Sweet Corn Water Productivity under Several Deficit Irrigation Regimes Applied during Vegetative Growth Stage using Treated Wastewater as Water Irrigation Source

Yield and Crop Water Productivity are crucial issues in sustainable agriculture, especially in high-demand resource crops such as sweet corn. This study was conducted to investigate agronomic responses such as plant growth, yield and soil parameters (EC and Nitrate accumulation) to several deficit irrigation treatments (100, 75, 50, 25 and 0% of ETm) applied during vegetative growth stage, rainfed treatment was also tested. The finding of this research indicates that under deficit irrigation during vegetative growth stage applying 75% of ETm lead to increasing of 19.4% in terms of fresh ear yield, 9.4% in terms of dry grain yield, 10.5% in terms of number of ears per plant, 11.5% for the 1000 grains weight and 19% in terms of crop water productivity compared with fully irrigated treatment. While those parameters in addition to root, shoot and plant height has been affected by deficit irrigation during vegetative growth stage when increasing water stress degree more than 50% of ETm.

Fungal Leaching of Hazardous Heavy Metals from a Spent Hydrotreating Catalyst

In this study, the ability of Aspergillus niger and Penicillium simplicissimum to extract heavy metals from a spent refinery catalyst was investigated. For the first step, a spent processing catalyst from one of the oil refineries in Iran was physically and chemically characterized. Aspergillus niger and Penicillium simplicissimum were used to mobilize Al/Co/Mo/Ni from hazardous spent catalysts. The fungi were adapted to the mixture of metals at 100-800 mg L-1 with increments in concentration of 100 mg L-1. Bioleaching experiments were carried out in batch cultures. To investigate the production of organic acids in sucrose medium, analyses of the culture medium by HPLC were performed at specific time intervals after inoculation. The results obtained from Inductive coupled plasma-optical emission spectrometry (ICP-OES) showed that after the one-step bioleaching process using Aspergillus niger, maximum removal efficiencies of 27%, 66%, 62% and 38% were achieved for Al, Co, Mo and Ni, respectively. However, the highest removal efficiencies using Penicillium simplicissimum were of 32%, 67%, 65% and 38% for Al, Co, Mo and Ni, respectively

Effect of the Machine Frame Structures on the Frequency Responses of Spindle Tool

Chatter vibration has been a troublesome problem for a machine tool toward the high precision and high speed machining. Essentially, the machining performance is determined by the dynamic characteristics of the machine tool structure and dynamics of cutting process. Therefore the dynamic vibration behavior of spindle tool system greatly determines the performance of machine tool. The purpose of this study is to investigate the influences of the machine frame structure on the dynamic frequency of spindle tool unit through finite element modeling approach. To this end, a realistic finite element model of the vertical milling system was created by incorporated the spindle-bearing model into the spindle head stock of the machine frame. Using this model, the dynamic characteristics of the milling machines with different structural designs of spindle head stock and identical spindle tool unit were demonstrated. The results of the finite element modeling reveal that the spindle tool unit behaves more compliant when the excited frequency approaches the natural mode of the spindle tool; while the spindle tool show a higher dynamic stiffness at lower frequency that may be initiated by the structural mode of milling head. Under this condition, it is concluded that the structural configuration of spindle head stock associated with the vertical column of milling machine plays an important role in determining the machining dynamics of the spindle unit.

A Hybrid Neural Network and Gravitational Search Algorithm (HNNGSA) Method to Solve well known Wessinger's Equation

This study presents a hybrid neural network and Gravitational Search Algorithm (HNGSA) method to solve well known Wessinger's equation. To aim this purpose, gravitational search algorithm (GSA) technique is applied to train a multi-layer perceptron neural network, which is used as approximation solution of the Wessinger's equation. A trial solution of the differential equation is written as sum of two parts. The first part satisfies the initial/ boundary conditions and does not contain any adjustable parameters and the second part which is constructed so as not to affect the initial/boundary conditions. The second part involves adjustable parameters (the weights and biases) for a multi-layer perceptron neural network. In order to demonstrate the presented method, the obtained results of the proposed method are compared with some known numerical methods. The given results show that presented method can introduce a closer form to the analytic solution than other numerical methods. Present method can be easily extended to solve a wide range of problems.

Adsorption of Copper by using Microwave Incinerated Rice Husk Ash (MIRHA)

Many non-conventional adsorbent have been studied as economic alternative to commercial activated carbon and mostly agricultural waste have been introduced such as rubber leaf powder and hazelnut shell. Microwave Incinerated Rice Husk Ash (MIRHA), produced from the rice husk is one of the low-cost materials that were used as adsorbent of heavy metal. The aim of this research was to study the feasibility of using MIRHA500 and MIRHA800 as adsorbent for the removal of Cu(II) metal ions from aqueous solutions by the batch studies. The adsorption of Cu(II) into MIRHA500 and MIRH800 favors Fruendlich isotherm and imply pseudo – kinetic second order which applied chemisorptions

Towards Sustainable Urban Transportation Case Studies

Climate change is one of the greatest environmental, economic, and social challenges of our time. Urban transportation has had a major negative impact on our environment—most of our air pollution comes from transport. This paper explores ways to move toward a more sustainable transport system by focusing on creating a more efficient and livable city and improving the environmental efficiency of transport activity. The analytical study covers some international examples of applying sustainable transportation and uses them to suggest a frame work to develop the transportation system in Egypt to be sustainable and more intelligent.

Effects of Coupling Agent and Flame Retardant on the Performances of Oil Palm Empty Fruit Bunch Fiber Reinforced Polypropylene Composites

Alkali treated oil palm empty fruit bunch (EFB) fibres (TEFBF) and untreated EFBF fibers (UEFBF) were incorporated in polypropylene (PP) with and without malic anhydride grafted PP (MAPP) and magnesium hydroxide as flame retardant (FR) to produce TEFBF-PP and UEFBF-PP composites by the melt casting method. The composites were characterized by mechanical and burning tests along with a scanning electron microscope and Fourier transform infrared spectroscopy. The significant improvement in flexural modulus (133%) and flame retardant property (60%) of TEFBF-PP composite with MAPP and FR is observed. The improved mechanical property is discussed by the development of encapsulated textures.

Prediction of Watermelon Consumer Acceptability based on Vibration Response Spectrum

It is difficult to judge ripeness by outward characteristics such as size or external color. In this paper a nondestructive method was studied to determine watermelon (Crimson Sweet) quality. Responses of samples to excitation vibrations were detected using laser Doppler vibrometry (LDV) technology. Phase shift between input and output vibrations were extracted overall frequency range. First and second were derived using frequency response spectrums. After nondestructive tests, watermelons were sensory evaluated. So the samples were graded in a range of ripeness based on overall acceptability (total desired traits consumers). Regression models were developed to predict quality using obtained results and sample mass. The determination coefficients of the calibration and cross validation models were 0.89 and 0.71 respectively. This study demonstrated feasibility of information which is derived vibration response curves for predicting fruit quality. The vibration response of watermelon using the LDV method is measured without direct contact; it is accurate and timely, which could result in significant advantage for classifying watermelons based on consumer opinions.

Dynamics and Control of Bouncing Ball

This paper investigates the control of a bouncing ball using Model Predictive Control. Bouncing ball is a benchmark problem for various rhythmic tasks such as juggling, walking, hopping and running. Humans develop intentions which may be perceived as our reference trajectory and tries to track it. The human brain optimizes the control effort needed to track its reference; this forms the central theme for control of bouncing ball in our investigations.

A Nobel Approach for Campus Monitoring

This paper presents one of the best applications of wireless sensor network for campus Monitoring. With the help of PIR sensor, temperature sensor and humidity sensor, effective utilization of energy resources has been implemented in one of rooms of Sharda University, Greater Noida, India. The RISC microcontroller is used here for analysis of output of sensors and providing proper control using ZigBee protocol. This wireless sensor module presents a tremendous power saving method for any campus

Modeling and Simulating of Gas Turbine Cooled Blades

In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and quasistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine first stage nozzle blade.

Nitrogen Removal in a High-efficiency Denitrification/Oxic Filter treatment System for Advanced Treatment of Municipal Wastewater

Biological treatment of secondary effluent wastewater by two combined denitrification/oxic filtration systems packed with Lock type(denitrification filter) and ceramic ball (oxic filter) has been studied for 5months. Two phases of operating conditions were carried out with an influent nitrate and ammonia concentrations varied from 5.8 to 11.7mg/L and 5.4 to 12.4mg/L,respectively. Denitrification/oxic filter treatment system were operated under an EBCT (Empty Bed Contact Time) of 4h at system recirculation ratio in the range from 0 to 300% (Linear Velocity increased 19.5m/d to 78m/d). The system efficiency of denitrification , nitrification over 95% respectively. Total nitrogen and COD removal range from 54.6%(recirculation 0%) to 92.3%(recirculation 300%) and 10% to 62.5%, respectively.

Application of Computational Intelligence for Sensor Fault Detection and Isolation

The new idea of this research is application of a new fault detection and isolation (FDI) technique for supervision of sensor networks in transportation system. In measurement systems, it is necessary to detect all types of faults and failures, based on predefined algorithm. Last improvements in artificial neural network studies (ANN) led to using them for some FDI purposes. In this paper, application of new probabilistic neural network features for data approximation and data classification are considered for plausibility check in temperature measurement. For this purpose, two-phase FDI mechanism was considered for residual generation and evaluation.

MITAutomatic ECG Beat Tachycardia Detection Using Artificial Neural Network

The application of Neural Network for disease diagnosis has made great progress and is widely used by physicians. An Electrocardiogram carries vital information about heart activity and physicians use this signal for cardiac disease diagnosis which was the great motivation towards our study. In our work, tachycardia features obtained are used for the training and testing of a Neural Network. In this study we are using Fuzzy Probabilistic Neural Networks as an automatic technique for ECG signal analysis. As every real signal recorded by the equipment can have different artifacts, we needed to do some preprocessing steps before feeding it to our system. Wavelet transform is used for extracting the morphological parameters of the ECG signal. The outcome of the approach for the variety of arrhythmias shows the represented approach is superior than prior presented algorithms with an average accuracy of about %95 for more than 7 tachy arrhythmias.

Study of EEGs from Somatosensory Cortex and Alzheimer's Disease Sources

This study is to investigate the electroencephalogram (EEG) differences generated from a normal and Alzheimer-s disease (AD) sources. We also investigate the effects of brain tissue distortions due to AD on EEG. We develop a realistic head model from T1 weighted magnetic resonance imaging (MRI) using finite element method (FEM) for normal source (somatosensory cortex (SC) in parietal lobe) and AD sources (right amygdala (RA) and left amygdala (LA) in medial temporal lobe). Then, we compare the AD sourced EEGs to the SC sourced EEG for studying the nature of potential changes due to sources and 5% to 20% brain tissue distortions. We find an average of 0.15 magnification errors produced by AD sourced EEGs. Different brain tissue distortion models also generate the maximum 0.07 magnification. EEGs obtained from AD sources and different brain tissue distortion levels vary scalp potentials from normal source, and the electrodes residing in parietal and temporal lobes are more sensitive than other electrodes for AD sourced EEG.

A New Fuzzy Decision Support Method for Analysis of Economic Factors of Turkey's Construction Industry

Imperfect knowledge cannot be avoided all the time. Imperfections may have several forms; uncertainties, imprecision and incompleteness. When we look to classification of methods for the management of imperfect knowledge we see fuzzy set-based techniques. The choice of a method to process data is linked to the choice of knowledge representation, which can be numerical, symbolic, logical or semantic and it depends on the nature of the problem to be solved for example decision support, which will be mentioned in our study. Fuzzy Logic is used for its ability to manage imprecise knowledge, but it can take advantage of the ability of neural networks to learn coefficients or functions. Such an association of methods is typical of so-called soft computing. In this study a new method was used for the management of imprecision for collected knowledge which related to economic analysis of construction industry in Turkey. Because of sudden changes occurring in economic factors decrease competition strength of construction companies. The better evaluation of these changes in economical factors in view of construction industry will made positive influence on company-s decisions which are dealing construction.

Implementation of Vertical Neutron Camera (VNC) for ITER Fusion Plasma Neutron Source Profile Reconstruction

In present work the problem of the ITER fusion plasma neutron source parameter reconstruction using only the Vertical Neutron Camera data was solved. The possibility of neutron source parameter reconstruction was estimated by the numerical simulations and the analysis of adequateness of mathematic model was performed. The neutron source was specified in a parametric form. The numerical analysis of solution stability with respect to data distortion was done. The influence of the data errors on the reconstructed parameters is shown: • is reconstructed with errors less than 4% at all examined values of δ (until 60%); • is determined with errors less than 10% when δ do not overcome 5%; • is reconstructed with relative error more than 10 %; • integral intensity of the neutron source is determined with error 10% while δ error is less than 15%; where -error of signal measurements, (R0,Z0), the plasma center position,- /parameter of neutron source profile.

Simulating Laboratory Short Term Aging to Suit Malaysian Field Conditions

This paper characterizes the effects of artificial short term aging in the laboratory on the rheological properties of virgin 80/100 penetration grade asphalt binder. After several years in service, asphalt mixture started to deteriorate due to aging. Aging is a complex physico-chemical phenomenon that influences asphalt binder rheological properties causing a deterioration in asphalt mixture performance. To ascertain asphalt binder aging effects, the virgin, artificially aged and extracted asphalt binder were tested via the Rolling Thin film Oven (RTFO), Dynamic Shear Rheometer (DSR) and Rotational Viscometer (RV). A comparative study between laboratory and field aging conditions were also carried out. The results showed that the specimens conditioned for 85 minutes inside the RTFO was insufficient to simulate the actual short term aging caused that took place in the field under Malaysian field conditions

Diagnostic Investigation of Liftoff Time of Solid Propellant Rockets

In this paper parametric analytical studies have been carried out to examine the intrinsic flow physics pertaining to the liftoff time of solid propellant rockets. Idealized inert simulators of solid rockets are selected for numerical studies to examining the preignition chamber dynamics. Detailed diagnostic investigations have been carried out using an unsteady two-dimensional k-omega turbulence model. We conjectured from the numerical results that the altered variations of the igniter jet impingement angle, turbulence level, time and location of the first ignition, flame spread characteristics, the overall chamber dynamics including the boundary layer growth history are having bearing on the time for nozzle flow chocking for establishing the required thrust for the rocket liftoff. We concluded that the altered flow choking time of strap-on motors with the pre-determined identical ignition time at the lift off phase will lead to the malfunctioning of the rocket. We also concluded that, in the light of the space debris, an error in predicting the liftoff time can lead to an unfavorable launch window amounts the satellite injection errors and/or the mission failures.

Solving Bus Terminal Location Problem Using Genetic Algorithm

Bus networks design is an important problem in public transportation. The main step to this design, is determining the number of required terminals and their locations. This is an especial type of facility location problem, a large scale combinatorial optimization problem that requires a long time to be solved. The genetic algorithm (GA) is a search and optimization technique which works based on evolutionary principle of natural chromosomes. Specifically, the evolution of chromosomes due to the action of crossover, mutation and natural selection of chromosomes based on Darwin's survival-of-the-fittest principle, are all artificially simulated to constitute a robust search and optimization procedure. In this paper, we first state the problem as a mixed integer programming (MIP) problem. Then we design a new crossover and mutation for bus terminal location problem (BTLP). We tested the different parameters of genetic algorithm (for a sample problem) and obtained the optimal parameters for solving BTLP with numerical try and error.