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Search Results: 1 - 10 of 1544 matches for " Don Ajith Rohana Dolage "
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The Impact of Adoption of Flexible Manufacturing Technology on Price Cost Margin of Malaysian Manufacturing Industry  [PDF]
Don Ajith Rohana Dolage, Abu Bakar Sade
Technology and Investment (TI) , 2012, DOI: 10.4236/ti.2012.31005
Abstract: This paper explores the impact of the adoption of Flexible Manufacturing Technology (FMT) on the Malaysian Manu-facturing Industry. The Principal Component Analysis has been adopted to extract the most appropriate underlying dimensions of FMT to use in place of the eight FMT variables owing to the potential multicollinearity. The study has been conducted within FMT intensively adopted 16 three-digit industries that encompass 50 five-digit industries cover-ing the years 2000-2005. The results obtained from the two scenarios, one, including the industry fixed effects dummy variables and the other without these, are contrasted. It is established that the model that included the industry fixed effect dummy variables has a greater explanatory power. The two principal components that account for the greater variation in FMT show positive and moderately significant relationship with PCM. The study provides sufficient evi-dence to conclude that FMT has a direct and moderately significant relationship with PCM.
A Frontier Approach to Measuring Impact of Adoption of Flexible Manufacturing Technology on Technical Efficiency of Malaysian Manufacturing Industry  [PDF]
Don Ajith Rohana Dolage, Abu Bakar Sade
Technology and Investment (TI) , 2012, DOI: 10.4236/ti.2012.34037
Abstract: This paper examines the impact of the adoption of Flexible Manufacturing Technology (FMT) on the Technical Efficiency of Malaysia Manufacturing Industry. Owing to the potential multicollinearity, the Principal Component Analysis has been adopted to extract the most appropriate underlying dimensions of FMT in an effort to substitute the eight FMT variables. The study has been conducted within FMT intensively adopted 16 three-digit industries that encompass 50 five-digit industries covering the years 2000-2005. The results obtained from the two situations, one, including the industry fixed effects dummy variables and the other without these, are contrasted. It is found that the model that included the industry fixed effect dummy variables possesses a greater explanatory power. The two principal components that account for the greater variation in FMT show positive and moderately significant relationship with TE. The study concludes with sufficient evidence that FMT has a direct and moderately significant relationship with TE.
Skilling Requirements in Textiles: Technical Training and Its Trainers-Sri Lanka in Perspective  [PDF]
Rohana U. Kuruppu
Journal of Textile Science and Technology (JTST) , 2018, DOI: 10.4236/jtst.2018.44007
Abstract: The textile and clothing industry has become very competitive in the world over. There are many players in the industry. The most prominent player is China. Recent statistics reveal that China continue to be the world’s largest textile and clothing producer in 2016 (Textiles outlook, 2017). China’s major export markets are EU, USA and Japan. However, rising labour costs and production costs of China will shift production to lower cost suppliers. This will give South Asia and South-East Asia an opportunity to capitalize in their exports. The question is, can these regions in Asia take this challenge? To overcome the challenges, they must be ready with highly skilled manpower. The Tertiary and Vocational Educational Training system across Asian region must be geared to take this challenge of training the new recruits. Can these countries have adequate numbers of skilled, effective and experienced trainers to train the new recruits? Qualified trainers may be in short supply. Then, how quickly can these trainers be made available for training? Half-baked trainers would turn half-baked workers that will not give right condition to meet the future challenges. A recent study by the author has revealed that there are not enough qualified trainers to impart knowledge and skill for those in the textile and clothing industry in Sri Lanka. This can be the case across Asia. It is time that responsible professionals in the training industry should consider about trainers if they are to launch a massive skilling project to meet requirements of the textile/clothing industry. Skilling the trainers must be a priority. It will be interesting to note that there is a mismatch between trainees and training courses. Also, students are not attracted to training courses. So, there is a concern about who should be trained and are they available?
Medical Food to Stop the Progression of Parkinson’s Disease  [PDF]
Don McCammon
Advances in Parkinson's Disease (APD) , 2014, DOI: 10.4236/apd.2014.32003
Abstract:

No progress has been made in the development of drugs to stop the progression of Parkinson’s Disease. Here the author has presented a novel approach to stopping the disease using a dietary supplement primarily composed of Mannitol. In vivo animal studies have shown that Mannitol was able to break up alpha-synuclein clusters and restore functioning in transgenic drosophila and mice. The author, who has Parkinson’s, used himself as a subject and was able to achieve similar results.

Ode to Epileptologists!
Cherian Ajith
Annals of Indian Academy of Neurology , 2011,
Abstract:
Gravitational-wave data analysis using binary black-hole waveforms
P. Ajith
Physics , 2007, DOI: 10.1088/0264-9381/25/11/114033
Abstract: Coalescing binary black-hole systems are among the most promising sources of gravitational waves for ground-based interferometers. While the \emph{inspiral} and \emph{ring-down} stages of the binary black-hole coalescence are well-modelled by analytical approximation methods in general relativity, the recent progress in numerical relativity has enabled us to compute accurate waveforms from the \emph{merger} stage also. This has an important impact on the search for gravitational waves from binary black holes. In particular, while the current gravitational-wave searches look for each stage of the coalescence separately, combining the results from analytical and numerical relativity enables us to \emph{coherently} search for all three stages using a single template family. `Complete' binary black-hole waveforms can now be produced by matching post-Newtonian waveforms with those computed by numerical relativity. These waveforms can be parametrised to produce analytical waveform templates. The `complete' waveforms can also be used to estimate the efficiency of different search methods aiming to detect signals from black-hole coalescences. This paper summarises some recent efforts in this direction.
Addressing the spin question in gravitational-wave searches: Waveform templates for inspiralling compact binaries with nonprecessing spins
P. Ajith
Physics , 2011, DOI: 10.1103/PhysRevD.84.084037
Abstract: This paper presents a post-Newtonian (PN) template family of gravitational waveforms from inspiralling compact binaries with non-precessing spins, where the spin effects are described by a single "reduced-spin" parameter. This template family, which reparametrizes all the spin-dependent PN terms in terms of the leading-order (1.5PN) spin-orbit coupling term \emph{in an approximate way}, has very high overlaps (fitting factor > 0.99) with non-precessing binaries with arbitrary mass ratios and spins. We also show that this template family is "effectual" for the detection of a significant fraction of generic spinning binaries in the comparable-mass regime (m_2/m_1 <~ 10), providing an attractive and feasible way of searching for gravitational waves (GWs) from spinning low-mass binaries. We also show that the secular (non-oscillatory) spin-dependent effects in the phase evolution (which are taken into account by the non-precessing templates) are more important than the oscillatory effects of precession in the comparable-mass (m_1 ~= m_2) regime. Hence the effectualness of non-spinning templates is particularly poor in this case, as compared to non-precessing-spin templates. For the case of binary neutron stars observable by Advanced LIGO, even moderate spins (L . S/m^2 ~= 0.015 - 0.1) will cause considerable mismatches (~ 3% - 25%) with non-spinning templates. This is contrary to the expectation that neutron-star spins may not be relevant for GW detection.
Business Intelligence from Web Usage Mining
Ajith Abraham
Computer Science , 2004,
Abstract: The rapid e-commerce growth has made both business community and customers face a new situation. Due to intense competition on one hand and the customer's option to choose from several alternatives business community has realized the necessity of intelligent marketing strategies and relationship management. Web usage mining attempts to discover useful knowledge from the secondary data obtained from the interactions of the users with the Web. Web usage mining has become very critical for effective Web site management, creating adaptive Web sites, business and support services, personalization, network traffic flow analysis and so on. In this paper, we present the important concepts of Web usage mining and its various practical applications. We further present a novel approach 'intelligent-miner' (i-Miner) to optimize the concurrent architecture of a fuzzy clustering algorithm (to discover web data clusters) and a fuzzy inference system to analyze the Web site visitor trends. A hybrid evolutionary fuzzy clustering algorithm is proposed in this paper to optimally segregate similar user interests. The clustered data is then used to analyze the trends using a Takagi-Sugeno fuzzy inference system learned using a combination of evolutionary algorithm and neural network learning. Proposed approach is compared with self-organizing maps (to discover patterns) and several function approximation techniques like neural networks, linear genetic programming and Takagi-Sugeno fuzzy inference system (to analyze the clusters). The results are graphically illustrated and the practical significance is discussed in detail. Empirical results clearly show that the proposed Web usage-mining framework is efficient.
Meta-Learning Evolutionary Artificial Neural Networks
Ajith Abraham
Computer Science , 2004,
Abstract: In this paper, we present MLEANN (Meta-Learning Evolutionary Artificial Neural Network), an automatic computational framework for the adaptive optimization of artificial neural networks wherein the neural network architecture, activation function, connection weights; learning algorithm and its parameters are adapted according to the problem. We explored the performance of MLEANN and conventionally designed artificial neural networks for function approximation problems. To evaluate the comparative performance, we used three different well-known chaotic time series. We also present the state of the art popular neural network learning algorithms and some experimentation results related to convergence speed and generalization performance. We explored the performance of backpropagation algorithm; conjugate gradient algorithm, quasi-Newton algorithm and Levenberg-Marquardt algorithm for the three chaotic time series. Performances of the different learning algorithms were evaluated when the activation functions and architecture were changed. We further present the theoretical background, algorithm, design strategy and further demonstrate how effective and inevitable is the proposed MLEANN framework to design a neural network, which is smaller, faster and with a better generalization performance.
Neuro Fuzzy Systems: Sate-of-the-Art Modeling Techniques
Ajith Abraham
Computer Science , 2004,
Abstract: Fusion of Artificial Neural Networks (ANN) and Fuzzy Inference Systems (FIS) have attracted the growing interest of researchers in various scientific and engineering areas due to the growing need of adaptive intelligent systems to solve the real world problems. ANN learns from scratch by adjusting the interconnections between layers. FIS is a popular computing framework based on the concept of fuzzy set theory, fuzzy if-then rules, and fuzzy reasoning. The advantages of a combination of ANN and FIS are obvious. There are several approaches to integrate ANN and FIS and very often it depends on the application. We broadly classify the integration of ANN and FIS into three categories namely concurrent model, cooperative model and fully fused model. This paper starts with a discussion of the features of each model and generalize the advantages and deficiencies of each model. We further focus the review on the different types of fused neuro-fuzzy systems and citing the advantages and disadvantages of each model.
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