This study includes process planning of prismatic parts by means of an expert system. On the computer controlled machine tools, operation methods and mostly used process types in…
Abstract
This study includes process planning of prismatic parts by means of an expert system. On the computer controlled machine tools, operation methods and mostly used process types in manufacture are drawn with solid modelling. Feature recognition process is achieved with the “B‐Rreb” modelling method to give vectorel direction knowledge and adjacent relationships of surface using the STEP standard interface program. Furthermore, operation type and sequence of operation are defined for the prismatic parts by using the databases achieved from the feature recognition module. This developed method was prepared on an IBM compatible PC by using C++ programming language for this purpose and is explained with a sample.
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Kurtulus Karamustafa and Sevki Ulama
Most of the European Mediterranean countries are suffering from seasonality and the problems caused by it. By applying different methods, this study proposes to measure…
Abstract
Purpose
Most of the European Mediterranean countries are suffering from seasonality and the problems caused by it. By applying different methods, this study proposes to measure seasonality in a Mediterranean country, Turkey. Studying seasonality and its measurement with the comparison of different methods could first provide useful guidelines for the countries, which may have similar problems, and could also broaden the current view in the related literature since the focus is also on the comparison of the widely used methods in the literature.
Design/methodology/approach
The study depends on the current literature and makes evaluations based on the secondary data acquired from the statistical publications of The Turkish Ministry of Culture and Tourism.
Findings
The findings reveal that none of the methods is superior to any other. They complement the weaknesses of one another. Therefore, it is suggested that destinations, when measuring their seasonality, should evaluate seasonality by applying different methods in order to give a proper decision to solve the problem caused by seasonality.
Originality/value
The study contributes to the seasonality literature by employing different measurement methods in a holistic way. It reveals differences and similarities among the different methods, using the case of a Mediterranean country, Turkey.
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Akhil Garg and Kang Tai
Generalization ability of genetic programming (GP) models relies highly on the choice of parameter settings chosen and the fitness function used. The purpose of this paper is to…
Abstract
Purpose
Generalization ability of genetic programming (GP) models relies highly on the choice of parameter settings chosen and the fitness function used. The purpose of this paper is to conduct critical survey followed by quantitative analysis to determine the appropriate parameter settings and fitness function responsible for evolving the GP models with higher generalization ability.
Design/methodology/approach
For having a better understanding about the parameter settings, the present work examines the notion, applications, abilities and the issues of GP in the modelling of machining processes. A gamut of model selection criteria have been used in fitness functions of GP, but, the choice of an appropriate one is unclear. In this work, GP is applied to model the turning process to study the effect of fitness functions on its performance.
Findings
The results show that the fitness function, structural risk minimization (SRM) gives better generalization ability of the models than those of other fitness functions.
Originality/value
This study is of its first kind where two main contributions are listed addressing the need of evolving GP models with higher generalization ability. First is the survey study conducted to determine the parameter settings and second, the quantitative analysis for unearthing the best fitness function.
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Ghassan H. Mardini and Fathia Elleuch Lahyani
Using agency theory and impression management theory, this study examines the impact of financial performance (FP) and corporate governance (CG) mechanisms on the extent of…
Abstract
Purpose
Using agency theory and impression management theory, this study examines the impact of financial performance (FP) and corporate governance (CG) mechanisms on the extent of intellectual capital disclosures (ICDs) and the three components within the CEO statement – human capital (HC), structural capital (SC) and relational capital (RC).
Design/methodology/approach
This study employs a sample of non-financial SPF-120 French listed firms to capture the relevant variables; it collects data for 2010–2017, using a panel data technique to run the random effects regressions.
Findings
The study finds that FP, measured using both market (Tobin's q) and accounting (return on equity and return on assets) indicators, plays a vital role in the extent of ICDs and the three components in the CEO statement published by SPF-120 companies. This confirms its impact on the decision-making needs of stakeholders. Among the CG mechanisms, this study finds that cultural diversity and gender diversity affect some ICD components. Moreover, CEO characteristics such as age, education and role duality affect ICD, while institutional ownership drives the extent of such disclosures.
Practical implications
Our findings have comprehensive implications for managers of French listed firms, the Autorité des Marchés Financiers, and stakeholders in general.
Originality/value
This study provides significant insights by investigating the impact of FP, CG and company characteristics on the extent of the ICDs published in CEO statements.
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Examines the fourteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects…
Abstract
Examines the fourteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.
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Youguo He, Chuandao Lu, Jie Shen and Chaochun Yuan
The purpose of this study is to improve vehicles’ brake stability, the problem of constraint control for an antilock braking system (ABS) with asymmetric slip ratio constraints is…
Abstract
Purpose
The purpose of this study is to improve vehicles’ brake stability, the problem of constraint control for an antilock braking system (ABS) with asymmetric slip ratio constraints is concerned. A nonlinear control method based on barrier Lyapunov function (BLF) is proposed not only to track the optimal slip ratio but also to guarantee no violation on slip ratio constraints.
Design/methodology/approach
A quarter vehicle braking model and Burckhardt’s tire model are considered. The asymmetric BLF is introduced into the controller for solving asymmetric slip ratio constraint problems.
Findings
The proposed controller can implement ABS zero steady-state error tracking of the optimal wheel slip ratio and make slip ratio constraints flexible for various runway surfaces and runway transitions. Simulation and experimental results show that the control scheme can guarantee no violation on slip ratio constraints and avoid self-locking.
Originality/value
The slip rate equation with uncertainties is established, and BLF is introduced into the design process of the constrained controller to realize the slip rate constrained control.
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Maciej Tabaszewski and Czeslaw Cempel
The observed diagnostic symptoms are often characterized by local fluctuations of their values. Hence, instead of direct observation of symptoms it is worth observing their grey…
Abstract
Purpose
The observed diagnostic symptoms are often characterized by local fluctuations of their values. Hence, instead of direct observation of symptoms it is worth observing their grey models and research similarity between life curves, which can enable to guess the nature of wear. The purpose of this paper is to find useful measures of similarity of diagnostics symptoms modeled by GM(1,1).
Design/methodology/approach
Measures of similarity may be used to determine the character of wear of the diagnosed object by way of comparison with known examples, which have previously been obtained and identified. A methodology for creation of such comparisons based on pre-smoothing by means of a GM(1,1) model with rolling window has been proposed. The process of smoothing enables to eliminate local fluctuations of a symptom. Their existence makes it difficult to compare symptoms. Application of a rolling window enables in turn to map the symptom properly, which may be difficult in the case of relatively short period of accelerated wear and changes of symptom values. To compare the life curves it is also necessary to normalize the life curves, so that they are represented by the same number of measurements (compression or extension of the measure of operation).
Findings
The paper concerns the similarity measures for symptom life curves obtained during vibration monitoring of fan mills working at a heat and power station. Similarity measures of symptoms were proposed and applied to the acquired data from the machines.
Practical implications
The method of symptom modeling and life curve comparing can be used to discover type of wear of the machine and eventually estimation of the remaining useful life.
Originality/value
The proposed method is very important for development of condition monitoring.
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It is possible to see effective use of Artificial Intelligence-based systems in many fields because it easily outperforms traditional solutions or provides solutions for the…
Abstract
It is possible to see effective use of Artificial Intelligence-based systems in many fields because it easily outperforms traditional solutions or provides solutions for the problems not previously solved. Prediction applications are a widely used mechanism in research because they allow for forecasting of future states. Logical inference mechanisms in the field of Artificial Intelligence allow for faster and more accurate and powerful computation. Machine Learning, which is a sub-field of Artificial Intelligence, has been used as a tool for creating effective solutions for prediction problems.
In this chapter the authors will focus on employing Machine Learning techniques for predicting data for future states of economic using techniques which include Artificial Neural Networks, Adaptive Neuro-Fuzzy Inference System, Dynamic Boltzmann Machine, Support Vector Machine, Hidden Markov Model, Bayesian Learning on Gaussian process model, Autoregressive Integrated Moving Average, Autoregressive Model (Poggi, Muselli, Notton, Cristofari, & Louche, 2003), and K-Nearest Neighbor Algorithm. Findings revealed positive results in terms of predicting economic data.
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Yuexin Zhang, Lihui Wang and Yaodong Liu
To reduce the effect of parameter uncertainties and input saturation on path tracking control for autonomous combine harvester, a path tracking controller is proposed, which…
Abstract
Purpose
To reduce the effect of parameter uncertainties and input saturation on path tracking control for autonomous combine harvester, a path tracking controller is proposed, which integrates an adaptive neural network estimator and a saturation-aided system.
Design/methodology/approach
First, to analyze and compensate the influence of external factors, the vehicle model is established combining a dynamic model and a kinematic model. Meanwhile, to make the model simple, a comprehensive error is used, weighting heading error and position error simultaneously. Second, an adaptive neural network estimator is presented to calculate uncertain parameters which eventually improve the dynamic model. Then, the path tracking controller based on the improved dynamic model is designed by using the backstepping method, and its stability is proved by the Lyapunov theorem. Third, to mitigate round-trip operation of the actuator due to input saturation, a saturation-aided variable is presented during the control design process.
Findings
To verify the tracking accuracy and environmental adaptability of the proposed controller, numerical simulations are carried out under three different cases, and field experiments are performed in harvesting wheat and paddy. The experimental results demonstrate the tracking errors of the proposed controller that are reduced by more than 28% with contrast to the conventional controllers.
Originality/value
An adaptive neural network-based path tracking control is proposed, which considers both parameter uncertainties and input saturation. As far as we know, this is the first time a path tracking controller is specifically designed for the combine harvester with full consideration of working characteristics.
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Manlu Liu, Rui Lin, Maotao Yang, Anaid V. Nazarova and Jianwen Huo
The characteristics of spherical robots, such as under-drive, non-holonomic constraints and strong coupling, make it difficult to establish its motion control model accurately. To…
Abstract
Purpose
The characteristics of spherical robots, such as under-drive, non-holonomic constraints and strong coupling, make it difficult to establish its motion control model accurately. To improve the anti-interference performance of spherical robots in practical engineering, this paper proposes a spherical robot motion controller based on auto-disturbance rejection control (ADRC) with parameter tuning.
Design/methodology/approach
This paper considers the influences of the spherical shell, internal frame and pendulum on the movement of the spherical robot during the rotation to establish the multi-body dynamics model of the XK-I spherical robot. Due to the serious coupling problem of the dynamic model, the motion control state equation is constructed using linearization and decoupling. The XK-I spherical robot PSO-ADRC motion controller with parameter tuning function is designed by combining the state equation with the particle swarm optimization (PSO) algorithm. Finally, experiments are performed to evaluate the feasibility of PSO-ADRC in an actual case compared to ADRC, PSO-PID and PID.
Findings
By analyzing the required time to reach the expected value, the control stability and the fluctuation range of the standard deviation after reaching the expected value, the superiority of PSO-ADRC to ADRC, PSO-PID and PID is demonstrated in terms of the speed and anti-interference ability.
Practical implications
The proposed method can be applied to the robot control field.
Originality/value
A parameter-tuning method for auto-disturbance-rejection motion control of the spherical robot is proposed. According to the experimental results, the anti-interference ability of the spherical robot moving on uneven ground is improved. Therefore, it provides a foundation for the autonomous environmental monitoring of the spherical robot equipped with sensors.