Search results

The purpose of this paper is to deeply study and compare the dual and single hedging strategy, from the direct and cross hedging perspective.

The authors not only first consider the dual hedge of integrated risks in this oil prices and foreign exchange rates setting but also make a novel comparison between the dual and single hedging strategy from a direct and cross hedging perspective. In total, six econometric models (to conduct one-step-ahead out-of-sample rolling estimation of the optimal hedge ratio) and two hedging performance criteria are employed in two different hedging backgrounds (direct and cross hedging).

Results show that in the direct hedging background, a dual hedge cannot outperform the single hedge. But in the cross dual hedging setting, a dual hedge performs much better, possibly because the dual hedge brings different levels of advantages and disadvantages in the two different settings and the superiority of the dual hedge is more obvious in the cross dual hedging setting.

The existing literature that deals with oil prices and foreign exchange rates mostly concentrates on their relationship and comovements, while the dual hedge of integrated risks in this setting remains underresearched. Besides, the existing literature that deals with dual hedge gets its conclusions only based on a single specific background (direct or cross hedging) and lacks deeper investigation. In this paper, the authors expand the width and depth of the existing literature. Results and implications are revealing.

The purpose of this paper is to develop a familiarity analysis of resistive-capacitive (RC) network active circuit operating with unfamiliar low-pass (LP) type negative group delay (NGD) behavior. The design method of NGD circuit is validated by simulation with commercial tool and experimental measurement.

The present research work methodology is structured in three main parts. The familiarity theory of RC-network LP-NGD circuit is developed. The LP-NGD circuit parameters are expressed in function of the targeted time-advance. Then, the feasibility study is based on the theory, simulation and measurement result comparisons.

The RC-network based LP-NGD proof of concept is validated with −1 and −0.5 ms targeted time-advances after design, simulation, test and characterized. The LP-NGD circuit unity gain prototype presents NGD cut-off frequencies of about 269 and 569 Hz for the targeted time-advances, −1 and −0.5 ms, respectively. Bi-exponential and arbitrary waveform signals were tested to verify the targeted time-advance.

The performance of the unfamiliar LP-NGD topology developed in the present study is limited by the parasitic elements of constituting lumped components.

The NGD circuit enables to naturally reduce the undesired delay effect from the electronic and communication systems. The NGD circuit can be exploited to reduce the delay induced by electronic devices and system.

As social impacts of the NGD circuit application, the NGD function is one of prominent solutions to improve the technology performances of future electronic device in term of communication aspect and the transportation system.

The originality of the paper concerns the theoretical approach of the RC-network parameters in function of the targeted time-advance and the input signal bandwidth. In addition, the experimental results are also particularly original.

During the powder bed fusion process, thermal distortion is one big problem owing to the thermal stress caused by the high cooling rate and temperature gradient. For the purpose of avoiding distortion caused by internal residual stresses, support structures are used in most selective laser melting (SLM) process especially for cantilever beams because they can assist the heat dissipation. Support structures can also help to hold the work piece in its place and reduce volume of the printing materials. The mitigation of high thermal gradients during the manufacturing process helps to reduce thermal distortion and thus alleviate cracking, curling, delamination and shrinkage. Therefore, this paper aims to study the displacement and residual stress evolution of SLMed parts.

The objective of this study was to examine and compare the distortion and residual stress properties of two cantilever structures, using both numerical and experimental methods. The part-scale finite element analysis modeling technique was applied to numerically analyze the overhang distortions, using the layer-by-layer model for predicting a part scale model. The validation experiments of these two samples were built in a SLM platform. Then average displacement of the four tip corners and residual stress on top surface of cantilever beams were tested to validate the model.

The validation experiments results of average displacement of the four tip corners and residual stress on top surface of cantilever beams were tested to validate the model. It was found that they matched well with each other. From displacement and residual stress standpoint, by introducing two different support structure, two samples with the same cantilever beam can be successfully printed. In terms of reducing wasted support materials, print time and high surface quality, sample with less support will need less post-processing and waste energy.

Numerical modeling in this work can be a very useful tool to parametrically study the feasibility of support structures of SLM parts in terms of residual stresses and deformations. It has the capability for fast prediction in the SLMed parts.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

As Chinese massage is increasingly popular, many physicians are needed these days. In order to promote the experience and skills of experts and reduce labour intensity during massage, a massage robot, which could reproduce the expert techniques with individualized manipulation parameters and enhanced safety control strategies, is presented in this paper.

The kinematic and force features of key massage techniques, such as Thumb Kneading, Pressing, Rolling, Vibrating and Pinching, are summarized by analyzing the massage processes of expert physicians, and a mathematical model for robotic massage is established. With safety issues taken into account, the overall system structure of the massage robot is proposed. The system generally consists of a positioning platform and a massage end‐effector which implements the massage techniques, and the end‐effector is further divided into a parallel mechanism and a massage hand to accommodate different techniques. Visual tracking is used for positioning acupuncture points by recognizing markers on a massage vest worn by the patient. A pain threshold value is introduced to individualize therapy schemes and a force‐position control method based on the pain threshold is presented.

VAS (Visual Analogue Scale) tests for lumbar muscle strain are carried out using the massage robot, and the treatment effect of the massage robot based on traditional Chinese massage therapy theory is initially validated.

The treatment effect of the massage robot needs to be assessed clinically for more occasions and more clinical experiments will be conducted, to optimize the configuration and control strategy to meet the clinical needs in future work.

The robotic massage system presented in this paper is acting on acupuncture points based on traditional Chinese massage therapy theory, with human manipulation techniques reproduced and expert experiences incorporated. The massage robot can take the place of a massager to perform Chinese massage. Most of the massage robotic systems published in the world perform only one massage technique and the whole massage process is not completely considered. By comparison, the authors' massage robot could perform five techniques. Furthermore, the authors have designed the procedure of robotic massage specifically for patients who suffer from lumbar muscle strain.

The purpose of this paper is to investigate Chinese food retailers' positioning strategies. Specifically, retail segments and critical factors related to the nature of the food supplier relationships that may be influenced by the positioning strategies are investigated.

The retail markets in Guangzou and Chengdu are investigated. Data are collected by means of observation and survey and then combined in the analyses. Observational research (i.e. expert assessments) is conducted in 152 retail outlets in order to assess their positioning strategies. The purchasing managers in the same retail outlets are personally interviewed by means of structured questionnaires.

A three‐cluster solution for the positioning strategies is revealed: down‐market stores, middle‐range stores, and up‐market stores. The annual sales and the number of self‐service counters are highest among up‐market retailers. They are also typically joint ventures, supermarkets and department stores, and members of a retail chain. A broad range of brands and products and also marketing support from the suppliers are most important for the up‐market stores.

The study is limited to two regional retail markets and should therefore be cross‐validated with other retail sectors and markets. Thumbnail sketches of the retailer segments enable food suppliers to make better and more informed decisions about how to position their product offer and marketing mix.

Although positioning strategies are at the core of modern marketing, relatively little research has been conducted addressing how retailers in general and Chinese retailers specifically include their retail buying behaviour and structural characteristics in the positioning strategy. This study contributes to filling this gap in knowledge.

To solve the path planning problem of the intelligent driving vehicular, this paper designs a hybrid path planning algorithm based on optimized reinforcement learning (RL) and improved particle swarm optimization (PSO).

First, the authors optimized the hyper-parameters of RL to make it converge quickly and learn more efficiently. Then the authors designed a pre-set operation for PSO to reduce the calculation of invalid particles. Finally, the authors proposed a correction variable that can be obtained from the cumulative reward of RL; this revises the fitness of the individual optimal particle and global optimal position of PSO to achieve an efficient path planning result. The authors also designed a selection parameter system to help to select the optimal path.

Simulation analysis and experimental test results proved that the proposed algorithm has advantages in terms of practicability and efficiency. This research also foreshadows the research prospects of RL in path planning, which is also the authors’ next research direction.

The authors designed a pre-set operation to reduce the participation of invalid particles in the calculation in PSO. And then, the authors designed a method to optimize hyper-parameters to improve learning efficiency of RL. And then they used RL trained PSO to plan path. The authors also proposed an optimal path evaluation system. This research also foreshadows the research prospects of RL in path planning, which is also the authors’ next research direction.

The National Audit Office of the People’s Republic of China issued 38 auditing standards and guidelines on 1 January 1997. This was the culmination of a variable historical development during which audit activity was either emphasised or downplayed altogether. With the open door policy and the socialist market economy, audit is again very much back on the agenda. Audit independence is a cornerstone of this great auditing leap forward, with CPA firms in a supporting role. There is a need to train up auditors to assume their role of responsibility in an economy which has huge growth potential, and which excites world‐wide interest.

The use of structured literature review methods like bibliometric analysis is growing in the management fields, but there is limited knowledge on how they can be facilitated by technology. Hence, we conducted a broad overview of software tools, their roles, and limitations in structured (bibliometric) literature reviewing activities. Subsequently, we show that several software tools are freely available to aid in searching the literature, identifying/ extracting relevant publications, screening/assessing quality of the extracted data, and performing analyses to generate insights from the literature. However, their applications may be confronted with several challenges such as limited analytical and functional capabilities, inadequate technological skills of researchers, and the fact that the researcher's insights are still needed to generate compelling conclusions from the results produced by software tools. Consequently, we contribute toward advancing the methodologies for performing structured reviews by providing a comprehensive and updated overview of the knowledge base of key technological software tools and the conduct of structured or bibliometric literature reviews.

Bearings play a critical role in the reliable operation of induction machines, and their failure can lead to significant operational challenges and downtime. Detecting and diagnosing these defects is imperative to ensure the longevity of induction machines and preventing costly downtime. The purpose of this paper is to develop a novel approach for diagnosis of bearing faults in induction machine.

To identify the different fault states of the bearing with accurately and efficiently in this paper, the original bearing vibration signal is first decomposed into several intrinsic mode functions (IMFs) using variational mode decomposition (VMD). The IMFs that contain more noise information are selected using the Pearson correlation coefficient. Subsequently, discrete wavelet transform (DWT) is used to filter the noisy IMFs. Second, the composite multiscale weighted permutation entropy (CMWPE) of each component is calculated to form the features vector. Finally, the features vector is reduced using the locality-sensitive discriminant analysis algorithm, to be fed into the support vector machine model for training and classification.

The obtained results showed the ability of the VMD_DWT algorithm to reduce the noise of raw vibration signals. It also demonstrated that the proposed method can effectively extract different fault features from vibration signals.

This study suggested a new VMD_DWT method to reduce the noise of the bearing vibration signal. The proposed approach for bearing fault diagnosis of induction machine based on VMD-DWT and CMWPE is highly effective. Its effectiveness has been verified using experimental data.