Impact of gate sidewall angle on the electrical characteristics of V-shaped gate III-nitride HEMTs: An investigation into self-heating and geometrical effects

Journal of Computational Electronics - Variation of gate sidewall angle in V-shaped gate HEMTs impacts the device electrical performance, including self-heating effects, high-frequency operation...     

Fast adjustable spectrum sensing circuit for cognitive radio applications

A fast and adjustable spectrum sensing method is proposed using a phase frequency detector for cognitive radio applications. Using this method, spectral sensing can be done in a very short time by a low‐cost, low‐power circuit, compared with available implemented methods. Different aspects of sensing procedure in different situations are investigated including frequency sweep time and system errors. Accurate operation of this method is verified through simulations, and comparison with other methods shows faster sweep rates. Copyright © 2013 John Wiley & Sons, Ltd.     

Estimation of Suspended Sediment Concentration by M5 Model Tree Based on Hydrological and Moderate Resolution Imaging Spectroradiometer (MODIS) Data

The Estimation of suspended sediment concentration (SSC) is an important factor in river engineering, which is used as an indicator of land-use change, water quality studies, and all projects related to constructions in rivers. In this research, the M5 model tree and the Moderate Resolution Imaging Spectroradiometer (MODIS) data were utilized to estimate the SSC at Ahvaz station on the Karun River. In this study, 135 cloud-free images of the MODIS sensor on the Terra satellite were taken for days corresponding to field SSC data, during the years 2000 to 2015. Input parameters of the model tree in this study were flow discharge, derived from hydrological data, and red (R), near-infrared (NIR) bands, and NIR/R ratio extracted from MODIS imagery. The results of statistical analysis illustrate that the M5 model outperforms the sediment rating curve (SRC) method, which is the most common method of estimating suspended sediment load. The Nash-Sutcliffe efficiency index for the M5 model tree of 0.58 was achieved, which was much better than that of the SRC method (0.26). At high fluxes, the efficiency of the SRC method significantly reduced, while the model tree provides acceptable results. The global sensitivity analysis on the M5 model pointed out that 93% of output variance was established by the main effects of input parameters, and less than 7% belong to the interaction effects. 73% and 12% of output variance specified by the main effects of flow discharge and NIR/R ratio, respectively.

     

A comparison of artificial neural networks learning algorithms in predicting tendency for suicide

New approaches adopted by behavioral science researchers to use modern modeling and predicting tools such as artificial neural networks have necessitated the study and comparison of the efficiency of different learning algorithms of these networks for various applications. By using well-known and different learning algorithms, this study examines and compares the Perceptron artificial neural network as predicting tendency for suicide based on risk factors within 33 input parameters framework used in neural network. To find the “best” learning algorithm, the algorithms were compared in terms of train and capability. The experimental data were collected through questionnaires distributed among 800 university students. All questionnaires used in this research were standardized with appropriate validity and reliability. The study findings indicated that LM and BFG algorithms had close evaluation in terms of performance index and true acceptance rate (TAR), and they showed higher predictive accuracy than the other algorithms. Furthermore, CFG algorithm had the minimum training time.     

Multi-colored type-I Ag-doped ZnCdS/ZnS core/shell quantum dots with intense emission

Although doped quantum dots (d-dots) with intense and tunable emission have been studied for long time, there are still great efforts to prepare new ones with promising characteristics. In the present work, we used a mild/effective strategy for preparing high quality and aqueous-soluble Ag:ZnCdS/ZnS core/shell quantum dots (QDs) with N-acetyl-l-cysteine as the capping agent. Through investigating the experimental variables, the impurity-related emission intensity of the as-prepared samples was optimized. The capability of the present work on creating quantum structures with tunable emission across the entire visible spectrum was approved through simple but effective variation in Zn-to-Cd molar ratio. Indeed, as the Zn:Cd molar ratio changed from 2:0 to 0:2, the emission color was changed significantly from blue to red color with a satisfactory photoluminescence quantum yield. The quantum yield value reached ～41% for the as-prepared core/shell d-dots without any pre/post-treatment, which is a remarkable result for such aqueous-soluble structures. XRD, EDX, ICP, and TEM measurements were applied to determine the structural features of the QDs in a strong quantum confinement regime. The generality of preparation route, its biocompatibility, along with a multi-color emission, can create new opportunities especially for the white light emitting technologies, or multi-color bioimaging for theranostics.     

Identifying the mean step change of UBM chart

The traditional control charts are developed based on the assumption that the successive observations are independent and identically distributed. In some processes, the independence assumption is violated when there is autocorrelation between observations. To solve this problem, two methods, classified as model-based and model-free, could be applied. When a control chart alarms an assignable cause, it is essential to detect the process change point in order to remove the root cause. In the presence of autocorrelated data, different methods for change-point identification have been applied only for model-based methods. Hence, this is considered as the research gap and an attempt is made to fill this gap by applying maximum likelihood function in unweighted batch mean control chart, one of the most applied model-free methods. In this article, an estimator is presented to determine the change point for the first-order autoregressive process, AR(1). When a real change occurs, the performance of proposed estimator is evaluated through simulation.     

Evaluating the effects of herbal essences from spearmint and wild thyme on the quality of camel's milk

The aim of this study was to improve the sensory and physicochemical properties of camel's milk using two essential oils (EOs), spearmint (Mentha spicata) and wild thyme (Zataria multiflora). Total bacterial counts in the flavoured milks were lower than those of the plain milk, and microbial population was the lowest in the milk containing spearmint EO during 5 days of storage. Considering the sensory evaluations, milks treated with the above EOs received higher scores compared with those of untreated milk. The highest scores were given to the milk containing spearmint EO at 0.09 mL L^?1. No significant differences were observed in the mean particle sizes of the samples after 5 days of storage. The addition of EOs from camel's milk resulted in higher organoleptic properties and shelf life, and, in turn, it can improve the consumption rate of camel's milk.     

The occurrence,fate, and distribution of natural and synthetic hormones in different types of wastewater treatment plants in Iran

Over the past few years, the presence of steroid estrogens in the environment has become a major concern. In this study, the concentrations of estrone(E1), 17β-estradiol(E2), and 17α-ethinyl estradiol(EE2) were measured in some wastewater treatment plants(WWTPs) in Iran. These samples were collected from the municipal, rural,livestock, commercial, and hospital WWTPs, extracted by dispersive liquid–liquid micro extraction(DLLME)technique, derivatized, and detected by GC/MS. In these treatment plants, various processes including conventional activated sludge(CAS), aerated lagoon(AL), moving bed biofilm reactor(MBBR), and activated sludge with wetland(AS + WL) are used. The highest concentration of hormones was observed in the influents and effluents of livestock, municipal, commercial, and hospital WWTPs, respectively. The maximum elimination rate was obtained in MBBR followed by AS + WL, CAS and AL. The biodegradation and adsorption rates along with adsorption coefficients of lg kdand lg kocwere measured for all target compounds.     

Evaluation of the effects of AlkylPhenolic compounds on kinetic coefficients and biomass activity in MBBR by means of respirometric techniques

The presence of AlkylPhenols (APs) in aquatic systems is considered as one of the environmental concerns in recent decades which are generally used as surfactants. APs are endocrine disruptors and estrogen-mimicking, causing harmful effects such as feminization and carcinogenesis on aquatic environment and human health. The most commercially important APs are 4-NonylPhenol (4-NP) and 4-tert-OctylPhenol (4-t-OP). Moving bed biofilm reactor (MBBR), which combined attached and suspended growth advantages, is an advanced biological treatment process for municipal and industrial wastewaters that has drawn considerable attention from many researchers to remove toxic pollutants from wastewater. The aim of this research was to evaluate Bacterial activities and kinetic coefficients in the presence of APs. This study was carried out using laboratory-scale MBBR fed with synthetic wastewater containing 4-NP and 4-t-OP. The reactor was operated at different loads of chemical oxygen demand (COD) and APs and different hydraulic retention time (HRT). The respirometric technique was applied to investigate the effect of APs on heterotrophic and autotrophic activity and kinetic coefficients in biomass obtained from MBBR. Respirometric technique demonstrates a reliable tool in order to assess the biofilm kinetic coefficients and biomass viability to insert in the mathematical models. The calculated kinetic parameters were in the range of conventional and extended aeration activated sludge processes. The results demonstrate that APs have significant inhibitory effects on activity and growth rate of heterotrophic and autotrophic bacteria, heterotrophs have been less affected by the presence of 4-NP and 4-t-OP, and these compounds had greater inhibitory effects on autotrophic bacteria.     

Review of Nickel-Based Electrodeposited Tribo-Coatings

Among various methods used for protecting the industrial components from wear/abrasion failures, electrodeposition has attracted considerable attention in recent years because of its advantages such as being efficient, accurate, affordable, and easy to perform. In this regard, electrodeposition of nickel-based composite and alloy coatings is an inexpensive method compared with other coating methods such as chemical vapor deposition and physical vapor deposition. Furthermore, nickel-based composite electrodeposition is an eco-friendly substitute for conventional toxic coatings such as hard chrome. Embedding hard particles within the metallic matrix improves the wear resistance by increasing the ductility of the matrix in the contact area, changing the preferred grain growth direction to close-packed directions, and boosting dispersion and grain-refinement strength. In addition, lubricant particles provide superior anti-abrasive behavior because of their non-sticky nature. Several factors affect the incorporation of the particles into the electrodeposited coating and therefore the wear behavior of these coatings is related to different parameters such as current density, bath composition, pH, amount and size of the embedded particles. This review paper provides an overview of the wear behavior of nickel-based electrodeposited coatings including their composites and alloys with the focus on the parameters affecting wear rate, coefficient of friction, hardness, and roughness.