Adaptive SOA Infrastructure Based on Variability Management

In order to exploit the adaptability of a SOA infrastructure, it becomes necessary to provide platform mechanisms that support a mapping of the variability in the applications to the variability provided by the infrastructure. The approach focuses on the configuration of the needed infrastructure mechanisms including support for the derivation of the infrastructure variability model.

Location management and routing in urban vehicular ad hoc networks

In recent years, urban vehicular ad hoc networks (VANETs) are gaining importance for inter-vehicle communication, because they allow for the local communication between vehicles without any infrastructure, configuration effort, and without expensive cellular networks. But such architecture may increase the complexity of routing since there is no central control system in urban VANETs. Therefore, a challenging research task is to improve urban VANETs' routing efficiency. ^ Hence, in this dissertation we propose two location-based routing protocols and a location management protocol to facilitate location-based routing in urban VANETs. The Multi-hop Routing Protocol (MURU) is proposed to make use of predicted mobility and geometry map in urban VANETs to estimate a path's life time and set up robust end-to-end routing paths. The Light-weight Routing Protocol (LIRU) is proposed to take advantage of the node diversity under dynamic channel condition to exploit opportunistic forwarding to achieve efficient data delivery. A scalable location management protocol (MALM) is also proposed to support location-based routing protocols in urban VANETs. MALM uses high mobility in VANETs to help disseminate vehicles' historical location information, and a vehicle is able to implement Kalman-filter based predicted to predict another vehicle's current location based on its historical location information. ^

Essays of strategic alliance portfolio configuration—Its performance properties, strategic antecedents and consequential effects on multinational firms' continuing foreign expansion

This dissertation focused on an increasingly prevalent phenomenon in today's global business environment—strategic alliance portfolio. Building on resource-based view, resource dependency theory and real options theory, this dissertation adopted a multi-dimensional perspective to examine the performance implications, strategic antecedents of alliance portfolio configuration, and its strategic effects on firms' decision-making on their continuing foreign expansion. The dissertation consisted of three interrelated essays, each of which dealt with a specific research question. In the first essay I applied a two-dimensional construct that embraces both alliance relations' and alliance partners' attributes to illustrate alliance portfolio configuration. Based on this framework, a longitudinal study was conducted attempting to explore the performance properties of alliance portfolio configuration. The results revealed that alliance diversity and partner diversity have different relative contributions to firms' economic performance. The relationship between alliance portfolio configuration and firm performance was shaped by degree of multinationality in a curvilinear pattern. The second essay attempted to identify the firm level driving forces of alliance portfolio configuration and how these forces interacting with firms' internationalization influence firms' strategic choices on alliance portfolio configuration. The empirical results indicated that past alliance experience, slack resource and firms' brand images are three critical determinants shaping alliance portfolios, but those shaping relationships are conditioned by firms' multinationality. The third essay primarily employed real options theory to build a conceptual framework, revealing how country-, alliance portfolio-, firm-, and industry level factors and their interactions influence firms' strategic decision-making on post-entry continuing expansion in foreign markets. The two empirical studies were resided in global hospitality and travel industries and use panel data to test the relevant theoretical models. Overall, the dissertation advanced and enriched the theoretical domain of alliance portfolio. It particularly shed valuable insights on three fundamental questions in the domain of alliance portfolio research, namely "if and how alliance portfolios contribute to firms' economic performance"; "what determines the appearance of alliance portfolios”; and "how alliance portfolios affect firms' strategic decision-making". This dissertation also extended the international business and strategic management research on service multinationals' foreign expansion and performance.

Event mining for system and service management

Modern IT infrastructures are constructed by large scale computing systems and administered by IT service providers. Manually maintaining such large computing systems is costly and inefficient. Service providers often seek automatic or semi-automatic methodologies of detecting and resolving system issues to improve their service quality and efficiency. This dissertation investigates several data-driven approaches for assisting service providers in achieving this goal. The detailed problems studied by these approaches can be categorized into the three aspects in the service workflow: 1) preprocessing raw textual system logs to structural events; 2) refining monitoring configurations for eliminating false positives and false negatives; 3) improving the efficiency of system diagnosis on detected alerts. Solving these problems usually requires a huge amount of domain knowledge about the particular computing systems. The approaches investigated by this dissertation are developed based on event mining algorithms, which are able to automatically derive part of that knowledge from the historical system logs, events and tickets. ^ In particular, two textual clustering algorithms are developed for converting raw textual logs into system events. For refining the monitoring configuration, a rule based alert prediction algorithm is proposed for eliminating false alerts (false positives) without losing any real alert and a textual classification method is applied to identify the missing alerts (false negatives) from manual incident tickets. For system diagnosis, this dissertation presents an efficient algorithm for discovering the temporal dependencies between system events with corresponding time lags, which can help the administrators to determine the redundancies of deployed monitoring situations and dependencies of system components. To improve the efficiency of incident ticket resolving, several KNN-based algorithms that recommend relevant historical tickets with resolutions for incoming tickets are investigated. Finally, this dissertation offers a novel algorithm for searching similar textual event segments over large system logs that assists administrators to locate similar system behaviors in the logs. Extensive empirical evaluation on system logs, events and tickets from real IT infrastructures demonstrates the effectiveness and efficiency of the proposed approaches.^

The Un-Politics of New Public Management in Ireland

Many of the principles and indeed the rhetoric of New Public Management proved attractive to both politicians and senior bureaucrats across the developed world as a remedy for problems in policy processes. Ireland shares many features of its constitutional structures and political practices with Britain, Canada, Australia, New Zealand, all of them early and enthusiastic adopters of NPM. Some of the organizational and procedural changes in Irish public administration do indeed bear similarities to those we would expect to see as a result of adopting principles of NPM. However, we contend that surface impressions are misleading. Drawing on a time-series database of Irish state institutions, we show that organizational changes were not necessarily driven by NPM. The absence of strong political drivers meant that reform initiatives did not fundamentally alter the configuration of the Irish public administration. Many of the problems that NPM was intended to address are only now coming under scrutiny.

Cloud-Architektur für Privacy-Management in kollaborativen Logistikprozessen

Durch den großen Erfolg des Cloud Computing und der hohen Geschwindigkeit, mit der Cloud-Innovationen seither Einzug in die Praxis finden, eröffnen sich für die Industrie neue Chancen im Wettbewerb. Von besonderer Bedeutung sind die Möglichkeiten, Cloud-gestützte Geschäftsprozesse dynamisch, als direkte Reaktion auf einen Kundenauftrag, anzupassen und auszuführen. Dies gilt insbesondere auch für kooperative und unternehmensübergreifende Anwendungen, welche aus mehreren IT-Diensten verschiedener Partner bestehen. Gegenstand dieses Artikels ist die Vorstellung eines Konzeptes und einer Architektur für eine zentrale Cloud-Plattform zur Konfiguration, Ausführung und Überwachung von kollaborativen Logistik-Prozessen. Auf dieser Plattform können Geschäftsprozesse modelliert und in ihren Privacy-Eigenschaften parametrisiert werden. Die einzelnen Prozesselemente werden dabei mit IT-Diensten verknüpft, die beispielsweise auf externen Cloud-Plattformen ausgeführt werden. Ein Schwerpunkt der Veröffentlichung liegt in der Betrachtung der Erstellung, Umsetzung und Überwachung von Privacy-Anforderungen.

Energy Management of a Battery-Ultracapacitor Hybrid Energy Storage System in Electric Vehicles

Electric vehicle (EV) batteries tend to have accelerated degradation due to high peak power and harsh charging/discharging cycles during acceleration and deceleration periods, particularly in urban driving conditions. An oversized energy storage system (ESS) can meet the high power demands; however, it suffers from increased size, volume and cost. In order to reduce the overall ESS size and extend battery cycle life, a battery-ultracapacitor (UC) hybrid energy storage system (HESS) has been considered as an alternative solution. In this work, we investigate the optimized configuration, design, and energy management of a battery-UC HESS. One of the major challenges in a HESS is to design an energy management controller for real-time implementation that can yield good power split performance. We present the methodologies and solutions to this problem in a battery-UC HESS with a DC-DC converter interfacing with the UC and the battery. In particular, a multi-objective optimization problem is formulated to optimize the power split in order to prolong the battery lifetime and to reduce the HESS power losses. This optimization problem is numerically solved for standard drive cycle datasets using Dynamic Programming (DP). Trained using the DP optimal results, an effective real-time implementation of the optimal power split is realized based on Neural Network (NN). This proposed online energy management controller is applied to a midsize EV model with a 360V/34kWh battery pack and a 270V/203Wh UC pack. The proposed online energy management controller effectively splits the load demand with high power efficiency and also effectively reduces the battery peak current. More importantly, a 38V-385Wh battery and a 16V-2.06Wh UC HESS hardware prototype and a real-time experiment platform has been developed. The real-time experiment results have successfully validated the real-time implementation feasibility and effectiveness of the real-time controller design for the battery-UC HESS. A battery State-of-Health (SoH) estimation model is developed as a performance metric to evaluate the battery cycle life extension effect. It is estimated that the proposed online energy management controller can extend the battery cycle life by over 60%.

Development of the Andalusian Registry of Patients Receiving Community Case Management, for the follow-up of people with complex chronic diseases.

Background: Complex chronic diseases are a challenge for the current configuration of Health services. Case management is a service frequently provided for people with chronic conditions and despite its effectiveness in many outcomes, such as mortality or readmissions, uncertainty remains about the most effective form of team organization, structures, and the nature of the interventions. Many processes and outcomes of case management for people with complex chronic conditions cannot be addressed with the information provided by electronic clinical records. Registries are frequently used to deal with this weakness. The aim of this study was to generate a registry-based information system of patients receiving case management to identify their clinical characteristics, their context of care, events identified during their follow-up, interventions developed by case managers, and services used. Methods and design: The study was divided into three phases, covering the detection of information needs, the design and its implementation in the healthcare system, using literature review and expert consensus methods to select variables that would be included in the registry. Objective: To describe the essential characteristics of the provision of ca re lo people who receive case management (structure, process and outcomes), with special emphasis on those with complex chronic diseases. Study population: Patients from any District of Primary Care, who initiate the utilization of case management services, to avoid information bias that may occur when including subjects who have already been received the service, and whose outcomes and characteristics could not be properly collected. Results: A total of 102 variables representing structure, processes and outcomes of case management were selected for their inclusion in the registry after the consensus phase. Total sample was composed of 427 patients, of which 211 (49.4%) were women and 216 (50.6%) were men. The average functional level (Barthel lndex) was 36.18 (SD 29.02), cognitive function (Pfeiffer) showed an average of 4.37 {SD 6.57), Chat1son Comorbidity lndex, obtained a mean of 3.03 (SD 2.7) and Social Support (Duke lndex) was 34.2 % (SD 17.57). More than half of patients include in the Registry, correspond lo immobilized or transitional care for patients discharged from hospital (66.5 %). The patient's educational level was low or very low (50.4%). Caregivers overstrain (Caregiver stress index), obtained an average value of 6.09% (SD 3.53). Only 1.2 % of patients had declared their advanced directives, 58.6 had not defined the tutelage and the vast majority lived at home 98.8 %. Regarding the major events recorded at RANGE Registry, 25.8 % of the selected patients died in the first three months, 8.2 % suffered a hospital admission at least once time, 2.3%, two times, and 1.2% three times, 7.5% suffered a fall, 8.7% had pressure ulcer, 4.7% had problems with medication, and 3.3 % were institutionalized. Stroke is the more prevalent health problem recorded (25.1%), followed by hypertension (11.1%) and COPD (11.1%). Patients registered by NCMs had as main processes diabetes (16.8%) and dementia (11.3 %). The most frequent nursing diagnoses referred to the self-care deficit in various activities of daily living. Regarding to nursing interventions, described by the Nursing Intervention Classification (NIC), dementia management is the most used intervention, followed by mutual goal setting, caregiver and emotional support. Conclusions: The patient profile who receive case management services is a chronic complex patient with severe dependence, cognitive impairment, normal social support, low educational level, health problems such as stroke, hypertension or COPD, diabetes or dementia, and has an informal caregiver. At the first follow up, mortality was 19.2%, and a discrete rate of readmissions and falls.

Typologies and spatialization of agricultural production systems in Rondônia, Brazil: linking land use, socioeconomics and territorial configuration.

The current Amazon landscape consists of heterogeneous mosaics formed by interactions between the original forest and productive activities. Recognizing and quantifying the characteristics of these landscapes is essential for understanding agricultural production chains, assessing the impact of policies, and in planning future actions. Our main objective was to construct the regionalization of agricultural production for Rondônia State (Brazilian Amazon) at the municipal level. We adopted a decision tree approach, using land use maps derived from remote sensing data (PRODES and TerraClass) combined with socioeconomic data. The decision trees allowed us to allocate municipalities to one of five agricultural production systems: (i) coexistence of livestock production and intensive agriculture; (ii) semi-intensive beef and milk production; (iii) semi-intensive beef production; (iv) intensive beef and milk production, and; (v) intensive beef production. These production systems are, respectively, linked to mechanized agriculture (i), traditional cattle farming with low management, with (ii) or without (iii) a significant presence of dairy farming, and to more intensive livestock farming with (iv) or without (v) a significant presence of dairy farming. The municipalities and associated production systems were then characterized using a wide variety of quantitative metrics grouped into four dimensions: (i) agricultural production; (ii) economics; (iii) territorial configuration, and; (iv) social characteristics. We found that production systems linked to mechanized agriculture predominate in the south of the state, while intensive farming is mainly found in the center of the state. Semi-intensive livestock farming is mainly located close to the southwest frontier and in the north of the state, where human occupation of the territory is not fully consolidated. This distributional pattern reflects the origins of the agricultural production system of Rondônia. Moreover, the characterization of the production systems provides insights into the pattern of occupation of the Amazon and the socioeconomic consequences of continuing agricultural expansion.