Realizations of fully differential voltage second generation current conveyor with an application

Three novel CMOS realizations for the fully differential voltage second‐generation inverting current conveyor (FDVCCII‐) are proposed in this paper. The first realization has a limited input range, and the other two realizations have a rail to rail input range and show excellent features in linearity and bandwidth. As an application to the FDVCCII‐, a floating gyrator is proposed. A floating inductor is realized using the floating gyrator and it is used in realizing a second‐order low‐pass filter, which is simulated and compared with the ideal result. All circuits are simulated with SPICE using CMOS 0.35µm technology and supply voltages ±1.5V to verify the theoretical results. Copyright © 2008 John Wiley & Sons, Ltd.     

ANN-Based STATCOM Tuning for Performance Enhancement of Combined Wind Farms

Although the wind farms based on squirrel cage induction generators (SCIG) is cheaper than the wind farms based on doubly fed induction generators (DFIG), it is always in desperate need for reactive power compensation. Nevertheless, the wind farms based on DFIG are expensive compared with the SCIG wind farm, it features by its ability to control the active power independent of reactive power. However, combined wind farm (CWF) has been developed to collect the benefits of SCIG and DFIG wind turbines in the same wind farm. In this article, artificial neural network (ANN) is used to evaluate gain parameters of static synchronous compensator (STATCOM) in order to improve the stability performance of CWF. The impact of tuned STATCOM on the performance of CWF during gust wind speed and during three-phase fault is comprehensively investigated. The performance of CWF with STATCOM tuned by ANN is compared with its performance when the STATCOM tuned by the multiobjective genetic algorithm (MOGA) and whale optimization algorithm (WOA). The results show that the performance of CWF can be enhanced using STATCOM tuned by ANN more than MOGA and WOA.     

An AW-HARIS Based Automated Segmentation of Human Liver Using CT Images

In the digestion of amino acids, carbohydrates, and lipids, as well as protein synthesis from the consumed food, the liver has many diverse responsibilities and functions that are to be performed. Liver disease may impact the hormonal and nutritional balance in the human body. The earlier diagnosis of such critical conditions may help to treat the patient effectively. A computationally efficient AW-HARIS algorithm is used in this paper to perform automated segmentation of CT scan images to identify abnormalities in the human liver. The proposed approach can recognize the abnormalities with better accuracy without training, unlike in supervisory procedures requiring considerable computational efforts for training. In the earlier stages, the CT images are pre-processed through an Adaptive Multiscale Data Condensation Kernel to normalize the underlying noise and enhance the image’s contrast for better segmentation. Then, the preliminary phase’s outcome is being fed as the input for the Anisotropic Weighted–-Heuristic Algorithm for Real-time Image Segmentation algorithm that uses texture-related information, which has resulted in precise outcome with acceptable computational latency when compared to that of its counterparts. It is observed that the proposed approach has outperformed in the majority of the cases with an accuracy of 78%. The smart diagnosis approach would help the medical staff accurately predict the abnormality and disease progression in earlier ailment stages.     

Full and reduced-order H∞ filtering of Takagi–Sugeno fuzzy time-varying delay systems: Input–output approach

This article addresses the issue of delay-dependent H_∞ filtering design for TakagiŮSugeno fuzzy time-varying delay systems using the input–output approach. A three-term approximation model has been used to transform the original system into two interconnected subsystems. Since the nonquadratic Lyapunov–Krasovskii functional requires to deal with the membership function's (MF) time derivative, upper-bound inequalities have been added to the obtained conditions. Based on the scaled small gain theorem, nonquadratic Lyapunov–Krasovskii functional approach and considering the bounds of the MF time-derivative, the H_∞ full- and reduced-order filters are designed and then formulated in terms of linear matrix inequalities. Finally, illustrative examples are presented to demonstrate the validity of the proposed methods.     

Recursive least squares estimation methods for a class of nonlinear systems based on non-uniform sampling

Many dynamic processes in practice have nonlinear characteristics and must be described by using nonlinear models. It remains to be a challenging problem to build the models of such nonlinear systems and to estimate their parameters. This article studies the parameter estimation problem for a class of Hammerstein-Wiener nonlinear systems based on non-uniform sampling. By means of the auxiliary model identification idea, an auxiliary model-based recursive least squares algorithm is derived for the systems. In order to enhance the computational efficiency, an auxiliary model-based hierarchical least squares algorithm is proposed by utilizing the hierarchical identification principle. The simulation results confirm the effectiveness of the proposed algorithms.     

Reliability-based fault analysis models with industrial applications: A systematic literature review

Effective and early fault detection and diagnosis techniques have tremendously enhanced over the years to ensure continuous operations of contemporary complex systems, control cost, and enhance safety in assets-intensive industries, including oil and gas, process, and power generation. The objective of this work is to understand the development of different fault detection and diagnosis methods, their applications, and benefits to the industry. This paper presents a contemporary state-of-the-art systematic literature survey focusing on a comprehensive review of the models for fault detection and their industrial applications. This study uses advanced tools from bibliometric analysis to systematically analyze over 500 peer-reviewed articles on focus areas published since 2010. We first present an exploratory analysis and identify the influential contributions to the field, authors, and countries, among other key indicators.  A network analysis is presented to unveil and visualize the clusters of the distinguishable areas using a co-citation network analysis. Later, a detailed content analysis of the top-100 most-cited papers is carried out to understand the progression of fault detection and artificial intelligence–based algorithms in different industrial applications. The findings of this paper allow us to comprehend the development of reliability-based fault analysis techniques over time, and the use of smart algorithms and their success. This work helps to make a unique contribution toward revealing the future avenues and setting up a prospective research road map for asset-intensive industry, researchers, and policymakers.     

Thermal hydraulic analysis of supercritical water reactor cooled by TiO2 nanofluid

Heat transfer study of nanofluids as coolant in SCWRs core has been performed at Helwan University. A thermal hydraulic code has been produced to study the effect of TiO₂ nanofluid water based as a coolant with comparison with pure water as a coolant. Various volume fractions of nanoparticles TiO₂ (2, 6 and 10%) were used in order to investigate its effects on reactor thermalhydraulic characteristics. Based on Parameters of a SCW Canadian Deuterium Uranium nuclear reactor (CANDU), the fuel assembly was modeled to study the effect of nanoparticles volume fraction on thermos-physical properties of basic fluid and the temperature distribution of fuel, cladding surface and coolant in axial direction. The theoretical results showed that the density, viscosity and thermal conductivity of the coolant increases with the increase of nanoparticles volume fraction, contrasting to specific heat, which decreases with the increase in nanoparticles volume fraction.     

Adsorption of U(Ⅵ) from acid solution on a low-cost sorbent:equilibrium,kinetic, and thermodynamic assessments

In this paper, waste clay was cured with ethyl acetate to obtain treated clay(TC), which was modified with gallic acid to obtain a low-cost sorbent that was characterized by EDX, SEM, and FTIR analysis. Uranium(Ⅵ) adsorption was achieved using the batch adsorption method on the TC and gallic acid-modified treated clay(GMTC). The maximum uptakes of U(Ⅵ) on TC and GMTC were 37.2 and 193.0 mg/g, respectively.The U(Ⅵ) adsorption kinetics on the TC and GMTC sorbents were well-fitted by the pseudo-second-order mechanism, and the adsorption equilibrium followed the Langmuir model. The optimum parameters were applied to El Sela leach solution for uranium recovery.     

阿拉伯东部地区宗教文化对传统建筑的影响

伊斯兰教和阿拉伯语是西亚地区统一的主要特征.它们构成了这些国家的共性,然而又有一些因素可将西亚世界区分开来,宗教就是其中2一。阿拉伯国家都是穆斯林国家, 它们的建筑是世界伊斯兰建筑的一部分,“伊斯兰建筑”概念本身就体现了宗教在地域建筑特征形成过程中所起的作用。地域性文化是地域性建筑的重要构成,宗教文化则是地域性文化诸因素之一。     

A novel image encryption scheme based on orthogonal matrix,skew tent map,and XOR operation

Neural Computing and Applications - Content protection is considered as an important issue in today’s world. Therefore, encryption of such contents is a challenging task for researchers. They...