Comparative Micro-Morphology, Anatomy and Architecture of Leaf of Physalis

Two species of Physalis, P.angulataL. and P. peruviana L. were used as models for comparative study to understand the values of micro-morphological, -anatomical and architectural characteristics of leaf for taxonomic purposes and possibly breeding and commercial applications. Both speciespossess amphistomaticleaves with 1-layer epidermis, 3-4-layer spongy mesophyll andbicollateral bundle midrib. Palisade parenchyma cells of P. angulatawere almost twice longer (65-75 μm) than the other one. Type of stomata was similar as anomocyticbut stomatal index(SI) at adaxial surface and abaxial surface of P. angulata were less than of P. peruvianaas 3.57, 4.00 and6.25, 6.66 respectively. Some leaf architectural characteristics such as leaf shape, order of venationalsoprovided information of taxonomic significance

Comparison between Associative Classification and Decision Tree for HCV Treatment Response Prediction

Combined therapy using Interferon and Ribavirin is the standard treatment in patients with chronic hepatitis C. However, the number of responders to this treatment is low, whereas its cost and side effects are high. Therefore, there is a clear need to predict patient’s response to the treatment based on clinical information to protect the patients from the bad drawbacks, Intolerable side effects and waste of money. Different machine learning techniques have been developed to fulfill this purpose. From these techniques are Associative Classification (AC) and Decision Tree (DT). The aim of this research is to compare the performance of these two techniques in the prediction of virological response to the standard treatment of HCV from clinical information. 200 patients treated with Interferon and Ribavirin; were analyzed using AC and DT. 150 cases had been used to train the classifiers and 50 cases had been used to test the classifiers. The experiment results showed that the two techniques had given acceptable results however the best accuracy for the AC reached 92% whereas for DT reached 80%.

An Image Encryption Method with Magnitude and Phase Manipulation using Carrier Images

We describe an effective method for image encryption which employs magnitude and phase manipulation using carrier images. Although it involves traditional methods like magnitude and phase encryptions, the novelty of this work lies in deploying the concept of carrier images for encryption purpose. To this end, a carrier image is randomly chosen from a set of stored images. One dimensional (1-D) discrete Fourier transform (DFT) is then carried out on the original image to be encrypted along with the carrier image. Row wise spectral addition and scaling is performed between the magnitude spectra of the original and carrier images by randomly selecting the rows. Similarly, row wise phase addition and scaling is performed between the original and carrier images phase spectra by randomly selecting the rows. The encrypted image obtained by these two operations is further subjected to one more level of magnitude and phase manipulation using another randomly chosen carrier image by 1-D DFT along the columns. The resulting encrypted image is found to be fully distorted, resulting in increasing the robustness of the proposed work. Further, applying the reverse process at the receiver, the decrypted image is found to be distortionless.

Potential of Solar Energy in Zarqa Region

The purpose of this work is to present the potential of solar energy in Zarqa region. The solar radiation along year 2009 was obtained from Pyranometer which measures the global radiation over horizontal surfaces. Solar data in several different forms, over period of 5 minutes, hour-by-hour, daily and monthly data radiation have been presented. Briefly, the yearly global solar radiation in Zarqa is 7297.5 MJ/m2 (2027 kWh/m²) and the average annual solar radiation per day is 20 MJ/m2 (5.5 Kwh/m2). More specifically, the average annual solar radiation per day is 12.9 MJ/m2 (3.57 Kwh/m2) in winter and 25 MJ/m2 (7 Kwh/m2) in summer.

Design of Non-Blocking and Rearrangeable Modified Banyan Network with Electro-Optic MZI Switching Elements

Banyan networks are really attractive for serving as the optical switching architectures due to their unique properties of small depth and absolute signal loss uniformity. The fact has been established that the limitations of blocking nature and the nonavailability of proper connections due to non-rearrangeable property can be easily ruled out using electro-optic MZI switches as basic switching elements. Combination of the horizontal expansion and vertical stacking of optical banyan networks is an appropriate scheme for constructing non-blocking banyan-based optical switching networks. The interconnected banyan switching fabrics (IBSF) have been considered and analyzed to best serve the purpose of optical switching with electro-optic MZI basic elements. The cross/bar state interchange for the switches has been facilitated by appropriate voltage switching or the by the switching of operating wavelength. The paper is dedicated to the modification of the basic switching element being used as well as the architecture of the switching network.

Characteristics of Corporate Social Responsibility Indicators

The aim of the study is to investigate a number of characteristics of Corporate Social Responsibility (CSR) indicators that should be adopted by CSR assessment methodologies. For the purpose of this paper, a survey among the Greek companies that belong to FTSE 20 in Athens Exchange (FTSE/Athex-20) has been conducted, as these companies are expected to pioneer in the field of CSR. The results show consensus as regards the characteristics of indicators such as the need for the adoption of general and specific sector indicators, financial and non-financial indicators, the origin and the weight rate. However, the results are contradictory concerning the appropriate number of indicators for the assessment of CSR and the unit of measurement. Finally, the company-s sector is a more important dimension of CSR than the size and the country where the company operates. The purpose of this paper is to standardize the main characteristics of CSR indicators.

Detection of Moving Images Using Neural Network

Motion detection is a basic operation in the selection of significant segments of the video signals. For an effective Human Computer Intelligent Interaction, the computer needs to recognize the motion and track the moving object. Here an efficient neural network system is proposed for motion detection from the static background. This method mainly consists of four parts like Frame Separation, Rough Motion Detection, Network Formation and Training, Object Tracking. This paper can be used to verify real time detections in such a way that it can be used in defense applications, bio-medical applications and robotics. This can also be used for obtaining detection information related to the size, location and direction of motion of moving objects for assessment purposes. The time taken for video tracking by this Neural Network is only few seconds.

Acceptance Single Sampling Plan with Fuzzy Parameter with The Using of Poisson Distribution

This purpose of this paper is to present the acceptance single sampling plan when the fraction of nonconforming items is a fuzzy number and being modeled based on the fuzzy Poisson distribution. We have shown that the operating characteristic (oc) curves of the plan is like a band having a high and low bounds whose width depends on the ambiguity proportion parameter in the lot when that sample size and acceptance numbers is fixed. Finally we completed discuss opinion by a numerical example. And then we compared the oc bands of using of binomial with the oc bands of using of Poisson distribution.

Effects of Dual Inoculation of Azotobacter and Mycorrhiza with Nitrogen and Phosphorus Fertilizer Rates on Grain Yield and Some of Characteristics of Spring Safflower

In order to evaluate the Effects of dual inoculation of Azotobacter and Mycorrhiza with Nitrogen and Phosphorus levels on yield and yield components of spring safflower, this study was carried out in field of Farahan university in Markazi province in 2007. A factorial in a randomized complete block design with three replications was used inoculation of Azotobacter (with inoculation and without inoculation) and Mycorrhiza (with inoculation and without inoculation ) with Nitrogen and Phosphorus levels [F0= N0+ P0 (kg.ha-1), F1= N50+ P25(kg.ha-1), F2= N100+ P50(kg.ha-1) and F3= N150+ P75 (kg.ha-1)] on spring safflower (cultivar IL-111). In this study characteristics such as: Harvest index, Hectolitre weight, Root dry weight, Seed yield, Mycorrhizal Colonization Root, Number of days to maturity were assessed. Results indicated that treatment (A0M1F3) with grain yield (1556 kg.ha-1) and treatment (A0M1F0) with grain yield (918 kg.ha-1) were significantly superior to the other treatments and according to calculated, inoculation seeds in plantig date with Azotobacter and Mycorrhiza to cause increase grain yield about 5/38 percentage. we can by inoculation safflower seeds with Azotobacter and Mycorrhiza too easily at the time sowing date. The purpose of this research, study and evaluation the role of biological fixation N and P, to provide for feeds plants.

Calculating Strain Energy in Multi-Surface Models of Cyclic Plasticity

When considering the development of constitutive equations describing the behavior of materials under cyclic plastic strains, different kinds of formulations can be adopted. The primary intention of this study is to develop computer programming of plasticity models to accurately predict the life of engineering components. For this purpose, the energy or cyclic strain is computed in multi-surface plasticity models in non-proportional loading and to present their procedures and codes results.

Bioprocessing of Proximally Analyzed Wheat Straw for Enhanced Cellulase Production through Process Optimization with Trichodermaviride under SSF

The purpose of the present work was to study the production and process parameters optimization for the synthesis of cellulase from Trichoderma viride in solid state fermentation (SSF) using an agricultural wheat straw as substrates; as fungal conversion of lignocellulosic biomass for cellulase production is one among the major increasing demand for various biotechnological applications. An optimization of process parameters is a necessary step to get higher yield of product. Several kinetic parameters like pretreatment, extraction solvent, substrate concentration, initial moisture content, pH, incubation temperature and inoculum size were optimized for enhanced production of third most demanded industrially important cellulase. The maximum cellulase enzyme activity 398.10±2.43 μM/mL/min was achieved when proximally analyzed lignocellulosic substrate wheat straw inocubated at 2% HCl as pretreatment tool along with distilled water as extraction solvent, 3% substrate concentration 40% moisture content with optimum pH 5.5 at 45°C incubation temperature and 10% inoculum size.

Primary School Principals in Turkey: Their Working Conditions and Professional Profiles

In order to achieve effective management, the professional and individual characteristics and qualifications of school principals and their system-oriented perception is very important. Therefore, it is necessary to conduct regular comprehensive studies into the profiles of school principals. The purpose of this study is to determine the perceptions of primary school principals about their working conditions and to present their professional profiles. The questionnaire was distributed to 1475 respondents and 1428 valid questionnaires were evaluated. The results of the research were discussed and compared to other similar studies.Keywordseducation, education management, primary school principal, principals profiles

Gate Tunnel Current Calculation for NMOSFET Based on Deep Sub-Micron Effects

Aggressive scaling of MOS devices requires use of ultra-thin gate oxides to maintain a reasonable short channel effect and to take the advantage of higher density, high speed, lower cost etc. Such thin oxides give rise to high electric fields, resulting in considerable gate tunneling current through gate oxide in nano regime. Consequently, accurate analysis of gate tunneling current is very important especially in context of low power application. In this paper, a simple and efficient analytical model has been developed for channel and source/drain overlap region gate tunneling current through ultra thin gate oxide n-channel MOSFET with inevitable deep submicron effect (DSME).The results obtained have been verified with simulated and reported experimental results for the purpose of validation. It is shown that the calculated tunnel current is well fitted to the measured one over the entire oxide thickness range. The proposed model is suitable enough to be used in circuit simulator due to its simplicity. It is observed that neglecting deep sub-micron effect may lead to large error in the calculated gate tunneling current. It is found that temperature has almost negligible effect on gate tunneling current. It is also reported that gate tunneling current reduces with the increase of gate oxide thickness. The impact of source/drain overlap length is also assessed on gate tunneling current.

Feature Extraction from Aerial Photos

In Geographic Information System, one of the sources of obtaining needed geographic data is digitizing analog maps and evaluation of aerial and satellite photos. In this study, a method will be discussed which can be used to extract vectorial features and creating vectorized drawing files for aerial photos. At the same time a software developed for these purpose. Converting from raster to vector is also known as vectorization and it is the most important step when creating vectorized drawing files. In the developed algorithm, first of all preprocessing on the aerial photo is done. These are; converting to grayscale if necessary, reducing noise, applying some filters and determining the edge of the objects etc. After these steps, every pixel which constitutes the photo are followed from upper left to right bottom by examining its neighborhood relationship and one pixel wide lines or polylines obtained. The obtained lines have to be erased for preventing confusion while continuing vectorization because if not erased they can be perceived as new line, but if erased it can cause discontinuity in vector drawing so the image converted from 2 bit to 8 bit and the detected pixels are expressed as a different bit. In conclusion, the aerial photo can be converted to vector form which includes lines and polylines and can be opened in any CAD application.

Improving Spatiotemporal Change Detection: A High Level Fusion Approach for Discovering Uncertain Knowledge from Satellite Image Database

This paper investigates the problem of tracking spa¬tiotemporal changes of a satellite image through the use of Knowledge Discovery in Database (KDD). The purpose of this study is to help a given user effectively discover interesting knowledge and then build prediction and decision models. Unfortunately, the KDD process for spatiotemporal data is always marked by several types of imperfections. In our paper, we take these imperfections into consideration in order to provide more accurate decisions. To achieve this objective, different KDD methods are used to discover knowledge in satellite image databases. Each method presents a different point of view of spatiotemporal evolution of a query model (which represents an extracted object from a satellite image). In order to combine these methods, we use the evidence fusion theory which considerably improves the spatiotemporal knowledge discovery process and increases our belief in the spatiotemporal model change. Experimental results of satellite images representing the region of Auckland in New Zealand depict the improvement in the overall change detection as compared to using classical methods.

Human Growth Curve Estimation through a Combination of Longitudinal and Cross-sectional Data

Parametric models have been quite popular for studying human growth, particularly in relation to biological parameters such as peak size velocity and age at peak size velocity. Longitudinal data are generally considered to be vital for fittinga parametric model to individual-specific data, and for studying the distribution of these biological parameters in a human population. However, cross-sectional data are easier to obtain than longitudinal data. In this paper, we present a method of combining longitudinal and cross-sectional data for the purpose of estimating the distribution of the biological parameters. We demonstrate, through simulations in the special case ofthePreece Baines model, how estimates based on longitudinal data can be improved upon by harnessing the information contained in cross-sectional data.We study the extent of improvement for different mixes of the two types of data, and finally illustrate the use of the method through data collected by the Indian Statistical Institute.

Using Dempster-Shafer Theory in XML Information Retrieval

XML is a markup language which is becoming the standard format for information representation and data exchange. A major purpose of XML is the explicit representation of the logical structure of a document. Much research has been performed to exploit logical structure of documents in information retrieval in order to precisely extract user information need from large collections of XML documents. In this paper, we describe an XML information retrieval weighting scheme that tries to find the most relevant elements in XML documents in response to a user query. We present this weighting model for information retrieval systems that utilize plausible inferences to infer the relevance of elements in XML documents. We also add to this model the Dempster-Shafer theory of evidence to express the uncertainty in plausible inferences and Dempster-Shafer rule of combination to combine evidences derived from different inferences.

Dynamic Analyze of Snake Robot

Crawling movement as a motive mode seen in nature of some animals such as snakes possesses a specific syntactic and dynamic analysis. Serpentine robot designed by inspiration from nature and snake-s crawling motion, is regarded as a crawling robot. In this paper, a serpentine robot with spiral motion model will be analyzed. The purpose of this analysis is to calculate the vertical and tangential forces along snake-s body and to determine the parameters affecting on these forces. Two types of serpentine robots have been designed in order to examine the achieved relations explained below.

Effect of Consumer Demographic Factors on Purchasing Herbal Products Online in Malaysia

The availability of broadband internet and increased access to computers has been instrumental in the rise of internet literacy in Malaysia. This development has led to the adoption of online shopping by many Malaysians. On another note, the Government has supported the development and production of local herbal products. This has resulted in an increase in the production and diversity of products by SMEs. The purpose of this study is to evaluate the influence of the Malaysian demographic factors and selected attitudinal characteristics in relation to the online purchasing of herbal products. In total, 1054 internet users were interviewed online and Chi-square analysis was used to determine the relationship between demographic variables and different aspects of online shopping for herbal products. The overall results show that the demographic variables such as age, gender, education level, income and ethnicity were significant when considering the online shopping antecedents of trust, quality of herbal products, perceived risks and perceived benefits.

Support Vector Machine Prediction Model of Early-stage Lung Cancer Based on Curvelet Transform to Extract Texture Features of CT Image

Purpose: To explore the use of Curvelet transform to extract texture features of pulmonary nodules in CT image and support vector machine to establish prediction model of small solitary pulmonary nodules in order to promote the ratio of detection and diagnosis of early-stage lung cancer. Methods: 2461 benign or malignant small solitary pulmonary nodules in CT image from 129 patients were collected. Fourteen Curvelet transform textural features were as parameters to establish support vector machine prediction model. Results: Compared with other methods, using 252 texture features as parameters to establish prediction model is more proper. And the classification consistency, sensitivity and specificity for the model are 81.5%, 93.8% and 38.0% respectively. Conclusion: Based on texture features extracted from Curvelet transform, support vector machine prediction model is sensitive to lung cancer, which can promote the rate of diagnosis for early-stage lung cancer to some extent.