Abstract: This paper presents an optimal and unsupervised satellite image segmentation approach based on Pearson system and k-Means Clustering Algorithm Initialization. Such method could be considered as original by the fact that it utilised K-Means clustering algorithm for an optimal initialisation of image class number on one hand and it exploited Pearson system for an optimal statistical distributions- affectation of each considered class on the other hand. Satellite image exploitation requires the use of different approaches, especially those founded on the unsupervised statistical segmentation principle. Such approaches necessitate definition of several parameters like image class number, class variables- estimation and generalised mixture distributions. Use of statistical images- attributes assured convincing and promoting results under the condition of having an optimal initialisation step with appropriated statistical distributions- affectation. Pearson system associated with a k-means clustering algorithm and Stochastic Expectation-Maximization 'SEM' algorithm could be adapted to such problem. For each image-s class, Pearson system attributes one distribution type according to different parameters and especially the Skewness 'β1' and the kurtosis 'β2'. The different adapted algorithms, K-Means clustering algorithm, SEM algorithm and Pearson system algorithm, are then applied to satellite image segmentation problem. Efficiency of those combined algorithms was firstly validated with the Mean Quadratic Error 'MQE' evaluation, and secondly with visual inspection along several comparisons of these unsupervised images- segmentation.
Abstract: A statistical optimization of the saccharification
process of EFB was studied. The statistical analysis was done by
applying faced centered central composite design (FCCCD) under
response surface methodology (RSM). In this investigation, EFB
dose, enzyme dose and saccharification period was examined, and the
maximum 53.45% (w/w) yield of reducing sugar was found with 4%
(w/v) of EFB, 10% (v/v) of enzyme after 120 hours of incubation. It
can be calculated that the conversion rate of cellulose content of the
substrate is more than 75% (w/w) which can be considered as a
remarkable achievement. All the variables, linear, quadratic and
interaction coefficient, were found to be highly significant, other than
two coefficients, one quadratic and another interaction coefficient.
The coefficient of determination (R2) is 0.9898 that confirms a
satisfactory data and indicated that approximately 98.98% of the
variability in the dependent variable, saccharification of EFB, could
be explained by this model.
Abstract: Continuously variable transmission (CVT) is a type of
automatic transmission that can change the gear ratio to any arbitrary
setting within the limits. The most common type of CVT operates on
a pulley system that allows an infinite variability between highest and
lowest gears with no discrete steps. However, the current CVT
system with hydraulic actuation method suffers from the power loss.
It needs continuous force for the pulley to clamp the belt and hold the
torque resulting in large amount of energy consumption. This study
focused on the development of an electromechanical actuated control
CVT to eliminate the problem that faced by the existing CVT. It is
conducted with several steps; computing and selecting the
appropriate sizing for stroke length, lead screw system and etc. From
the visual observation it was found that the CVT system of this
research is satisfactory.
Abstract: Video streaming over lossy IP networks is very
important issues, due to the heterogeneous structure of networks.
Infrastructure of the Internet exhibits variable bandwidths, delays,
congestions and time-varying packet losses. Because of variable
attributes of the Internet, video streaming applications should not
only have a good end-to-end transport performance but also have a
robust rate control, furthermore multipath rate allocation mechanism.
So for providing the video streaming service quality, some other
components such as Bandwidth Estimation and Adaptive Rate
Controller should be taken into consideration. This paper gives an
overview of video streaming concept and bandwidth estimation tools
and then introduces special architectures for bandwidth adaptive
video streaming. A bandwidth estimation algorithm – pathChirp,
Optimized Rate Controllers and Multipath Rate Allocation Algorithm
are considered as all-in-one solution for video streaming problem.
This solution is directed and optimized by a decision center which is
designed for obtaining the maximum quality at the receiving side.
Abstract: Evapotranspiration (ET) is a major component of the hydrologic cycle and its accurate estimation is essential for hydrological studies. In past, various estimation methods have been developed for different climatological data, and the accuracy of these methods varies with climatic conditions. Reference crop evapotranspiration (ET0) is a key variable in procedures established for estimating evapotranspiration rates of agricultural crops. Values of ET0 are used with crop coefficients for many aspects of irrigation and water resources planning and management. Numerous methods are used for estimating ET0. As per internationally accepted procedures outlined in the United Nations Food and Agriculture Organization-s Irrigation and Drainage Paper No. 56(FAO-56), use of Penman-Monteith equation is recommended for computing ET0 from ground based climatological observations. In the present study, seven methods have been selected for performance evaluation. User friendly software has been developed using programming language visual basic. The visual basic has ability to create graphical environment using less coding. For given data availability the developed software estimates reference evapotranspiration for any given area and period for which data is available. The accuracy of the software has been checked by the examples given in FAO-56.The developed software is a user friendly tool for estimating ET0 under different data availability and climatic conditions.
Abstract: In this paper, we study statistical multiplexing of VBR
video in ATM networks. ATM promises to provide high speed realtime
multi-point to central video transmission for telemedicine
applications in rural hospitals and in emergency medical services.
Video coders are known to produce variable bit rate (VBR) signals
and the effects of aggregating these VBR signals need to be
determined in order to design a telemedicine network infrastructure
capable of carrying these signals. We first model the VBR video
signal and simulate it using a generic continuous-data autoregressive
(AR) scheme. We carry out the queueing analysis by the Fluid
Approximation Model (FAM) and the Markov Modulated Poisson
Process (MMPP). The study has shown a trade off: multiplexing
VBR signals reduces burstiness and improves resource utilization,
however, the buffer size needs to be increased with an associated
economic cost. We also show that the MMPP model and the Fluid
Approximation model fit best, respectively, the cell region and the
burst region. Therefore, a hybrid MMPP and FAM completely
characterizes the overall performance of the ATM statistical
multiplexer. The ramifications of this technology are clear: speed,
reliability (lower loss rate and jitter), and increased capacity in video
transmission for telemedicine. With migration to full IP-based
networks still a long way to achieving both high speed and high
quality of service, the proposed ATM architecture will remain of
significant use for telemedicine.
Abstract: In this paper, a single period inventory model with resalable returns has been analyzed in an imprecise and uncertain mixed environment. Demand has been introduced as a fuzzy random variable. In this model, a single order is placed before the start of the selling season. The customer, for a full refund, may return purchased products within a certain time interval. Returned products are resalable, provided they arrive back before the end of the selling season and are found to be undamaged. Products remaining at the end of the season are salvaged. All demands not met directly are lost. The probabilities that a sold product is returned and that a returned product is resalable, both imprecise in a real situation, have been assumed to be fuzzy in nature.
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 objective of this study is to present the test
results of variable air volume (VAV) air conditioning system
optimized by two objective genetic algorithm (GA). The objective
functions are energy savings and thermal comfort. The optimal set
points for fuzzy logic controller (FLC) are the supply air temperature
(Ts), the supply duct static pressure (Ps), the chilled water
temperature (Tw), and zone temperature (Tz) that is taken as the
problem variables. Supply airflow rate and chilled water flow rate are
considered to be the constraints. The optimal set point values are
obtained from GA process and assigned into fuzzy logic controller
(FLC) in order to conserve energy and maintain thermal comfort in
real time VAV air conditioning system. A VAV air conditioning
system with FLC installed in a software laboratory has been taken for
the purpose of energy analysis. The total energy saving obtained in
VAV GA optimization system with FLC compared with constant air
volume (CAV) system is expected to achieve 31.5%. The optimal
duct static pressure obtained through Genetic fuzzy methodology
attributes to better air distribution by delivering the optimal quantity
of supply air to the conditioned space. This combination enhanced
the advantages of uniform air distribution, thermal comfort and
improved energy savings potential.
Abstract: The purpose of this paper is to present the design and
instrumentation of a new benchmark multivariable nonlinear control
laboratory. The mathematical model of this system may be used to
test the applicability and performance of various nonlinear control
procedures. The system is a two degree-of-freedom robotic arm with
soft and hard (discontinuous) nonlinear terms. Two novel
mechanisms are designed to allow the implementation of adjustable
Coulomb friction and backlash.
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 main objectives of this study were to identify
attributes that influence customer satisfaction and determine their
relationships with customer satisfaction. The variables included in
this research are place/ambience, food quality and service quality as
independent variables and customer satisfaction as the dependent
variable. A survey questionnaire which consisted of three parts to
measure demographic factors, independent variables, and dependent
variables was constructed based on items determined by past
research. 149 respondents from one of the well known hotel in Kuala
Lumpur, MALAYSIA were selected as a sample. Psychometric
testing was conducted to determine the reliability and validity of the
questionnaire. From the findings, there were positive significant
relationship between place/ambience (r=0.563**, p=0.000) and
service quality (r=0.544**, p=0.000) with customer satisfaction.
However, although relationship between food quality and customer
satisfaction was significant, it was in the negative direction (r=-
0.268**, p=0.001). New findings were discovered after conducting
this research and previous research findings were strengthened by the
results of this research. Future researchers could concentrate on
determining attributes that influence customer satisfaction when
cost/price is not a factor and reasons for place/ambience is currently
becoming the leading factor in determining customer satisfaction.
Abstract: In this article, we consider the estimation of P[Y < X], when strength, X and stress, Y are two independent variables of Burr Type XII distribution. The MLE of the R based on one simple iterative procedure is obtained. Assuming that the common parameter is known, the maximum likelihood estimator, uniformly minimum variance unbiased estimator and Bayes estimator of P[Y < X] are discussed. The exact confidence interval of the R is also obtained. Monte Carlo simulations are performed to compare the different proposed methods.
Abstract: Islamic institutions in Malaysia play a variety of
socioeconomic roles such as poverty alleviation. To perform this role,
these institutions face a major task in identifying the poverty group.
Most of these institutions measure and operationalize poverty from
the monetary perspective using variables such as income, expenditure
or consumption. In practice, most Islamic institutions in Malaysia use
the monetary approach in measuring poverty through the
conventional Poverty Line Income (PLI) method and recently, the
had al kifayah (HAK) method using total necessities of a household
from an Islamic perspective. The objective of this paper is to present
the PLI and also the HAK method. This micro-data study would
highlight the similarities and differences of both the methods.A
survey aided by a structured questionnaire was carried out on 260
selected head of households in the state of Selangor. The paper
highlights several demographic factors that are associated with the
three monetary indicators in the study, namely income, PLI and
HAK. In addition, the study found that these monetary variables are
significantly related with each other.
Abstract: This qualitative, quantitative mixed-method study explores how students- motivation and interest in creative hands-on activities affected their conceptual understanding of science. The objectives of this research include developing a greater understanding about how creative activities, incorporated into the classroom as instructional strategies, increase student motivation and their learning or mastery of science concepts. The creative activities are viewed as a motivational tool, a specific type of task, which have an impact on student goals. Pre-and-post tests, pre-and-post interviews, and student responses measure motivational-goal theory variables, interest in the activity, and conceptual change. Implications for education and future research will be discussed.
Abstract: This study presents energy saving in general-purpose
pumps widely used in industrial applications. Such pumps are
normally driven by a constant-speed electrical motor which in most
applications must support varying load conditions. This is equivalent
to saying the loading conditions mismatch the designed optimal
energy consumption requirements of the intended application thus
resulting in substantial energy losses. In the held experiments it was
indicated that combination of mechanical and electrical speed drives
can contribute to lower energy consumption in the pump without
negatively distorting the required performance indices of a typical
centrifugal pump at substantially lower energy consumption. The
registered energy savings were recorded to be within the 15-40%
margin. It was also indicated that although VSDs are installed at a
cost, the financial burden is balanced against the earnings resulting
from the associated energy savings.
Abstract: this paper presents an auto-regressive network called the Auto-Regressive Multi-Context Recurrent Neural Network (ARMCRN), which forecasts the daily peak load for two large power plant systems. The auto-regressive network is a combination of both recurrent and non-recurrent networks. Weather component variables are the key elements in forecasting because any change in these variables affects the demand of energy load. So the AR-MCRN is used to learn the relationship between past, previous, and future exogenous and endogenous variables. Experimental results show that using the change in weather components and the change that occurred in past load as inputs to the AR-MCRN, rather than the basic weather parameters and past load itself as inputs to the same network, produce higher accuracy of predicted load. Experimental results also show that using exogenous and endogenous variables as inputs is better than using only the exogenous variables as inputs to the network.
Abstract: The Time-Domain Boundary Element Method (TDBEM)
is a well known numerical technique that handles quite
properly dynamic analyses considering infinite dimension media.
However, when these analyses are also related to nonlinear behavior,
very complex numerical procedures arise considering the TD-BEM,
which may turn its application prohibitive. In order to avoid this
drawback and model nonlinear infinite media, the present work
couples two BEM formulations, aiming to achieve the best of two
worlds. In this context, the regions expected to behave nonlinearly
are discretized by the Domain Boundary Element Method (D-BEM),
which has a simpler mathematical formulation but is unable to deal
with infinite domain analyses; the TD-BEM is employed as in the
sense of an effective non-reflexive boundary. An iterative procedure
is considered for the coupling of the TD-BEM and D-BEM, which is
based on a relaxed renew of the variables at the common interfaces.
Elastoplastic models are focused and different time-steps are allowed
to be considered by each BEM formulation in the coupled analysis.
Abstract: A bond graph model of an electrical transformer
including the nonlinear saturation is presented. A nonlinear observer for the transformer based on multivariable circle
criterion in the physical domain is proposed. In order to show the saturation and hysteresis effects on the electrical transformer,
simulation results are obtained. Finally, the paper describes that convergence of the estimates to the true states is achieved.
Abstract: The paper explores the development of an optimization of method and apparatus for retrieving extended high dynamic range from digital negative image. Architectural photo imaging can benefit from high dynamic range imaging (HDRI) technique for preserving and presenting sufficient luminance in the shadow and highlight clipping image areas. The HDRI technique that requires multiple exposure images as the source of HDRI rendering may not be effective in terms of time efficiency during the acquisition process and post-processing stage, considering it has numerous potential imaging variables and technical limitations during the multiple exposure process. This paper explores an experimental method and apparatus that aims to expand the dynamic range from digital negative image in HDRI environment. The method and apparatus explored is based on a single source of RAW image acquisition for the use of HDRI post-processing. It will cater the optimization in order to avoid and minimize the conventional HDRI photographic errors caused by different physical conditions during the photographing process and the misalignment of multiple exposed image sequences. The study observes the characteristics and capabilities of RAW image format as digital negative used for the retrieval of extended high dynamic range process in HDRI environment.