Decentralized Networked Control System Design Using Takagi-Sugeno (TS) Fuzzy Approach

This paper proposes a new method for control of continuous large-scale systems where the measures and control functions are distributed on calculating members which can be shared with other applications and connected to digital network communications.At first, the nonlinear large-scale system is described by a Takagi-Sugeno(TS) fuzzy model. After that, by using a fuzzy LyapunovKrasovskii functional, sufficient conditions of asymptotic stability of the behavior of the decentralized networked control system(DNCS),are developed in terms of linear matrix inequalities(LMIs). Finally, to illustrate the proposed approach, a numerical example and simulation results are presented.     

Discrimination between accelerated life models via Approximate Bayesian Computation

Accelerated life testing (ALT) is widely used in high-reliability product estimation to get relevant information about an item's performance and its failure mechanisms. To analyse the observed ALT data, reliability practitioners need to select a suitable accelerated life model based on the nature of the stress and the physics involved. A statistical model consists of (i) a lifetime distribution that represents the scatter in product life and (ii) a relationship between life and stress. In practice, several accelerated life models could be used for the same failure mode and the choice of the best model is far from trivial. For this reason, an efficient selection procedure to discriminate between a set of competing accelerated life models is of great importance for practitioners. In this paper, accelerated life model selection is approached by using the Approximate Bayesian Computation (ABC) method and a likelihood-based approach for comparison purposes. To demonstrate the efficiency of the ABC method in calibrating and selecting accelerated life model, an extensive Monte Carlo simulation study is carried out using different distances to measure the discrepancy between the empirical and simulated times of failure data. Then, the ABC algorithm is applied to real accelerated fatigue life data in order to select the most likely model among five plausible models. It has been demonstrated that the ABC method outperforms the likelihood-based approach in terms of reliability predictions mainly at lower percentiles particularly useful in reliability engineering and risk assessment applications. Moreover, it has shown that ABC could mitigate the effects of model misspecification through an appropriate choice of the distance function.     

3D Target Scale Estimation and Target Feature Separation for Size Preserving Tracking in PTZ Video

To achieve size preserving tracking, in addition to controlling the camera’s pan and tilt motions to keep the object of interest in the camera’s field of view (FOV), the camera’s focal length is adjusted automatically to compensate for the changes in the target’s image size caused by the relative motion between the camera and the target. The estimation accuracy of these changes determines the effectiveness of the resulting zoom control. The existing method of choice for real-time target scale estimation applies structure from motion (SFM) based on the weak perspective projection model. In this paper we propose a target scale estimation algorithm with a linear solution based on the more advanced paraperspective projection model, which improves the accuracy of scale estimation by considering center offset. Another key issue in SFM based algorithms is the separation of target and background features, especially when composite camera (pan/tilt/zoom) and target motions are involved. This paper designs a fast target feature separation/grouping algorithm, the 3D affine shape method. The resulting separation automatically adapts to the target’s 3D geometry and motion and is able to accommodate a large amount of off-plane rotation, which most existing separation/grouping algorithms find difficult to achieve. Experimental results illustrate the effectiveness of the proposed scale estimation and feature separation algorithms in tracking translating and rotating objects with a PTZ camera while preserving their sizes. In comparison with the leading size preserving tracking algorithm described by Tordoff and Murray, our algorithm is able to reduce the cumulative tracking error significantly from 17.4% to 3.3%.     

A Case‐Based Reasoning system for complex medical diagnosis

A Case‐Based Reasoning (CBR) system for medical diagnosis mimics the way doctors make a diagnosis. Given a new case, its accuracy in practice depends on successful retrieval of similar cases. CBR systems have had some success in dealing with simple diseases because of the robustness of their case base. However, their diagnostic accuracy suffers when dealing with complex diseases particularly those that involve multiple domains in medicine. An example of such a condition is Premenstrual syndrome (PMS) as it falls under both gynaecology and psychiatry. To address this issue, the paper proposes a CBR‐based expert system that uses the K‐nearest neighbour (KNN) algorithm to search k similar cases based on the Euclidean distance measure. The novelty of the system is in the design of a flexible auto‐set tolerance (T), which serves as a threshold to extract cases for which similarities are greater than the assigned value of T. A prototype software tool with a menu‐driven Graphical User Interface (GUI) has been developed for case input, analysis of results, and case adaptation within the system. Finally, the performance of the tool has been checked on a set of real‐world PMS cases.     

Effect of annealing time and substrates nature on the physical properties of CuSbS2 thin films

In this study, the annealing time and substrates nature effects on the physical properties of CuSbS₂ thin films were investigated. CuSbS₂ thin films were prepared on various substrates via thermal evaporation technique. The as^_deposited films were annealed in air for 60 and 120 min at 250 °C. The atomic force microscope micrographs of as^_made and annealed thin films show that the surface morphology is affected by annealing time and substrate variation. X^_ray diffraction results show that crystallinity increased with annealing time. The microstructure parameters: crystallite size and dislocation density were calculated. The optical properties were obtained from the analysis of the experimental recorded transmittance and reflectance spectral data over the wavelength range 300–1800 nm. High absorption coefficients (10⁵–10⁶ cm^?1) are reached. Values of E_g are close to the theoretical optimum for efficient conversion of solar radiation into electrical power making the material suitable for photovoltaic applications.     

Growth and vacuum post-annealing effect on the properties of the new absorber CuSbS2 thin films

Post-growth treatments in vacuum atmosphere were performed on CuSbS₂ films prepared by the single-source thermal evaporation method on glass substrates. The films were annealed in vacuum atmosphere for 2 h in temperature range 130-200 °C. The effect of this thermal treatment on the structural, optical and electrical properties of the films was studied. X-ray diffraction (XRD) patterns indicated that the films exhibited an amorphous structure for annealing temperature below 200 °C and a polycrystalline structure with CuSbS₂ principal phase. For the films annealed at temperatures below 200 °C one direct optical transition in range 1.8-2 eV was found. For the films annealed at 200 °C, two optical direct transitions emerged at 1.3 and 1.79 eV corresponding to the CuSbS₂ and Sb₂S₃ values respectively. The electrical measurements showed a conversion from low resistivities (3.10^− 2-9.10^− 2) Ω cm for the samples annealed at temperatures below 200 °C to relatively high resistivities (2 Ω cm) for the samples annealed at 200 °C. In all cases the samples exhibited p-Ztype conductivity.     

Modelling of heat and mass transfer in a tunnel dryer

This work presents a numerical model for heat and mass transfer of granular products in a fixed-bed tunnel dryer. The drying process is simulated under real operating conditions based on a thin layer model and experimental drying kinetics. A simplified heat and mass transfer numerical model is developed based on the governing equations and the drying rate of a thin layer bed of granular products.The obtained system of non-linear partial differential equations is numerically solved by a finite volume method. The turbulent airflow and granular bed convection coefficient as well as the effective conductivity are estimated using the turbulent airflow over flat-plate correlations. Simulations are compared with experimental data from drying of grapes in a thin layer model.In order to study the effects of the air inlet conditions on the relative moisture content and the drying time and therefore to optimise the tunnel dryer operation, the influences of different parameters essentially the air flow characteristics and the fixed-bed dryer length are examined. The numerical code allows establishing the drying front propagation for several operating conditions.     

The ToxicFarm Integrated Cooperation Framework for Virtual Teams

Developing a collaboration solution, that scales to an entire organization, that offers an integrated collection of cooperation tools, that is general enough to address a large range of applications, and that is easy to deploy for most people, is still an open challenge. This paper presents ToxicFarm services that are an integral part of a framework for hosting Internet virtual teams. The originality of this work is in providing a synthesis between contributions from different domains, including version management in software engineering, process management in data engineering, and awareness in groupware tools. The paper describes the overall services offered, discusses design choices for their integration and implementation, presents relations with existing work and describes their use in several emerging e-business application domains, such as e-finance, e-learning and e-telecom.     

Formation,rapid thermal oxidation and passivation of solar grade silicon nanowires for advanced photovoltaic applications

Uniform and regular silicon nanowires (SiNWs) arrays are fabricated on both sides of solar grade silicons (SiGS) by silver assist-electrochemical etching. SiNWs arrays exhibit an excellent antireflection character with an overall reflectance of 2% in the range from 300 to 1000 nm. More importantly, the effective lifetimes of the symmetric SiNWs/Si structures decreased due to the high densities of dangling bonds and surface defects. Surface passivation to overcome lifetime degradation is realized by means of rapid thermal oxidation (RTO). Following rapid oxidation, Fourier Transform Infrared spectroscopy reveals that oxygen diffusion is enhanced inside silicon nanowires where the morphological structure is preserved during RTO. Moreover, it is shown that even the rapid thermal oxidation process is not effective to recover initial τ_eff due to the high density of imperfections involved during nanowires formation and the contamination level induced by silver. The interdiffusion between residual silver and metal contaminants in the core of the nanowire can probably limit the passivation effect due to the segregation of metal atoms at SiO₂ and to the redistribution of both impurities across the wire.     

Gray-level grouping (GLG): an automatic method for optimized image contrast enhancement--Part II: the variations.

This is Part II of the paper, "Gray-Level Grouping (GLG): an Automatic Method for Optimized Image Contrast Enhancement". Part I of this paper introduced a new automatic contrast enhancement technique: gray-level grouping (GLG). GLG is a general and powerful technique, which can be conveniently applied to a broad variety of low-contrast images and outperforms conventional contrast enhancement techniques. However, the basic GLG method still has limitations and cannot enhance certain classes of low-contrast images well, e.g., images with a noisy background. The basic GLG also cannot fulfill certain special application purposes, e.g., enhancing only part of an image which corresponds to a certain segment of the image histogram. In order to break through these limitations, this paper introduces an extension of the basic GLG algorithm, selective gray-level grouping (SGLG), which groups the histogram components in different segments of the grayscale using different criteria and, hence, is able to enhance different parts of the histogram to various extents. This paper also introduces two new preprocessing methods to eliminate background noise in noisy low-contrast images so that such images can be properly enhanced by the (S)GLG technique. The extension of (S)GLG to color images is also discussed in this paper. SGLG and its variations extend the capability of the basic GLG to a larger variety of low-contrast images, and can fulfill special application requirements. SGLG and its variations not only produce results superior to conventional contrast enhancement techniques, but are also fully automatic under most circumstances, and are applicable to a broad variety of images.