Development of a Neural Network based Algorithm for Multi-Scale Roughness Parameters and Soil Moisture Retrieval

The overall objective of this paper is to retrieve soil surfaces parameters namely, roughness and soil moisture related to the dielectric constant by inverting the radar backscattered signal from natural soil surfaces. Because the classical description of roughness using statistical parameters like the correlation length doesn't lead to satisfactory results to predict radar backscattering, we used a multi-scale roughness description using the wavelet transform and the Mallat algorithm. In this description, the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each having a spatial scale. A second step in this study consisted in adapting a direct model simulating radar backscattering namely the small perturbation model to this multi-scale surface description. We investigated the impact of this description on radar backscattering through a sensitivity analysis of backscattering coefficient to the multi-scale roughness parameters. To perform the inversion of the small perturbation multi-scale scattering model (MLS SPM) we used a multi-layer neural network architecture trained by backpropagation learning rule. The inversion leads to satisfactory results with a relative uncertainty of 8%.

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.

Applying Fuzzy FP-Growth to Mine Fuzzy Association Rules

In data mining, the association rules are used to find for the associations between the different items of the transactions database. As the data collected and stored, rules of value can be found through association rules, which can be applied to help managers execute marketing strategies and establish sound market frameworks. This paper aims to use Fuzzy Frequent Pattern growth (FFP-growth) to derive from fuzzy association rules. At first, we apply fuzzy partition methods and decide a membership function of quantitative value for each transaction item. Next, we implement FFP-growth to deal with the process of data mining. In addition, in order to understand the impact of Apriori algorithm and FFP-growth algorithm on the execution time and the number of generated association rules, the experiment will be performed by using different sizes of databases and thresholds. Lastly, the experiment results show FFPgrowth algorithm is more efficient than other existing methods.

On Strong(Weak) Domination in Fuzzy Graphs

Let G be a fuzzy graph. Then D Ôèå V is said to be a strong (weak) fuzzy dominating set of G if every vertex v ∈ V -D is strongly (weakly) dominated by some vertex u in D. We denote a strong (weak) fuzzy dominating set by sfd-set (wfd-set). The minimum scalar cardinality of a sfd-set (wfd-set) is called the strong (weak) fuzzy domination number of G and it is denoted by γsf (G)γwf (G). In this paper we introduce the concept of strong (weak) domination in fuzzy graphs and obtain some interesting results for this new parameter in fuzzy graphs.

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.

Biodiversity of Micromycetes Isolated from Soils of Different Agricultures in Kazakhstan and Their Plant Growth Promoting Potential

The comparative analysis of different taxonomic groups of microorganisms isolated from dark chernozem soils under different agricultures (alfalfa, melilot, sainfoin, soybean, rapeseed) at Almaty region of Kazakhstan was conducted. It was shown that the greatest number of micromycetes was typical to the soil planted with alfalfa and canola. Species diversity of micromycetes markedly decreases as it approaches the surface of the root, so that the species composition in the rhizosphere is much more uniform than in the virgin soil. Promising strains of microscopic fungi and yeast with plant growth-promoting activity to agricultures were selected. Among the selected fungi there are representatives of Penicillium bilaiae, Trichoderma koningii, Fusarium equiseti, Aspergillus ustus. The highest rates of growth and development of seedlings of plants observed under the influence of yeasts Aureobasidium pullulans, Rhodotorula mucilaginosa, Metschnikovia pulcherrima. Using molecular - genetic techniques confirmation of the identification results of selected micromycetes was conducted.

On the Solution of the Towers of Hanoi Problem

In this paper, two versions of an iterative loopless algorithm for the classical towers of Hanoi problem with O(1) storage complexity and O(2n) time complexity are presented. Based on this algorithm the number of different moves in each of pegs with its direction is formulated.

Development of Accident Predictive Model for Rural Roadway

This paper present the study carried out of accident analysis, black spot study and to develop accident predictive models based on the data collected at rural roadway, Federal Route 50 (F050) Malaysia. The road accident trends and black spot ranking were established on the F050. The development of the accident prediction model will concentrate in Parit Raja area from KM 19 to KM 23. Multiple non-linear regression method was used to relate the discrete accident data with the road and traffic flow explanatory variable. The dependent variable was modeled as the number of crashes namely accident point weighting, however accident point weighting have rarely been account in the road accident prediction Models. The result show that, the existing number of major access points, without traffic light, rise in speed, increasing number of Annual Average Daily Traffic (AADT), growing number of motorcycle and motorcar and reducing the time gap are the potential contributors of increment accident rates on multiple rural roadway.

The Effect of Multi-Layer Bandage on the Interface Pressure Applied by Compression Bandages

Medical compression bandages are widely used in the treatment of chronic venous disorder. In order to design effective compression bandages, researchers have attempted to describe the interface pressure applied by multi-layer bandages using mathematical models. This paper reports on the work carried out to compare and validate the mathematical models used to describe the interface pressure applied by multi-layer bandages. Both analytical and experimental results showed that using simple multiplication of a number of bandage layers with the pressure applied by one layer of bandage or ignoring the increase in the limb radius due to former layers of bandage will result in overestimating the pressure. Experimental results showed that the mathematical models, which take into consideration the increase in the limb radius due to former bandage layers, are more accurate than the one which does not.

SDS-induced Serine Protease Activity of an Antiviral Red Fluorescent Protein

A rare phenomenon of SDS-induced activation of a latent protease activity associated with the purified silkworm excretory red fluorescent protein (SE-RFP) was noticed. SE-RFP aliquots incubated with SDS for different time intervals indicated that the protein undergoes an obligatory breakdown into a number of subunits which exhibit autoproteolytic (acting upon themselves) and/or heteroproteolytic (acting on other proteins) activities. A strong serine protease activity of SE-RFP subunits on Bombyx mori nucleopolyhedrovirus (BmNPV) polyhedral protein was detected by zymography technique. A complete inhibition of BmNPV infection to silkworms was observed by the oral administration assay of the SE-RFP. Here, it is proposed that the SE-RFP prevents the initial infection of BmNPV to silkworms by obliterating the polyhedral protein. This is the first report on a silkworm red fluorescent protein that exhibits a protease activity on exposure to SDS. The present studies would help in understanding the antiviral mechanism of silkworm red fluorescent proteins.

The Optimal Equilibrium Capacity of Information Hiding Based on Game Theory

Game theory could be used to analyze the conflicted issues in the field of information hiding. In this paper, 2-phase game can be used to build the embedder-attacker system to analyze the limits of hiding capacity of embedding algorithms: the embedder minimizes the expected damage and the attacker maximizes it. In the system, the embedder first consumes its resource to build embedded units (EU) and insert the secret information into EU. Then the attacker distributes its resource evenly to the attacked EU. The expected equilibrium damage, which is maximum damage in value from the point of view of the attacker and minimum from the embedder against the attacker, is evaluated by the case when the attacker attacks a subset from all the EU. Furthermore, the optimal equilibrium capacity of hiding information is calculated through the optimal number of EU with the embedded secret information. Finally, illustrative examples of the optimal equilibrium capacity are presented.

Design of High-speed Modified Booth Multipliers Operating at GHz Ranges

This paper describes the pipeline architecture of high-speed modified Booth multipliers. The proposed multiplier circuits are based on the modified Booth algorithm and the pipeline technique which are the most widely used to accelerate the multiplication speed. In order to implement the optimally pipelined multipliers, many kinds of experiments have been conducted. The speed of the multipliers is greatly improved by properly deciding the number of pipeline stages and the positions for the pipeline registers to be inserted. We described the proposed modified Booth multiplier circuits in Verilog HDL and synthesized the gate-level circuits using 0.13um standard cell library. The resultant multiplier circuits show better performance than others. Since the proposed multipliers operate at GHz ranges, they can be used in the systems requiring very high performance.

Numerical Study of Flow around Flat Tube between Parallel Walls

Flow around a flat tube is studied numerically. Reynolds number is defined base on equivalent circular tube and it is varied in range of 100 to 300. Equations are solved by using finite volume method and results are presented in form of drag and lift coefficient. Results show that drag coefficient of flat tube is up to 66% lower than circular tube with equivalent diameter. In addition, by increasing l/D from 1 to 2, the drag coefficient of flat tube is decreased about 14-27%.

Optimization of Parametric Studies Using Strategies of Sampling Techniques

To improve the efficiency of parametric studies or tests planning the method is proposed, that takes into account all input parameters, but only a few simulation runs are performed to assess the relative importance of each input parameter. For K input parameters with N input values the total number of possible combinations of input values equals NK. To limit the number of runs, only some (totally N) of possible combinations are taken into account. The sampling procedure Updated Latin Hypercube Sampling is used to choose the optimal combinations. To measure the relative importance of each input parameter, the Spearman rank correlation coefficient is proposed. The sensitivity and the influence of all parameters are analyzed within one procedure and the key parameters with the largest influence are immediately identified.

Genetic-Based Multi Resolution Noisy Color Image Segmentation

Segmentation of a color image composed of different kinds of regions can be a hard problem, namely to compute for an exact texture fields. The decision of the optimum number of segmentation areas in an image when it contains similar and/or un stationary texture fields. A novel neighborhood-based segmentation approach is proposed. A genetic algorithm is used in the proposed segment-pass optimization process. In this pass, an energy function, which is defined based on Markov Random Fields, is minimized. In this paper we use an adaptive threshold estimation method for image thresholding in the wavelet domain based on the generalized Gaussian distribution (GGD) modeling of sub band coefficients. This method called Normal Shrink is computationally more efficient and adaptive because the parameters required for estimating the threshold depend on sub band data energy that used in the pre-stage of segmentation. A quad tree is employed to implement the multi resolution framework, which enables the use of different strategies at different resolution levels, and hence, the computation can be accelerated. The experimental results using the proposed segmentation approach are very encouraging.

Control-flow Complexity Measurement of Processes and Weyuker's Properties

Process measurement is the task of empirically and objectively assigning numbers to the properties of business processes in such a way as to describe them. Desirable attributes to study and measure include complexity, cost, maintainability, and reliability. In our work we will focus on investigating process complexity. We define process complexity as the degree to which a business process is difficult to analyze, understand or explain. One way to analyze a process- complexity is to use a process control-flow complexity measure. In this paper, an attempt has been made to evaluate the control-flow complexity measure in terms of Weyuker-s properties. Weyuker-s properties must be satisfied by any complexity measure to qualify as a good and comprehensive one.

Auto Tuning PID Controller based on Improved Genetic Algorithm for Reverse Osmosis Plant

An optimal control of Reverse Osmosis (RO) plant is studied in this paper utilizing the auto tuning concept in conjunction with PID controller. A control scheme composing an auto tuning stochastic technique based on an improved Genetic Algorithm (GA) is proposed. For better evaluation of the process in GA, objective function defined newly in sense of root mean square error has been used. Also in order to achieve better performance of GA, more pureness and longer period of random number generation in operation are sought. The main improvement is made by replacing the uniform distribution random number generator in conventional GA technique to newly designed hybrid random generator composed of Cauchy distribution and linear congruential generator, which provides independent and different random numbers at each individual steps in Genetic operation. The performance of newly proposed GA tuned controller is compared with those of conventional ones via simulation.

Effect of Flaying Capacitors on Improving the 4 Level Three-Cell Inverter

With the rapid advanced of technology, the industrial processes become increasingly demanding, from the point of view, power quality and controllability. The advent of multi levels inverters responds partially to these requirements. But actually, the new generation of multi-cells inverters permits to reach more performances, since, it offers more voltage levels. The disadvantage in the increase of voltage levels by the number of cells in cascades is on account of series igbts synchronisation loss, from where, a limitation of cells in cascade to 4. Regarding to these constraints, a new topology is proposed in this paper, which increases the voltage levels of the three-cell inverter from 4 to 8; with the same number of igbts, and using less stored energy in the flaying capacitors. The details of operation and modelling of this new inverter structure are also presented, then tested thanks to a three phase induction motor. KeywordsFlaying capacitors, Multi-cells inverter, pwm, switchers, modelling.

A Systems Modeling Approach to Support Environmentally Sustainable Business Development in Manufacturing SMEs

Small and Medium Sized Enterprises (SMEs) play an important role in many economies. In New Zealand, for example, 97% of all manufacturing companies employ less than 100 staff, and generate the predominant part of this industry sector-s economic output. Manufacturing SMEs as a group also have a significant impact on the environment. This situation is similar in many developed economies, including the European Union. Sustainable economic development therefore needs to strongly consider the role of manufacturing SMEs, who generally find it challenging to move towards more environmentally friendly business practices. This paper presents a systems thinking approach to modelling and understanding the factors which have an influence on the successful uptake of environmental practices in small and medium sized manufacturing companies. It presents a number of causal loop diagrams which have been developed based on primary action research, and a thorough understanding of the literature in this area. The systems thinking model provides the basis for further development of a strategic framework for the successful uptake of environmental innovation in manufacturing SMEs.

The Use of Minor Setups in an EPQ Model with Constrained Production Period Length

Extensive research has been devoted to economic production quantity (EPQ) problem. However, no attention has been paid to problems where production period length is constrained. In this paper, we address the problem of deciding the optimal production quantity and the number of minor setups within each cycle, in which, production period length is constrained but a minor setup is possible for pass the constraint. A mathematical model is developed and Iterated Local Search (ILS) is proposed to solve this problem. Finally, solution procedure illustrated with a numerical example and results are analyzed.