mapping Study on Software Product
Page 659 and 660: most relevant sources in software e
Page 661 and 662: TABLE IV TOOL’S CLASSIFICATION AC
Page 663 and 664: [2] P. Clements and L. Northrop, So
Page 665 and 666: and future works. II. BACKGROUND ON
Page 667 and 668:
System Advanced Standard Module A M
Page 669 and 670:
Algorithm 1: Backtracking for MIN-A
Page 671 and 672:
outcomes from such research fields,
Page 673 and 674:
TABLE IV. CONTINUED FROM PREVIOUS P
Page 675 and 676:
contribution of each study was made
Page 677 and 678:
assets, the plugin approach can be
Page 679 and 680:
Figure 3: PlugSPL Feature Model Edi
Page 681 and 682:
contributions from the several acto
Page 683 and 684:
o Guideline 6.4: Softgoal dependenc
Page 685 and 686:
descriptions must also b e configur
Page 687 and 688:
It means that throughout the develo
Page 689 and 690:
B. Instrumentation The experiment w
Page 691 and 692:
• External Validity: W e have con
Page 693 and 694:
II. THE PROPOSED TAXONOMY The taxon
Page 695 and 696:
sub-dimension is categorized as, co
Page 697 and 698:
A Proposal of Reference Architectur
Page 699 and 700:
Figure. 1. Reference Architecture M
Page 701 and 702:
A Variability Management Method for
Page 703 and 704:
C. Correctness of configuration fil
Page 705 and 706:
means patterns which are shown in s
Page 707 and 708:
Tool Support for Anomaly Detection
Page 709 and 710:
Figure 1. System overview of the SD
Page 711 and 712:
Once the datasets were evaluated us
Page 713 and 714:
Reconfiguration of Robot Applicatio
Page 715 and 716:
data dependencies required for keep
Page 717 and 718:
Spacemaker: Practical Formal Synthe
Page 719 and 720:
Fig. 1. The ecommerce object model.
Page 721 and 722:
Fig. 3. Mapping diagram for Figure
Page 723 and 724:
A formal support for incremental be
Page 725 and 726:
machine may be empty which should l
Page 727 and 728:
software, based on revised requirem
Page 729 and 730:
A Process-Based Approach to Improvi
Page 731 and 732:
Appropriate processes m ust support
Page 733 and 734:
Figure 2. Reordered layers of the k
Page 735 and 736:
Automatic Acquisition of isA Relati
Page 737 and 738:
III. VALIDATING THE DIMENSION HEADE
Page 739 and 740:
The table title and the dimension s
Page 741 and 742:
A light weight alternative for OLAP
Page 743 and 744:
i.d. subsets of cubes focused on se
Page 745 and 746:
Match production rules Enterprise S
Page 747 and 748:
A Tool for Visualization of a Knowl
Page 749 and 750:
other ontology visualization tools
Page 751 and 752:
shown at Figure 5. Objectives are s
Page 753 and 754:
Rendering UML Activity Diagrams as
Page 755 and 756:
a = O1 → a → O2 b = O2 → b
Page 757 and 758:
ecordProblem → A → reproducePro
Page 759 and 760:
umlTUowl - A Both Generic and Vendo
Page 761 and 762:
The tool’s ability to deal with S
Page 763 and 764:
Elem. UML Example D 12 Harmonizing
Page 765 and 766:
4) Associations: In the first test
Page 767 and 768:
III. GRAPH REPRESENTATION OF CLASS
Page 769 and 770:
as an add-in to popular UML m odeli
Page 771 and 772:
742
Page 773 and 774:
744
Page 775 and 776:
746
Page 777 and 778:
her necessities. However, the progr
Page 779 and 780:
Figure 3. Global Log. of terms. The
Page 781 and 782:
two stages. The first stage is focu
Page 783 and 784:
754
Page 785 and 786:
756
Page 787 and 788:
758
Page 789 and 790:
With the GDUC approach, we can mode
Page 791 and 792:
Figure 6. Three proposals containin
Page 793 and 794:
764
Page 795 and 796:
766
Page 797 and 798:
Proactive Two Way Mobile Advertisem
Page 799 and 800:
information. If more than one adver
Page 801 and 802:
Users can al so publish adv ertisem
Page 803 and 804:
The COIN Platform: Supporting the M
Page 805 and 806:
A-3
Page 807 and 808:
Checking Contracts for AOP using XP
Page 809 and 810:
Maicon B. da Silveira, 112 Aldo Dag
Page 811 and 812:
Seyedehmehrnaz Mireslami, 70 Takao
Page 813 and 814:
Wei Zhang, 422 Wenbo Zhang, 188 Zhi
Page 815 and 816:
Desmond Greer Eric Gregoire Christi
Page 817 and 818:
Poster/Demo Presenter’s Index A A
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SEKE 2012 Proceedings - Knowledge Systems Institute

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