Abstract: The aim of this paper is to present a comparative
study on two different methods for the evaluation of the equilibrium
point of a ship, core issue for designing an On Board Stability System
(OBSS) module that, starting from geometry information of a ship
hull, described by a discrete model in a standard format, and the
distribution of all weights onboard calculates the ship floating
conditions (in draught, heel and trim).
Abstract: Recently, some convergent results of the generalized AOR iterative (GAOR) method for solving linear systems with strictly diagonally dominant matrices are presented in [Darvishi, M.T., Hessari, P.: On convergence of the generalized AOR method for linear systems with diagonally dominant cofficient matrices. Appl. Math. Comput. 176, 128-133 (2006)] and [Tian, G.X., Huang, T.Z., Cui, S.Y.: Convergence of generalized AOR iterative method for linear systems with strictly diagonally dominant cofficient matrices. J. Comp. Appl. Math. 213, 240-247 (2008)]. In this paper, we give the convergence of the GAOR method for linear systems with strictly doubly diagonally dominant matrix, which improves these corresponding results.
Abstract: This research work takes a different approach in
the discussion of urban form impacts on transport planning and
auto dependency. Concentrated density represented by effective
density explains auto dependency better than the conventional
density and it is proved to be a realistic density representative for
the urban transportation analysis. Model analysis reveals that
effective density is influenced by the shopping accessibility
index as well as job density factor. It is also combined with the
job access variable to classify four levels of Transport Activity
Centers (TACs) in Okinawa, Japan. Trip attraction capacity and
levels of the newly classified TACs was found agreeable with the
amount of daily trips attracted to each center. The trip attraction
data set was drawn from a 2007 Okinawa personal trip survey.
This research suggests a planning methodology which guides
logical transport supply routes and concentrated local
development schemes.
Abstract: The purpose of this study was to investigate the
relationships among students- process of study, creative self-efficacy
and creativity while attending college. A total of 60 students enrolled
in Hsiuping Institute of Technology in central Taiwan were selected as
samples for the study. The instruments for this study included three
questionnaires to explore the aforesaid aspects.
This researchers tested creative self-efficacy and process of study,
and creativity with Pearson correlation and hierarchical regression
analyses. The major findings of this research are (1) the process of
study had direct positive predictability on creativity, and (2) the
relationship between process of study and creativity is partially
mediated by creative self-efficacy.
Abstract: This paper investigates the performance of a speech
recognizer in an interactive voice response system for various coded
speech signals, coded by using a vector quantization technique namely
Multi Switched Split Vector Quantization Technique. The process of
recognizing the coded output can be used in Voice banking application.
The recognition technique used for the recognition of the coded speech
signals is the Hidden Markov Model technique. The spectral distortion
performance, computational complexity, and memory requirements of
Multi Switched Split Vector Quantization Technique and the
performance of the speech recognizer at various bit rates have been
computed. From results it is found that the speech recognizer is
showing better performance at 24 bits/frame and it is found that the
percentage of recognition is being varied from 100% to 93.33% for
various bit rates.
Abstract: Let p be a prime number, Fpbe a finite field and let Qpdenote the set of quadratic residues in Fp. In the first section we givesome notations and preliminaries from elliptic curves. In the secondsection, we consider some properties of rational points on ellipticcurves Ep,b: y2= x3+ b2 over Fp, where b ∈ F*p. Recall that theorder of Ep,bover Fpis p + 1 if p ≡ 5(mod 6). We generalize thisresult to any field Fnp for an integer n≥ 2. Further we obtain someresults concerning the sum Σ[x]Ep,b(Fp) and Σ[y]Ep,b(Fp), thesum of x- and y- coordinates of all points (x, y) on Ep,b, and alsothe the sum Σ(x,0)Ep,b(Fp), the sum of points (x, 0) on Ep,b.
Abstract: This report shows the performance of composite
biodegradable film from chitosan, starch and sawdust fiber. The main
objectives of this research are to fabricate and characterize composite
biodegradable film in terms of morphology and physical properties.
The film was prepared by casting method. Sawdust fiber was used as
reinforcing agent and starch as polymer matrix in the casting
solution. The morphology of the film was characterized using atomic
force microscope (AFM). The result showed that the film has
smooth structure. Chemical composition of the film was investigated
using Fourier transform infrared (FTIR) where the result revealed
present of starch in the film. The thermal properties were
characterized using thermal gravimetric analyzer (TGA) and
differential scanning calorimetric (DSC) where the results showed
that the film has small difference in melting and degradation
temperature.
Abstract: In order to reduce cost, increase quality, and for
timely supplying production systems has considerably taken the
advantages of supply chain management and these advantages are
also competitive. Selection of appropriate supplier has an important
role in improvement and efficiency of systems.
The models of supplier selection which have already been used by
researchers have considered selection one or more suppliers from
potential suppliers but in this paper selecting one supplier as partner
from one supplier that have minimum one period supplying to buyer
is considered.
This paper presents a conceptual model for partner selection and
application of Degree of Adoptive (DOA) model for final selection.
The attributes weight in this model is prepared through AHP
model. After making the descriptive model, determining the
attributes and measuring the parameters of the adaptive is examined
in an auto industry of Iran(Zagross Khodro co.) and results are
presented.
Abstract: In this research work, investigations are carried out on
Continuous Wave (CW) Nd:YAG laser welding system after
preliminary experimentation to understand the influencing parameters
associated with laser welding of AISI 304. The experimental
procedure involves a series of laser welding trials on AISI 304
stainless steel sheets with various combinations of process parameters
like beam power, beam incident angle and beam incident angle. An
industrial 2 kW CW Nd:YAG laser system, available at Welding
Research Institute (WRI), BHEL Tiruchirappalli, is used for
conducting the welding trials for this research. After proper tuning of
laser beam, laser welding experiments are conducted on AISI 304
grade sheets to evaluate the influence of various input parameters on
weld bead geometry i.e. bead width (BW) and depth of penetration
(DOP). From the laser welding results, it is noticed that the beam
power and welding speed are the two influencing parameters on
depth and width of the bead. Three dimensional finite element
simulation of high density heat source have been performed for laser
welding technique using finite element code ANSYS for predicting
the temperature profile of laser beam heat source on AISI 304
stainless steel sheets. The temperature dependent material properties
for AISI 304 stainless steel are taken into account in the simulation,
which has a great influence in computing the temperature profiles.
The latent heat of fusion is considered by the thermal enthalpy of
material for calculation of phase transition problem. A Gaussian
distribution of heat flux using a moving heat source with a conical
shape is used for analyzing the temperature profiles. Experimental
and simulated values for weld bead profiles are analyzed for stainless
steel material for different beam power, welding speed and beam
incident angle. The results obtained from the simulation are
compared with those from the experimental data and it is observed
that the results of numerical analysis (FEM) are in good agreement
with experimental results, with an overall percentage of error
estimated to be within ±6%.
Abstract: Biomass is becoming a large renewable resource for
power generation; it is involved in higher frequency in
environmentally clean processes, and even it is used for biofuels
preparation. On the other hand, hydrogen – other energy source – can
be produced in a variety of methods including gasification of
biomass. In this study, the production of hydrogen by gasification of
biomass waste is examined. This work explores the production of a
gaseous mixture with high power potential from Amazonas´ specie
known as copoazu, using a counter-flow fixed-bed bioreactor.
Abstract: In this paper the development of a heat exchanger as a
pilot plant for educational purpose is discussed and the use of neural
network for controlling the process is being presented. The aim of the
study is to highlight the need of a specific Pseudo Random Binary
Sequence (PRBS) to excite a process under control. As the neural
network is a data driven technique, the method for data generation
plays an important role. In light of this a careful experimentation
procedure for data generation was crucial task. Heat exchange is a
complex process, which has a capacity and a time lag as process
elements. The proposed system is a typical pipe-in- pipe type heat
exchanger. The complexity of the system demands careful selection,
proper installation and commissioning. The temperature, flow, and
pressure sensors play a vital role in the control performance. The
final control element used is a pneumatically operated control valve.
While carrying out the experimentation on heat exchanger a welldrafted
procedure is followed giving utmost attention towards safety
of the system. The results obtained are encouraging and revealing
the fact that if the process details are known completely as far as
process parameters are concerned and utilities are well stabilized then
feedback systems are suitable, whereas neural network control
paradigm is useful for the processes with nonlinearity and less
knowledge about process. The implementation of NN control
reinforces the concepts of process control and NN control paradigm.
The result also underlined the importance of excitation signal
typically for that process. Data acquisition, processing, and
presentation in a typical format are the most important parameters
while validating the results.
Abstract: There are four challenges of sustainable development
and in corporate level sustainability management-s role is to answer
for ecological sustainability challenge, social sustainability challenge,
economic sustainability challenges to environment and social
management and integration challenge of corporate sustainable
challenges by the help of different concepts, methods, instruments,
which are in the toolbox of sustainability management. These
instruments, concepts have different relevance in these challenges,
and according to different literatures environmental management is
outside of social and integration challenge. Main aim of this paper is
to represent the answer for the question that: is it true that social and
integration point of view is outside of the concept environmental
accounting? Using literature review and primer research at the end of
the paper the answer will be confirmed.
Abstract: Nowadays, several techniques such as; Fuzzy
Inference System (FIS) and Neural Network (NN) are employed for
developing of the predictive models to estimate parameters of water
quality. The main objective of this study is to compare between the
predictive ability of the Adaptive Neuro-Fuzzy Inference System
(ANFIS) model and Artificial Neural Network (ANN) model to
estimate the Biochemical Oxygen Demand (BOD) on data from 11
sampling sites of Saen Saep canal in Bangkok, Thailand. The data is
obtained from the Department of Drainage and Sewerage, Bangkok
Metropolitan Administration, during 2004-2011. The five parameters
of water quality namely Dissolved Oxygen (DO), Chemical Oxygen
Demand (COD), Ammonia Nitrogen (NH3N), Nitrate Nitrogen
(NO3N), and Total Coliform bacteria (T-coliform) are used as the
input of the models. These water quality indices affect the
biochemical oxygen demand. The experimental results indicate that
the ANN model provides a higher correlation coefficient (R=0.73)
and a lower root mean square error (RMSE=4.53) than the
corresponding ANFIS model.
Abstract: The development of renewable energies - particularly energy from wind, water, solar power and biomass - is a central aim of the European Commission's energy policy. There are several reasons for this choice: renewable energies are sustainable, nonpolluting, widely available and clean. Increasing the share of renewable energy in the energy balance enhances sustainability. It also helps to improve the security of energy supply by reducing the Community's growing dependence on imported energy sources.In this paper it was studied the possibility to realize three photovoltaic systems in the Italian Natural Park “Gola della Rossa e di Frasassi". The first photovoltaic system is a grid-connected system for Services and Documentation Center of Castelletta with a nominal power of about 6 kWp. The second photovoltaic system is a grid-connected integrated system on the ticket office-s roof with a nominal power of about 4 kWp. The third project is set up by five grid-connected systems integrated on the roofs of the bungalows in Natural Park-s tourist camping with a nominal power of about 10 kWp. The electricity which is generated by all these plants is purchased according to the Italian program called “Conto Energia". Economical analysis and the amount of the avoided CO2 emissions are elaborated for these photovoltaic systems.
Abstract: Bidding is a very important business function to find
latent contractors of construction projects. Moreover, bid markup is
one of the most important decisions for a bidder to gain a reasonable
profit. Since the bidding system is a complex adaptive system, bidding
agent need a learning process to get more valuable knowledge for a bid,
especially from past public bidding information. In this paper, we
proposed an iterative agent leaning model for bidders to make markup
decisions. A classifier for public bidding information named PIBS is
developed to make full use of history data for classifying new bidding
information. The simulation and experimental study is performed to
show the validity of the proposed classifier. Some factors that affect
the validity of PIBS are also analyzed at the end of this work.
Abstract: In this paper, we observe that developed countries are generally equipped with innovation capabilities and produce major chunk of the world-s knowledge and technology. The contribution of developing countries, on the other hand, is insignificant, and most of them far behind the global technological front. More specifically, we empirically observe that the developing world neither contributes substantially to the world-s scientific publications nor to the R&D activities. They also have lesser “absorptive capacity" and “technological capability", and their “innovation systems" are plagued with many problems. Finally, we argue that these countries can break the shackles and improve their innovation capabilities by pursuing genuine innovation policies on long-term basis with honesty and commitment.
Abstract: This research is part of a broad program aimed at
advancing the science and technology involved in the rescue and
rehabilitation of oiled wildlife. One aspect of this research involves
the use of oil-sequestering magnetic particles for the removal of
contaminants from plumage – so-called “magnetic cleansing". This
treatment offers a number of advantages over conventional
detergent-based methods including portability - which offers the
possibility of providing a “quick clean" to the animal upon first
encounter in the field. This could be particularly advantageous
when the contaminant is toxic and/or corrosive and/or where there
is a delay in transporting the victim to a treatment centre. The
method could also be useful as part of a stabilization protocol when
large numbers of affected animals are awaiting treatment. This
presentation describes the design, development and testing of a
prototype field kit for providing a “quick clean" to contaminated
wildlife in the field.
Abstract: The cyberspace is an instrument through which
internet users could get new experiences. It could contribute to foster
one-s own growth, widening cognitive, creative and communicative
abilities and promoting relationships. In the cyberspace, in fact, it is
possible to create virtual learning communities where internet users
improve their interpersonal sphere, knowledge and skills. The main
element of e-learning is the establishment of online relationships, that
are often collaborative.
Abstract: Understanding proteins functions is a major goal in
the post-genomic era. Proteins usually work in context of other
proteins and rarely function alone. Therefore, it is highly relevant to
study the interaction partners of a protein in order to understand its
function. Machine learning techniques have been widely applied to
predict protein-protein interactions. Kernel functions play an
important role for a successful machine learning technique. Choosing
the appropriate kernel function can lead to a better accuracy in a
binary classifier such as the support vector machines. In this paper,
we describe a Bayesian kernel for the support vector machine to
predict protein-protein interactions. The use of Bayesian kernel can
improve the classifier performance by incorporating the probability
characteristic of the available experimental protein-protein
interactions data that were compiled from different sources. In
addition, the probabilistic output from the Bayesian kernel can assist
biologists to conduct more research on the highly predicted
interactions. The results show that the accuracy of the classifier has
been improved using the Bayesian kernel compared to the standard
SVM kernels. These results imply that protein-protein interaction can
be predicted using Bayesian kernel with better accuracy compared to
the standard SVM kernels.
Abstract: This paper presents methodologies for developing an
intelligent CAD system assisting in analysis and design of
reconfigurable special machines. It describes a procedure for
determining feasibility of utilizing these machines for a given part
and presents a model for developing an intelligent CAD system. The
system analyzes geometrical and topological information of the given
part to determine possibility of the part being produced by
reconfigurable special machines from a technical point of view. Also
feasibility of the process from a economical point of view is
analyzed. Then the system determines proper positioning of the part
considering details of machining features and operations needed.
This involves determination of operation types, cutting tools and the
number of working stations needed. Upon completion of this stage
the overall layout of the machine and machining equipment required
are determined.