Metaheuristics for minimizing the makespan of the dynamic shop scheduling problem

For the shop scheduling problems such as flow-shop, job-shop, open-shop, mixed-shop, and group-shop, most research focuses on optimizing the makespan under static conditions and does not take into consideration dynamic disturbances such as machine breakdown and new job arrivals. We regard the shop scheduling problem under static conditions as the static shop scheduling problem, while the shop scheduling problem with dynamic disturbances as the dynamic shop scheduling problem. In this paper, we analyze the characteristics of the dynamic shop scheduling problem when machine breakdown and new job arrivals occur, and present a framework to model the dynamic shop scheduling problem as a static group-shop-type scheduling problem. Using the proposed framework, we apply a metaheuristic proposed for solving the static shop scheduling problem to a number of dynamic shop scheduling benchmark problems. The results show that the metaheuristic methodology which has been successfully applied to the static shop scheduling problems can also be applied to solve the dynamic shop scheduling problem efficiently.

Internet-enabled international entrepreneurship : a conceptual exploration of the link between a firm’s resource base, dynamic capabilities and international market performance

It has been suggested that the accumulation of valuable resources and capabilities, such as Internet application, is not enough to support a firm’s sustainable competitive advantage, especially for high technology-mediated firms; which often operate in fast changing dynamic environments. While the idea of ‘Internet-enabled resources and capabilities’ has been recognised by RBV theorists, the notion has largely been ignored in conceptual and empirical studies. Given this finding, a conceptual framework is constructed and research issues are then developed in order to focus attention on the relationship between, the Internet and a firm’s resource base, dynamic capabilities and international market performance. We postulate that successful Internet-enabled market performance arises from those international entrepreneurial-oriented firms which encompass: international vision, international business experience, Internet-international marketing capabilities and international networking capabilities. Recommendations for future theory development are presented, along with the implications for international entrepreneurial managers in Australian small and medium sized firms

Human seat modelling using inverse dynamic musculoskeletal models

In this work a biomechanical model is used for simulation of muscle forces necessary to maintain the posture in a car seat under different support conditions.

Mapping the dynamic of Project Management field : Project Management in action

Focusing on the role within and between organizations of the project management discipline to design and implement strategy, as source of competitive advantage, leads us to question the scientific field behind this discipline. This science should be the basis for the development and use of bodies of knowledge, standards, certification programs, education, and competencies, and beyond this as a source of value for people, organizations, and society. Thus the importance to characterize, define, and understand this field and its underlying strength, basis, and development is paramount. For this purpose we propose to give some insights on the current situation. This will lead us to clarify our epistemological position and demonstrate that both constructivism and positivist approaches are required to seize the full dimension and dynamics of the field.We will referee to sociology of actor-networks and qualitative scientometrics leading to the choice of the co-word analysis method in enabling us to capture the project management field and its dynamics.Results of a study based on the analysis of ABI Inform database will be presented and some future trends and scenarios proposed.

Strategic Management Practices in the Construction Industry : a Dynamic Capabilities View

This book is an empirical study of strategic management practices in the construction industry. It examines the dynamic capabilities paradigm within the context of the Indonesian construction industry. The characteristics of asset-capability combinations were found to be significant determinants of the competitive advantage of the Indonesian construction enterprises, and that such advantage sequentially contributes to organizational performance. In doing so, this study fills an important gap in the empirical literature and reinforces the dynamic capabilities framework’s recognition as a rigorous theory of strategic management. As the dynamic capabilities framework can work in the context of Indonesia, it suggests that the framework has potential applicability in other emerging and developing countries

Static and dynamic strain sensing using a polymer : carbon nanotube film strain sensor

The search for new multipoint, multidirectional strain sensing devices has received a new impetus since the discovery of carbon nanotubes. The excellent electrical, mechanical, and electromechanical properties of carbon nanotubes make them ideal candidates as primary materials in the design of this new generation of sensing devices. Carbon nanotube based strain sensors proposed so far include those based on individual carbon nanotubes for integration in nano or micro elecromechanical systems (NEMS/MEMS) [1], or carbon nanotube films consisting of spatially connected carbon nanotubes [2], carbon nanotube - polymer composites [3,4] for macroscale strain sensing. Carbon nanotube films have good strain sensing response and offer the possibility of multidirectional and multipoint strain sensing, but have poor performance due to weak interaction between carbon nanotubes. In addition, the carbon nanotube film sensor is extremely fragile and difficult to handle and install. We report here the static and dynamic strain sensing characteristics as well as temperature effects of a sandwich carbon nanotube - polymer sensor fabricated by infiltrating carbon nanotube films with polymer.

Syntaxin 11 binds Vti1b and regulates late endosome to lysosome fusion in macrophages

Syntaxin 11 (Stx11) is a SNARE protein enriched in cells of the immune system. Loss or mutation of Stx11 results in familial hemophagocytic lymphohistiocytosis type-4 (FHL-4), an autosomal recessive disorder of immune dysregulation characterized by high levels of inflammatory cytokines along with defects in T-cell and natural killer cell function. We show here Stx11 is located on endosomalmembranes including late endosomes and lysosomes in macrophages. While Stx11 did not form a typical trans-SNARE complex, it did bind to the Q-SNARE Vti1b and was able to regulate the availability of Vti1b to form the Q-SNARE complexes Stx6/Stx7/Vtib and Stx7/Stx8/Vti1b. The mutant form of Stx11 sequestered Vti1b from forming the Q-SNARE complex that mediates late endosome to lysosome fusion. Depletion of Stx11 in activated macrophages leads to an accumulation of enlarged late endocytic compartments, increased trafficking to the cell surface and inhibition of late endosome to lysosome fusion. These phenotypes arerescued by the expression of an siRNA-resistant Stx11 construct in Stx11-depleted cells. Our results suggest that by regulating the availability of Vti1b, Stx11 regulates trafficking steps between late endosomes, lysosomes and the cell surface in macrophages.

Sequential Fusion Using Correlated Decisions for Controlled Verification Errors

Fusion techniques have received considerable attention for achieving lower error rates with biometrics. A fused classifier architecture based on sequential integration of multi-instance and multi-sample fusion schemes allows controlled trade-off between false alarms and false rejects. Expressions for each type of error for the fused system have previously been derived for the case of statistically independent classifier decisions. It is shown in this paper that the performance of this architecture can be improved by modelling the correlation between classifier decisions. Correlation modelling also enables better tuning of fusion model parameters, ‘N’, the number of classifiers and ‘M’, the number of attempts/samples, and facilitates the determination of error bounds for false rejects and false accepts for each specific user. Error trade-off performance of the architecture is evaluated using HMM based speaker verification on utterances of individual digits. Results show that performance is improved for the case of favourable correlated decisions. The architecture investigated here is directly applicable to speaker verification from spoken digit strings such as credit card numbers in telephone or voice over internet protocol based applications. It is also applicable to other biometric modalities such as finger prints and handwriting samples.

Interplay effects during enhanced dynamic wedge deliveries

In this study the interplay effects for Enhanced Dynamic Wedge (EDW) treatments are experimentally investigated. Single and multiple field EDW plans for different wedge angles were delivered to a phantom and detector on a moving platform, with various periods, amplitudes for parallel and perpendicular motions. A four field 4D CT planned lung EDW treatment was delivered to a dummy tumor over four fractions. For the single field parallel case the amplitude and the period of motion both affect the interplay resulting in the appearance of a step function and penumbral cut off with the discrepancy worst where collimator-tumor speed is similar. For perpendicular motion the amplitude of tumor motion is the only dominant factor. For large wedge angle the dose discrepancy is more pronounced compared to the small wedge angle for the same field size and amplitude-period values. For a small field size i.e. 5 × 5 cm2 the loss of wedged distribution was observed for both 60º and 15º wedge angles for of parallel and perpendicular motions. Film results from 4D CT planned delivery displayed a mix of over and under dosages over 4 fractions, with the gamma pass rate of 40% for the averaged film image at 3%/1 mm DTA (Distance to Agreement). Amplitude and period of the tumor motion both affect the interplay for single and multi-field EDW treatments and for a limited (4 or 5) fraction delivery there is a possibility of non-averaging of the EDW interplay.

Condition deterioration prediction of bridge elements using Dynamic Bayesian Networks (DBNs)

The ability of bridge deterioration models to predict future condition provides significant advantages in improving the effectiveness of maintenance decisions. This paper proposes a novel model using Dynamic Bayesian Networks (DBNs) for predicting the condition of bridge elements. The proposed model improves prediction results by being able to handle, deterioration dependencies among different bridge elements, the lack of full inspection histories, and joint considerations of both maintenance actions and environmental effects. With Bayesian updating capability, different types of data and information can be utilised as inputs. Expert knowledge can be used to deal with insufficient data as a starting point. The proposed model established a flexible basis for bridge systems deterioration modelling so that other models and Bayesian approaches can be further developed in one platform. A steel bridge main girder was chosen to validate the proposed model.

Sequential fusion of decisions from adaptive and random samples for controlled verification of errors

Fusion techniques have received considerable attention for achieving performance improvement with biometrics. While a multi-sample fusion architecture reduces false rejects, it also increases false accepts. This impact on performance also depends on the nature of subsequent attempts, i.e., random or adaptive. Expressions for error rates are presented and experimentally evaluated in this work by considering the multi-sample fusion architecture for text-dependent speaker verification using HMM based digit dependent speaker models. Analysis incorporating correlation modeling demonstrates that the use of adaptive samples improves overall fusion performance compared to randomly repeated samples. For a text dependent speaker verification system using digit strings, sequential decision fusion of seven instances with three random samples is shown to reduce the overall error of the verification system by 26% which can be further reduced by 6% for adaptive samples. This analysis novel in its treatment of random and adaptive multiple presentations within a sequential fused decision architecture, is also applicable to other biometric modalities such as finger prints and handwriting samples.

Sequential fusion of decisions with favorable dependence for controlled verification errors

Statistical dependence between classifier decisions is often shown to improve performance over statistically independent decisions. Though the solution for favourable dependence between two classifier decisions has been derived, the theoretical analysis for the general case of 'n' client and impostor decision fusion has not been presented before. This paper presents the expressions developed for favourable dependence of multi-instance and multi-sample fusion schemes that employ 'AND' and 'OR' rules. The expressions are experimentally evaluated by considering the proposed architecture for text-dependent speaker verification using HMM based digit dependent speaker models. The improvement in fusion performance is found to be higher when digit combinations with favourable client and impostor decisions are used for speaker verification. The total error rate of 20% for fusion of independent decisions is reduced to 2.1% for fusion of decisions that are favourable for both client and impostors. The expressions developed here are also applicable to other biometric modalities, such as finger prints and handwriting samples, for reliable identity verification.