Abstract: This paper is proposed the dynamic simulation of
small power induction motor based on Mathematical modeling. The
dynamic simulation is one of the key steps in the validation of the
design process of the motor drive systems and it is needed for
eliminating inadvertent design mistakes and the resulting error in the
prototype construction and testing. This paper demonstrates the
simulation of steady-state performance of induction motor by
MATLAB Program Three phase 3 hp induction motor is modeled
and simulated with SIMULINK model.
Abstract: In this paper, we propose APO, a new packet scheduling
scheme with Quality of Service (QoS) support for hybrid of
real and non-real time services in HSDPA networks. The APO
scheduling algorithm is based on the effective channel anticipation
model. In contrast to the traditional schemes, the proposed method is
implemented based on a cyclic non-work-conserving discipline.
Simulation results indicated that proposed scheme has good
capability to maximize the channel usage efficiency in compared to
another exist scheduling methods. Simulation results demonstrate the
effectiveness of the proposed algorithm.
Abstract: This study examined the effects of 8-week Pilates training program on limits of stability (LOS) and abdominal muscle strength in young dancers. Twenty-four female volunteered and randomly assigned as experimental group (EG) or control group (CG). All subjects received the same dance lessons but the EG underwent an extra Pilates mat exercises for 40 minutes, three times a week, for 8 weeks. LOS was evaluated by the Biodex Balance System and the abdominal strength was measured by 30/60 seconds sit-ups test. One factor ANCOVA was used to examine the differences between groups after training. The results showed that the overall LOS scores at levels 2/8 and the 30/60 seconds sit-ups for the EG group pre- and post-training were changed from 22/38 % to 31/51 % and 20/33 times to 24/42 times, respectively. The study demonstrated that 8-week Pilates training can improve the LOS performance and abdominal strength in young dancers.
Abstract: Construction project control attempts to obtain real-time information and effectively enhance dynamic control and management via information sharing and analysis among project participants to eliminate construction conflicts and project delays. However, survey results for Taiwan indicate that construction commercial project management software is not widely accepted for subcontractors and suppliers. To solve the project communications problems among participants, this study presents a novel system called the Construction Dynamic Teams Communication Management (Con-DTCM) system for small-to-medium sized subcontractors and suppliers in Taiwanese Construction industry, and demonstrates that the Con-DTCM system responds to the most recent project information efficiently and enhances management of project teams (general contractor, suppliers and subcontractors) through web-based environment. Web-based technology effectively enhances information sharing during construction project management, and generates cost savings via the Internet. The main unique characteristic of the proposed Con-DTCM system is extremely user friendly and easily design compared with current commercial project management applications. The Con-DTCM system is applied to a case study of construction of a building project in Taiwan to confirm the proposed methodology and demonstrate the effectiveness of information sharing during the construction phase. The advantages of the Con-DTCM system are in improving project control and management efficiency for general contractors, and in providing dynamic project tracking and management, which enables subcontractors and suppliers to acquire the most recent project-related information. Furthermore, this study presents and implements a generic system architecture.
Abstract: Most integrated inertial navigation systems (INS) and
global positioning systems (GPS) have been implemented using the
Kalman filtering technique with its drawbacks related to the need for
predefined INS error model and observability of at least four
satellites. Most recently, a method using a hybrid-adaptive network
based fuzzy inference system (ANFIS) has been proposed which is
trained during the availability of GPS signal to map the error
between the GPS and the INS. Then it will be used to predict the
error of the INS position components during GPS signal blockage.
This paper introduces a genetic optimization algorithm that is used to
update the ANFIS parameters with respect to the INS/GPS error
function used as the objective function to be minimized. The results
demonstrate the advantages of the genetically optimized ANFIS for
INS/GPS integration in comparison with conventional ANFIS
specially in the cases of satellites- outages. Coping with this problem
plays an important role in assessment of the fusion approach in land
navigation.
Abstract: Automated discovery of Rule is, due to its applicability, one of the most fundamental and important method in KDD. It has been an active research area in the recent past. Hierarchical representation allows us to easily manage the complexity of knowledge, to view the knowledge at different levels of details, and to focus our attention on the interesting aspects only. One of such efficient and easy to understand systems is Hierarchical Production rule (HPRs) system. A HPR, a standard production rule augmented with generality and specificity information, is of the following form: Decision If < condition> Generality Specificity . HPRs systems are capable of handling taxonomical structures inherent in the knowledge about the real world. This paper focuses on the issue of mining Quantified rules with crisp hierarchical structure using Genetic Programming (GP) approach to knowledge discovery. The post-processing scheme presented in this work uses Quantified production rules as initial individuals of GP and discovers hierarchical structure. In proposed approach rules are quantified by using Dempster Shafer theory. Suitable genetic operators are proposed for the suggested encoding. Based on the Subsumption Matrix(SM), an appropriate fitness function is suggested. Finally, Quantified Hierarchical Production Rules (HPRs) are generated from the discovered hierarchy, using Dempster Shafer theory. Experimental results are presented to demonstrate the performance of the proposed algorithm.
Abstract: Broccoli has been widely recognized as a wealthy
vegetable which contains multiple nutrients with potent anti-cancer
properties. Lamb’s lettuce has been used as food for many centuries
but only recently became commercially available and literature is
therefore exiguous concerning these vegetables. The aim of this work
was to evaluate the influence of the extraction conditions on the yield
of phenolic compounds and the corresponding antioxidant capacity of
broccoli and lamb’s lettuce. The results indicate that lamb’s lettuce,
compared to broccoli, contains simultaneously a large amount of total
polyphenols as well as high antioxidant activity. It is clearly
demonstrated that extraction solvent significantly influences the
antioxidant activity. Methanol is the solvent that can globally
maximize the antioxidant extraction yield. The results presented
herein prove lamb’s lettuce as a very interesting source of
polyphenols, and thus a potential health-promoting food.
Abstract: For scores of years now, several microfinance
organizations, non governmental organizations and other welfare
organizations have, with a view to aiding the progress of
communities rooted in poverty have been focusing on creating
microentrepreneurs, besides taking several other measures. In recent
times, business corporations have joined forces to combat poverty by
taking up microenterprise development. Hindustan Unilever Limited
(HUL), the Indian subsidiary of Unilever Limited exemplifies this
through its Project Shakti. The company through the Project creates
rural women entrepreneurs by making them direct to home sales
distributors of its products in villages that have thus far been ignored
by multinational corporations. The members participating in Project
Shakti are largely self help group members. The paper focuses on
assessing the impact made by the company on the members engaged
in Project Shakti. The analysis involves use of quantitative methods
to study the effect of Project Shakti on those self help group
members engaged in Project Shakti and those not engaged with
Project Shakti. Path analysis has been used to study the impact made
on those members engaged in Project Shakti. Significant differences
were observed on fronts of entrepreneurial development, economic
empowerment and social empowerment between members associated
with Project Shakti and those not associated with Project Shakti.
Path analysis demonstrated that involvement in Project Shakti led to
entrepreneurial development resulting in economic empowerment
that in turn led to social empowerment and that these three elements
independently induced a feeling of privilege in the women for being
associated with the Project.
Abstract: Self-organizing map (SOM) is a well known data reduction technique used in data mining. Data visualization can reveal structure in data sets that is otherwise hard to detect from raw data alone. However, interpretation through visual inspection is prone to errors and can be very tedious. There are several techniques for the automatic detection of clusters of code vectors found by SOMs, but they generally do not take into account the distribution of code vectors; this may lead to unsatisfactory clustering and poor definition of cluster boundaries, particularly where the density of data points is low. In this paper, we propose the use of a generic particle swarm optimization (PSO) algorithm for finding cluster boundaries directly from the code vectors obtained from SOMs. The application of our method to unlabeled call data for a mobile phone operator demonstrates its feasibility. PSO algorithm utilizes U-matrix of SOMs to determine cluster boundaries; the results of this novel automatic method correspond well to boundary detection through visual inspection of code vectors and k-means algorithm.
Abstract: In this paper we present a novel approach for density estimation. The proposed approach is based on using the logistic regression model to get initial density estimation for the given empirical density. The empirical data does not exactly follow the logistic regression model, so, there will be a deviation between the empirical density and the density estimated using logistic regression model. This deviation may be positive and/or negative. In this paper we use a linear combination of Gaussian (LCG) with positive and negative components as a model for this deviation. Also, we will use the expectation maximization (EM) algorithm to estimate the parameters of LCG. Experiments on real images demonstrate the accuracy of our approach.
Abstract: The aim of this study was to develop a dynamic cardiac phantom for quality control in myocardial scintigraphy. The dynamic heart phantom constructed only contained the left ventricle, made of elastic material (latex), comprising two cavities: one internal and one external. The data showed a non-significant variation in the values of left ventricular ejection fraction (LVEF) obtained by varying the heart rate. It was also possible to evaluate the ejection fraction (LVEF) through different arrays of image acquisition and to perform an intercomparison of LVEF by two different scintillation cameras. The results of the quality control tests were satisfactory, showing that they can be used as parameters in future assessments. The new dynamic heart phantom was demonstrated to be effective for use in LVEF measurements. Therefore, the new heart simulator is useful for the quality control of scintigraphic cameras.
Abstract: Embedded hardware simulator is a valuable computeraided
tool for embedded application development. This paper focuses
on the ARM926EJ-S MMU, builds state transition models and
formally verifies critical properties for the models. The state transition
models include loading instruction model, reading data model, and
writing data model. The properties of the models are described by
CTL specification language, and they are verified in VIS. The results
obtained in VIS demonstrate that the critical properties of MMU are
satisfied in the state transition models. The correct models can be
used to implement the MMU component in our simulator. In the
end of this paper, the experimental results show that the MMU can
successfully accomplish memory access requests from CPU.
Abstract: This work was to study batch biosorption of Pb(II)
ions from aqueous solution by Luffa charcoal. The effect of operating
parameters such as adsorption contact time, initial pH solution and
different initial Pb(II) concentration on the sorption of Pb(II) were
investigated. The results showed that the adsorption of Pb(II) ions
was initially rapid and the equilibrium time was 10 h. Adsorption
kinetics of Pb(II) ions onto Luffa charcoal could be best described by
the pseudo-second order model. At pH 5.0 was favorable for the
adsorption and removal of Pb(II) ions. Freundlich adsorption
isotherm model was better fitted for the adsorption of Pb(II) ions than
Langmuir and Timkin isotherms, respectively. The highest monolayer
adsorption capacity obtained from Langmuir isotherm model was
51.02 mg/g. This study demonstrated that Luffa charcoal could be
used for the removal of Pb(II) ions in water treatment.
Abstract: The paper proposes a unified model for multimedia data retrieval which includes data representatives, content representatives, index structure, and search algorithms. The multimedia data are defined as k-dimensional signals indexed in a multidimensional k-tree structure. The benefits of using the k-tree unified model were demonstrated by running the data retrieval application on a six networked nodes test bed cluster. The tests were performed with two retrieval algorithms, one that allows parallel searching using a single feature, the second that performs a weighted cascade search for multiple features querying. The experiments show a significant reduction of retrieval time while maintaining the quality of results.
Abstract: Using maximal consistent blocks of tolerance relation
on the universe in incomplete decision table, the concepts of join block
and meet block are introduced and studied. Including tolerance class,
other blocks such as tolerant kernel and compatible kernel of an object
are also discussed at the same time. Upper and lower approximations
based on those blocks are also defined. Default definite decision rules
acquired from incomplete decision table are proposed in the paper. An
incremental algorithm to update default definite decision rules is
suggested for effective mining tasks from incomplete decision table
into which data is appended. Through an example, we demonstrate
how default definite decision rules based on maximal consistent
blocks, join blocks and meet blocks are acquired and how optimization
is done in support of discernibility matrix and discernibility function
in the incomplete decision table.
Abstract: Duplicated region detection is a technical method to
expose copy-paste forgeries on digital images. Copy-paste is one
of the common types of forgeries to clone portion of an image
in order to conceal or duplicate special object. In this type of
forgery detection, extracting robust block feature and also high
time complexity of matching step are two main open problems.
This paper concentrates on computational time and proposes a local
block matching algorithm based on block clustering to enhance time
complexity. Time complexity of the proposed algorithm is formulated
and effects of two parameter, block size and number of cluster, on
efficiency of this algorithm are considered. The experimental results
and mathematical analysis demonstrate this algorithm is more costeffective
than lexicographically algorithms in time complexity issue
when the image is complex.
Abstract: In this paper an algorithm based on the adaptive
neuro-fuzzy controller is provided to enhance the tipover stability of
mobile manipulators when they are subjected to predefined
trajectories for the end-effector and the vehicle. The controller
creates proper configurations for the manipulator to prevent the robot
from being overturned. The optimal configuration and thus the most
favorable control are obtained through soft computing approaches
including a combination of genetic algorithm, neural networks, and
fuzzy logic. The proposed algorithm, in this paper, is that a look-up
table is designed by employing the obtained values from the genetic
algorithm in order to minimize the performance index and by using
this data base, rule bases are designed for the ANFIS controller and
will be exerted on the actuators to enhance the tipover stability of the
mobile manipulator. A numerical example is presented to
demonstrate the effectiveness of the proposed algorithm.
Abstract: One of the major challenges in the Information
Retrieval field is handling the massive amount of information
available to Internet users. Existing ranking techniques and strategies
that govern the retrieval process fall short of expected accuracy.
Often relevant documents are buried deep in the list of documents
returned by the search engine. In order to improve retrieval accuracy
we examine the issue of language effect on the retrieval process.
Then, we propose a solution for a more biased, user-centric relevance
for retrieved data. The results demonstrate that using indices based
on variations of the same language enhances the accuracy of search
engines for individual users.
Abstract: This survey of recent literature examines the link between growth and poverty. It is widely accepted that economic growth is a necessary condition for sustainable poverty reduction. But it is the fact that the economic growth of some countries has been pro-poor while others not. Some factors such as labor market, policies and demographic factors may lead to a weak relationship between economic performance and poverty rate. In this sense pro-growth policies should be pro-poor to increase the poverty alleviation effects of the growth. The purpose of this study is to review the recent studies on the effects of macroeconomic policies on poverty and inequality and to review the poverty analyses which examine the relationship between growth, poverty and inequality. Also this study provides some facts about the relationship between economic growth, inequality and poverty from Turkey. Keywordseconomic growth, inequality, macroeconomic policy, poverty
Abstract: A considerable amount of energy is consumed during
transmission and reception of messages in a wireless mesh network
(WMN). Reducing per-node transmission power would greatly
increase the network lifetime via power conservation in addition to
increasing the network capacity via better spatial bandwidth reuse. In
this work, the problem of topology control in a hybrid WMN of
heterogeneous wireless devices with varying maximum transmission
ranges is considered. A localized distributed topology control
algorithm is presented which calculates the optimal transmission
power so that (1) network connectivity is maintained (2) node
transmission power is reduced to cover only the nearest neighbours
(3) networks lifetime is extended. Simulations and analysis of results
are carried out in the NS-2 environment to demonstrate the
correctness and effectiveness of the proposed algorithm.