An adaptive, real-time, traffic monitoring system

In this paper we describe a computer vision-based traffic monitoring system able to detect individual vehicles in real-time. Our fully integrated system first obtains the main traffic variables: counting, speed and category; and then computes a complete set of statistical variables. The objective is to investigate some of the difficulties impeding existing traffic systems to achieve balanced accuracy in every condition; i.e. day and night transitions, shadows, heavy vehicles, occlusions, slow traffic and congestions. The system we present is autonomous, works for long periods of time without human intervention and adapts automatically to the changing environmental conditions. Several innovations, designed to deal with the above circumstances, are proposed in the paper: an integrated calibration and image rectification step, differentiated methods for day and night, an adaptive segmentation algorithm, a multistage shadow detection method and special considerations for heavy vehicle identification and treatment of slow traffic. A specific methodology has been developed to benchmark the accuracy of the different methods proposed.     

Adapting plans in progress in distributed supervisory work: aspects of complexity, coupling, and control

Distributed supervisory control systems often rely on complex and centralized plans to cope with a variety of unanticipated situations. Replanning requires practitioners to forgo standard procedures in favor of making simple plans without simplifying, managing task coupling, and anticipating team needs to provide decentralized and elaborate plans. This article proposes a plan classification scheme to study what features of plans facilitate or hinder adaptation and a framework to examine how features of plans influence the cognitive processes of replanning. The plan features have been assigned to the categories of plan complexity, coupling, and control. Plans are task networks sharing similar features of complexity and coupling to technical systems. The proposed framework sets out to explore how plan features influence the processes of recognizing plan disruptions, reviewing challenges and different team stances, repairing plans to resolve new risks, and reacting by coordinating team efforts to execute plans. The framework draws on the Extended Control Model (ECOM) to integrate the four processes of replanning into a set of control loops. The benefits of this framework are illustrated in the context of operator training and decision support.     

Impact of ZnO gate interfacial layer on piezoelectric response of AlGaN/GaN C-HEMT based ring gate capacitor

We report on a piezoelectric response investigation of AlGaN/GaN circular high electron mobility transistor (C-HEMT) based ring gate capacitor as a new stress sensor device to be potentially applied for dynamic high-pressure sensing. A ring gate capacitor of C-HEMT with an additional ZnO gate interfacial layer was used to measure the changes in the piezoelectric charge induced directly by the variation of piezoelectric polarization of both gate piezoelectric layers (AlGaN, ZnO) for harmonic loading at different excitation frequences. Our experimental results show that about 10 nm thick piezoelectric ZnO layer grown on ring gate/AlGaN interface of C-HEMT can yield almost a 60% increase in the piezoelectric detection sensitivity of the device due to its higher piezoelectric coefficient. A three-dimensional CoventorWare simulation is carried out to confirm the increase in the measured piezoelectric response of ZnO based ring gate capacitor of C-HEMT.     

Kritische Erfolgsfaktoren f��r die Gestaltung serviceorientierter Informationssysteme

Service orientation has been a major buzz-word in recent years. While the buzz is on a decline, organizations are slowly, but steadily moving towards service oriented designs. However, service orientation turns out to be as much of a managerial challenge as of a technical one. The most important complexity drivers in the service oriented design of information systems seem to be (a) inconsistent design goals of stakeholders and (b) the pursuit of exhaustive service orientation coverage. This research focuses on the following two questions: (1) What are the characteristics of successful implementations of service oriented information systems, and (2) what are the critical success factors influencing, driving and/or determining these characteristics? Data of an empirical analysis is used to test a set of cause-effect relationship hypotheses based on nine latent variables. In the core of this model we differentiate the variables ??overall service orientation infrastructure success?? and ??service orientation project success??. The hypothesized interrelationships between the nine variables lead to a causal model which is proven to hold.     

Requirements Engineering f��r Product Service Systems

In recent years, manufacturing companies and service providers have moved towards offering customer-specific problem solutions. These integrated bundles usually consist of hardware, software, and service components and are called product service systems (PSS) or hybrid products. Since the success of the resulting solution depends on the understanding of all requirements, requirements engineering (RE) has become a key factor. The article analyzes the state of the art of RE for PSS based on an extensive literature review in the domains of product-, software-, and service engineering. For this, criteria are derived from the characteristics of PSS and from the task area of RE in the life cycle of PSS. Based on these criteria we analyze the most established RE approaches for their suitability for PSS. An important finding is that integrated/interdisciplinary approaches for RE are missing. Moreover, the maturity of RE approaches in the three domains varies significantly. All analyzed approaches heavily rely on concepts and solution characteristics of their own domain so that a transfer to other domains is hardly possible. This literature review lays the foundation for successful RE for PSS and especially for future research aiming at combining and integrating RE approaches and models of product-, software-, and service engineering. Such requirement models could connect concepts of single domains and enable an integrated and seamless RE for PSS.     

A generalized multiple layer data envelopment analysis model for hierarchical structure assessment: A case study in road safety performance evaluation

Data envelopment analysis (DEA) is a powerful analytical research tool for measuring the relative efficiency of a homogeneous set of decision making units (DMUs) by obtaining empirical estimates of relations between multiple inputs and multiple outputs related to the DMUs. To further embody multilayer hierarchical structures of these inputs and outputs in the DEA framework, which are prevalent in today’s performance evaluation activities, we propose a generalized multiple layer DEA (MLDEA) model. Starting from the input-oriented CCR model, we elaborate the mathematical deduction process of the MLDEA model, formulate the weights in each layer of the hierarchy, and indicate different types of possible weight restrictions. Meanwhile, its linear transformation is realized and further extended to the BCC form. To demonstrate the proposed MLDEA model, a case study in evaluating the road safety performance of a set of 19 European countries is carried out. By using 13 hierarchical safety performance indicators in terms of road user behavior (e.g., inappropriate or excessive speed) as the model’s input and 4 layered road safety final outcomes (e.g., road fatalities) as the output, we compute the most optimal road safety efficiency score for the set of European countries, and further analyze the weights assigned to each layer of the hierarchy. A comparison of the results with the ones from the one layer DEA model clearly indicates the usefulness and effectiveness of this improvement in dealing with a great number of performance evaluation activities with hierarchical structures.     

Suppressing intersample behavior in iterative learning control

Iterative Learning Control (ILC) is a control strategy to improve the performance of digital batch repetitive processes. Due to its digital implementation, discrete time ILC approaches do not guarantee good intersample behavior. In fact, common discrete time ILC approaches may deteriorate the intersample behavior, thereby reducing the performance of the sampled-data system. In this paper, a generally applicable multirate ILC approach is presented that enables to balance the at-sample performance and the intersample behavior. Furthermore, key theoretical issues regarding multirate systems are addressed, including the time-varying nature of the multirate ILC setup. The proposed multirate ILC approach is shown to outperform discrete time ILC in realistic simulation examples.     

Der Stand der Forschung zur Erfolgsmessung von Informationssystemen

Measuring information systems (IS) success is of great interest to both researchers and practitioners. This article examines multidimensional approaches to measuring IS success and explores the current state of IS success research through a literature review and by classifying articles published between 2003 and 2007. Based on a total of 41 academic journal and conference publications, the relevant research carried out is identified, while the research results are categorized, consolidated, and discussed. The results show that the dominant empirical research analyzes the individual impact of a certain type of information system by ascertaining users’ evaluation of it by means of surveys and then applying structural equation modeling. The DeLone and McLean Information Systems Success Model is the main theoretical basis of the reviewed empirical studies. This article provides researchers with a comprehensive review and structuring of IS success research. Furthermore, opportunities for additional development are identified and future research directions suggested.     

Treiber der Adoption SaaS-basierter Anwendungen

Software-as-a-Service (SaaS) is said to become an important cornerstone of the Internet of Services. However, while some market research and IT provider firms fervently support this point of view, others already conjure up the failure of this on-demand sourcing option. Oftentimes based on weak empirical data and shaky reasoning, these inconsistent perspectives lack scientific rigor and neglect to present a more differentiated picture of SaaS-adoption. This study seeks to deepen the understanding of factors driving the adoption of Software-as-a-Service (SaaS). Grounded in transaction cost theory, the resource-based view, and the theory of planned behavior, the authors develop a research model to assess SaaS-adoption at the application level. Survey data of 297 firms in Germany with 374 valid response items across different industries were collected to test the theoretical model. Our analysis revealed that patterns of the decision on SaaS-adoption differ across application types. Social influence, attitude toward SaaS-adoption, adoption uncertainty, and strategic value turned out to be the strongest and most consistent drivers across all application types. Furthermore, it was found that firm size does not matter in SaaS-adoption, since large enterprises and small- and medium-sized companies had similar adoptation rates. Overall, this study provides relevant findings that IT vendors can use to better appeal to potential companies that consider adopting SaaS.