Study of Barriers to Women's Entrepreneurship Development among Iranian Women (Case Entrepreneur Women)

In this research, effort was made to identify and evaluate barriers to the development of entrepreneurship among Iranian entrepreneur women who were graduated from universities. In this study, perspectives of thirty-seven available entrepreneur women were examined. In order to prepare questionnaires and receive knowledge about barriers among these women, seven cases of entrepreneur women took part in in-depth interviews. Then, to evaluate the importance of barriers, the researchers made a questionnaire with closed questions in which the barriers were classified into the following categories: personal-familial barriers; socio-cultural barriers; economic-financial-commercial barriers; and structural barriers. Entrepreneur women were requested to rate the importance of each item. The results indicated that there were different obstacles among entrepreneur women. The order of the important barriers was as fallow: economic-financial-commercial, structural, socio-cultural, and personal-familial.

Heat and Mass Transfer in a Solar Dryer with Biomass Backup Burner

Majority of pepper farmers in Malaysia are using the open-sun method for drying the pepper berries. This method is time consuming and exposed the berries to rain and contamination. A maintenance-friendly and properly enclosed dryer is therefore desired. A dryer design with a solar collector and a chimney was studied and adapted to suit the needs of small-scale pepper farmers in Malaysia. The dryer will provide an environment with an optimum operating temperature meant for drying pepper berries. The dryer model was evaluated by using commercially available computational fluid dynamic (CFD) software in order to understand the heat and mass transfer inside the dryer. Natural convection was the only mode of heat transportation considered in this study as in accordance to the idea of having a simple and maintenance-friendly design. To accommodate the effect of low buoyancy found in natural convection driers, a biomass burner was integrated into the solar dryer design.

A Model of Market Segmentation for the Customers of Mellat Bank in Iran

If organizations like Mellat Bank want to identify its customer market completely to reach its specified goals, it can segment the market to offer the product package to the right segment. Our objective is to offer a segmentation model for Iran banking market in Mellat bank view. The methodology of this project is combined by “segmentation on the basis of four part-quality variables" and “segmentation on the basis of different in means". Required data are gathered from E-Systems and researcher personal observation. Finally, the research offers the organization that at first step form a four dimensional matrix with 756 segments using four variables named value-based, behavioral, activity style, and activity level, and at the second step calculate the means of profit for every cell of matrix in two distinguished work level (levels α1:normal condition and α2: high pressure condition) and compare the segments by checking two conditions that are 1- homogeneity every segment with its sub segment and 2- heterogeneity with other segments, and so it can do the necessary segmentation process. After all, the last offer (more explained by an operational example and feedback algorithm) is to test and update the model because of dynamic environment, technology, and banking system.

Data Mining Classification Methods Applied in Drug Design

Data mining incorporates a group of statistical methods used to analyze a set of information, or a data set. It operates with models and algorithms, which are powerful tools with the great potential. They can help people to understand the patterns in certain chunk of information so it is obvious that the data mining tools have a wide area of applications. For example in the theoretical chemistry data mining tools can be used to predict moleculeproperties or improve computer-assisted drug design. Classification analysis is one of the major data mining methodologies. The aim of thecontribution is to create a classification model, which would be able to deal with a huge data set with high accuracy. For this purpose logistic regression, Bayesian logistic regression and random forest models were built using R software. TheBayesian logistic regression in Latent GOLD software was created as well. These classification methods belong to supervised learning methods. It was necessary to reduce data matrix dimension before construct models and thus the factor analysis (FA) was used. Those models were applied to predict the biological activity of molecules, potential new drug candidates.

A New Self-Adaptive EP Approach for ANN Weights Training

Evolutionary Programming (EP) represents a methodology of Evolutionary Algorithms (EA) in which mutation is considered as a main reproduction operator. This paper presents a novel EP approach for Artificial Neural Networks (ANN) learning. The proposed strategy consists of two components: the self-adaptive, which contains phenotype information and the dynamic, which is described by genotype. Self-adaptation is achieved by the addition of a value, called the network weight, which depends on a total number of hidden layers and an average number of neurons in hidden layers. The dynamic component changes its value depending on the fitness of a chromosome, exposed to mutation. Thus, the mutation step size is controlled by two components, encapsulated in the algorithm, which adjust it according to the characteristics of a predefined ANN architecture and the fitness of a particular chromosome. The comparative analysis of the proposed approach and the classical EP (Gaussian mutation) showed, that that the significant acceleration of the evolution process is achieved by using both phenotype and genotype information in the mutation strategy.

High Quality Speech Coding using Combined Parametric and Perceptual Modules

A novel approach to speech coding using the hybrid architecture is presented. Advantages of parametric and perceptual coding methods are utilized together in order to create a speech coding algorithm assuring better signal quality than in traditional CELP parametric codec. Two approaches are discussed. One is based on selection of voiced signal components that are encoded using parametric algorithm, unvoiced components that are encoded perceptually and transients that remain unencoded. The second approach uses perceptual encoding of the residual signal in CELP codec. The algorithm applied for precise transient selection is described. Signal quality achieved using the proposed hybrid codec is compared to quality of some standard speech codecs.

Potential of Selected Microbial Strains to Degrade the Gasoil of Hydrocarbon Polluted Soil

Although oil-based drilling fluids are of paramount practical and economical interest, they represent a serious source of pollution, once released into the environment as drill cuttings. The aim of this study is to assess the capability of isolated microorganisms to degrade gasoil fuel. The commonly used physicochemical and biodegradation remediation techniques of petroleum contaminated soil were both investigated. The study revealed that natural biodegradation is favorable. Even though, the presence of heavy metals, the moisture level of (8.55%) and nutrient deficiencies put severe constrains on microorganisms- survival ranges inhibiting the biodegradation process. The selected strains were able to degrade the diesel fuel at significantly high rates (around 98%).

Potential of Exopolysaccharides in Yoghurt Production

Consumer demand for products with low fat or sugar content and low levels of food additives, as well as cost factors, make exopolysaccharides (EPS) a viable alternative. EPS remain an interesting tool to modulate the sensory properties of yoghurt. This study was designed to evaluate EPS production potential of commercial yoghurt starter cultures (Yo-Flex starters: Harmony 1.0, TWIST 1.0 and YF-L902, Chr.Hansen, Denmark) and their influence on an apparent viscosity of yoghurt samples. The production of intracellularly synthesized EPS by different commercial yoghurt starters varies roughly from 144,08 to 440,81 mg/l. Analysing starters’ producing EPS, they showed large variations in concentration and supposedly composition. TWIST 1.0 had produced greater amounts of EPS in MRS medium and in yoghurt samples but there wasn’t determined significant contribution to development of texture as well as an apparent viscosity of the final product. YF-L902 and Harmony 1.0 starters differed considerably in EPS yields, but not in apparent viscosities (p>0.05) of the final yoghurts. Correlation between EPS concentration and viscosity of yoghurt samples was not established in the study.

Orchestra/Percussion Classification Algorithm for United Speech Audio Coding System

Unified Speech Audio Coding (USAC), the latest MPEG standardization for unified speech and audio coding, uses a speech/audio classification algorithm to distinguish speech and audio segments of the input signal. The quality of the recovered audio can be increased by well-designed orchestra/percussion classification and subsequent processing. However, owing to the shortcoming of the system, introducing an orchestra/percussion classification and modifying subsequent processing can enormously increase the quality of the recovered audio. This paper proposes an orchestra/percussion classification algorithm for the USAC system which only extracts 3 scales of Mel-Frequency Cepstral Coefficients (MFCCs) rather than traditional 13 scales of MFCCs and use Iterative Dichotomiser 3 (ID3) Decision Tree rather than other complex learning method, thus the proposed algorithm has lower computing complexity than most existing algorithms. Considering that frequent changing of attributes may lead to quality loss of the recovered audio signal, this paper also design a modified subsequent process to help the whole classification system reach an accurate rate as high as 97% which is comparable to classical 99%.

A Novel Genetic Algorithm Designed for Hardware Implementation

A new genetic algorithm, termed the 'optimum individual monogenetic genetic algorithm' (OIMGA), is presented whose properties have been deliberately designed to be well suited to hardware implementation. Specific design criteria were to ensure fast access to the individuals in the population, to keep the required silicon area for hardware implementation to a minimum and to incorporate flexibility in the structure for the targeting of a range of applications. The first two criteria are met by retaining only the current optimum individual, thereby guaranteeing a small memory requirement that can easily be stored in fast on-chip memory. Also, OIMGA can be easily reconfigured to allow the investigation of problems that normally warrant either large GA populations or individuals many genes in length. Local convergence is achieved in OIMGA by retaining elite individuals, while population diversity is ensured by continually searching for the best individuals in fresh regions of the search space. The results given in this paper demonstrate that both the performance of OIMGA and its convergence time are superior to those of a range of existing hardware GA implementations.

Mathematical Analysis of EEG of Patients with Non-fatal Nonspecific Diffuse Encephalitis

Diffuse viral encephalitis may lack fever and other cardinal signs of infection and hence its distinction from other acute encephalopathic illnesses is challenging. Often, the EEG changes seen routinely are nonspecific and reflect diffuse encephalopathic changes only. The aim of this study was to use nonlinear dynamic mathematical techniques for analyzing the EEG data in order to look for any characteristic diagnostic patterns in diffuse forms of encephalitis.It was diagnosed on clinical, imaging and cerebrospinal fluid criteria in three young male patients. Metabolic and toxic encephalopathies were ruled out through appropriate investigations. Digital EEGs were done on the 3rd to 5th day of onset. The digital EEGs of 5 male and 5 female age and sex matched healthy volunteers served as controls.Two sample t-test indicated that there was no statistically significant difference between the average values in amplitude between the two groups. However, the standard deviation (or variance) of the EEG signals at FP1-F7 and FP2-F8 are significantly higher for the patients than the normal subjects. The regularisation dimension is significantly less for the patients (average between 1.24-1.43) when compared to the normal persons (average between 1.41-1.63) for the EEG signals from all locations except for the Fz-Cz signal. Similarly the wavelet dimension is significantly less (P = 0.05*) for the patients (1.122) when compared to the normal person (1.458). EEGs are subdued in the case of the patients with presence of uniform patterns, manifested in the values of regularisation and wavelet dimensions, when compared to the normal person, indicating a decrease in chaotic nature.

Denoising by Spatial Domain Averaging for Wireless Local Area Network Terminal Localization

Terminal localization for indoor Wireless Local Area Networks (WLANs) is critical for the deployment of location-aware computing inside of buildings. A major challenge is obtaining high localization accuracy in presence of fluctuations of the received signal strength (RSS) measurements caused by multipath fading. This paper focuses on reducing the effect of the distance-varying noise by spatial filtering of the measured RSS. Two different survey point geometries are tested with the noise reduction technique: survey points arranged in sets of clusters and survey points uniformly distributed over the network area. The results show that the location accuracy improves by 16% when the filter is used and by 18% when the filter is applied to a clustered survey set as opposed to a straight-line survey set. The estimated locations are within 2 m of the true location, which indicates that clustering the survey points provides better localization accuracy due to superior noise removal.

Characterisation of Hydrocarbons in Atmospheric Aerosols from Different European Sites

The concentrations of aliphatic and polycyclic aromatic hydrocarbons (PAH) were determined in atmospheric aerosol samples collected at a rural site in Hungary (K-puszta, summer 2008), a boreal forest (Hyytiälä,  April 2007) and a polluted rural area in Italy (San Pietro Capofiume, Po Valley, April 2008). A clear distinction between “clean" and “polluted" periods was observed. Concentrations obtained for Hyytiälä are significantly lower than those for the other two sites. Source reconciliation was performed using diagnostic parameters, such as the carbon preference index and ratios between PAH. The presence of an unresolved complex mixture of hydrocarbons, especially for the Finnish and Italian samples, is indicative of petrogenic inputs. In K-puszta, the aliphatic hydrocarbons are dominated by leaf wax n-alkanes. The long range transport of anthropogenic pollution contributed to the Finnish aerosol. Industrial activities and vehicular emissions represent major sources in San Pietro Capofiume. PAH in K-puszta consist of both pyrogenic and petrogenic compounds.

A Novel FFT-Based Frequency Offset Estimator for OFDM Systems

This paper proposes a novel frequency offset (FO) estimator for orthogonal frequency division multiplexing. Simplicity is most significant feature of this algorithm and can be repeated to achieve acceptable accuracy. Also fractional and integer part of FO is estimated jointly with use of the same algorithm. To do so, instead of using conventional algorithms that usually use correlation function, we use DFT of received signal. Therefore, complexity will be reduced and we can do synchronization procedure by the same hardware that is used to demodulate OFDM symbol. Finally, computer simulation shows that the accuracy of this method is better than other conventional methods.

The Implementation of Spatio-Temporal Graph to Represent Situations in the Virtual World

In this paper, we develop a Spatio-Temporal graph as of a key component of our knowledge representation Scheme. We design an integrated representation Scheme to depict not only present and past but future in parallel with the spaces in an effective and intuitive manner. The resulting multi-dimensional comprehensive knowledge structure accommodates multi-layered virtual world developing in the time to maximize the diversity of situations in the historical context. This knowledge representation Scheme is to be used as the basis for simulation of situations composing the virtual world and for implementation of virtual agents' knowledge used to judge and evaluate the situations in the virtual world. To provide natural contexts for situated learning or simulation games, the virtual stage set by this Spatio-Temporal graph is to be populated by agents and other objects interrelated and changing which are abstracted in the ontology.

Biosensor Measurement of Urea Coonncentration in Human Blood Serum

An application of the highly biosensor based on pH-sensitive field immobilized urease for urea analysis was demo The main analytical characteristics of the bios determined; the conditions of urea measureme blood were optimized. A conceptual possibility biosensor for detection of urea concentratio patients suffering from renal insufficiency was sensitive and selective effect transistor and monstrated in this work. iosensor developed were ment in real samples of ility of application of the tion in blood serum of as shown.

Optimization Approaches for a Complex Dairy Farm Simulation Model

This paper describes the optimization of a complex dairy farm simulation model using two quite different methods of optimization, the Genetic algorithm (GA) and the Lipschitz Branch-and-Bound (LBB) algorithm. These techniques have been used to improve an agricultural system model developed by Dexcel Limited, New Zealand, which describes a detailed representation of pastoral dairying scenarios and contains an 8-dimensional parameter space. The model incorporates the sub-models of pasture growth and animal metabolism, which are themselves complex in many cases. Each evaluation of the objective function, a composite 'Farm Performance Index (FPI)', requires simulation of at least a one-year period of farm operation with a daily time-step, and is therefore computationally expensive. The problem of visualization of the objective function (response surface) in high-dimensional spaces is also considered in the context of the farm optimization problem. Adaptations of the sammon mapping and parallel coordinates visualization are described which help visualize some important properties of the model-s output topography. From this study, it is found that GA requires fewer function evaluations in optimization than the LBB algorithm.

A Temperature-Insensitive Wide-Dynamic Range Positive/Negative Full-Wave Rectifier Based on Operational Trasconductance Amplifier using Commercially Available ICs

This paper presents positive and negative full-wave rectifier. The proposed structure is based on OTA using commercially available ICs (LT1228). The features of the proposed circuit are that: it can rectify and amplify voltage signal with controllable output magnitude via input bias current: the output voltage is free from temperature variation. The circuit description merely consists of 1 single ended and 3 fully differential OTAs. The performance of the proposed circuit are investigated though PSpice. They show that the proposed circuit can function as positive/negative full-wave rectifier, where the voltage input wide-dynamic range from -5V to 5V. Furthermore, the output voltage is slightly dependent on the temperature variations.

Identification of Seat Belt Wearing Compliance Associate Factors in Malaysia: Evidence-based Approach

The aim of the study was to identify seat belt wearing factor among road users in Malaysia. Evidence-based approach through in-depth crash investigation was utilised to determine the intended objectives. The objective was scoped into crashes investigated by Malaysian Institute of Road Safety Research (MIROS) involving passenger vehicles within 2007 and 2010. Crash information of a total of 99 crash cases involving 240 vehicles and 864 occupants were obtained during the study period. Statistical test and logistic regression analysis have been performed. Results of the analysis revealed that gender, seat position and age were associated with seat belt wearing compliance in Malaysia. Males are 97.6% more likely to wear seat belt compared to females (95% CI 1.317 to 2.964). By seat position, the finding indicates that frontal occupants were 82 times more likely to be wearing seat belt (95% CI 30.199 to 225.342) as compared to rear occupants. It is also important to note that the odds of seat belt wearing increased by about 2.64% (95% CI 1.0176 to 1.0353) for every one year increase in age. This study is essential in understanding the Malaysian tendency in belting up while being occupied in a vehicle. The factors highlighted in this study should be emphasized in road safety education in order to increase seat belt wearing rate in this country and ultimately in preventing deaths due to road crashes.