Abstract: In this article, we introduce a mechanism by which the same concept of differentiated services used in network transmission can be applied to provide quality of service levels to pervasive systems applications. The classical DiffServ model, including marking and classification, assured forwarding, and expedited forwarding, are all utilized to create quality of service guarantees for various pervasive applications requiring different levels of quality of service. Through a collection of various sensors, personal devices, and data sources, the transmission of contextsensitive data can automatically occur within a pervasive system with a given quality of service level. Triggers, initiators, sources, and receivers are four entities labeled in our mechanism. An explanation of the role of each is provided, and how quality of service is guaranteed.
Abstract: We introduce an algorithm based on the
morphological shared-weight neural network. Being nonlinear and
translation-invariant, the MSNN can be used to create better
generalization during face recognition. Feature extraction is
performed on grayscale images using hit-miss transforms that are
independent of gray-level shifts. The output is then learned by
interacting with the classification process. The feature extraction and
classification networks are trained together, allowing the MSNN to
simultaneously learn feature extraction and classification for a face.
For evaluation, we test for robustness under variations in gray levels
and noise while varying the network-s configuration to optimize
recognition efficiency and processing time. Results show that the
MSNN performs better for grayscale image pattern classification
than ordinary neural networks.
Abstract: Three dimensional simulations are carried out to estimate the effect of wind direction, wind speed and geometry on the flow and dispersion of vehicular pollutant in a street canyon. The pollutant sources are motor vehicles passing between the two buildings. Suitable emission factors for petrol and diesel vehicles at varying vehicle speed are used for the estimation of the rate of emission from the streets. The dispersion of automobile pollutant released from the street is simulated by introducing vehicular emission source term as a fixed-flux boundary condition at the ground level over the road. The emission source term is suitably calculated by adopting emission factors from literature for varying conditions of street traffic. It is observed that increase in wind angle disturbs the symmetric pattern of pollution distribution along the street length. The concentration increases in the far end of the street as compared to the near end.
Abstract: This study examined the effects of neuromuscular
training (NT) on limits of stability (LOS) in female individuals.
Twenty female basketball amateurs were assigned into NT
experimental group or control group by volunteer. All the players were
underwent regular basketball practice, 90 minutes, 3 times per week
for 6 weeks, but the NT experimental group underwent extra NT with
plyometric and core training, 50 minutes, 3 times per week for 6 weeks
during this period. Limits of stability (LOS) were evaluated by the
Biodex Balance System. One factor ANCOVA was used to examine
the differences between groups after training. The significant level for
statistic was set at p
Abstract: The nanosized polymeric micelles release the drug
due to acoustic cavitation, which is enhanced in dual frequency
ultrasonic fields. In this study, adult female Balb/C mice were
transplanted with spontaneous breast adenocarcinoma tumors and
were injected with a dose of 1.3 mg/kg doxorubicin in one of three
forms: free doxorubicin, micellar doxorubicin without sonication and
micellar doxorubicin with sonication. To increase cavitation yield,
the tumor region was sonicated with low level dual frequency of 3
MHz and 28 kHz. The animals were sacrificed 24 h after injection,
and their tumor, heart, spleen, liver, kidneys and plasma were
separated and homogenized. The drug content in their tumor, heart,
spleen, liver, kidneys and plasma was determined using tissue
fluorimetry. The results show that in the group that received micellar
doxorubicin with sonication, the drug concentration in the tumor
tissue was nine and three times higher than in the free doxorubicin
group and the micellar doxorubicin without sonication group,
respectively. In the micellar doxorubicin with sonication group, the
drug concentration in other tissues was lower than other groups
(p
Abstract: Knowledge modelling, a main activity for the development of Knowledge Based Systems, have no set standards and are mostly done in an ad hoc way. There is a lack of support for the transition from abstract level to implementation. In this paper, a methodology for the development of the knowledge model, which is inspired by both Software and Knowledge Engineering, is proposed. Use of UML which is the de-facto standard for modelling in the software engineering arena is explored for knowledge modelling. The methodology proposed, is used to develop a knowledge model of a knowledge based system for recommending suitable hotels for tourists visiting Mauritius.
Abstract: The present work analyses different parameters of pressure die casting to minimize the casting defects. Pressure diecasting is usually applied for casting of aluminium alloys. Good surface finish with required tolerances and dimensional accuracy can be achieved by optimization of controllable process parameters such as solidification time, molten temperature, filling time, injection pressure and plunger velocity. Moreover, by selection of optimum process parameters the pressure die casting defects such as porosity, insufficient spread of molten material, flash etc. are also minimized. Therefore, a pressure die casting component, carburetor housing of aluminium alloy (Al2Si2O5) has been considered. The effects of selected process parameters on casting defects and subsequent setting of parameters with the levels have been accomplished by Taguchi-s parameter design approach. The experiments have been performed as per the combination of levels of different process parameters suggested by L18 orthogonal array. Analyses of variance have been performed for mean and signal-to-noise ratio to estimate the percent contribution of different process parameters. Confidence interval has also been estimated for 95% consistency level and three conformational experiments have been performed to validate the optimum level of different parameters. Overall 2.352% reduction in defects has been observed with the help of suggested optimum process parameters.
Abstract: In the past decade, artificial neural networks (ANNs)
have been regarded as an instrument for problem-solving and
decision-making; indeed, they have already done with a substantial
efficiency and effectiveness improvement in industries and businesses.
In this paper, the Back-Propagation neural Networks (BPNs) will be
modulated to demonstrate the performance of the collaborative
forecasting (CF) function of a Collaborative Planning, Forecasting and
Replenishment (CPFR®) system. CPFR functions the balance between
the sufficient product supply and the necessary customer demand in a
Supply and Demand Chain (SDC). Several classical standard BPN will
be grouped, collaborated and exploited for the easy implementation of
the proposed modular ANN framework based on the topology of a
SDC. Each individual BPN is applied as a modular tool to perform the
task of forecasting SKUs (Stock-Keeping Units) levels that are
managed and supervised at a POS (point of sale), a wholesaler, and a
manufacturer in an SDC. The proposed modular BPN-based CF
system will be exemplified and experimentally verified using lots of
datasets of the simulated SDC. The experimental results showed that a
complex CF problem can be divided into a group of simpler
sub-problems based on the single independent trading partners
distributed over SDC, and its SKU forecasting accuracy was satisfied
when the system forecasted values compared to the original simulated
SDC data. The primary task of implementing an autonomous CF
involves the study of supervised ANN learning methodology which
aims at making “knowledgeable" decision for the best SKU sales plan
and stocks management.
Abstract: The Ad Hoc on demand distance vector (AODV) routing protocol is designed for mobile ad hoc networks (MANETs). AODV offers quick adaptation to dynamic link conditions; it is characterized by low memory overhead and low network utilization. The security issues related to the protocol remain challenging for the wireless network designers. Numerous schemes have been proposed for establishing secure communication between end users, these schemes identify that the secure operation of AODV is a bi tier task (routing and secure exchange of information at separate levels). Our endeavor in this paper would focus on achieving the routing and secure data exchange in a single step. This will facilitate the user nodes to perform routing, mutual authentications, generation and secure exchange of session key in one step thus ensuring confidentiality, integrity and authentication of data exchange in a more suitable way.
Abstract: Nagaland, the 16th state of India in order of
statehood, is situated between 25° 6' and 27° 4' latitude north and
between 93º 20' E and 95º 15' E longitude of equator in the North
Eastern part of the India. Endowed with varied topography, soil and
agro climatic conditions it is known for its potentiality to grow all
most all kinds of horticultural crops. Pineapple being grown since
long organically by default is one of the most promising crops of the
state with emphasis being laid for commercialization by the
government of Nagaland. In light of commercialization, globalization
and scope of setting small-scale industries, a research study was
undertaken to examine the socio-economic and personal
characteristics, entrepreneurial characteristics and attitude of the
pineapple growers towards improved package of practices of
pineapple cultivation. The study was conducted in Medziphema
block of Dimapur district of the Nagaland state of India following ex
post facto research design. Ninety pineapple growers were selected
from four different villages of Medziphema block based on
proportionate random selection procedure. Findings of the study
revealed that majority of the respondents had medium level of
entrepreneurial characteristics in terms of knowledge level, risk
orientation, self confidence, management orientation, farm decision
making ability and leadership ability and most of them had
favourable attitude towards improved package of practices of
pineapple cultivation. The variables age, education, farm size, risk
orientation, management orientation and sources of information
utilized were found important to influence the attitude of the
respondents. The study revealed that favourable attitude and
entrepreneurial characteristics of the pineapple cultivators might be
harnessed for increased production of pineapple in the state thereby
bringing socio economic upliftment of the marginal and small-scale
farmers.
Abstract: The association between emotional inhibition strategies linked to depression has been showed inconsistent among studies. Mild emotional inhibition maybe benefit for social interaction, especially for female among East Asian cultures. The present study aimed to examine whether the inhibition–depression relationship is dependent on level of emotion inhibition and gender context, given differing value of suppressing emotional displays. We hypothesized that the negative associations between inhibition and adolescent depression would not directly, in which affected by interaction between emotion inhibition and gender. To test this hypothesis, we asked 309 junior high school students which age range from 12 to14 years old to report on their use of emotion inhibition and depression syndrome. A multiple regressions analysis revealed that significant interaction that gender as a moderator to the relationships between emotion inhibition and adolescent depression. The group with the highest level of depression was girls with high levels of emotion inhibition, whose depression score was higher than that of boys with high levels of emotion inhibition. The result highlights that the importance of context in understanding the inhibition-depression relationship.
Abstract: The successful implementation of Service-Oriented Architecture (SOA) is not confined to Information Technology systems and required changes of the whole enterprise. In order to adapt IT and business, the enterprise requires adequate and measurable methods. The adoption of SOA creates new problem with regard to measuring and analysis the performance. In fact the enterprise should investigate to what extent the development of services will increase the value of business. It is required for every business to measure the extent of SOA adaptation with the goals of enterprise. Moreover, precise performance metrics and their combination with the advanced evaluation methodologies as a solution should be defined. The aim of this paper is to present a systematic methodology for designing a measurement system at the technical and business levels, so that: (1) it will determine measurement metrics precisely (2) the results will be analysed by mapping identified metrics to the measurement tools.
Abstract: Food safety is an important concern for holiday
makers in foreign and unfamiliar tourist destinations. In fact, risk
from food in these tourist destinations has an influence on tourist
perception. This risk can potentially affect physical health and lead to
an inability to pursue planned activities. The objective of this paper
was to compare foreign tourists- demographics including gender, age
and education level, with the level of perceived risk towards food
safety. A total of 222 foreign tourists during their stay at Khao San
Road in Bangkok were used as the sample. Independent- samples ttest,
analysis of variance, and Least Significant Difference or LSD
post hoc test were utilized. The findings revealed that there were few
demographic differences in level of perceived risk among the foreign
tourists. The post hoc test indicated a significant difference among
the old and the young tourists, and between the higher and lower
level of education. Ranks of tourists- perceived risk towards food
safety unveiled some interesting results. Tourists- perceived risk of
food safety in established restaurants can be ranked as i) cleanliness
of dining utensils, ii) sanitation of food preparation area, and iii)
cleanliness of food seasoning and ingredients. Whereas, the tourists-
perceived risk of food safety in street food and drink can be ranked
as i) cleanliness of stalls and pushcarts, ii) cleanliness of food sold,
and iii) personal hygiene of street food hawkers or vendors.
Abstract: The available data on the cross sections of electronimpact
excitation of krypton 5s and 5p configuration levels out of the
ground state are represented in convenient and compact form. The
results are obtained by regression through all known published data
related to this process.
Abstract: Support vector regression (SVR) has been regarded
as a state-of-the-art method for approximation and regression. The
importance of kernel function, which is so-called admissible support
vector kernel (SV kernel) in SVR, has motivated many studies
on its composition. The Gaussian kernel (RBF) is regarded as a
“best" choice of SV kernel used by non-expert in SVR, whereas
there is no evidence, except for its superior performance on some
practical applications, to prove the statement. Its well-known that
reproducing kernel (R.K) is also a SV kernel which possesses many
important properties, e.g. positive definiteness, reproducing property
and composing complex R.K by simpler ones. However, there are a
limited number of R.Ks with explicit forms and consequently few
quantitative comparison studies in practice. In this paper, two R.Ks,
i.e. SV kernels, composed by the sum and product of a translation
invariant kernel in a Sobolev space are proposed. An exploratory
study on the performance of SVR based general R.K is presented
through a systematic comparison to that of RBF using multiple
criteria and synthetic problems. The results show that the R.K is
an equivalent or even better SV kernel than RBF for the problems
with more input variables (more than 5, especially more than 10) and
higher nonlinearity.
Abstract: As in today's semiconductor industries test costs can make up to 50 percent of the total production costs, an efficient test error detection becomes more and more important. In this paper, we present a new machine learning approach to test error detection that should provide a faster recognition of test system faults as well as an improved test error recall. The key idea is to learn a classifier ensemble, detecting typical test error patterns in wafer test results immediately after finishing these tests. Since test error detection has not yet been discussed in the machine learning community, we define central problem-relevant terms and provide an analysis of important domain properties. Finally, we present comparative studies reflecting the failure detection performance of three individual classifiers and three ensemble methods based upon them. As base classifiers we chose a decision tree learner, a support vector machine and a Bayesian network, while the compared ensemble methods were simple and weighted majority vote as well as stacking. For the evaluation, we used cross validation and a specially designed practical simulation. By implementing our approach in a semiconductor test department for the observation of two products, we proofed its practical applicability.
Abstract: The impact of noise upon live quality has become an
important aspect to make both urban and environmental policythroughout
Europe and in Turkey. Concern over the quality of urban
environments, including noise levels and declining quality of green
space, is over the past decade with increasing emphasis on designing
livable and sustainable communities. According to the World Health
Organization, noise pollution is the third most hazardous
environmental type of pollution which proceeded by only air (gas
emission) and water pollution. The research carried out in two
phases, the first stage of the research noise and plant types providing
the suction of noise was evaluated through literature study and at the
second stage, definite types (Juniperus horizontalis L., Spirea
vanhouetti Briot., Cotoneaster dammerii C.K., Berberis thunbergii
D.C., Pyracantha coccinea M. etc.) were selected for the city of
Konya. Trials were conducted on the highway of Konya. The biggest
value of noise reduction was 6.3 dB(A), 4.9 dB(A), 6.2 dB(A) value
with compared to the control which includes the group that formed
by the bushes at the distance of 7m, 11m, 20m from the source and
5m, 9m, 20m of plant width, respectively. In this paper, definitions
regarding to noise and its sources were made and the precautions
were taken against to noise that mentioned earlier with the adverse
effects of noise. Plantation design approaches and suggestions
concerning to the diversity to be used, which are peculiar to roadside,
were developed to discuss the role and the function of plant material
to reduce the noise of the traffic.
Abstract: With increasing complexity in electronic systems
there is a need for system level anomaly detection and fault isolation.
Anomaly detection based on vector similarity to a training set is used
in this paper through two approaches, one the preserves the original
information, Mahalanobis Distance (MD), and the other that
compresses the data into its principal components, Projection Pursuit
Analysis. These methods have been used to detect deviations in
system performance from normal operation and for critical parameter
isolation in multivariate environments. The study evaluates the
detection capability of each approach on a set of test data with known
faults against a baseline set of data representative of such “healthy"
systems.
Abstract: The two-phase flow field and the motion of the free
surface in an oscillating channel are simulated numerically to assess
the methodology for simulating nuclear reacotr thermal hydraulics
under seismic conditions. Two numerical methods are compared: one
is to model the oscillating channel directly using the moving grid of
the Arbitrary Lagrangian-Eulerian method, and the other is to simulate
the effect of channel motion using the oscillating acceleration acting
on the fluid in the stationary channel. The two-phase flow field in the
oscillating channel is simulated using the level set method in both
cases. The calculated results using the oscillating acceleration are
found to coinside with those using the moving grid, and the theoretical
back ground and the limitation of oscillating acceleration are discussed.
It is shown that the change in the interfacial area between liquid and
gas phases under seismic conditions is important for nuclear reactor
thermal hydraulics.
Abstract: An automatic speech recognition system for the
formal Arabic language is needed. The Quran is the most formal
spoken book in Arabic, it is spoken all over the world. In this
research, an automatic speech recognizer for Quranic based speakerindependent
was developed and tested. The system was developed
based on the tri-phone Hidden Markov Model and Maximum
Likelihood Linear Regression (MLLR). The MLLR computes a set
of transformations which reduces the mismatch between an initial
model set and the adaptation data. It uses the regression class tree, as
well as, estimates a set of linear transformations for the mean and
variance parameters of a Gaussian mixture HMM system. The 30th
Chapter of the Quran, with five of the most famous readers of the
Quran, was used for the training and testing of the data. The chapter
includes about 2000 distinct words. The advantages of using the
Quranic verses as the database in this developed recognizer are the
uniqueness of the words and the high level of orderliness between
verses. The level of accuracy from the tested data ranged 68 to 85%.