Characteristics of Suspended Solids Removal by Electrocoagulation

The electrochemical coagulation of a kaolin suspension was investigated at the currents of 0.06, 0.12, 0.22, 0.44, 0.85 A (corresponding to 0.68, 1.36, 2.50, 5.00, 9.66 mA·cm-2, respectively) for the contact time of 5, 10, 20, 30, and 50 min. The TSS removal efficiency at currents of 0.06 A, 0.12 A and 0.22 A increased with the amount of iron generated by the sacrificial anode, while the removal efficiencies did not increase proportionally with the amount of iron generated at the currents of 0.44 and 0.85 A, where electroflotation was clearly observed. Zeta potential measurement illustrated the presence of the highly positive charged particles created by sorption of highly charged polymeric metal hydroxyl species onto the negative surface charged kaolin particles at both low and high applied currents. The disappearance of the individual peaks after certain contact times indicated the attraction between these positive and negative charged particles causing agglomeration. It was concluded that charge neutralization of the individual species was not the only mechanism operating in the electrocoagulation process at any current level, but electrostatic attraction was likely to co-operate or mainly operate.

Artificial Neural Network Development by means of Genetic Programming with Graph Codification

The development of Artificial Neural Networks (ANNs) is usually a slow process in which the human expert has to test several architectures until he finds the one that achieves best results to solve a certain problem. This work presents a new technique that uses Genetic Programming (GP) for automatically generating ANNs. To do this, the GP algorithm had to be changed in order to work with graph structures, so ANNs can be developed. This technique also allows the obtaining of simplified networks that solve the problem with a small group of neurons. In order to measure the performance of the system and to compare the results with other ANN development methods by means of Evolutionary Computation (EC) techniques, several tests were performed with problems based on some of the most used test databases. The results of those comparisons show that the system achieves good results comparable with the already existing techniques and, in most of the cases, they worked better than those techniques.

Daily Global Solar Radiation Modeling Using Multi-Layer Perceptron (MLP) Neural Networks

Predict daily global solar radiation (GSR) based on meteorological variables, using Multi-layer perceptron (MLP) neural networks is the main objective of this study. Daily mean air temperature, relative humidity, sunshine hours, evaporation, wind speed, and soil temperature values between 2002 and 2006 for Dezful city in Iran (32° 16' N, 48° 25' E), are used in this study. The measured data between 2002 and 2005 are used to train the neural networks while the data for 214 days from 2006 are used as testing data.

Fast Wavelength Calibration Algorithm for Optical Spectrum Analyzers

In this paper an algorithm for fast wavelength calibration of Optical Spectrum Analyzers (OSAs) using low power reference gas spectra is proposed. In existing OSAs a reference spectrum with low noise for precise detection of the reference extreme values is needed. To generate this spectrum costly hardware with high optical power is necessary. With this new wavelength calibration algorithm it is possible to use a noisy reference spectrum and therefore hardware costs can be cut. With this algorithm the reference spectrum is filtered and the key information is extracted by segmenting and finding the local minima and maxima. Afterwards slope and offset of a linear correction function for best matching the measured and theoretical spectra are found by correlating the measured with the stored minima. With this algorithm a reliable wavelength referencing of an OSA can be implemented on a microcontroller with a calculation time of less than one second.

e/b-Learning Activities and High School Pedagogy

This article presents the implementation of several different e/b-Learning collaborative activities, used to improve the students learning process in an high school Polytechnic Institution. A new learning model arises, based on a combination between face-toface and distance leaning. Learning is now becoming centered with the development of collaborative activities, and its actors (teachers and students) have to be re-socialized to a new e/b-Learning paradigm. Measuring approaches are proposed for this model and results are presented, showing prospective correlation between students learning success and the use of online collaborative activities.

Exploring Structure of Mobile Ecosystem: Inter-Industry Network Analysis Approach

As increasing importance of symbiosis and cooperation among mobile communication industries, the mobile ecosystem has been especially highlighted in academia and practice. The structure of mobile ecosystem is quite complex and the ecological role of actors is important to understand that structure. In this respect, this study aims to explore structure of mobile ecosystem in the case of Korea using inter-industry network analysis. Then, the ecological roles in mobile ecosystem are identified using centrality measures as a result of network analysis: degree of centrality, closeness, and betweenness. The result shows that the manufacturing and service industries are separate. Also, the ecological roles of some actors are identified based on the characteristics of ecological terms: keystone, niche, and dominator. Based on the result of this paper, we expect that the policy makers can formulate the future of mobile industry and healthier mobile ecosystem can be constructed.

Role of Direct and Secondary Traumatic Experience on Later Functioning

Trauma in early life is widely regarded as a cause for adult mental health problems. This study explores the role of secondary trauma on later functioning in a sample of 359 university students enrolled in undergraduate psychology classes in the United States. Participants were initially divided into four groups based on 1) having directly experienced trauma (assaultive violence), 2) having directly experienced trauma and secondary traumatization through the unanticipated death of a close friend or family member or witnessing of an injury or shocking even), 3) having no experience of direct trauma but having experienced indirect trauma (secondary trauma), or 4) reporting no exposure. Participants completed a battery of measures on concepts associated with psychological functioning which included measures of psychological well-being, problem solving, coping and resiliency. Findings discuss differences in psychological functioning and resilience based on participants who experienced secondary traumatization and assaultive violence versus secondary traumatization alone.

Experimental Investigation of S-Rotors in Open and Bounded Flows

The common practice of operating S-rotor is in an open environment; however there are times when the rotor is installed in a bounded environment and there might be changes in the performance of the rotor. This paper presents the changes in the performance of S-rotor when operated in bounded flows. The investigation was conducted experimentally to compare the performance of the rotors in bounded environment against open environment. Three different rotors models were designed, fabricated and subjected to experimental measurements. All of the three models were having 600 mm height and 300 mm Diameter. They were tested in three different flow environments; namely: partially bounded environment, fully bounded environment and open environment. Rotors were found to have better starting up capabilities when operated in bounded environment. Apart from that, all rotors manage to achieve higher Power and Torque Coefficients at a higher Tip Speed Ratio as compared to the open environment.

On the Use of Image Processing Techniques for the Estimation of the Porosity of Textile Fabrics

This paper presents a novel approach to assessing textile porosity by the application of the image analysis techniques. The images of different types of sample fabrics, taken through a microscope when the fabric is placed over a constant light source,transfer the problem into the image analysis domain. Indeed, porosity can thus be expressed in terms of a brightness percentage index calculated on the digital microscope image. Furthermore, it is meaningful to compare the brightness percentage index with the air permeability and the tightness indices of each fabric type. We have experimentally shown that there exists an approximately linear relation between brightness percentage and air permeability indices.

Increase of Organization in Complex Systems

Measures of complexity and entropy have not converged to a single quantitative description of levels of organization of complex systems. The need for such a measure is increasingly necessary in all disciplines studying complex systems. To address this problem, starting from the most fundamental principle in Physics, here a new measure for quantity of organization and rate of self-organization in complex systems based on the principle of least (stationary) action is applied to a model system - the central processing unit (CPU) of computers. The quantity of organization for several generations of CPUs shows a double exponential rate of change of organization with time. The exact functional dependence has a fine, S-shaped structure, revealing some of the mechanisms of self-organization. The principle of least action helps to explain the mechanism of increase of organization through quantity accumulation and constraint and curvature minimization with an attractor, the least average sum of actions of all elements and for all motions. This approach can help describe, quantify, measure, manage, design and predict future behavior of complex systems to achieve the highest rates of self organization to improve their quality. It can be applied to other complex systems from Physics, Chemistry, Biology, Ecology, Economics, Cities, network theory and others where complex systems are present.

A Qualitative Evaluation of an Instrument for Measuring the Influence of Factors Affecting Use of Business-to-Employee (B2E) Portals

B2E portals represent a new class of web-based information technologies which many organisations are introducing in recent years to stay in touch with their distributed workforces and enable them to perform value added activities for organisations. However, actual usage of these emerging systems (measured using suitable instruments) has not been reported in the contemporary scholarly literature. We argue that many of the instruments to measure usage of various types of IT-enabled information systems are not directly applicable for B2E portals because they were developed for the context of traditional mainframe and PC-based information systems. It is therefore important to develop a new instrument for web-based portal technologies aimed at employees. In this article, we report on the development and initial qualitative evaluation of an instrument that seeks to operationaise a set of independent factors affecting the usage of portals by employees. The proposed instrument is useful to IT/e-commerce researchers and practitioners alike as it enhances their confidence in predicting employee usage of portals in organisations.

Acoustic Source Localization Based On the Extended Kalman Filter for an Underwater Vehicle with a Pair of Hydrophones

In this study, we consider a special situation that only a pair of hydrophone on a moving underwater vehicle is available to localize a fixed acoustic source of far distance. The trigonometry can be used in this situation by using two different DOA of different locations. Notice that the distance between the two locations should be measured. Therefore, we assume that the vehicle is sailing straightly and the moving distance for each unit time is measured continuously. However, the accuracy of the localization using the trigonometry is highly dependent to the accuracy of DOAs and measured moving distances. Therefore, we proposed another method based on the extended Kalman filter that gives more robust and accurate localization result.

Study the Effect of Soft Errors on FlexRay-Based Automotive Systems

FlexRay, as a communication protocol for automotive control systems, is developed to fulfill the increasing demand on the electronic control units for implementing systems with higher safety and more comfort. In this work, we study the impact of radiation-induced soft errors on FlexRay-based steer-by-wire system. We injected the soft errors into general purpose register set of FlexRay nodes to identify the most critical registers, the failure modes of the steer-by-wire system, and measure the probability distribution of failure modes when an error occurs in the register file.

Distribution and Source of PAHs in Surface Sediments of Canon River Mouth, Taiwan

Surface sediment samples were collected from the Canon River mouth, Taiwan and analyzed for polycyclic aromatic hydrocarbons (PAHs). Total PAHs concentrations varied from 337 to 1,252 ng/g dry weight, with a mean concentration of 827 ng/g dry weight. The spatial distribution of PAHs reveals that the PAHs concentration is relatively high in the river mouth region, and gradually diminishes toward the harbor region. Diagnostic ratios showed that the possible source of PAHs in the Canon River mouth could be petroleum combustion. The toxic equivalent concentrations (TEQcarc) of PAHs varied from 47 to 112 ng TEQ/g dry weight. Higher total TEQcarc values were found in the river mouth region. As compared with the US Sediment Quality Guidelines (SQGs), the observed levels of PAHs at Canon River mouth were lower than the effects range low (ERL), and would probably not exert adverse biological effects.

Food Habits and Nutritional Status of Fiji Rugby Players

The 15-a-side Fiji rugby team trains well in preparations for any rugby competition but rarely performs to expectations. In order to help the Fiji local based rugby players to identify some key basic areas in improving their performance, a series of workshops were conducted to assess their nutritional status and dietary habits in relation to energy demand during rugby matches. The nutrition workshop included the administration of questionnaires to 19 local based rugby players, requesting the following information: usual food intakes, training camp food intakes, carbohydrate loading, pre-game meals and post-game meals. The study revealed that poor eating habits of the players resulted in the low carbohydrate intake, which may have contributed to increase levels of fatigue leading to loss of stamina even before the second half of the game. It appears that the diet of most 15-a-side players does not provide enough energy to enable them to last the full eightyminutes of the game.

Automatic Segmentation of Lung Areas in Magnetic Resonance Images

Segmenting the lungs in medical images is a challenging and important task for many applications. In particular, automatic segmentation of lung cavities from multiple magnetic resonance (MR) images is very useful for oncological applications such as radiotherapy treatment planning. However, distinguishing of the lung areas is not trivial due to largely changing lung shapes, low contrast and poorly defined boundaries. In this paper, we address lung segmentation problem from pulmonary magnetic resonance images and propose an automated method based on a robust regionaided geometric snake with a modified diffused region force into the standard geometric model definition. The extra region force gives the snake a global complementary view of the lung boundary information within the image which along with the local gradient flow, helps detect fuzzy boundaries. The proposed method has been successful in segmenting the lungs in every slice of 30 magnetic resonance images with 80 consecutive slices in each image. We present results by comparing our automatic method to manually segmented lung cavities provided by an expert radiologist and with those of previous works, showing encouraging results and high robustness of our approach.

Investigation on Feature Extraction and Classification of Medical Images

In this paper we present the deep study about the Bio- Medical Images and tag it with some basic extracting features (e.g. color, pixel value etc). The classification is done by using a nearest neighbor classifier with various distance measures as well as the automatic combination of classifier results. This process selects a subset of relevant features from a group of features of the image. It also helps to acquire better understanding about the image by describing which the important features are. The accuracy can be improved by increasing the number of features selected. Various types of classifications were evolved for the medical images like Support Vector Machine (SVM) which is used for classifying the Bacterial types. Ant Colony Optimization method is used for optimal results. It has high approximation capability and much faster convergence, Texture feature extraction method based on Gabor wavelets etc..

Computing Entropy for Ortholog Detection

Biological sequences from different species are called or-thologs if they evolved from a sequence of a common ancestor species and they have the same biological function. Approximations of Kolmogorov complexity or entropy of biological sequences are already well known to be useful in extracting similarity information between such sequences -in the interest, for example, of ortholog detection. As is well known, the exact Kolmogorov complexity is not algorithmically computable. In prac-tice one can approximate it by computable compression methods. How-ever, such compression methods do not provide a good approximation to Kolmogorov complexity for short sequences. Herein is suggested a new ap-proach to overcome the problem that compression approximations may notwork well on short sequences. This approach is inspired by new, conditional computations of Kolmogorov entropy. A main contribution of the empir-ical work described shows the new set of entropy-based machine learning attributes provides good separation between positive (ortholog) and nega-tive (non-ortholog) data - better than with good, previously known alter-natives (which do not employ some means to handle short sequences well).Also empirically compared are the new entropy based attribute set and a number of other, more standard similarity attributes sets commonly used in genomic analysis. The various similarity attributes are evaluated by cross validation, through boosted decision tree induction C5.0, and by Receiver Operating Characteristic (ROC) analysis. The results point to the conclu-sion: the new, entropy based attribute set by itself is not the one giving the best prediction; however, it is the best attribute set for use in improving the other, standard attribute sets when conjoined with them.

Optical Fish Tracking in Fishways using Neural Networks

One of the main issues in Computer Vision is to extract the movement of one or several points or objects of interest in an image or video sequence to conduct any kind of study or control process. Different techniques to solve this problem have been applied in numerous areas such as surveillance systems, analysis of traffic, motion capture, image compression, navigation systems and others, where the specific characteristics of each scenario determine the approximation to the problem. This paper puts forward a Computer Vision based algorithm to analyze fish trajectories in high turbulence conditions in artificial structures called vertical slot fishways, designed to allow the upstream migration of fish through obstructions in rivers. The suggested algorithm calculates the position of the fish at every instant starting from images recorded with a camera and using neural networks to execute fish detection on images. Different laboratory tests have been carried out in a full scale fishway model and with living fishes, allowing the reconstruction of the fish trajectory and the measurement of velocities and accelerations of the fish. These data can provide useful information to design more effective vertical slot fishways.

Investigating the Effect of Using Capacitors in the Pumping Station on the Harmonic Contents (Case Study: Kafr El - Shikh Governorate, Egypt)

Power Factor (PF) is one of the most important parameters in the electrical systems, especially in the water pumping station. The low power factor value of the water pumping stations causes penalty for the electrical bill. There are many methods use for power factor improvement. Each one of them uses a capacitor on the electrical power network. The position of the capacitors is varied depends on many factors such as; voltage level and capacitors rating. Adding capacitors on the motor terminals increase the supply power factor from 0.8 to more than 0.9 but these capacitors cause some problems for the electrical grid network, such as increasing the harmonic contents of the grid line voltage. In this paper the effects of using capacitors in the water pumping stations to improve the power factor value on the harmonic contents of the electrical grid network are studied. One of large water pumping stations in Kafr El-Shikh Governorate in Egypt was used, as a case study. The effect of capacitors on the line voltage harmonic contents is measured. The station uses capacitors to improve the PF values at the 1 lkv grid network. The power supply harmonics values are measured by a power quality analyzer at different loading conditions. The results showed that; the capacitors improved the power factor value of the feeder and its value increased than 0.9. But the THD values are increased by adding these capacitors. The harmonic analysis showed that; the 13th, 17th, and 19th harmonics orders are increased also by adding the capacitors.