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.

ABURAS Index: A Statistically Developed Index for Dengue-Transmitting Vector Population Prediction

“Dengue" is an African word meaning “bone breaking" because it causes severe joint and muscle pain that feels like bones are breaking. It is an infectious disease mainly transmitted by female mosquito, Aedes aegypti, and causes four serotypes of dengue viruses. In recent years, a dramatic increase in the dengue fever confirmed cases around the equator-s belt has been reported. Several conventional indices have been designed so far to monitor the transmitting vector populations known as House Index (HI), Container Index (CI), Breteau Index (BI). However, none of them describes the adult mosquito population size which is important to direct and guide comprehensive control strategy operations since number of infected people has a direct relationship with the vector density. Therefore, it is crucial to know the population size of the transmitting vector in order to design a suitable and effective control program. In this context, a study is carried out to report a new statistical index, ABURAS Index, using Poisson distribution based on the collection of vector population in Jeddah Governorate, Saudi Arabia.

Effects of Mixed Convection and Double Dispersion on Semi Infinite Vertical Plate in Presence of Radiation

In this paper, the effects of radiation, chemical reaction and double dispersion on mixed convection heat and mass transfer along a semi vertical plate are considered. The plate is embedded in a Newtonian fluid saturated non - Darcy (Forchheimer flow model) porous medium. The Forchheimer extension and first order chemical reaction are considered in the flow equations. The governing sets of partial differential equations are nondimensionalized and reduced to a set of ordinary differential equations which are then solved numerically by Fourth order Runge– Kutta method. Numerical results for the detail of the velocity, temperature, and concentration profiles as well as heat transfer rates (Nusselt number) and mass transfer rates (Sherwood number) against various parameters are presented in graphs. The obtained results are checked against previously published work for special cases of the problem and are found to be in good agreement.

Photodegradation of Phenol Red in the Presence of ZnO Nanoparticles

In our recent study, we have used ZnO nanoparticles assisted with UV light irradiation to investigate the photocatalytic degradation of Phenol Red (PR). The ZnO photocatalyst was characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), specific surface area analysis (BET) and UVvisible spectroscopy. X-ray diffractometry result for the ZnO nanoparticles exhibit normal crystalline phase features. All observed peaks can be indexed to the pure hexagonal wurtzite crystal structures, with the space group of P63mc. There are no other impurities in the diffraction peak. In addition, TEM measurement shows that most of the nanoparticles are rod-like and spherical in shape and fairly monodispersed. A significant degradation of the PR was observed when the catalyst was added into the solution even without the UV light exposure. In addition, the photodegradation increases with the photocatalyst loading. The surface area of the ZnO nanomaterials from the BET measurement was 11.9 m2/g. Besides the photocatalyst loading, the effect of some parameters on the photodegradation efficiency such as initial PR concentration and pH were also studied.

Muscularity and Leg Tissue Composition of Lambs Fed with Hydrolyzed Sugarcane

This study aimed to evaluate the muscularity and tissue composition of 24 legs of Ile de France lambs. They were fed with diets containing “in nature" or hydrolyzed sugarcane with 0.6% of calcium oxide in aerobic and anaerobic environments. Animals entered the trial at 15 and were slaughtered at 32 kg of body weight. The leg tissue composition, as well as muscularity (0.47), muscle:bone (6.66) and muscle:fat (4.25) were not affected (P>0.05) by treatments. The proportions found were: 67.62% for muscle, 17.52% for bone and 10.15% for fat. In relation to lambs fed with “in nature" sugarcane, hydrolyzed sugarcane with calcium oxide in aerobic and anaerobic environments did not affect muscularity and leg tissue composition of lambs.

Boundary Effect on the Onset of Marangoni Convection with Internal Heat Generation

The onset of Marangoni convection in a horizontal fluid layer with internal heat generation overlying a solid layer heated from below is studied. The upper free surface of a fluid is nondeformable and the bottom boundary are rigid and no-slip. The resulting eigenvalue problem is solved exactly. The critical values of the Marangoni numbers for the onset of Marangoni convection are calculated and the latter is found to be critically dependent on the internal heating, depth ratio and conductivity ratio. The effects of the thermal conductivity and the thickness of the solid plate on the onset of convective instability with internal heating are studied in detail.

Word Stemming Algorithms and Retrieval Effectiveness in Malay and Arabic Documents Retrieval Systems

Documents retrieval in Information Retrieval Systems (IRS) is generally about understanding of information in the documents concern. The more the system able to understand the contents of documents the more effective will be the retrieval outcomes. But understanding of the contents is a very complex task. Conventional IRS apply algorithms that can only approximate the meaning of document contents through keywords approach using vector space model. Keywords may be unstemmed or stemmed. When keywords are stemmed and conflated in retrieving process, we are a step forwards in applying semantic technology in IRS. Word stemming is a process in morphological analysis under natural language processing, before syntactic and semantic analysis. We have developed algorithms for Malay and Arabic and incorporated stemming in our experimental systems in order to measure retrieval effectiveness. The results have shown that the retrieval effectiveness has increased when stemming is used in the systems.

Multi-objective Optimization with Fuzzy Based Ranking for TCSC Supplementary Controller to Improve Rotor Angle and Voltage Stability

Many real-world optimization problems involve multiple conflicting objectives and the use of evolutionary algorithms to solve the problems has attracted much attention recently. This paper investigates the application of multi-objective optimization technique for the design of a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the performance of a power system. The design objective is to improve both rotor angle stability and system voltage profile. A Genetic Algorithm (GA) based solution technique is applied to generate a Pareto set of global optimal solutions to the given multi-objective optimisation problem. Further, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set. Simulation results are presented to show the effectiveness and robustness of the proposed approach.

Towards a New Era of Sustainability in the Automotive Industry: Strategic Human Resource Management and Green Technology Innovation

Although automotive industry has brought different beneficiaries to human life, it is being pointed out as one of the major cause of global air pollution which resulted in climate change, smog, green house gases (GHGs), and human diseases by many reasons. Since auto industry is one of the largest consumers of fossil fuels, the realization of green innovations is becoming a crucial choice to meet the challenges towards sustainable development. Recently, many auto manufacturers have embarked on green technology initiatives to gain a competitive advantage in the global market; however, innovative manufacturing systems and technologies can enhance operational performance only if the human resource management is in place to elicit the motivation of the employees and develop their organizational expertise. No organization can perform at peak levels unless each employee is committed to the company goals and works as an effective team member. Strategic human resource practices are the primary means by which firms can shape the skills, attitudes, and behavior of individuals to align with the business strategic objectives. This study investigates on the comprehensive approach of multiple advanced technology innovations and human resource management at Toyota Motor Corporation as the market leader of full hybrid technology in the automotive industry. Then, HRM framework of the company is described and three sets of human resource practices that support the innovation-oriented HR system, presented. Finally, a conceptual framework for innovativeness in green technology in automotive industry by applying a deliberate strategic HR management system and knowledge management with the intervening factors of organizational culture, knowledge application and knowledge sharing is proposed.

Effects of Rarefaction and Compressibility on Fluid Flow at Slip Flow Regime by Direct Simulation of Roughness

A two dimensional numerical simulation has been performed for incompressible and compressible fluid flow through microchannels in slip flow regime. The Navier-Stokes equations have been solved in conjunction with Maxwell slip conditions for modeling flow field associated with slip flow regime. The wall roughness is simulated with triangular microelements distributed on wall surfaces to study the effects of roughness on fluid flow. Various Mach and Knudsen numbers are used to investigate the effects of rarefaction as well as compressibility. It is found that rarefaction has more significant effect on flow field in microchannels with higher relative roughness. It is also found that compressibility has more significant effects on Poiseuille number when relative roughness increases. In addition, similar to incompressible models the increase in average fRe is more significant at low Knudsen number flows but the increase of Poiseuille number duo to relative roughness is sharper for compressible models. The numerical results have also validated with some available theoretical and experimental relations and good agreements have been seen.

Effect of Peak-to-Average Power Ratio Reduction on the Multicarrier Communication System Performance Parameters

Multicarrier transmission system such as Orthogonal Frequency Division Multiplexing (OFDM) is a promising technique for high bit rate transmission in wireless communication system. OFDM is a spectrally efficient modulation technique that can achieve high speed data transmission over multipath fading channels without the need for powerful equalization techniques. However the price paid for this high spectral efficiency and less intensive equalization is low power efficiency. OFDM signals are very sensitive to nonlinear effects due to the high Peak-to-Average Power Ratio (PAPR), which leads to the power inefficiency in the RF section of the transmitter. This paper investigates the effect of PAPR reduction on the performance parameter of multicarrier communication system. Performance parameters considered are power consumption of Power Amplifier (PA) and Digital-to-Analog Converter (DAC), power amplifier efficiency, SNR of DAC and BER performance of the system. From our analysis it is found that irrespective of PAPR reduction technique being employed, the power consumption of PA and DAC reduces and power amplifier efficiency increases due to reduction in PAPR. Moreover, it has been shown that for a given BER performance the requirement of Input-Backoff (IBO) reduces with reduction in PAPR.

Study on the Characteristics of the Measurement System for pH Array Sensors

A measurement system for pH array sensors is introduced to increase accuracy, and decrease non-ideal effects successfully. An array readout circuit reads eight potentiometric signals at the same time, and obtains an average value. The deviation value or the extreme value is counteracted and the output voltage is a relatively stable value. The errors of measuring pH buffer solutions are decreased obviously with this measurement system, and the non-ideal effects, drift and hysteresis, are lowered to 1.638mV/hr and 1.118mV, respectively. The efficiency and stability are better than single sensor. The whole sensing characteristics are improved.

A Sequential Pattern Mining Method Based On Sequential Interestingness

Sequential mining methods efficiently discover all frequent sequential patterns included in sequential data. These methods use the support, which is the previous criterion that satisfies the Apriori property, to evaluate the frequency. However, the discovered patterns do not always correspond to the interests of analysts, because the patterns are common and the analysts cannot get new knowledge from the patterns. The paper proposes a new criterion, namely, the sequential interestingness, to discover sequential patterns that are more attractive for the analysts. The paper shows that the criterion satisfies the Apriori property and how the criterion is related to the support. Also, the paper proposes an efficient sequential mining method based on the proposed criterion. Lastly, the paper shows the effectiveness of the proposed method by applying the method to two kinds of sequential data.

Islamic Corporate Social Responsibility, Corporate Reputation and Performance

This study examines the effect of Islamic Corporate Social Responsibility disclosure and on corporate reputation as well as performance. These relationships are examined based on content analysis of of annual reports of 17 Islamic banks in Malaysia for 2008, 2009 and 2010. Results of this study provide evidence that CSR activities communicated in corporate annual reports are significantly positively related with corporate reputation as well as firm performance. These results indicate that CSR activities and disclosure from Islamic perspectives are equally important business strategies in creating continuous superior performance for organisations. In addition, it also highlights that organisations need to develop a stakeholder orientation particularly in an environment of increasing pressure from jurisdictions dominated by Islamic stakeholders on organisations engaging in Islamic products to increase their social responsibilities from the Islamic perspectives.

Valorization of Lignocellulosic Wastes – Evaluation of Its Toxicity When Used in Adsorption Systems

The agriculture lignocellulosic by-products are receiving increased attention, namely in the search for filter materials that retain contaminants from water. These by-products, specifically almond and hazelnut shells are abundant in Portugal once almond and hazelnuts production is a local important activity. Hazelnut and almond shells have as main constituents lignin, cellulose and hemicelluloses, water soluble extractives and tannins. Along the adsorption of heavy metals from contaminated waters, water soluble compounds can leach from shells and have a negative impact in the environment. Usually, the chemical characterization of treated water by itself may not show environmental impact caused by the discharges when parameters obey to legal quality standards for water. Only biological systems can detect the toxic effects of the water constituents. Therefore, the evaluation of toxicity by biological tests is very important when deciding the suitability for safe water discharge or for irrigation applications. The main purpose of the present work was to assess the potential impacts of waters after been treated for heavy metal removal by hazelnut and almond shells adsorption systems, with short term acute toxicity tests. To conduct the study, water at pH 6 with 25 mg.L-1 of lead, was treated with 10 g of shell per litre of wastewater, for 24 hours. This procedure was followed for each bark. Afterwards the water was collected for toxicological assays; namely bacterial resistance, seed germination, Lemna minor L. test and plant grow. The effect in isolated bacteria strains was determined by disc diffusion method and the germination index of seed was evaluated using lettuce, with temperature and humidity germination control for 7 days. For aquatic higher organism, Lemnas were used with 4 days contact time with shell solutions, in controlled light and temperature. For terrestrial higher plants, biomass production was evaluated after 14 days of tomato germination had occurred in soil, with controlled humidity, light and temperature. Toxicity tests of water treated with shells revealed in some extent effects in the tested organisms, with the test assays showing a close behaviour as the control, leading to the conclusion that its further utilization may not be considered to create a serious risk to the environment.

Generalized Maximal Ratio Combining as a Supra-optimal Receiver Diversity Scheme

Maximal Ratio Combining (MRC) is considered the most complex combining technique as it requires channel coefficients estimation. It results in the lowest bit error rate (BER) compared to all other combining techniques. However the BER starts to deteriorate as errors are introduced in the channel coefficients estimation. A novel combining technique, termed Generalized Maximal Ratio Combining (GMRC) with a polynomial kernel, yields an identical BER as MRC with perfect channel estimation and a lower BER in the presence of channel estimation errors. We show that GMRC outperforms the optimal MRC scheme in general and we hereinafter introduce it to the scientific community as a new “supraoptimal" algorithm. Since diversity combining is especially effective in small femto- and pico-cells, internet-associated wireless peripheral systems are to benefit most from GMRC. As a result, many spinoff applications can be made to IP-based 4th generation networks.

A Proposed Performance Prediction Approach for Manufacturing Processes using ANNs

this paper aims to provide an approach to predict the performance of the product produced after multi-stages of manufacturing processes, as well as the assembly. Such approach aims to control and subsequently identify the relationship between the process inputs and outputs so that a process engineer can more accurately predict how the process output shall perform based on the system inputs. The approach is guided by a six-sigma methodology to obtain improved performance. In this paper a case study of the manufacture of a hermetic reciprocating compressor is presented. The application of artificial neural networks (ANNs) technique is introduced to improve performance prediction within this manufacturing environment. The results demonstrate that the approach predicts accurately and effectively.

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).

Data Mining Applied to the Predictive Model of Triage System in Emergency Department

The Emergency Department of a medical center in Taiwan cooperated to conduct the research. A predictive model of triage system is contracted from the contract procedure, selection of parameters to sample screening. 2,000 pieces of data needed for the patients is chosen randomly by the computer. After three categorizations of data mining (Multi-group Discriminant Analysis, Multinomial Logistic Regression, Back-propagation Neural Networks), it is found that Back-propagation Neural Networks can best distinguish the patients- extent of emergency, and the accuracy rate can reach to as high as 95.1%. The Back-propagation Neural Networks that has the highest accuracy rate is simulated into the triage acuity expert system in this research. Data mining applied to the predictive model of the triage acuity expert system can be updated regularly for both the improvement of the system and for education training, and will not be affected by subjective factors.