Service Descriptions and Linked Data for Integrating WSNs into Enterprise IT

This paper presents our ongoing work on enterprise IT integration of sensor networks based on the idea of service descriptions and applying linked data principles to them. We argue that using linked service descriptions facilitates a better integration of sensor nodes into enterprise IT systems and allows SOA principles to be used within the enterprise IT and within the sensor network itself.

Inaugural Conference of The Mosakowski Institute for Public Enterprise- Program

Program for University Research and the American Agenda: Discovering Knowledge, Enabling Leadership. The Inaugural Conference of the Mosakowski Institute for Public Enterprise.

A unified approach to modeling multivariate binary data using copulas over partitions

Many seemingly disparate approaches for marginal modeling have been developed in recent years. We demonstrate that many current approaches for marginal modeling of correlated binary outcomes produce likelihoods that are equivalent to the proposed copula-based models herein. These general copula models of underlying latent threshold random variables yield likelihood based models for marginal fixed effects estimation and interpretation in the analysis of correlated binary data. Moreover, we propose a nomenclature and set of model relationships that substantially elucidates the complex area of marginalized models for binary data. A diverse collection of didactic mathematical and numerical examples are given to illustrate concepts.

Connectionism as metaphor: Towards an integrated, unified conception of self-system and individual difference

Comments on an article by Kashima et al. (see record 2007-10111-001). In their target article Kashima and colleagues try to show how a connectionist model conceptualization of the self is best suited to capture the self's temporal and socio-culturally contextualized nature. They propose a new model and to support this model, the authors conduct computer simulations of psychological phenomena whose importance for the self has long been clear, even if not formally modeled, such as imitation, and learning of sequence and narrative. As explicated when we advocated connectionist models as a metaphor for self in Mischel and Morf (2003), we fully endorse the utility of such a metaphor, as these models have some of the processing characteristics necessary for capturing key aspects and functions of a dynamic cognitive-affective self-system. As elaborated in that chapter, we see as their principal strength that connectionist models can take account of multiple simultaneous processes without invoking a single central control. All outputs reflect a distributed pattern of activation across a large number of simple processing units, the nature of which depends on (and changes with) the connection weights between the links and the satisfaction of mutual constraints across these links (Rummelhart & McClelland, 1986). This allows a simple account for why certain input features will at times predominate, while others take over on other occasions. (PsycINFO Database Record (c) 2008 APA, all rights reserved)

The Influence of Enterprise Systems on Business and Information Technology

Business strategy is important to all organizations. Nearly all Fortune 500 firms are implementing Enterprise Resource Planning (ERP) systems to improve the execution of their business strategy and to improve integration with its information technology (IT) strategy. Successful implementation of these multi-million dollar software systems are requiring new emphasis on change management and on Business and IT strategic alignment. This paper examines business and IT strategic alignment and seeks to explore whether an ERP implementation can drive business process reengineering and business and IT strategic alignment. An overview of business strategy and strategic alignment are followed by an analysis of ERP. The “As-Is/To-Be” process model is then presented and explained as a simple, but vital tool for improving business strategy, strategic alignment, and ERP implementation success.

Enabling the evolution of J2EE applications through reverse engineering and quality assurance

Enterprise Applications are complex software systems that manipulate much persistent data and interact with the user through a vast and complex user interface. In particular applications written for the Java 2 Platform, Enterprise Edition (J2EE) are composed using various technologies such as Enterprise Java Beans (EJB) or Java Server Pages (JSP) that in turn rely on languages other than Java, such as XML or SQL. In this heterogeneous context applying existing reverse engineering and quality assurance techniques developed for object-oriented systems is not enough. Because those techniques have been created to measure quality or provide information about one aspect of J2EE applications, they cannot properly measure the quality of the entire system. We intend to devise techniques and metrics to measure quality in J2EE applications considering all their aspects and to aid their evolution. Using software visualization we also intend to inspect to structure of J2EE applications and all other aspects that can be investigate through this technique. In order to do that we also need to create a unified meta-model including all elements composing a J2EE application.

Driving the refactoring of Java Enterprise applications by evaluating the distance between application elements

Java Enterprise Applications (JEAs) are complex systems composed using various technologies that in turn rely on languages other than Java, such as XML or SQL. Given the complexity of these applications, the need to reverse engineer them in order to support further development becomes critical. In this paper we show how it is possible to split a system into layers and how is possible to interpret the distance between application elements in order to support the refactoring of JEAs. The purpose of this paper is to explore ways to provide suggestions about the refactoring operations to perform on the code by evaluating the distance between layers and elements belonging those layers. We split JEAs into layers by considering the kinds and the purposes of the elements composing the application. We measure distance between elements by using the notion of the shortest path in a graph. Also we present how to enrich the interpretation of the distance value with enterprise pattern detection in order to refine the suggestion about modifications to perform on the code.

Enterprise Integration of Smart Objects using Semantic Service Descriptions

Integrating physical objects (smart objects) and enterprise IT systems is still a labor intensive, mainly manual task done by domain experts. On one hand, enterprise IT backend systems are based on service oriented architectures (SOA) and driven by business rule engines or business process execution engines. Smart objects on the other hand are often programmed at very low levels. In this paper we describe an approach that makes the integration of smart objects with such backends systems easier. We introduce semantic endpoint descriptions based on Linked USDL. Furthermore, we show how different communication patterns can be integrated into these endpoint descriptions. The strength of our endpoint descriptions is that they can be used to automatically create REST or SOAP endpoints for enterprise systems, even if which they are not able to talk to the smart objects directly. We evaluate our proposed solution with CoAP, UDP and 6LoWPAN, as we anticipate the industry converge towards these standards. Nonetheless, our approach also allows easy integration with backend systems, even if no standardized protocol is used.

Critical Control Points for Profitability in the Cow-Calf Enterprise

Financial, economic, and biological data collected from cow-calf producers who participated in the Illinois and Iowa Standardized Performance Analysis (SPA) programs were used in this study. Data used were collected for the 1996 through 1999 calendar years, with each herd within year representing one observation. This resulted in a final database of 225 observations (117 from Iowa and 108 from Illinois) from commercial herds with a range in size from 20 to 373 cows. Two analyses were conducted, one utilizing financial cost of production data, the other economic cost of production data. Each observation was analyzed as the difference from the mean for that given year. The independent variable utilized in both the financial and economic models as an indicator of profit was return to unpaid labor and management per cow (RLM). Used as dependent variables were the five factors that make up total annual cow cost: feed cost, operating cost, depreciation cost, capital charge, and hired labor, all on an annual cost per cow basis. In the economic analysis, family labor was also included. Production factors evaluated as dependent variables in both models were calf weight, calf price, cull weight, cull price, weaning percentage, and calving distribution. Herd size and investment were also analyzed. All financial factors analyzed were significantly correlated to RLM (P < .10) except cull weight, and cull price. All economic factors analyzed were significantly correlated to RLM (P < .10) except calf weight, cull weight and cull price. Results of the financial prediction equation indicate that there are eight measurements capable of explaining over 82 percent of the farm-to-farm variation in RLM. Feed cost is the overriding factor driving RLM in both the financial and economic stepwise regression analyses. In both analyses over 50 percent of the herd-to-herd variation in RLM could be explained by feed cost. Financial feed cost is correlated (P < .001) to operating cost, depreciation cost, and investment. Economic feed cost is correlated (P < .001) with investment and operating cost, as well as capital charge. Operating cost, depreciation, and capital charge were all negatively correlated (P < .10) to herd size, and positively correlated (P < .01) to feed cost in both analyses. Operating costs were positively correlated with capital charge and investment (P < .01) in both analyses. In the financial regression model, depreciation cost was the second critical factor explaining almost 9 percent of the herd-to-herd variation in RLM followed by operating cost (5 percent). Calf weight had a greater impact than calf price on RLM in both the financial and economic regression models. Calf weight was the fourth indicator of RLM in the financial model and was similar in magnitude to operating cost. Investment was not a significant variable in either regression model; however, it was highly correlated to a number of the significant cost variables including feed cost, depreciation cost, and operating cost (P < .001, financial; P < .10, economic). Cost factors were far more influential in driving RLM than production, reproduction, or producer controlled marketing factors. Of these cost factors, feed cost had by far the largest impact. As producers focus attention on factors that affect the profitability of the operation, feed cost is the most critical control point because it was responsible for over 50 percent of the herd-to-herd variation in profit.

Noisy kriging-based optimization methods: A unified implementation within the DiceOptim package

Kriging-based optimization relying on noisy evaluations of complex systems has recently motivated contributions from various research communities. Five strategies have been implemented in the DiceOptim package. The corresponding functions constitute a user-friendly tool for solving expensive noisy optimization problems in a sequential framework, while offering some flexibility for advanced users. Besides, the implementation is done in a unified environment, making this package a useful device for studying the relative performances of existing approaches depending on the experimental setup. An overview of the package structure and interface is provided, as well as a description of the strategies and some insight about the implementation challenges and the proposed solutions. The strategies are compared to some existing optimization packages on analytical test functions and show promising performances.