Abstract: The incorporation of computational fluid dynamics in the design of modern hydraulic turbines appears to be necessary in order to improve their efficiency and cost-effectiveness beyond the traditional design practices. A numerical optimization methodology is developed and applied in the present work to a Turgo water turbine. The fluid is simulated by a Lagrangian mesh-free approach that can provide detailed information on the energy transfer and enhance the understanding of the complex, unsteady flow field, at very small computing cost. The runner blades are initially shaped according to hydrodynamics theory, and parameterized using Bezier polynomials and interpolation techniques. The use of a limited number of free design variables allows for various modifications of the standard blade shape, while stochastic optimization using evolutionary algorithms is implemented to find the best blade that maximizes the attainable hydraulic efficiency of the runner. The obtained optimal runner design achieves considerably higher efficiency than the standard one, and its numerically predicted performance is comparable to a real Turgo turbine, verifying the reliability and the prospects of the new methodology.
Abstract: Information sharing and gathering are important in the rapid advancement era of technology. The existence of WWW has caused rapid growth of information explosion. Readers are overloaded with too many lengthy text documents in which they are more interested in shorter versions. Oil and gas industry could not escape from this predicament. In this paper, we develop an Automated Text Summarization System known as AutoTextSumm to extract the salient points of oil and gas drilling articles by incorporating statistical approach, keywords identification, synonym words and sentence-s position. In this study, we have conducted interviews with Petroleum Engineering experts and English Language experts to identify the list of most commonly used keywords in the oil and gas drilling domain. The system performance of AutoTextSumm is evaluated using the formulae of precision, recall and F-score. Based on the experimental results, AutoTextSumm has produced satisfactory performance with F-score of 0.81.
Abstract: In this paper we propose segmentation approach based
on Vector Quantization technique. Here we have used Kekre-s fast
codebook generation algorithm for segmenting low-altitude aerial
image. This is used as a preprocessing step to form segmented
homogeneous regions. Further to merge adjacent regions color
similarity and volume difference criteria is used. Experiments
performed with real aerial images of varied nature demonstrate that
this approach does not result in over segmentation or under
segmentation. The vector quantization seems to give far better results
as compared to conventional on-the-fly watershed algorithm.
Abstract: Sensitive and predictive DILI (Drug Induced Liver
Injury) biomarkers are needed in drug R&D to improve early
detection of hepatotoxicity. The discovery of DILI biomarkers that
demonstrate the predictive power to identify individuals at risk to
DILI would represent a major advance in the development of
personalized healthcare approaches. In this healthy volunteer
acetaminophen study (4g/day for 7 days, with 3 monitored nontreatment
days before and 4 after), 450 serum samples from 32
subjects were analyzed using protein profiling by antibody
suspension bead arrays. Multiparallel protein profiles were generated
using a DILI target protein array with 300 antibodies, where the
antibodies were selected based on previous literature findings of
putative DILI biomarkers and a screening process using pre dose
samples from the same cohort. Of the 32 subjects, 16 were found to
develop an elevated ALT value (2Xbaseline, responders). Using the
plasma profiling approach together with multivariate statistical
analysis some novel findings linked to lipid metabolism were found
and more important, endogenous protein profiles in baseline samples
(prior to treatment) with predictive power for ALT elevations were
identified.
Abstract: Cloud Computing is an approach that provides computation and storage services on-demand to clients over the network, independent of device and location. In the last few years, cloud computing became a trend in information technology with many companies that transfer their business processes and applications in the cloud. Cloud computing with service oriented architecture has contributed to rapid development of Geographic Information Systems. Open Geospatial Consortium with its standards provides the interfaces for hosted spatial data and GIS functionality to integrated GIS applications. Furthermore, with the enormous processing power, clouds provide efficient environment for data intensive applications that can be performed efficiently, with higher precision, and greater reliability. This paper presents our work on the geospatial data services within the cloud computing environment and its technology. A cloud computing environment with the strengths and weaknesses of the geographic information system will be introduced. The OGC standards that solve our application interoperability are highlighted. Finally, we outline our system architecture with utilities for requesting and invoking our developed data intensive applications as a web service.
Abstract: While service quality is acceptably most valued in the tourism industry, the issue of safety and security plays a key role in sustaining the industry success. Such an issue has been part of Thailand-s tourism development and promotion for several years. Evidently, the Tourist Police Department was set up for this purpose. Its main responsibility is to deal with international tourists- safety and confidence in travelling within Thai territory. However, to strengthen the tourism safety of the country, it is important to better understand international tourists- safety concerns about Thailand. This article seeks to compare international tourists- safety needs and Thai tourist polices- perception towards the tourists- safety concern to determine what measure should be taken to assure the tourist of Thailand-s secure environment. Through the employment of quantitative and qualitative methodological approaches, the tourism safety need of international tourists from Europe, North America and Asia was excavated, how Thai tourist polices and local polices perceived the international tourist-s safety concern was investigated, and opinion and experiences about how the police deal with international tourists- problems in eight touristic areas were also explored. A comparative result reveals a certain degrees of differences in international tourists- safety needs and Thai polices- perception towards their needs. The tourism safety prevention and protection measure and practice are also suggested.
Abstract: Censored Production Rule is an extension of standard
production rule, which is concerned with problems of reasoning with
incomplete information, subject to resource constraints and problem
of reasoning efficiently with exceptions. A CPR has a form: IF A
(Condition) THEN B (Action) UNLESS C (Censor), Where C is the
exception condition. Fuzzy CPR are obtained by augmenting
ordinary fuzzy production rule “If X is A then Y is B with an
exception condition and are written in the form “If X is A then Y is B
Unless Z is C. Such rules are employed in situation in which the
fuzzy conditional statement “If X is A then Y is B" holds frequently
and the exception condition “Z is C" holds rarely. Thus “If X is A
then Y is B" part of the fuzzy CPR express important information
while the unless part acts only as a switch that changes the polarity of
“Y is B" to “Y is not B" when the assertion “Z is C" holds. The
proposed approach is an attempt to discover fuzzy censored
production rules from set of discovered fuzzy if then rules in the
form:
A(X)  B(Y) || C(Z).
Abstract: Battery storage system is emerging as an essential component of hybrid power system based on renewable energy resources such as solar and wind in order to make these sources dispatchable. Accurate modeling of battery storage system is ssential in order to ensure optimal planning of hybrid power systems incorporating battery storage. Majority of the system planning studies involving battery storage assume battery charging efficiency to be constant. However a strong correlation exists between battery charging efficiency and battery state of charge. In this work a Fuzzy logic based model has been presented for determining battery charging efficiency relative to a particular SOC. In order to demonstrate the efficacy of proposed approach, reliability evaluation studies are carried out for a hypothetical autonomous hybrid power system located in Jaisalmer, Rajasthan, India. The impact of considering battery charging efficiency as a function of state of charge is compared against the assumption of fixed battery charging efficiency for three different configurations comprising of wind-storage, solar-storage and wind-solar-storage.
Abstract: Heavy rainfall greatly affects the aerodynamic performance of the aircraft. There are many accidents of aircraft caused by aerodynamic efficiency degradation by heavy rain. In this Paper we have studied the heavy rain effects on the aerodynamic efficiency of NACA 64-210 & NACA 0012 airfoils. For our analysis, CFD method and preprocessing grid generator are used as our main analytical tools, and the simulation of rain is accomplished via two phase flow approach-s Discrete Phase Model (DPM). Raindrops are assumed to be non-interacting, non-deforming, non-evaporating and non-spinning spheres. Both airfoil sections exhibited significant reduction in lift and increase in drag for a given lift condition in simulated rain. The most significant difference between these two airfoils was the sensitivity of the NACA 64-210 to liquid water content (LWC), while NACA 0012 performance losses in the rain environment is not a function of LWC . It is expected that the quantitative information gained in this paper will be useful to the operational airline industry and greater effort such as small scale and full scale flight tests should put in this direction to further improve aviation safety.
Abstract: This research focus on the intrusion detection system (IDS) development which using artificial immune system (AIS) with population based incremental learning (PBIL). AIS have powerful distinguished capability to extirpate antigen when the antigen intrude into human body. The PBIL is based on past learning experience to adjust new learning. Therefore we propose an intrusion detection system call PBIL-AIS which combine two approaches of PBIL and AIS to evolution computing. In AIS part we design three mechanisms such as clonal selection, negative selection and antibody level to intensify AIS performance. In experimental result, our PBIL-AIS IDS can capture high accuracy when an intrusion connection attacks.
Abstract: Over last two decades, due to hostilities of environment
over the internet the concerns about confidentiality of information
have increased at phenomenal rate. Therefore to safeguard the information
from attacks, number of data/information hiding methods have
evolved mostly in spatial and transformation domain.In spatial domain
data hiding techniques,the information is embedded directly on
the image plane itself. In transform domain data hiding techniques the
image is first changed from spatial domain to some other domain and
then the secret information is embedded so that the secret information
remains more secure from any attack. Information hiding algorithms
in time domain or spatial domain have high capacity and relatively
lower robustness. In contrast, the algorithms in transform domain,
such as DCT, DWT have certain robustness against some multimedia
processing.In this work the authors propose a novel steganographic
method for hiding information in the transform domain of the gray
scale image.The proposed approach works by converting the gray
level image in transform domain using discrete integer wavelet
technique through lifting scheme.This approach performs a 2-D
lifting wavelet decomposition through Haar lifted wavelet of the cover
image and computes the approximation coefficients matrix CA and
detail coefficients matrices CH, CV, and CD.Next step is to apply the
PMM technique in those coefficients to form the stego image. The
aim of this paper is to propose a high-capacity image steganography
technique that uses pixel mapping method in integer wavelet domain
with acceptable levels of imperceptibility and distortion in the cover
image and high level of overall security. This solution is independent
of the nature of the data to be hidden and produces a stego image
with minimum degradation.
Abstract: A new approach for protection of power transformer is
presented using a time-frequency transform known as Wavelet transform.
Different operating conditions such as inrush, Normal, load,
External fault and internal fault current are sampled and processed
to obtain wavelet coefficients. Different Operating conditions provide
variation in wavelet coefficients. Features like energy and Standard
deviation are calculated using Parsevals theorem. These features
are used as inputs to PNN (Probabilistic neural network) for fault
classification. The proposed algorithm provides more accurate results
even in the presence of noise inputs and accurately identifies inrush
and fault currents. Overall classification accuracy of the proposed
method is found to be 96.45%. Simulation of the fault (with and
without noise) was done using MATLAB AND SIMULINK software
taking 2 cycles of data window (40 m sec) containing 800 samples.
The algorithm was evaluated by using 10 % Gaussian white noise.
Abstract: Telemedicine is brought to life by contemporary changes of our world and summarizes the entire range of services that are at the crossroad of traditional healthcare and information technology. It is believed that eHealth can help in solving critical issues of rising costs, care for ageing and housebound population, staff shortage. It is a feasible tool to provide routine as well as specialized health service as it has the potential to improve both the access to and the standard of care. eHealth is no more an optional choice. It has already made quite a way but it still remains a fantastic challenge for the future requiring cooperation and coordination at all possible levels. The strategic objectives of this paper are: 1. To start with an attempt to clarify the mass of terms used nowadays; 2. To answer the question “Who needs eHealth"; 3. To focus on the necessity of bridging telemedicine and medical (health) informatics as well as on the dual relationship between them; as well as 4. To underline the need of networking in understanding, developing and implementing eHealth.
Abstract: In this paper a novel approach for generalized image
retrieval based on semantic contents is presented. A combination of
three feature extraction methods namely color, texture, and edge
histogram descriptor. There is a provision to add new features in
future for better retrieval efficiency. Any combination of these
methods, which is more appropriate for the application, can be used
for retrieval. This is provided through User Interface (UI) in the
form of relevance feedback. The image properties analyzed in this
work are by using computer vision and image processing algorithms.
For color the histogram of images are computed, for texture cooccurrence
matrix based entropy, energy, etc, are calculated and for
edge density it is Edge Histogram Descriptor (EHD) that is found.
For retrieval of images, a novel idea is developed based on greedy
strategy to reduce the computational complexity. The entire system
was developed using AForge.Imaging (an open source product),
MATLAB .NET Builder, C#, and Oracle 10g. The system was tested
with Coral Image database containing 1000 natural images and
achieved better results.
Abstract: The Knowledge Management (KM) Criteria is an
essential foundation to evaluate KM outcomes. Different sets of
criteria were developed and tailored by many researchers to
determine the results of KM initiatives. However, literature review
has emphasized on incomplete set of criteria for evaluating KM
outcomes. Hence, this paper tried to address the problem of
determining the criteria for measuring knowledge management
outcomes among different types of Malaysian organizations.
Successively, this paper was assumed to develop widely accepted
criteria to measure success of knowledge management efforts for
Malaysian organizations. Our analysis approach was based on the
ANOVA procedure to compare a set of criteria among different types
of organizations. This set of criteria was exploited from literature
review. It is hoped that this study provides a better picture for
different types of Malaysian organizations to establish a
comprehensive set of criteria due to measure results of KM programs.
Abstract: This paper focuses on issues of engagement by staff in professional development related to the delivery of e-learning. The paper reports on findings drawn from a New Zealand research project which is producing a sector-wide framework for professional development in tertiary e-learning. The research findings indicate that staff engaged in e-learning in tertiary institutions is not making the most effective use of the professional development opportunities available to them; rather they seem to gain their knowledge and support from a variety of informal means. This is despite an emphasis on the provision of professional development opportunities by both Government Policies and Institutions themselves. The conclusion drawn from the findings is that institutional approaches to professional development for e-learning do not yet fully reflect the demands and constraints that working in a digital context impose.
Abstract: Interaction effects of xanthan gum (XG), carboxymethyl
cellulose (CMC), and locust bean gum (LBG) on the flow properties
of oil-in-water emulsions were investigated by a mixture design
experiment. Blends of XG, CMC and LBG were prepared according
to an augmented simplex-centroid mixture design (10 points) and used
at 0.5% (wt/wt) in the emulsion formulations. An appropriate
mathematical model was fitted to express each response as a function
of the proportions of the blend components that are able to
empirically predict the response to any blend of combination of the
components. The synergistic interaction effect of the ternary
XG:CMC:LBG blends at approximately 33-67% XG levels was
shown to be much stronger than that of the binary XG:LBG blend at
50% XG level (p < 0.05). Nevertheless, an antagonistic interaction
effect became significant as CMC level in blends was more than 33%
(p < 0.05). Yield stress and apparent viscosity (at 10 s-1) responses
were successfully fitted with a special quartic model while flow
behaviour index and consistency coefficient were fitted with a full
quartic model (R2
adjusted ≥ 0.90). This study found that a mixture
design approach could serve as a valuable tool in better elucidating
and predicting the interaction effects beyond the conventional twocomponent
blends.
Abstract: In this study, a Loop Back Algorithm for component
connected labeling for detecting objects in a digital image is
presented. The approach is using loop back connected component
labeling algorithm that helps the system to distinguish the object
detected according to their label. Deferent than whole window
scanning technique, this technique reduces the searching time for
locating the object by focusing on the suspected object based on
certain features defined. In this study, the approach was also
implemented for a face detection system. Face detection system is
becoming interesting research since there are many devices or
systems that require detecting the face for certain purposes. The input
can be from still image or videos, therefore the sub process of this
system has to be simple, efficient and accurate to give a good result.
Abstract: In this paper the problem of face recognition under variable illumination conditions is considered. Most of the works in the literature exhibit good performance under strictly controlled acquisition conditions, but the performance drastically drop when changes in pose and illumination occur, so that recently number of approaches have been proposed to deal with such variability. The aim of this work is to introduce an efficient local appearance feature extraction method based steerable pyramid (SP) for face recognition. Local information is extracted from SP sub-bands using LBP(Local binary Pattern). The underlying statistics allow us to reduce the required amount of data to be stored. The experiments carried out on different face databases confirm the effectiveness of the proposed approach.
Abstract: This paper describes a practical approach to design
and develop a hybrid learning with acceleration feedback control
(HLC) scheme for input tracking and end-point vibration suppression
of flexible manipulator systems. Initially, a collocated proportionalderivative
(PD) control scheme using hub-angle and hub-velocity
feedback is developed for control of rigid-body motion of the system.
This is then extended to incorporate a further hybrid control scheme
of the collocated PD control and iterative learning control with
acceleration feedback using genetic algorithms (GAs) to optimize the
learning parameters. Experimental results of the response of the
manipulator with the control schemes are presented in the time and
frequency domains. The performance of the HLC is assessed in terms
of input tracking, level of vibration reduction at resonance modes and
robustness with various payloads.