Abstract: In view of geological origin, formation of the shallow
gas reservoir of the Hangzhou Bay, northern Zhejiang Province,
eastern China, and original occurrence characteristics of the gassy
sand are analyzed. Generally, gassy sand in scale gas reservoirs is in
the state of residual moisture content and the approximate scope of
initial matric suction of sand ranges about from 0kPa to100kPa.
Results based on GDS triaxial tests show that the classical shear
strength formulas of unsaturated soil can not effectively describe basic
strength characteristics of gassy sand; the relationship between
apparent cohesion and matric suction of gassy sand agrees well with
the power function, which can reasonably be used to describe the
strength of gassy sand. In the stress path of gas release, shear strength
of gassy sand will increase and experimental results show the formula
proposed in this paper can effectively predict the strength increment.
When saturated strength indexes of the sand are used in engineering
design, moderate reduction should be considered.
Abstract: Measuring the complexity of software has been an
insoluble problem in software engineering. Complexity measures can
be used to predict critical information about testability, reliability,
and maintainability of software systems from automatic analysis of
the source code. During the past few years, many complexity
measures have been invented based on the emerging Cognitive
Informatics discipline. These software complexity measures,
including cognitive functional size, lend themselves to the approach
of the total cognitive weights of basic control structures such as loops
and branches. This paper shows that the current existing calculation
method can generate different results that are algebraically
equivalence. However, analysis of the combinatorial meanings of this
calculation method shows significant flaw of the measure, which also
explains why it does not satisfy Weyuker's properties. Based on the
findings, improvement directions, such as measures fusion, and
cumulative variable counting scheme are suggested to enhance the
effectiveness of cognitive complexity measures.
Abstract: Changing in consumers lifestyles and food
consumption patterns provide a great opportunity in developing the
functional food sector in Malaysia. There is only a little knowledge
about whether Malaysian consumers are aware of functional food and
if so what image consumers have of this product. The objective of
this research is to determine the extent to which selected socioeconomic
characteristics and attitudes influence consumers-
awareness of functional food. A survey was conducted in the Klang
Valley, Malaysia where 439 respondents were interviewed using a
structured questionnaire. The result shows that most respondents
have a positive attitude towards functional food. For the binary
logistic estimation, the results indicate that age, income and other
factors such as concern about food safety, subscribing to cooking or
health magazines, being a vegetarian and consumers who have been
involved in a food production company significantly influence
Malaysian consumers- awareness towards functional food.
Abstract: The classification of the protein structure is commonly
not performed for the whole protein but for structural domains, i.e.,
compact functional units preserved during evolution. Hence, a first
step to a protein structure classification is the separation of the
protein into its domains. We approach the problem of protein domain
identification by proposing a novel graph theoretical algorithm. We
represent the protein structure as an undirected, unweighted and
unlabeled graph which nodes correspond the secondary structure
elements of the protein. This graph is call the protein graph. The
domains are then identified as partitions of the graph corresponding
to vertices sets obtained by the maximization of an objective function,
which mutually maximizes the cycle distributions found in the
partitions of the graph. Our algorithm does not utilize any other kind
of information besides the cycle-distribution to find the partitions. If
a partition is found, the algorithm is iteratively applied to each of
the resulting subgraphs. As stop criterion, we calculate numerically
a significance level which indicates the stability of the predicted
partition against a random rewiring of the protein graph. Hence,
our algorithm terminates automatically its iterative application. We
present results for one and two domain proteins and compare our
results with the manually assigned domains by the SCOP database
and differences are discussed.
Abstract: One of the basic concepts in marketing is the concept
of meeting customers- needs. Since customer satisfaction is essential
for lasting survival and development of a business, screening and
observing customer satisfaction and recognizing its underlying
factors must be one of the key activities of every business.
The purpose of this study is to recognize the drivers that effect
customer satisfaction in a business-to-business situation in order to
improve marketing activities. We conducted a survey in which 93
business customers of a manufacturer of Diesel Generator in Iran
participated and they talked about their ideas and satisfaction of
supplier-s services related to its products. We developed the measures
for drivers of satisfaction first by as investigative research (by means
of feedback from executives and customers of sponsoring firm). Then
based on these measures, we created a mail survey, and asked the
respondents to explain their opinion about the sponsoring firm which
was a supplier of diesel generator and similar products. Furthermore,
the survey required the participants to mention their functional areas
and their company features.
In Conclusion we found that there are three drivers for customer
satisfaction, which are reliability, information about product, and
commercial features. Buyers/users from different functional areas
attribute different degree of importance to the last two drivers. For
instance, people from buying and management areas believe that
commercial features are more important than information about
products. But people in engineering, maintenance and production
areas believe that having information about products is more
important than commercial aspects. Marketing experts should
consider the attribute of customers regarding information about the
product and commercial features to improve market share.
Abstract: This paper proposes a delay-dependent leader-following consensus condition of multi-agent systems with both communication delay and probabilistic self-delay. The proposed methods employ a suitable piecewise Lyapunov-Krasovskii functional and the average dwell time approach. New consensus criterion for the systems are established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. Numerical example showed that the proposed method is effective.
Abstract: The intelligent fuzzy input estimator is used to estimate
the input force of the rigid bar structural system in this study. The
fuzzy Kalman filter without the input term and the fuzzy weighting
recursive least square estimator are two main portions of this method.
The practicability and accuracy of the proposed method were verified
with numerical simulations from which the input forces of a rigid bar
structural system were estimated from the output responses. In order to
examine the accuracy of the proposed method, a rigid bar structural
system is subjected to periodic sinusoidal dynamic loading. The
excellent performance of this estimator is demonstrated by comparing
it with the use of difference weighting function and improper the
initial process noise covariance. The estimated results have a good
agreement with the true values in all cases tested.
Abstract: This paper presents dynamic voltage collapse prediction on an actual power system using support vector machines.
Dynamic voltage collapse prediction is first determined based on the PTSI calculated from information in dynamic simulation output. Simulations were carried out on a practical 87 bus test system by considering load increase as the contingency. The data collected from the time domain simulation is then used as input to the SVM in which support vector regression is used as a predictor to determine the
dynamic voltage collapse indices of the power system. To reduce training time and improve accuracy of the SVM, the Kernel function type and Kernel parameter are considered. To verify the
effectiveness of the proposed SVM method, its performance is compared with the multi layer perceptron neural network (MLPNN). Studies show that the SVM gives faster and more accurate results for dynamic voltage collapse prediction compared with the MLPNN.
Abstract: Proteomics is one of the largest areas of research for
bioinformatics and medical science. An ambitious goal of proteomics
is to elucidate the structure, interactions and functions of all proteins
within cells and organisms. Predicting Protein-Protein Interaction
(PPI) is one of the crucial and decisive problems in current research.
Genomic data offer a great opportunity and at the same time a lot of
challenges for the identification of these interactions. Many methods
have already been proposed in this regard. In case of in-silico
identification, most of the methods require both positive and negative
examples of protein interaction and the perfection of these examples
are very much crucial for the final prediction accuracy. Positive
examples are relatively easy to obtain from well known databases. But
the generation of negative examples is not a trivial task. Current PPI
identification methods generate negative examples based on some
assumptions, which are likely to affect their prediction accuracy.
Hence, if more reliable negative examples are used, the PPI prediction
methods may achieve even more accuracy. Focusing on this issue, a
graph based negative example generation method is proposed, which
is simple and more accurate than the existing approaches. An
interaction graph of the protein sequences is created. The basic
assumption is that the longer the shortest path between two
protein-sequences in the interaction graph, the less is the possibility of
their interaction. A well established PPI detection algorithm is
employed with our negative examples and in most cases it increases
the accuracy more than 10% in comparison with the negative pair
selection method in that paper.
Abstract: In this paper; we are interested principally in dynamic modelling of quadrotor while taking into account the high-order nonholonomic constraints in order to develop a new control scheme as well as the various physical phenomena, which can influence the dynamics of a flying structure. These permit us to introduce a new state-space representation. After, the use of Backstepping approach for the synthesis of tracking errors and Lyapunov functions, a sliding mode controller is developed in order to ensure Lyapunov stability, the handling of all system nonlinearities and desired tracking trajectories. Finally simulation results are also provided in order to illustrate the performances of the proposed controller.
Abstract: In this paper, a periodic predator-prey system with harvesting terms and Holling II type functional response is considered. Sufficient criteria for the existence of at least sixteen periodic solutions are established by using the well known continuation theorem due to Mawhin. An example is given to illustrate the main result.
Abstract: As a part of an evaluation system for R&D programs,
the Korean Government has applied the preliminary feasibility study
to new government R&D program plans. Basically, the fundamental purpose of the preliminary feasibility study is to decide that the
government will either do or do not invest in a new R&D Program. Additionally, the preliminary feasibility study can contribute to the
improvement of R&D program plans. For example, 2 cases of new
R&D program plans applied to the study are explained in this paper and there are expectations that these R&D programs would yield better
performance than without the study. It is thought that the important point of the preliminary feasibility study is not only the effective
decision making process of R&D program but also the opportunity to improve R&D program plan actually.
Abstract: This paper introduces a new method called ARPDC (Advanced Robust Parallel Distributed Compensation) for automatic control of nonlinear systems. This method improves a quality of robust control by interpolating of robust and optimal controller. The weight of each controller is determined by an original criteria function for model validity and disturbance appreciation. ARPDC method is based on nonlinear Takagi-Sugeno (T-S) fuzzy systems and Parallel Distributed Compensation (PDC) control scheme. The relaxed stability conditions of ARPDC control of nominal system have been derived. The advantages of presented method are demonstrated on the inverse pendulum benchmark problem. From comparison between three different controllers (robust, optimal and ARPDC) follows, that ARPDC control is almost optimal with the robustness close to the robust controller. The results indicate that ARPDC algorithm can be a good alternative not only for a robust control, but in some cases also to an adaptive control of nonlinear systems.
Abstract: This paper presents a mark-up approach to service creation in Next Generation Networks. The approach allows deriving added value from network functions exposed by Parlay/OSA (Open Service Access) interfaces. With OSA interfaces service logic scripts might be executed both on callrelated and call-unrelated events. To illustrate the approach XMLbased language constructions for data and method definitions, flow control, time measuring and supervision and database access are given and an example of OSA application is considered.
Abstract: Nowadays, the pace of business change is such that,
increasingly, new functionality has to be realized and reliably
installed in a matter of days, or even hours. Consequently, more and
more business processes are prone to a continuous change. The
objective of the research in progress is to use the MAP model, in a
conceptual modeling method for flexible and adaptive business
process. This method can be used to capture the flexibility
dimensions of a business process; it takes inspiration from
modularity concept in the object oriented paradigm to establish a
hierarchical construction of the BP modeling. Its intent is to provide
a flexible modeling that allows companies to quickly adapt their
business processes.
Abstract: The objective of this paper, is to apply support vector machine (SVM) approach for the classification of cancerous and normal regions of prostate images. Three kinds of textural features are extracted and used for the analysis: parameters of the Gauss- Markov random field (GMRF), correlation function and relative entropy. Prostate images are acquired by the system consisting of a microscope, video camera and a digitizing board. Cross-validated classification over a database of 46 images is implemented to evaluate the performance. In SVM classification, sensitivity and specificity of 96.2% and 97.0% are achieved for the 32x32 pixel block sized data, respectively, with an overall accuracy of 96.6%. Classification performance is compared with artificial neural network and k-nearest neighbor classifiers. Experimental results demonstrate that the SVM approach gives the best performance.
Abstract: The purpose of this study is to suggest energy efficient
routing for ad hoc networks which are composed of nodes with limited
energy. There are diverse problems including limitation of energy
supply of node, and the node energy management problem has been
presented. And a number of protocols have been proposed for energy
conservation and energy efficiency. In this study, the critical point of
the EA-MPDSR, that is the type of energy efficient routing using only
two paths, is improved and developed. The proposed TP-MESR uses
multi-path routing technique and traffic prediction function to increase
number of path more than 2. It also verifies its efficiency compared to
EA-MPDSR using network simulator (NS-2). Also, To give a
academic value and explain protocol systematically, research
guidelines which the Hevner(2004) suggests are applied. This
proposed TP-MESR solved the existing multi-path routing problem
related to overhead, radio interference, packet reassembly and it
confirmed its contribution to effective use of energy in ad hoc
networks.
Abstract: An inflation–extension test with human vena cava
inferior was performed with the aim to fit a material model. The vein
was modeled as a thick–walled tube loaded by internal pressure and
axial force. The material was assumed to be an incompressible
hyperelastic fiber reinforced continuum. Fibers are supposed to be
arranged in two families of anti–symmetric helices. Considered
anisotropy corresponds to local orthotropy. Used strain energy
density function was based on a concept of limiting strain
extensibility. The pressurization was comprised by four pre–cycles
under physiological venous loading (0 – 4kPa) and four cycles under
nonphysiological loading (0 – 21kPa). Each overloading cycle was
performed with different value of axial weight. Overloading data
were used in regression analysis to fit material model. Considered
model did not fit experimental data so good. Especially predictions
of axial force failed. It was hypothesized that due to
nonphysiological values of loading pressure and different values of
axial weight the material was not preconditioned enough and some
damage occurred inside the wall. A limiting fiber extensibility
parameter Jm was assumed to be in relation to supposed damage.
Each of overloading cycles was fitted separately with different values
of Jm. Other parameters were held the same. This approach turned out
to be successful. Variable value of Jm can describe changes in the
axial force – axial stretch response and satisfy pressure – radius
dependence simultaneously.
Abstract: In the micro and nano-technology industry, the
«clean-rooms» dedicated to manufacturing chip, are equipped with
the most sophisticated equipment-tools. There use a large number of
resources in according to strict specifications for an optimum
working and result. The distribution of «utilities» to the production is
assured by teams who use a supervision tool.
The studies show the interest to control the various parameters of
production or/and distribution, in real time, through a reliable and
effective supervision tool. This document looks at a large part of the
functions that the supervisor must assure, with complementary
functionalities to help the diagnosis and simulation that prove very
useful in our case where the supervised installations are complexed
and in constant evolution.
Abstract: In this paper a PID control strategy using neural
network adaptive RASP1 wavelet for WECS-s control is proposed.
It is based on single layer feedforward neural networks with hidden
nodes of adaptive RASP1 wavelet functions controller and an infinite
impulse response (IIR) recurrent structure. The IIR is combined by
cascading to the network to provide double local structure resulting
in improving speed of learning. This particular neuro PID controller
assumes a certain model structure to approximately identify the
system dynamics of the unknown plant (WECS-s) and generate the
control signal. The results are applied to a typical turbine/generator
pair, showing the feasibility of the proposed solution.