164 resultados para Islam.


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Continuous biometric authentication schemes (CBAS) are built around the biometrics supplied by user behavioural characteristics and continuously check the identity of the user throughout the session. The current literature for CBAS primarily focuses on the accuracy of the system in order to reduce false alarms. However, these attempts do not consider various issues that might affect practicality in real world applications and continuous authentication scenarios. One of the main issues is that the presented CBAS are based on several samples of training data either of both intruder and valid users or only the valid users' profile. This means that historical profiles for either the legitimate users or possible attackers should be available or collected before prediction time. However, in some cases it is impractical to gain the biometric data of the user in advance (before detection time). Another issue is the variability of the behaviour of the user between the registered profile obtained during enrollment, and the profile from the testing phase. The aim of this paper is to identify the limitations in current CBAS in order to make them more practical for real world applications. Also, the paper discusses a new application for CBAS not requiring any training data either from intruders or from valid users.

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Advances in data mining have provided techniques for automatically discovering underlying knowledge and extracting useful information from large volumes of data. Data mining offers tools for quick discovery of relationships, patterns and knowledge in large complex databases. Application of data mining to manufacturing is relatively limited mainly because of complexity of manufacturing data. Growing self organizing map (GSOM) algorithm has been proven to be an efficient algorithm to analyze unsupervised DNA data. However, it produced unsatisfactory clustering when used on some large manufacturing data. In this paper a data mining methodology has been proposed using a GSOM tool which was developed using a modified GSOM algorithm. The proposed method is used to generate clusters for good and faulty products from a manufacturing dataset. The clustering quality (CQ) measure proposed in the paper is used to evaluate the performance of the cluster maps. The paper also proposed an automatic identification of variables to find the most probable causative factor(s) that discriminate between good and faulty product by quickly examining the historical manufacturing data. The proposed method offers the manufacturers to smoothen the production flow and improve the quality of the products. Simulation results on small and large manufacturing data show the effectiveness of the proposed method.

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Dr. Isakahn is currently a research associate with the Centre for Dialogue at La Trobe University in Australia. His latest works include several forthcoming books: Democracy in Iraq is a monograph soon to be released; whilst The Edinburgh Companion to the History of Democracy and The Secret History of Democracy, both done in concert with Stephen Stockwell, are edited collections. His most recent articles include “Targeting the Symbolic Dimension of Baathist Iraq,” “Measuring Islam in Australia” and “Manufacturing Consent in Iraq.” For further information regarding Dr. Isakhan and his works, please visit his website, www.benjaminisakhan.com.

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In today's technological age, fraud has become more complicated, and increasingly more difficult to detect, especially when it is collusive in nature. Different fraud surveys showed that the median loss from collusive fraud is much greater than fraud perpetrated by a single person. Despite its prevalence and potentially devastating effects, collusion is commonly overlooked as an organizational risk. Internal auditors often fail to proactively consider collusion in their fraud assessment and detection efforts. In this paper, we consider fraud scenarios with collusion. We present six potentially collusive fraudulent behaviors and show their detection process in an ERP system. We have enhanced our fraud detection framework to utilize aggregation of different sources of logs in order to detect communication and have further enhanced it to render it system-agnostic thus achieving portability and making it generally applicable to all ERP systems.

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The objective was to understand the influence of the surface roughness of lactose carriers on the adhesion and dispersion of salmeterol xinafoate (SX) from interactive mixtures. The surface roughness of lactose carriers was determined by confocal microscopy. Particle images and adhesion forces between SX and lactose particles were determined by Atomic Force Microscopy. The dispersion of SX (2.5%) from interactive mixtures with lactose was determined using a twin-stage impinger (TSI) with a Rotahaler® at an airflow rate of 60L/min. SX was analysed using a validated HPLC assay. The RMS Rq of lactose carriers ranged from 0.93-2.84μm, the Fine Particle Fraction (FPF) of SX ranged between 4 and 24 percent and average adhesion force between a SX and lactose particles ranged between 49 and 134 nN. No direct correlation was observed between the RMS Rq of lactose carriers and either the FPF of SX for the interactive mixtures or the adhesion force of a SX on the lactose particles; however, the presence of fine lactose associated with the carrier surface increased the FPF of SX. Dispersion through direct SX detachment from the carrier surface was not consistent with the poor correlations described and was more likely to occur through complex particulate interactions involving fine lactose.

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Dry powder inhaler (DPI) formulations is one of the most useful aerosol preparations in which drugs may be formulated as carrier-based interactive mixtures with micronised drug particles (<5 μm) adhered onto the surface of large inert carriers (lactose powders). The addition of magnesium stearate (MgSt) (1-3), was found to increase dispersion of various drugs from DPI formulations. Recently, some active compounds coated with 5% (wt/wt) MgSt using the mechanofusion method showed significant improvements in aerosolization behavior due to the reduction in intrinsic cohesion force (4). Application of MgSt in powder formulations is not new; however, no studies demonstrated the minimum threshold level for this excipient in efficient aerosolization of drug powders from the interactive mixtures. Therefore, this study investigated the role of MgSt concentration on the efficient dispersion of salbutamol sulphate (SS) from DPI formulations.

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Magneto-rheological (MR) fluid damper is a semi-active control device that has recently received more attention by the vibration control community. But inherent nonlinear hysteresis character of magneto-rheological fluid dampers is one of the challenging aspects for utilizing this device to achieve high system performance. So the development of accurate model is necessary to take the advantage their unique characteristics. Research by others [3] has shown that a system of nonlinear differential equations can successfully be used to describe the hysteresis behavior of the MR damper. The focus of this paper is to develop an alternative method for modeling a damper in the form of centre average fuzzy interference system, where back propagation learning rules are used to adjust the weight of network. The inputs for the model are used from the experimental data. The resulting fuzzy interference system is satisfactorily represents the behavior of the MR fluid damper with reduced computational requirements. Use of the neuro-fuzzy model increases the feasibility of real time simulation.

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The purpose of this study is to identify the most common manufacturing practices adopted by the Malaysian manufacturers, company performance factors and relationship between practices and performances. To fulfil the study objectives, 400 manufacturers were surveyed by a standard 400 questionnaire. Three research methodologies such as descriptive analysis, ANOVA and regression analysis have been employed in this study. The analysis revealed that Malaysian manufacturers focus on optimizing three critical performance factors: product development, less customer return rate and on time delivery (OTD). The most important competitive factor was found to be company reputation and design and manufacturing capacity is the least important factor. The findings also proved that manufacturing practices significantly influence company performances

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Presently, the manufacturing sector faces unprecedented levels of competition in both the domestic and international markets. This competition is mainly as a result of rapidly expanding international trade, gradual removal of protection, substantial reforms in labour markets and industrial relations, rapid technological changes and discerning customers. Intense global competition requires manufacturers to deliver products with higher quality in a shorter time. Simultaneously, owing to new technological innovations, the complexity of the products is increasing. In Australia, the impact of this intense competition and structural changes appear to be having negative effects on the manufacturing sector. This paper discusses the quality and reliability (Q & R) practices and associated drawbacks of Australian manufacturers and presents the findings of an investigation of the challenges Australian manufacturers are currently facing. The results reported in the paper are based on the data collected from a survey using the standard questionnaire. The study was driven by a conceptual model, which relates advanced quality practices to manufacturing performance and manufacturing difficulties.Evidence indicates that Q & R is the main competitive factor for Australian manufacturers. Design capability and on time delivery (OTD) came second. Results show that Australian manufacturers in general are facing some manufacturing difficulties. The relationship between advanced quality practices and company performance and manufacturing difficulties are explored. It is found that the companies who have more emphasis on advanced quality practices have fewer problems in manufacturing practices. Moreover, companies who have actively implemented the advanced quality practices have managed to improve the quality of the product continuously. The results validate the proposed hypothesis and lend credence to current thinking that improvement in Q & R is a vital tool for competitive advantage.

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A magneto-rheological (MR) fluid damper is a semi-active control device that has recently begun to receive more attention in the vibration control community. However, the inherent nonlinear nature of the MR fluid damper makes it challenging to use this device to achieve high damping control system performance. Therefore the development of an accurate modeling method for a MR fluid damper is necessary to take advantage of its unique characteristics. Our goal was to develop an alternative method for modeling a MR fluid damper by using a self tuning fuzzy (STF) method based on neural technique. The behavior of the researched damper is directly estimated through a fuzzy mapping system. In order to improve the accuracy of the STF model, a back propagation and a gradient descent method are used to train online the fuzzy parameters to minimize the model error function. A series of simulations had been done to validate the effectiveness of the suggested modeling method when compared with the data measured from experiments on a test rig with a researched MR fluid damper. Finally, modeling results show that the proposed STF interference system trained online by using neural technique could describe well the behavior of the MR fluid damper without need of calculation time for generating the model parameters.

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This study reports the factors controlling aerosolization of salbutamol sulfate (SS) from mixtures with polycaprolactone (PCL) microspheres fabricated using an emulsion technique with polyvinyl alcohol (PVA) as stabilizer. The fine particle fraction (FPF) of SS from PCL measured by a twin-stage impinger was unexpectedly found to be zero, although scanning electron microscopy showed that the drug coated the entire microsphere. Precoating the microspheres with magnesium stearate (MgSt) excipient solutions (1%–2%) significantly increased (p < 0.05, n = 5) the FPF of SS (11.4%–15.4%), whereas precoating with leucine had a similar effect (FPF = 11.3 ± 1.1%), but was independent of the solution concentration. The force of adhesion (by atomic force microscopy) between the PCL microspheres and SS was reduced from 301.4 ± 21.7 nN to 110.9 ± 30.5 nN and 121.8 ± 24.6 nN, (p < 0.05, n = 5) for 1% and 2% MgSt solutions, respectively, and to 148.1 ± 21.0 nN when coated with leucine. The presence of PVA on the PCL microspheres (detected by X-ray photoelectron spectroscopy) affected the detachment of SS due to strong adhesion between the two, presumably due to capillary forces acting between them. Precoating the microspheres with excipients increased the FPF significantly by reducing the drug–carrier adhesion. © 2011 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 101:733–745, 2012

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Reflecting on the legal consequences of globalisation in the 21st century, Twining predicted that societies in the West would have to 'wrestle with the extent to which the state should recognise, make concessions to, or even enforce norms and values embedded in different religions, cultures or traditions'. This is borne out as the direction across the common law world moves towards entrenching legal pluralism. The concessions each nation has made to minorities with different religions, cultures and traditions have varied. The special character of Islam, as a comprehensive blueprint for life in which law and religion unite, has meant that the negotiations for a special place for Muslims within each common law jurisdiction has been at the forefront of new legal ordering possibilities. This is the crux of the pluralism debate. Cautiously, Australians have watched the, at times histrionic, discourse in Canada and Great Britain on official recognition for Islamic law.