Two dynamic discrete choice estimation problems and simulation method solutions

This paper considers two problems that frequently arise in dynamic discrete choice problems but have not received much attention with regard to simulation methods. The first problem is how to simulate unbiased simulators of probabilities conditional on past history. The second is simulating a discrete transition probability model when the underlying dependent variable is really continuous. Both methods work well relative to reasonable alternatives in the application discussed. However, in both cases, for this application, simpler methods also provide reasonably good results.

Approximate solutions to stochastic dynamic programs

This paper examines the properties of various approximation methods for solving stochastic dynamic programs in structural estimation problems. The problem addressed is evaluating the expected value of the maximum of available choices. The paper shows that approximating this by the maximum of expected values frequently has poor properties. It also shows that choosing a convenient distributional assumptions for the errors and then solving exactly conditional on the distributional assumption leads to small approximation errors even if the distribution is misspecified. © 1997 Cambridge University Press.

A dynamic Web agent for verifying the security and integrity of a Web site's contents

To harness safe operation of Web-based systems in Web environments, we propose an SSPA (Server-based SHA-1 Page-digest Algorithm) to verify the integrity of Web contents before the server issues an HTTP response to a user request. In addition to standard security measures, our Java implementation of the SSPA, which is called the Dynamic Security Surveillance Agent (DSSA), provides further security in terms of content integrity to Web-based systems. Its function is to prevent the display of Web contents that have been altered through the malicious acts of attackers and intruders on client machines. This is to protect the reputation of organisations from cyber-attacks and to ensure the safe operation of Web systems by dynamically monitoring the integrity of a Web site's content on demand. We discuss our findings in terms of the applicability and practicality of the proposed system. We also discuss its time metrics, specifically in relation to its computational overhead at the Web server, as well as the overall latency from the clients' point of view, using different Internet access methods. The SSPA, our DSSA implementation, some experimental results and related work are all discussed

Improvement of a dynamic accumulator at ICICS 07 and its application in multi-user keyword-based retrieval on encrypted data

A dynamic accumulator is an algorithm, which merges a large set of elements into a constant-size value such that for an element accumulated, there is a witness confirming that the element was included into the value, with a property that accumulated elements can be dynamically added and deleted into/from the original set. Recently Wang et al. presented a dynamic accumulator for batch updates at ICICS 2007. However, their construction suffers from two serious problems. We analyze them and propose a way to repair their scheme. We use the accumulator to construct a new scheme for common secure indices with conjunctive keyword-based retrieval.

Dynamic self-organization phenomena in complex ionized gas systems : new paradigms and technological aspects

An overview of dynamic self-organization phenomena in complex ionized gas systems, associated physical phenomena, and industrial applications is presented. The most recent experimental, theoretical, and modeling efforts to understand the growth mechanisms and dynamics of nano- and micron-sized particles, as well as the unique properties of the plasma-particle systems (colloidal, or complex plasmas) and the associated physical phenomena are reviewed and the major technological applications of micro- and nanoparticles are discussed. Until recently, such particles were considered mostly as a potential hazard for the microelectronic manufacturing and significant efforts were applied to remove them from the processing volume or suppress the gas-phase coagulation. Nowadays, fine clusters and particulates find numerous challenging applications in fundamental science as well as in nanotechnology and other leading high-tech industries.

Buffer scheme with battery energy storage capability for enhancement of network transient stability and load ride-through

This paper examines a buffer scheme to mitigate the negative impacts of power-conditioned loads on network voltage and transient stabilities. The scheme is based on the use of battery energy-storage systems in the buffers. The storage systems ensure that protected loads downstream of the buffers can ride through upstream voltage sags and swells. Also, by controlling the buffers to operate in either constant impedance or constant power modes, power is absorbed or injected by the storage systems. The scheme thereby regulates the rotor-angle deviations of generators and enhances network transient stability. A computational method is described in which the capacity of the storage systems is determined to achieve simultaneously the above dual objectives of load ride-through and stability enhancement. The efficacy of the resulting scheme is demonstrated through numerical examples.

The role of intellectual resources, product innovation capability, reputational resources and marketing capability combinations in SME growth

This article examines the extent to which combinations of intellectual resources and product innovation capability, and reputational resources and marketing capability, influence the ability of small and medium-sized enterprises (SME) to meet or exceed performance goals. Empirical results drawn from 171 SMEs suggest that when the combination of intellectual resources and product innovation capability in addition to the combination of reputational resources and marketing capability are high, SME growth is enhanced. However, a high level of intellectual resources combined with a low level of product innovation capability as well as a combination of a high level of reputational resources with a low level of marketing capability (and vice versa) are not significantly related to growth. These results imply that a high level of resources cannot compensate for a low level of capabilities (and vice versa).

Understanding service firms brand value creation : a multilevel perspective including the overarching role of service brand marketing capability

Purpose This study seeks to extend the existing literature on value creation by specifically focusing on service brand value creation (SBVC) and the role of brand marketing. Design/methodology/approach The authors first develop a model of SBVC and simultaneously investigate SBVC from the firm perspective (service brand value offering – SBVO) and from the customer perspective (service brand perceive value-in use – SBPVI). Subsequently, they investigate the effects of SBVO on SBPVI and integrate the moderation role of service brand marketing capability (SBMC) on the relationship between SBVO-SBPVI outcomes. SBVO is viewed as the firms' interpretation of and responsiveness to customer requirements via the delivery of superior performance the value offering through the service brand and SBPVI customers' perceived value from the firms' service brand. The contributions of SBVC to customer-based performance outcomes are then investigated. Hypotheses were tested using a sample of the senior managers of service firms in Cambodia and their customers. A survey was used to gather data via a drop-and-collect approach. Findings Results indicated that SBVO is positively related to SBPVI and SBPVI is positively related to customer-based performance. Noticeably, the results revealed that SBMC enhances the positive relationship between the firm SBVO and the customers SBPVI. Originality/value The paper extends the previous literature on value creation to capture SBVC. More significantly, the premise of the theoretical framework provides a breakthrough in the current SBVC literature which has so far neglected to take into account the dyadic approach (firm-customer) in understanding value creation and more specifically SBVC. The model is expanded by looking at the contingency role of SBMC in communicating value to customers.

Keyword field-free conjunctive keyword searches on encrypted data and extension for dynamic groups

We consider the following problem: a user stores encrypted documents on an untrusted server, and wishes to retrieve all documents containing some keywords without any loss of data confidentiality. Conjunctive keyword searches on encrypted data have been studied by numerous researchers over the past few years, and all existing schemes use keyword fields as compulsory information. This however is impractical for many applications. In this paper, we propose a scheme of keyword field-free conjunctive keyword searches on encrypted data, which affirmatively answers an open problem asked by Golle et al. at ACNS 2004. Furthermore, the proposed scheme is extended to the dynamic group setting. Security analysis of our constructions is given in the paper.

Lower partial moment and information entropy-based dynamic electricity purchasing strategy

In the electricity market environment, load-serving entities (LSEs) will inevitably face risks in purchasing electricity because there are a plethora of uncertainties involved. To maximize profits and minimize risks, LSEs need to develop an optimal strategy to reasonably allocate the purchased electricity amount in different electricity markets such as the spot market, bilateral contract market, and options market. Because risks originate from uncertainties, an approach is presented to address the risk evaluation problem by the combined use of the lower partial moment and information entropy (LPME). The lower partial moment is used to measure the amount and probability of the loss, whereas the information entropy is used to represent the uncertainty of the loss. Electricity purchasing is a repeated procedure; therefore, the model presented represents a dynamic strategy. Under the chance-constrained programming framework, the developed optimization model minimizes the risk of the electricity purchasing portfolio in different markets because the actual profit of the LSE concerned is not less than the specified target under a required confidence level. Then, the particle swarm optimization (PSO) algorithm is employed to solve the optimization model. Finally, a sample example is used to illustrate the basic features of the developed model and method.

Detection of dynamic primary user with cooperative spectrum sensing

In this paper we demonstrate that existing cooperative spectrum sensing formulated for static primary users cannot accurately detect dynamic primary users regardless of the information fusion method. Performance error occurs as the sensing parameters calculated by the conventional detector result in sensing performance that violates the sensing requirements. Furthermore, the error is accumulated and compounded by the number of cooperating nodes. To address this limitation, we design and implement the duty cycle detection model for the context of cooperative spectrum sensing to accurately calculate the sensing parameters that satisfy the sensing requirements. We show that longer sensing duration is required to compensate for dynamic primary user traffic.

A gray-box neural network-based model identification and fault estimation scheme for nonlinear dynamic systems

A novel gray-box neural network model (GBNNM), including multi-layer perception (MLP) neural network (NN) and integrators, is proposed for a model identification and fault estimation (MIFE) scheme. With the GBNNM, both the nonlinearity and dynamics of a class of nonlinear dynamic systems can be approximated. Unlike previous NN-based model identification methods, the GBNNM directly inherits system dynamics and separately models system nonlinearities. This model corresponds well with the object system and is easy to build. The GBNNM is embedded online as a normal model reference to obtain the quantitative residual between the object system output and the GBNNM output. This residual can accurately indicate the fault offset value, so it is suitable for differing fault severities. To further estimate the fault parameters (FPs), an improved extended state observer (ESO) using the same NNs (IESONN) from the GBNNM is proposed to avoid requiring the knowledge of ESO nonlinearity. Then, the proposed MIFE scheme is applied for reaction wheels (RW) in a satellite attitude control system (SACS). The scheme using the GBNNM is compared with other NNs in the same fault scenario, and several partial loss of effect (LOE) faults with different severities are considered to validate the effectiveness of the FP estimation and its superiority.

Improved energy harvesting capability of poly(vinylidene fluoride) films modified by reduced graphene oxide

Piezoelectric energy harvesters can be used to convert ambient energy into electrical energy and power small autonomous devices. In recent years, massive effort has been made to improve the energy harvesting ability in piezoelectric materials. In this study, reduced graphene oxide was added into poly(vinylidene fluoride) to fabricate the piezoelectric nanocomposite films. Open-circuit voltage and electrical power harvesting experiments showed remarkable enhancement in the piezoelectricity of the fabricated poly(vinylidene fluoride)/reduced graphene oxide nanocomposite, especially at an optimal reduced graphene oxide content of 0.05 wt%. Compared to pristine poly(vinylidene fluoride) films, the open-circuit voltage, the density of harvested power of alternating current, and direct current of the poly(vinylidene fluoride)/reduced graphene oxide nanocomposite films increased by 105%, 153%, and 233%, respectively, indicating a great potential for a broad range of applications.

Enterprise Business Technology Governance: Three Competencies to Build Board Digital Leadership Capability.

The competent leadership of digital transformation needs to involve the board of directors. The reported lack of such capability in boards is becoming a pressing issue. A part of leadership in such transformation is the board of director’s competence to lead Enterprise Business Technology Governance (EBTG). In this paper we take the position that EBTG competencies are essential in boards, because competent EBTG has been shown to contribute to increased revenue, profit, and returns. We update and expand on the results of a multi-method approach to the development of a set of three board of director competencies needed for effective EBTG.

Emotion recognition of static and dynamic faces in autism spectrum disorder

There is substantial evidence for facial emotion recognition (FER) deficits in autism spectrum disorder (ASD). The extent of this impairment, however, remains unclear, and there is some suggestion that clinical groups might benefit from the use of dynamic rather than static images. High-functioning individuals with ASD (n = 36) and typically developing controls (n = 36) completed a computerised FER task involving static and dynamic expressions of the six basic emotions. The ASD group showed poorer overall performance in identifying anger and disgust and were disadvantaged by dynamic (relative to static) stimuli when presented with sad expressions. Among both groups, however, dynamic stimuli appeared to improve recognition of anger. This research provides further evidence of specific impairment in the recognition of negative emotions in ASD, but argues against any broad advantages associated with the use of dynamic displays.