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Privacy preservation is a significant concern in Internet of Things (IoT)-enabled event-driven wireless sensor networks (WSNs). Low energy utilization in the event-driven system is essential if events do not happen. When events occur, IoT-enabled sensor network is required to deal with enormous traffic from the concentration of demand data delivery. This paper aims to explore an effective framework for safeguarding privacy at source in event-driven WSNs.

This paper discusses three algorithms in IoT-enabled event-driven WSNs: source location privacy for event detection (SLP_ED), chessboard alteration pattern (SLP_ED_CBA) and grid-based source location privacy (GB_SLP). Performance evaluation is done using simulation results and security analysis of the proposed scheme.

The sensors observe bound events or sensitive items within the network area in the field of interest. The open wireless channel lets an opponent search traffic designs, trace back and reach the start node or the event-detecting node. SLP_ED and SLP_ED_CBA provide better safety level results than dynamic shortest path scheme and energy-efficient source location privacy protection schemes. This paper discusses security analysis for the GB_SLP. Comparative analysis shows that the proposed scheme is more efficient on safety level than existing techniques.

The authors develop the privacy protection scheme in IoT-enabled event-driven WSNs. There are two categories of occurrences: nominal events and critical events. The choice of the route from source to sink relies on the two types of events: nominal or critical; the privacy level required for an event; and the energy consumption needed for the event. In addition, phantom node selection scheme is designed for source location privacy.

The business operations of today's enterprises are heavily influenced by numerous of internal and external business events. With the Event Driven Architecture and particularly the Complex Event Processing (CEP), the technology required for identifying complex correlations in these large amounts of event data right after its appearance has already emerged. The resulting gain in operational transparency builds the foundation for (near) real-time reactions. This motivated extensive research activities especially in the field of Business Process Management (BPM), which essentially coined the term Event-Driven BPM (EDBPM). Now, several years after the advent of this new concept, the purpose of this paper is to shed light to the question: where are we now on our way towards a sophisticated adoption of the CEP technology within BPM?

The research methodology of this paper is a structured literature analysis. It basically follows the procedure proposed by vom Brocke et al. (2009). This verified five-step process – entitled “Reconstructing the giant” – allowed a rigorous study. As a result, various research clusters were derived, whose state-of-the-art exposed existing research gaps within EDBPM.

First of all, the paper provides a concise conceptual basis on different application possibilities of EDBPM. Afterwards, it synthesizes current research into six clusters and highlights most significant work within them. Finally, a research agenda is proposed to tackle existing research gaps to pave the way towards fully realizing the potentials of the paradigm.

So far, a comparable study of the current state-of-the-art within EDBPM is non-existent. The findings of this paper, e.g. the proposed research agenda, help scholars to focus their research efforts on specific aspects that need to be considered in order to advance the adoption of the CEP technology within BPM.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

The purpose of this paper is to construct a process theory of cluster development, in order to complement the many studies focusing on the factors that determine successful clusters.

This theory‐building effort relies on event‐driven methodology, which triangulates narratives collected at different points in time with other documented materials, in order to trace cluster development over a six‐year period. The empirical data are analysed according to theoretical classes formed a priori and anchored in Aldrich's framework of emergence, events and consequences. The idea is to identify critical events that subsequently inform theory development.

The authors show that three critical processes drive sustainable cluster development: the exploitation of current opportunities, the exploration of future opportunities, and processes that facilitate the balancing of the two. Whereas the conceptual focus in the extant literature is on exploration and exploitation processes, the authors find that balancing processes are also critical.

The paper's findings are of practical relevance to private and public policy makers with regard to the management and financing of balancing mechanisms that help to secure sustainable development. The authors will continue to follow the development of this specific cluster in order to identify a wider range of sub‐processes that contribute to the long‐term viability of clusters in general.

This work is original in the sense that it extends March's exploration and exploitation theory, applies it to the inter‐organisational context of clusters, and links the two processes through a process of balancing. The empirical evidence and the methodological approach used contribute in terms of building a “real process theory”, according to Aldrich's specification of an event‐driven research approach.

Bar‐tacking is a specialized sewing stitch designed to provide immense tensile strength to the garment which requires a high‐speed precision bar‐tacking sewing machine. This paper aims to present an event‐driven multi‐axis cooperative control method for a bar‐tacking sewing machine.

The control method consists of two parts: the multi‐axis cooperative control and the needle stop positioning control. The challenges include the high speed and the precision. For example, the needle must stop at a set position in milliseconds.

The presented multi‐axis cooperative control can ensure the high speed response and the precision of the cooperative control. The needle stop positioning control is based on a combination of the velocity control and the position control with velocity feed‐forward and limitation.

The bar‐tacking sewing machine requires high‐speed start and stop response and coordination of displacement and velocity only at some given points. Therefore, the conventional multi‐axis cooperative control methods are not suitable. In addition, it requires high‐speed precision control under varying loading conditions.

While there are a number of commercial textile machines available in the market, designing a smart bar‐tacking sewing machine with good speed and precision performance remains a challenge.

The bar‐tacking sewing machine requires highly accurate multi‐axes cooperative control. The presented event‐driven multi‐axis control method is effective. It has not only the required high accuracy but also the fast time response.

Purpose – This research pinpoints the limitations of conventional models for evaluating the performance of hedge funds and attempts to provide a new framework for modeling the dynamics of risk structures of hedge funds.

Methodology/approach – This chapter aims to explore how the systematic risk exposures of hedge funds vary over time and depend on exogenous variables that managers are supposed to use in their dynamic investment strategies. To achieve this, we used a Bayesian time-varying CAPM-based beta model within a state space technology.

Findings – The results showed that the volatility, term spread rate, and shocks in liquidity influence significantly on the time variation of hedge funds. Besides, the dynamics of beta indicates that the transmission channels of systematic risk are mainly the leverage levels of hedge funds and liquidity shocks.

Originality/value of chapter – These results are original because they help to explain how expected and unexpected hedge fund returns are correlated with the systematic risk factors via the beta dynamics.

Customer satisfaction assessment is now widely recognized as a vital input to any strategy for customer focused business performance improvement. The need to improve responsiveness and reduce overheads is focusing management attention on the major internal business functions such as IT. Argues that these functions, threatened with major cost reductions or outsourcing, are increasingly feeling the need to understand better their customers business needs and to assess how successful they are in satisfying them. Any customer satisfaction assessment tool must recognize the varying needs of individual “customers” within the “customer” organizations. Data collection must lead to prompt action: “event‐driven” assessments owned by “empowered” teams of service providers can help achieve this. Such a “fast cycle” satisfaction assessment/improvement process will not happen spontaneously: “selling”, training, culture change and management leadership are needed to embed action‐oriented customer‐satisfaction assessment in internal service providers.

The purpose of this paper is to investigate the local feature of driven granular gases in event-driven molecular dynamic simulation, in order to achieve spatial profiles of local velocity distribution and granular temperature, and the local state with various coefficients of restitution.

Event-driven molecular dynamic simulation is performed to study a vibro-fluidized granular gas system. Triangular-wave vibration is adopted in the simulation. The authors focus on the steady state of a driven granular gas.

The simulation finds the local velocity distribution is asymmetric along vibration direction in this driven granular gas system, which agrees with the experimental results obtained in micro-gravity. A nonlinear spatial profile of the skewness of local velocity distribution in vibration direction is found in the simulation. Furthermore, it is found that the value of skewness increases with the system dissipation. It is also found that the two temperature components T+ and T− differ from each other. This shows breakdown of energy equipartition. The ratio between them drops exponentially along y direction in various coefficients of restitution. All results confirm that the bulk boundary effect relates to the dissipation properties of granular gases.

This is the first MD simulation that investigates the bulk boundary effect to the local velocity distribution. The spatial profiles of the skewness of local velocity distribution are also investigated when changing the coefficient of restitution to study the influence of the system dissipative nature.

The purpose of this paper is to show how to employ complex event processing (CEP) for the observation and management of business processes. It proposes a conceptual architecture of BPM event producer, processor, and consumer and describes technical implications for the application with standard software in a perfect order scenario.

The authors discuss business process analytics as the technological background. The capabilities of CEP in a BPM context are outlined an architecture design is proposed. A sophisticated proof‐of‐concept demonstrates its applicability.

The results overcome the separation and data latency issues of process controlling, monitoring, and simulation. Distinct analyses of past, present, and future blur into a holistic real‐time approach. The authors highlight the necessity for configurable event producer in BPM engines, process event support in CEP engines, a common process event format, connectors to visualizers, notifiers and return channels to the BPM engine.

Further research will thoroughly evaluate the approach in a variety of business settings. New concepts and standards for the architecture's building blocks will be needed to improve maintainability and operability.

Managers learn how CEP can yield insights into business processes' operations. The paper illustrates a path to overcome inflexibility, latency, and missing feedback mechanisms of current process modeling and control solutions. Software vendors might be interested in the conceptualization and the described needs for further development.

So far, there is no commercial CEP‐based BPM solution which facilitates a round trip from insight to action as outlines. As major software vendors have begun developing solutions (BPM/BPA solutions), this paper will stimulate a debate between research and practice on suitable design and technology.

The author suggests an empirical model to analyze the investment style of individual hedge funds and fund of funds. This approach is based on a mixture of the style analysis approach suggested by Sharpe [1988], the factor push approach used in stress testing, and historical simulation. The parameter estimates from this model are inputs in the Value‐at‐Risk analysis for a sample of 2,934 funds over the 1994–2000 period. The in‐sample and out‐of‐sample results suggest that the proposed approach is useful and may constitute a valuable tool for assessing the investment style and risk of hedge funds.