A K-Means Based Clustering Approach for Finding Faulty Modules in Open Source Software Systems

Prediction of fault-prone modules provides one way to support software quality engineering. Clustering is used to determine the intrinsic grouping in a set of unlabeled data. Among various clustering techniques available in literature K-Means clustering approach is most widely being used. This paper introduces K-Means based Clustering approach for software finding the fault proneness of the Object-Oriented systems. The contribution of this paper is that it has used Metric values of JEdit open source software for generation of the rules for the categorization of software modules in the categories of Faulty and non faulty modules and thereafter empirically validation is performed. The results are measured in terms of accuracy of prediction, probability of Detection and Probability of False Alarms.

Modeling and Optimization of Abrasive Waterjet Parameters using Regression Analysis

Abrasive waterjet is a novel machining process capable of processing wide range of hard-to-machine materials. This research addresses modeling and optimization of the process parameters for this machining technique. To model the process a set of experimental data has been used to evaluate the effects of various parameter settings in cutting 6063-T6 aluminum alloy. The process variables considered here include nozzle diameter, jet traverse rate, jet pressure and abrasive flow rate. Depth of cut, as one of the most important output characteristics, has been evaluated based on different parameter settings. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. The pairwise effects of process parameters settings on process response outputs are also shown graphically. The proposed model is then embedded into a Simulated Annealing algorithm to optimize the process parameters. The optimization is carried out for any desired values of depth of cut. The objective is to determine proper levels of process parameters in order to obtain a certain level of depth of cut. Computational results demonstrate that the proposed solution procedure is quite effective in solving such multi-variable problems.

The Determination of Rating Points of Objects with Qualitative Characteristics and their Usagein Decision Making Problems

The paper presents the method developed to assess rating points of objects with qualitative indexes. The novelty of the method lies in the fact that the authors use linguistic scales that allow to formalize the values of the indexes with the help of fuzzy sets. As a result it is possible to operate correctly with dissimilar indexes on the unified basis and to get stable final results. The obtained rating points are used in decision making based on fuzzy expert opinions.

Three Computational Mathematics Techniques: Comparative Determination of Area under Curve

The objective of this manuscript is to find area under the plasma concentration- time curve (AUC) for multiple doses of salbutamol sulphate sustained release tablets (Ventolin® oral tablets SR 8 mg, GSK, Pakistan) in the group of 18 healthy adults by using computational mathematics techniques. Following the administration of 4 doses of Ventolin® tablets 12 hourly to 24 healthy human subjects and bioanalysis of obtained plasma samples, plasma drug concentration-time profile was constructed. AUC, an important pharmacokinetic parameter, was measured using integrated equation of multiple oral dose regimens. The approximated AUC was also calculated by using computational mathematics techniques such as repeated rectangular, repeated trapezium and repeated Simpson's rule and compared with exact value of AUC calculated by using integrated equation of multiple oral dose regimens to find best computational mathematics method that gives AUC values closest to exact. The exact values of AUC for four consecutive doses of Ventolin® oral tablets were 150.5819473, 157.8131756, 164.4178231 and 162.78 ng.h/ml while the closest values approximated AUC values were 149.245962, 157.336171, 164.2585768 and 162.289224 ng.h/ml, respectively as found by repeated rectangular rule. The errors in the approximated values of AUC were negligible. It is concluded that all computational tools approximated values of AUC accurately but the repeated rectangular rule gives slightly better approximated values of AUC as compared to repeated trapezium and repeated Simpson's rules.

Effects of Winter and Spring Sowing on Yield Components of Safflower Genotypes

The research was conducted with three replications as “Randomized Block Design” in Konya-Turkey ecological conditions. In the study, 16 of promising safflower lines (A8, E1, F4, F6, G16, H14, I1), and 1 cultivar (Dinçer) were evaluated in 2008-09 growing season. Some of the yield components such as plant height (cm), first branch height (cm), number of branches per plant, 1000 seed weight (g), seed yield (kg ha-1), oil content (%), oil yield (kg ha-1) were determined. Winter sowing showed higher values than spring sowing. The highest values were taken from Dinçer for plant height (86.7 cm), E1 (37.5 cm) for first branch height, F6 for number of branch (11.6 per plant), I1 for number of head (24.9 per plant), A8 for 1000 seed weight (51.75 g), Dinçer for seed yield (2927.1 kg ha-1), oil content (28.79 %) and also for oil yield (87.44 kg ha-1) respectively.

The Role of State in Combating Religious Extremism and Terrorism

terrorism and extremism are among the most dangerous and difficult to forecast the phenomena of our time, which are becoming more diverse forms and rampant. Terrorist attacks often produce mass casualties, involve the destruction of material and spiritual values, beyond the recovery times, sow hatred among nations, provoke war, mistrust and hatred between the social and national groups, which sometimes can not be overcome within a generation. Currently, the countries of Central Asia are a topical issue – the threat of terrorism and religious extremism, which grow not only in our area, but throughout the world. Of course, in each of the terrorist threat is assessed differently. In our country the problem of terrorism should not be acutely. Thus, after independence and sovereignty of Kazakhstan has chosen the path of democracy, progress and free economy. With the policy of the President of Kazakhstan Nursultan Nazarbayev and well-organized political and economic reforms, there has been economic growth and rising living standards, socio-political stability, ensured civil peace and accord in society [1].

On the Influence of Certain Natural Factors on the Sperm Quality and Sexual Behaviour of Rams

In the Northern hemisphere, sheep reproduction is seasonal (September-November). Among several natural factors influencing the reproduction status of rams, we studied the daylight length and temperature. Rams from different breeds were studied: Merinos de Palas (half-precocious), Karakul de Botosani (halfbelated) and Turcana (belated breed, low reproductive plasticity). In Merinos de Palas, ejaculate volume during sexual repose is 51.3% from normal quantity. When autumn climate was experimentally induced, ejaculate volume reached 98.45% (Merinos), 94.97% (Karakul) and 97.59% (Turcana). Semen density increased from 1.031-1.033 till 1.035 after exposition to artificial light and temperature conditions. Spermatozoids mobility and sperm pH improved, passing over 82% and 6.75, values identical to those in the natural reproduction season. Behaviour analysis after photoperiodicity indicated that over 83.3% Merinos and Karakul males and all Turcana rams exteriorised normal and intense sexual reflexes. Certain effort and reduced expenses brought rams in good condition, producing higher quantity and quality sperm.

A Novel Spectrum Sensing Scheme Based on Periodicity of DVB-T Pilot Signals

This paper proposes a novel spectrum sensing technique for the digital video broadcasting-terrestrial (DVB-T) systems, which utilizes the periodicity of pilot signals in the orthogonal frequency division multiplexing (OFDM) symbols. The proposed scheme can overcome the effect of the timing synchronization error by recorrelating the correlation values in the same sample distances. The numerical results demonstrate that the detection probability performance of the proposed scheme outperforms that of the conventional scheme when there exists a timing synchronization error.

Comparison of Compression Ability Using DCT and Fractal Technique on Different Imaging Modalities

Image compression is one of the most important applications Digital Image Processing. Advanced medical imaging requires storage of large quantities of digitized clinical data. Due to the constrained bandwidth and storage capacity, however, a medical image must be compressed before transmission and storage. There are two types of compression methods, lossless and lossy. In Lossless compression method the original image is retrieved without any distortion. In lossy compression method, the reconstructed images contain some distortion. Direct Cosine Transform (DCT) and Fractal Image Compression (FIC) are types of lossy compression methods. This work shows that lossy compression methods can be chosen for medical image compression without significant degradation of the image quality. In this work DCT and Fractal Compression using Partitioned Iterated Function Systems (PIFS) are applied on different modalities of images like CT Scan, Ultrasound, Angiogram, X-ray and mammogram. Approximately 20 images are considered in each modality and the average values of compression ratio and Peak Signal to Noise Ratio (PSNR) are computed and studied. The quality of the reconstructed image is arrived by the PSNR values. Based on the results it can be concluded that the DCT has higher PSNR values and FIC has higher compression ratio. Hence in medical image compression, DCT can be used wherever picture quality is preferred and FIC is used wherever compression of images for storage and transmission is the priority, without loosing picture quality diagnostically.

A Dynamic RGB Intensity Based Steganography Scheme

Steganography meaning covered writing. Steganography includes the concealment of information within computer files [1]. In other words, it is the Secret communication by hiding the existence of message. In this paper, we will refer to cover image, to indicate the images that do not yet contain a secret message, while we will refer to stego images, to indicate an image with an embedded secret message. Moreover, we will refer to the secret message as stego-message or hidden message. In this paper, we proposed a technique called RGB intensity based steganography model as RGB model is the technique used in this field to hide the data. The methods used here are based on the manipulation of the least significant bits of pixel values [3][4] or the rearrangement of colors to create least significant bit or parity bit patterns, which correspond to the message being hidden. The proposed technique attempts to overcome the problem of the sequential fashion and the use of stego-key to select the pixels.

Implementation of Response Surface Methodology using in Small Brown Rice Peeling Machine: Part I

Implementation of response surface methodology (RSM) was employed to study the effects of two factor (rubber clearance and round per minute) in brown rice peeling machine of The optimal BROKENS yield (19.02, average of three repeats),.The optimized composition derived from RSM regression was analyzed using Regression analysis and Analysis of Variance (ANOVA). At a significant level α = 0.05, the values of Regression coefficient, R 2 (adj)were 97.35 % and standard deviation were 1.09513. The independent variables are initial rubber clearance, and round per minute parameters namely. The investigating responses are final rubber clearance, and round per minute (RPM). The restriction of the optimization is the designated.

Examination of the Water and Nutrient Utilization of Maize Hybrids on Chernozem Soil

The research was set up on chernozem soil at the Látókép AGTC MÉK research area of the University of Debrecen in Hungary. We examined the yield, the yield production per 1kg NPK fertilizer and the water and nutrient utilization of hybrid PR37N01 and PR37M81 in 2013. We found that PR37N01 produced the most yield at the level of N120+P (17,476kg ha-1) while PR37M81 reached the highest yield at level N150+PK (16,754kg ha-1). Studies related to yield production per 1kg NPK indicated that the best results were achieved at level N30+PK compared to the control treatment. Yield production per 1kg NPK was17.6kg kg-1 by P37N01 and 44.2kg kg-1 by PR37M81. By comparing the water utilization of hybrids we found that the worst water utilization results were reached in the control treatment (PR37N01: 26.2kg mm-1, PR37M81: 19.5kg mm-1). The best water utilization values were produced at level N120+PK in the case of hybrid PR37N01 (32.1kg mm-1) and at N150+PK in the case of hybrid PR37M81 (30.8kg mm-1). We established the values of the nutrient reaction and the fertilizer optimum of hybrids. We discovered a strong relationship between the amount of fertilizer applied and the yield produced (r2= 0.8228–0.9515). The best nutrient response was induced by hybrid PR37N01, while the weakest results were reached by hybrid PR37M81.

Approaches and Schemes for Storing DTDIndependent XML Data in Relational Databases

The volume of XML data exchange is explosively increasing, and the need for efficient mechanisms of XML data management is vital. Many XML storage models have been proposed for storing XML DTD-independent documents in relational database systems. Benchmarking is the best way to highlight pros and cons of different approaches. In this study, we use a common benchmarking scheme, known as XMark to compare the most cited and newly proposed DTD-independent methods in terms of logical reads, physical I/O, CPU time and duration. We show the effect of Label Path, extracting values and storing in another table and type of join needed for each method-s query answering.

Measuring Teachers- Beliefs about Mathematics: A Fuzzy Set Approach

This paper deals with the application of a fuzzy set in measuring teachers- beliefs about mathematics. The vagueness of beliefs was transformed into standard mathematical values using a fuzzy preferences model. The study employed a fuzzy approach questionnaire which consists of six attributes for measuring mathematics teachers- beliefs about mathematics. The fuzzy conjoint analysis approach based on fuzzy set theory was used to analyze the data from twenty three mathematics teachers from four secondary schools in Terengganu, Malaysia. Teachers- beliefs were recorded in form of degrees of similarity and its levels of agreement. The attribute 'Drills and practice is one of the best ways of learning mathematics' scored the highest degree of similarity at 0. 79860 with level of 'strongly agree'. The results showed that the teachers- beliefs about mathematics were varied. This is shown by different levels of agreement and degrees of similarity of the measured attributes.

Chemical Compositions and Physico-Chemical Properties of Malted Sorghum Flour and Characteristics of Gluten Free Bread

This study investigated the effect of germination on chemical compositions, physio-chemical properties of malted (germinated) red sorghum flours and evaluated characteristics of gluten free breads from sorghum flour. Results showed that germinated sorghum flour had higher amylase activity, swelling power and solubility at 95°C, but lower in the peak, break down, final and set back viscosities than ungerminated sample (p≤0.05). Five gluten free breads made from sorghum flour blends, with different ratios of ungerminated and germinated sorghum flour, were compared for the physical properties with those made from wheat flour. Crumb hardness, cohesiveness, gumminess and chewiness of sorghum breads were found significantly higher than those of wheat bread. With increasing of ungerminated flour proportion, the bread hardness increased while the cohesiveness declined. Sorghum breads appeared red to human eyes with a*values of 10.41-15.77.Their crust and crumb colors differed significantly from those of wheat bread.

Durability Study Partially Saturated Fly Ash Blended Cement Concrete

This paper presents the experimental results of the investigation of various properties related to the durability and longterm performance of mortars made of Fly Ash blended cement, FA and Ordinary Portland cement, OPC. The properties that were investigated in an experimental program include; equilibration of specimen in different relative humidity, determination of total porosity, compressive strength, chloride permeability index, and electrical resistivity. Fly Ash blended cement mortar specimens exhibited 10% to 15% lower porosity when measured at equilibrium conditions in different relative humidities as compared to the specimens made of OPC mortar, which resulted in 6% to 8% higher compressive strength of FA blended cement mortar specimens. The effects of ambient relative humidity during sample equilibration on porosity and strength development were also studied. For specimens equilibrated in higher relative humidity conditions, such as 75%, the total porosity of different mortar specimens was between 35% to 50% less than the porosity of samples equilibrated in 12% relative humidity, consequently leading to higher compressive strengths of these specimens.A valid statistical correlation between values of compressive strength, porosity and the degree of saturation was obtained. Measured values of chloride permeability index of fly ash blended cement mortar were obtained as one fourth to one sixth of those measured for OPC mortar specimens, which indicates high resistance against chloride ion penetration in FA blended cement specimens, hence resulting in a highly durable mortar.

Estimating Saturated Hydraulic Conductivity from Soil Physical Properties using Neural Networks Model

Saturated hydraulic conductivity is one of the soil hydraulic properties which is widely used in environmental studies especially subsurface ground water. Since, its direct measurement is time consuming and therefore costly, indirect methods such as pedotransfer functions have been developed based on multiple linear regression equations and neural networks model in order to estimate saturated hydraulic conductivity from readily available soil properties e.g. sand, silt, and clay contents, bulk density, and organic matter. The objective of this study was to develop neural networks (NNs) model to estimate saturated hydraulic conductivity from available parameters such as sand and clay contents, bulk density, van Genuchten retention model parameters (i.e. r θ , α , and n) as well as effective porosity. We used two methods to calculate effective porosity: : (1) eff s FC φ =θ -θ , and (2) inf φ =θ -θ eff s , in which s θ is saturated water content, FC θ is water content retained at -33 kPa matric potential, and inf θ is water content at the inflection point. Total of 311 soil samples from the UNSODA database was divided into three groups as 187 for the training, 62 for the validation (to avoid over training), and 62 for the test of NNs model. A commercial neural network toolbox of MATLAB software with a multi-layer perceptron model and back propagation algorithm were used for the training procedure. The statistical parameters such as correlation coefficient (R2), and mean square error (MSE) were also used to evaluate the developed NNs model. The best number of neurons in the middle layer of NNs model for methods (1) and (2) were calculated 44 and 6, respectively. The R2 and MSE values of the test phase were determined for method (1), 0.94 and 0.0016, and for method (2), 0.98 and 0.00065, respectively, which shows that method (2) estimates saturated hydraulic conductivity better than method (1).

Effects of Mach Number and Angle of Attack on Mass Flow Rates and Entropy Gain in a Supersonic Inlet

A parametric study of a mixed-compression supersonic inlet is performed and reported. The effects of inlet Mach Numbers, varying from 4 to 10, and angle of attack, varying from 0 to 10, are reported for a constant inlet dynamic pressure. The paper looked at the variations of mass flow rates through the inlet, gain in entropy through the inlet, and the angles of the external oblique shocks. The mass flow rates were found to decrease monotonically with Mach numbers and increase with angle of attacks. On the other hand the entropy gain through the inlet increased with increasing Mach number and angle of attack. The variation in static pressure was found to be identical from the inlet throat to the exit for Mach number values higher than 6.

A Study on the Average Information Ratio of Perfect Secret-Sharing Schemes for Access Structures Based On Bipartite Graphs

A perfect secret-sharing scheme is a method to distribute a secret among a set of participants in such a way that only qualified subsets of participants can recover the secret and the joint share of participants in any unqualified subset is statistically independent of the secret. The collection of all qualified subsets is called the access structure of the perfect secret-sharing scheme. In a graph-based access structure, each vertex of a graph G represents a participant and each edge of G represents a minimal qualified subset. The average information ratio of a perfect secret-sharing scheme  realizing the access structure based on G is defined as AR = (Pv2V (G) H(v))/(|V (G)|H(s)), where s is the secret and v is the share of v, both are random variables from  and H is the Shannon entropy. The infimum of the average information ratio of all possible perfect secret-sharing schemes realizing a given access structure is called the optimal average information ratio of that access structure. Most known results about the optimal average information ratio give upper bounds or lower bounds on it. In this present structures based on bipartite graphs and determine the exact values of the optimal average information ratio of some infinite classes of them.

Enhanced GA-Fuzzy OPF under both Normal and Contingent Operation States

The genetic algorithm (GA) based solution techniques are found suitable for optimization because of their ability of simultaneous multidimensional search. Many GA-variants have been tried in the past to solve optimal power flow (OPF), one of the nonlinear problems of electric power system. The issues like convergence speed and accuracy of the optimal solution obtained after number of generations using GA techniques and handling system constraints in OPF are subjects of discussion. The results obtained for GA-Fuzzy OPF on various power systems have shown faster convergence and lesser generation costs as compared to other approaches. This paper presents an enhanced GA-Fuzzy OPF (EGAOPF) using penalty factors to handle line flow constraints and load bus voltage limits for both normal network and contingency case with congestion. In addition to crossover and mutation rate adaptation scheme that adapts crossover and mutation probabilities for each generation based on fitness values of previous generations, a block swap operator is also incorporated in proposed EGA-OPF. The line flow limits and load bus voltage magnitude limits are handled by incorporating line overflow and load voltage penalty factors respectively in each chromosome fitness function. The effects of different penalty factors settings are also analyzed under contingent state.