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: Array signal processing involves signal enumeration and source localization. Array signal processing is centered on the ability to fuse temporal and spatial information captured via sampling signals emitted from a number of sources at the sensors of an array in order to carry out a specific estimation task: source characteristics (mainly localization of the sources) and/or array characteristics (mainly array geometry) estimation. Array signal processing is a part of signal processing that uses sensors organized in patterns or arrays, to detect signals and to determine information about them. Beamforming is a general signal processing technique used to control the directionality of the reception or transmission of a signal. Using Beamforming we can direct the majority of signal energy we receive from a group of array. Multiple signal classification (MUSIC) is a highly popular eigenstructure-based estimation method of direction of arrival (DOA) with high resolution. This Paper enumerates the effect of missing sensors in DOA estimation. The accuracy of the MUSIC-based DOA estimation is degraded significantly both by the effects of the missing sensors among the receiving array elements and the unequal channel gain and phase errors of the receiver.
Abstract: Distance visualization of large datasets often takes the direction of remote viewing and zooming techniques of stored static images. However, the continuous increase in the size of datasets and visualization operation causes insufficient performance with traditional desktop computers. Additionally, the visualization techniques such as Isosurface depend on the available resources of the running machine and the size of datasets. Moreover, the continuous demand for powerful computing powers and continuous increase in the size of datasets results an urgent need for a grid computing infrastructure. However, some issues arise in current grid such as resources availability at the client machines which are not sufficient enough to process large datasets. On top of that, different output devices and different network bandwidth between the visualization pipeline components often result output suitable for one machine and not suitable for another. In this paper we investigate how the grid services could be used to support remote visualization of large datasets and to break the constraint of physical co-location of the resources by applying the grid computing technologies. We show our grid enabled architecture to visualize large medical datasets (circa 5 million polygons) for remote interactive visualization on modest resources clients.
Abstract: Many-core GPUs provide high computing ability and
substantial bandwidth; however, optimizing irregular applications
like SpMV on GPUs becomes a difficult but meaningful task. In this
paper, we propose a novel method to improve the performance of
SpMV on GPUs. A new storage format called HYB-R is proposed to
exploit GPU architecture more efficiently. The COO portion of the
matrix is partitioned recursively into a ELL portion and a COO
portion in the process of creating HYB-R format to ensure that there
are as many non-zeros as possible in ELL format. The method of
partitioning the matrix is an important problem for HYB-R kernel, so
we also try to tune the parameters to partition the matrix for higher
performance. Experimental results show that our method can get
better performance than the fastest kernel (HYB) in NVIDIA-s
SpMV library with as high as 17% speedup.
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: This paper studies dynamic stability of homogeneous
beams with piezoelectric layers subjected to periodic axial
compressive load that is simply supported at both ends lies on a
continuous elastic foundation. The displacement field of beam is
assumed based on Bernoulli-Euler beam theory. Applying the
Hamilton's principle, the governing dynamic equation is established.
The influences of applied voltage, foundation coefficient and
piezoelectric thickness on the unstable regions are presented. To
investigate the accuracy of the present analysis, a compression study
is carried out with a known data.
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: This paper focuses on PSS/E modeling of wind farms
of Doubly-fed Induction Generator (DFIG) type and their impact on
issues of power system operation. Since Wind Turbine Generators
(WTG) don-t have the same characteristics as synchronous
generators, the appropriate modeling of wind farms is essential for
transmission system operators to analyze the best options of
transmission grid reinforcements as well as to evaluate the wind
power impact on reliability and security of supply. With the high
excepted penetration of wind power into the power system a
simultaneous loss of Wind Farm generation will put at risk power
system security and reliability. Therefore, the main wind grid code
requirements concern the fault ride through capability and frequency
operation range of wind turbines. In case of grid faults wind turbines
have to supply a definite reactive power depending on the
instantaneous voltage and to return quickly to normal operation.
Abstract: The concept of flexible manufacturing is highly
appealing in gaining a competitive edge in the market by quickly
adapting to the changing customer needs. Scheduling jobs on flexible
manufacturing systems (FMSs) is a challenging task of managing the
available flexibility on the shop floor to react to the dynamics of the
environment in real-time. In this paper, an agent-oriented scheduling
framework that can be integrated with a real or a simulated FMS is
proposed. This framework works in stochastic environments with a
dynamic model of job arrival. It supports a hierarchical cooperative
scheduling that builds on the available flexibility of the shop floor.
Testing the framework on a model of a real FMS showed the
capability of the proposed approach to overcome the drawbacks of
the conventional approaches and maintain a near optimal solution
despite the dynamics of the operational environment.
Abstract: This paper presents an application of particle swarm
optimization (PSO) to the grounding grid planning which compares to
the application of genetic algorithm (GA). Firstly, based on IEEE
Std.80, the cost function of the grounding grid and the constraints of
ground potential rise, step voltage and touch voltage are constructed
for formulating the optimization problem of grounding grid planning.
Secondly, GA and PSO algorithms for obtaining optimal solution of
grounding grid are developed. Finally, a case of grounding grid
planning is shown the superiority and availability of the PSO
algorithm and proposal planning results of grounding grid in cost and
computational time.
Abstract: Teaching and learning about sustainability is a pedagogical endeavour with various innate difficulties and increased demands. Higher education has a dual role to play in addressing this challenge: to identify and explore innovative approaches and tools for addressing the complex and value-laden nature of sustainability in more meaningful ways, and to help teachers to integrate these approaches into their practice through appropriate professional development programs. The study reported here was designed and carried out within the context of a Masters course in Environmental Education. Eight teachers were collaboratively engaged in reconstructing a digital game microworld which was deliberately designed by the researchers to be questioned and evoke critical discussion on the idea of ‘sustainable city’. The study was based on the design-based research method. The findings indicate that the teachers’ involvement in processes of co-constructing the microworld initiated discussion and reflection upon the concepts of sustainability and sustainable lifestyles.
Abstract: The objective of this work is to present a expertise on
flooding hazard analysis and how to reduce the risk. The analysis
concerns the disaster induced by the flood on November 10/11, 2001
in the Bab El Oued district of the city of Algiers.The study begins by
an expertise of damages in related with the urban environment and
the history of the urban growth of the site. After this phase, the work
is focalized on the identification of the existing correlations between
the development of the town and its vulnerability. The final step
consists to elaborate the interpretations on the interactions between
the urban growth, the sewerage network and the vulnerability of the
urban system.In conclusion, several recommendations are formulated
permitting the mitigation of the risk in the future. The principal
recommendations concern the new urban operations and the existing
urbanized sites.
Abstract: This paper evaluates the association between
economic environment in the districts of Madrid (Spain) and physical
inactivity, using income per capita as indicator of economic
environment. The analysis included 6,601 individuals aged 16 to 74
years. The measure of association estimated was the prevalence odds
ratio for physical inactivity by income per capita. After adjusting for
sex, age, and individual socioeconomic characteristics, people living
in the districts with the lowest per capita income had an odds ratio for
physical inactivity 1.58 times higher (95% confidence interval 1.35 to
1.85) than those living in districts with the highest per capita income.
Additional adjustment for the availability of sports facilities in each
district did not decrease the magnitude of the association. These
findings show that the widely believed assumption that the
availability of sports and recreational facilities, as a possible
explanation for the relation between economic environment and
physical inactivity, cannot be considered a universal observation.
Abstract: It is difficult to judge ripeness by outward
characteristics such as size or external color. In this paper a nondestructive
method was studied to determine watermelon (Crimson
Sweet) quality. Responses of samples to excitation vibrations were
detected using laser Doppler vibrometry (LDV) technology. Phase
shift between input and output vibrations were extracted overall
frequency range. First and second were derived using frequency
response spectrums. After nondestructive tests, watermelons were
sensory evaluated. So the samples were graded in a range of ripeness
based on overall acceptability (total desired traits consumers).
Regression models were developed to predict quality using obtained
results and sample mass. The determination coefficients of the
calibration and cross validation models were 0.89 and 0.71
respectively. This study demonstrated feasibility of information
which is derived vibration response curves for predicting fruit
quality. The vibration response of watermelon using the LDV method
is measured without direct contact; it is accurate and timely, which
could result in significant advantage for classifying watermelons
based on consumer opinions.
Abstract: This paper describes the historical development of
interethnic concord in the Republic of Kazakhstan, and emphasizes
the role of tolerance mentality of the Kazakh people in ethno-political
policy of the country. Moreover, pointing out interethnic concord as a
powerful stabilizing factor, it analyses the specifics of interethnic
policy in multinational Kazakh society. It summarizes that the culture
of interethnic concord can be a model of ethno- political policy of
Kazakhstan.
Abstract: This paper considers the influence of promotion
instruments for renewable energy sources (RES) on a multi-energy
modeling framework. In Europe, so called Feed-in Tariffs are
successfully used as incentive structures to increase the amount of
energy produced by RES. Because of the stochastic nature of large
scale integration of distributed generation, many problems have
occurred regarding the quality and stability of supply. Hence, a
macroscopic model was developed in order to optimize the power
supply of the local energy infrastructure, which includes electricity,
natural gas, fuel oil and district heating as energy carriers. Unique
features of the model are the integration of RES and the adoption of
Feed-in Tariffs into one optimization stage. Sensitivity studies are
carried out to examine the system behavior under changing profits
for the feed-in of RES. With a setup of three energy exchanging
regions and a multi-period optimization, the impact of costs and
profits are determined.
Abstract: The decisions made by admission control algorithms are
based on the availability of network resources viz. bandwidth, energy,
memory buffers, etc., without degrading the Quality-of-Service (QoS)
requirement of applications that are admitted. In this paper, we
present an energy-aware admission control (EAAC) scheme which
provides admission control for flows in an ad hoc network based
on the knowledge of the present and future residual energy of the
intermediate nodes along the routing path. The aim of EAAC is to
quantify the energy that the new flow will consume so that it can
be decided whether the future residual energy of the nodes along
the routing path can satisfy the energy requirement. In other words,
this energy-aware routing admits a new flow iff any node in the
routing path does not run out of its energy during the transmission
of packets. The future residual energy of a node is predicted using
the Multi-layer Neural Network (MNN) model. Simulation results
shows that the proposed scheme increases the network lifetime. Also
the performance of the MNN model is presented.
Abstract: The linear methods of heart rate variability analysis
such as non-parametric (e.g. fast Fourier transform analysis) and
parametric methods (e.g. autoregressive modeling) has become an
established non-invasive tool for marking the cardiac health, but their
sensitivity and specificity were found to be lower than expected with
positive predictive value
Abstract: This study examines the relevance of disclosure
practices in improving the accountability and transparency of
religious nonprofit organizations (RNPOs). The assessment of
disclosure is based on the annual returns of RNPOs for the financial
year 2010. In order to quantify the information disclosed in the
annual returns, partial disclosure indexes of basic information (BI)
disclosure index, financial information (FI) disclosure index and
governance information (GI) disclosure index have been built which
takes into account the content of information items in the annual
returns. The empirical evidence obtained revealed low disclosure
practices among RNPOs in the sample. The multiple regression
results showed that the organizational attribute of the board size
appeared to be the most significant predictor for both partial index on
the extent of BI disclosure index, and FI disclosure index. On the
other hand, the extent of financial information disclosure is related to
the amount of donation received by RNPOs. On GI disclosure index,
the existence of an external audit appeared to be significant variable.
This study has contributed to the academic literature in providing
empirical evidence of the disclosure practices among RNPOs.
Abstract: Soil organic carbon (SOC) plays a key role in soil
fertility, hydrology, contaminants control and acts as a sink or source
of terrestrial carbon content that can affect the concentration of
atmospheric CO2. SOC supports the sustainability and quality of
ecosystems, especially in semi-arid region. This study was
conducted to determine relative importance of 13 different
exploratory climatic, soil and geometric factors on the SOC contents
in one of the semiarid watershed zones in Iran. Two methods
canonical discriminate analysis (CDA) and feed-forward back
propagation neural networks were used to predict SOC. Stepwise
regression and sensitivity analysis were performed to identify
relative importance of exploratory variables. Results from sensitivity
analysis showed that 7-2-1 neural networks and 5 inputs in CDA
models output have highest predictive ability that explains %70 and
%65 of SOC variability. Since neural network models outperformed
CDA model, it should be preferred for estimating SOC.