A Comparative Study on Survival and Growth of Larvivorous Fish, Rasbora daniconius, Puntius ticto, and Puntius Conchonius

Experiments were carried out on the survival and growth of Rasbora daniconius, Puntius ticto and Puntius conchonius. The motivation of the study was to obtain information for growing the fish on a commercial scale for their use as biological control agents against mosquito larvae. The effects of temperature, total hardness, DO, pH and feed on the growth of fish were also investigated. Excessive value of total hardness was found because very rich calcium ion is present in Chitrakoot area. There was significant increases in growth rates of fish as temperature was increased from 280C to 300C. Further increases in temperature up to 320C, did not further affect growth. The positive and highly significant correlations 0.991488, 0.9581 and 0.9935 were found between length and weight of P. ticto, P. conchonius and R. daniconius respectively. The regression was significant at 5% level of probability.

A Comparative Study of Turbulence Models Performance for Turbulent Flow in a Planar Asymmetric Diffuser

This paper presents a computational study of the separated flow in a planer asymmetric diffuser. The steady RANS equations for turbulent incompressible fluid flow and six turbulence closures are used in the present study. The commercial software code, FLUENT 6.3.26, was used for solving the set of governing equations using various turbulence models. Five of the used turbulence models are available directly in the code while the v2-f turbulence model was implemented via User Defined Scalars (UDS) and User Defined Functions (UDF). A series of computational analysis is performed to assess the performance of turbulence models at different grid density. The results show that the standard k-ω, SST k-ω and v2-f models clearly performed better than other models when an adverse pressure gradient was present. The RSM model shows an acceptable agreement with the velocity and turbulent kinetic energy profiles but it failed to predict the location of separation and attachment points. The standard k-ε and the low-Re k- ε delivered very poor results.

Bandwidth Optimization through Dynamic Routing in ATM Networks: Genetic Algorithm and Tabu Search Approach

Asynchronous Transfer Mode (ATM) is widely used in telecommunications systems to send data, video and voice at a very high speed. In ATM network optimizing the bandwidth through dynamic routing is an important consideration. Previous research work shows that traditional optimization heuristics result in suboptimal solution. In this paper we have explored non-traditional optimization technique. We propose comparison of two such algorithms - Genetic Algorithm (GA) and Tabu search (TS), based on non-traditional Optimization approach, for solving the dynamic routing problem in ATM networks which in return will optimize the bandwidth. The optimized bandwidth could mean that some attractive business applications would become feasible such as high speed LAN interconnection, teleconferencing etc. We have also performed a comparative study of the selection mechanisms in GA and listed the best selection mechanism and a new initialization technique which improves the efficiency of the GA.

A Comparative Study of Web-pages Classification Methods using Fuzzy Operators Applied to Arabic Web-pages

In this study, a fuzzy similarity approach for Arabic web pages classification is presented. The approach uses a fuzzy term-category relation by manipulating membership degree for the training data and the degree value for a test web page. Six measures are used and compared in this study. These measures include: Einstein, Algebraic, Hamacher, MinMax, Special case fuzzy and Bounded Difference approaches. These measures are applied and compared using 50 different Arabic web-pages. Einstein measure was gave best performance among the other measures. An analysis of these measures and concluding remarks are drawn in this study.

Color View Synthesis for Animated Depth Security X-ray Imaging

We demonstrate the synthesis of intermediary views within a sequence of color encoded, materials discriminating, X-ray images that exhibit animated depth in a visual display. During the image acquisition process, the requirement for a linear X-ray detector array is replaced by synthetic image. Scale Invariant Feature Transform, SIFT, in combination with material segmented morphing is employed to produce synthetic imagery. A quantitative analysis of the feature matching performance of the SIFT is presented along with a comparative study of the synthetic imagery. We show that the total number of matches produced by SIFT reduces as the angular separation between the generating views increases. This effect is accompanied by an increase in the total number of synthetic pixel errors. The trends observed are obtained from 15 different luggage items. This programme of research is in collaboration with the UK Home Office and the US Dept. of Homeland Security.

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.

Comparative Study of Tensile Properties of Cortical Bone Using Sub-size Specimens and Finite Element Simulation

Bone material is treated as heterogeneous and hierarchical in nature therefore appropriate size of bone specimen is required to analyze its tensile properties at a particular hierarchical level. Tensile properties of cortical bone are important to investigate the effect of drug treatment, disease and aging as well as for development of computational and analytical models. In the present study tensile properties of buffalo as well as goat femoral and tibiae cortical bone are analyzed using sub-size tensile specimens. Femoral cortical bone was found to be stronger in tension as compared to the tibiae cortical bone and the tensile properties obtained using sub-size specimens show close resemblance with the tensile properties of full-size cortical specimens. A two dimensional finite element (FE) modal was also applied to simulate the tensile behavior of sub-size specimens. Good agreement between experimental and FE model was obtained for sub-size tensile specimens of cortical bone.

3D Rendering of American Sign Language Finger-Spelling: A Comparative Study of Two Animation Techniques

In this paper we report a study aimed at determining the most effective animation technique for representing ASL (American Sign Language) finger-spelling. Specifically, in the study we compare two commonly used 3D computer animation methods (keyframe animation and motion capture) in order to ascertain which technique produces the most 'accurate', 'readable', and 'close to actual signing' (i.e. realistic) rendering of ASL finger-spelling. To accomplish this goal we have developed 20 animated clips of fingerspelled words and we have designed an experiment consisting of a web survey with rating questions. 71 subjects ages 19-45 participated in the study. Results showed that recognition of the words was correlated with the method used to animate the signs. In particular, keyframe technique produced the most accurate representation of the signs (i.e., participants were more likely to identify the words correctly in keyframed sequences rather than in motion captured ones). Further, findings showed that the animation method had an effect on the reported scores for readability and closeness to actual signing; the estimated marginal mean readability and closeness was greater for keyframed signs than for motion captured signs. To our knowledge, this is the first study aimed at measuring and comparing accuracy, readability and realism of ASL animations produced with different techniques.

Wavelet - Based Classification of Outdoor Natural Scenes by Resilient Neural Network

Natural outdoor scene classification is active and promising research area around the globe. In this study, the classification is carried out in two phases. In the first phase, the features are extracted from the images by wavelet decomposition method and stored in a database as feature vectors. In the second phase, the neural classifiers such as back-propagation neural network (BPNN) and resilient back-propagation neural network (RPNN) are employed for the classification of scenes. Four hundred color images are considered from MIT database of two classes as forest and street. A comparative study has been carried out on the performance of the two neural classifiers BPNN and RPNN on the increasing number of test samples. RPNN showed better classification results compared to BPNN on the large test samples.

Emotion Recognition Using Neural Network: A Comparative Study

Emotion recognition is an important research field that finds lots of applications nowadays. This work emphasizes on recognizing different emotions from speech signal. The extracted features are related to statistics of pitch, formants, and energy contours, as well as spectral, perceptual and temporal features, jitter, and shimmer. The Artificial Neural Networks (ANN) was chosen as the classifier. Working on finding a robust and fast ANN classifier suitable for different real life application is our concern. Several experiments were carried out on different ANN to investigate the different factors that impact the classification success rate. Using a database containing 7 different emotions, it will be shown that with a proper and careful adjustment of features format, training data sorting, number of features selected and even the ANN type and architecture used, a success rate of 85% or even more can be achieved without increasing the system complicity and the computation time

A Comparative Study into Observer based Fault Detection and Diagnosis in DC Motors: Part-I

A model based fault detection and diagnosis technique for DC motor is proposed in this paper. Fault detection using Kalman filter and its different variants are compared. Only incipient faults are considered for the study. The Kalman Filter iterations and all the related computations required for fault detection and fault confirmation are presented. A second order linear state space model of DC motor is used for this work. A comparative assessment of the estimates computed from four different observers and their relative performance is evaluated.

Comparative Study of Indoor Environment in Residential Buildings in Hot Humid Climate of Malaysia

There-s a lack in understanding the indoor climate of Malaysian residential. The assumption of traditional house could provide the best indoor environment is too good to be true. This research is to understand indoor environment in three types of Malaysian residential and thermo recorder TR72Ui were placed in indoor spaces for measurement. There are huge differences of indoor environment between housing types, and building material helps to control indoor climate. Traditional house indoor climate was similar to the outdoor. Temperature in the bedroom of terrace and town houses were slightly higher than the living room. Indoor temperature was 2oC lower in the rainy season than the hot season. It was hard to control indoor humidity level in traditional house compared with terrace and town house. As for conclusion, town house provides the best thermal environment to the building occupants and can be improved with good roof insulation.

Centre Of Mass Selection Operator Based Meta-Heuristic For Unbounded Knapsack Problem

In this paper a new Genetic Algorithm based on a heuristic operator and Centre of Mass selection operator (CMGA) is designed for the unbounded knapsack problem(UKP), which is NP-Hard combinatorial optimization problem. The proposed genetic algorithm is based on a heuristic operator, which utilizes problem specific knowledge. This center of mass operator when combined with other Genetic Operators forms a competitive algorithm to the existing ones. Computational results show that the proposed algorithm is capable of obtaining high quality solutions for problems of standard randomly generated knapsack instances. Comparative study of CMGA with simple GA in terms of results for unbounded knapsack instances of size up to 200 show the superiority of CMGA. Thus CMGA is an efficient tool of solving UKP and this algorithm is competitive with other Genetic Algorithms also.

Automatic Discrimimation of the Modes of Permanent Flow of a Liquid Simulating Blood

In order to be able to automatically differentiate between two modes of permanent flow of a liquid simulating blood, it was imperative to put together a data bank. Thus, the acquisition of the various amplitude spectra of the Doppler signal of this liquid in laminar flow and other spectra in turbulent flow enabled us to establish an automatic difference between the two modes. According to the number of parameters and their nature, a comparative study allowed us to choose the best classifier.

Comparative Study of Sustainable Architecture in Stairway-like Ushtobin Village, Iran

Stairway Ushtobin Village is one of the five villages with original and sustainable architecture in Northwest of Iran along the border of Armenia, which has been able to maintain its environment and sustainable ecosystem. Studying circulation, function and scale (grand, medium and minor) of space, ratio of full and empty spaces, number and height of stairs, ratio of compound volume to luxury spaces, openings, type of local masonry (stone, mud, wood) and form of covering elements have been carried out in four houses of this village comparatively as some samples in this article, and furthermore, this article analyzes that the architectural shapes and organic texture of the village meet the needs of cold and dry climate. Finally, some efficient plans are offered suiting the present needs of the village to have a sustainable architecture.

Structural Characterization of Piscine Globin Superfamily Proteins

Globin superfamily proteins including myoglobin and hemoglobin, have welcome new members recently, namely, cytoglobin, neuroglobin and globin X, though their physiological functions are still to be addressed. Fish are the excellent models for the study of these globins, but their characteristics have not yet been discussed to date. In the present study, attempts have been made to characterize their structural uniqueness by making use of proteomics approach. This is the first comparative study on the characterization of globin superfamily proteins from fish.

Relevance Feedback within CBIR Systems

We present here the results for a comparative study of some techniques, available in the literature, related to the relevance feedback mechanism in the case of a short-term learning. Only one method among those considered here is belonging to the data mining field which is the K-nearest neighbors algorithm (KNN) while the rest of the methods is related purely to the information retrieval field and they fall under the purview of the following three major axes: Shifting query, Feature Weighting and the optimization of the parameters of similarity metric. As a contribution, and in addition to the comparative purpose, we propose a new version of the KNN algorithm referred to as an incremental KNN which is distinct from the original version in the sense that besides the influence of the seeds, the rate of the actual target image is influenced also by the images already rated. The results presented here have been obtained after experiments conducted on the Wang database for one iteration and utilizing color moments on the RGB space. This compact descriptor, Color Moments, is adequate for the efficiency purposes needed in the case of interactive systems. The results obtained allow us to claim that the proposed algorithm proves good results; it even outperforms a wide range of techniques available in the literature.

Comparative Study on the Antioxidant Activity of Leaf Extract and Carotenoids Extract from Ipomoea batatas var. Oren (Sweetpotato) Leaves

Ipomoea batatas (Sweetpotato) is currently ranked sixth in the total world food production and are planted mainly for their storage roots. The present study was undertaken to evaluate and compare the antioxidant properties of the leaf and carotenoids extract from the Ipomoea batatas var. Oren leaves. Total flavonoids in the leaf extract was 144.6 ± 40.5 μg/g compared to 114.86 ± 4.35 μg/g catechin equivalent in the carotenoids extract. Total polyphenols in the leaf extracts (3.470 ± 0.024 GAE g/100g DW) was slightly higher compared to carotenoids extract (2.994 ± 0.078 GAE g/100g DW). The carotenoids extract marked a higher radical scavenging capacity with the IC50= 491.86 μg/ml compared to leaf extract (IC50= 545.39 μg/ml). Concentration-dependent reducing activity was observed for both extracts. Thus, the carotenoids extraction process retained most of the antioxidant capacity from the leaves and can be made into potential natural yellow dye with antioxidant property.

Description and Analysis of Embedded Firewall Techniques

With the turn of this century, many researchers started showing interest in Embedded Firewall (EF) implementations. These are not the usual firewalls that are used as checkpoints at network gateways. They are, rather, applied near those hosts that need protection. Hence by using them, individual or grouped network components can be protected from the inside as well as from external attacks. This paper presents a study of EF-s, looking at their architecture and problems. A comparative study assesses how practical each kind is. It particularly focuses on the architecture, weak points, and portability of each kind. A look at their use by different categories of users is also presented.

A Study of Color Transformation on Website Images for the Color Blind

In this paper, we study on color transformation method on website images for the color blind. The most common category of color blindness is red-green color blindness which is viewed as beige color. By transforming the colors of the images, the color blind can improve their color visibility. They can have a better view when browsing through the websites. To transform colors on the website images, we study on two algorithms which are the conversion techniques from RGB color space to HSV color space and self-organizing color transformation. The comparative study focuses on criteria based on the ease of use, quality, accuracy and efficiency. The outcome of the study leads to enhancement of website images to meet the color blinds- vision requirements in perceiving image detailed.