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Book part
Publication date: 15 December 1998

Jianping Wu and Nick Hounsell

The need to provide efficient public transport services in urban areas has led to the implementation of bus priority measures in many congested cities. Much interest has…

Abstract

The need to provide efficient public transport services in urban areas has led to the implementation of bus priority measures in many congested cities. Much interest has recently centred on priority at signal controlled junctions, including the concept of pre-signals, where traffic signals are installed at or near the end of a with-flow bus lane to provide buses with priority access to the downstream junction. Although a number of pre-signals have now been installed in the UK, particularly in London, there has been very little published research into the analysis of benefits and disbenefits to both buses and non-priority vehicles at pre-signalised intersections. This paper addresses these points through the development of analytical procedures which allow pre-implementation evaluation of specific categories of pre-signals.

Details

Mathematics in Transport Planning and Control
Type: Book
ISBN: 978-0-08-043430-8

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Article
Publication date: 14 October 2021

Ankit Kumar Srivastava, A. N. Tiwari and S. N. Singh

This paper aims to accurately estimate harmonics/interharmonics in modern power system. There are several high spectral resolution techniques that have been in use for…

Abstract

Purpose

This paper aims to accurately estimate harmonics/interharmonics in modern power system. There are several high spectral resolution techniques that have been in use for several years like Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT), Prony methods, etc. but these techniques require prior knowledge of number of modes present in the signal. Model Order (MO) estimation techniques have to make a trade-off between accuracy and their speed i.e., computational burden. Therefore, there is always a requirement of a technique that is fast as well as accurate.

Design/methodology/approach

The proposed standard deviation (SD) method eliminates the requirement of energy validation test and analyses the distribution pattern, i.e. standard deviation of eigenvalues to identify the number of modes present in the signal. Signal is reconstructed using estimated modes and reconstruction error is obtained to show accuracy of the proposed estimation.

Findings

Six test synthetic signals as well as one practical signal have been taken for validating the proposed method. The paper shows that proposed methodology has a better accuracy compared to modified exact model order (MEMO) method in high noise environment and takes very less computation time compared to the exact model order (EMO) method.

Practical implications

The proposed method has been practically implemented for harmonic/interharmonic analysis at a sewage treatment plant at GIFT City, Gujarat, India. Apart from this the proposed method is modeled in python-based tool and is run into low-cost Raspberry Pi like hardware to create an onsite as well as remote monitoring device.

Originality/value

SD-based approach for model order estimation is novel to this area. Further, the proposed method is compared with EMO and MEMO under varying noise conditions to check for accuracy and estimation time.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0332-1649

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Article
Publication date: 4 October 2021

Dorian Laurentiu Florea, Cătălin Mihail Barbu and Claudia Cristina Rotea

Drawing on signaling theory, this paper aims to argue in favor of a “placebo outsourcing effect” (POE) consisting of a positive relationship between provider’s bluffing…

Abstract

Purpose

Drawing on signaling theory, this paper aims to argue in favor of a “placebo outsourcing effect” (POE) consisting of a positive relationship between provider’s bluffing and customer satisfaction.

Design/methodology/approach

The authors applied prediction-oriented segmentation SEM on a dyadic sample of 171 outsourcing relationships.

Findings

The authors highlighted two segments that display a form of POE, representing about three-quarters of the customer-provider dyads. The first segment exhibits a positive relationship between the provider’s bluffing and customer satisfaction that is further strengthened by the provider’s reputation and customer’s operational capabilities, while for the other segment, the provider’s bluffing has positive interactions with both operational capabilities and outsourcing experience. These findings show that service providers have reached the bluffing proficiency that enables them to bluff customer firms with varying levels of operational capabilities and outsourcing experience by using the most appealing signals for every type of customer.

Practical implications

Based on the findings, the authors provided to customer firms extensive guidelines to avoid the POE by frustrating service provider’s bluffing proficiency.

Originality/value

This study’s originality resides in the amendment of the disconfirmation paradigm of satisfaction in the outsourcing context by introducing and testing the POE.

Details

Journal of Business & Industrial Marketing, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0885-8624

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Article
Publication date: 20 September 2021

Subimal Chatterjee, Debi P. Mishra, Jennifer JooYeon Lee and Sirajul A. Shibly

Service providers often recommend unnecessary and expensive services to unsuspecting consumers, such as recommending a new part when a simple fix to the old will do, a…

Abstract

Purpose

Service providers often recommend unnecessary and expensive services to unsuspecting consumers, such as recommending a new part when a simple fix to the old will do, a phenomenon known as overprovisioning. The purpose of this paper is to examine to what extent consumers tend to defer their decisions should they suspect that sellers are overproviding services to them and they cannot prevent the sellers from doing so (they lack personal control); and how proper market signals can mitigate such suspicions, restore personal control and reduce deferrals.

Design/methodology/approach

The paper conducts three laboratory experiments. The experiments expose the participants to hypothetical repair scenarios and measure to what extent they suspect that sellers might be overproviding services to them and they feel that they lack the personal control to prevent the sellers from doing so. Thereafter, the experiments expose them to two different market signals, one conveying that the seller is providing quality services (a repair warranty; quality signal) and the other conveying that the seller is taking away any incentives their agents (technicians) may have to overprovide services (the technicians are paid a flat salary; quantity signal). The paper examines how these quality/quantity signals are able to reduce overprovisioning suspicions, restore personal control and reduce decision deferrals.

Findings

The paper has two main findings. First, the paper shows a mediation process at work i.e. suspecting potential overprovisioning by sellers leads consumers to defer their decisions indirectly because they feel that they lack personal control to prevent the sellers from doing so. Second, the paper shows that the quantity signal (flat salary disclosure), but not the quality signal (warranty), is able to mitigate suspicions of overprovisioning, restore personal control and reduce decision deferrals.

Practical implications

The paper suggests that although buyers may rely on quality signals to assure them of superior service, these signals do not guarantee that the quantity of service they are receiving is appropriate. Therefore, sellers will have to send a credible quality signal and a credible quantity signal to the consumers if they wish to tackle suspicions about service overprovision and service quality.

Originality/value

The paper is original in two ways. First, the paper theorizes and tests a mediation process model whereby quality/quantity signals differentially mitigate overprovisioning suspicions, restore personal control and reduce decision deferrals. Second, the paper speaks to the necessity of expanding the traditional signaling literature, designed primarily to detect poor quality hidden in the products/services of lower-quality sellers, to include detecting/solving overprovisioning often hidden in the services provided by higher-quality sellers.

Details

Journal of Consumer Marketing, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0736-3761

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Article
Publication date: 24 September 2021

Qiang Wang, Chen Meng and Cheng Wang

This study aims to reveal the essential characteristics of nonstationary signals and explore the high-concentration representation in the joint time–frequency (TF) plane.

Abstract

Purpose

This study aims to reveal the essential characteristics of nonstationary signals and explore the high-concentration representation in the joint time–frequency (TF) plane.

Design/methodology/approach

In this paper, the authors consider the effective TF analysis for nonstationary signals consisting of multiple components.

Findings

To make it, the authors propose the combined multi-window Gabor transform (CMGT) under the scheme of multi-window Gabor transform by introducing the combination operator. The authors establish the completeness utilizing the discrete piecewise Zak transform and provide the perfect-reconstruction conditions with respect to combined TF coefficients. The high-concentration is achieved by optimization. The authors establish the optimization function with considerations of TF concentration and computational complexity. Based on Bergman formulation, the iteration process is further analyzed to obtain the optimal solution.

Originality/value

With numerical experiments, it is verified that the proposed CMGT performs better in TF analysis for multi-component nonstationary signals.

Details

Engineering Computations, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0264-4401

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Article
Publication date: 29 July 2021

A. Lynn Matthews and Meike Eilert

Authenticity is a complex character that is valued in service contexts. Frontline service employees (FSEs), as both brand representatives and individuals who interact with…

Abstract

Purpose

Authenticity is a complex character that is valued in service contexts. Frontline service employees (FSEs), as both brand representatives and individuals who interact with clients, can signal their authenticity to customers. The purpose of this study is to investigate how FSEs signal their authenticity to customers. The authors investigate authenticity signal themes and develop a typology of how FSEs use these signals in the workplace.

Design/methodology/approach

This research uses a multi-method approach: qualitative data were collected through in-depth interviews with FSE and customers and quantitative data were collected in a follow-up survey using a sample of financial planners.

Findings

Findings from both studies show that FSE can use signals reflecting the display of client-centricity, positive emotions, transparency and disclosure of personal information. A latent profile analysis reveals three authenticity signal profiles, differing in the extent to which FSE uses each of these signals.

Research limitations/implications

This study identifies how FSEs can shape perceptions of authenticity in a service context, thus expanding theory by integrating both personal and brand authenticity perspectives. The findings further demonstrate that authenticity can be signaled on multiple dimensions, reflecting the complex nature of this construct.

Practical implications

The findings from this research can guide managers in developing workplace policies that enable FSEs to display authenticity in various ways to customers. Managers can further use the insights from this research to identify needs for FSE training and development.

Originality/value

The authors create novel insights into how FSEs signal authenticity to customers given their dual roles as individuals and brand representatives. This study offers nuanced insights into different types of signals and their application in a service context.

Details

Journal of Services Marketing, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0887-6045

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Article
Publication date: 9 August 2021

Haijie Yu, Haijun Wei, Daping Zhou, Jingming Li and Hong Liu

This study aims to reconstruct the frictional vibration signal from noise and characterize the running-in process by frictional vibration.

Abstract

Purpose

This study aims to reconstruct the frictional vibration signal from noise and characterize the running-in process by frictional vibration.

Design/methodology/approach

There is a strong correlation between tangential frictional vibration and normal frictional vibration. On this basis, a new frictional vibration reconstruction method combining cross-correlation analysis with ensemble empirical mode decomposition (EEMD) was proposed. Moreover, the concept of information entropy of friction vibration is introduced to characterize the running-in process.

Findings

Compared with the wavelet packet method, the tangential friction vibration and the normal friction vibration reconstructed by the method presented in this paper have a stronger correlation. More importantly, during the running-in process, the information entropy of friction vibration gradually decreases until the equilibrium point is reached, which is the same as the changing trend of friction coefficient, indicating that the information entropy of friction vibration can be used to characterize the running-in process.

Practical implications

The study reveals that the application EEMD method is an appropriate approach to reconstruct frictional vibration and the information entropy of friction vibration represents the running-in process. Based on these results, a condition monitoring system can be established to automatically evaluate the running-in state of mechanical parts.

Originality/value

The EEMD method was applied to reconstruct the frictional vibration. Furthermore, the information entropy of friction vibration was used to analysis the running-in process.

Details

Industrial Lubrication and Tribology, vol. 73 no. 6
Type: Research Article
ISSN: 0036-8792

Keywords

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Article
Publication date: 9 August 2021

Hrishikesh B Vanjari and Mahesh T Kolte

Speech is the primary means of communication for humans. A proper functioning auditory system is needed for accurate cognition of speech. Compressed sensing (CS) is a…

Abstract

Purpose

Speech is the primary means of communication for humans. A proper functioning auditory system is needed for accurate cognition of speech. Compressed sensing (CS) is a method for simultaneous compression and sampling of a given signal. It is a novel method increasingly being used in many speech processing applications. The paper aims to use Compressive sensing algorithm for hearing aid applications to reduce surrounding noise.

Design/methodology/approach

In this work, the authors propose a machine learning algorithm for improving the performance of compressive sensing using a neural network.

Findings

The proposed solution is able to reduce the signal reconstruction time by about 21.62% and root mean square error of 43% compared to default L2 norm minimization used in CS reconstruction. This work proposes an adaptive neural network–based algorithm to enhance the compressive sensing so that it is able to reconstruct the signal in a comparatively lower time and with minimal distortion to the quality.

Research limitations/implications

The use of compressive sensing for speech enhancement in a hearing aid is limited due to the delay in the reconstruction of the signal.

Practical implications

In many digital applications, the acquired raw signals are compressed to achieve smaller size so that it becomes effective for storage and transmission. In this process, even unnecessary signals are acquired and compressed leading to inefficiency.

Social implications

Hearing loss is the most common sensory deficit in humans today. Worldwide, it is the second leading cause for “Years lived with Disability” the first being depression. A recent study by World health organization estimates nearly 450 million people in the world had been disabled by hearing loss, and the prevalence of hearing impairment in India is around 6.3% (63 million people suffering from significant auditory loss).

Originality/value

The objective is to reduce the time taken for CS reconstruction with minimal degradation to the reconstructed signal. Also, the solution must be adaptive to different characteristics of the signal and in presence of different types of noises.

Details

World Journal of Engineering, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1708-5284

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Article
Publication date: 8 August 2016

Faris Elasha and David Mba

– The purpose of this paper is to suggest new method for improving the condition indicators (CIs) used in health and usage monitoring system based on signal separation of gears.

Abstract

Purpose

The purpose of this paper is to suggest new method for improving the condition indicators (CIs) used in health and usage monitoring system based on signal separation of gears.

Design/methodology/approach

The research method is based on employing signal separation techniques to improve gears signal and fault signature. The signal separation is based on adaptive filters concept.

Findings

CIs estimated for the deterministic part of vibration signal show higher sensitivity to gears faults in comparison to indicators estimated based on the original signal. This method proposed could enhance early fault detection in gears, particularly for those applications where strong background noise from other sources in the machine masks the characteristics fault components.

Originality/value

The contribution of this research is improving the CIs currently used for helicopter gearboxes. As consequence the safe operation and availability will be improved.

Details

International Journal of Structural Integrity, vol. 7 no. 4
Type: Research Article
ISSN: 1757-9864

Keywords

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Article
Publication date: 16 October 2009

Junguo Wang, Jianzhong Zhou and Bing Peng

The purpose of this paper is to detect the periodic signal under strong noise background, and estimate its amplitude/phase.

Abstract

Purpose

The purpose of this paper is to detect the periodic signal under strong noise background, and estimate its amplitude/phase.

Design/methodology/approach

Melnikov method is adopted as calculating the threshold value when chaos occurs, and the detected signal is taken as a system parameter. The system's output state is changed if the parameter has a slight change near the threshold. Meantime, the phase of system's output is recognized to judge whether the output state changes, and the signal parameter is estimated according to the necessary condition.

Findings

A small periodic signal in noise can be detected by Duffing oscillator via a transition from chaotic motion to periodic motion.

Research limitations/implications

The paper shows how to calculate the amplitude/phase in low signal‐to‐noise ratios.

Practical implications

The Duffing system is sensitive to the weak periodic signal and has definite immunity to noise, so it is easy to construct a system composed of many oscillators that could process complex signals, even though the environmental noise is intense.

Originality/value

This paper presents a nonlinear method for detecting and extracting the weak signal.

Details

Kybernetes, vol. 38 no. 10
Type: Research Article
ISSN: 0368-492X

Keywords

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