Discrimination of Seismic Signals Using Artificial Neural Networks

The automatic discrimination of seismic signals is an important practical goal for earth-science observatories due to the large amount of information that they receive continuously. An essential discrimination task is to allocate the incoming signal to a group associated with the kind of physical phenomena producing it. In this paper, two classes of seismic signals recorded routinely in geophysical laboratory of the National Center for Scientific and Technical Research in Morocco are considered. They correspond to signals associated to local earthquakes and chemical explosions. The approach adopted for the development of an automatic discrimination system is a modular system composed by three blocs: 1) Representation, 2) Dimensionality reduction and 3) Classification. The originality of our work consists in the use of a new wavelet called "modified Mexican hat wavelet" in the representation stage. For the dimensionality reduction, we propose a new algorithm based on the random projection and the principal component analysis.

Extent of Highway Capacity Loss Due to Rainfall

Traffic flow in adverse weather conditions have been investigated in this study for general traffic, week day and week end traffic. The empirical evidence is strong in support of the view that rainfall affects macroscopic traffic flow parameters. Data generated from a basic highway section along J5 in Johor Bahru, Malaysia was synchronized with 161 rain events over a period of three months. This revealed a 4.90%, 6.60% and 11.32% reduction in speed for light rain, moderate rain and heavy rain conditions respectively. The corresponding capacity reductions in the three rainfall regimes are 1.08% for light rain, 6.27% for moderate rain and 29.25% for heavy rain. In the week day traffic, speed drops of 8.1% and 16.05% were observed for light and heavy conditions. The moderate rain condition speed increased by 12.6%. The capacity drops for week day traffic are 4.40% for light rain, 9.77% for moderate rain and 45.90% for heavy rain. The weekend traffic indicated speed difference between the dry condition and the three rainy conditions as 6.70% for light rain, 8.90% for moderate rain and 13.10% for heavy rain. The capacity changes computed for the weekend traffic were 0.20% in light rain, 13.90% in moderate rain and 16.70% in heavy rain. No traffic instabilities were observed throughout the observation period and the capacities reported for each rain condition were below the norain condition capacity. Rainfall has tremendous impact on traffic flow and this may have implications for shock wave propagation.

Whole Body CT for a Patient with Sepsis

This study retrospectively investigated the significance of whole body CT (WCT) for patients with sepsis. A medical chart review was retrospectively performed for all patients with systemic inflammatory response syndrome that were treated initially between April 2011 and March 2012. The subjects were divided into a WCT group that underwent WCT on arrival and a control group. Results of this study suggested that WCT for sepsis was useful for elderly patients whose chief complaint or physiological findings could not suggest the anatomical site of infection, to determine the infectious focus and indications/method for surgery, to diagnose the basic diseases associated with opportunistic infections and to evaluate complicated diseases

Customer Segmentation in Foreign Trade based on Clustering Algorithms Case Study: Trade Promotion Organization of Iran

The goal of this paper is to segment the countries based on the value of export from Iran during 14 years ending at 2005. To measure the dissimilarity among export baskets of different countries, we define Dissimilarity Export Basket (DEB) function and use this distance function in K-means algorithm. The DEB function is defined based on the concepts of the association rules and the value of export group-commodities. In this paper, clustering quality function and clusters intraclass inertia are defined to, respectively, calculate the optimum number of clusters and to compare the functionality of DEB versus Euclidean distance. We have also study the effects of importance weight in DEB function to improve clustering quality. Lastly when segmentation is completed, a designated RFM model is used to analyze the relative profitability of each cluster.

Cereals' Products with Red Grape and Walnut Extracts as Functional Foods for Prevention of Kidney Dysfunction

In the present research, two nutraceuticals made from red grape and walnut that showed previously to improve kidney dysfunction were incorporated separately into functional foods' bread made from barley and rice bran. The functional foods were evaluated in rats in which chronic renal failure was induced through feeding diet rich in adenine and phosphate (APD). The evaluation based on assessing kidney function, oxidative stress, inflammatory biomarkers and body weight gain. Results showed induction of chronic kidney failure reflected in significant increase in plasma urea, creatinine, malondialdehyde, tumor necrosis factor- α and low density lipoprotein cholesterol along with significant reduction of plasma albumin, and total antioxidant and creatinine clearance and body weight gain on feeding APD compared to control healthy group. Feeding the functional foods produced amelioration in the different biochemical parameters and body weight gain indicating improvement in kidney function.

Solution of Fuzzy Differential Equation under Generalized Differentiability by Genetic Programming

In this paper, solution of fuzzy differential equation under general differentiability is obtained by genetic programming (GP). The obtained solution in this method is equivalent or very close to the exact solution of the problem. Accuracy of the solution to this problem is qualitatively better. An illustrative numerical example is presented for the proposed method.

Input Textural Feature Selection By Mutual Information For Multispectral Image Classification

Texture information plays increasingly an important role in remotely sensed imagery classification and many pattern recognition applications. However, the selection of relevant textural features to improve this classification accuracy is not a straightforward task. This work investigates the effectiveness of two Mutual Information Feature Selector (MIFS) algorithms to select salient textural features that contain highly discriminatory information for multispectral imagery classification. The input candidate features are extracted from a SPOT High Resolution Visible(HRV) image using Wavelet Transform (WT) at levels (l = 1,2). The experimental results show that the selected textural features according to MIFS algorithms make the largest contribution to improve the classification accuracy than classical approaches such as Principal Components Analysis (PCA) and Linear Discriminant Analysis (LDA).

A Graphical Environment for Petri Nets INA Tool Based on Meta-Modelling and Graph Grammars

The Petri net tool INA is a well known tool by the Petri net community. However, it lacks a graphical environment to cerate and analyse INA models. Building a modelling tool for the design and analysis from scratch (for INA tool for example) is generally a prohibitive task. Meta-Modelling approach is useful to deal with such problems since it allows the modelling of the formalisms themselves. In this paper, we propose an approach based on the combined use of Meta-modelling and Graph Grammars to automatically generate a visual modelling tool for INA for analysis purposes. In our approach, the UML Class diagram formalism is used to define a meta-model of INA models. The meta-modelling tool ATOM3 is used to generate a visual modelling tool according to the proposed INA meta-model. We have also proposed a graph grammar to automatically generate INA description of the graphically specified Petri net models. This allows the user to avoid the errors when this description is done manually. Then the INA tool is used to perform the simulation and the analysis of the resulted INA description. Our environment is illustrated through an example.

Computer Aided Detection on Mammography

A typical definition of the Computer Aided Diagnosis (CAD), found in literature, can be: A diagnosis made by a radiologist using the output of a computerized scheme for automated image analysis as a diagnostic aid. Often it is possible to find the expression Computer Aided Detection (CAD or CADe): this definition emphasizes the intent of CAD to support rather than substitute the human observer in the analysis of radiographic images. In this article we will illustrate the application of CAD systems and the aim of these definitions. Commercially available CAD systems use computerized algorithms for identifying suspicious regions of interest. In this paper are described the general CAD systems as an expert system constituted of the following components: segmentation / detection, feature extraction, and classification / decision making. As example, in this work is shown the realization of a Computer- Aided Detection system that is able to assist the radiologist in identifying types of mammary tumor lesions. Furthermore this prototype of station uses a GRID configuration to work on a large distributed database of digitized mammographic images.

Swelling Behavior and Cytotoxicity of Maleic Acid Grafted Chitosan

Chitosan is an attractive polysaccharide obtained by deacetylation of an abundant natural biopolymer called chitin. Chitin and chitosan are excellent materials. To improve the potential of chitin and chitosan modification is needed. In the present study, grafting of maleic acid on to chitosan by cerium ammonium nitrate in acetic acid solution was investigated with use of a microwave and reflux system. The grafted chitosan was characterized by using a Fourier-transform infrared spectrometry. The solubility and swelling behavior of grafted chitosans were determined in acetate buffer (pH 3.6), citrophosphate buffer (pH 5.6 and pH 7.0), and boric buffer (pH 9.2) solutions. The sample obtained by microwave system with use of a chitosan/maleic anhydride/ceric ammonium nitrate 0.2/3.922/0.99 gram of raw material within 30 minute showed the maximum swelling ratio (13.6) in boric buffer solution.

Target Detection using Adaptive Progressive Thresholding Based Shifted Phase-Encoded Fringe-Adjusted Joint Transform Correlator

A new target detection technique is presented in this paper for the identification of small boats in coastal surveillance. The proposed technique employs an adaptive progressive thresholding (APT) scheme to first process the given input scene to separate any objects present in the scene from the background. The preprocessing step results in an image having only the foreground objects, such as boats, trees and other cluttered regions, and hence reduces the search region for the correlation step significantly. The processed image is then fed to the shifted phase-encoded fringe-adjusted joint transform correlator (SPFJTC) technique which produces single and delta-like correlation peak for a potential target present in the input scene. A post-processing step involves using a peak-to-clutter ratio (PCR) to determine whether the boat in the input scene is authorized or unauthorized. Simulation results are presented to show that the proposed technique can successfully determine the presence of an authorized boat and identify any intruding boat present in the given input scene.

Pro-inflammatory Phenotype of COPD Fibroblasts not Compatible with Repair in COPD Lung

COPD is characterized by loss of elastic fibers from small airways and alveolar walls, with the decrease in elastin increasing with disease severity. It is unclear why there is a lack of repair of elastic fibers. We have examined fibroblasts cultured from lung tissue from normal and COPD subjects to determine if the secretory profile explains lack of tissue repair. In this study, fibroblasts were cultured from lung parenchyma of bronchial carcinoma patients with varying degrees of COPD; controls (non-COPD, n=5), mild COPD (GOLD 1, n=5) and moderate-severe COPD (GOLD 2-3, n=12). Measurements were made of proliferation, senescence-associated beta-galactosidase-1, mRNA expression of IL-6, IL-8, MMP-1, tropoelastin and versican, and protein levels for IL-6, IL-8, PGE2, tropoelastin, insoluble elastin, and versican. It was found that GOLD 2-3 fibroblasts proliferated more slowly (p

On the Symbol Based Decision Feedback Equalizer

Decision Feedback equalizers (DFEs) usually outperform linear equalizers for channels with intersymbol interference. However, the DFE performance is highly dependent on the availability of reliable past decisions. Hence, in coded systems, where reliable decisions are only available after decoding the full block, the performance of the DFE will be affected. A symbol based DFE is a DFE that only uses the decision after the block is decoded. In this paper we derive the optimal settings of both the feedforward and feedback taps of the symbol based equalizer. We present a novel symbol based DFE filterbank, and derive its taps optimal settings. We also show that it outperforms the classic DFE in terms of complexity and/or performance.

Pervasiveness of Aflatoxin in Peanuts Growing in the Area of Pothohar, Pakistan

Mycotoxin (aflatoxins) contamination of peanuts is a great concern for human health. A total of 72 samples of unripe, roasted, and salty peanuts were collected randomly from Pothohar plateau of Pakistan for the assessment of aflatoxin. Samples were dried, ground and extracted by acetonitrile (84%). The filtered extracts were cleaned up by MycoSep-226 and analyzed by high performance liquid chromatography with flourescence detector. Quantification limit of Aflatoxin was 1 μg/kg and 70% Recovery was observed in spiked samples in the range 1–10 μg/kg. The screening of mycotoxins indicated that aflatoxins were present in most of the samples being detected in 82%, in concentrations from 14.25 μg/kg to 98.80 μg/kg. Optimal conditions for mycotoxin production and fungal growth are frequently found in the crop fields as well as in store houses. Human exposure of such toxin can be controlled by pointed out such awareness and implemented the regulations.

Soil-Vegetation Relationships in Arid Rangelands (Case Study: Nodushan Rangelands of Yazd, Iran)

The objective of this research was to identify the vegetation-soil relationships in Nodushan arid rangelands of Yazd. 5 sites were selected for measuring the cover of plant species and soil attributes. Soil samples were taken in 0-10 and 10-80 cm layers. The species studied were Salsola tomentosa, Salsola arbuscula, Peganum harmala, Zygophylum eurypterum and Eurotia ceratoides. Canonical correspondence analysis (CCA) was used to analyze the data. Based on the CCA results, 74.9 % of vegetation-soil variation was explained by axis 1-3. Axis 1, 2 and 3 accounted for 27.2%, 24.9 % and 22.8% of variance respectively. Correlation between axis 1, 2, 3 and speciesedaphic variables were 0.995, 0.989, 0.981 respectively. Soil texture, lime, salinity and organic matter significantly influenced the distribution of these plant species. Determination of soil-vegetation relationships will be useful for managing and improving rangelands in arid and semi arid environments.

New Exact Solutions for the (3+1)-Dimensional Breaking Soliton Equation

In this work, we obtain some analytic solutions for the (3+1)-dimensional breaking soliton after obtaining its Hirota-s bilinear form. Our calculations show that, three-wave method is very easy and straightforward to solve nonlinear partial differential equations.

Breast Skin-Line Estimation and Breast Segmentation in Mammograms using Fast-Marching Method

Breast skin-line estimation and breast segmentation is an important pre-process in mammogram image processing and computer-aided diagnosis of breast cancer. Limiting the area to be processed into a specific target region in an image would increase the accuracy and efficiency of processing algorithms. In this paper we are presenting a new algorithm for estimating skin-line and breast segmentation using fast marching algorithm. Fast marching is a partial-differential equation based numerical technique to track evolution of interfaces. We have introduced some modifications to the traditional fast marching method, specifically to improve the accuracy of skin-line estimation and breast tissue segmentation. Proposed modifications ensure that the evolving front stops near the desired boundary. We have evaluated the performance of the algorithm by using 100 mammogram images taken from mini-MIAS database. The results obtained from the experimental evaluation indicate that this algorithm explains 98.6% of the ground truth breast region and accuracy of the segmentation is 99.1%. Also this algorithm is capable of partially-extracting nipple when it is available in the profile.

Relational Impact of Job Stress on Gender Based Managerial Effectiveness in Ghanaian Organizations

This study explored the relationship between occupational stress and the perceived effectiveness of men and women managers in Ghanaian organizations. The exploration is underlined by attempt to understand the degree to which male and female managers in Ghanaian organizations experience occupational stress at the workplace. The purpose is to examine the sources and extents of occupational stress experienced by male and female managers in Ghana. Data was collected using questionnaires and analyzed using both descriptive statistics and correlation analysis. The results showed that female managers in Ghana are more likely to report of more stress experiences in the workplace than their male counterparts. The female managers are more likely to perceive role conflict and alienation as job stressors while the male managers perceived blocked career as a major source of workplace stress. It is concluded that despite the female managers experiencing enormous level of occupational stress, there was no significant differences between their managerial effectiveness and that of the male.

Branding Urban Spaces as an Approach for City Branding -Case study: Cairo City, Egypt

With the beginning of the new century, man still faces many challenges in how to form and develop his urban environment. To meet these challenges, many cities have tried to develop its visual image. This is by transforming their urban environment into a branded visual image; this is at the level of squares, the main roads, the borders, and the landmarks. In this realm, the paper aims at activating the role of branded urban spaces as an approach for the development of visual image of cities, especially in Egypt. It concludes the need to recognize the importance of developing the visual image in Egypt, through directing the urban planners to the important role of such spaces in achieving sustainability.

Anti-Synchronization of two Different Chaotic Systems via Active Control

This paper presents anti-synchronization of chaos between two different chaotic systems using active control method. The proposed technique is applied to achieve chaos antisynchronization for the Lü and Rössler dynamical systems. Numerical simulations are implemented to verify the results.