Effect of Inhibitors on Weld Corrosion under Sweet Conditions Using Flow Channel

The aim of this paper is to compare the effectiveness and electrochemical behavior of typical oilfield corrosion inhibitors with previous oilfield corrosion inhibitors under the same electrochemical techniques to control preferential weld corrosion of X65 pipeline steel in artificial seawater saturated with carbon dioxide at a pressure of one bar. A secondary aim is to investigate the conditions under which current reversal takes place. A flow channel apparatus was used in the laboratory to simulate the actual condition that occurs in marine pipelines. Different samples from the parent metal, the weld metal and the heat affected zone in the pipeline steel were galvanically coupled. The galvanic currents flowing between the weld regions were recorded using zero-resistance ammeters and tested under static and flowing conditions in both inhibited and uninhibited media. The results show that a current reversal took place when 30ppm of both green oilfield inhibitors were present, resulting in accelerated weld corrosion.

Model Transformation with a Visual Control Flow Language

Graph rewriting-based visual model processing is a widely used technique for model transformation. Visual model transformations often need to follow an algorithm that requires a strict control over the execution sequence of the transformation steps. Therefore, in Visual Model Processors (VMPs) the execution order of the transformation steps is crucial. This paper presents the visual control flow support of Visual Modeling and Transformation System (VMTS), which facilitates composing complex model transformations of simple transformation steps and executing them. The VMTS Visual Control Flow Language (VCFL) uses stereotyped activity diagrams to specify control flow structures and OCL constraints to choose between different control flow branches. This paper introduces VCFL, discusses its termination properties and provides an algorithm to support the termination analysis of VCFL transformations.

Generation of Sets of Synthetic Classifiers for the Evaluation of Abstract-Level Combination Methods

This paper presents a new technique for generating sets of synthetic classifiers to evaluate abstract-level combination methods. The sets differ in terms of both recognition rates of the individual classifiers and degree of similarity. For this purpose, each abstract-level classifier is considered as a random variable producing one class label as the output for an input pattern. From the initial set of classifiers, new slightly different sets are generated by applying specific operators, which are defined at the purpose. Finally, the sets of synthetic classifiers have been used to estimate the performance of combination methods for abstract-level classifiers. The experimental results demonstrate the effectiveness of the proposed approach.

Applying GQM Approach towards Development of Criterion-Referenced Assessment Model for OO Programming Courses

The most influential programming paradigm today is object oriented (OO) programming and it is widely used in education and industry. Recognizing the importance of equipping students with OO knowledge and skills, it is not surprising that most Computer Science degree programs offer OO-related courses. How do we assess whether the students have acquired the right objectoriented skills after they have completed their OO courses? What are object oriented skills? Currently none of the current assessment techniques would be able to provide this answer. Traditional forms of OO programming assessment provide a ways for assigning numerical scores to determine letter grades. But this rarely reveals information about how students actually understand OO concept. It appears reasonable that a better understanding of how to define and assess OO skills is needed by developing a criterion referenced model. It is even critical in the context of Malaysia where there is currently a growing concern over the level of competency of Malaysian IT graduates in object oriented programming. This paper discussed the approach used to develop the criterion-referenced assessment model. The model can serve as a guideline when conducting OO programming assessment as mentioned. The proposed model is derived by using Goal Questions Metrics methodology, which helps formulate the metrics of interest. It concluded with a few suggestions for further study.

A Strategic Evaluation Approach for Defining the Maturity of Manufacturing Technologies

Due to dynamic evolution, the ability of a manufacturing technology to produce a special product is changing. Therefore, it is essential to monitor the established techniques and processes to detect whether a company-s production will fit future circumstances. Concerning the manufacturing technology planning process, companies must decide when to change to a new technology for maintaining and increasing competitive advantages. In this context, the maturity assessment of the focused technologies is crucial. This article presents an approach for defining the maturity of a manufacturing technology from a strategic point of view. The concept is based on the approach of technology readiness level (TRL) according to NASA (National Aeronautics and Space Administration), but also includes dynamic changes. Therefore, the model takes into account the concept of the technology life cycle. Furthermore, it enables a company to estimate the ideal date for implementation of a new manufacturing technology.

Interference Reduction Technique in Multistage Multiuser Detector for DS-CDMA System

This paper presents the results related to the interference reduction technique in multistage multiuser detector for asynchronous DS-CDMA system. To meet the real-time requirements for asynchronous multiuser detection, a bit streaming, cascade architecture is used. An asynchronous multiuser detection involves block-based computations and matrix inversions. The paper covers iterative-based suboptimal schemes that have been studied to decrease the computational complexity, eliminate the need for matrix inversions, decreases the execution time, reduces the memory requirements and uses joint estimation and detection process that gives better performance than the independent parameter estimation method. The stages of the iteration use cascaded and bits processed in a streaming fashion. The simulation has been carried out for asynchronous DS-CDMA system by varying one parameter, i.e., number of users. The simulation result exhibits that system gives optimum bit error rate (BER) at 3rd stage for 15-users.

Automatic Generation Control of Multi-Area Electric Energy Systems Using Modified GA

A modified Genetic Algorithm (GA) based optimal selection of parameters for Automatic Generation Control (AGC) of multi-area electric energy systems is proposed in this paper. Simulations on multi-area reheat thermal system with and without consideration of nonlinearity like governor dead band followed by 1% step load perturbation is performed to exemplify the optimum parameter search. In this proposed method, a modified Genetic Algorithm is proposed where one point crossover with modification is employed. Positional dependency in respect of crossing site helps to maintain diversity of search point as well as exploitation of already known optimum value. This makes a trade-off between exploration and exploitation of search space to find global optimum in less number of generations. The proposed GA along with decomposition technique as developed has been used to obtain the optimum megawatt frequency control of multi-area electric energy systems. Time-domain simulations are conducted with trapezoidal integration along with decomposition technique. The superiority of the proposed method over existing one is verified from simulations and comparisons.

Performance Evaluation of A Stratified Chilled- Water Thermal Storage System

In countries with hot climates, air-conditioning forms a large proportion of annual peak electrical demand, requiring expansion of power plants to meet the peak demand, which goes unused most of the time. Use of well-designed cool storage can offset the peak demand to a large extent. In this study, an air conditioning system with naturally stratified storage tank was designed, constructed and tested. A new type of diffuser was designed and used in this study. Factors that influence the performance of chilled water storage tanks were investigated. The results indicated that stratified storage tank consistently stratified well without any physical barrier. Investigation also showed that storage efficiency decreased with increasing flow rate due to increased mixing of warm and chilled water. Diffuser design and layout primarily affected the mixing near the inlet diffuser and the extent of this mixing had primary influence on the shape of the thermocline. The heat conduction through tank walls and through the thermocline caused widening of mixed volume. Thermal efficiency of stratified storage tanks was as high as 90 percent, which indicates that stratified tanks can effectively be used as a load management technique.

Seed-Based Region Growing (SBRG) vs Adaptive Network-Based Inference System (ANFIS) vs Fuzzyc-Means (FCM): Brain Abnormalities Segmentation

Segmentation of Magnetic Resonance Imaging (MRI) images is the most challenging problems in medical imaging. This paper compares the performances of Seed-Based Region Growing (SBRG), Adaptive Network-Based Fuzzy Inference System (ANFIS) and Fuzzy c-Means (FCM) in brain abnormalities segmentation. Controlled experimental data is used, which designed in such a way that prior knowledge of the size of the abnormalities are known. This is done by cutting various sizes of abnormalities and pasting it onto normal brain tissues. The normal tissues or the background are divided into three different categories. The segmentation is done with fifty seven data of each category. The knowledge of the size of the abnormalities by the number of pixels are then compared with segmentation results of three techniques proposed. It was proven that the ANFIS returns the best segmentation performances in light abnormalities, whereas the SBRG on the other hand performed well in dark abnormalities segmentation.

Evaluating Spectral Relationships between Signals by Removing the Contribution of a Common, Periodic Source A Partial Coherence-based Approach

Partial coherence between two signals removing the contribution of a periodic, deterministic signal is proposed for evaluating the interrelationship in multivariate systems. The estimator expression was derived and shown to be independent of such periodic signal. Simulations were used for obtaining its critical value, which were found to be the same as those for Gaussian signals, as well as for evaluating the technique. An Illustration with eletroencephalografic (EEG) signals during photic stimulation is also provided. The application of the proposed technique in both simulation and real EEG data indicate that it seems to be very specific in removing the contribution of periodic sources. The estimate independence of the periodic signal may widen partial coherence application to signal analysis, since it could be used together with simple coherence to test for contamination in signals by a common, periodic noise source.

Fish Marketing: A Panacea towards Sustainable Agriculture in Ogun State, Nigeria

This study assessed fish marketing as panacea towards sustainable agriculture in Ogun State, Nigeria. Multi-stage sampling technique was used in the selection of 150 fish marketers for this study. Descriptive statistics were used for the objectives while Product Pearson Moment Correlation was used to test the hypothesis. Result of the findings revealed that the mean age of the respondents was 38.60 years. Majority (93.33%) of the respondents had acceptable levels of formal education. Many (44.00%) of the respondents had spent 1-5 years in fish marketing. The average quantity of fish sold in a day was 94.10kg. However, efficient fish marketing were hindered by inadequate processing equipment, storage rooms and ice holding facilities (86.67%). There was a significant relationship between socio-economic characteristics and profit realized from fish marketing (p < 0.05). It was recommended that storage and warehousing facilities should be provided to the fish marketers in the study area.

Optimized Detection in Multi-Antenna System using Particle Swarm Algorithm

In this paper we propose a Particle Swarm heuristic optimized Multi-Antenna (MA) system. Efficient MA systems detection is performed using a robust stochastic evolutionary computation algorithm based on movement and intelligence of swarms. This iterative particle swarm optimized (PSO) detector significantly reduces the computational complexity of conventional Maximum Likelihood (ML) detection technique. The simulation results achieved with this proposed MA-PSO detection algorithm show near optimal performance when compared with ML-MA receiver. The performance of proposed detector is convincingly better for higher order modulation schemes and large number of antennas where conventional ML detector becomes non-practical.

Line Balancing in the Hard Disk Drive Process Using Simulation Techniques

Simulation model is an easy way to build up models to represent real life scenarios, to identify bottlenecks and to enhance system performance. Using a valid simulation model may give several advantages in creating better manufacturing design in order to improve the system performances. This paper presents result of implementing a simulation model to design hard disk drive manufacturing process by applying line balancing to improve both productivity and quality of hard disk drive process. The line balance efficiency showed 86% decrease in work in process, output was increased by an average of 80%, average time in the system was decreased 86% and waiting time was decreased 90%.

Predicting the Three Major Dimensions of the Learner-s Emotions from Brainwaves

This paper investigates how the use of machine learning techniques can significantly predict the three major dimensions of learner-s emotions (pleasure, arousal and dominance) from brainwaves. This study has adopted an experimentation in which participants were exposed to a set of pictures from the International Affective Picture System (IAPS) while their electrical brain activity was recorded with an electroencephalogram (EEG). The pictures were already rated in a previous study via the affective rating system Self-Assessment Manikin (SAM) to assess the three dimensions of pleasure, arousal, and dominance. For each picture, we took the mean of these values for all subjects used in this previous study and associated them to the recorded brainwaves of the participants in our study. Correlation and regression analyses confirmed the hypothesis that brainwave measures could significantly predict emotional dimensions. This can be very useful in the case of impassive, taciturn or disabled learners. Standard classification techniques were used to assess the reliability of the automatic detection of learners- three major dimensions from the brainwaves. We discuss the results and the pertinence of such a method to assess learner-s emotions and integrate it into a brainwavesensing Intelligent Tutoring System.

The Long Run Relationship between Exports and Imports in South Africa: Evidence from Cointegration Analysis

This study empirically examines the long run equilibrium relationship between South Africa’s exports and imports using quarterly data from 1985 to 2012. The theoretical framework used for the study is based on Johansen’s Maximum Likelihood cointegration technique which tests for both the existence and number of cointegration vectors that exists. The study finds that both the series are integrated of order one and are cointegrated. A statistically significant cointegrating relationship is found to exist between exports and imports. The study models this unique linear and lagged relationship using a Vector Error Correction Model (VECM). The findings of the study confirm the existence of a long run equilibrium relationship between exports and imports.

Predicting Protein-Protein Interactions from Protein Sequences Using Phylogenetic Profiles

In this study, a high accuracy protein-protein interaction prediction method is developed. The importance of the proposed method is that it only uses sequence information of proteins while predicting interaction. The method extracts phylogenetic profiles of proteins by using their sequence information. Combining the phylogenetic profiles of two proteins by checking existence of homologs in different species and fitting this combined profile into a statistical model, it is possible to make predictions about the interaction status of two proteins. For this purpose, we apply a collection of pattern recognition techniques on the dataset of combined phylogenetic profiles of protein pairs. Support Vector Machines, Feature Extraction using ReliefF, Naive Bayes Classification, K-Nearest Neighborhood Classification, Decision Trees, and Random Forest Classification are the methods we applied for finding the classification method that best predicts the interaction status of protein pairs. Random Forest Classification outperformed all other methods with a prediction accuracy of 76.93%

Effect of Shallow Groundwater Table on the Moisture Depletion Pattern in Crop Root Zone

Different techniques for estimating seasonal water use from soil profile water depletion frequently do not account for flux below the root zone. Shallow water table contribution to supply crop water use may be important in arid and semi-arid regions. Development of predictive root uptake models, under influence of shallow water table makes it possible for planners to incorporate interaction between water table and root zone into design of irrigation projects. A model for obtaining soil moisture depletion from root zone and water movement below it is discussed with the objective to determine impact of shallow water table on seasonal moisture depletion patterns under water table depth variation, up to the bottom of root zone. The role of different boundary conditions has also been considered. Three crops: Wheat (Triticum aestivum), Corn (Zea mays) and Potato (Solanum tuberosum), common in arid & semi-arid regions, are chosen for the study. Using experimentally obtained soil moisture depletion values for potential soil moisture conditions, moisture depletion patterns using a non linear root uptake model have been obtained for different water table depths. Comparative analysis of the moisture depletion patterns under these conditions show a wide difference in percent depletion from different layers of root zone particularly top and bottom layers with middle layers showing insignificant variation in moisture depletion values. Moisture depletion in top layer, when the water table rises to root zone increases by 19.7%, 22.9% & 28.2%, whereas decrease in bottom layer is 68.8%, 61.6% & 64.9% in case of wheat, corn & potato respectively. The paper also discusses the causes and consequences of increase in moisture depletion from top layers and exceptionally high reduction in bottom layer, and the possible remedies for the same. The numerical model developed for the study can be used to help formulating irrigation strategies for areas where shallow groundwater of questionable quality is an option for crop production.

Visualizing Transit Through a Web Based Geographic Information System

Currently in many major cities, public transit schedules are disseminated through lists of routes, grids of stop times and static maps. This paper describes a web based geographic information system which disseminates the same schedule information through intuitive GIS techniques. Using data from Calgary, Canada, an map based interface has been created to allow users to see routes, stops and moving buses all at once. Zoom and pan controls as well as satellite imagery allows users to apply their personal knowledge about the local geography to achieve faster, and more pertinent transit results. Using asynchronous requests to web services, users are immersed in an application where buses and stops can be added and removed interactively, without the need to wait for responses to HTTP requests.

Vector Control of Multimotor Drive

Three-phase induction machines are today a standard for industrial electrical drives. Cost, reliability, robustness and maintenance free operation are among the reasons these machines are replacing dc drive systems. The development of power electronics and signal processing systems has eliminated one of the greatest disadvantages of such ac systems, which is the issue of control. With modern techniques of field oriented vector control, the task of variable speed control of induction machines is no longer a disadvantage. The need to increase system performance, particularly when facing limits on the power ratings of power supplies and semiconductors, motivates the use of phase number other than three, In this paper a novel scheme of connecting two, three phase induction motors in parallel fed by two inverters; viz. VSI and CSI and their vector control is presented.

A New IT-Convergence Service Design Framework

In many countries, digital city or ubiquitous city (u-City) projects have been initiated to provide digitalized economic environments to cities. Recently in Korea, Kangwon Province has started the u-Kangwon project to boost local economy with digitalized tourism services. We analyze the limitations of the ubiquitous IT approach through the u-Kangwon case. We have found that travelers are more interested in quality over speed in access of information. For improved service quality, we are looking to develop an IT-convergence service design framework (ISDF). The ISDF is based on the service engineering technique and composed of three parts: Service Design, Service Simulation, and the Service Platform.