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Nuwan, K.A. Sameera,Wickramasuriya, Samiru Sudharaka,Jayasena, Dinesh D.,Tharangani, R.M. Himali,Song, Zhang,Yi, Young-Joo,Heo, Jung Min The Korean Society of Poultry Science 2016 韓國家禽學會誌 Vol.43 No.3
An experiment was conducted to evaluate the growth performance and meat quality traits of broilers fed a diet supplemented with dry-ground curry leaves (Murraya koenigii). A total of 750 one-day-old broiler chicks (Cobbs 500) were arranged in the experiment with a completely randomized design and allotted to one of five treatments, with $T_1-Control$ and $T_2-T_5$ curry leaves powder levels (i.e., 0.3%, 0.6%, 0.9% and 1.2%, respectively). The initial body weights, final body weights and daily feed intake were measured over an experimental period of 32 days. At the conclusion of the experiment, the carcass weights and meat quality parameters were measured. The birds fed diets supplemented with curry leaves powder had a higher weight gain (P<0.05; ADG), improved feed conversion ratio (P<0.05; FCR) and lower mortality (P<0.05) rates compared to the birds in the control group. Nonetheless, there was no difference (P>0.05) in feed intake among the dietary treatments. Similarly, supplementation of curry leaves powder had no effect (P>0.05) on the proportions of the carcass, leg meat and drumstick. No differences were (P>0.05) observed in cooking loss or the pH of meat from broilers fed the curry leaves supplemented diet. However, curry leaf supplementation affected (P<0.05) the meat water holding capacity. A sensory evaluation showed higher levels of taste and tenderness in meat from broilers fed with curry leaves powder. In conclusion, our results suggested that curry leaves powder improved the growth performance of broilers, with a lower incidence of mortality and improvement of some meat qualities.
Community-based Informed Agents Selection for Flocking with a Virtual Leader
Nuwan Ganganath,Chi-Tsun Cheng,Xiaofan Wang,Chi K. Tse 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.1
It has been studied that a few informed individuals in a group of interacting dynamic agents can influencethe majority to follow the position and velocity of a virtual leader. Previously it has been shown that a cluster-basedselection of informed agents can drive more agents to follow the virtual leader compared to a random selection. However, a practical question is: How many informed agents to select? In order to address this, here we proposea novel method for selecting informed agents based on community structures in the initial spatial distribution ofagents. The number of informed agents are decided based on the strongest community structure. We test andanalyze the performance of the proposed method against random and cluster-based selections of informed agentsusing extensive computer simulations. Results of our study show that community-based selection can be usefulin deciding an optimum number of informed agents such that a majority of the group can achieve their commonobjective.
Real Time Moving Object Detection Based on Frame Difference and Doppler Effects in HSV color model
Nuwan Sanjeewa,김원호 사단법인 한국위성정보통신학회 2014 한국위성정보통신학회논문지 Vol.9 No.4
This paper propose a method to detect moving object and locating in real time from video sequence. first the proposedmethod extract moving object by differencing two consecutive frames from the video sequence. If the interval betweencaptured two frames is long, it cause to generate fake moving object as tail of the real moving object. secondly this paperproposed method to overcome this problem by using doppler effects and HSV color model. finally the object segmentationand locating is done by combining the result that obtained from steps above. The proposed method has 99.2% of detectionrate in practical and also this method is comparatively speed than other similar methods those proposed in past. Since thecomplexity of the algorithm is directly affects to the speed of the system, the proposed method can be used as lowcomplexity algorithm for real time moving object detection.
Madusanka, Nuwan,Choi, Yu Yong,Choi, Kyu Yeong,Lee, Kun Ho,Choi, Heung-Kook Korea Multimedia Society 2017 멀티미디어학회논문지 Vol.20 No.2
The brain magnetic resonance images (MRI) is an important imaging biomarker in Alzheimer's disease (AD) as the cerebral atrophy has been shown to strongly associate with cognitive symptoms. The decrease of volume estimates in different structures of the medial temporal lobe related to memory correlates with the decline of cognitive functions in neurodegenerative diseases. During the past decades several methods have been developed for quantifying the disease related atrophy of hippocampus from MRI. Special effort has been dedicated to separate AD and mild cognitive impairment (MCI) related modifications from normal aging for the purpose of early detection and prediction. We trained a multi-class support vector machine (SVM) with probabilistic outputs on a sample (n = 58) of 20 normal controls (NC), 19 individuals with MCI, and 19 individuals with AD. The model was then applied to the cross-validation of same data set which no labels were known and the predictions. This study presents data on the association between MRI quantitative parameters of hippocampus and its quantitative structural changes examination use on the classification of the diseases.
3D Rendering of Magnetic Resonance Images using Visualization Toolkit and Microsoft.NET Framework
Madusanka, Nuwan,Zaben, Naim Al,Shidaifat, Alaaddin Al,Choi, Heung-Kook Korea Multimedia Society 2015 The journal of multimedia information system Vol.2 No.2
In this paper, we proposed new software for 3D rendering of MR images in the medical domain using C# wrapper of Visualization Toolkit (VTK) and Microsoft .NET framework. Our objective in developing this software was to provide medical image segmentation, 3D rendering and visualization of hippocampus for diagnosis of Alzheimer disease patients using DICOM Images. Such three dimensional visualization can play an important role in the diagnosis of Alzheimer disease. Segmented images can be used to reconstruct the 3D volume of the hippocampus, and it can be used for the feature extraction, measure the surface area and volume of hippocampus to assist the diagnosis process. This software has been designed with interactive user interfaces and graphic kernels based on Microsoft.NET framework to get benefited from C# programming techniques, in particular to design pattern and rapid application development nature, a preliminary interactive window is functioning by invoking C#, and the kernel of VTK is simultaneously embedded in to the window, where the graphics resources are then allocated. Representation of visualization is through an interactive window so that the data could be rendered according to user's preference.