Abstract: We present the induced generalized hybrid
averaging (IGHA) operator. It is a new aggregation operator
that generalizes the hybrid averaging (HA) by using
generalized means and order inducing variables. With this
formulation, we get a wide range of mean operators such as
the induced HA (IHA), the induced hybrid quadratic
averaging (IHQA), the HA, etc. The ordered weighted
averaging (OWA) operator and the weighted average (WA)
are included as special cases of the HA operator. Therefore,
with this generalization we can obtain a wide range of
aggregation operators such as the induced generalized OWA
(IGOWA), the generalized OWA (GOWA), etc. We further
generalize the IGHA operator by using quasi-arithmetic
means. Then, we get the Quasi-IHA operator. Finally, we also
develop an illustrative example of the new approach in a
financial decision making problem. The main advantage of the
IGHA is that it gives a more complete view of the decision
problem to the decision maker because it considers a wide
range of situations depending on the operator used.
Abstract: The management of the health-care wastes is one of
the most important problems in Istanbul, a city with more than 12
million inhabitants, as it is in most of the developing countries.
Negligence in appropriate treatment and final disposal of the healthcare
wastes can lead to adverse impacts to public health and to the
environment. This paper employs a fuzzy multi-criteria group
decision making approach, which is based on the principles of fusion
of fuzzy information, 2-tuple linguistic representation model, and
technique for order preference by similarity to ideal solution
(TOPSIS), to evaluate health-care waste (HCW) treatment
alternatives for Istanbul. The evaluation criteria are determined
employing nominal group technique (NGT), which is a method of
systematically developing a consensus of group opinion. The
employed method is apt to manage information assessed using multigranularity
linguistic information in a decision making problem with
multiple information sources. The decision making framework
employs ordered weighted averaging (OWA) operator that
encompasses several operators as the aggregation operator since it
can implement different aggregation rules by changing the order
weights. The aggregation process is based on the unification of
information by means of fuzzy sets on a basic linguistic term set
(BLTS). Then, the unified information is transformed into linguistic
2-tuples in a way to rectify the problem of loss information of other
fuzzy linguistic approaches.
Abstract: There is a renewed interest in land use transport integration as a means of achieving sustainable accessibility. Such accessibility requires designing more than simply the transport network; it also requires attention to place (built form). Transitoriented development would appear to capture many of the criteria deemed important in land use transport integration. In Perth, Australia, there have been planning policies for the past 20 years requiring transit-oriented development around railway stations throughout the metropolitan area. While the policy intent, particularly at the State level, is clear the implementation of policy has been fairly ineffective. The first part of this paper provides an examination of state and local government planning and transport policies, evaluating them using a set of land use transport integration criteria considered all encompassing. This provides some insight into the extent of state and local government capacity to deliver land use transport integration. The second part of this paper examines the extent of implementation by examining existing and proposed land use around station precincts throughout metropolitan Perth. The findings of this research suggest that the capacity of state and local government to deliver land use transport integration is reasonable in a planning policy sense. Implementation, despite long policy lead times, has been lacking. It appears to be more effective where local planning controls have been suspended with new redevelopment authorities given powers to develop land around railway stations.
Abstract: Proton transfer and hydrogen bonding are two aspects
of the chemistry of hydrogen that respectively govern the behaviour
and structure of many molecules, both simple and complex. All the
theoretical enol and keto conformations of 1,3-diphenyl-1,3-
propandion known as dibenzoylmethane (DBM), have been
investigated by means of atoms in molecules (AIM) theory. It was
found that the most stable conformers are those stabilized by
hydrogen bridges.The aim of the present paper is a thorough
conformational analysis of DBM (with special attention on chelated
cis-enol conformers) in order to obtain detailed information on the
geometrical parameters, relative stabilities and rotational motion of
the phenyl groups. It is also important to estimate the barrier height
for ptoton transfer and hydrogen bond strength, which are the main
factors governing conformational stability.
Abstract: The many feasible alternatives and conflicting
objectives make equipment selection in materials handling a
complicated task. This paper presents utilizing Monte Carlo (MC)
simulation combined with the Analytic Hierarchy Process (AHP) to
evaluate and select the most appropriate Material Handling
Equipment (MHE). The proposed hybrid model was built on the base
of material handling equation to identify main and sub criteria critical
to MHE selection. The criteria illustrate the properties of the material
to be moved, characteristics of the move, and the means by which the
materials will be moved. The use of MC simulation beside the AHP
is very powerful where it allows the decision maker to represent
his/her possible preference judgments as random variables. This will
reduce the uncertainty of single point judgment at conventional AHP,
and provide more confidence in the decision problem results. A small
business pharmaceutical company is used as an example to illustrate
the development and application of the proposed model.
Abstract: The international society focuses on the environment
protection and natural energy sources control for the global
cooperation against weather change and sustainable growth. The study
presents the overview of the water shortage status and the necessity of wastewater reuse facility in military facilities and for the possibility of
the introduction, compares the economics by means of cost-benefit
analysis. The military features such as the number of users of military barracks and the water use were surveyed by the design principles by
facility types, the application method of wastewater reuse facility was selected, the feed water, its application and the volume of reuse volume were defined and the expectation was estimated, confirming
the possibility of introducing a wastewater reuse possibility by means of cost-benefit analysis.
Abstract: An overview of the important aspects of managing
and controlling industrial effluent discharges to public sewers namely
sampling, characterization, quantification and legislative controls has
been presented. The findings have been validated by means of a case
study covering three industrial sectors namely, tanning, textile
finishing and food processing industries. Industrial effluents
discharges were found to be best monitored by systematic and
automatic sampling and quantified using water meter readings
corrected for evaporative and consumptive losses. Based on the
treatment processes employed in the public owned treatment works
and the chemical oxygen demand and biochemical oxygen demand
levels obtained, the effluent from all the three industrial sectors
studied were found to lie in the toxic zone. Thus, physico-chemical
treatment of these effluents is required to bring them into the
biodegradable zone. KL values (quoted to base e) were greater than
0.50 day-1 compared to 0.39 day-1 for typical municipality
wastewater.
Abstract: As is needless to say; a majority of accidents, which occur, are due to drunk driving. As such, there is no effective mechanism to prevent this. Here we have designed an integrated system for the same purpose. Alcohol content in the driver-s body is detected by means of an infrared breath analyzer placed at the steering wheel. An infrared cell directs infrared energy through the sample and any unabsorbed energy at the other side is detected. The higher the concentration of ethanol, the more infrared absorption occurs (in much the same way that a sunglass lens absorbs visible light, alcohol absorbs infrared light). Thus the alcohol level of the driver is continuously monitored and calibrated on a scale. When it exceeds a particular limit the fuel supply is cutoff. If the device is removed also, the fuel supply will be automatically cut off or an alarm is sounded depending upon the requirement. This does not happen abruptly and special indicators are fixed at the back to avoid inconvenience to other drivers using the highway signals. Frame work for integration of sensors and control module in a scalable multi-agent system is provided .A SMS which contains the current GPS location of the vehicle is sent via a GSM module to the police control room to alert the police. The system is foolproof and the driver cannot tamper with it easily. Thus it provides an effective and cost effective solution for the problem of drunk driving in vehicles.
Abstract: Recognition of Indian languages scripts is challenging problems. In Optical Character Recognition [OCR], a character or symbol to be recognized can be machine printed or handwritten characters/numerals. There are several approaches that deal with problem of recognition of numerals/character depending on the type of feature extracted and different way of extracting them. This paper proposes a recognition scheme for handwritten Hindi (devnagiri) numerals; most admired one in Indian subcontinent. Our work focused on a technique in feature extraction i.e. global based approach using end-points information, which is extracted from images of isolated numerals. These feature vectors are fed to neuro-memetic model [18] that has been trained to recognize a Hindi numeral. The archetype of system has been tested on varieties of image of numerals. . In proposed scheme data sets are fed to neuro-memetic algorithm, which identifies the rule with highest fitness value of nearly 100 % & template associates with this rule is nothing but identified numerals. Experimentation result shows that recognition rate is 92-97 % compared to other models.
Abstract: Exposure to ambient air pollution has been linked to a
number of health outcomes, starting from modest transient changes in
the respiratory tract and impaired pulmonary function, continuing to
restrict activity/reduce performance and to the increase emergency
rooms visits, hospital admissions or mortality. The increase of
allergenic symptoms has been associated with air contaminants such
as ozone, particulate matter, fungal spores and pollen.
Considering the potential relevance of crossed effects of nonbiological
pollutants and airborne pollens and fungal spores on
allergy worsening, the aim of this work was to evaluate the influence
of non-biological pollutants (O3 and PM10) and meteorological
parameters on the concentrations of pollen and fungal spores using
multiple linear regressions.
The data considered in this study were collected in Oporto which
is the second largest Portuguese city, located in the North. Daily
mean of O3, PM10, pollen and fungal spore concentrations,
temperature, relative humidity, precipitation, wind velocity, pollen
and fungal spore concentrations, for 2003, 2004 and 2005 were
considered. Results showed that the 90th percentile of the adjusted
coefficient of determination, P90 (R2aj), of the multiple regressions
varied from 0.613 to 0.916 for pollen and from 0.275 to 0.512 for
fungal spores. O3 and PM10 showed to have some influence on the
biological pollutants. Among the meteorological parameters
analysed, temperature was the one that most influenced the pollen
and fungal spores airborne concentrations. Relative humidity also
showed to have some influence on the fungal spore dispersion.
Nevertheless, the models for each pollen and fungal spore were
different depending on the analysed period, which means that the
correlations identified as statistically significant can not be, even so,
consistent enough.
Abstract: The motion planning procedure described in this paper has been developed in order to eliminate or reduce the residual vibrations of electromechanical positioning systems, without augmenting the motion time (usually imposed by production requirements), nor introducing overtime for vibration damping. The proposed technique is based on a suitable choice of the motion law assigned to the servomotor that drives the mechanism. The reference profile is defined by a Bezier curve, whose shape can be easily changed by modifying some numerical parameters. By means of an optimization technique these parameters can be modified without altering the continuity conditions imposed on the displacement and on its time derivatives at the initial and final time instants.
Abstract: As the number of networked computers grows,
intrusion detection is an essential component in keeping networks
secure. Various approaches for intrusion detection are currently
being in use with each one has its own merits and demerits. This
paper presents our work to test and improve the performance of a
new class of decision tree c-fuzzy decision tree to detect intrusion.
The work also includes identifying best candidate feature sub set to
build the efficient c-fuzzy decision tree based Intrusion Detection
System (IDS). We investigated the usefulness of c-fuzzy decision
tree for developing IDS with a data partition based on horizontal
fragmentation. Empirical results indicate the usefulness of our
approach in developing the efficient IDS.
Abstract: In this paper a Pattern Recognition algorithm based on
a constrained version of the k-means clustering algorithm will be
presented. The proposed algorithm is a non parametric supervised
statistical pattern recognition algorithm, i.e. it works under very mild
assumptions on the dataset. The performance of the algorithm will
be tested, togheter with a feature extraction technique that captures
the information on the closed two-dimensional contour of an image,
on images of industrial mineral ores.
Abstract: InGaAsN and GaAsN epitaxial layers with similar
nitrogen compositions in a sample were successfully grown on a
GaAs (001) substrate by solid source molecular beam epitaxy. An
electron cyclotron resonance nitrogen plasma source has been used to
generate atomic nitrogen during the growth of the nitride layers. The
indium composition changed from sample to sample to give
compressive and tensile strained InGaAsN layers. Layer
characteristics have been assessed by high-resolution x-ray
diffraction to determine the relationship between the lattice constant
of the GaAs1-yNy layer and the fraction x of In. The objective was to
determine the In fraction x in an InxGa1-xAs1-yNy epitaxial layer which
exactly cancels the strain present in a GaAs1-yNy epitaxial layer with
the same nitrogen content when grown on a GaAs substrate.
Abstract: Psoriasis is a chronic inflammatory skin condition
which affects 2-3% of population around the world. Psoriasis Area
and Severity Index (PASI) is a gold standard to assess psoriasis
severity as well as the treatment efficacy. Although a gold standard,
PASI is rarely used because it is tedious and complex. In practice,
PASI score is determined subjectively by dermatologists, therefore
inter and intra variations of assessment are possible to happen even
among expert dermatologists. This research develops an algorithm to
assess psoriasis lesion for PASI scoring objectively. Focus of this
research is thickness assessment as one of PASI four parameters
beside area, erythema and scaliness. Psoriasis lesion thickness is
measured by averaging the total elevation from lesion base to lesion
surface. Thickness values of 122 3D images taken from 39 patients
are grouped into 4 PASI thickness score using K-means clustering.
Validation on lesion base construction is performed using twelve
body curvature models and show good result with coefficient of
determinant (R2) is equal to 1.
Abstract: This paper presents a implementation of an object tracking system in a video sequence. This object tracking is an important task in many vision applications. The main steps in video analysis are two: detection of interesting moving objects and tracking of such objects from frame to frame. In a similar vein, most tracking algorithms use pre-specified methods for preprocessing. In our work, we have implemented several object tracking algorithms (Meanshift, Camshift, Kalman filter) with different preprocessing methods. Then, we have evaluated the performance of these algorithms for different video sequences. The obtained results have shown good performances according to the degree of applicability and evaluation criteria.
Abstract: In this paper, we propose a Connect6 solver which
adopts a hybrid approach based on a tree-search algorithm and image
processing techniques. The solver must deal with the complicated
computation and provide high performance in order to make real-time
decisions. The proposed approach enables the solver to be
implemented on a single Spartan-6 XC6SLX45 FPGA produced by
XILINX without using any external devices. The compact
implementation is achieved through image processing techniques to
optimize a tree-search algorithm of the Connect6 game. The tree
search is widely used in computer games and the optimal search brings
the best move in every turn of a computer game. Thus, many
tree-search algorithms such as Minimax algorithm and artificial
intelligence approaches have been widely proposed in this field.
However, there is one fundamental problem in this area; the
computation time increases rapidly in response to the growth of the
game tree. It means the larger the game tree is, the bigger the circuit
size is because of their highly parallel computation characteristics.
Here, this paper aims to reduce the size of a Connect6 game tree using
image processing techniques and its position symmetric property. The
proposed solver is composed of four computational modules: a
two-dimensional checkmate strategy checker, a template matching
module, a skilful-line predictor, and a next-move selector. These
modules work well together in selecting next moves from some
candidates and the total amount of their circuits is small. The details of
the hardware design for an FPGA implementation are described and
the performance of this design is also shown in this paper.
Abstract: On one hand, SNMP (Simple Network Management
Protocol) allows integrating different enterprise elements connected
through Internet into a standardized remote management. On the
other hand, as a consequence of the success of Intelligent Houses
they can be connected through Internet now by means of a residential
gateway according to a common standard called OSGi (Open
Services Gateway initiative). Due to the specifics of OSGi Service
Platforms and their dynamic nature, specific design criterions should
be defined to implement SNMP Agents for OSGi in order to integrate
them into the SNMP remote management. Based on the analysis of
the relation between both standards (SNMP and OSGi), this paper
shows how OSGi Service Platforms can be included into the SNMP
management of a global enterprise, giving implementation details
about an SNMP Agent solution and the definition of a new MIB
(Management Information Base) for managing OSGi platforms that
takes into account the specifics and dynamic nature of OSGi.
Abstract: In this study, a fuzzy integrated logical forecasting method (FILF) is extended for multi-variate systems by using a vector autoregressive model. Fuzzy time series forecasting (FTSF) method was recently introduced by Song and Chissom [1]-[2] after that Chen improved the FTSF method. Rather than the existing literature, the proposed model is not only compared with the previous FTS models, but also with the conventional time series methods such as the classical vector autoregressive model. The cluster optimization is based on the C-means clustering method. An empirical study is performed for the prediction of the chartering rates of a group of dry bulk cargo ships. The root mean squared error (RMSE) metric is used for the comparing of results of methods and the proposed method has superiority than both traditional FTS methods and also the classical time series methods.
Abstract: In high bitrate information hiding techniques, 1 bit is
embedded within each 4 x 4 Discrete Cosine Transform (DCT)
coefficient block by means of vector quantization, then the hidden bit
can be effectively extracted in terminal end. In this paper high bitrate
information hiding algorithms are summarized, and the scheme of
video in video is implemented. Experimental result shows that the host
video which is embedded numerous auxiliary information have little
visually quality decline. Peak Signal to Noise Ratio (PSNR)Y of host
video only degrades 0.22dB in average, while the hidden information
has a high percentage of survives and keeps a high robustness in
H.264/AVC compression, the average Bit Error Rate(BER) of hiding
information is 0.015%.