Abstract: Like any sentient organism, a smart environment
relies first and foremost on sensory data captured from the real
world. The sensory data come from sensor nodes of different
modalities deployed on different locations forming a Wireless Sensor
Network (WSN). Embedding smart sensors in humans has been a
research challenge due to the limitations imposed by these sensors
from computational capabilities to limited power. In this paper, we
first propose a practical WSN application that will enable blind
people to see what their neighboring partners can see. The challenge
is that the actual mapping between the input images to brain pattern
is too complex and not well understood. We also study the
connectivity problem in 3D/2D wireless sensor networks and propose
distributed efficient algorithms to accomplish the required
connectivity of the system. We provide a new connectivity algorithm
CDCA to connect disconnected parts of a network using cooperative
diversity. Through simulations, we analyze the connectivity gains
and energy savings provided by this novel form of cooperative
diversity in WSNs.
Abstract: This paper proposes a new technique based on nonlinear Minmax Detector Based (MDB) filter for image restoration. The aim of image enhancement is to reconstruct the true image from the corrupted image. The process of image acquisition frequently leads to degradation and the quality of the digitized image becomes inferior to the original image. Image degradation can be due to the addition of different types of noise in the original image. Image noise can be modeled of many types and impulse noise is one of them. Impulse noise generates pixels with gray value not consistent with their local neighborhood. It appears as a sprinkle of both light and dark or only light spots in the image. Filtering is a technique for enhancing the image. Linear filter is the filtering in which the value of an output pixel is a linear combination of neighborhood values, which can produce blur in the image. Thus a variety of smoothing techniques have been developed that are non linear. Median filter is the one of the most popular non-linear filter. When considering a small neighborhood it is highly efficient but for large window and in case of high noise it gives rise to more blurring to image. The Centre Weighted Mean (CWM) filter has got a better average performance over the median filter. However the original pixel corrupted and noise reduction is substantial under high noise condition. Hence this technique has also blurring affect on the image. To illustrate the superiority of the proposed approach, the proposed new scheme has been simulated along with the standard ones and various restored performance measures have been compared.
Abstract: In this paper, two versions of an iterative loopless
algorithm for the classical towers of Hanoi problem with O(1) storage complexity and O(2n) time complexity are presented. Based
on this algorithm the number of different moves in each of pegs with its direction is formulated.
Abstract: This paper present the study carried out of accident
analysis, black spot study and to develop accident predictive models
based on the data collected at rural roadway, Federal Route 50 (F050)
Malaysia. The road accident trends and black spot ranking were
established on the F050. The development of the accident prediction
model will concentrate in Parit Raja area from KM 19 to KM 23.
Multiple non-linear regression method was used to relate the discrete
accident data with the road and traffic flow explanatory variable. The
dependent variable was modeled as the number of crashes namely
accident point weighting, however accident point weighting have
rarely been account in the road accident prediction Models. The result
show that, the existing number of major access points, without traffic
light, rise in speed, increasing number of Annual Average Daily
Traffic (AADT), growing number of motorcycle and motorcar and
reducing the time gap are the potential contributors of increment
accident rates on multiple rural roadway.
Abstract: Generalized Center String (GCS) problem are
generalized from Common Approximate Substring problem
and Common substring problems. GCS are known to be
NP-hard allowing the problems lies in the explosion of
potential candidates. Finding longest center string without
concerning the sequence that may not contain any motifs is
not known in advance in any particular biological gene
process. GCS solved by frequent pattern-mining techniques
and known to be fixed parameter tractable based on the
fixed input sequence length and symbol set size. Efficient
method known as Bpriori algorithms can solve GCS with
reasonable time/space complexities. Bpriori 2 and Bpriori
3-2 algorithm are been proposed of any length and any
positions of all their instances in input sequences. In this
paper, we reduced the time/space complexity of Bpriori
algorithm by Constrained Based Frequent Pattern mining
(CBFP) technique which integrates the idea of Constraint
Based Mining and FP-tree mining. CBFP mining technique
solves the GCS problem works for all center string of any
length, but also for the positions of all their mutated copies
of input sequence. CBFP mining technique construct TRIE
like with FP tree to represent the mutated copies of center
string of any length, along with constraints to restraint
growth of the consensus tree. The complexity analysis for
Constrained Based FP mining technique and Bpriori
algorithm is done based on the worst case and average case
approach. Algorithm's correctness compared with the
Bpriori algorithm using artificial data is shown.
Abstract: Using the quantum hydrodynamic (QHD) model for quantum plasma at finite temperature the modulational instability of electron plasma waves is investigated by deriving a nonlinear Schrodinger equation. It was found that the electron degeneracy parameter significantly affects the linear and nonlinear properties of electron plasma waves in quantum plasma.
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: A virtualized and virtual approach is presented on
academically preparing students to successfully engage at a strategic
perspective to understand those concerns and measures that are both
structured and not structured in the area of cyber security and
information assurance. The Master of Science in Cyber Security and
Information Assurance (MSCSIA) is a professional degree for those
who endeavor through technical and managerial measures to ensure
the security, confidentiality, integrity, authenticity, control,
availability and utility of the world-s computing and information
systems infrastructure. The National University Cyber Security and
Information Assurance program is offered as a Master-s degree. The
emphasis of the MSCSIA program uniquely includes hands-on
academic instruction using virtual computers. This past year, 2011,
the NU facility has become fully operational using system
architecture to provide a Virtual Education Laboratory (VEL)
accessible to both onsite and online students. The first student cohort
completed their MSCSIA training this past March 2, 2012 after
fulfilling 12 courses, for a total of 54 units of college credits. The
rapid pace scheduling of one course per month is immensely
challenging, perpetually changing, and virtually multifaceted. This
paper analyses these descriptive terms in consideration of those
globalization penetration breaches as present in today-s world of
cyber security. In addition, we present current NU practices to
mitigate risks.
Abstract: Medical compression bandages are widely used in the
treatment of chronic venous disorder. In order to design effective
compression bandages, researchers have attempted to describe the
interface pressure applied by multi-layer bandages using mathematical
models. This paper reports on the work carried out to
compare and validate the mathematical models used to describe the
interface pressure applied by multi-layer bandages. Both analytical
and experimental results showed that using simple multiplication
of a number of bandage layers with the pressure applied by one
layer of bandage or ignoring the increase in the limb radius due to
former layers of bandage will result in overestimating the pressure.
Experimental results showed that the mathematical models, which
take into consideration the increase in the limb radius due to former
bandage layers, are more accurate than the one which does not.
Abstract: In Virtual organization, Knowledge Discovery (KD)
service contains distributed data resources and computing grid nodes.
Computational grid is integrated with data grid to form Knowledge
Grid, which implements Apriori algorithm for mining association
rule on grid network. This paper describes development of parallel
and distributed version of Apriori algorithm on Globus Toolkit using
Message Passing Interface extended with Grid Services (MPICHG2).
The creation of Knowledge Grid on top of data and
computational grid is to support decision making in real time
applications. In this paper, the case study describes design and
implementation of local and global mining of frequent item sets. The
experiments were conducted on different configurations of grid
network and computation time was recorded for each operation. We
analyzed our result with various grid configurations and it shows
speedup of computation time is almost superlinear.
Abstract: With the proliferation of the mobile device
technologies, mobile learning can be used to complement and
improve traditional learning problems. Both students and teachers
need a proper and handy system to monitor and keep track the
performance of the students. This paper presents an implementation
of M-learning for primary school in Malaysia by using an open
source technology. It focuses on learning mathematics using
handheld devices for primary schools- students aged 11 and 12 years
old. Main users for this system include students, teachers and the
administrator. This application suggests a new mobile learning
environment with mobile graph for tracking the students- progress
and performance. The purpose of this system is not to replace
traditional classroom but to complement the learning process. In a
testing conducted, students who used this system performed better in
their examination.
Abstract: The Wind Turbine Modeling in Wind Energy Conversion System (WECS) using Doubly-Fed Induction Generator (DFIG) PI Controller based design is presented. To study about the variable wind speed. The PI controller performs responding to the dynamic performance. The objective is to study the characteristic of wind turbine and finding the optimum wind speed suitable for wind turbine performance. This system will allow the specification setting (2.5MW). The output active power also corresponding same the input is given. And the reactive power produced by the wind turbine is regulated at 0 Mvar. Variable wind speed is optimum for drive train performance at 12.5 m/s (at maximum power coefficient point) from the simulation of DFIG by Simulink is described.
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: Signature represents an individual characteristic of a
person which can be used for his / her validation. For such application
proper modeling is essential. Here we propose an offline signature
recognition and verification scheme which is based on extraction of
several features including one hybrid set from the input signature
and compare them with the already trained forms. Feature points
are classified using statistical parameters like mean and variance.
The scanned signature is normalized in slant using a very simple
algorithm with an intention to make the system robust which is
found to be very helpful. The slant correction is further aided by the
use of an Artificial Neural Network (ANN). The suggested scheme
discriminates between originals and forged signatures from simple
and random forgeries. The primary objective is to reduce the two
crucial parameters-False Acceptance Rate (FAR) and False Rejection
Rate (FRR) with lesser training time with an intension to make the
system dynamic using a cluster of ANNs forming a multiple classifier
system.
Abstract: Hidden failure in a protection system has been
recognized as one of the main reasons which may cause to a power
system instability leading to a system cascading collapse. This paper
presents a computationally systematic approach used to obtain the
estimated average probability of a system cascading collapse by
considering the effect of probability hidden failure in a protection
system. The estimated average probability of a system cascading
collapse is then used to determine the severe loading condition
contributing to the higher risk of critical system cascading collapse.
This information is essential to the system utility since it will assist
the operator to determine the highest point of increased system
loading condition prior to the event of critical system cascading
collapse.
Abstract: The purposes of this research are 1) to study English language learning strategies used by the fourth-year students majoring in English and Business English, 2) to study the English language learning strategies which have an affect on English learning achievement, and 3) to compare the English language learning strategies used by the students majoring in English and Business English. The population and sampling comprise of 139 university students of the Suan Sunandha Rajabhat University. Research instruments are language learning strategies questionnaire which was constructed by the researcher and improved on by three experts and the transcripts that show the results of English learning achievement. The questionnaire includes 1) Language Practice Strategy 2)Memory Strategy 3) Communication Strategy 4)Making an Intelligent Guess or Compensation Strategy 5) Self-discipline in Learning Management Strategy 6) Affective Strategy 7)Self-Monitoring Strategy 8) Self-studySkill Strategy. Statistics used in the study are mean, standard deviation, T-test and One Way ANOVA, Pearson product moment correlation coefficient and Regression Analysis. The results of the findings reveal that the English language learning strategies most frequently used by the students are affective strategy, making an intelligent guess or compensation strategy, self-studyskill strategy and self-monitoring strategy respectively. The aspect of making an intelligent guess or compensation strategy had the most significant affect on English learning achievement. It is found that the English language learning strategies mostly used by the Business English major students and moderately used by the English major students. Their language practice strategies uses were significantly different at the 0.05 level and their communication strategies uses were significantly different at the 0.01 level. In addition, it is found that the poor students and the fair ones most frequently used affective strategy while the good ones most frequently used making an intelligent guess or compensation strategy. KeywordsEnglish language, language learning strategies, English learning achievement, and students majoring in English, Business English. Pranee Pathomchaiwat is an Assistant Professor in Business English Program, Suan Sunandha Rajabhat University, Bangkok, Thailand (e-mail: [email protected]).
Abstract: In this paper, we study the multi-scenario knapsack problem, a variant of the well-known NP-Hard single knapsack problem. We investigate the use of an adaptive algorithm for solving heuristically the problem. The used method combines two complementary phases: a size reduction phase and a dynamic 2- opt procedure one. First, the reduction phase applies a polynomial reduction strategy; that is used for reducing the size problem. Second, the adaptive search procedure is applied in order to attain a feasible solution Finally, the performances of two versions of the proposed algorithm are evaluated on a set of randomly generated instances.
Abstract: One promising way to achieve low temperature
combustion regime is the use of a large amount of cooled EGR. In
this paper, the effect of injection timing on low temperature
combustion process and emissions were investigated via three
dimensional computational fluid dynamics (CFD) procedures in a DI
diesel engine using high EGR rates. The results show when
increasing EGR from low levels to levels corresponding to reduced
temperature combustion, soot emission after first increasing, is
decreased beyond 40% EGR and get the lowest value at 58% EGR
rate. Soot and NOx emissions are simultaneously decreased at
advanced injection timing before 20.5 ºCA BTDC in conjunction
with 58% cooled EGR rate in compared to baseline case.
Abstract: This paper challenges the relevance of knowledgebased
management research by arguing that the majority of the
literature emphasizes information and knowledge provision instead of
their business usage. For this reason the related processes are
considered valuable and eligible as such, which has led to
overlapping nature of knowledge-based management disciplines. As
a solution, this paper turns the focus on the information usage. Value
of knowledge and respective management tasks are then defined by
the business need and the knowledge-user becomes the main actor.
The paper analyses the prevailing literature streams and recognizes
the need for a more focused and robust understanding of knowledgebased
value creation. The paper contributes by synthetizing the
existing literature and pinpointing the essence of knowledge-based
management disciplines.
Abstract: the elastic scattering of protons, deuterons and 3He on 6Li at different incident energies have been analyzed in the framework of the optical model using ECIS88 as well as SPI GENOA codes. The potential parameters were extracted in the phenomenological treatment of measured by us angular distributions and literature data. A good agreement between theoretical and experimental differential cross sections was obtained in whole angular range. Parameters for real part of potential have been also calculated microscopically with singleand double-folding model for the p and d, 3He scattering, respectively, using DFPOT code. For best agreement with experiment the normalization factor N for the potential depth is obtained in the range of 0.7-0.9.