Adaptive output feedback neural network control of uncertain non-affine systems with unknown control direction

This paper deals with the problem of adaptive output feedback neural network controller design for a SISO non-affine nonlinear system. Since in practice all system states are not available in output measurement, an observer is designed to estimate these states. In comparison with the existing approaches, the current method does not require any information about the sign of control gain. In order to handle the unknown sign of the control direction, the Nussbaum-type function is utilized. In order to approximate the unknown nonlinear function, neural network is firstly exploited, and then to compensate the approximation error and external disturbance a robustifying term is employed. The proposed controller is designed based on strict-positive-real (SPR) Lyapunov stability theory to ensure the asymptotic stability of the closed-loop system. Finally, two simulation studies are presented to demonstrate the effectiveness of the developed scheme.     

An Empirical Examination of Factors Affecting Group Effectiveness in Information Systems Projects

Although group project concepts and skills have become a major component in most information systems (IS) academic programs, very little research has attempted to examine factors that may improve or undermine effectiveness of IS group projects. Accordingly, based on relevant literatures, this study develops and empirically tests a model of factors affecting IS group project effectiveness. The research model posits that group cohesion and group efficacy will have positive effects on group effectiveness (project success and expected impact), whereas perceived loafing is expected to have a negative effect on IS group effectiveness. Data collected from 104 students working in 29 groups to complete semester‐long projects in two IS courses revealed that group efficacy had positive impact on group effectiveness and perceived loafing demonstrated a partial effect. Contrary to expectations, the impact of group cohesion was nonsignificant. These results could be useful in evaluating groups' potential for success and creating conditions conducive to enhancing effectiveness and success of IS student group projects.     

An extended discrete particle swarm optimization algorithm for the dynamic facility layout problem

We extended an improved version of the discrete particle swarm optimization （DPSO） algorithm proposed by Liao et al.（2007） to solve the dynamic facility layout problem （DFLP）. A computational study was performed with the existing heuristic algorithms, including the dynamic programming （DP）, genetic algorithm （GA）, simulated annealing （SA）, hybrid ant system （HAS）, hybrid simulated annealing （SA-EG）, hybrid genetic algorithms （NLGA and CONGA）. The proposed DPSO algorithm, SA, HAS, GA, DP, SA-EG, NLGA, and CONGA obtained the best solutions for 33, 24, 20, 10, 12, 20, 5, and 2 of the 48 problems from （Balakrishnan and Cheng, 2000）, respectively. These results show that the DPSO is very effective in dealing with the DFLP. The extended DPSO also has very good computational efficiency when the problem size increases.     

Environmental impact prediction using remote sensing images

Environmental impact prediction is an important step in many environmental studies. A wide variety of methods have been developed in this concern. During this study, remote sensing images were used for environmental impact prediction in Robatkarim area, Iran, during the years of 2005-2007. It was assumed that environmental impact could be predicted using time series satellite imageries. Natural vegetation cover was chosen as a main environmental element and a case study. Environmental impacts of the regional development on natural vegetation of the area were investigated considering the changes occurred on the extent of natural vegetation cover and the amount of biomass. Vegetation data, land use and land cover classes （as activity factors） within several years were prepared using satellite images. The amount ofbiomass was measured by Soil-adjusted Vegetation Index （SAVI） and Normalized Difference Vegetation Index （NDVI） based on satellite images. The resulted biomass estimates were tested by the paired samples t-test method. No significant difference was observed between the average biomass of estimated and control samples at the 5% significance level. Finally, regression models were used for the environmental impacts prediction. All obtained regression models for prediction of impacts on natural vegetation cover show values over 0.9 for both correlation coefficient and R-squared. According to the resulted methodology, the prediction models of projects and plans impacts can also be developed for other environmental elements which may be derived using time series remote sensing images.     

Cytokine Gene Polymorphism in Idiopathic Nephrotic Syndrome Children

The pathogenesis of idiopathic nephrotic syndrome is not completely understood. We postulate that cytokine gene polymorphisms may influence susceptibility or clinical course in Idiopathic Nephrotic Syndrome. Polymorphisms of IL-4, IL-6, and TNF-α cytokines were investigated in 150 children with Idiopathic Nephrotic Syndrome and 569 healthy controls by using polymerase chain reaction and restriction fragment length polymorphism. On comparing patient with controls strong association were found for IL-6, TNF-α and IL-4 at allelic level (IL-6-G174C (G vs. C): P = <0.001; OR = 6.33, TNF-α-G308A (G vs. A): P = <0.001; OR = 1.99, IL-4-C590T (C vs. T): P = 0.048; OR = 1.38). Further when SR group was compared with SS group significant association was found at genotypic level in all the studied genetic polymorphisms. Studied cytokine gene polymorphisms may influence susceptibility to idiopathic nephrotic syndrome and might affect steroid response in INS patients.     

Association of Vitamin D Receptor (FokI and BsmI) Gene Polymorphism with Bone Mineral Density and Their Effect on 25-Hydroxyvitamin D Level in North Indian Postmenopausal Women with Osteoporosis

Osteoporosis is a systemic disease with a strong genetic component. Vitamin D receptor (VDR) has been suggested as a candidate gene for osteoporosis. Therefore the present study was aimed to investigate the pattern of allelic variants of VDR gene polymorphism (FokI and BsmI), its influence on vitamin D levels and bone mineral density (BMD) in North Indian postmenopausal women with osteoporosis for possible genetic association. 254 postmenopausal osteoporotic women and 254 postmenopausal non osteoporotic women were included in the study. VDR FokI and BsmI gene polymorphism gene were assessed by the PCR-RFLP method. Serum 25-hydroxyvitamin D was measured by the ELISA. BMD at the L₁–L₄ lumbar spine, hip, forearm and femoral neck was assessed by dual energy X-ray absorptiometry. The average BMD at spine and hip in postmenopausal women with bb and spine, hip, femoral neck and forearm with ff genotype had significantly low BMD. The frequency of ff genotype and f allele was significantly higher in postmenopausal osteoporotic women when compared with postmenopausal non osteoporotic women. However, no significant association was found between the genotypes and vitamin D levels. Our study reveals that VDR gene FokI and BsmI polymorphism is significantly associated with low bone mineral density. Therefore the ff genotype and f allele of VDR FokI gene may be used as an important risk factor for osteoporosis.     

Design and comparison of LQG/LTR and H∞ controllers for a VSTOL flight control system

In this paper two robust controllers for a multivariable vertical short take-off and landing (VSTOL) aircraft system are designed and compared. The aim of these controllers is to achieve robust stability margins and good performance in step response of the system. LQG/LTR method is a systematic design approach based on shaping and recovering open-loop singular values while mixed-sensitivity H_∞ method is established by defining appropriate weighting functions to achieve good performance and robustness. Comparison of the two controllers show that LQG method requires rate feedback to increase damping of closed-loop system, while H_∞ controller by only proper choose the weighting functions, meets the same performance for step response. Output robustness of both controllers is good but H_∞ controller has poor input stability margin. The net controller order of H_∞ is higher than the LQG/LTR method and the control effort of them is in the acceptable range.     

Asymmetric Gaussian chirplet model and parameter estimation for generalized echo representation

Gaussian Chirplet Model (GCM) is commonly used for signal analysis in many fields including ultrasound, radar, sonar, seismology, and biomedicine. The symmetric envelope of GCM is often inadequate in representing real echo envelopes which are more likely to be asymmetric. In our previous work we introduced the Asymmetric Gaussian Chirplet Model (AGCM) that generalizes the GCM. In this paper, an efficient successive parameter estimation algorithm is proposed utilizing echo envelope and instantaneous phase obtained via analytical signal representation. The initial parameters obtained via successive estimation are fine-tuned with a fast Gauss–Newton algorithm developed for the AGCM to achieve Maximum Likelihood Estimation (MLE) of model parameters. The performance of parameter estimation algorithm is formally verified employing Monte-Carlo simulations and Cramer–Rao Lower Bounds. Parameter estimation is shown to be minimum variance and unbiased for SNR levels 10 dB and higher. Furthermore, AGCM has been tested on real ultrasound echoes measured from planar targets. AGCM provides better echo fits than the GCM due to its more flexible envelope.     

The design of networked distributed sliding mode controllers with non-ideal links

In this paper, a methodology is proposed for the design of Networked Distributed Sliding Mode Controllers (NDSMC) for large-scale systems consisting of interconnected discrete-time subsystems. The state of each of these subsystems has time varying delays and there is also delay and packet loss in their interconnection links. The Networked Distributed Control System (NDCS), which is subject to the non-idealities of these interconnection links, is modeled and a Linear Matrix Inequality (LMI) based sufficient condition for designing asymptotically stable sliding surfaces, as well as the stabilizing NDSMC, is proposed. Finally, the proposed NDSMC structure is employed for the formation control of Unmanned Aerial Vehicles (UAVs); in which five vehicles are flying in a leader–follower architecture, in two platoons, whilst attempting to maintain the desired speed with a constant desired Euclidean distance between successive vehicles despite the presence of external perturbations such as wind disturbances.