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Magnesium has attracted considerable medical interest due to its mechanical properties being similar to bone. In addition, magnesium is also biocompatible and biodegradable, which makes it an ideal candidate for biodegradable orthopaedic implants. However, magnesium's high corrosion rate in body fluids makes it an unsuitable material for the manufacture of implants. The present study investigates a straightforward chemical immersion technique that deposits di-calcium phosphate dehydrate (DCPD) coatings onto magnesium substrates to increase their corrosion resistance to body simulated fluids like phosphate buffer saline solution and Ringer's solution. Scanning electron microscopy revealed the coating structures and morphologies were characterised by flower-like surface feature that were resistant to both body simulated fluids. Thus, indicating the coatings could significantly reduce magnesium corrosion rates in the body environment.Read Complete Article at ijSciences: V92020022281 AND DOI: http://dx.doi.org/10.18483/ijSci.2281

The global demand for energy is increasing and the detrimental consequences of rising greenhouse gas emissions, global warming and environmental degradation present major challenges. Solar energy offers a clean and viable renewable energy source with the potential to alleviate the detrimental consequences normally associated with fossil fuel-based energy generation. However, there are two inherent problems associated with conventional solar thermal energy conversion systems. The first involves low thermal conductivity values of heat transfer fluids, and the second involves the poor optical properties of many absorbers and their coating. Hence, there is an imperative need to improve both thermal and optical properties of current solar conversion systems. Direct solar thermal absorption collectors incorporating a nanofluid offers the opportunity to achieve significant improvements in both optical and thermal performance. Since nanofluids offer much greater heat absorbing and heat transfer properties compared to traditional working fluids. The review summarizes current research in this innovative field. It discusses direct solar absorber collectors and methods for improving their performance. This is followed by a discussion of the various types of nanofluids available and the synthesis techniques used to manufacture them. In closing, a brief discussion of nanofluid property modelling is also presented.

Visibility problems are central to many computational geometry applications. One of the typical visibility problems is computing the view from a given point. In this paper, a linear time procedure is proposed to compute the visibility subsets from a corner of a rectangular prism in an orthogonal polyhedron. The proposed algorithm could be useful to solve classic 3D problems., {"references":["F. d. Durand, et al., \"The 3D Visibility Complex,\" ACM Transactions on Graphics, vol. 21, pp. 176 - 206, 2002.","M. N. Bygi and M. Ghodsi, \"3D Visibility Graph,\" presented at the Computational Science and its Applications, Kuala Lampur, 2007.","M. Pocchiola and G. Vegter, \"Topologically sweeping visibility complexes via pseudotriangulations,\" Discrete & Computational Geometry, vol. 16, pp. 419–453, 1996.","S. K. Ghosh and D. Mount, \"An output sensitive algorithm for computing visibility graphs,\" SIAM Journal Computing, vol. 20, pp. 888-910, 1991.","H. S. M. Coxeter, Regular polytopes. New York: Dover Publications, 1973.","J. R. Rossignac and A. A. G. Requicha, \"Construcitve Non-Regularized Geometry,\" Computer - Aided Design, vol. 23, pp. 21-32, 1991.","T. Biedl and B. Genc, \"Reconstructing orthogonal polyhedra from putative vertex sets,\" technical reports, 2007.","K. Tang and T. C. Woo, \"Algorithmic aspects of alternating sum of volumes. Part 1: Data structure and difference operation,\" Computer-Aided Design, vol. 23, pp. 357-366, June 1991.","A. P. Tomas, et al., \"On visibility problems in the plane - solving minimum vertex guard problems by successive approximation,\" in the 9th Int. Symp. on Artif. Intel. and Math., 2006.\n[10]\tA. Aquilera and D. Ayala, \"Solving point and plane vs orthogonal polyhedra using the extreme vertices model (EVM),\" presented at the The Sixth International Conference in Central Europe on Computer Graphics and Visualization'98, 1998.\n[11]\tR. Juan-Arinyo, \"Domain extension of isothetic polyhedra with minimal CSG representation,\" Computer Graphics Forum, vol. 5, pp. 281-293, 1995.\n[12]\tJ. Marzal, et al., \"Vertex Configurations and Their Relationship on Orthogonal Pseudo Polyhedra \" World Academy of Science, Engineering and Technology pp. 1-8, 2011."]}

Despite the ever increasing pervasion of Information Systems (IS) in business processes the industry lacks a focus on sustainability. While concepts of sustainability have been applied to many other areas, IS is yet to demonstrate a balanced economic, ecological and social focus. This paper discusses the issues of IS sustainability and the implications for strategic IS management. It analyses the major stakeholder businesses that the Information and Communications (ICT) industry deal with and identifies requirements for successful sustainable IS management. It also discusses current emerging technologies in the field of ICT and their potential for supporting sustainable IS management. Bringing these ideas together will extend the ongoing discussion of ICT's environmental impact by providing Chief Information Officers, IS and environmental managers and researchers alike with a conceptual foundation towards future sustainable information systems management.

Vertex configuration for a vertex in an orthogonal pseudo-polyhedron is an identity of a vertex that is determined by the number of edges, dihedral angles, and non-manifold properties meeting at the vertex. There are up to sixteen vertex configurations for any orthogonal pseudo-polyhedron (OPP). Understanding the relationship between these vertex configurations will give us insight into the structure of an OPP and help us design better algorithms for many 3-dimensional geometric problems. In this paper, 16 vertex configurations for OPP are described first. This is followed by a number of formulas giving insight into the relationship between different vertex configurations in an OPP. These formulas will be useful as an extension of orthogonal polyhedra usefulness on pattern analysis in 3D-digital images., {"references":["D. Ayala and J. Rodriquez, \"Connected component labeling based on the\nEVM Model,\" in The 18th spring conference on Computer graphics,\n2002, pp. 63-71.","B. Yip and R. Klette, \"Angle Counts for Isothetic Polygons and\nPolyhedra,\" Pattern Recognition Letter, vol. 24, pp. 1275-1278, 2003.","A. Aquilera and D. Ayala, \"Solving point and plane vs orthogonal\npolyhedra using the extreme vertices model (EVM),\" presented at the\nThe Sixth International Conference in Central Europe on Computer\nGraphics and Visualization'98, 1998.","J. Czyzowicz, et al., \"Illuminating rectangles and triangles in the plane,\"\nJournal of Combinatorial Theory Series B archive, vol. 57, 1993.","M. d. Berg, et al., Computational Geometry, Second ed.: Springer, 2000.","F. P. Preparata and M. I. Shamos, Computational Geometry an\nIntroduction. New York: Springer-Verlag, 1985.","K. Tang and T. C. Woo, \"Algorithmic aspects of alternating sum of\nvolumes. Part 1: Data structure and difference operation,\" Computer-\nAided Design, vol. 23, pp. 357-366, June 1991.","J. R. Rossignac and A. A. G. Requicha, \"Construcitve Non-Regularized\nGeometry,\" Computer - Aided Design, vol. 23, pp. 21-32, 1991.","H. S. M. Coxeter, Regular polytopes. New York: Dover Publications,\n1973.\n[10] J. D. Foley, et al., Computer Graphics: Principles and Practice in C, 2nd\nedition ed.: Addison-Wesley, 1996.\n[11] T. Biedl and B. Genc, \"Reconstructing orthogonal polyhedra from\nputative vertex sets,\" technical reports, 2007.\n[12] R. Juan-Arinyo, \"Domain extension of isothetic polyhedra with minimal\nCSG representation,\" Computer Graphics Forum, vol. 5, pp. 281-293,\n1995.\n[13] K. Voss, Discrete Images, Objects, and Functions in Zn. Berlin:\nSpringer, 1993.\n[14] S. L. Senk, Advanced Algebra. Chicago: Scott Foresman/Addison\nWesley, 1998."]}

This paper proposes a novel approach to the question of lithofacies classification based on an assessment of the uncertainty in the classification results. The proposed approach has multiple neural networks (NN), and interval neutrosophic sets (INS) are used to classify the input well log data into outputs of multiple classes of lithofacies. A pair of n-class neural networks are used to predict n-degree of truth memberships and n-degree of false memberships. Indeterminacy memberships or uncertainties in the predictions are estimated using a multidimensional interpolation method. These three memberships form the INS used to support the confidence in results of multiclass classification. Based on the experimental data, our approach improves the classification performance as compared to an existing technique applied only to the truth membership. In addition, our approach has the capability to provide a measure of uncertainty in the problem of multiclass classification., {"references":["P. Smets, Uncertainty Management in Information Systems: From Needs\nto Solutions. Kluwer Academic Publishers, 1997, ch. Imperfect\ninformation: Imprecision-Uncertainty, pp. 225-254.","M. Duckham, \"Uncertainty and geographic information: Computational\nand critical convergence,\" in Representation in a Digital Geography.\nNew York: John Wiley, 2002.","P. F. Fisher, Geographical Information Systems: Principles, Techniques,\nManagement and Applications, 2nd ed. Chichester: John Wiley, 2005,\nvol. 1, ch. Models of uncertainty in spatial data, pp. 69-83.","C. C. Fung, K. W. Wong, and H. Eren, \"Modular Artificial Neural\nNetwork for Prediction of Petrophysical Properties From Well Log\nData,\" in IEEE Transactions on Instrumentation and Measurement,\nvol. 46, no. 6, 1997, pp. 1259-1263.","H. Crocker, C. C. Fung, and K. W. Wong, \"The STAG Oilfield Formation\nEvaluation: A Neural Network Approach,\" Australian Petroleum Production\nand Exploration Association APPEA99 Journal, vol. 39, part1, pp.\n451-460, 1999.","K. W. Wong and T. D. Gedeon, \"Fuzzy Rule Interpolation for Multidimensional\nInput Space with Petroleum Engineering Application,\"\nin Proceedings of Joint 9th IFSA World Congress and 20th NAFIPS\nInternational Conference, Vancouver, Canada, July 2001, pp. 2470-\n2475.","K. W. Wong, Y. S. Ong, T. D. Gedeon, and C. C. Fung, \"Reservoir\nCharacterization Using Support Vector Machines,\" in Proceedings of\nthe 2005 International Conference on Computational Intelligence for\nModelling, Control and Automation, vol. 2, November 2005, pp. 354-\n359.","G. Ou, Y. L. Murphey, and L. A. Feldkamp, \"Multiclass Pattern Classification\nUsing Neural Networks,\" in Proceeding of the 17th International\nConference on Pattern Recognition (ICPR), 2004, pp. 585-588.","H. Wang, D. Madiraju, Y.-Q. Zhang, and R. Sunderraman, \"Interval\nneutrosophic sets,\" International Journal of Applied Mathematics and\nStatistics, vol. 3, pp. 1-18, March 2005.\n[10] R. Erenshteyn, P. Laskov, D. M. Saxe, and R. A. Foulds, \"Distributed\nOutput Encoding for Multi-Class Pattern Recognition,\" in Proceeding\nof the 10th International Conference on Image Analysis and Processing\n(ICIAP), 1999, pp. 229-234.\n[11] T. G. Dietterich and G. Bakiri, \"Solving Multiclass Learning Problems\nvia Error-Correcting Output Codes,\" Journal of Artificial Intelligence\nResearch, vol. 2, pp. 263-286, 1995.\n[12] K. Crammer and Y. Singer, \"On the Learnability and Design of Output\nCodes for Multiclass Problems,\" Machine Learning, vol. 47, no. 2-3,\npp. 201-233, 2002.\n[13] P. Kraipeerapun, C. C. Fung, and W. Brown, \"Assessment of Uncertainty\nin Mineral Prospectivity Prediction Using Interval Neutrosophic\nSet,\" in Proceedings of the International Conference on Computational\nIntelligence and Security, ser. Lecture Notes in Artificial Intelligence,\nno. 3802. Xi-an, China: Springer Verlag, 2005, pp. 1074-1079.\n[14] P. Kraipeerapun, C. C. Fung, W. Brown, and K. W. Wong, \"Mineral\nProspectivity Prediction using Interval Neutrosophic Sets,\" in IASTED\nInternational Conference on Artificial Intelligence and Applications,\nInnsbruck, Austria, February 2006, pp. 235-239.\n[15] H. Wang, F. Smarandache, Y.-Q. Zhang, and R. Sunderraman, Interval\nNeutrosophic Sets and Logic: Theory and Applications in Computing,\nser. Neutrosophic Book Series, No.5. http://arxiv.org/abs/cs/0505014,\nMay 2005."]}

The evaluation of conversational agents or chatterbots question answering systems is a major research area that needs much attention. Before the rise of domain-oriented conversational agents based on natural language understanding and reasoning, evaluation is never a problem as information retrieval-based metrics are readily available for use. However, when chatterbots began to become more domain specific, evaluation becomes a real issue. This is especially true when understanding and reasoning is required to cater for a wider variety of questions and at the same time to achieve high quality responses. This paper discusses the inappropriateness of the existing measures for response quality evaluation and the call for new standard measures and related considerations are brought forward. As a short-term solution for evaluating response quality of conversational agents, and to demonstrate the challenges in evaluating systems of different nature, this research proposes a blackbox approach using observation, classification scheme and a scoring mechanism to assess and rank three example systems, AnswerBus, START and AINI., {"references":["J. Lin, V. Sinha, B. Katz, K. Bakshi, D. Quan, D. Huynh, and D. Karger,\n\"What Makes a Good Answer? The Role of Context in Question\nAnswering,\" presented at.the 9th International Conference on Human-\nComputer Interaction, 2003.","L. Hirschman and R. Gaizauskas., \"Natural Language Question\nAnswering: The View from Here,\" Natural Language Engineering, vol.\n7, pp. 275-300, 2001.","U. Hermjakob, \"Parsing and Question Classification for Question\nAnswering,\" presented at the ACL Workshop on Open-Domain\nQuestion Answering, 2001.","Z. Zheng, \"Developing a Web-based Question Answering System,\"\npresented at.the 11th International Conference on World Wide Web,\n2002a.","C. Kwok, D. Weld, and O. Etzioni, \"Scaling Question Answering to the\nWeb,\" ACM Transactions on Information Systems, vol. 19, pp. 242-262,\n2001.","P. Zweigenbaum, \"Question Answering in Biomedicine,\" presented at\nthe 10th Conference of the European Chapter of the Association for\nComputational Linguistics, 2003.","H. Chung, K. Han, H. Rim, S. Kim, J. Lee, Y. Song, and D.Yoon, \"A\nPractical QA System in Restricted Domains,\" presented at the ACL\nWorkshop on Question Answering in Restricted Domains, 2004.","F. Benamara, \"Cooperative Question Answering in Restricted Domains:\nthe WEBCOOP Experiment,\" presented at the ACL Workshop on\nQuestion Answering in Restricted Domains, 2004.","F. Benamara and P. Saint-Dizier, \"Advanced Relaxation for Cooperative\nQuestion Answering,\" in.New Directions in Question Answering: MIT\nPress, 2004.\n[10] W. Wong, O. S. Goh, M. I. Desa, and S. Sahib, \"Online Cyberlaw\nKnowledge Base Construction Using Semantic Network,\" presented at\nInternational Conference on Computational Intelligence for Modelling,\nControl and Automation, Rhodes, Greece, 2004.\n[11] O. S. Goh, C. C. Fung, and M. P. Lee, \"Intelligent Agents for an\nInternet-based Global Crisis Communication System,\" Journal of\nTechnology Management and Entrepreneurship, vol. 2, pp. 65-78, 2005.\n[12] B. Katz and J. Lin, \"START and Beyond.,\" presented at the 6th World\nMulticonference Systemics, Cybernetics and Informatics, 2002.\n[13] B. Katz, \"Annotating the World Wide Web using Natural Language,\"\npresented at the 5th Conference on Computer Assisted Information\nSearching on the Internet., 1997.\n[14] D. Moldovan, M. Pasca, M. Surdeanu, and S. Harabagiu., \"Performance\nIssues and Error Analysis in an Open-Domain Question Answering\nSystem,\" presented at the 40th Annual Meeting of the Association for\nComputational Linguistics, 2002.\n[15] J. Allen, D. Byron, M. Dzikovska, G. Ferguson, L. Galescu, and A.\nStent, \"Towards conversational human-computer interaction,\" AI\nMagazine, vol. 22, 2001.\n[16] J. Cassell, \"Embodied Conversation: Integrating Face and Gesture into\nAutomatic Spoken Dialogue Systems,\" in Spoken Dialogue Systems,\nLuperfoy, Ed.: MIT Press, to appear.\n[17] R. J. Lempert, S. W. Popper, and S. C. Bankes, Shaping the next one\nhundred years: new methods for quantitative, long-term policy analysis.\nSanta Monica, CA.: RAND, 2003.\n[18] O. S. Goh and C. C. Fung, \"Automated Knowledge Extraction from\nInternet for a Crisis Communication Portal,\" in First International\nConference on Natural Computation. Changsha, China: Lecture Notes in\nComputer Science (LNCS), 2005, pp. 1226-1235.\n[19] J. A. Fodor, Elm and the Expert: An Introduction to Mentalese and Its\nSemantics: Cambridge University Press, 1994.\n[20] R. A. Brooks, \"The Cog Project: Building a Humanoid Robot,\"\npresented at The 1st International Conference on Humanoid Robots and\nHuman friendly Robots, Tsukuba, Japan, 1998.\n[21] O. S. Goh, A. Depickere, C. C. Fung, and K. W. Wong, \"Top-down\nNatural Language Query Approach for Embodied Conversational\nAgent,\" presented at the International MultiConference of Engineers and\nComputer Scientists 2006, Hong Kong, 2006.\n[22] M. King, \"Evaluating Natural Language Processing Systems,\"\nCommunications of the ACM., vol. 39, pp. 73-79, 1996.\n[23] E. Voorhees, \"Overview of TREC 2003,\" presented at the 12th Text\nRetrieval Conference, 2003.\n[24] J. Facemire, \"A Proposed Metric for the Evaluation of Natural Language\nSystems,\" presented at the IEEE Energy and Information Technologies\nin the Southeast,, 1989.\n[25] G. Guida and G. Mauri, \"A Formal Basis for Performance Evaluation of\nNatural Language Understanding Systems.,\" Computational Linguistics.,\nvol. 10, pp. 15-30, 1984.\n[26] A. Srivastava and V. Rajaraman, \"A Vector Measure for the Intelligence\nof a Question-Answering (Q-A) System,\" IEEE Transactions on\nSystems: Man and Cybernetics., vol. 25, pp. 814-823, 1995.\n[27] J. Allen, Natural Language Understanding: Benjamin/Cummins\nPublishing, 1995.\n[28] E. Nyberg and T. Mitamura, \"Evaluating QA Systems on Multiple\nDimensions,\" presented at the Workshop on QA Strategy and Resources,\n2002.\n[29] A. Diekema, O. Yilmazel, and E. Liddy., \"Evaluation of Restricted\nDomain Question-Answering Systems,\" presented at the ACL Workshop\non Question Answering in Restricted Domains, 2004.\n[30] M. Maybury, \"Toward a Question Answering Roadmap,\" presented at\nthe AAAI Spring Symposium on New Directions in Question\nAnswering, 2003.\n[31] Z. Zheng, \"AnswerBus Question Answering System,\" presented at the\nConference on Human Language Technology, 2002b.\n[32] B. Katz, S. Felshin, and J. Lin, \"The START Multimedia Information\nSystem: Current Technology and Future Directions,\" presented at the\nInternational Workshop on Multimedia Information Systems, 2002."]}

In this paper, we proposed a new framework to incorporate an intelligent agent software robot into a crisis communication portal (CCNet) in order to send alert news to subscribed users via email and other mobile services such as Short Message Service (SMS), Multimedia Messaging Service (MMS) and General Packet Radio Services (GPRS). The content on the mobile services can be delivered either through mobile phone or Personal Digital Assistance (PDA). This research has shown that with our proposed framework, the embodied conversation agents system can handle questions intelligently with our multilayer architecture. At the same time, the extended framework can take care of delivery content through a more humanoid interface on mobile devices., {"references":["L. Palen, M. Salzman, and E. Youngs, \"Going wireless: behavior &\npractice of new mobile phone users,\" presented at the 2000 ACM\nconference on Computer Supported Cooperative Work, Philadelphia,\n2000.","J. Rickel and W. L. Johnson, \"Animated agents for procedural training\nin virtual reality: Perception, cognition and motor control.,\" Applied\nArtificial Intelligence Journal, vol. 13, pp. 343-382, 1998.","J. Cassell, J. Sullivan, S. Prevost, and E. Churchill, Embodied\nConversational Agents. Cambridge, MA: MIT Press, 2000.","C. M. Karat, J. Vergo, and D. Nahamoo, \"Conversational interface\ntechnologies,\" in The Human-Computer Interaction Handbook:\nFundamentals, Evolving Technologies and Emerging Applications, J.\nJacko and A. Sears, Eds. Mahwah, NJ: Lawrence Erlbaum Assoc., 2003,\npp. 169-186.","J. Lai and N. Yanlelovich, \"Conversational speech interfaces,\" in The\nHuman-Computer Interaction Handbook: Fundamentals, Evolving\nTechnologies and Emerging Applications, J. Jacko and A. Sears, Eds.\nMahwah, NJ: Lawrence Erlbaum Assoc, 2003, pp. 698-713.","S. L. Oviatt, C. Darves, and R. Coulston, \"Toward Adaptive\nConversational Interfaces: Modelling Speech Convergence with\nAnimated Personas,\" ACM Transactions on Computer-Human\nInteraction (TOCHI), vol. 11, September 2004.","J. Weizenbaum, \"ELIZA - A computer program for the study of natural\nlanguage communication between man and machine,\" Communications\nof the ACM, vol. 9, pp. 36-45, 1966.","Alice, (2005),Artificial Linguistic Internet Computer Entity, (Online).\nAvailable: http://www.alicebot.org","B. Alfonsi, \"\"Sassy\" Chatbot Wins with Wit,\" in IEEE Intelligent\nSystems, 2006, pp. 6-7.\n[10] J. Hutchens and M. D. Alder, \"Introducing MegaHAL,\" presented at The\nHuman-Computer Communication Workshop, 1998.\n[11] Turing Test, (2005),Loebner Prize, (Online). Available:\nhttp://www.loebner.net/Prizef/loebner-prize.html\n[12] O. S. Goh, C. C. Fung, and M. P. Lee, \"Intelligent Agents for an\nInternet-based Global Crisis Communication System,\" Journal of\nTechnology Management and Entrepreneurship, vol. 2, pp. 65-78, 2005.\n[13] O. S. Goh, C. Ardil, W. Wong, and C. C. Fung, \"A Black-box Approach\nfor Response Quality Evaluation Conversational Agent System,\"\nInternational Journal of Computational Intelligence, vol. 3, pp. 195-\n203, 2006.\n[14] O. S. Goh, C. C. Fung, A. Depickere, K. W. Wong, and W. Wilson,\n\"Domain Knowledge Model for Embodied Conversation Agent,\"\npresented at the 3rd International Conference on Computational\nIntelligence, Robotics and Autonomous Systems (CIRAS 2005),\nSingapore, 2005.\n[15] H. Loebner, (2003),Loebner Prize Gold Medal, (Online). Available:\nhttp://www.loebner.net/Prizef/loebner-prize.html\n[16] Kannel, (2005),Kannel: Open Source WAP and SMS gateway, (Online).\nAvailable: http://www.kannel.org/\n[17] O. S. Goh, A. Depickere, C. C. Fung, and K. W. Wong, \"Top-down\nNatural Language Query Approach for Embodied Conversational\nAgent,\" presented at the International MultiConference of Engineers and\nComputer Scientists, Hong Kong, 2006.\n[18] S. Brewster, \"Overcoming the Lack of Screen Spaces on Mobile\nComputers,\" vol. 6, pp. 188-205., 2002.\n[19] GSMWorld, (2006),3GSM Statistics, (Online). Available:\nhttp://www.gsmworld.com/technology/3g/statistics.shtml\n[20] Adobe, (2006),Mobile and Devices, (Online). Available:\nwww.macromedia.com/mobile/\n[21] D. Sleator and D. Temperley, \"Parsing English with a link grammar,\"\npresented at the 3rd International Workshop on Parsing Technologies,\nPrague, Czech Republic, 1993.\n[22] D. Lin, \"Dependency-based evaluation of MINIPAR,\" presented at the\n1st International Conference on Language Resources and Evaluation.,\nSpain, 1998.\n[23] M. Collins and Y. Singer, \"Unsupervised models for named entity\nclassification,\" presented at Joint SIGDAT Conference on Empirical\nMethods in NLP and Very Large Corpora, University of Maryland,\nUSA, 1999.\n[24] O. S. Goh, S. Sahib, and R. Elangsegaran, \"An Intelligent Virtual\nFinancial Advisor System (IVFAS),\" presented at 2nd International\nConference on Neural Network and Computational Intelligence (NCI\n2004), Zurich, Switzerland, 2004.\n[25] HighBeam, (2003),Software robot for PDAs, (Online). Available:\nhttp://www.highbeam.com/doc/1P1:84894246/Software+robot+for+PD\nAs.html\n[26] The American Association for Artificial Intelligence (AAAI), Natural\nLanguage Processing, AI software interactive robot gets recognition,\n(Online). http://www.aaai.org/AITopics/newstopics/nlp1.html\n[27] Microsoft, (2005),Microsoft Windows Mobile, (Online). Available:\nhttp://www.microsoft.com/windowsmobile/"]}