Intelligent control of static synchronous series compensator via an adaptive self-tuning PID controller for suppression of torsional oscillations

In this paper, an intelligent controller is proposed to control a static synchronous series compensator (SSSC) in order to mitigate subsynchronous resonance (SSR) oscillations in a power system. This intelligent controller is an adaptive self-tuning PID controller. To train the PID controller, the gradient descent method is employed where the learning rate is adapted in every iteration in order to accelerate the speed of convergence. This control scheme also requires a wavelet neural network (WNN) to identify the controlled system dynamic. To update the parameters of WNN, the gradient descent (GD) along with the adaptive learning rates derived by the Lyapunov method is used. The computer simulations are used to show the ability of the proposed controller. In addition, the performance of the proposed controller is compared with another self-tuning PID controller. The results demonstrate that the proposed controller has a successful performance in minimizing the SSR.     

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Poly(acrylic acid)/gum arabic/ZnO semi-IPN hydrogels: synthesis,characterization and their optimizations by response surface methodology

Iranian Polymer Journal - Synthesis of novel semi-interpenetrating poly(acrylic acid) (PAA)/gum arabic (AG)/ZnO hydrogels by in situ free radical polymerization was optimized using response surface...     

A study on the mechanical strength of Fe2O3/Cr2O3/CuO catalyst for high temperature water gas shift reaction

Journal of Porous Materials - The present study aims to investigate the effects of iron (hydr)oxide phases formed during precipitation and the addition of different binders on the mechanical and...     

On Iron Metabolism and Its Regulation

Iron is a critical metal for several vital biological processes. Most of the body’s iron is bound to hemoglobin in erythrocytes. Iron from senescent red blood cells is recycled by macrophages in the spleen, liver and bone marrow. Dietary iron is taken up by the divalent metal transporter 1 (DMT1) in enterocytes and transported to portal blood via ferroportin (FPN), where it is bound to transferrin and taken up by hepatocytes, macrophages and bone marrow cells via transferrin receptor 1 (TfR1). While most of the physiologically active iron is bound hemoglobin, the major storage of most iron occurs in the liver in a ferritin-bound fashion. In response to an increased iron load, hepatocytes secrete the peptide hormone hepcidin, which binds to and induces internalization and degradation of the iron transporter FPN, thus controlling the amount of iron released from the cells into the blood. This review summarizes the key mechanisms and players involved in cellular and systemic iron regulation.     

Multicast routing protocols in wireless mesh networks: a survey

Wireless mesh networks (WMNs) introduce a new type of network that has been applied over the last few years. One of the most important developing issues in WMNs is multicast routing, which is a key technology that provides dissemination of data to a group of members in an efficient way. In this article, after an introduction about the structure of a WMN, multicast routing algorithms and protocols in WMNs are surveyed in a detailed and efficient manner. Moreover, effort is made to scale the study into one of the important potential capabilities of multicast routing mechanisms in WMNs, which is taking advantage of using different channels and radios association. While nodes in a single-radio mesh network operating on single-channel have restrictions for capacity, equipping mesh routers with multiple radios using multiple channels can decrease the intention of capacity problem as well as increase the aggregate bandwidth available to the network and improving the throughput. Hence, the purpose of channel assignment is to decrease the interferences while increasing the network capacity and keeping the connectivity of the network. Therefore, this article investigates the multicast protocols considering a definition of three types of WMNs, based on channel-radio association including SRSC, SRMC and MRMC. In its follow, a classification for multicast routing algorithms regarding the achieved optimal solutions will be presented. Finally, a study of MRMC and its relevant problems will be offered, considering the joint channel assignment and the multicast tree construction problem.     

Effect of stabilizer type on the physicochemical properties of rigid PVC. III

The crystallinity of rigid PVC specimens, stabilized by a tin mercaptide or a lead stabilizer, has been studied. It is found that the crystallinity of rigid PVC is greatly influenced by the type of stabilizer added, and that the response of the PVC toward subsequent UV exposure was also different. The effects of unstable structures and crystallinity, after UV irradiation, on the mechanical properties of rigid PVC have been investigated.     

Reserve estimation of an open pit mine under price uncertainty by real option approach

Reserve estimation is a key to find the correct NPV in a mining project. The most important factor in reserve estimation is the metal price. Metal price fluctuations in recent years were exaggerated, and imposed a high degree of uncertainty to the re-serve estimation, and in consequence to the whole mine planning procedure. Real option approach is an efficient method of deci-sion making in the uncertain conditions. This approach has been used for evaluation of defined natural resources projects until now. This study considering the metal price uncertainty used real option approach to prepare a methodology for reserve estimation in open pit mines. This study was done on a copper cylindrical deposit, but the achieved methodology can be adjusted for all kinds of deposits. This methodology was comprehensively described through the examples in such a manner that can be used by the mine planners.     

Synthesis and properties of new poly(amide imide)s containing trimellitic rings and hydantoin moieties in the main chain under microwave irradiation

Trimellitic anhydride was reacted with 4,4′‐diaminodiphenyl ether in a mixture of acetic acid and pyridine (3 : 2) at room temperature and was refluxed at 90–100°C, and N,N′‐(4,4′‐diphenylether) bistrimellitimide (3) was obtained in a quantitative yield. 3 was converted into N,N′‐(4,4′‐diphenylether) bistrimellitimide diacid chloride (4) by a reaction with thionyl chloride. Then, six new poly(amide imide)s were synthesized under microwave irradiation with a domestic microwave oven through the polycondensation reactions of 4 with six different derivatives of 5,5‐disubstituted hydantoin in the presence of a small amount of a polar organic medium such as o‐cresol. The polycondensation proceeded rapidly and was completed within 7–10 min, producing a series of new poly(amide imide)s in high yields with inherent viscosities of 0.27–0.66 dL/g. The resulting poly(amide imide)s were characterized by elemental analysis, viscosity measurements, differential scanning calorimetry, thermogravimetric analysis, derivative thermogravimetry, solubility testing, and Fourier transform infrared spectroscopy. All the polymers were soluble at room temperature in polar solvents such as N,N‐dimethylacetamide, N,N‐dimethylformamide, dimethyl sulfoxide, tetrahydrofuran, and N‐methyl‐2‐pyrrolidone. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 92: 3447–3453, 2004     

A GMM/HMM model for reconstruction of missing speech spectral components for continuous speech recognition

This paper presents a method for reconstructing unreliable spectral components of speech signals using the statistical distributions of the clean components. Our goal is to model the temporal patterns in speech signal and take advantage of correlations between speech features in both time and frequency domain simultaneously. In this approach, a hidden Markov model (HMM) is first trained on clean speech data to model the temporal patterns which appear in the sequences of the spectral components. Using this model and according to the probabilities of occurring noisy spectral component at each states, a probability distributions for noisy components are estimated. Then, by applying maximum a posteriori (MAP) estimation on the mentioned distributions, the final estimations of the unreliable spectral components are obtained. The proposed method is compared to a common missing feature method which is based on the probabilistic clustering of the feature vectors and also to a state of the art method based on sparse reconstruction. The experimental results exhibits significant improvement in recognition accuracy over a noise polluted Persian corpus.