Abstract: This work proposes a novel market-based air traffic flow control model considering competitive airlines in air traffic network. In the flow model, an agent based framework for resources (link/time pair) pricing is described. Resource agent and auctioneer for groups of resources are also introduced to simulate the flow management in Air Traffic Control (ATC). Secondly, the distributed group pricing algorithm is introduced, which efficiently reflect the competitive nature of the airline industry. Resources in the system are grouped according to the degree of interaction, and each auctioneer adjust s the price of one group of resources respectively until the excess demand of resources becomes zero when the demand and supply of resources of the system changes. Numerical simulation results show the feasibility of solving the air traffic flow control problem using market mechanism and pricing algorithms on the air traffic network.
Abstract: MATCH project [1] entitle the development of an
automatic diagnosis system that aims to support treatment of colon
cancer diseases by discovering mutations that occurs to tumour
suppressor genes (TSGs) and contributes to the development of
cancerous tumours. The constitution of the system is based on a)
colon cancer clinical data and b) biological information that will be
derived by data mining techniques from genomic and proteomic
sources The core mining module will consist of the popular, well
tested hybrid feature extraction methods, and new combined
algorithms, designed especially for the project. Elements of rough
sets, evolutionary computing, cluster analysis, self-organization maps
and association rules will be used to discover the annotations
between genes, and their influence on tumours [2]-[11].
The methods used to process the data have to address their high
complexity, potential inconsistency and problems of dealing with the
missing values. They must integrate all the useful information
necessary to solve the expert's question. For this purpose, the system
has to learn from data, or be able to interactively specify by a domain
specialist, the part of the knowledge structure it needs to answer a
given query. The program should also take into account the
importance/rank of the particular parts of data it analyses, and adjusts
the used algorithms accordingly.
Abstract: The temporal nature of negative selection is an under exploited area. In a negative selection system, newly generated antibodies go through a maturing phase, and the survivors of the phase then wait to be activated by the incoming antigens after certain number of matches. These without having enough matches will age and die, while these with enough matches (i.e., being activated) will become active detectors. A currently active detector may also age and die if it cannot find any match in a pre-defined (lengthy) period of time. Therefore, what matters in a negative selection system is the dynamics of the involved parties in the current time window, not the whole time duration, which may be up to eternity. This property has the potential to define the uniqueness of negative selection in comparison with the other approaches. On the other hand, a negative selection system is only trained with “normal" data samples. It has to learn and discover unknown “abnormal" data patterns on the fly by itself. Consequently, it is more appreciate to utilize negation selection as a system for pattern discovery and recognition rather than just pattern recognition. In this paper, we study the potential of using negative selection in discovering unknown temporal patterns.
Abstract: In this paper, two very different optimization
algorithms, Genetic and DIRECT algorithms, are used to history
match a bottomhole pressure response for a reservoir with wellbore
storage and skin with the best possible analytical model. No initial
guesses are available for reservoir parameters. The results show that
the matching process is much faster and more accurate for DIRECT
method in comparison with Genetic algorithm. It is furthermore
concluded that the DIRECT algorithm does not need any initial
guesses, whereas Genetic algorithm needs to be tuned according to
initial guesses.
Abstract: Fungal infections are becoming more common and the
range of susceptible individuals has expanded. While Candida
albicans remains the most common infective species, other Candida
spp. are becoming increasingly significant. In a range of large-scale
studies of candidaemia between 1999 and 2006, about 52% of 9717
cases involved C. albicans, about 30% involved either C. glabrata or
C. parapsilosis and less than 15% involved C. tropicalis, C. krusei or
C. guilliermondii. However, the probability of mortality within 30
days of infection with a particular species was at least 40% for C.
tropicalis, C. albicans, C. glabrata and C. krusei and only 22% for
C. parapsilopsis. Clinical isolates of Candida spp. grew at rates
ranging from 1.65 h-1 to 4.9 h-1. Three species (C. krusei, C. albicans
and C. glabrata) had relatively high growth rates (μm > 4 h-1), C.
tropicalis and C. dubliniensis grew moderately quickly (Ôëê 3 h-1) and
C. parapsilosis and C. guilliermondii grew slowly (< 2 h-1). Based
on these data, the log of the odds of mortality within 30 days of
diagnosis was linearly related to μm. From this the underlying
probability of mortality is 0.13 (95% CI: 0.10-0.17) and it increases
by about 0.09 ± 0.02 for each unit increase in μm. Given that the
overall crude mortality is about 0.36, the growth of Candida spp.
approximately doubles the rate, consistent with the results of larger
case-matched studies of candidaemia.
Abstract: This study presents a new approach based on Tanaka's
fuzzy linear regression (FLP) algorithm to solve well-known power
system economic load dispatch problem (ELD). Tanaka's fuzzy linear
regression (FLP) formulation will be employed to compute the
optimal solution of optimization problem after linearization. The
unknowns are expressed as fuzzy numbers with a triangular
membership function that has middle and spread value reflected on
the unknowns. The proposed fuzzy model is formulated as a linear
optimization problem, where the objective is to minimize the sum of
the spread of the unknowns, subject to double inequality constraints.
Linear programming technique is employed to obtain the middle and
the symmetric spread for every unknown (power generation level).
Simulation results of the proposed approach will be compared with
those reported in literature.
Abstract: This paper describes an optimal approach for feature
subset selection to classify the leaves based on Genetic Algorithm
(GA) and Kernel Based Principle Component Analysis (KPCA). Due
to high complexity in the selection of the optimal features, the
classification has become a critical task to analyse the leaf image
data. Initially the shape, texture and colour features are extracted
from the leaf images. These extracted features are optimized through
the separate functioning of GA and KPCA. This approach performs
an intersection operation over the subsets obtained from the
optimization process. Finally, the most common matching subset is
forwarded to train the Support Vector Machine (SVM). Our
experimental results successfully prove that the application of GA
and KPCA for feature subset selection using SVM as a classifier is
computationally effective and improves the accuracy of the classifier.
Abstract: Personal name matching system is the core of
essential task in national citizen database, text and web mining,
information retrieval, online library system, e-commerce and record
linkage system. It has necessitated to the all embracing research in
the vicinity of name matching. Traditional name matching methods
are suitable for English and other Latin based language. Asian
languages which have no word boundary such as Myanmar language
still requires sounds alike matching system in Unicode based
application. Hence we proposed matching algorithm to get analogous
sounds alike (phonetic) pattern that is convenient for Myanmar
character spelling. According to the nature of Myanmar character, we
consider for word boundary fragmentation, collation of character.
Thus we use pattern conversion algorithm which fabricates words in
pattern with fragmented and collated. We create the Myanmar sounds
alike phonetic group to help in the phonetic matching. The
experimental results show that fragmentation accuracy in 99.32% and
processing time in 1.72 ms.
Abstract: In this paper, we propose a hardware and software
design method for automotive Electronic Control Units (ECU)
considering the functional safety. The proposed ECU is considered for
the application to Electro-Mechanical Actuator systems and the
validity of the design method is shown by the application to the
Electro-Mechanical Brake (EMB) control system which is used as a
brake actuator in Brake-By-Wire (BBW) systems. The importance of a
functional safety-based design approach to EMB ECU design has been
emphasized because of its safety-critical functions, which are executed
with the aid of many electric actuators, sensors, and application
software. Based on hazard analysis and risk assessment according to
ISO26262, the EMB system should be ASIL-D-compliant, the highest
ASIL level. To this end, an external signature watchdog and an
Infineon 32-bit microcontroller TriCore are used to reduce risks
considering common-cause hardware failure. Moreover, a software
design method is introduced for implementing functional
safety-oriented monitoring functions based on an asymmetric dual
core architecture considering redundancy and diversity. The validity
of the proposed ECU design approach is verified by using the EMB
Hardware-In-the-Loop (HILS) system, which consists of the EMB
assembly, actuator ECU, a host PC, and a few debugging devices.
Furthermore, it is shown that the existing sensor fault tolerant control
system can be used more effectively for mitigating the effects of
hardware and software faults by applying the proposed ECU design
method.
Abstract: The designing of charge pump with high gain Op-
Amp is a challenging task for getting faithful response .Design of
high performance phase locked loop require ,a design of high
performance charge pump .We have designed a operational amplifier
for reducing the error caused by high speed glitch in a transistor and
mismatch currents . A separate Op-Amp has designed in 180 nm
CMOS technology by CADENCE VIRTUOSO tool. This paper
describes the design of high performance charge pump for GHz
CMOS PLL targeting orthogonal frequency division multiplexing
(OFDM) application. A high speed low power consumption Op-Amp
with more than 500 MHz bandwidth has designed for increasing the
speed of charge pump in Phase locked loop.
Abstract: Graph decompositions are vital in the study of combinatorial design theory. Given two graphs G and H, an H-decomposition of G is a partition of the edge set of G into disjoint isomorphic copies of H. An n-sun is a cycle Cn with an edge terminating in a vertex of degree one attached to each vertex. In this paper we have proved that the complete graph of order 2n, K2n can be decomposed into n-2 n-suns, a Hamilton cycle and a perfect matching, when n is even and for odd case, the decomposition is n-1 n-suns and a perfect matching. For an odd order complete graph K2n+1, delete the star subgraph K1, 2n and the resultant graph K2n is decomposed as in the case of even order. The method of building n-suns uses Walecki's construction for the Hamilton decomposition of complete graphs. A spanning tree decomposition of even order complete graphs is also discussed using the labeling scheme of n-sun decomposition. A complete bipartite graph Kn, n can be decomposed into n/2 n-suns when n/2 is even. When n/2 is odd, Kn, n can be decomposed into (n-2)/2 n-suns and a Hamilton cycle.
Abstract: The objective of this study is to identify the factors
that influence the online purchasing loyalty for Thai herbal products.
Survey research is used to gather data from Thai herb online
merchants to assess factors that have impacts on enhancing loyalty.
Data were collected from 300 online customers who had experience
in online purchasing of Thai Herbal products. Prior experience
consists of data from previous usage of online herbs, herb purchase
and internet usage. E-Quality data consists of information quality,
system quality, service quality and the product quality of Thai herbal
products sold online. The results suggest that prior experience, Equality,
attitude toward purchase and trust in online merchant have
major impacts on loyalty. The good attitude and E-Quality of
purchasing Thai herbal product online are the most significant
determinants affecting loyalty.
Abstract: This paper presents the application of an enhanced
Particle Swarm Optimization (EPSO) combined with Gaussian
Mutation (GM) for solving the Dynamic Economic Dispatch (DED)
problem considering the operating constraints of generators. The
EPSO consists of the standard PSO and a modified heuristic search
approaches. Namely, the ability of the traditional PSO is enhanced
by applying the modified heuristic search approach to prevent the
solutions from violating the constraints. In addition, Gaussian
Mutation is aimed at increasing the diversity of global search, whilst
it also prevents being trapped in suboptimal points during search. To
illustrate its efficiency and effectiveness, the developed EPSO-GM
approach is tested on the 3-unit and 10-unit 24-hour systems
considering valve-point effect. From the experimental results, it can
be concluded that the proposed EPSO-GM provides, the accurate
solution, the efficiency, and the feature of robust computation
compared with other algorithms under consideration.
Abstract: In the present study, 49 Hybrid (Catla catla ♂ x
Labeo rohita ♀) were sampled from Al-Raheem Fish Hatchery,
Village Ali Pure Shamali, Jhang Road, 18 Km from Muzaffar Garh
using a cast net and Live fishes were transported to research
laboratory. Mean percentage for water found 79.13 %, ash 6.58 %, fat
2.22 % and protein content 12.06 % in whole wet body weight. It was
observed that body constituents were found increasing in the same
proportion with an increase in body weight while significant
proportional increase was observed with total length. However,
condition factor remained insignificant (P>0.05) with body
constituents.
Abstract: Flood zoning studies have become more efficient in
recent years because of the availability of advanced computational
facilities and use of Geographic Information Systems (GIS). In the
present study, flood inundated areas were mapped using GIS for the
Dikrong river basin of Arunachal Pradesh, India, corresponding to
different return periods (2, 5, 25, 50, and 100 years). Further, the developed inundation maps corresponding to 25, 50, and 100 year return period floods were compared to corresponding maps
developed by conventional methods as reported in the Brahmaputra Board Master Plan for Dikrong basin. It was found that, the average
deviation of modelled flood inundation areas from reported map
inundation areas is below 5% (4.52%). Therefore, it can be said that
the modelled flood inundation areas matched satisfactorily with
reported map inundation areas. Hence, GIS techniques were proved to be successful in extracting the flood inundation extent in a time and cost effective manner for the remotely located hilly basin of Dikrong, where conducting conventional surveys is very difficult.
Abstract: In this study, the ability of Aspergillus niger and
Penicillium simplicissimum to extract heavy metals from a spent
refinery catalyst was investigated. For the first step, a spent
processing catalyst from one of the oil refineries in Iran was
physically and chemically characterized. Aspergillus niger and
Penicillium simplicissimum were used to mobilize Al/Co/Mo/Ni from
hazardous spent catalysts. The fungi were adapted to the mixture of
metals at 100-800 mg L-1 with increments in concentration of 100 mg
L-1. Bioleaching experiments were carried out in batch cultures. To
investigate the production of organic acids in sucrose medium,
analyses of the culture medium by HPLC were performed at specific
time intervals after inoculation. The results obtained from Inductive
coupled plasma-optical emission spectrometry (ICP-OES) showed
that after the one-step bioleaching process using Aspergillus niger,
maximum removal efficiencies of 27%, 66%, 62% and 38% were
achieved for Al, Co, Mo and Ni, respectively. However, the highest
removal efficiencies using Penicillium simplicissimum were of 32%,
67%, 65% and 38% for Al, Co, Mo and Ni, respectively
Abstract: Different methods containing biometric algorithms are
presented for the representation of eigenfaces detection including
face recognition, are identification and verification. Our theme of this
research is to manage the critical processing stages (accuracy, speed,
security and monitoring) of face activities with the flexibility of
searching and edit the secure authorized database. In this paper we
implement different techniques such as eigenfaces vector reduction
by using texture and shape vector phenomenon for complexity
removal, while density matching score with Face Boundary Fixation
(FBF) extracted the most likelihood characteristics in this media
processing contents. We examine the development and performance
efficiency of the database by applying our creative algorithms in both
recognition and detection phenomenon. Our results show the
performance accuracy and security gain with better achievement than
a number of previous approaches in all the above processes in an
encouraging mode.
Abstract: Many non-conventional adsorbent have been studied
as economic alternative to commercial activated carbon and mostly
agricultural waste have been introduced such as rubber leaf powder
and hazelnut shell. Microwave Incinerated Rice Husk Ash
(MIRHA), produced from the rice husk is one of the low-cost
materials that were used as adsorbent of heavy metal. The aim of
this research was to study the feasibility of using MIRHA500 and
MIRHA800 as adsorbent for the removal of Cu(II) metal ions from
aqueous solutions by the batch studies. The adsorption of Cu(II) into
MIRHA500 and MIRH800 favors Fruendlich isotherm and imply
pseudo – kinetic second order which applied chemisorptions
Abstract: The rapid growth of e-Commerce services is
significantly observed in the past decade. However, the method to
verify the authenticated users still widely depends on numeric
approaches. A new search on other verification methods suitable for
online e-Commerce is an interesting issue. In this paper, a new online
signature-verification method using angular transformation is
presented. Delay shifts existing in online signatures are estimated by
the estimation method relying on angle representation. In the
proposed signature-verification algorithm, all components of input
signature are extracted by considering the discontinuous break points
on the stream of angular values. Then the estimated delay shift is
captured by comparing with the selected reference signature and the
error matching can be computed as a main feature used for verifying
process. The threshold offsets are calculated by two types of error
characteristics of the signature verification problem, False Rejection
Rate (FRR) and False Acceptance Rate (FAR). The level of these two
error rates depends on the decision threshold chosen whose value is
such as to realize the Equal Error Rate (EER; FAR = FRR). The
experimental results show that through the simple programming,
employed on Internet for demonstrating e-Commerce services, the
proposed method can provide 95.39% correct verifications and 7%
better than DP matching based signature-verification method. In
addition, the signature verification with extracting components
provides more reliable results than using a whole decision making.
Abstract: Organic Flash Cycle (OFC) has potential of improving
efficiency for recovery of low temperature heat sources mainly due to
reducing temperature mismatch in the heat exchanger. In this work
exergetical performance analysis of ORC is conducted for recovery of
low grade heat source. Effects of system parameters such as flash
evaporation temperature or heating temperature are theoretically
investigated on the exergy destructions (anergies) at various
components of the system as well as exergy efficiency. Results show
that exergy efficiency has a peak with respect to the flash temperature,
and the optimum flash temperature increases with the heating
temperature. The component where the largest exergy destruction
occurs varies with the flash temperature or heating temperature.