Abstract: This work presents a new algorithm based on a combination of fuzzy (FUZ), Dynamic Programming (DP), and Genetic Algorithm (GA) approach for capacitor allocation in distribution feeders. The problem formulation considers two distinct objectives related to total cost of power loss and total cost of capacitors including the purchase and installation costs. The novel formulation is a multi-objective and non-differentiable optimization problem. The proposed method of this article uses fuzzy reasoning for sitting of capacitors in radial distribution feeders, DP for sizing and finally GA for finding the optimum shape of membership functions which are used in fuzzy reasoning stage. The proposed method has been implemented in a software package and its effectiveness has been verified through a 9-bus radial distribution feeder for the sake of conclusions supports. A comparison has been done among the proposed method of this paper and similar methods in other research works that shows the effectiveness of the proposed method of this paper for solving optimum capacitor planning problem.
Abstract: The combustion of liquid fuel in the porous burner
(PB) was experimented to investigate evaporation mechanism and
combustion behavior. The diesel oil was used as fuel and the pebbles
carefully chosen in the same size like the solid sphere homogeneously
was adopted as the porous media. Two structures of the liquid porous
burner, i.e. the PB without and with installation of porous emitter
(PE), were performed. PE was installed by lower than PB with
distance of 20 cm. The pebbles having porosity (φ) of 0.45 and 0.52
were, respectively, used in PB and PE. The fuel was supplied dropwise
from the top through the PB and the combustion was occurred between
PB and PE. Axial profiles of temperature along the burner length were
measured to clarify the evaporation and combustion phenomena. The
pollutant emission characteristics were monitored at the burner exit.
From the experiment, it was found that the temperature profiles of both
structures decreased with the three ways swirling air flows (QA)
increasing. On the other hand, the temperature profiles increased with
fuel heat input (QF). Obviously, the profile of the porous burner
installed with PE was higher than that of the porous burner without
PE
Abstract: Content-based Image Retrieval (CBIR) aims at searching image databases for specific images that are similar to a given query image based on matching of features derived from the image content. This paper focuses on a low-dimensional color based indexing technique for achieving efficient and effective retrieval performance. In our approach, the color features are extracted using the mean shift algorithm, a robust clustering technique. Then the cluster (region) mode is used as representative of the image in 3-D color space. The feature descriptor consists of the representative color of a region and is indexed using a spatial indexing method that uses *R -tree thus avoiding the high-dimensional indexing problems associated with the traditional color histogram. Alternatively, the images in the database are clustered based on region feature similarity using Euclidian distance. Only representative (centroids) features of these clusters are indexed using *R -tree thus improving the efficiency. For similarity retrieval, each representative color in the query image or region is used independently to find regions containing that color. The results of these methods are compared. A JAVA based query engine supporting query-by- example is built to retrieve images by color.
Abstract: Several valve stiction models have been proposed in the literature to help understand and study the behavior of sticky valves. In this paper, an alternative black-box modeling approach based on Neural Network (NN) is presented. It is shown that with proper network type and optimum model structures, the performance of the developed NN stiction model is comparable to other established method. The resulting NN model is also tested for its robustness against the uncertainty in the stiction parameter values. Predictive mode operation also shows excellent performance of the proposed model for multi-steps ahead prediction.
Abstract: With the increasing number of on-chip components and the critical requirement for processing power, Chip Multiprocessor (CMP) has gained wide acceptance in both academia and industry during the last decade. However, the conventional bus-based onchip communication schemes suffer from very high communication delay and low scalability in large scale systems. Network-on-Chip (NoC) has been proposed to solve the bottleneck of parallel onchip communications by applying different network topologies which separate the communication phase from the computation phase. Observing that the memory bandwidth of the communication between on-chip components and off-chip memory has become a critical problem even in NoC based systems, in this paper, we propose a novel 3D NoC with on-chip Dynamic Random Access Memory (DRAM) in which different layers are dedicated to different functionalities such as processors, cache or memory. Results show that, by using our proposed architecture, average link utilization has reduced by 10.25% for SPLASH-2 workloads. Our proposed design costs 1.12% less execution cycles than the traditional design on average.
Abstract: The load frequency control problem of power systems has attracted a lot of attention from engineers and researchers over the years. Increasing and quickly changing load demand, coupled with the inclusion of more generators with high variability (solar and wind power generators) on the network are making power systems more difficult to regulate. Frequency changes are unavoidable but regulatory authorities require that these changes remain within a certain bound. Engineers are required to perform the tricky task of adjusting the control system to maintain the frequency within tolerated bounds. It is well known that to minimize frequency variations, a large proportional feedback gain (speed regulation constant) is desirable. However, this improvement in performance using proportional feedback comes about at the expense of a reduced stability margin and also allows some steady-state error. A conventional PI controller is then included as a secondary control loop to drive the steadystate error to zero. In this paper, we propose a robust controller to replace the conventional PI controller which guarantees performance and stability of the power system over the range of variation of the speed regulation constant. Simulation results are shown to validate the superiority of the proposed approach on a simple single-area power system model.
Abstract: The objectives of this research are to search the
management pattern of Bang Khonthi lodging entrepreneurs for
sufficient economy ways, to know the threat that affects this sector
and design fit arrangement model to sustain their business with
Samut Songkram style. What will happen if they do not use this
approach? Will they have a financial crisis? The data and information
are collected by informal discussions with 8 managers and 400
questionnaires. A mixed methods of both qualitative research and
quantitative research are used. Bent Flyvbjerg-s phronesis is utilized
for this analysis. Our research will prove that sufficient economy can
help small business firms to solve their problems. We think that the
results of our research will be a financial model to solve many
problems of the entrepreneurs and this way will can be a model for
other provinces of Thailand.
Abstract: Stochastic resonance (SR) is a phenomenon whereby
the signal transmission or signal processing through certain nonlinear
systems can be improved by adding noise. This paper discusses SR in
nonlinear signal detection by a simple test statistic, which can be
computed from multiple noisy data in a binary decision problem based
on a maximum a posteriori probability criterion. The performance of
detection is assessed by the probability of detection error Per . When
the input signal is subthreshold signal, we establish that benefit from
noise can be gained for different noises and confirm further that the
subthreshold SR exists in nonlinear signal detection. The efficacy of
SR is significantly improved and the minimum of Per can
dramatically approach to zero as the sample number increases. These
results show the robustness of SR in signal detection and extend the
applicability of SR in signal processing.
Abstract: In the last decades, a number of robust fuzzy clustering algorithms have been proposed to partition data sets affected by noise and outliers. Robust fuzzy C-means (robust-FCM) is certainly one of the most known among these algorithms. In robust-FCM, noise is modeled as a separate cluster and is characterized by a prototype that has a constant distance δ from all data points. Distance δ determines the boundary of the noise cluster and therefore is a critical parameter of the algorithm. Though some approaches have been proposed to automatically determine the most suitable δ for the specific application, up to today an efficient and fully satisfactory solution does not exist. The aim of this paper is to propose a novel method to compute the optimal δ based on the analysis of the distribution of the percentage of objects assigned to the noise cluster in repeated executions of the robust-FCM with decreasing values of δ . The extremely encouraging results obtained on some data sets found in the literature are shown and discussed.
Abstract: This paper proposes an investment cost recovery
based efficient and fast sequential optimization approach to optimal
allocation of thyristor controlled series compensator (TCSC) in
competitive power market. The optimization technique has been used
with an objective to maximizing the social welfare and minimizing
the device installation cost by suitable location and rating of TCSC in
the system. The effectiveness of proposed approach for location of
TCSC has been compared with some existing methods of TCSC
placement, in terms of its impact on social welfare, TCSC investment
recovery and optimal generation as well as load patterns. The results
have been obtained on modified IEEE 14-bus system.
Abstract: This paper proposes an analytical method for the
dynamics of generating firms- alliance networks along with business
phases. Dynamics in network developments have previously been
discussed in the research areas of organizational strategy rather than in
the areas of regional cluster, where the static properties of the
networks are often discussed. The analytical method introduces the
concept of business phases into innovation processes and uses
relationships called prior experiences; this idea was developed in
organizational strategy to investigate the state of networks from the
viewpoints of tradeoffs between link stabilization and node
exploration. This paper also discusses the results of the analytical
method using five cases of the network developments of firms. The
idea of Embeddedness helps interpret the backgrounds of the
analytical results. The analytical method is useful for policymakers of
regional clusters to establish concrete evaluation targets and a
viewpoint for comparisons of policy programs.
Abstract: Homogeneous Charge Compression (HCCI) Ignition technology has been around for a long time, but has recently received renewed attention and enthusiasm. This paper deals with experimental investigations of HCCI engine using hydrous methanol as a primary fuel and Dimethyl Ether (DME) as an ignition improver. A regular diesel engine has been modified to work as HCCI engine for this investigation. The hydrous methanol is inducted and DME is injected into a single cylinder engine. Hence, hydrous methanol is used with 15% water content in HCCI engine and its performance and emission behavior is documented. The auto-ignition of Methanol is enabled by DME. The quantity of DME varies with respect to the load. In this study, the experiments are conducted independently and the effect of the hydrous methanol on the engine operating limit, heat release rate and exhaust emissions at different load conditions are investigated. The investigation also proves that the Hydrous Methanol with DME operation reduces the oxides of Nitrogen and smoke to an extreme low level which is not possible by the direct injection CI engine. Therefore, it is beneficial to use hydrous methanol-DME HCCI mode while using hydrous methanol in internal Combustion Engines.
Abstract: This paper presents the experimental results on effect of applied voltage stress frequency to the occurrence of electrical treeing in 22 kV cross linked polyethylene (XLPE) insulated cable.Hallow disk of XLPE insulating material with thickness 5 mm taken from unused high voltage cable was used as the specimen in this study. Stainless steel needle was inserted gradually into the specimen to give a tip to earth plane electrode separation of 2.50.2 mm at elevated temperature 105-110°C. The specimen was then annealed for 5 minute to minimize any mechanical stress build up around the needle-plane region before it was cooled down to room temperature. Each specimen were subjected to the same applied voltage stress level at 8 kV AC rms, with various frequency, 50, 100, 500, 1000 and 2000 Hz. Initiation time, propagation speed and pattern of electrical treeing were examined in order to study the effect of applied voltage stress frequency. By the experimental results, initial time of visible treeing decreases with increasing in applied voltage frequency. Also, obviously, propagation speed of electrical treeing increases with increasing in applied voltage frequency.Furthermore, two types of electrical treeing, bush-like and branch-like treeing were observed.The experimental results confirmed the effect of voltage stress frequency as well.
Abstract: Image watermarking has proven to be quite an
efficient tool for the purpose of copyright protection and
authentication over the last few years. In this paper, a novel image
watermarking technique in the wavelet domain is suggested and
tested. To achieve more security and robustness, the proposed
techniques relies on using two nested watermarks that are embedded
into the image to be watermarked. A primary watermark in form of a
PN sequence is first embedded into an image (the secondary
watermark) before being embedded into the host image. The
technique is implemented using Daubechies mother wavelets where
an arbitrary embedding factor α is introduced to improve the
invisibility and robustness. The proposed technique has been applied
on several gray scale images where a PSNR of about 60 dB was
achieved.
Abstract: Educational institutions increasingly adopt the
students-as-customers concept to satisfy their students.
Understanding students- perspectives on the use of this business
concept in educational institutions is necessary for the institutions to
effectively align these perspectives with their management practice.
The study investigates whether students in technology and business
disciplines have significantly different attitudes toward using the
students-as-customers concept in educational institutions and
explores the impact of treating students as customers in technology
disciplines under students- perspectives. The results from
quantitative and qualitative data analyses show that technology
students, in contrast to business students, fairly disagree with
educational institutions to treat students as customers. Treating
students as customers in technology disciplines will have a negative
influence on teaching performance, instructor-student relationships
and educational institutions- aim, but a positive influence on service
quality in educational institutions. The paper discusses the findings
and concludes with implications and limitations of the study.
Abstract: In this manuscript, a wavelet-based blind
watermarking scheme has been proposed as a means to provide
security to authenticity of a fingerprint. The information used for
identification or verification of a fingerprint mainly lies in its
minutiae. By robust watermarking of the minutiae in the fingerprint
image itself, the useful information can be extracted accurately even
if the fingerprint is severely degraded. The minutiae are converted in
a binary watermark and embedding these watermarks in the detail
regions increases the robustness of watermarking, at little to no
additional impact on image quality. It has been experimentally shown
that when the minutiae is embedded into wavelet detail coefficients
of a fingerprint image in spread spectrum fashion using a
pseudorandom sequence, the robustness is observed to have a
proportional response while perceptual invisibility has an inversely
proportional response to amplification factor “K". The DWT-based
technique has been found to be very robust against noises,
geometrical distortions filtering and JPEG compression attacks and is
also found to give remarkably better performance than DCT-based
technique in terms of correlation coefficient and number of erroneous
minutiae.
Abstract: Today's business environment requires that companies have access to highly relevant information in a matter of seconds.
Modern Business Intelligence tools rely on data structured mostly in traditional dimensional database schemas, typically represented by
star schemas. Dimensional modeling is already recognized as a
leading industry standard in the field of data warehousing although
several drawbacks and pitfalls were reported. This paper focuses on
the analysis of another data warehouse modeling technique - the
anchor modeling, and its characteristics in context with the standardized dimensional modeling technique from a query performance perspective. The results of the analysis show
information about performance of queries executed on database
schemas structured according to principles of each database modeling
technique.
Abstract: This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of Pulping of Sugar Maple problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified problem where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.
Abstract: Product customization is an essential requirement for
manufacturing firms to achieve higher customers- satisfaction and
fulfill business target. In order to achieve these objectives, firms need
to handle both external varieties such as customer preference,
government regulations, cultural considerations etc and internal
varieties such as functional requirements of product, production
efficiency, quality etc. Both of the varieties need to be accumulated
and integrated together for the purpose of producing customized
product. These varieties are presented and discussed in this paper
along with the perspectives of modular product design and
development process. Other development strategies such as
modularity, component commonality, product family design and
product platform are presented with a view to achieve product variety
quickly and economically. A case example both for the concept of
modular design and platform based product development process is
also presented with the help of design structure matrix (DSM) tool.
This paper is concluded with several managerial implications and
future research direction.
Abstract: Robust face recognition under various illumination
environments is very difficult and needs to be accomplished for
successful commercialization. In this paper, we propose an improved
illumination normalization method for face recognition. Illumination
normalization algorithm based on anisotropic smoothing is well known
to be effective among illumination normalization methods but
deteriorates the intensity contrast of the original image, and incurs less
sharp edges. The proposed method in this paper improves the previous
anisotropic smoothing-based illumination normalization method so
that it increases the intensity contrast and enhances the edges while
diminishing the effect of illumination variations. Due to the result of
these improvements, face images preprocessed by the proposed
illumination normalization method becomes to have more distinctive
feature vectors (Gabor feature vectors) for face recognition. Through
experiments of face recognition based on Gabor feature vector
similarity, the effectiveness of the proposed illumination
normalization method is verified.