The purpose of this project is to develop a statistical method for use in rapid detection of biological agents using portable gas chromatography mass spectrometry (GC/MS) devices. Of particular interest is 2,6-pyridinedicarboxylic acid (dipicolinic acid, or DPA), a molecule that is present at high concentrations in spores of Clostridium and Bacillus, the latter of which includes the threat organism Bacillus anthracis, or anthrax. Dipicolinic acid may be useful as a first-step discriminator of the biological warfare agent B. anthracis. The results of experiments with B. anthracis Sterne strain and Bacillus thuringiensis spores lead to a conceptual model for the chemical phenomena that are believed to occur between Calcium, DPA and its esters, water, acid, and alkali during treatment of spores by a novel analytical procedure. The hypothesized model for chemical phenomena is tested using a compound study in the form of a mixture experiment.

Malware is a fast growing threat that consists of a malicious script or piece of software that is used to disrupt the integrity of a user's experience. Antivirus software can help protect a user against these threats and there are numerous vendors users can choose from for their antivirus protection. However, each vendor has their own set of virus definitions varying in resources and capabilities in recognizing new threats. Currently, a persistent system is not in place that measures and displays data on the performance of antivirus vendors in responding to new malware over a continuous period of time. There is a need for a system that can evaluate antivirus performance in order to better inform end users of their security options, in addition to informing clients of prevalent threats occurring in their network. This project is dedicated to assessing the viability of a cloud sourced malware reporting framework that uses distributed agents to evaluate the performance of antivirus software based on malware signatures.

Hurricane Sandy hit New York City on October 29, 2012 and greatly disrupted transportation systems, power systems, work, and schools. This research used survey data from 397 respondents in the NYC Metropolitan Area to develop an agent-based model for capturing commuter behavior and adaptation after the disruption. Six different recovery scenarios were tested to find which systems are more critical to recover first to promote a faster return to productivity. Important factors in the restoration timelines depends on the normal commuting pattern of people in that area. In the NYC Metropolitan Area, transit is one of the common modes of transportation; therefore, it was found that the subway/rail system recovery is the top factor in returning to productivity. When the subway/rail system recovers earlier (with the associated power), more people are able to travel to work and be productive. The second important factor is school and daycare closure (with the associated power and water systems). Parents cannot travel unless they can find a caregiver for their children, even if the transportation system is functional. Therefore, policy makers should consider daycare and school condition as one of the important factors in recovery planning. The next most effective scenario is power restoration. Telework is a good substitute for the physical movement of people to work. By teleworking, people are productive while they skip using the disrupted transportation system. To telework, people need power and communication systems. Therefore, accelerating power restoration and encouraging companies to let their employees' telework can promote a faster return to productivity. Finally, the restoration of major crossings like bridges and tunnels is effective in the recovery process. / Master of Science / Natural and man-made disasters, cause massive destruction of property annually and disrupt the normal economic productivity of an area. Although the occurrence of these disasters cannot be controlled, society can minimize the effects with post-disaster recovery strategies. Hurricane Sandy hit New York City on October 29, 2012 and greatly disrupted transportation systems, power systems, work, and schools. In this research, commuter behavior and adaptation after the hurricane were captured by using a survey data that asked questions from people living in NYC metropolitan area about their commuting behavior before and after Hurricane Sandy. An agent-based model was developed and six different recovery strategies were tested in order to find effective factors in returning people to normal productive life faster. In the NYC Metropolitan Area, transit is one of the common modes of transportation; therefore, it was found that the subway/rail system recovery is the top factor in returning to productivity. The next important factor is school and daycare closure. Parents are responsible for their children, therefore; they may not travel to work when school and daycares are closed. The third important factor is power restoration. To telework, people need power and communication systems. By teleworking, people are productive while they skip using the disrupted transportation system. The final important factor is the restoration of major crossings like bridges and tunnels.

No / This intention of this chapter is to critically examine uses of the World Wide Web by fans of cult movies. It begins by outlining how cult movies are categorised, and notes the problems that this engenders. Then the relationship between technologies and subcultural practices is observed. Examples are presented to illustrate the question of whether, through remediation processes, such practices tell us anything new about forms of contemporary communication and consumption.

Yes / Modern manufacturing companies face increased pressures to adapt to shorter product life cycles and the need to reconfigure more frequently their production systems to offer new product variants. This paper proposes a new multi-agent architecture utilising “plug and produce” principles for configuration and reconfiguration of production systems with minimum human intervention. A new decision-making approach for system reconfiguration based on tasks re-allocation is presented using goal driven methods. The application of the proposed architecture is described with a number of architectural views and its deployment is illustrated using a validation scenario implemented on an industrial assembly platform. The proposed methodology provides an innovative application of a multi-agent control environment and architecture with the objective of significantly reducing the time for deployment and ramp-up of small footprint assembly systems. / The reported research has been part of the EU FP7 research project “PRIME”

The growing popularity of multi-agent based approaches towards the formation and operation of virtual organizations (VO) present over the Internet, offer both opportunities and risks. One of the risks involved in such community is in the identification of trustworthy agent partners for transaction. In this paper we aim to describe our trust model which would contribute in measuring trust in the interacting agents. Named as TruMet, the trust metric model works on the basis of the parameters that we have identified as relevant to the features of the community. The model primarily analyses trust value on the basis of the agent¿s reputation, as provided by the agent itself, and the agent¿s aggregate rating as provided by the witness agents. The final computation of the trust value is given by a weighted average of these two components. While computing the aggregate rating, a weight based method has been adopted to discount the contribution of possibly un-fair ratings by the witness agents.

No description available.

While progress has been made in querying digital information contained in XML and HTML documents, success in retrieving information from the so called "hidden Web" (data behind Web forms) has been modest. There has been a nascent trend of developing autonomous tools for extracting information from the hidden Web. Automatic tools for ontology generation, wrapper generation, Weborm querying, response gathering, etc., have been reported in recent research. This thesis presents a system called Chameleon for automatic querying of and response gathering from the hidden Web. The approach to response gathering is based on automatic table structure identification, since most information repositories of the hidden Web are structured databases, and so the information returned in response to a query will have regularities. Information extraction from the identified record structures is performed based on domain knowledge corresponding to the domain specified in a query. So called "domain plug-ins" are used to make the dynamically generated wrappers domain-specific, rather than conventionally used document-specific.

Kidney transplantation is an effective treatment for renal disease that was previously fatal. However, the demand for donor kidneys far exceeds the supply. Due to the scarcity of volunteer donors, the cadaver organs that are retrieved must be optimally utilized. By expanding organ retrieval and sharing pools and improving donor-patient matching algorithms, the utilization of donated organs is enhanced and encouraging medical results are obtained. However, the benefits of enlarged donor and recipient pools may be offset by increasing complexity and decreasing efficiency in the organ distribution process thus increasing cold ischemia time. It is critical to improve distribution process efficiency in order to minimize the time taken to complete the entire process, and thus further enhance patient and graft survival. I attempt to apply supply chain management concepts, agent technologies, mobile communication technologies and decision-making theory to improve the efficiency of the cadaver kidney distribution process. In this thesis I analyze what are the bottlenecks in current cadaver kidney distribution and investigate how agent technology can be applied to improve this process. I propose a distributed multi-agent system operating in a mobile and wireless communication environment to assist transplant coordinators in coordinating with multi-parties in this time-critical distribution process. A prototype system has been developed to help transplanting coordinators in allocating the kidney recipient. / Thesis / Master of Science (MS)

The paper examines a continuous-time principal-agent model in which agent’s preference exhibits habit formation over consumption. As agent’s concern over the standard of living strengthens, his continuation utility is less sensitive to current wealth but more sensitive to the standard of living, leading to lower demand for risk-sharing compensation. The optimal contract has lower pay-for-performance but incentivizes agent’s higher effort. In the Leland (1994) capital structure model, agent’s habit formation preference combined with the optimal contract lowers firm’s leverage and mitigates the debt-overhang problem. / 2025-05-28T00:00:00Z