Novel Dual Stage Membrane Bioreactor for the Continuous Remediation of Electroplating Wastewater

In this study, the designed dual stage membrane bioreactor (MBR) system was conceptualized for the treatment of cyanide and heavy metals in electroplating wastewater. The design consisted of a primary treatment stage to reduce the impact of fluctuations and the secondary treatment stage to remove the residual cyanide and heavy metal contaminants in the wastewater under alkaline pH conditions. The primary treatment stage contained hydrolyzed Citrus sinensis (C. sinensis) pomace and the secondary treatment stage contained active Aspergillus awamori (A. awamori) biomass, supplemented solely with C. sinensis pomace extract from the hydrolysis process. An average of 76.37%, 95.37%, 93.26 and 94.76% and 99.55%, 99.91%, 99.92% and 99.92% degradation efficiency for total cyanide (T-CN), including the sorption of nickel (Ni), zinc (Zn) and copper (Cu) were observed after the first and second treatment stages, respectively. Furthermore, cyanide conversion by-products degradation was 99.81% and 99.75 for both formate (CHOO-) and ammonium (NH4 +) after the second treatment stage. After the first, second and third regeneration cycles of the C. sinensis pomace in the first treatment stage, Ni, Zn and Cu removal achieved was 99.13%, 99.12% and 99.04% (first regeneration cycle), 98.94%, 98.92% and 98.41% (second regeneration cycle) and 98.46 %, 98.44% and 97.91% (third regeneration cycle), respectively. There was relatively insignificant standard deviation detected in all the measured parameters in the system which indicated reproducibility of the remediation efficiency in this continuous system.

Appraisal of Energy Efficiency of Urban Development Plans: The Fidelity Concept on Izmir-Balcova Case

Design and land use are closely linked to the energy efficiency levels for an urban area. The current city planning practice does not involve an effective land useenergy evaluation in its 'blueprint' urban plans. The study proposed an appraisal method that can be embedded in GIS programs using five planning criteria as how far a planner can give away from the planning principles (criteria) for the most energy output s/he can obtain. The case of Balcova, a district in the Izmir Metropolitan area, is used conformingly for evaluating the proposed master plan and the geothermal energy (heating only) use for the concern district. If the land use design were proposed accordingly at-most energy efficiency (a 30% obtained), mainly increasing the density around the geothermal wells and also proposing more mixed use zones, we could have 17% distortion (infidelity to the main planning principles) from the original plan. The proposed method can be an effective tool for planners as simulation media, of which calculations can be made by GIS ready tools, to evaluate efficiency levels for different plan proposals, letting to know how much energy saving causes how much deviation from the other planning ideals. Lower energy uses can be possible for different land use proposals for various policy trials.

Dynamic Models versus Frailty Models for Recurrent Event Data

Recurrent event data is a special type of multivariate survival data. Dynamic and frailty models are one of the approaches that dealt with this kind of data. A comparison between these two models is studied using the empirical standard deviation of the standardized martingale residual processes as a way of assessing the fit of the two models based on the Aalen additive regression model. Here we found both approaches took heterogeneity into account and produce residual standard deviations close to each other both in the simulation study and in the real data set.

Brain MRI Segmentation and Lesions Detection by EM Algorithm

In Multiple Sclerosis, pathological changes in the brain results in deviations in signal intensity on Magnetic Resonance Images (MRI). Quantitative analysis of these changes and their correlation with clinical finding provides important information for diagnosis. This constitutes the objective of our work. A new approach is developed. After the enhancement of images contrast and the brain extraction by mathematical morphology algorithm, we proceed to the brain segmentation. Our approach is based on building statistical model from data itself, for normal brain MRI and including clustering tissue type. Then we detect signal abnormalities (MS lesions) as a rejection class containing voxels that are not explained by the built model. We validate the method on MR images of Multiple Sclerosis patients by comparing its results with those of human expert segmentation.

Effect of Endplate Shape on Performance and Stability of Wings-in Ground (WIG) Craft

Numerical analysis for the aerodynamic characteristics of the WIG (wing-in ground effect) craft with highly cambered and aspect ratio of one is performed to predict the ground effect for the case of with- and without- lower-extension endplate. The analysis is included varying angles of attack from 0 to10 deg. and ground clearances from 5% of chord to 50%. Due to the ground effect, the lift by rising in pressure on the lower surface is increased and the influence of wing-tip vortices is decreased. These two significant effects improve the lift-drag ratio. On the other hand, the endplate prevents the high-pressure air escaping from the air cushion at the wing tip and causes to increase the lift and lift-drag ratio further. It is found from the visualization of computation results that two wing-tip vortices are generated from each surface of the wing tip and their strength are weak and diminished rapidly. Irodov-s criteria are also evaluated to investigate the static height stability. The comparison of Irodov-s criteria shows that the endplate improves the deviation of the static height stability with respect to pitch angles and heights. As the results, the endplate can improve the aerodynamic characteristics and static height stability of wings in ground effect, simultaneously.

Tracking Objects in Color Image Sequences: Application to Football Images

In this paper, we present a comparative study between two computer vision systems for objects recognition and tracking, these algorithms describe two different approach based on regions constituted by a set of pixels which parameterized objects in shot sequences. For the image segmentation and objects detection, the FCM technique is used, the overlapping between cluster's distribution is minimized by the use of suitable color space (other that the RGB one). The first technique takes into account a priori probabilities governing the computation of various clusters to track objects. A Parzen kernel method is described and allows identifying the players in each frame, we also show the importance of standard deviation value research of the Gaussian probability density function. Region matching is carried out by an algorithm that operates on the Mahalanobis distance between region descriptors in two subsequent frames and uses singular value decomposition to compute a set of correspondences satisfying both the principle of proximity and the principle of exclusion.

An Efficient Adaptive Thresholding Technique for Wavelet Based Image Denoising

This frame work describes a computationally more efficient and adaptive threshold estimation method for image denoising in the wavelet domain based on Generalized Gaussian Distribution (GGD) modeling of subband coefficients. In this proposed method, the choice of the threshold estimation is carried out by analysing the statistical parameters of the wavelet subband coefficients like standard deviation, arithmetic mean and geometrical mean. The noisy image is first decomposed into many levels to obtain different frequency bands. Then soft thresholding method is used to remove the noisy coefficients, by fixing the optimum thresholding value by the proposed method. Experimental results on several test images by using this method show that this method yields significantly superior image quality and better Peak Signal to Noise Ratio (PSNR). Here, to prove the efficiency of this method in image denoising, we have compared this with various denoising methods like wiener filter, Average filter, VisuShrink and BayesShrink.

Increasing Value Added of Recycling Business Management: A Case of Thailand

This policy participation action research explores the roles of Thai government units during its 2010 fiscal year on how to create value added to recycling business in the central part of Thailand. The research aims to a) study how the government plays a role to support the business, and its problems and obstacles on supporting the business, b) to design a strategic action – short, medium, and long term plans -- to create value added to the recycling business, particularly in local full-loop companies/organizations licensed by Wongpanit Waste Separation Plant as well as those licensed by the Department of Provincial Administration. Mixed method research design, i.e., a combination of quantitative and qualitative methods is utilized in the present study in both data collection and analysis procedures. Quantitative data was analyzed by frequency, percent value, mean scores, and standard deviation, and aimed to note trend and generalizations. Qualitative data was collected via semi-structured interviews/focus group interviews to explore in-depth views of the operators. The sampling included 1,079 operators in eight provinces in the central part of Thailand.

The Determination of Cellulose Spiral Angle by Small-Angle X-Ray Scattering from Structurally Characterized Acacia mangium Cell Wall

The spiral angle of the elementary cellulose fibril in the wood cell wall, often called microfibril angle, (MFA). Microfibril angle in hardwood is one of the key determinants of solid timber performance due to its strong influence on the stiffness, strength, shrinkage, swelling, thermal-dynamics mechanical properties and dimensional stability of wood. Variation of MFA (degree) in the S2 layer of the cell walls among Acacia mangium trees was determined using small-angle X-ray scattering (SAXS). The length and orientation of the microfibrils of the cell walls in the irradiated volume of the thin samples are measured using SAXS and optical microscope for 3D surface measurement. The undetermined parameters in the analysis are the MFA, (M) and the standard deviation (σФ) of the intensity distribution arising from the wandering of the fibril orientation about the mean value. Nine separate pairs of values are determined for nine different values of the angle of the incidence of the X-ray beam relative to the normal to the radial direction in the sample. The results show good agreement. The curve distribution of scattered intensity for the real cell wall structure is compared with that calculated with that assembly of rectangular cells with the same ratio of transverse to radial cell wall length. It is demonstrated that for β = 45°, the peaks in the curve intensity distribution for the real and the rectangular cells coincide. If this peak position is Ф45, then the MFA can be determined from the relation M = tan-1 (tan Ф45 / cos 45°), which is precise for rectangular cells. It was found that 92.93% of the variation of MFA can be attributed to the distance from pith to bark. Here we shall present our results of the MFA in the cell wall with respect to its shape, structure and the distance from pith to park as an important fast check and yet accurate towards the quality of wood, its uses and application.

Defect Detection of Tiles Using 2D-Wavelet Transform and Statistical Features

In this article, a method has been offered to classify normal and defective tiles using wavelet transform and artificial neural networks. The proposed algorithm calculates max and min medians as well as the standard deviation and average of detail images obtained from wavelet filters, then comes by feature vectors and attempts to classify the given tile using a Perceptron neural network with a single hidden layer. In this study along with the proposal of using median of optimum points as the basic feature and its comparison with the rest of the statistical features in the wavelet field, the relational advantages of Haar wavelet is investigated. This method has been experimented on a number of various tile designs and in average, it has been valid for over 90% of the cases. Amongst the other advantages, high speed and low calculating load are prominent.

Automatic Generation Control of an Interconnected Power System with Capacitive Energy Storage

This paper is concerned with the application of small rating Capacitive Energy Storage units for the improvement of Automatic Generation Control of a multiunit multiarea power system. Generation Rate Constraints are also considered in the investigations. Integral Squared Error technique is used to obtain the optimal integral gain settings by minimizing a quadratic performance index. Simulation studies reveal that with CES units, the deviations in area frequencies and inter-area tie-power are considerably improved in terms of peak deviations and settling time as compared to that obtained without CES units.

Conventional and Fuzzy Logic Controllers at Generator Location for Low Frequency Oscillation Damping

This paper investigates and compares performance of various conventional and fuzzy logic based controllers at generator locations for oscillation damping. Performance of combination of conventional and fuzzy logic based controllers also studied by comparing overshoot on the active power deviation response for a small disturbance and damping ratio of the critical mode. Fuzzy logic based controllers can not be modeled in the state space form to get the eigenvalues and corresponding damping ratios of various modes of generators and controllers. Hence, a new method based on tracing envelop of time domain waveform is also presented and used in the paper for comparing performance of controllers. The paper also shows that if the fuzzy based controllers designed separately combining them could not lead to a better performance.

Industrial Compressor Anti-Surge Computer Control

The paper presents a compressor anti-surge control system, that results in maximizing compressor throughput with pressure standard deviation reduction, increased safety margin between design point and surge limit line and avoiding possible machine surge. Alternative control strategies are presented.

Typical Day Prediction Model for Output Power and Energy Efficiency of a Grid-Connected Solar Photovoltaic System

A novel typical day prediction model have been built and validated by the measured data of a grid-connected solar photovoltaic (PV) system in Macau. Unlike conventional statistical method used by previous study on PV systems which get results by averaging nearby continuous points, the present typical day statistical method obtain the value at every minute in a typical day by averaging discontinuous points at the same minute in different days. This typical day statistical method based on discontinuous point averaging makes it possible for us to obtain the Gaussian shape dynamical distributions for solar irradiance and output power in a yearly or monthly typical day. Based on the yearly typical day statistical analysis results, the maximum possible accumulated output energy in a year with on site climate conditions and the corresponding optimal PV system running time are obtained. Periodic Gaussian shape prediction models for solar irradiance, output energy and system energy efficiency have been built and their coefficients have been determined based on the yearly, maximum and minimum monthly typical day Gaussian distribution parameters, which are obtained from iterations for minimum Root Mean Squared Deviation (RMSD). With the present model, the dynamical effects due to time difference in a day are kept and the day to day uncertainty due to weather changing are smoothed but still included. The periodic Gaussian shape correlations for solar irradiance, output power and system energy efficiency have been compared favorably with data of the PV system in Macau and proved to be an improvement than previous models.

Efficient Tools for Managing Uncertainties in Design and Operation of Engineering Structures

Actual load, material characteristics and other quantities often differ from the design values. This can cause worse function, shorter life or failure of a civil engineering structure, a machine, vehicle or another appliance. The paper shows main causes of the uncertainties and deviations and presents a systematic approach and efficient tools for their elimination or mitigation of consequences. Emphasis is put on the design stage, which is most important for reliability ensuring. Principles of robust design and important tools are explained, including FMEA, sensitivity analysis and probabilistic simulation methods. The lifetime prediction of long-life objects can be improved by long-term monitoring of the load response and damage accumulation in operation. The condition evaluation of engineering structures, such as bridges, is often based on visual inspection and verbal description. Here, methods based on fuzzy logic can reduce the subjective influences.

Evaluating per-user Fairness of Goal-Oriented Parallel Computer Job Scheduling Policies

Fair share objective has been included into the goaloriented parallel computer job scheduling policy recently. However, the previous work only presented the overall scheduling performance. Thus, the per-user performance of the policy is still lacking. In this work, the details of per-user fair share performance under the Tradeoff-fs(Tx:avgX) policy will be further evaluated. A basic fair share priority backfill policy namely RelShare(1d) is also studied. The performance of all policies is collected using an event-driven simulator with three real job traces as input. The experimental results show that the high demand users are usually benefited under most policies because their jobs are large or they have a lot of jobs. In the large job case, one job executed may result in over-share during that period. In the other case, the jobs may be backfilled for performances. However, the users with a mixture of jobs may suffer because if the smaller jobs are executing the priority of the remaining jobs from the same user will be lower. Further analysis does not show any significant impact of users with a lot of jobs or users with a large runtime approximation error.