Recommended patrol routes can be used by organizations such as police agencies, emergency medical responders, and taxi services whose agents patrol roadway segments at proper times to assist or deter their target events. The creation of optimal complementary patrol routes for multiple agents targeting temporal event hotspots and minimizing travel distance is an NP-hard combinatorial problem that belongs to a class of problems known as the vehicle routing problem with time windows (VRPTW). Traffic safety patrol routing problems share many characteristics of VRPTW problems but differ in ways that prevent the application of existing solutions. In our approach, nondeterministic patrol routing algorithms are used to specify the movements of simulated mobile agents on a roadway system. Nondeterminism is critical in the traffic safety patrol routing domain, as rigidity and predictability can negatively impact the effectiveness of law enforcement agents' efforts.This paper addresses the problem of expressing, executing, evaluating, and engaging patrol routing algorithms that target event hotspots on roadways. The patrol algorithms are first expressed using Turn, which is our extensible domain-specific language (DSL) created for this purpose. Algorithms specified using Turn syntax are then executed in a custom simulation environment. Utilizing predefined metrics, users evaluate the resulting patrol routes to ensure that the criteria of interest in a given patrol context are met. Acceptable patrol routes are then engaged by end users via a web-based geographic information system (GIS) portal. To demonstrate the applicability and efficacy of our approach, we present two illustrative case studies.

Information technologies such as data mining and social network analysis have been widely used in law enforcement to solve crimes. Recent research indicates that geographic profiling also plays an important role in facilitating the investigation of crimes. However, lack of integration makes those systems less helpful in practice. In this paper, we propose an integrated system called PerpSearch that will take a given description of a crime, including its location, type, and the physical description of suspects (personal characteristics or vehicles) as input. To detect suspects, the system will process these inputs through four integrated components: geographic profiling, social network analysis, crime patterns, and physical matching. Essentially, geographic profiling determines ldquowhererdquo the suspects are, while other components determine ldquowhordquo the suspects are. We then process the results using a score engine to give investigators a ranked list of individuals. To date, we have implemented a prototype of the system based on current Alabama law enforcement data.

Commodity computing hardware continues to increase performance while decreasing price. This combination is driving a renewed interest in parallel and distributed computing. In this study, we examine the performance of an existing application in a ten-node computing cluster using commodity off-the-shelf components. The application is a statistical analysis software package that processes categorical data used by state public safety programs. The study examines various network topologies and focuses on minimizing the software modifications required to distribute the application. We conclude that parallel computing using commodity components is an effective mechanism to increase the performance of real-world applications especially when the underlying application architectures have the flexibility to support efficient reuse of the existing code. Copyright © 2005 John Wiley & Sons, Ltd.

At one time, commercial software applications were released as single binary executable files. Discussions of the notion of a "software component" were almost always limited to the context of source code. However, with the proliferation of numerous new technologies, applications are now more typically released as collections of cooperating binary components. While there is significant industrial emphasis on binary component technologies, computer science curricula have not yet standardized upon a corpus of fundamentally sound concepts to support education within this paradigm. In this paper, we describe our efforts to define a fundamental core set of concepts to support this important programming paradigm, as well as our efforts to integrate these concepts into a typical undergraduate computer science curriculum.

The field of component-based software engineering (CBSE) is currently in a period of rapid growth and change. No longer is the field dominated by discussions of traditional kinds of source-code components, but the predominant view encompasses so-called "binary" components: components that adhere to industry standards and are shipped as "plug-ins" into an existing run-time architecture. Computer science and software engineering curricula have not yet caught up with this transition in providing a corpus of fundamentally sound concepts to support education within this discipline. In this paper, we describe our efforts to develop fundamentals-driven CBSE educational materials, as well as our efforts to integrate these materials into a traditional undergraduate computer science curriculum.

This paper describes the development of a new software engineering curriculum at the University of Alabama. This curriculum is jointly administered by three separate academic programs: computer engineering, computer science and management information systems. These programs have combined to develop a unified software engineering track, consisting of an optional sequence of courses for majors in the three programs. Our software engineering track is characterized by two key elements: the use of software component engineering as a technical foundation, and the integration of students from the three participating programs into a single capstone laboratory. The capstone laboratory involves the development of a multifaceted product, requiring the interdisciplinary cooperation of all three groups of students to complete. This paper describes the design and conceptual foundations of this program, which has received funding from the National Science Foundation.

Komlós has devised a way to use a linear number of binary comparisons to test whether a given spanning tree of a graph with edge costs is a minimum spanning tree. The total computational work required by his method is much larger than linear, however. This paper describes a linear-time algorithm for verifying a minimum spanning tree. This algorithm combines the result of Komlós with a preprocessing and table look-up method for small subproblems and with a previously known almost-linear-time algorithm. Additionally, an optimal deterministic algorithm and a linear-time randomized algorithm for sensitivity analysis of minimum spanning trees are presented.