Scholarly

Model Parameters Estimating on Lyman–Kutcher–Burman Normal Tissue Complication Probability for Xerostomia on Head and Neck Cancer

Year: 2012 Volume: 6 Issue: 7 299 - 302 Pages

Abstract: The purpose of this study is to derive parameters estimating for the Lyman–Kutcher–Burman (LKB) normal tissue complication probability (NTCP) model using analysis of scintigraphy assessments and quality of life (QoL) measurement questionnaires for the parotid gland (xerostomia). In total, 31 patients with head-and-neck (HN) cancer were enrolled. Salivary excretion factor (SEF) and EORTC QLQ-H&N35 questionnaires datasets are used for the NTCP modeling to describe the incidence of grade 4 xerostomia. Assuming that n= 1, NTCP fitted parameters are given as TD50= 43.6 Gy, m= 0.18 in SEF analysis, and as TD50= 44.1 Gy, m= 0.11 in QoL measurements, respectively. SEF and QoL datasets can validate the Quantitative Analyses of Normal Tissue Effects in the Clinic (QUANTEC) guidelines well, resulting in NPV-s of 100% for the both datasets and suggests that the QUANTEC 25/20Gy gland-spared guidelines are suitable for clinical used for the HN cohort to effectively avoid xerostomia.

Keywords:
HN
NTCP
SEF
QoL
QUANTEC

Reciprocating Equipment Piston Rod Dynamic Elastic-Plastic Deformation Analysis

Year: 2009 Volume: 3 Issue: 7 766 - 770 Pages

Authors:
Amin Almasi

Abstract: Analysis of reciprocating equipment piston rod leads to nonlinear elastic-plastic deformation analysis of rod with initial imperfection under axial dynamic load. In this paper a new and effective model and analytical formulations are presented to evaluate dynamic deformation and elastic-plastic stresses of reciprocating machine piston rod. This new method has capability to account for geometric nonlinearity, elastic-plastic deformation and dynamic effects. Proposed method can be used for evaluation of piston rod performance for various reciprocating machines under different operation situations. Rod load curves and maximum allowable rod load are calculated with presented method for a refinery type reciprocating compressor. Useful recommendations and guidelines for rod load, rod load reversal and rod drop monitoring are also addressed.

Automation of Heat Exchanger using Neural Network

Year: 2008 Volume: 2 Issue: 3 267 - 271 Pages

Abstract: In this paper the development of a heat exchanger as a pilot plant for educational purpose is discussed and the use of neural network for controlling the process is being presented. The aim of the study is to highlight the need of a specific Pseudo Random Binary Sequence (PRBS) to excite a process under control. As the neural network is a data driven technique, the method for data generation plays an important role. In light of this a careful experimentation procedure for data generation was crucial task. Heat exchange is a complex process, which has a capacity and a time lag as process elements. The proposed system is a typical pipe-in- pipe type heat exchanger. The complexity of the system demands careful selection, proper installation and commissioning. The temperature, flow, and pressure sensors play a vital role in the control performance. The final control element used is a pneumatically operated control valve. While carrying out the experimentation on heat exchanger a welldrafted procedure is followed giving utmost attention towards safety of the system. The results obtained are encouraging and revealing the fact that if the process details are known completely as far as process parameters are concerned and utilities are well stabilized then feedback systems are suitable, whereas neural network control paradigm is useful for the processes with nonlinearity and less knowledge about process. The implementation of NN control reinforces the concepts of process control and NN control paradigm. The result also underlined the importance of excitation signal typically for that process. Data acquisition, processing, and presentation in a typical format are the most important parameters while validating the results.

“Magnetic Cleansing” for the Provision of a ‘Quick Clean’ to Oiled Wildlife

Year: 2012 Volume: 6 Issue: 12 743 - 745 Pages

Abstract: This research is part of a broad program aimed at advancing the science and technology involved in the rescue and rehabilitation of oiled wildlife. One aspect of this research involves the use of oil-sequestering magnetic particles for the removal of contaminants from plumage – so-called “magnetic cleansing". This treatment offers a number of advantages over conventional detergent-based methods including portability - which offers the possibility of providing a “quick clean" to the animal upon first encounter in the field. This could be particularly advantageous when the contaminant is toxic and/or corrosive and/or where there is a delay in transporting the victim to a treatment centre. The method could also be useful as part of a stabilization protocol when large numbers of affected animals are awaiting treatment. This presentation describes the design, development and testing of a prototype field kit for providing a “quick clean" to contaminated wildlife in the field.

Convergence of ICT and Education

Year: 2008 Volume: 2 Issue: 4 237 - 240 Pages

Authors:
Raju Kumar

Abstract: Information and communication technology (ICT) has become, within a very short time, one of the basic building blocks of modern society. Many countries now understanding the importance of ICT and mastering the basic skills and concepts of it as part of the core of education. Organizations, experts and practitioners in the education sector increasingly recognizing the importance of ICT in supporting educational improvement and reform. This paper addresses the convergence of ICT and education. When two technologies are converging to each other, together they will generate some great opportunities and challenges. This paper focuses on these issues. In introduction section, it explains the ICT, education, and ICT-enhanced education. In next section it describes need of ICT in education, relationship between ICT skills and education, and stages of teaching learning process. The next two sections describe opportunities and challenges in integrating ICT in education. Finally the concluding section summaries the idea and its usefulness.

Reality and Preferences in Community Mopane (Colophospermum Mopane) Woodland Management in Zimbabwe and Namibia

Year: 2007 Volume: 1 Issue: 4 23 - 27 Pages

Abstract: There is increasing pressure on, and decline of mopane woodlands due to increasing use and competition for mopane resources in Zimbabwe in Namibia. Community management strategies, based largely on local knowledge are evidently unable to cope. Research has generated potentially useful information for mopane woodland management, but this information has not been utilized. The work reported in this paper sought to add value to research work conducted on mopane woodlands by developing effective community-based mopane woodland management regimes that were based on both local and scientific knowledge in Zimbabwe and Namibia. The conditions under which research findings were likely to be adopted for mopane woodland management by communities were investigated. The study was conducted at two sites each in Matobo and Omusati Districts in Zimbabwe and Namibia respectively. The mopane woodland resources in the two study areas were assessed using scientific ecological methods. A range of participatory methods was used to collect information on use of mopane woodland resources by communities, institutional arrangements governing access to and use of these resources and to evaluate scientific knowledge for applicability in local management regimes. Coppicing, thinning and pollarding were the research generated management methods evaluated. Realities such as availability of woodland resources and social roles and responsibilities influenced preferences for woodland management interventions

Design and Fabrication of a Low Cost Heart Monitor using Reflectance Photoplethysmogram

Year: 2011 Volume: 5 Issue: 8 305 - 314 Pages

Abstract: This paper presents a low cost design of heart beat monitoring device using reflectance mode PhotoPlethysmography (PPG). PPG is known for its simple construction, ease of use and cost effectiveness and can provide information about the changes in cardiac activity as well as aid in earlier non-invasive diagnostics. The proposed device is divided into three phases. First is the detection of pulses through the fingertip. The signal is then passed to the signal processing unit for the purpose of amplification, filtering and digitizing. Finally the heart rate is calculated and displayed on the computer using parallel port interface. The paper is concluded with prototyping of the device followed by verification procedure of the heartbeat signal obtained in laboratory setting.

Corporate Credit Rating using Multiclass Classification Models with order Information

Year: 2011 Volume: 5 Issue: 12 1825 - 1830 Pages

Abstract: Corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has been one of the attractive research topics in the literature. In recent years, multiclass classification models such as artificial neural network (ANN) or multiclass support vector machine (MSVM) have become a very appealing machine learning approaches due to their good performance. However, most of them have only focused on classifying samples into nominal categories, thus the unique characteristic of the credit rating - ordinality - has been seldom considered in their approaches. This study proposes new types of ANN and MSVM classifiers, which are named OMANN and OMSVM respectively. OMANN and OMSVM are designed to extend binary ANN or SVM classifiers by applying ordinal pairwise partitioning (OPP) strategy. These models can handle ordinal multiple classes efficiently and effectively. To validate the usefulness of these two models, we applied them to the real-world bond rating case. We compared the results of our models to those of conventional approaches. The experimental results showed that our proposed models improve classification accuracy in comparison to typical multiclass classification techniques with the reduced computation resource.

Effect of Size of the Step in the Response Surface Methodology using Nonlinear Test Functions

Year: 2012 Volume: 6 Issue: 6 1064 - 1069 Pages

Abstract: The response surface methodology (RSM) is a collection of mathematical and statistical techniques useful in the modeling and analysis of problems in which the dependent variable receives the influence of several independent variables, in order to determine which are the conditions under which should operate these variables to optimize a production process. The RSM estimated a regression model of first order, and sets the search direction using the method of maximum / minimum slope up / down MMS U/D. However, this method selects the step size intuitively, which can affect the efficiency of the RSM. This paper assesses how the step size affects the efficiency of this methodology. The numerical examples are carried out through Monte Carlo experiments, evaluating three response variables: efficiency gain function, the optimum distance and the number of iterations. The results in the simulation experiments showed that in response variables efficiency and gain function at the optimum distance were not affected by the step size, while the number of iterations is found that the efficiency if it is affected by the size of the step and function type of test used.

Independent Component Analysis to Mass Spectra of Aluminium Sulphate

Year: 2007 Volume: 1 Issue: 2 7 - 11 Pages

Abstract: Independent component analysis (ICA) is a computational method for finding underlying signals or components from multivariate statistical data. The ICA method has been successfully applied in many fields, e.g. in vision research, brain imaging, geological signals and telecommunications. In this paper, we apply the ICA method to an analysis of mass spectra of oligomeric species emerged from aluminium sulphate. Mass spectra are typically complex, because they are linear combinations of spectra from different types of oligomeric species. The results show that ICA can decomposite the spectral components for useful information. This information is essential in developing coagulation phases of water treatment processes.

Ultrasonic Echo Image Adaptive Watermarking Using the Just-Noticeable Difference Estimation

Year: 2009 Volume: 3 Issue: 12 2771 - 2775 Pages

Abstract: Most of the image watermarking methods, using the properties of the human visual system (HVS), have been proposed in literature. The component of the visual threshold is usually related to either the spatial contrast sensitivity function (CSF) or the visual masking. Especially on the contrast masking, most methods have not mention to the effect near to the edge region. Since the HVS is sensitive what happens on the edge area. This paper proposes ultrasound image watermarking using the visual threshold corresponding to the HVS in which the coefficients in a DCT-block have been classified based on the texture, edge, and plain area. This classification method enables not only useful for imperceptibility when the watermark is insert into an image but also achievable a robustness of watermark detection. A comparison of the proposed method with other methods has been carried out which shown that the proposed method robusts to blockwise memoryless manipulations, and also robust against noise addition.

Analytical Analysis of Image Representation by Their Discrete Wavelet Transform

Year: 2008 Volume: 2 Issue: 9 639 - 644 Pages

Authors:
R. M. Farouk

Abstract: In this paper, we present an analytical analysis of the representation of images as the magnitudes of their transform with the discrete wavelets. Such a representation plays as a model for complex cells in the early stage of visual processing and of high technical usefulness for image understanding, because it makes the representation insensitive to small local shifts. We found that if the signals are band limited and of zero mean, then reconstruction from the magnitudes is unique up to the sign for almost all signals. We also present an iterative reconstruction algorithm which yields very good reconstruction up to the sign minor numerical errors in the very low frequencies.

Classifying Bio-Chip Data using an Ant Colony System Algorithm

Year: 2008 Volume: 2 Issue: 8 2608 - 2612 Pages

Abstract: Bio-chips are used for experiments on genes and contain various information such as genes, samples and so on. The two-dimensional bio-chips, in which one axis represent genes and the other represent samples, are widely being used these days. Instead of experimenting with real genes which cost lots of money and much time to get the results, bio-chips are being used for biological experiments. And extracting data from the bio-chips with high accuracy and finding out the patterns or useful information from such data is very important. Bio-chip analysis systems extract data from various kinds of bio-chips and mine the data in order to get useful information. One of the commonly used methods to mine the data is classification. The algorithm that is used to classify the data can be various depending on the data types or number characteristics and so on. Considering that bio-chip data is extremely large, an algorithm that imitates the ecosystem such as the ant algorithm is suitable to use as an algorithm for classification. This paper focuses on finding the classification rules from the bio-chip data using the Ant Colony algorithm which imitates the ecosystem. The developed system takes in consideration the accuracy of the discovered rules when it applies it to the bio-chip data in order to predict the classes.

Development of Subjective Measures of Interestingness: From Unexpectedness to Shocking

Year: 2007 Volume: 1 Issue: 11 600 - 602 Pages

Abstract: Knowledge Discovery of Databases (KDD) is the process of extracting previously unknown but useful and significant information from large massive volume of databases. Data Mining is a stage in the entire process of KDD which applies an algorithm to extract interesting patterns. Usually, such algorithms generate huge volume of patterns. These patterns have to be evaluated by using interestingness measures to reflect the user requirements. Interestingness is defined in different ways, (i) Objective measures (ii) Subjective measures. Objective measures such as support and confidence extract meaningful patterns based on the structure of the patterns, while subjective measures such as unexpectedness and novelty reflect the user perspective. In this report, we try to brief the more widely spread and successful subjective measures and propose a new subjective measure of interestingness, i.e. shocking.

Keywords:
Shocking rules (SHR).

Cascaded ANN for Evaluation of Frequency and Air-gap Voltage of Self-Excited Induction Generator

Year: 2007 Volume: 1 Issue: 3 410 - 416 Pages

Abstract: Self-Excited Induction Generator (SEIG) builds up voltage while it enters in its magnetic saturation region. Due to non-linear magnetic characteristics, the performance analysis of SEIG involves cumbersome mathematical computations. The dependence of air-gap voltage on saturated magnetizing reactance can only be established at rated frequency by conducting a laboratory test commonly known as synchronous run test. But, there is no laboratory method to determine saturated magnetizing reactance and air-gap voltage of SEIG at varying speed, terminal capacitance and other loading conditions. For overall analysis of SEIG, prior information of magnetizing reactance, generated frequency and air-gap voltage is essentially required. Thus, analytical methods are the only alternative to determine these variables. Non-existence of direct mathematical relationship of these variables for different terminal conditions has forced the researchers to evolve new computational techniques. Artificial Neural Networks (ANNs) are very useful for solution of such complex problems, as they do not require any a priori information about the system. In this paper, an attempt is made to use cascaded neural networks to first determine the generated frequency and magnetizing reactance with varying terminal conditions and then air-gap voltage of SEIG. The results obtained from the ANN model are used to evaluate the overall performance of SEIG and are found to be in good agreement with experimental results. Hence, it is concluded that analysis of SEIG can be carried out effectively using ANNs.

The Index of Sustainable Functionality: An Application for Measuring Sustainability

Year: 2009 Volume: 3 Issue: 4 272 - 278 Pages

Authors:
G.T. Cirella
L. Tao

Abstract: The index of sustainable functionality (ISF) is an adaptive, multi-criteria technique that is used to measure sustainability; it is a concept that can be transposed to many regions throughout the world. An ISF application of the Southern Regional Organisation of Councils (SouthROC) in South East Queensland (SEQ) – the fastest growing region in Australia – indicated over a 25 year period an increase of over 10% level of functionality from 58.0% to 68.3%. The ISF of SouthROC utilised methodologies that derived from an expert panel based approach. The overall results attained an intermediate level of functionality which amounted to related concerns of economic progress and lack of social awareness. Within the region, a solid basis for future testing by way of measured changes and developed trends can be established. In this regard as management tool, the ISF record offers support for regional sustainability practice and decision making alike. This research adaptively analyses sustainability – a concept that is lacking throughout much of the academic literature and any reciprocal experimentation. This lack of knowledge base has been the emphasis of where future sustainability research can grow from and prove useful in rapidly growing regions. It is the intentions of this research to help further develop the notions of index-based quantitative sustainability.

A Study on the Application of TRIZ to CAD/CAM System

Year: 2008 Volume: 2 Issue: 2 320 - 324 Pages

Abstract: This study created new graphical icons and operating functions in a CAD/CAM software system by analyzing icons in some of the popular systems, such as AutoCAD, AlphaCAM, Mastercam and the 1st edition of LiteCAM. These software systems all focused on geometric design and editing, thus how to transmit messages intuitively from icon itself to users is an important function of graphical icons. The primary purpose of this study is to design innovative icons and commands for new software. This study employed the TRIZ method, an innovative design method, to generate new concepts systematically. Through literature review, it then investigated and analyzed the relationship between TRIZ and idea development. Contradiction Matrix and 40 Principles were used to develop an assisting tool suitable for icon design in software development. We first gathered icon samples from the selected CAD/CAM systems. Then grouped these icons by meaningful functions, and compared useful and harmful properties. Finally, we developed new icons for new software systems in order to avoid intellectual property problem.

Keywords:
Icon
TRIZ
CAD/CAM.

Economic Evaluations Using Genetic Algorithms to Determine the Territorial Impact Caused by High Speed Railways

Year: 2012 Volume: 6 Issue: 11 2860 - 2868 Pages

Abstract: The evolution of technology and construction techniques has enabled the upgrading of transport networks. In particular, the high-speed rail networks allow convoys to peak at above 300 km/h. These structures, however, often significantly impact the surrounding environment. Among the effects of greater importance are the ones provoked by the soundwave connected to train transit. The wave propagation affects the quality of life in areas surrounding the tracks, often for several hundred metres. There are substantial damages to properties (buildings and land), in terms of market depreciation. The present study, integrating expertise in acoustics, computering and evaluation fields, outlines a useful model to select project paths so as to minimize the noise impact and reduce the causes of possible litigation. It also facilitates the rational selection of initiatives to contain the environmental damage to the already existing railway tracks. The research is developed with reference to the Italian regulatory framework (usually more stringent than European and international standards) and refers to a case study concerning the high speed network in Italy.

Actionable Rules: Issues and New Directions

Year: 2007 Volume: 1 Issue: 5 1229 - 1232 Pages

Authors:
Harleen Kaur

Abstract: Knowledge Discovery in Databases (KDD) is the process of extracting previously unknown, hidden and interesting patterns from a huge amount of data stored in databases. Data mining is a stage of the KDD process that aims at selecting and applying a particular data mining algorithm to extract an interesting and useful knowledge. It is highly expected that data mining methods will find interesting patterns according to some measures, from databases. It is of vital importance to define good measures of interestingness that would allow the system to discover only the useful patterns. Measures of interestingness are divided into objective and subjective measures. Objective measures are those that depend only on the structure of a pattern and which can be quantified by using statistical methods. While, subjective measures depend only on the subjectivity and understandability of the user who examine the patterns. These subjective measures are further divided into actionable, unexpected and novel. The key issues that faces data mining community is how to make actions on the basis of discovered knowledge. For a pattern to be actionable, the user subjectivity is captured by providing his/her background knowledge about domain. Here, we consider the actionability of the discovered knowledge as a measure of interestingness and raise important issues which need to be addressed to discover actionable knowledge.

Extraction and Characterisation of Protein Fraction from Date Palm Fruit Seeds

Year: 2012 Volume: 6 Issue: 10 869 - 871 Pages

Abstract: Date palm (Phoenix dactylifera L.) seeds are waste streams which are considered a major problem to the food industry. They contain potentially useful protein (10-15% of the whole date-s weight). Global production, industrialisation and utilisation of dates are increasing steadily. The worldwide production of date palm fruit has increased from 1.8 million tons in 1961 to 6.9 million tons in 2005, thus from the global production of dates are almost 800.000 tonnes of date palm seeds are not currently used [1]. The current study was carried out to convert the date palm seeds into useful protein powder. Compositional analysis showed that the seeds were rich in protein and fat 5.64 and 8.14% respectively. We used several laboratory scale methods to extract proteins from seed to produce a high protein powder. These methods included simple acid or alkali extraction, with or without ultrafiltration and phenol trichloroacetic acid with acetone precipitation (Ph/TCA method). The highest protein content powder (68%) was obtained by Ph/TCA method with yield of material (44%) whereas; the use of just alkali extraction gave the lowest protein content of 8%, and a yield of 32%.

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