Forecasting the Level of Reservoirs Using Multiple Input Fuzzification in ANFIS

Estimation the Level of water is one of the crucial subjects in reservoir management influencing on reservoir operation and decision making. One of the most accurate artificial intelligence model used broadly in water resource aspects is adaptive neuro-fuzzy interface system (ANFIS) taking in to account the membership functions (MF) on the basis of the smoothness characteristics and mathematical components each for set of input data. All researches in hydrological estimation used ANFIS, merely a type of MF has been noticed for all sets of inputs without considering the response of each of them. This study is applying a specified certain MFs for each type of input to improve the accuracy of ANFIS model in forecasting the water level in Klang Gates Dam in Malaysia. On the basis of the previous studies, two most popular MFs, Generalized Bell Shape MF and, Gaussian MF, are employed for examine the new pattern in two inputs ANFIS architecture resulted less stress in error performance, and higher accuracy in estimation, compare to the traditional ANFIS model. The aim is achieved by evaluating the performance in and fitness of the model in daily reservoir estimation.     

High-Temperature Very Low Frequency Noise-Based Investigation of Slow Transients in AlGaN/GaN MODFETs

The variations of the very low frequency noise (i.e., 100 mHz to 100 kHz) and the dc characteristics of unpassivated AlGaN/GaN modulation-doped field-effect transistors (MODFETs) with temperature from 300 to 500 K are investigated. The rise in temperature to 500 K is shown to reveal generation-recombination (G-R) noise characteristics within the 100 mHz to 1 Hz frequency range. It is experimentally evidenced that these manifestations can predict the existence of very slow transients in the drain-current characteristics of AlGaN/GaN MODFETs. Due to the very long time constant of the transients at room temperature (i.e., on the order of several hours or even days), the observed features can be classified as semipermanent. The comparison between the energy levels predicted by the noise data and the levels previously reported in literature supports these observations.     

Technical and economic assessment of the integrated solar combined cycle power plants in Iran

Thermal efficiency, capacity factor, environmental considerations, investment, fuel and O&M² costs are the main parameters for technical and economic assessment of solar power plants. This analysis has shown that the Integrated Solar Combined Cycle System with 67 MW e solar field (ISCCS-67) is the most suitable plan for the first solar power plant in Iran. The Levelized Energy Costs (LEC) of combined cycle and ISCCS-67 power plants would be equal if 49 million $ of ISCCS-67 capital cost supplied by the international environmental organizations such as Global Environmental Facilities (GEF) and World Bank. This study shows that an ISCCS-67 saves 59 million $ in fuel consumption and reduces about 2.4 million ton in CO₂ emission during 30 years operating period. Increasing of steam turbine capacity by 50%, and 4% improvement in overall efficiency are other advantages of ISCCS-67 power plant. The LEC of ISCCS-67 is 10 and 33% lower than the combined cycle and gas turbine, respectively, at the same capacity factor with consideration of environmental costs.     

Using Copulas for analysis of large datasets in renewable distributed generation: PV and wind power integration in Iran

Renewable distributed generation introduced as an environmental friendly alternative energy supply while it provided the power system with ever-growing technical benefits such as loss reduction and feeder voltage improvement. The evaluation of the effects of small residential photovoltaic and wind DG systems on various system operating indices and the system net load is complicated by both the probabilistic nature of their output and the variety of their spatial allocations. The increasing penetration of renewable distributed generation in power systems necessitates the modeling of this stochastic structure in operation and planning studies. An advanced stochastic modeling of the system requires multivariate uncertainty analysis involving non-normal correlated random variables. Such an analysis is to epitomize the aggregate uncertainty corresponding to spatially spread stochastic variables. In this paper, an integration study of photovoltaics and wind turbines, distributed in a distribution network, is investigated based on the stochastic modeling using Archimedean copulas as a new efficient tool. The basic theory concerning the use of copulas for dependence modeling is presented and focus is given on an Archimedean algorithm. A comprehensive case study for Davarzan area in Iran is presented after reviewing Iran's renewable energy status. This study shows an application of the presented technique when large datasets, assuming 10-min interval between data points of PV, wind and load profiles, are involved where a deterministic study is not trivial.     

Physicochemical characterization of solid dispersions of indomethacin with PEG 6000, Myrj 52, lactose, sorbitol, dextrin, and Eudragit E100

The purpose of this study was to prepare and characterize solid dispersions of indomethacin with polyethylene glycol (PEG) 6000, Myrj 52, Eudragit® E100, and different carbohydrates such as lactose, mannitol, sorbitol, and dextrin. Indomethacin is a class II substance according to the Biopharmaceutics Classification System. It is a poorly water soluble antirheumatic agent. The goal was to investigate whether the solid dispersion can improve the dissolution properties of indomethacin. The solid dispersions were prepared by three different methods depending on the type of carrier. The evaluation of the properties of the dispersions was performed using solubility measurements, dissolution studies, Fourier-transform infrared spectroscopy, and x-ray powder diffractometery. The results indicate that lactose, mannitol, sorbitol, and especially Myrj 52 are suitable carriers to enhance the in vitro dissolution rate of indomethacin at pH 7.2. Eudragit E100, Myrj 52, and mannitol increase the dissolution properties at pH 1.2. The data from the x-ray diffraction showed that the drug was still detectable in its solid state in all solid dispersions except solid dispersions with dextrin and high amounts of mannitol. However, the results from infrared spectroscopy together with those from x-ray diffraction showed well-defined drug-carrier interactions for dextrin coevaporates.     

Very High Cycle Fatigue of Two Ductile Iron Grades

Two ductile iron grades, EN‐GJS‐600‐3 a ferritic–pearlitic grade, and EN‐GJS‐600‐10 a silicon strengthened ferritic nodular iron grade, are studied in the very high cycle fatigue range using a 20 kHz ultrasonic test equipment. Fatigue strengths and SN‐curves are achieved, and fracture surfaces and microstructures are investigated. The ferritic grade with higher ductility displays a lower fatigue strength at 10⁸ load cycles than the ferritic–pearlitic grade, 142 and 167 MPa, respectively. Examination of fracture surfaces shows that fatigue failures are controlled by micropores in both of the ductile iron grades, while the graphite nodule distributions do not seem to influence the difference in fatigue strengths. Prediction of the fatigue strengths, using a model for ductile iron proposed by Endo and Yanase, indicates a large potential for improvement in particular for the ferritic grade.     

Interactions Between Tumor Biology and Targeted Nanoplatforms for Imaging Applications

Although considerable efforts have been conducted to diagnose, improve, and treat cancer in the past few decades, existing therapeutic options are insufficient, as mortality and morbidity rates remain high. Perhaps the best hope for substantial improvement lies in early detection. Recent advances in nanotechnology are expected to increase the current understanding of tumor biology, and will allow nanomaterials to be used for targeting and imaging both in vitro and in vivo experimental models. Owing to their intrinsic physicochemical characteristics, nanostructures (NSs) are valuable tools that have received much attention in nanoimaging. Consequently, rationally designed NSs have been successfully employed in cancer imaging for targeting cancer‐specific or cancer‐associated molecules and pathways. This review categorizes imaging and targeting approaches according to cancer type, and also highlights some new safe approaches involving membrane‐coated nanoparticles, tumor cell‐derived extracellular vesicles, circulating tumor cells, cell‐free DNAs, and cancer stem cells in the hope of developing more precise targeting and multifunctional nanotechnology‐based imaging probes in the future.     

An adaptive water flow model for binarization of degraded document images

In this paper, we present an adaptive water flow model for the binarization of degraded document images. We regard an image surface as a three-dimensional terrain and pour water on it. The water finds the valleys and fills them. Our algorithm controls the rainfall process, pouring the water, in such a way that the water fills up to half of the valley’s depth. After stopping the rainfall, each wet region represents one character or a noisy component. To segment each character, we labeled the wet regions and regarded them as blobs; since some of the blobs are noisy components, we use a multilayer Perceptron to label each blob as either text or non-text. Since our algorithm classifies the blobs instead of pixels, it preserves stroke connectivity. After several experiments, the proposed binarization algorithm demonstrated superior performance against six well-known algorithms on three sets of degraded document images. The main superiority of our algorithm is on document images with uneven illumination.     

A thermal-calorimetric gas flow meter with improved isolating feature

This paper presents design and characterization of a novel thermal-calorimetric flow-meter using suspended-cantilever-structure. There is an air gap between the heater and each individual thermistor providing a good thermal isolation. Due to the suspended-structure which consists of three cantilevers, the thermal convection effect is present on both sides of the active area. Also the velocity boundary layer thickness of the cantilever is much less than closed-membrane one. This characteristic enhances the sensitivity of sensor. The simulation results indicate that the average temperature difference between upstream and downstream thermistors are 36.5 and 1.04 K for flow rate of 1 m/s and the worst case of 0.1 m/s respectively. This solution significantly improves the sensitivity compared to the closed-membrane-structures. The maximum temperature difference causes 94 mV at the output of Wheatstone bridge with 3 V of voltage supply. The calculated and simulated results show that the maximum power consumption of sensor is 4.7 mW at the maximum flow velocity of 1 m/s. The operational range of the designed flow meter is from 0 to 1 m/s. The features of the device are analytically evaluated and simulated under various conditions.

     

An in vitro evaluation of fenugreek mucilage as a potential excipient for oral controlled-release matrix tablet

A polysaccharide mucilage derived from the seeds of fenugreek, Trigonella foenum-graceum L (family Fabaceae) was investigated for use in matrix formulations containing propranolol hydrochloride. Methocel^® hypomellose K4M was used as a standard controlled release polymer for comparison purposes. In this study the effect of lactose on the release behaviour of propranolol hydrochloride from matrices formulated to contain the fenugreek mucilage also was investigated. An increase in concentration of the mucilage in matrices resulted in a reduction in the release rate of propranolol hydrochloride comparable to that observed with hypomellose matrices. The rate of release of propranolol hydrochloride from fenugreek mucilage matrices was mainly controlled by the drug:mucilage ratio. However, the mechanism of release from matrices containing drug:mucilage ratios of 1:1, 1:1.25, 1:1.5, and 1:2 remained the same. The kinetics of release, utilising the release exponent n, showed that the values of n were between 0.46-0.57 indicating that the release from fenugreek mucilage matrices was predominantly by diffusion. The presence of lactose in matrices containing mucilage increased the release rate of propranolol hydrochloride. This is due to a reduction in tortuoisity and increased pore size of channels caused by lactose through which propranolol diffuses and therefore diffusion of water into the tablet is facilitated.