Search

Introduction & Objective: Physical activity (PA) is inversely associated with obesity but the effect has been difficult to quantify using questionnaires. Pedometers provide an opportunity to better characterize the association. The aim of present study was to examine the relationship between pedometer-determined PA (steps/day) and anthropometric risk factors of the cardiovascular system (CVS) in Hamadanian middle aged men.Materials & Methods: Anthropometric variables, total daily energy expenditure and Vo2rest were measured in 101 apparently healthy men (40-65yr). Subjects wore a pedometer (Hj-113 Omron, Japan) throughout the day for 2 consecutive weeks.Results: A significant negative correlation was found between average steps per day and weight (-0.574), %BF (-0.484), BMI (-0.721) WC (-0.584), HC (-0.369), AC (-0.559) and WHR (-0.568) P=0.0000. There was a significant difference in body composition variables, Daily Energy Expenditure and Vo2rest among activity groups (G1: ≥10,000step/day and G2 :< 10,000step/day), with higher values found in the less active groups (P>0.005).Conclusion: Anthropometric risk factors of the CVS in the active men with more daily steps are lower than the inactive counterparts. This point from clinical strategy, especially in the body composition parameters (BMI, WHR and central obesity) is important.(Sci J Hamadan Univ Med Sci 2012;19(3):49-56)

The aim of this study was to assay a chemical method for the reduction of aflatoxins B1 (AFB1), B2 (AFB2), G1 (AFG1), G2 (AFG2) and ochratoxin A (OTA) in black pepper. The efficiency of AF and OTA reduction by sodium hydrosulphite (Na2S2O4) at different concentrations (0.25, 0.5, 1, 1.5 and 2%) in artificially contaminated black pepper was investigated under atmospheric and high pressure. The first treatment was performed under atmospheric pressure in boiling water at 100 °C for 30 min, and the second treatment was performed under high pressure (1.5 bar) at 121 °C for 15 s. The concentrations of the AFs and OTA were determined by high performance liquid chromatography (HPLC) using fluorescence detection (FD). Maximal respective reductions of 96.0%, 96.1%, 77.7%, 100% and 100% for OTA, AFB1, AFB2, AFG1 and AFG2, respectively, were achieved by treatment with 2% Na2S2O4 under high pressure. These findings suggest that AFs and OTA can be degraded by treatment with Na2S2O4 and heat under pressure.

Introduction & Objective: Relationship between overweight being and obese with metabolic risk factors of the cardiovascular disease in adolescent boy considering the variety and irregular motional patterns, has attracted the researchers' attention. The aim of this study was to investigate biochemical and anthropometrical risk factors of the cardiovascular system, daily physical activity (steps/day) and aerobic capacity of overweight and normal weight adolescent boys. Materials & Methods: Fifty six adolescent boys were recruited in two groups; over weight-obese as a risk receptive group (n=28) and normal weight (n=28). Blood lipids, daily steps (physical activity volume), body composition and aerobic capacity were measured with standard methods.Results: TG, TC, LDL-C and VLDL–C concentrations and TC/HDL-C and LDL-C/HDL-C in the normal weight individuals were significantly lower than the overweight subjects (P

Non-sanitary conditions during the drying, transport and storage stages in the production of chili could introduce mycotoxin contamination. The aim of this study was to determine the level of the aflatoxins B 1 , B 2 , G 1 and G 2 (AFB 1 , AFB 2 , AFG 1 , AFG 2 ) and ochratoxin A (OTA) in 80 samples of chili marketed in supermarkets and open markets in Malaysia. Mycotoxins were determined by high performance liquid chromatography (HPLC) with fluorescence detection after immunoaffinity column clean-up. The limits of detections (LODs) were 0.02, 0.02, 0.1, 0.06 and 0.02 ng/g for AFB 1 , AFB 2 , AFG 1, AFG 2 and OTA, respectively. Fifty-two chili samples (65.0%) were contaminated with total aflatoxin level in the range of 0.2–79.7 ng/g. The AFB 1 exhibited the highest incidence compared to the other examined aflatoxins. Sixty-five of 80 chili samples (81.25%) were found to be contaminated with OTA in the range of 0.2–101.2 ng/g. Results showed that the level of mycotoxin contamination of the chili samples purchased from the open markets were significantly higher ( p

Gamma ray was applied to reduce mycotoxins, i.e. ochratoxin A (OTA) and aflatoxins B1, B2, G1 and G2 (AFB1, AFB2, AFG1 and AFG2) in black pepper. Response surface methodology (RSM) was applied to evaluate the effect of dose of gamma ray ranging from 0 to 60 kGy and mycotoxin concentration ranging from 10 to 100 ng g−1 on the mycotoxin reduction. The maximum reduction was found at 60 kGy which was 52%, 43%, 24%, 40% and 36% for OTA, AFB1, AFB2, AFG1 and AFG2, respectively. Results showed the gamma rays even at 60 kGy were not effective in completely destroying of ochratoxin and aflatoxins.

The concentration of ochratoxin A (OTA) in 120 commercial pepper (84 pre-packed and 36 bulk samples), which consist of local and imported white and black pepper in powder and seed form in Malaysia were determined. The objective of the study was to investigate and compare OTA concentration in black pepper and white pepper being commercialized in Malaysia. Determination method was based on HPLC with fluorescence detection coupled with immunoaffinity column clean-up step. Mobile phase consisted of acetonitrile-water-acetic acid (49.5:49.5:1.0, v/v/v), and flow rate was 1 ml/min. The LOD was 0.02 ng/g, and the average recovery values of OTA ranged from 79.5 to 92.0% in black pepper and 81.2-90.3% in white pepper. A total of 57 samples (47.5%) were contaminated with OTA ranging from 0.15 to 13.58 ng/g. The results showed that there was a significant difference between type of pepper and brands. OTA concentration in black pepper was significantly higher than white pepper (p < 0.05). The highest concentration of ochratoxin, 13.58 ng/g, was detected in a sample of black pepper seed followed by 12.64 ng/g in a sample of black pepper powder, both were bulk samples purchased from open market.

Quantity prediction of municipal solid waste (MSW) is crucial for design and programming municipal solid waste management system (MSWMS). Because effect of various parameters on MSW quantity and its high fluctuation, prediction of generated MSW is a difficult task that can lead to enormous error. The works presented here involve developing an improved support vector machine (SVM) model, which combines the principal component analysis (PCA) technique with the SVM to forecast the weekly generated waste of Mashhad city. In this study, the PCA technique was first used to reduce and orthogonalize the original input variables (data). Then these treated data were used as new input variables in SVM model. This improved model was evaluated by using weekly time series of waste generation (WG) and the number of trucks that carry waste in week of t. These data have been collected from 2005 to 2008. By comparing the predicted WG with the observed data, the effectiveness of the proposed model was verified. Therefore, in authors' opinion, the model presented in this article is a potential tool for predicting WG and has advantages over the traditional SVM model.

Due to lack of previous research on applying additives in Cold In-Place Recycling (CIR) mixes in this study, Portland cement and lime were used as additives. The Portland cement was introduced in powder form and lime was utilized as hydrated lime in powder form and lime slurry, and the effects of each additive on properties of CIR mixes has been evaluated. The results showed that both lime and Portland cement can increase Marshall stability, resilient modulus, tensile strength, resistance to moisture damage and resistance to permanent deformation of CIR mixes. Use of Portland cement and lime slurry had better results than hydrated lime but due to the difficulties in producing lime slurry in practice, the use of Portland cement is recommended.

A total of 126 local and imported samples of commercial white and black pepper in Malaysia were analysed for aflatoxins B1, B2, G1 and G2 (AFB1, AFB2, AFG1, AFG2) content using high-performance liquid chromatography (HPLC) with a fluorescence detector (FD). An acetonitrile–methanol–water (17 : 29 : 54; v/v) mixture was used as a mobile phase and clean-up was using an immunoaffinity column (IAC). Seventy out of 126 (55.5%) samples were contaminated with total aflatoxins, although only low levels of aflatoxins were found ranging from 0.1 to 4.9 ng g−1. Aflatoxin B1 showed the highest incidence of contamination and was found in all contaminated samples. There was a significant difference between type of samples and different brands (p < 0.05). The results showed black peppers were more contaminated than white peppers.

The effect of 18 different chemicals, which included acidic compounds (sulfuric acid, chloridric acid, phosphoric acid, benzoic acid, citric acid, acetic acid), alkaline compounds (ammonia, sodium bicarbonate, sodium hydroxide, potassium hydroxide, calcium hydroxide), salts (acetate ammonium, sodium bisulfite, sodium hydrosulfite, sodium chloride, sodium sulfate) and oxidising agents (hydrogen peroxide, sodium hypochlorite), on the reduction of aflatoxins B(1), B(2), G(1) and G(2) and ochratoxin A (OTA) was investigated in black and white pepper. OTA and aflatoxins were determined using HPLC after immunoaffinity column clean-up. Almost all of the applied chemicals showed a significant degree of reduction on mycotoxins (p0.05). The lowest and highest reduction of aflatoxin B(1), which is the most dangerous aflatoxin, was 20.5% ± 2.7% using benzoic acid and 54.5% ± 2.7% using sodium hydroxide. There was no significant difference between black and white peppers (p0.05).

In this paper the application of robust variable structure sliding mode control algorithm to position control in a voltage-controlled magnetic levitation system is considered. This system is inherently nonlinear associated with the electromechanical dynamics, so the control problem is quite complicated and challenging. Simulation results of the proposed control action show better performance in comparison with classic feedback linearization method

Network congestion control remains a critical and high priority issue. The rapid growth of the Internet, the massive amount of data traffic it carries and increased demand to use the Internet for time-sensitive voice and video applications necessitates the design and utilization of effective congestion control algorithms. The reliance of the Internet on the TCP/IP protocol suite suggests that we must focus our efforts in this area. Existing TCP/IP protocol suite has been designed for best effort (delay tolerant) services and cannot effectively support time sensitive applications. We will use the integrated dynamic congestion control (IDCC) scheme. The problem that comes up is the lack of an effective way of dealing with congestion. On the other hand, the IDCC scheme controls the traffic using information on the status of each queue in the network. It is based on a nonlinear model of the network that is generated using fluid flow considerations. The aim of this paper is to design a robust active queue management system to secure high utilization, bounded delay and loss, while the network complies with the demands each traffic class sets. To this end, we will use the H, control theory. Simulation results of the proposed control action demonstrate the effectiveness of the controller in providing robust queue management system.

In this paper, a new discrete-time sliding mode approach for linear time-varying system is proposed. The proposed method guarantees that the system states are globally uniformly ultimately bounded in the presence of time-varying disturbance and uncertainly. It is also shown that the closed-loop system is globally asymptotically stable if disturbance and uncertainty are time invariant. Using the proposed control algorithm, steering control of highway vehicles is designed for a fundamentally new deriving maneuver and the tracking problem of relative lateral position is investigated. Also, the robust performance of the proposed controller in response to external disturbance is verified. Simulation results reveal the efficiency of proposed controller.

Decision support systems (DSS) and expert systems (ES), have joined other human beings interactive auxiliary systems. Decision support systems and expert systems usually work on a relatively limited-in comparison with a huge data base-knowledge base (KB) rather than a data base (DB) and have relatively large processing operations. These systems have the capability of self-inserting and self-correcting of information housed in the knowledge base. In other words, the facts or rules inferred or concluded from available facts and conditions, could be added to the knowledge base automatically without any contradictions or inconsistencies. In the other hand, search engines and web directories usually work on massive data bases, which could not be updated automatically as a result of processing, unless some special software like Web Spiders do that job for it. Intelligent and intellectual processing functions in these systems are relatively smaller than those of members of first group. In second group much of processing time will be spent on tasks related to searching, categorizing and sorting information.

In this paper, a method to design a nonlinear optimal controller using approximate solution of the HJB equation is presented. Using this method, the power system stabilizer is designed. In order to regulate generator terminal voltage to its nominal value, we use a simple neuro-automatic voltage regulator. The final control action is the sum of nonlinear optimal controller and neuro-voltage regulator. Also, the advantages of the controller with nonlinear feedback in some grounds like increasing domain of validity of the system are shown. Simulation results show that the nonlinear control action exhibits a better performance compared to that of corresponding linear counter part. As a result, the fault tolerance of the system using the nonlinear control law is increased. Also, the proposed voltage regulator, which can be trained on-line, shows satisfactory performance.

Acquisition and utilization of lateral guidance is crucial for steering a vehicle. In practice, human drivers have performed this function quite successfully using perception and hand-eye coordination. However, this task becomes difficult when the vehicle losses its stability. In this paper, we try to investigate this problem using predictive control strategy. The most important advantage of the MPC technology comes from the process model itself, which allows the controller to deal with an exact replica of the real process dynamics, implying a much better control quality. Simulation results of the closed-loop system with proposed predictive control algorithm reveal the effectiveness of the proposed control action in controlling the steering of the vehicle.

Active Queue Management (AQM) takes a trade-off between link utilization and delay experienced by data packets. From control point of view, it is rational to regard AQM as a typical regulation system. In this paper, a new fuzzy adaptive second order sliding mode controller is designed for the objective of AQM. In the proposed method, the sliding parameter is adapted using fuzzy logic. Some computer simulations are provided to show the effectiveness of the proposed control action. Simulation results show the fuzzy logic based adaptive second order sliding mode has better performance in comparison with classic second order sliding mode control action in providing efficient queue management.

In this paper, a neural network-based predictive controller is designed to govern the dynamics of heat exchanger process. Heat exchanger is a highly nonlinear process; therefore, a nonlinear prediction method can be a better match in a predictive control strategy. Advantages of neural networks for the process modeling are studied and a neural network based predictor is designed, trained and tested as a part of the predictive controller. The neuro predictive controller is utilized in setpoint tracking of a heat exchanger plant. The performance of the proposed controller is compared with that of Generalized Predictive Control (GPC) through simulation studies. Obtained results demonstrate the effectiveness and superiority of the proposed approach.

In this paper, a high performance control applied to speed control of interior permanent magnet synchronous motors. The design strategy is performed with constraint on the power factor, i.e., the power factor is maximized. In order to enhance the performance of the control system, a decoupling current vector control strategy is developed to ensure high performance operation. Simulation results reveal the effectiveness of the proposed controller.

A predictive control algorithm based on locally linear model tree model (LOLIMOT) is implemented to control a fossil fuel power unite. The controller is a non-model based system that uses a LOLIMOT identifier to predict the response of the plant in a future time interval. An evolutionary programming (EP) approach, optimizes the identifier-predicted outputs and determines input sequence in a time window. This intelligent system provides a predictive control of multi-input multi-output nonlinear systems with slow time variation.

The control of a permanent magnet synchronous motor under a sliding mode controller is presented in this paper. A hyperbolic tangent switching function is used to overcome the chattering problem. The system is examined under extensive load disturbances, parameter uncertainty and noisy feedback signals by computer simulation. The results prove a superior motor performance over a PI controller in terms of robustness, smoothness and fast dynamics.

In this paper an optimal nonlinear controller for stabilization of a power system is presented. In order to the design of the controller an approximate solution of the HJB equation using Taylor's series expansion is used. The advantages of the nonlinear feedback controller in some grounds like increasing the region of asymptotic stability of the system or in the other words increasing the domain of validity will be shown. Also, the fault tolerance of the system under the controller is investigated. Simulation results reveal the effectiveness of the proposed approach.

An optimal displacement feedback control law is derived for a vibration control of a single-degree-of-freedom structure with an active tuned mass damper (ATMD). Analytical expressions of the linear quadratic regulator (LQR) feedback gains for the ATMD are derived by solving the Ricatti equation straightforwardly. The mean-square responses of the structure as well as the auxiliary mass against Gaussian white noise excitations are evaluated by solving the Lyapunov equation analytically based on the stochastic optimal control theory. Using these analytical solutions, the optimal damping parameter for the auxiliary mass is also derived. Finally, the optimal displacement feedback control law is presented.

A feedback linearization controller based on sliding mode control action for a gas metal arc welding (GMAW) system is proposed. The controller uses nonlinear state feedback to exactly linearize and decouple the GMAW system. The linearized system is then controlled using model reference sliding mode controllers. The effect of parameter uncertainty over the closed loop system performance is investigated. Simulation results show the effectiveness of the proposed controller.

In this paper an adaptive linear quadratic controller (LQR) with a repetitive controller (RP) for uninterruptible power supplies (UPS) is proposed. The gain of the controller is determined by minimizing a cost function, which reduces the tracking error and smoothes the control signal. A recursive least square (RLS) estimator is used to identify the plant parameters at different load conditions. A RP controller with forgetting coefficients is used for cyclic disturbances attenuation and the final control action is the sum of the LQR and RP controllers. Simulation results show the effectiveness of the proposed controller in producing an output signal with low total harmonic distortion.

In this paper, the design of nonlinear H/sub /spl infin// controller for autopilot application is presented. The design of nonlinear H/sub /spl infin// control action leads to a partial differential inequality or equation, namely, Hamilton-Jacobi-Isaacs (HJI) inequality. It is too difficult, if not impossible, to find an exact closed form solution for this inequality. However, there are some approximate solutions. In this paper, we will make use of one of the most efficient possible methods, Taylor Series Expansion of nonlinear terms appear in HJI. Simulation results of the proposed method on a missile's autopilot design show the effectiveness of the proposed algorithm.

The internal model control (IMC) scheme has been widely applied in the field of process control. So far, IMC has been mainly applied to linear processes. This paper discusses the extension of the IMC scheme to nonlinear processes based on local linear models where the properties of linear design procedures can be exploited. The IMC scheme results in controllers that are comparable to conventional multi layer perceptron (MLP) networks. In practice, the tuning of conventional MLP based controllers can be very time-consuming whereas the IMC design procedure is very simple and reliable. In this paper, the design effort of the IMC based on locally linear model tree (LOLIMOT) algorithm are discussed and the control results are compared by application to nonlinear control of an industrial-scale PH neutralization process. Simulation studies of a PH neutralization process confirm the excellent nonlinear modeling properties of the proposed locally linear network and illustrate the potential for set point tracking and disturbance rejection within an IMC framework.

In this article, a new and powerful analytical method which does not need small parameters, called the Homotopy-perturbation method, is introduced to solve strongly nonlinear coupled systems. Jaulent-Miodek equations are chosen to illustrate the capability and effectiveness of the method. The obtained results are compared with those obtained by the variational iteration method and exact solutions. The comparison shows that both methods are tremendously effective.

Recently, the stability of the cubic functional equation in fuzzy normed spaces was proved in earlier work; and the stability of the additive functional equations , in random normed spaces was proved as well. In this paper, we prove the stability of the cubic functional equation in random normed spaces by an alternative proof which provides a better estimation. Finally, we prove the stability of the quartic functional equation in random normed spaces.