Characterization of an Acetobacter Strain Isolated from Iranian Peach that Tolerates High Temperatures and Ethanol Concentrations

Vinegar is a precious food additive and complement as well as effective preservative against food spoilage. Recently traditional vinegar production has been improved using various natural substrates and fruits such as grape, palm, cherry, coconut, date, sugarcane, rice and balsam. These neoclassical fermentations resulted in several vinegar types with different tastes, fragrances and nutritional values because of applying various acetic acid bacteria as starters. Acetic acid bacteria include genera Acetobacter, Gluconacetobacter and Gluconobacter according to latest edition of Bergy-s Manual of Systematic Bacteriology that classifies genera on the basis of their 16s RNA differences. Acetobacter spp as the main vinegar starters belong to family Acetobacteraceae that are gram negative obligate aerobes, chemoorganotrophic bacilli that are oxidase negative and oxidize ethanol to acetic acid. In this research we isolated and identified a native Acetobacter strain with high acetic acid productivity and tolerance against high ethanol concentrations from Iranian peach as a summer delicious fruit that is very susceptible to food spoilage and decay. We used selective and specific laboratorial culture media such as Standard GYC, Frateur and Carr medium. Also we used a new industrial culture medium and a miniature fermentor with a new aeration system innovated by Pars Yeema Biotechnologists Co., Isfahan Science and Technology Town (ISTT), Isfahan, Iran. The isolated strain was successfully cultivated in modified Carr media with 2.5% and 5% ethanol simultaneously in high temperatures, 34 - 40º C after 96 hours of incubation period. We showed that the increase of ethanol concentration resulted in rising of strain sensitivity to high temperature. In conclusion we isolated and characterized a new Acetobacter strain from Iranian peach that could be considered as a potential strain for production of a new vinegar type, peach vinegar, with a delicious taste and advantageous nutritional value in food biotechnology and industrial microbiology.

Assessing Stakeholders’ Interests in Postal Security

The events of October 2010, where terrorists managed to get explosive devices onboard of three passenger aircrafts and two air freighters, demonstrated weaknesses of the international air cargo and airmail security. Ever since, postal security has gained interest among policymakers and authorities. This study augments the limited body of academic literature on the topic bydemarcating areas of postal security, identifying relevant stakeholders in each area, and investigating why these stakeholders engage in postal security. Research is based on a case study on Swiss Post’s mail service.

Dynamic Economic Dispatch Constrained by Wind Power Weibull Distribution: A Here-and-Now Strategy

In this paper, a Dynamic Economic Dispatch (DED) model is developed for the system consisting of both thermal generators and wind turbines. The inclusion of a significant amount of wind energy into power systems has resulted in additional constraints on DED to accommodate the intermittent nature of the output. The probability of stochastic wind power based on the Weibull probability density function is included in the model as a constraint; A Here-and-Now Approach. The Environmental Protection Agency-s hourly emission target, which gives the maximum emission during the day, is used as a constraint to reduce the atmospheric pollution. A 69-bus test system with non-smooth cost function is used to illustrate the effectiveness of the proposed model compared with static economic dispatch model with including the wind power.

Technological Deep Assessment of Automotive Parts Manufacturers Case of Iranian Manufacturers

In order to develop any strategy, it is essential to first identify opportunities, threats, weak and strong points. Assessment of technology level provides the possibility of concentrating on weak and strong points. The results of technology assessment have a direct effect on decision making process in the field of technology transfer or expansion of internal research capabilities so it has a critical role in technology management. This paper presents a conceptual model to analyze the technology capability of a company as a whole and in four main aspects of technology. This model was tested on 10 automotive parts manufacturers in IRAN. Using this model, capability level of manufacturers was investigated in four fields of managing aspects, hard aspects, human aspects, and information and knowledge aspects. Results show that these firms concentrate on hard aspect of technology while others aspects are poor and need to be supported more. So this industry should develop other aspects of technology as well as hard aspect to have effective and efficient use of its technology. These paper findings are useful for the technology planning and management in automotive part manufactures in IRAN and other Industries which are technology followers and transport their needed technologies.

Multiuser Detection in CDMA Fast Fading Multipath Channel using Heuristic Genetic Algorithms

In this paper, a simple heuristic genetic algorithm is used for Multistage Multiuser detection in fast fading environments. Multipath channels, multiple access interference (MAI) and near far effect cause the performance of the conventional detector to degrade. Heuristic Genetic algorithms, a rapidly growing area of artificial intelligence, uses evolutionary programming for initial search, which not only helps to converge the solution towards near optimal performance efficiently but also at a very low complexity as compared with optimal detector. This holds true for Additive White Gaussian Noise (AWGN) and multipath fading channels. Experimental results are presented to show the superior performance of the proposed techque over the existing methods.

Performance Analysis of Routing Protocol for WSN Using Data Centric Approach

Sensor Network are emerging as a new tool for important application in diverse fields like military surveillance, habitat monitoring, weather, home electrical appliances and others. Technically, sensor network nodes are limited in respect to energy supply, computational capacity and communication bandwidth. In order to prolong the lifetime of the sensor nodes, designing efficient routing protocol is very critical. In this paper, we illustrate the existing routing protocol for wireless sensor network using data centric approach and present performance analysis of these protocols. The paper focuses in the performance analysis of specific protocol namely Directed Diffusion and SPIN. This analysis reveals that the energy usage is important features which need to be taken into consideration while designing routing protocol for wireless sensor network.

WiPoD Wireless Positioning System based on 802.11 WLAN Infrastructure

This paper describes WiPoD (Wireless Position Detector) which is a pure software based location determination and tracking (positioning) system. It uses empirical signal strength measurements from different wireless access points for mobile user positioning. It is designed to determine the location of users having 802.11 enabled mobile devices in an 802.11 WLAN infrastructure and track them in real time. WiPoD is the first main module in our LBS (Location Based Services) framework. We tested K-Nearest Neighbor and Triangulation algorithms to estimate the position of a mobile user. We also give the analysis results of these algorithms for real time operations. In this paper, we propose a supportable, i.e. understandable, maintainable, scalable and portable wireless positioning system architecture for an LBS framework. The WiPoD software has a multithreaded structure and was designed and implemented with paying attention to supportability features and real-time constraints and using object oriented design principles. We also describe the real-time software design issues of a wireless positioning system which will be part of an LBS framework.

Illumination Invariant Face Recognition using Supervised and Unsupervised Learning Algorithms

In this paper, a comparative study of application of supervised and unsupervised learning algorithms on illumination invariant face recognition has been carried out. The supervised learning has been carried out with the help of using a bi-layered artificial neural network having one input, two hidden and one output layer. The gradient descent with momentum and adaptive learning rate back propagation learning algorithm has been used to implement the supervised learning in a way that both the inputs and corresponding outputs are provided at the time of training the network, thus here is an inherent clustering and optimized learning of weights which provide us with efficient results.. The unsupervised learning has been implemented with the help of a modified Counterpropagation network. The Counterpropagation network involves the process of clustering followed by application of Outstar rule to obtain the recognized face. The face recognition system has been developed for recognizing faces which have varying illumination intensities, where the database images vary in lighting with respect to angle of illumination with horizontal and vertical planes. The supervised and unsupervised learning algorithms have been implemented and have been tested exhaustively, with and without application of histogram equalization to get efficient results.

Real Time Approach for Data Placement in Wireless Sensor Networks

The issue of real-time and reliable report delivery is extremely important for taking effective decision in a real world mission critical Wireless Sensor Network (WSN) based application. The sensor data behaves differently in many ways from the data in traditional databases. WSNs need a mechanism to register, process queries, and disseminate data. In this paper we propose an architectural framework for data placement and management. We propose a reliable and real time approach for data placement and achieving data integrity using self organized sensor clusters. Instead of storing information in individual cluster heads as suggested in some protocols, in our architecture we suggest storing of information of all clusters within a cell in the corresponding base station. For data dissemination and action in the wireless sensor network we propose to use Action and Relay Stations (ARS). To reduce average energy dissipation of sensor nodes, the data is sent to the nearest ARS rather than base station. We have designed our architecture in such a way so as to achieve greater energy savings, enhanced availability and reliability.

Effect of Cyclotron Resonance Frequencies in Particles Due to AC and DC Electromagnetic Fields

A fundamental model consisting of charged particles moving in free space exposed to alternating and direct current (ACDC) electromagnetic fields is analyzed. Effects of charged particles initial position and initial velocity to cyclotron resonance frequency are observed. Strong effects are observed revealing that effects of electric and magnetic fields on a charged particle in free space varies with the initial conditions. This indicates the frequency where maximum displacement occur can be changed. At this frequency the amplitude of oscillation of the particle displacement becomes unbounded.

Mechanical Behaviour and Electrical Conductivity of Oxygen Separation Membrane under Uniaxial Compressive Loading

The mechanical deformation and the electrical conductivity of lanthanum strontium cobalt ferrite oxide under uniaxial compression were investigated at various temperatures up to 1073 K. The material reveals a rather complex mechanical behaviour related to its ferroelasticity and completely different stress-strain curves are obtained during the 1st and 2nd loading cycles. A distinctive ferroelastic creep was observed at 293 K whilst typical ferroelastic stress-strain curve were obtained in the temperature range from 473 K to 873 K. At 1073 K, on the other hand, high-temperature creep deformation was observed instead of ferroelastic deformation. The conductivity increases with increasing compressive stress at all the temperatures. The increase in conductivity is related to both geometrical and piezoelectric effects. From 293 K to 873 K, where the material exhibits ferroelastic behaviour, the variation in the total conductivity decreases with increasing temperature. The contribution of the piezoelectric effect to the total conductivity variation also decreases with increasing temperature and the maximum in piezoconductivity has a value of about 0.75 % at 293 K for a compressive stress of 100 MPa. There is no effect of domain switching on conductivity except for the geometric effect. At 1073 K, the conductivity is simply proportional to the compressive strain.

Journey on Image Clustering Based on Color Composition

Image clustering is a process of grouping images based on their similarity. The image clustering usually uses the color component, texture, edge, shape, or mixture of two components, etc. This research aims to explore image clustering using color composition. In order to complete this image clustering, three main components should be considered, which are color space, image representation (feature extraction), and clustering method itself. We aim to explore which composition of these factors will produce the best clustering results by combining various techniques from the three components. The color spaces use RGB, HSV, and L*a*b* method. The image representations use Histogram and Gaussian Mixture Model (GMM), whereas the clustering methods use KMeans and Agglomerative Hierarchical Clustering algorithm. The results of the experiment show that GMM representation is better combined with RGB and L*a*b* color space, whereas Histogram is better combined with HSV. The experiments also show that K-Means is better than Agglomerative Hierarchical for images clustering.

Some Rotational Flows of an Incompressible Fluid of Variable Viscosity

The Navier Stokes Equations (NSE) for an incompressible fluid of variable viscosity in the presence of an unknown external force in Von-Mises system x,\ are transformed, and some new exact solutions for a class of flows characterized by equation y f x a\b for an arbitrary state equation are determined, where f x is a function, \ the stream function, a z 0 and b are the arbitrary constants. In three, out of four cases, the function f x is arbitrary, and the solutions are the solutions of the flow equations for all the flows characterized by the equationy f x a\b. Streamline patterns for some forms of f x in unbounded and bounded regions are given.

Biogas Production from Waste using Biofilm Reactor: Factor Analysis in Two Stages System

Factor analysis was applied to two stages biogas production from banana stem waste allowing a screening of the experimental variables second stage temperature (T), organic loading rates (OLR) and hydraulic retention times (HRT). Biogas production was found to be strongly influenced by all the above experimental variables. Results from factorial analysis have shown that all variables which were HRT, OLR and T have significant effect to biogas production. Increased in HRT and OLR could increased the biogas yield. The performance was tested under the conditions of various T (35oC-60oC), OLR (0.3 g TS/l.d–1.9 gTS/l.d), and HRT (3 d–15 d). Conditions for temperature, OLR and HRT in this study were based on the best range obtained from literature review.

A Genetic and Simulated Annealing Based Algorithms for Solving the Flow Assignment Problem in Computer Networks

Selecting the routes and the assignment of link flow in a computer communication networks are extremely complex combinatorial optimization problems. Metaheuristics, such as genetic or simulated annealing algorithms, are widely applicable heuristic optimization strategies that have shown encouraging results for a large number of difficult combinatorial optimization problems. This paper considers the route selection and hence the flow assignment problem. A genetic algorithm and simulated annealing algorithm are used to solve this problem. A new hybrid algorithm combining the genetic with the simulated annealing algorithm is introduced. A modification of the genetic algorithm is also introduced. Computational experiments with sample networks are reported. The results show that the proposed modified genetic algorithm is efficient in finding good solutions of the flow assignment problem compared with other techniques.

The Effect of Carboxymethyl Cellulose on the Stability of Emulsions Stabilized by Whey Proteins under Digestion in vitro and in vivo

In vitro gastro-duodenal digestion model was used to investigate the changes of emulsions under digestion conditions. Oil in water emulsions stabilized by whey proteins (2%) and stabilized by whey proteins (2%) with addition of carboxymethyl cellulose (0.75%) as gelling agent of continuous phase were prepared at pH7. Both emulsions were destabilized under gastric conditions; however the protective role of carboxymethyl cellulose was indicated by recording delay of fat digestibility of this emulsion. In the presence of carboxymethyl cellulose whey proteins on the interfacial surface of droplets were more resistant to gastric degradation causing limited hydrolysis of fat due to the poor acceptability of lipids for the enzymes. Studies of emulsions using in vivo model supported results from in vitro studies. Lower content of triglycerides in blood serum and higher amount of fecal fat of rats were determined when rats were fed by diet containing emulsion made with whey proteins and carboxymethyl cellulose. 

Adaptive Group of Pictures Structure Based On the Positions of Video Cuts

In this paper we propose a method which improves the efficiency of video coding. Our method combines an adaptive GOP (group of pictures) structure and the shot cut detection. We have analyzed different approaches for shot cut detection with aim to choose the most appropriate one. The next step is to situate N frames to the positions of detected cuts during the process of video encoding. Finally the efficiency of the proposed method is confirmed by simulations and the obtained results are compared with fixed GOP structures of sizes 4, 8, 12, 16, 32, 64, 128 and GOP structure with length of entire video. Proposed method achieved the gain in bit rate from 0.37% to 50.59%, while providing PSNR (Peak Signal-to-Noise Ratio) gain from 1.33% to 0.26% in comparison to simulated fixed GOP structures.

Speaker Identification by Joint Statistical Characterization in the Log Gabor Wavelet Domain

Real world Speaker Identification (SI) application differs from ideal or laboratory conditions causing perturbations that leads to a mismatch between the training and testing environment and degrade the performance drastically. Many strategies have been adopted to cope with acoustical degradation; wavelet based Bayesian marginal model is one of them. But Bayesian marginal models cannot model the inter-scale statistical dependencies of different wavelet scales. Simple nonlinear estimators for wavelet based denoising assume that the wavelet coefficients in different scales are independent in nature. However wavelet coefficients have significant inter-scale dependency. This paper enhances this inter-scale dependency property by a Circularly Symmetric Probability Density Function (CS-PDF) related to the family of Spherically Invariant Random Processes (SIRPs) in Log Gabor Wavelet (LGW) domain and corresponding joint shrinkage estimator is derived by Maximum a Posteriori (MAP) estimator. A framework is proposed based on these to denoise speech signal for automatic speaker identification problems. The robustness of the proposed framework is tested for Text Independent Speaker Identification application on 100 speakers of POLYCOST and 100 speakers of YOHO speech database in three different noise environments. Experimental results show that the proposed estimator yields a higher improvement in identification accuracy compared to other estimators on popular Gaussian Mixture Model (GMM) based speaker model and Mel-Frequency Cepstral Coefficient (MFCC) features.

Application of Staining Intensity Correlation Analysis to Visualize Protein Colocalizationat a Cellular Level

Mutations of the telomeric copy of the survival motor neuron 1 (SMN1) gene cause spinal muscular atrophy. A deletion of the Eef1a2 gene leads to lower motor neuron degeneration in wasted mice. Indirect evidences have been shown that the eEF1A protein family may interact with SMN, and our previous study showed that abnormalities of neuromuscular junctions in wasted mice were similar to those of Smn mutant mice. To determine potential colocalization between SMN and tissue-specific translation elongation factor 1A2 (eEF1A2), an immunochemical analysis of HeLa cells transfected with the plasmid pcDNA3.1(+)C-hEEF1A2- myc and a new quantitative test of colocalization by intensity correlation analysis (ICA) was used to explore the association of SMN and eEF1A2. Here the results showed that eEF1A2 redistributed from the cytoplasm to the nucleus in response to serum and epidermal growth factor. In the cytoplasm, compelling evidence showed that staining for myc-tagged eEF1A2 varied in synchrony with that for SMN, consistent with the formation of a SMN-eEF1A2 complex in the cytoplasm of HeLa cells. These findings suggest that eEF1A2 may colocalize with SMN in the cytoplasm and may be a component of the SMN complex. However, the limitation of the ICA method is an inability to resolve colocalization in components of small organelles such as the nucleus.

Thermal Treatments and Characteristics Study On Unalloyed Structural (AISI 1140) Steel

The main emphasis of metallurgists has been to process the materials to obtain the balanced mechanical properties for the given application. One of the processing routes to alter the properties is heat treatment. Nearly 90% of the structural applications are related to the medium carbon an alloyed steels and hence are regarded as structural steels. The major requirement in the conventional steel is to improve workability, toughness, hardness and grain refinement. In this view, it is proposed to study the mechanical and tribological properties of unalloyed structural (AISI 1140) steel with different thermal (heat) treatments like annealing, normalizing, tempering and hardening and compared with as brought (cold worked) specimen. All heat treatments are carried out in atmospheric condition. Hardening treatment improves hardness of the material, a marginal decrease in hardness value with improved ductility is observed in tempering. Annealing and normalizing improve ductility of the specimen. Normalized specimen shows ultimate ductility. Hardened specimen shows highest wear resistance in the initial period of slide wear where as above 25KM of sliding distance, as brought steel dominates the hardened specimen. Both mild and severe wear regions are observed. Microstructural analysis shows the existence of pearlitic structure in normalized specimen, lath martensitic structure in hardened, pearlitic, ferritic structure in annealed specimen.