Abstract: In recent years demolished concrete waste handling and management is the new primary challenging issue faced by the countries all over the world. It is very challenging and hectic problem that has to be tackled in an indigenous manner, it is desirable to completely recycle demolished concrete waste in order to protect natural resources and reduce environmental pollution. In this research paper an experimental study is carried out to investigate the feasibility and recycling of demolished waste concrete for new construction. The present investigation to be focused on recycling demolished waste materials in order to reduce construction cost and resolving housing problems faced by the low income communities of the world. The crushed demolished concrete wastes is segregated by sieving to obtain required sizes of aggregate, several tests were conducted to determine the aggregate properties before recycling it into new concrete. This research shows that the recycled aggregate that are obtained from site make good quality concrete. The compressive strength test results of partial replacement and full recycled aggregate concrete and are found to be higher than the compressive strength of normal concrete with new aggregate.
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: A novel direction-of-arrival (DOA) estimation technique, which uses a conventional multiple signal classification (MUSIC) algorithm with periodic signals, is applied to a single RF-port parasitic array antenna for direction finding. Simulation results show that the proposed method gives high resolution (1 degree) DOA estimation in an uncorrelated signal environment. The novelty lies in that the MUSIC algorithm is applied to a simplified antenna configuration. Only one RF port and one analogue-to-digital converter (ADC) are used in this antenna, which features low DC power consumption, low cost, and ease of fabrication. Modifications to the conventional MUSIC algorithm do not bring much additional complexity. The proposed technique is also free from the negative influence by the mutual coupling between elements. Therefore, the technique has great potential to be implemented into the existing wireless mobile communications systems, especially at the power consumption limited mobile terminals, to provide additional position location (PL) services.
Abstract: In this paper we propose an NLP-based method for
Ontology Population from texts and apply it to semi automatic
instantiate a Generic Knowledge Base (Generic Domain Ontology) in
the risk management domain. The approach is semi-automatic and
uses a domain expert intervention for validation. The proposed
approach relies on a set of Instances Recognition Rules based on
syntactic structures, and on the predicative power of verbs in the
instantiation process. It is not domain dependent since it heavily
relies on linguistic knowledge.
A description of an experiment performed on a part of the
ontology of the PRIMA1 project (supported by the European
community) is given. A first validation of the method is done by
populating this ontology with Chemical Fact Sheets from
Environmental Protection Agency2. The results of this experiment
complete the paper and support the hypothesis that relying on the
predicative power of verbs in the instantiation process improves the
performance.
Abstract: Academia-industry relationship is not like that of
technology donator-acceptor, but is of interactive and collaborative
nature, acknowledging and ensuring mutual respect for each other-s
role and contributions with an eye to attaining the true purpose of
such relationships, namely, bringing about research-outcome
synergy. Indeed, academia-industry interactions are a system that
requires active and collaborative participations of all the
stakeholders.
This paper examines various issues associated with academic
institutions and industry collaboration with special attention to the
nature of resources and potentialities of stakeholders in the context of
knowledge management. This paper also explores the barriers of
academia-industry interaction. It identifies potential areas where
industry-s participation with academia would be most effective for
synergism. Lastly, this paper proposes an integrated model of several
new collaborative approaches that are possible, mainly in the Indian
scenario to strengthen academia-industry interface.
Abstract: Interior brick-infill partitions are usually considered as
non-structural components and only their weight is accounted for in
practical structural design. In this study, their effect on the progressive
collapse resistance of an RC building subjected to sudden column loss
is investigated. Three notional column loss conditions with four
different brick-infill locations are considered. Column-loss response
analyses of the RC building with and without brick infills are carried
out. Analysis results indicate that the collapse resistance is only
slightly influenced by the brick infills due to their brittle failure
characteristic. Even so, they may help to reduce the inelastic
displacement response under column loss. For practical engineering, it
is reasonably conservative to only consider the weight of brick-infill
partitions in the structural analysis.
Abstract: This paper observed the interhemispheric conjugate
auroral activity occurred on 21 September 2009. The GPS derived
ionospheric total electron content (TEC) during a weak substorm
interval recorded at interhemispheric conjugate points at Husafell in
Iceland and Syowa in Antarctica is investigated to look at their
signatures on the auroral features. Selection of all-sky camera (ASC)
images and keogram at Tjörnes and Syowa during the interval
00:47:54 – 00:50:14 UT on 21 September 2009 found that the auroral
activity had exerted their influence on the GPS TEC as a
consequence of varying interplanetary magnetic field (IMF) By
polarity.
Abstract: Spare parts inventory management is one of the major
areas of inventory research. Analysis of recent literature showed that
an approach integrating spare parts classification, demand
forecasting, and stock control policies is essential; however, adapting
this integrated approach is limited. This work presents an integrated
framework for spare part inventory management and an Excel based
application developed for the implementation of the proposed
framework. A multi-criteria analysis has been used for spare
classification. Forecasting of spare parts- intermittent demand has
been incorporated into the application using three different
forecasting models; namely, normal distribution, exponential
smoothing, and Croston method. The application is also capable of
running with different inventory control policies. To illustrate the
performance of the proposed framework and the developed
application; the framework is applied to different items at a service
organization. The results achieved are presented and possible areas
for future work are highlighted.
Abstract: The ability of the brain to organize information and generate the functional structures we use to act, think and communicate, is a common and easily observable natural phenomenon. In object-oriented analysis, these structures are represented by objects. Objects have been extensively studied and documented, but the process that creates them is not understood. In this work, a new class of discrete, deterministic, dissipative, host-guest dynamical systems is introduced. The new systems have extraordinary self-organizing properties. They can host information representing other physical systems and generate the same functional structures as the brain does. A simple mathematical model is proposed. The new systems are easy to simulate by computer, and measurements needed to confirm the assumptions are abundant and readily available. Experimental results presented here confirm the findings. Applications are many, but among the most immediate are object-oriented engineering, image and voice recognition, search engines, and Neuroscience.
Abstract: Five crystal modifications of water insoluble
artesunate were generated by recrystallizing it from various solvents
with improved physicochemical properties. These generated crystal
forms were characterized to select the most potent and soluble form.
SEM of all the forms showed changes in external shape leading them
to be different morphologically. DSC thermograms of Form III and
Form V showed broad endotherm peaks at 83.04oC and 76.96oC prior
to melting fusion of drug respectively. Calculated weight loss in TGA
revealed that Form III and Form V are methanol and acetone solvates
respectively. However, few additional peaks were appeared in XRPD
pattern in these two solvate forms. All forms exhibit exothermic
behavior in buffer and two solvates display maximum ease of
molecular release from the lattice. Methanol and acetone solvates
were found to be most soluble forms and exhibited higher
antimalarial efficacy showing higher survival rate (83.3%) after 30
days.
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: As a simple to method estimate the plant heating energy
capacity of an apartment complex, a new load calculation method has
been proposed. The method which can be called as unit building
method, predicts the heating load of the entire complex instead of
summing up that of each apartment belonging to complex.
Comparison of the unit heating load for various floor sizes between the
present method and conventional approach shows a close agreement
with dynamic load calculation code. Some additional calculations are
performed to demonstrate it-s application examples.
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: This paper focuses on developing an integrated
reliable and sophisticated model for ultra large wind turbines And to
study the performance and analysis of vector control on large wind
turbines. With the advance of power electronics technology, direct
driven multi-pole radial flux PMSG (Permanent Magnet Synchronous
Generator) has proven to be a good choice for wind turbines
manufacturers. To study the wind energy conversion systems, it is
important to develop a wind turbine simulator that is able to produce
realistic and validated conditions that occur in real ultra MW wind
turbines. Three different packages are used to simulate this model,
namely, Turbsim, FAST and Simulink. Turbsim is a Full field wind
simulator developed by National Renewable Energy Laboratory
(NREL). The wind turbine mechanical parts are modeled by FAST
(Fatigue, Aerodynamics, Structures and Turbulence) code which is
also developed by NREL. Simulink is used to model the PMSG, full
scale back to back IGBT converters, and the grid.
Abstract: Describes the current situation of educational Robotics
"the State of the art" its concept, its evolution their niches of
opportunity, academic and business and the importance of education
and academic outreach. It shows that the development of high-tech
automated educational materials influence the teaching-learning
process and that communication between machines and humans is a
reality.
Abstract: The objective of this research was to find the diffusion properties of vehicles on the road by using the V-Sphere Code. The diffusion coefficient and the size of the height of the wake were estimated with the LES option and the third order MUSCL scheme. We evaluated the code with the changes in the moments of Reynolds Stress along the mean streamline. The results show that at the leading part of a bluff body the LES has some advantages over the RNS since the changes in the strain rates are larger for the leading part. We estimated that the diffusion coefficient with the computed Reynolds stress (non-dimensional) was about 0.96 times the mean velocity.
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: In this study, the Multi-Layer Perceptron (MLP)with Back-Propagation learning algorithm are used to classify to effective diagnosis Parkinsons disease(PD).It-s a challenging problem for medical community.Typically characterized by tremor, PD occurs due to the loss of dopamine in the brains thalamic region that results in involuntary or oscillatory movement in the body. A feature selection algorithm along with biomedical test values to diagnose Parkinson disease.Clinical diagnosis is done mostly by doctor-s expertise and experience.But still cases are reported of wrong diagnosis and treatment. Patients are asked to take number of tests for diagnosis.In many cases,not all the tests contribute towards effective diagnosis of a disease.Our work is to classify the presence of Parkinson disease with reduced number of attributes.Original,22 attributes are involved in classify.We use Information Gain to determine the attributes which reduced the number of attributes which is need to be taken from patients.The Artificial neural networks is used to classify the diagnosis of patients.Twenty-Two attributes are reduced to sixteen attributes.The accuracy is in training data set is 82.051% and in the validation data set is 83.333%.
Abstract: Majority of researches conducted on Iranian urban
development plans indicate that they have been almost unsuccessful
in terms of draft, execution and goal achievement. Lack or shortage
of essential statistics and information can be listed as an important
reason of the failure of these plans. Lack of figures and information
has turned into an obvious part of the country-s statistics officials.
This problem has made urban planner themselves to embark on
physical surveys including real estate and land pricing, population
and economic census of the city. Apart from the problems facing
urban developers, the possibility of errors is high in such surveys.
In the present article, applying the interview technique, it has
been mentioned that utilizing multipurpose cadastre system as a land
information system is essential for urban development plans in Iran.
It can minimize or even remove the failures facing urban
development plans.
Abstract: In this paper we use exponential particle swarm
optimization (EPSO) to cluster data. Then we compare between
(EPSO) clustering algorithm which depends on exponential variation
for the inertia weight and particle swarm optimization (PSO)
clustering algorithm which depends on linear inertia weight. This
comparison is evaluated on five data sets. The experimental results
show that EPSO clustering algorithm increases the possibility to find
the optimal positions as it decrease the number of failure. Also show
that (EPSO) clustering algorithm has a smaller quantization error
than (PSO) clustering algorithm, i.e. (EPSO) clustering algorithm
more accurate than (PSO) clustering algorithm.