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This study examines the incentives motivating listed companies in Malaysia to voluntarily choose the Direct Method over the Indirect Method in reporting cash flow from operating (CFO) activities in their 1997 annual financial reports following the adoption of the IAS 7 (Revised) Statement of Cash Flows (SCF), which was used prior to the current standard MASB No. 5 Cash Flow Statement promulgated by the Malaysian Accounting Standards Board (MASB) in 1999. Adopting the signalling perspective, the general hypothesis of this study is that the choice of the Direct Method over the Indirect Method in reporting CFO activities is to maximize a firm’s value via engagement in quality signalling to the market. Specifically, it is hypothesised that such decision is influenced by the firm’s level of managerial efficiency, financial risk, size, its auditor, and industry membership. The sample consists of 231 firms listed on the Kuala Lumpur Stock Exchange; 32 firms in the treatment group (Direct Method) and 199 firms in the control group (Indirect Method). Based on the results from the univariate and multivariate analyses, we found all variables to be in the hypothesised directions. However, we infer that the decision to choose the Direct Method for reporting CFO activities in SCF is significantly influenced by the firm’s level of managerial efficiency, size, and its auditor. Thus, there is support for the general hypothesis of maximization of the value of the firm via quality signalling. The authors gratefully appreciate the helpful comments of the discussant and workshop participants at the 11th Asian‐Pacific Conference on International Accounting

The paper's objective is to investigate the relation between direct and indirect marketing channels applied by French wine producers, and to identify the elements that can enhance the success of direct distribution methods.

Secondary data collected though a questionnaire survey, and published in a study of Viniflhor was analysed in order to identify the distribution channels used by French wine producers. In the second part of the study, primary qualitative data obtained through face‐to‐face interviews with 17 wine producers was used to explore their direct marketing approach.

The findings indicated that French wine producers use a large variety of both direct and indirect marketing channels, although the importance of these distribution methods varies with the size of the producer (defined in terms of vineyard area and wine production). An integrated distribution strategy is applied by more than a half of the respondents. Although the strategic planning process is applied informally and intuitively, a series of innovative elements are combined in order to enhance the value of the product offer and to develop long‐term relationships with satisfied customers.

The low response rate obtained in the application of data collection methods raises questions regarding the possibility to generalize the findings to the entire population of study.

The paper applies a three layer analysis to the situation of the French wine producers from various regions, creatively combining focused investigation with an integrative perspective.

The magnitude of the informal economy has been estimated using either indirect measurement methods that employ proxy indicators or small‐scale household surveys. This paper seeks to provide an analysis of the findings of the first direct survey in an advanced market economy of national business opinion on its magnitude and impacts.

This paper analyses the findings of a UK survey of business opinion on the prevalence of the informal economy in their sector and its impacts on their businesses, namely the Small Business Service's (SBS) 2004/05 Small Business Survey of 7,505 small businesses.

The finding is that 14 per cent of UK small businesses view themselves as negatively affected by the informal economy, with businesses estimating on average that 8 per cent of trade in their sector is conducted on an off‐the‐books basis. The sectors most affected by the informal economy are land transport, construction, the motor vehicle trade, and hotels and restaurants, with fledgling enterprises and businesses in peripheral regions most affected.

This survey records only business perceptions of the size of the informal economy in their sector rather than directly collecting data on the amount of informal work that businesses conduct.

This paper demonstrates that it is wholly feasible to conduct business surveys on the size and impacts of the informal economy and recommends modifications to the SBS survey method to improve data collection.

This paper reports the findings of the first survey in an advanced economy of national business opinion on the size and impacts of the informal economy.

The purpose of this paper is to present a control strategy which uses two independent PID controllers to realize the hovering control for unmanned aerial systems (UASs). In addition, the aim of using two PID controller is to achieve the position control and velocity control simultaneously.

The dynamic of the UASs is mathematically modeled. One PID controller is used for position tracking control, while the other is selected for the vertical component of velocity tracking control. Meanwhile, fuzzy logic algorithm is presented to use the actual horizontal component of velocity to compute the desired position.

Based on this fuzzy logic algorithm, the control error of the horizontal component of velocity tracking control is narrowed gradually to be zero. The results show that the fuzzy logic algorithm can make the UASs hover still in the air and vertical to the ground.

The acquired results are based on simulation not experiment.

This is the first study to use two independent PID controllers to realize stable hovering control for UAS. It is also the first to use the velocity of the UAS to calculate the desired position.

The purpose of this paper is to conduct a comparative analysis between a straight blade (SB) and a curved caudal-fin tidal turbine blade (CB) and to examine the aspects relating to geometry, turbulence modelling, non-dimensional forces lift and power coefficients.

The comparison utilises results obtained from a default horizontal axis tidal turbine with turbine models available from the literature. A computational design method was then developed and implemented for “horizontal axis tidal turbine blade”. Computational fluid dynamics (CFD) results for the blade design are presented in terms of lift coefficient distribution at mid-height blades, power coefficients and blade surface pressure distributions. Moving the CB back towards the SB ensures that the total blade height stays constant for all geometries. A 3D mesh independency study of a “straight blade horizontal axis tidal turbine blade” modelled using CFD was carried out. The grid convergence study was produced by employing two turbulence models, the standard k-ε model and shear stress transport (SST) in ANSYS CFX. Three parameters were investigated: mesh resolution, turbulence model, and power coefficient in the initial CFD, analysis.

It was found that the mesh resolution and the turbulence model affect the power coefficient results. The power coefficients obtained from the standard k-ε model are 15 to 20 per cent lower than the accuracy of the SST model. Further analysis was performed on both the designed blades using ANSYS CFX and SST turbulence model. The variation in pressure distributions yields to the varying lift coefficient distribution across blade spans. The lift coefficient reached its peak between 0.75 and 0.8 of the blade span where the total lift accelerates with increasing pressure before drastically dropping down at 0.9 onwards due to the escalating rotational velocity of the blades.

The work presents a computational design methodological approach that is entirely original. While this numerical method has proven to be accurate and robust for many traditional tidal turbines, it has now been verified further for CB tidal turbines.

The purpose of this paper is to present novel robust fault tolerant control design architecture to detect and isolate spacecraft attitude control actuators and reconfigure to redundant backups to improve the practicality of actuator fault detection.

The Robust Fault Tolerant Control is designed for spacecraft Autonomous Rendezvous and Docking (AR&D) using Lyapunov direct approach applied to non‐linear model. An extended Kalman observer is used to accurately estimate the state of the attitude control actuators. Actuators on all three axes (roll/pitch/yaw) sequentially fail one after another and the robust fault tolerant controller acts to reconfigure to redundant backups to stabilize the spacecrafts and complete the required maneuver.

In the simulations, the roll, pitch and yaw dynamics of the spacecraft are considered and the attitude control actuators failures are detected and isolated. Furthermore, by switching to redundant backups, the guarantee of overall stability performance is demonstrated.

A real time actuator failure detection and reconfiguration process using robust fault tolerant control is applied for spacecraft AR&D maneuvers. Finding an appropriate Lyapunov function for the non‐linear dynamics is not easy and always challenging. Failure of actuators on all three axes at the same time is not considered. It is a very useful approach to solve self‐assembly problems in space, spacecraft proximity maneuvers as well as co‐operative control of planetary vehicles in presence of actuator failures.

An approach has been proposed to detect, isolate and reconfigure spacecraft actuator failures occurred in the spacecraft attitude control system. A Robust Fault Tolerant Control scheme has been developed for the nonlinear AR&D maneuver for two spacecrafts. Failures that affect the control performance characteristics are considered and overall performance is guaranteed even in presence of control actuator failures. The architecture is demonstrated through model‐based simulation.

This study aims at enhancing the performance of a 16-stage axial compressor and improving the operating stability. The adopted approaches for upgrading the compressor are artificial neural network, optimization algorithms and computational fluid dynamics.

The process starts with developing several data sets for certain 2D sections by means of training several artificial neural networks (ANNs) as surrogate models. Afterward, the trained ANNs are applied to the 3D shape optimization along with parametrization of the blade stacking line. Specifying the significant design parameters, a wide range of geometrical variations are considered by implementation of appropriate number of design variables. The optimized shapes are analyzed by applying computational fluid dynamic to obtain the best geometry.

3D optimal results show improvements, especially in the case of decreasing or elimination of near walls corner separations. In addition, in comparison with the base geometry, numerical optimization shows an increase of 1.15 per cent in total isentropic efficiency in the first four stages, which results in 0.6 per cent improvement for the whole compressor, even while keeping the rest of the stages unchanged. To evaluate the numerical results, experimental data are compared with obtained data from simulation. Based on the results, the highest absolute relative deviation between experimental and numerical static pressure is approximately 7.5 per cent.

The blades geometry of an axial compressor used in a heavy-duty gas turbine is optimized by applying artificial neural network, and the results are compared with the base geometry numerically and experimentally.

In the past decades, artificial intelligence (AI)-based hybrid methods have been increasingly applied in construction risk management practices. The purpose of this paper is to review and compile the current AI methods used for cost-risk assessment in the construction management domain in order to capture complexity and risk interdependencies under high uncertainty.

This paper makes a content analysis, based on a comprehensive literature review of articles published in high-quality journals from the years 2008 to 2018. Fuzzy hybrid methods, such as fuzzy-analytical network processing, fuzzy-artificial neural network and fuzzy-simulation, have been widely used and dominated in the literature due to their ability to measure the complexity and uncertainty of the system.

The findings of this review article suggest that due to the limitation of subjective risk data and complex computation, the applications of these AI methods are limited in order to address cost overrun issues under high uncertainty. It is suggested that a hybrid approach of fuzzy logic and extended form of Bayesian belief network (BBN) can be applied in cost-risk assessment to better capture complexity-risk interdependencies under uncertainty.

This study only focuses on the subjective risk assessment methods applied in construction management to overcome cost overrun problem. Therefore, future research can be extended to interpret the input data required to deal with uncertainties, rather than relying solely on subjective judgments in risk assessment analysis.

These results may assist in the management of cost overrun while addressing complexity and uncertainty to avoid chaos in a project. In addition, project managers, experts and practitioners should address the interrelationship between key complexity and risk factors in order to plan risk impact on project cost. The proposed hybrid method of fuzzy logic and BBN can better support the management implications in recent construction risk management practice.

This study addresses the applications of AI-based methods in complex construction projects. A proposed hybrid approach could better address the complexity-risk interdependencies which increase cost uncertainty in project.

Traditionally, industrial power supplies have been exclusively controlled through analog control to sustain high reliability with low cost. However, with the perpetual decrement in cost of digital controllers, the feasibility of a digitally controlled switch mode power supply has elevated significantly. This paper aims to outline the challenges related to the design of digital proportional-integral (PI) controlled synchronous rectifier (SR) buck converter by comparing controller performance in continuous and discrete time. The trapezoidal approximation-based digital PI control is designed for low voltage and high-frequency SR buck converter operating under continuous conduction mode.

The analog and digital controller are designed using a SISO tool of MATLAB. Here, zero-order hold transform is used to convert the transfer function from continuous to discrete time. Frequency and time domain analysis of continuous plant, discrete plant and close loop system is performed. The designed digital PI control is simulated in MATLAB Simulink. The simulated results is also verified on hardware designed around digital signal processing control.

The continuous and discrete control loops are validated with multiple tests in the time and frequency domain. The detailed steady state theoretical analysis and performance of the SR buck converter is presented and verified by simulation. It is found that the delay in digital control loop results in a low phase margin. This phase margin decreases with higher bandwidth. The hardware experiments with the digital control loop are carried out on a 10 W prototype. The chosen parameters for the SR buck converter are found to be optimum for steady and transient state response.

This paper compares the digital and analog control approach of compensator design. It focuses on the implications created at the time of transforming the control design from continuous to discrete time. Further, it also focuses on the selection of parameters such as phase margin, bandwidth and low pass filter.

This paper aims to propose a composite form of the robust disturbance fuzzy control scheme. The proposed method uses the benefits of fuzzy system modeling and Lyapunov direct methods.

The effciency of the control technique was demonstrated with assistance of numerical simulation in control problems of unmanned aerial vehicle (UAV) simulation.

To evaluate the control performance, the comparison of the proposed controller was made with conventional control techniques. The Lyapunov stability theorem has been used to testify for asymptotic stability and convergence of the closed loop system.

Implementation of the control law in the real world environment can be easier due to significant reduction in the fuzzy rules, tuning parameters and computation stages.

Simulation results confirm that the proposed control scheme performs remarkably well in terms of the robustness and disturbance attenuation.