Designing and Manufacturing High Voltage Pulse Generator with Adjustable Pulse and Monitoring Current and Voltage: Food Processing Application

Using strength Pulse Electrical Field (PEF) in food industries is a non-thermal process that can deactivate microorganisms and increase penetration in plant and animals tissues without serious impact on food taste and quality. In this paper designing and fabricating of a PEF generator has been presented. Pulse generation methods have been surveyed and the best of them selected. The equipment by controller set can generate square pulse with adjustable parameters such as amplitude 1-5kV, frequency 0.1-10Hz, pulse width 10-100s, and duty cycle 0-100%. Setting the number of pulses, and presenting the output voltage and current waveforms on the oscilloscope screen are another advantages of this equipment. Finally, some food samples were tested that yielded the satisfactory results. PEF applying had considerable effects on potato, banana and purple cabbage. It caused increase Brix factor from 0.05 to 0.15 in potato solution. It is also so effective in extraction color material from purple cabbage. In the last experiment effects of PEF voltages on color extraction of saffron scum were surveyed (about 6% increasing yield).

Using Rao-Blackwellised Particle Filter Track 3D Arm Motion based on Hierarchical Limb Model

For improving the efficiency of human 3D tracking, we present an algorithm to track 3D Arm Motion. First, the Hierarchy Limb Model (HLM) is proposed based on the human 3D skeleton model. Second, via graph decomposition, the arm motion state space, modeled by HLM, can be discomposed into two low dimension subspaces: root nodes and leaf nodes. Finally, Rao-Blackwellised Particle Filter is used to estimate the 3D arm motion. The result of experiment shows that our algorithm can advance the computation efficiency.

Automated Particle Picking based on Correlation Peak Shape Analysis and Iterative Classification

Cryo-electron microscopy (CEM) in combination with single particle analysis (SPA) is a widely used technique for elucidating structural details of macromolecular assemblies at closeto- atomic resolutions. However, development of automated software for SPA processing is still vital since thousands to millions of individual particle images need to be processed. Here, we present our workflow for automated particle picking. Our approach integrates peak shape analysis to the classical correlation and an iterative approach to separate macromolecules and background by classification. This particle selection workflow furthermore provides a robust means for SPA with little user interaction. Processing simulated and experimental data assesses performance of the presented tools.

The Effects of an Information Delivery Modality on Psychology of E-learning Students

Does a communication modality matter in delivering e-learning information? With the recent growth of broadcasting systems, media technologies and e-learning contents, various systems with different communication modalities have been introduced. In accordance with these trends, this study examines the effects of the information delivery modality on psychology of students. Findings from an experiment indicated that the delivering information which includes a video modality elicited higher degrees of credibility, quality, representativeness of content, and perceived suitability for delivering information than those of auditory information. However, there is no difference between content liking and attitude. The Implications of the findings and the limitations are discussed.

Error-Robust Nature of Genome Profiling Applied for Clustering of Species Demonstrated by Computer Simulation

Genome profiling (GP), a genotype based technology, which exploits random PCR and temperature gradient gel electrophoresis, has been successful in identification/classification of organisms. In this technology, spiddos (Species identification dots) and PaSS (Pattern similarity score) were employed for measuring the closeness (or distance) between genomes. Based on the closeness (PaSS), we can buildup phylogenetic trees of the organisms. We noticed that the topology of the tree is rather robust against the experimental fluctuation conveyed by spiddos. This fact was confirmed quantitatively in this study by computer-simulation, providing the limit of the reliability of this highly powerful methodology. As a result, we could demonstrate the effectiveness of the GP approach for identification/classification of organisms.

Incremental Algorithm to Cluster the Categorical Data with Frequency Based Similarity Measure

Clustering categorical data is more complicated than the numerical clustering because of its special properties. Scalability and memory constraint is the challenging problem in clustering large data set. This paper presents an incremental algorithm to cluster the categorical data. Frequencies of attribute values contribute much in clustering similar categorical objects. In this paper we propose new similarity measures based on the frequencies of attribute values and its cardinalities. The proposed measures and the algorithm are experimented with the data sets from UCI data repository. Results prove that the proposed method generates better clusters than the existing one.

Inferring the Dynamics of “Hidden“ Neurons from Electrophysiological Recordings

Statistical analysis of electrophysiological recordings obtained under, e.g. tactile, stimulation frequently suggests participation in the network dynamics of experimentally unobserved “hidden" neurons. Such interneurons making synapses to experimentally recorded neurons may strongly alter their dynamical responses to the stimuli. We propose a mathematical method that formalizes this possibility and provides an algorithm for inferring on the presence and dynamics of hidden neurons based on fitting of the experimental data to spike trains generated by the network model. The model makes use of Integrate and Fire neurons “chemically" coupled through exponentially decaying synaptic currents. We test the method on simulated data and also provide an example of its application to the experimental recording from the Dorsal Column Nuclei neurons of the rat under tactile stimulation of a hind limb.

Effect of Different Methods of Soil Fertility on Grain Yield and Chickpea Quality

In order to evaluation the effects of natural, biological and chemical fertilizers on grain yield and chickpea quality, field experiments were carried out in 2007 and 2008 growing seasons. In this research the effects of different organic, chemical and biological fertilizers were investigated on grain yield and quality of chickpea. Experimental units were arranged in split-split plots based on randomized complete blocks with three replications. The highest amounts of yield and yield components were obtained in G1×N5 interaction. Significant increasing of N, P, K, Fe and Mg content in leaves and grains emphasized on superiority of mentioned treatment because each one of these nutrients has an approved role in chlorophyll synthesis and photosynthesis ability of the crop. The combined application of compost, farmyard manure and chemical phosphorus (N5) had the best grain quality due to high protein, starch and total sugar contents, low crude fiber and reduced cooking time.

Finite Element Prediction on the Machining Stability of Milling Machine with Experimental Verification

Chatter vibration has been a troublesome problem for a machine tool toward the high precision and high speed machining. Essentially, the machining performance is determined by the dynamic characteristics of the machine tool structure and dynamics of cutting process, which can further be identified in terms of the stability lobe diagram. Therefore, realization on the machine tool dynamic behavior can help to enhance the cutting stability. To assess the dynamic characteristics and machining stability of a vertical milling system under the influence of a linear guide, this study developed a finite element model integrated the modeling of linear components with the implementation of contact stiffness at the rolling interface. Both the finite element simulations and experimental measurements reveal that the linear guide with different preload greatly affects the vibration behavior and milling stability of the vertical column spindle head system, which also clearly indicate that the predictions of the machining stability agree well with the cutting tests. It is believed that the proposed model can be successfully applied to evaluate the dynamics performance of machine tool systems of various configurations.

Statistical Process Optimization Through Multi-Response Surface Methodology

In recent years, response surface methodology (RSM) has brought many attentions of many quality engineers in different industries. Most of the published literature on robust design methodology is basically concerned with optimization of a single response or quality characteristic which is often most critical to consumers. For most products, however, quality is multidimensional, so it is common to observe multiple responses in an experimental situation. Through this paper interested person will be familiarize with this methodology via surveying of the most cited technical papers. It is believed that the proposed procedure in this study can resolve a complex parameter design problem with more than two responses. It can be applied to those areas where there are large data sets and a number of responses are to be optimized simultaneously. In addition, the proposed procedure is relatively simple and can be implemented easily by using ready-made standard statistical packages.

Multi-Label Hierarchical Classification for Protein Function Prediction

Hierarchical classification is a problem with applications in many areas as protein function prediction where the dates are hierarchically structured. Therefore, it is necessary the development of algorithms able to induce hierarchical classification models. This paper presents experimenters using the algorithm for hierarchical classification called Multi-label Hierarchical Classification using a Competitive Neural Network (MHC-CNN). It was tested in ten datasets the Gene Ontology (GO) Cellular Component Domain. The results are compared with the Clus-HMC and Clus-HSC using the hF-Measure.

Microbiological Assessment of Yoghurt Enriched with Flakes from Barley Grain and Malt Extract during Shelf-Life

The effect of flakes from biologically activated hullless barley grain and malt extract on microbiological safety of yoghurt was studied. Pasteurized milk, freeze-dried yoghurt culture YF-L811 (Chr. Hansen, Denmark), flakes from biologically activated hull-less barley grain (Latvia) and malt extract (Ilgezeem, Latvia) were used for experiments. Yoghurt samples with flakes from biologically activated hull-less barley grain and malt extract were analyzed for total plate count of mesophylic aerobic and facultative anaerobic microorganisms, as well yeasts and moulds population during shelflife. Results showed that the changes of pH and titratable acidity affected the concentration of added malt extract. The lowest pH and the highest titratable acidity were determined in samples YFBG5% ME4% and YFBG5% ME6% on the 14th day. The total plate count decreased in all yoghurt samples except sample YFBG5% ME6%, where was determined the increase of microorganisms from 7th till 14th day. The adding of flakes from biologically activated hull-less barley grain in yoghurt samples caused the higher initial content of yeasts and moulds comparing with control. The growth of yeasts and moulds during shelf-life provided the added malt extract in yoghurt samples. Yoghurt enriched with flakes from biologically activated hull-less barley grain and malt extract from a microbiological perspective is safe product.

Statistical Distributions of the Lapped Transform Coefficients for Images

Discrete Cosine Transform (DCT) based transform coding is very popular in image, video and speech compression due to its good energy compaction and decorrelating properties. However, at low bit rates, the reconstructed images generally suffer from visually annoying blocking artifacts as a result of coarse quantization. Lapped transform was proposed as an alternative to the DCT with reduced blocking artifacts and increased coding gain. Lapped transforms are popular for their good performance, robustness against oversmoothing and availability of fast implementation algorithms. However, there is no proper study reported in the literature regarding the statistical distributions of block Lapped Orthogonal Transform (LOT) and Lapped Biorthogonal Transform (LBT) coefficients. This study performs two goodness-of-fit tests, the Kolmogorov-Smirnov (KS) test and the 2- test, to determine the distribution that best fits the LOT and LBT coefficients. The experimental results show that the distribution of a majority of the significant AC coefficients can be modeled by the Generalized Gaussian distribution. The knowledge of the statistical distribution of transform coefficients greatly helps in the design of optimal quantizers that may lead to minimum distortion and hence achieve optimal coding efficiency.

The Effect of Plant Growth Promoting Rhizobacteria (PGPR) on Germination, Seedling Growth and Yield of Maize

The effect of plant growth-promoting rhizobacteria (PGPR) on seed germination, seedling growth and yield of field grown maize were evaluated in three experiments. In these experiments six bacterial strains include P.putida strain R-168, P.fluorescens strain R-93, P.fluorescens DSM 50090, P.putida DSM291, A.lipoferum DSM 1691, A.brasilense DSM 1690 were used. Results of first study showed seed Inoculation significantly enhanced seed germination and seedling vigour of maize. In second experiment, leaf and shoot dry weight and also leaf surface area significantly were increased by bacterial inoculation in both sterile and non-sterile soil. The results showed that inoculation with bacterial treatments had a more stimulating effect on growth and development of plants in nonsterile than sterile soil. In the third experiment, Inoculation of maize seeds with all bacterial strains significantly increased plant height, 100 seed weight, number of seed per ear and leaf area .The results also showed significant increase in ear and shoot dry weight of maize.

Osmotic Dehydration of Apricot using Saltsucrose Solutions

Fruit drying is a well known process mostly used for preservation of fruits. Osmotic dehydration of apricot slices were carried out in three different salt-sucrose concentrations and four different temperatures. Also three different weight ratios of solution to sample were conducted to one set of experiments. The dehydration curves were constructed using Peleg-s model. Increasing the solution volume increased the mass transfer rate and hence the solid gain increased rapidly. Increasing the volume of osmotic media caused an increase in overall mass transfer but a 'solution to sample' ratio of 5:1 gave the best product quality. The best temperature and concentration that had a high water loss to solid gain ratio and an acceptable taste were 40°C and 5%, respectively.

A Performance Evaluation of Cellular Network Suitability for VANET

Recently, a vehicular ad-hoc networks(VANETs) for Intelligent Transport System(ITS) have become able safety and convenience services surpassing the simple services such as an electronic toll collection system. To provide the proper services, VANET needs infrastructure over the country infrastructure. Thus, we have to spend a huge sum of human resources. In this reason, several studies have been made on the usage of cellular networks instead of new protocols this study is to assess a performance evaluation of the cellular network for VANET. In this paper, the result of a for the suitability of cellular networks for VANET experiment, The LTE(Long Term Evolution) of cellular networks found to be most suitable among the others cellular networks

A Perceptual Image Coding method of High Compression Rate

In the framework of the image compression by Wavelet Transforms, we propose a perceptual method by incorporating Human Visual System (HVS) characteristics in the quantization stage. Indeed, human eyes haven-t an equal sensitivity across the frequency bandwidth. Therefore, the clarity of the reconstructed images can be improved by weighting the quantization according to the Contrast Sensitivity Function (CSF). The visual artifact at low bit rate is minimized. To evaluate our method, we use the Peak Signal to Noise Ratio (PSNR) and a new evaluating criteria witch takes into account visual criteria. The experimental results illustrate that our technique shows improvement on image quality at the same compression ratio.

Experimental Determination of Reactions of Wind-Resistant Support of Circular Stacks in Various Configurations

Higher capacities of power plants together with increased awareness on environmental considerations have led to taller height of stacks. It is seen that strong wind can result in falling of stacks. So, aerodynamic consideration of stacks is very important in order to save the falling of stacks. One stack is not enough in industries and power sectors and two or three stacks are required for proper operation of the unit. It is very important to arrange the stacks in proper way to resist their downfall. The present experimental study concentrates on the mutual effect of three nearby stacks on each other at three different arrangements, viz. linear, side-by-side and triangular. The experiments find out the directions of resultant forces acting on the stacks in different configurations so that proper arrangement of supports can be made with respect to the wind directionality obtained from local meteorological data. One can also easily ascertain which stack is more vulnerable to wind in comparison to the others for a particular configuration. Thus, this study is important in studying the effect of wind force on three stacks in different arrangements and is very helpful in placing the supports in proper places in order to avoid failing of stack-like structures due to wind.

Critical Assessment of Scoring Schemes for Protein-Protein Docking Predictions

Protein-protein interactions (PPI) play a crucial role in many biological processes such as cell signalling, transcription, translation, replication, signal transduction, and drug targeting, etc. Structural information about protein-protein interaction is essential for understanding the molecular mechanisms of these processes. Structures of protein-protein complexes are still difficult to obtain by biophysical methods such as NMR and X-ray crystallography, and therefore protein-protein docking computation is considered an important approach for understanding protein-protein interactions. However, reliable prediction of the protein-protein complexes is still under way. In the past decades, several grid-based docking algorithms based on the Katchalski-Katzir scoring scheme were developed, e.g., FTDock, ZDOCK, HADDOCK, RosettaDock, HEX, etc. However, the success rate of protein-protein docking prediction is still far from ideal. In this work, we first propose a more practical measure for evaluating the success of protein-protein docking predictions,the rate of first success (RFS), which is similar to the concept of mean first passage time (MFPT). Accordingly, we have assessed the ZDOCK bound and unbound benchmarks 2.0 and 3.0. We also createda new benchmark set for protein-protein docking predictions, in which the complexes have experimentally determined binding affinity data. We performed free energy calculation based on the solution of non-linear Poisson-Boltzmann equation (nlPBE) to improve the binding mode prediction. We used the well-studied thebarnase-barstarsystem to validate the parameters for free energy calculations. Besides,thenlPBE-based free energy calculations were conducted for the badly predicted cases by ZDOCK and ZRANK. We found that direct molecular mechanics energetics cannot be used to discriminate the native binding pose from the decoys.Our results indicate that nlPBE-based calculations appeared to be one of the promising approaches for improving the success rate of binding pose predictions.

Adaptive Multi-Camera Shooting System Based on Dynamic Workflow in a Compact Studio

We developed a multi-camera control system that a (one) cameraman can operate several cameras at a compact studio. we analyzed a workflow of a cameraman of some program shootings with two cameras and clarified their heavy tasks. The system based on a dynamic workflow which adapts a program progressing and recommends of cameraman. we perform the automation of multicamera controls by modeling of studio environment and perform automatic camera adjustment for suitable angle of view with face detection. Our experiment at a real program shooting showed that one cameraman can carry out the task of shooting sufficiently.