Proceedings, MSVSCC 2013

Proceedings of the 7th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 11, 2013 at VMASC in Suffolk, Virginia

Improving the Semantics of Conceptual-Modeling Grammars: A New Perspective on an Old Problem

A core activity in information systems development involves understanding the conceptual model of the domain that the information system supports. Any conceptual model is ultimately created using a conceptual-modeling (CM) grammar. Accordingly, just as high quality conceptual models facilitate high quality systems development, high quality CM grammars facilitate high quality conceptual modeling. This paper seeks to provide a new perspective on improving the quality of CM grammar semantics. For the past twenty years, the leading approach to this topic has drawn on ontological theory. However, the ontological approach captures just half of the story. It needs to be coupled with a logical approach. We show how ontological quality and logical quality interrelate and we outline three contributions of a logical approach: the ability to see familiar conceptual-modeling problems in simpler ways, the illumination of new problems, and the ability to prove the benefit of modifying CM grammars

Proceedings, MSVSCC 2014

Proceedings of the 8th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 17, 2014 at VMASC in Suffolk, Virginia

Representing Things and Properties in Conceptual Modeling: Understanding the Impact of Task Type

The representation of things and properties is a fundamental issue in conceptual modeling. The proponents of different modeling approaches, for example entity relationship modeling and object-role modeling, offer very different advice about the distinction between things and properties and their representation. We use ontological theory to provide guidelines about how things and properties should be represented. Previous experimental work has provided evidence to support the use of ontologically sound representations of things and properties in conceptual modeling. However the results also indicate that the type of task undertaken (for example comprehension, problem solving, discrepancy checking, and decomposition) may also impact the use of conceptual models. In this paper, a research project is proposed to examine the sorts of tasks that are best supported by distinguishing between things and properties in conceptual modeling

24th International Conference on Information Modelling and Knowledge Bases

In the last three decades information modelling and knowledge bases have become essentially important subjects not only in academic communities related to information systems and computer science but also in the business area where information technology is applied. The series of European – Japanese Conference on Information Modelling and Knowledge Bases (EJC) originally started as a co-operation initiative between Japan and Finland in 1982. The practical operations were then organised by professor Ohsuga in Japan and professors Hannu Kangassalo and Hannu Jaakkola in Finland (Nordic countries). Geographical scope has expanded to cover Europe and also other countries. Workshop characteristic - discussion, enough time for presentations and limited number of participants (50) / papers (30) - is typical for the conference. Suggested topics include, but are not limited to: 1. Conceptual modelling: Modelling and specification languages; Domain-specific conceptual modelling; Concepts, concept theories and ontologies; Conceptual modelling of large and heterogeneous systems; Conceptual modelling of spatial, temporal and biological data; Methods for developing, validating and communicating conceptual models. 2. Knowledge and information modelling and discovery: Knowledge discovery, knowledge representation and knowledge management; Advanced data mining and analysis methods; Conceptions of knowledge and information; Modelling information requirements; Intelligent information systems; Information recognition and information modelling. 3. Linguistic modelling: Models of HCI; Information delivery to users; Intelligent informal querying; Linguistic foundation of information and knowledge; Fuzzy linguistic models; Philosophical and linguistic foundations of conceptual models. 4. Cross-cultural communication and social computing: Cross-cultural support systems; Integration, evolution and migration of systems; Collaborative societies; Multicultural web-based software systems; Intercultural collaboration and support systems; Social computing, behavioral modeling and prediction. 5. Environmental modelling and engineering: Environmental information systems (architecture); Spatial, temporal and observational information systems; Large-scale environmental systems; Collaborative knowledge base systems; Agent concepts and conceptualisation; Hazard prediction, prevention and steering systems. 6. Multimedia data modelling and systems: Modelling multimedia information and knowledge; Contentbased multimedia data management; Content-based multimedia retrieval; Privacy and context enhancing technologies; Semantics and pragmatics of multimedia data; Metadata for multimedia information systems. Overall we received 56 submissions. After careful evaluation, 16 papers have been selected as long paper, 17 papers as short papers, 5 papers as position papers, and 3 papers for presentation of perspective challenges. We thank all colleagues for their support of this issue of the EJC conference, especially the program committee, the organising committee, and the programme coordination team. The long and the short papers presented in the conference are revised after the conference and published in the Series of “Frontiers in Artificial Intelligence” by IOS Press (Amsterdam). The books “Information Modelling and Knowledge Bases” are edited by the Editing Committee of the conference. We believe that the conference will be productive and fruitful in the advance of research and application of information modelling and knowledge bases. Bernhard Thalheim Hannu Jaakkola Yasushi Kiyok

Mars Science Helicopter Conceptual Design

Robotic planetary aerial vehicles increase the range of terrain that can be examined, compared to traditional landers and rovers, and have more near-surface capability than orbiters. Aerial mobility is a promising possibility for planetary exploration as it reduces the challenges that difficult obstacles pose to ground vehicles. The first use of a rotorcraft for a planetary mission will be in 2021, when the Mars Helicopter technology demonstrator will be deployed from the Mars 2020 rover. The Jet Propulsion Laboratory and NASA Ames Research Center are exploring possibilities for a Mars Science Helicopter, a second-generation Mars rotorcraft with the capability of conducting science investigations independently of a lander or rover (although this type of vehicle could also be used assist rovers or landers in future missions). This report describes the conceptual design of Mars Science Helicopters. The design process began with coaxial-helicopter and hexacopter configurations, with a payload in the range of two to three kilograms and an overall vehicle mass of approximately twenty kilograms. Initial estimates of weight and performance were based on the capabilities of the Mars Helicopter. Rotorcraft designs for Mars are constrained by the dimensions of the aeroshell for the trip to the planet, requiring attention to the aircraft packaging in order to maximize the rotor dimensions and hence overall performance potential. Aerodynamic performance optimization was conducted, particularly through airfoils designed specifically for the low Reynolds number and high Mach number inherent in operation on Mars. The final designs show a substantial capability for science operations on Mars: a 31 kg hexacopter that fits within a 2.5 m diameter aeroshell could carry a 5 kg payload for 10 min of hover time or over a range of 5 km

Emerging infectious diseases

Emerging Infectious Diseases is providing access to these abstracts on behalf of the ICEID 2012 program committee (www.iceid.org), which performed peer review. Emerging Infectious Diseases has not edited or proofread these materials and is not responsible for inaccuracies or omissions. All information is subject to change. Comments and corrections should be brought to the attention of the authors.Influenza preparedness: lessons learned -- Policy implications and infectious diseases -- Improving preparedness for infectious diseases -- New or rapid diagnostics -- Foodborne and waterborne infections -- Effective and sustainable surveillance platforms -- Healthcare-associated infections -- Molecular epidemiology -- Antimicrobial resistance -- Tropical infections and parasitic diseases -- H1N1 influenza -- Risk Assessment -- Laboratory Support -- Zoonotic and Animal Diseases -- Viral Hepatitis -- E1. Zoonotic and animal diseases -- E2. Vaccine issues -- E3. H1N1 influenza -- E4. Novel surveillance systems -- E5. Antimicrobial resistance -- E6. Late-breakers I -- Antimicrobial resistance -- Influenza preparedness: lessons learned -- Zoonotic and animal diseases -- Improving preparedness for infectious diseases -- Laboratory support -- Early warning systems -- H1N1 influenza -- Policy implications and infectious diseases -- Modeling -- Molecular epidemiology -- Novel surveillance systems -- Tropical infections and parasitic diseases -- Strengthening public health systems -- Immigrant and refugee health -- Foodborne and waterborne infections -- Healthcare-associated infections -- Foodborne and waterborne infections -- New or rapid diagnostics -- Improving global health equity for infectious diseases -- Vulnerable populations -- Novel agents of public health importance -- Influenza preparedness: lessons learned -- Molecular epidemiology -- Zoonotic and animal diseases -- Vaccine-preventable diseases -- Outbreak investigation: lab and epi response -- H1N1 influenza -- laboratory support -- effective and sustainable surveillance platforms -- new vaccines -- vector-borne diseases and climate change -- travelers' health -- J1. Vectorborne diseases and climate change -- J2. Policy implications and infectious diseases -- J3. Influenza preparedness: lessons learned -- J4. Effective and sustainable surveillance platforms -- J5. Outbreak investigation: lab and epi response I -- J6. Late-breakers II -- Strengthening public health systems -- Bacterial/viral coinfections -- H1N1 influenza -- Novel agents of public health importance -- Foodborne and waterborne infections -- New challenges for old vaccines -- Vectorborne diseases and climate change -- Novel surveillance systems -- Geographic information systems (GIS) -- Improving global health equity for infectious diseases -- Vaccine preventable diseases -- Vulnerable populations -- Laboratory support -- Prevention challenges for respiratory diseases -- Zoonotic and animal diseases -- Outbreak investigation: lab and epi response -- Vectorborne diseases and climate change -- Outbreak investigation: lab and epi response -- Laboratory proficiency testing/quality assurance -- Effective and sustainable surveillance platforms -- Sexually transmitted diseases -- H1N1 influenza -- Surveillance of vaccine-preventable diseases -- Foodborne and waterborne infections -- Role of health communication -- Emerging opportunistic infections -- Host and microbial genetics -- Respiratory infections in special populations -- Zoonotic and animal diseases -- Laboratory support -- Antimicrobial resistance -- Vulnerable populations -- Global vaccine initiatives -- Tuberculosis -- Prevention challenges for respiratory diseases -- Infectious causes of chronic diseases -- O1. Outbreak investigation: lab and epi response II -- O2. Prevention challenges for respiratory diseases -- O3. Populations at high risk for infectious diseases -- O4. Foodborne and waterborne infections -- O5. Laboratory support: surveillance and monitoring infections -- O6. Late-breakers IIIAbstracts published in advance of the conference

Supporting Electronic Collaboration in Conceptual Modeling

We study collaborative modeling by analyzing conversations and loud thinking during modeling sessions and the resulting models themselves. We identify the basic activities of the modeling teams on the social, pragmatic, semantic and syntactic levels and derive a schema for the pragmatic level. Our main conclusion is that team-based modeling is largely a negotiation process. Drawing on these results we derive an architecture of a system that supports the distributed development of conceptual models

Proceedings, MSVSCC 2016

Proceedings of the 10th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 14, 2016 at VMASC in Suffolk, Virginia