Effects of Chitosan as the Growth Stimulator for Grammatophyllum speciosum in Vitro Culture

The effects of chitosan, a biodegradable polymer, were studied in Grammatophyllum speciosum protocorm-like bodies (PLBs) in vitro culture. The chitosan concentration of 0, 5, 10, 15, 20, 25, 50 or 100 mg/l were supplemented in half-strength Murashige and Skoog (1/2 MS) liquid or on agar media containing 2% (w/v) sucrose. The results showed that liquid medium supplemented with 15 mg/l chitosan showed the highest relative growth rate (7-fold increase) of PLBs. On 1/2 MS agar medium supplemented with 25 mg/l chitosan gave the highest relative growth rate (4-fold increase). The relative growth rate of G. speciosum PLBs on agar medium was significantly lower than that in liquid medium. Moreover, chitosan, supplemented to agar medium promoted shoot formation but not rooting. However, supplementation at too high a level, such as 100 mg/l can inhibit growth and kill PLBs.

A Normalization-based Robust Watermarking Scheme Using Zernike Moments

Digital watermarking has become an important technique for copyright protection but its robustness against attacks remains a major problem. In this paper, we propose a normalizationbased robust image watermarking scheme. In the proposed scheme, original host image is first normalized to a standard form. Zernike transform is then applied to the normalized image to calculate Zernike moments. Dither modulation is adopted to quantize the magnitudes of Zernike moments according to the watermark bit stream. The watermark extracting method is a blind method. Security analysis and false alarm analysis are then performed. The quality degradation of watermarked image caused by the embedded watermark is visually transparent. Experimental results show that the proposed scheme has very high robustness against various image processing operations and geometric attacks.

Unsteady Transonic Aerodynamic Analysis for Oscillatory Airfoils using Time Spectral Method

This research proposes an algorithm for the simulation of time-periodic unsteady problems via the solution unsteady Euler and Navier-Stokes equations. This algorithm which is called Time Spectral method uses a Fourier representation in time and hence solve for the periodic state directly without resolving transients (which consume most of the resources in a time-accurate scheme). Mathematical tools used here are discrete Fourier transformations. It has shown tremendous potential for reducing the computational cost compared to conventional time-accurate methods, by enforcing periodicity and using Fourier representation in time, leading to spectral accuracy. The accuracy and efficiency of this technique is verified by Euler and Navier-Stokes calculations for pitching airfoils. Because of flow turbulence nature, Baldwin-Lomax turbulence model has been used at viscous flow analysis. The results presented by the Time Spectral method are compared with experimental data. It has shown tremendous potential for reducing the computational cost compared to the conventional time-accurate methods, by enforcing periodicity and using Fourier representation in time, leading to spectral accuracy, because results verify the small number of time intervals per pitching cycle required to capture the flow physics.

Analysis of the Effect of 1980 Transformation on the Foreign Trade of Turkey with Chow Test

While import-substituting industrialization policy constitute the basis for the industrialization strategies of the 1960s and 1970s in Turkey, this policy was no longer sustainable by the 1980s. For this reason, export-oriented industrialization policy was adopted with the decisions taken on January 24, 1980. In other words, the post-1980 period, Turkey's economy has adopted outwardoriented industrialization strategy. In this study, it is aimed to analyze the effect of the change in economic structure on foreign trade with the transformation of foreign trade and industrialization policies in the post-1980 period. In this respect, in order to analyze the relationship between import, export and economic growth by using variables of the 1960-2011 period, Chow test was applied. In the analysis the reason for using Chow test is whether there is any difference in economic terms between import-substituting industrialization policy applied in the 1960-1980 period and the 1981-2011 period during which exportoriented industrialization policy was applied as a result of the structural transformation.

An Evaluation Framework of Transportation Responsiveness: Case of Pattaya City

Transportation is one of the main activities related to creating value for the tourists. Transport management in tourism mainly focuses on managing transfer points and vehicle capacity. However, transport service level must also be ensured as it now relates to tourist-s experiences. This paper emphasizes on the responsiveness as one of key service performance measures. An evaluation framework is developed and illustarted by using the case of small bus service in Pattaya city. It can be seen as a great potential for the city to utilize the small bus transportation in order to meet the needs of more diverse group of passengers and to support the expansion of tourist areas. The framework integrates with service operations management, logistics, and tourism behavior perspectives. The findings from the investigation of existing small bus service are presented and preliminarily validate the usability of the framework.

Validation Testing for Temporal Neural Networks for RBF Recognition

A neuron can emit spikes in an irregular time basis and by averaging over a certain time window one would ignore a lot of information. It is known that in the context of fast information processing there is no sufficient time to sample an average firing rate of the spiking neurons. The present work shows that the spiking neurons are capable of computing the radial basis functions by storing the relevant information in the neurons' delays. One of the fundamental findings of the this research also is that when using overlapping receptive fields to encode the data patterns it increases the network-s clustering capacity. The clustering algorithm that is discussed here is interesting from computer science and neuroscience point of view as well as from a perspective.

Design and Analysis of a Solar Refrigeration System with a Rotating Generator

A solar refrigeration system based on the adsorptiondesorption phenomena is designed and analyzed. An annular tubular generator filled with silica gel adsorbent and with a perforated inner cylinder is integrated within a flat solar collector. The working fluid in the refrigeration cycle is water. The thermodynamic analysis and because of the temperature level that could be attained with a flat solar collector it is required that the system operates under vacuum conditions. In order to enhance the performance of the system and to get uniform temperature in the silica gel and higher desorbed mass, an apparatus for rotation of the generator is incorporated in the system. Testing is carried out and measurements are taken on the designed installation. The effect of rotation is checked on the temperature distribution and on the performance of this machine and compared to the flat solar collector with fixed generator.

Face Localization and Recognition in Varied Expressions and Illumination

In this paper, we propose a robust scheme to work face alignment and recognition under various influences. For face representation, illumination influence and variable expressions are the important factors, especially the accuracy of facial localization and face recognition. In order to solve those of factors, we propose a robust approach to overcome these problems. This approach consists of two phases. One phase is preprocessed for face images by means of the proposed illumination normalization method. The location of facial features can fit more efficient and fast based on the proposed image blending. On the other hand, based on template matching, we further improve the active shape models (called as IASM) to locate the face shape more precise which can gain the recognized rate in the next phase. The other phase is to process feature extraction by using principal component analysis and face recognition by using support vector machine classifiers. The results show that this proposed method can obtain good facial localization and face recognition with varied illumination and local distortion.

Automatic Detection and Spatio-temporal Analysis of Commercial Accumulations Using Digital Yellow Page Data

In this study, the locations and areas of commercial accumulations were detected by using digital yellow page data. An original buffering method that can accurately create polygons of commercial accumulations is proposed in this paper.; by using this method, distribution of commercial accumulations can be easily created and monitored over a wide area. The locations, areas, and time-series changes of commercial accumulations in the South Kanto region can be monitored by integrating polygons of commercial accumulations with the time-series data of digital yellow page data. The circumstances of commercial accumulations were shown to vary according to areas, that is, highly- urbanized regions such as the city center of Tokyo and prefectural capitals, suburban areas near large cities, and suburban and rural areas.

Fuzzy Logic Controlled Shunt Active Power Filter for Three-phase Four-wire Systems with Balanced and Unbalanced Loads

This paper presents a fuzzy logic controlled shunt active power filter used to compensate for harmonic distortion in three-phase four-wire systems. The shunt active filter employs a simple method for the calculation of the reference compensation current based of Fast Fourier Transform. This presented filter is able to operate in both balanced and unbalanced load conditions. A fuzzy logic based current controller strategy is used to regulate the filter current and hence ensure harmonic free supply current. The validity of the presented approach in harmonic mitigation is verified via simulation results of the proposed test system under different loading conditions.

Effect of Welding Processes on Fatigue Properties of Ti-6Al-4V Alloy Joints

This paper reports the fatigue crack growth behaviour of gas tungsten arc, electron beam and laser beam welded Ti-6Al-4V titanium alloy. Centre cracked tensile specimens were prepared to evaluate the fatigue crack growth behaviour. A 100kN servo hydraulic controlled fatigue testing machine was used under constant amplitude uniaxial tensile load (stress ratio of 0.1 and frequency of 10 Hz). Crack growth curves were plotted and crack growth parameters (exponent and intercept) were evaluated. Critical and threshold stress intensity factor ranges were also evaluated. Fatigue crack growth behaviour of welds was correlated with mechanical properties and microstructural characteristics of welds. Of the three joints, the joint fabricated by laser beam welding exhibited higher fatigue crack growth resistance due to the presence of fine lamellar microstructure in the weld metal.

The modeling of Brand Loyalty in the Brewing Market in Poland

Brand loyalty is a strategic asset of the company. In the era of competition to have loyal customers decides on the market superiority of enterprises. Creating the loyalty of buyers, however, is a lengthy process and requires the appropriate business strategy, preceded by the proper market research. The purpose of the paper is to present the concept of brand loyalty, the creation of loyalty of customers, the benefits and determinants of loyalty on the example of brewery market in Poland.

Unsupervised Segmentation using Fuzzy Logicbased Texture Spectrum for MRI Brain Images

Textures are replications, symmetries and combinations of various basic patterns, usually with some random variation one of the gray-level statistics. This article proposes a new approach to Segment texture images. The proposed approach proceeds in 2 stages. First, in this method, local texture information of a pixel is obtained by fuzzy texture unit and global texture information of an image is obtained by fuzzy texture spectrum. The purpose of this paper is to demonstrate the usefulness of fuzzy texture spectrum for texture Segmentation. The 2nd Stage of the method is devoted to a decision process, applying a global analysis followed by a fine segmentation, which is only focused on ambiguous points. The above Proposed approach was applied to brain image to identify the components of brain in turn, used to locate the brain tumor and its Growth rate.

A Hamiltonian Decomposition of 5-star

Star graphs are Cayley graphs of symmetric groups of permutations, with transpositions as the generating sets. A star graph is a preferred interconnection network topology to a hypercube for its ability to connect a greater number of nodes with lower degree. However, an attractive property of the hypercube is that it has a Hamiltonian decomposition, i.e. its edges can be partitioned into disjoint Hamiltonian cycles, and therefore a simple routing can be found in the case of an edge failure. The existence of Hamiltonian cycles in Cayley graphs has been known for some time. So far, there are no published results on the much stronger condition of the existence of Hamiltonian decompositions. In this paper, we give a construction of a Hamiltonian decomposition of the star graph 5-star of degree 4, by defining an automorphism for 5-star and a Hamiltonian cycle which is edge-disjoint with its image under the automorphism.

ANFIS Modeling of the Surface Roughness in Grinding Process

The objective of this study is to design an adaptive neuro-fuzzy inference system (ANFIS) for estimation of surface roughness in grinding process. The Used data have been generated from experimental observations when the wheel has been dressed using a rotary diamond disc dresser. The input parameters of model are dressing speed ratio, dressing depth and dresser cross-feed rate and output parameter is surface roughness. In the experimental procedure the grinding conditions are constant and only the dressing conditions are varied. The comparison of the predicted values and the experimental data indicates that the ANFIS model has a better performance with respect to back-propagation neural network (BPNN) model which has been presented by the authors in previous work for estimation of the surface roughness.

The Effect of Compost Addition on Chemical and Nitrogen Characteristics, Respiration Activity and Biomass Production in Prepared Reclamation Substrates

Land degradation is of concern in many countries. People more and more must address the problems associated with the degradation of soil properties due to man. Increasingly, organic soil amendments, such as compost are being examined for their potential use in soil restoration and for preventing soil erosion. In the Czech Republic, compost is the most used to improve soil structure and increase the content of soil organic matter. Land reclamation / restoration is one of the ways to evaluate industrially produced compost because Czech farmers are not willing to use compost as organic fertilizer. The most common use of reclamation substrates in the Czech Republic is for the rehabilitation of landfills and contaminated sites. This paper deals with the influence of reclamation substrates (RS) with different proportions of compost and sand on selected soil properties–chemical characteristics, nitrogen bioavailability, leaching of mineral nitrogen, respiration activity and plant biomass production. Chemical properties vary proportionally with addition of compost and sand to the control variant (topsoil). The highest differences between the variants were recorded in leaching of mineral nitrogen (varies from 1.36mg dm-3 in C to 9.09mg dm-3). Addition of compost to soil improves conditions for plant growth in comparison with soil alone. However, too high addition of compost may have adverse effects on plant growth. In addition, high proportion of compost increases leaching of mineral N. Therefore, mixture of 70% of soil with 10% of compost and 20% of sand may be recommended as optimal composition of RS.

The Performance of Alternating Top-Bottom Strategy for Successive Over Relaxation Scheme on Two Dimensional Boundary Value Problem

This paper present the implementation of a new ordering strategy on Successive Overrelaxation scheme on two dimensional boundary value problems. The strategy involve two directions alternatingly; from top and bottom of the solution domain. The method shows to significantly reduce the iteration number to converge. Four numerical experiments were carried out to examine the performance of the new strategy.

Attacks Classification in Adaptive Intrusion Detection using Decision Tree

Recently, information security has become a key issue in information technology as the number of computer security breaches are exposed to an increasing number of security threats. A variety of intrusion detection systems (IDS) have been employed for protecting computers and networks from malicious network-based or host-based attacks by using traditional statistical methods to new data mining approaches in last decades. However, today's commercially available intrusion detection systems are signature-based that are not capable of detecting unknown attacks. In this paper, we present a new learning algorithm for anomaly based network intrusion detection system using decision tree algorithm that distinguishes attacks from normal behaviors and identifies different types of intrusions. Experimental results on the KDD99 benchmark network intrusion detection dataset demonstrate that the proposed learning algorithm achieved 98% detection rate (DR) in comparison with other existing methods.

Study on Environmental Statement for Home Appliances at Online Stores in Japan

This study aims to identify the current situation and problems of environmental statement for major four home appliances (refrigerators, washing machines, air conditioners and television receivers) sold at online stores in Japan, and then to suggest how to improve the situation, through a questionnaire survey conducted among businesses that operate online stores and online malls with multiple online stores. Results of the study boil down to: (1) It is found out that environmental statement for the home appliances at online stores have four problems; (i) less information on “three Rs" and “chemical substances" than the one on “energy conservation", (ii) cost for providing environmental statement, (iii) issues associated with a label and mark placement, and (iv) issues associated with energy conservation statement. (2) Improvements are suggested for each of the four problems listed above, and shown are (i) the effectiveness of, and need to promote, a label and mark placement, (ii) cost burden on buyers, and (iii) need of active efforts made by businesses and of dissemination of legal regulations to businesses.

An Algebra for Protein Structure Data

This paper presents an algebraic approach to optimize queries in domain-specific database management system for protein structure data. The approach involves the introduction of several protein structure specific algebraic operators to query the complex data stored in an object-oriented database system. The Protein Algebra provides an extensible set of high-level Genomic Data Types and Protein Data Types along with a comprehensive collection of appropriate genomic and protein functions. The paper also presents a query translator that converts high-level query specifications in algebra into low-level query specifications in Protein-QL, a query language designed to query protein structure data. The query transformation process uses a Protein Ontology that serves the purpose of a dictionary.