Abstract: Cosmic showers, from their places of origin in space,
after entering earth generate secondary particles called Extensive Air
Shower (EAS). Detection and analysis of EAS and similar High
Energy Particle Showers involve a plethora of experimental setups
with certain constraints for which soft-computational tools like
Artificial Neural Network (ANN)s can be adopted. The optimality
of ANN classifiers can be enhanced further by the use of Multiple
Classifier System (MCS) and certain data - dimension reduction
techniques. This work describes the performance of certain data
dimension reduction techniques like Principal Component Analysis
(PCA), Independent Component Analysis (ICA) and Self Organizing
Map (SOM) approximators for application with an MCS formed
using Multi Layer Perceptron (MLP), Recurrent Neural Network
(RNN) and Probabilistic Neural Network (PNN). The data inputs are
obtained from an array of detectors placed in a circular arrangement
resembling a practical detector grid which have a higher dimension
and greater correlation among themselves. The PCA, ICA and SOM
blocks reduce the correlation and generate a form suitable for real
time practical applications for prediction of primary energy and
location of EAS from density values captured using detectors in a
circular grid.
Abstract: Both the minimum energy consumption and
smoothness, which is quantified as a function of jerk, are generally
needed in many dynamic systems such as the automobile and the
pick-and-place robot manipulator that handles fragile equipments.
Nevertheless, many researchers come up with either solely
concerning on the minimum energy consumption or minimum jerk
trajectory. This research paper proposes a simple yet very interesting
relationship between the minimum direct and indirect jerks
approaches in designing the time-dependent system yielding an
alternative optimal solution. Extremal solutions for the cost functions
of direct and indirect jerks are found using the dynamic optimization
methods together with the numerical approximation. This is to allow
us to simulate and compare visually and statistically the time history
of control inputs employed by minimum direct and indirect jerk
designs. By considering minimum indirect jerk problem, the
numerical solution becomes much easier and yields to the similar
results as minimum direct jerk problem.
Abstract: The Maximum Weighted Independent Set (MWIS)
problem is a classic graph optimization NP-hard problem. Given an
undirected graph G = (V, E) and weighting function defined on the
vertex set, the MWIS problem is to find a vertex set S V whose total
weight is maximum subject to no two vertices in S are adjacent. This
paper presents a novel approach to approximate the MWIS of a graph
using minimum weighted vertex cover of the graph. Computational
experiments are designed and conducted to study the performance
of our proposed algorithm. Extensive simulation results show that
the proposed algorithm can yield better solutions than other existing
algorithms found in the literature for solving the MWIS.
Abstract: This paper proposes a balance control scheme for a biped robot to trace an arbitrary path using image information. While moving, it estimates the zero moment point(ZMP) of the biped robot in the next step using a Kalman filter and renders an appropriate balanced pose of the robot. The ZMP can be calculated from the robot's pose, which is measured from the reference object image acquired by a CCD camera on the robot's head. For simplifying the kinematical model, the coordinates systems of individual joints of each leg are aligned and the robot motion is approximated as an inverted pendulum so that a simple linear dynamics, 3D-LIPM(3D-Linear Inverted Pendulum Mode) can be applied. The efficiency of the proposed algorithm has been proven by the experiments performed on unknown trajectory.
Abstract: A Picard-Newton iteration method is studied to accelerate the numerical solution procedure of a class of two-dimensional nonlinear coupled parabolic-hyperbolic system. The Picard-Newton iteration is designed by adding higher-order terms of small quantity to an existing Picard iteration. The discrete functional analysis and inductive hypothesis reasoning techniques are used to overcome difficulties coming from nonlinearity and coupling, and theoretical analysis is made for the convergence and approximation properties of the iteration scheme. The Picard-Newton iteration has a quadratic convergent ratio, and its solution has second order spatial approximation and first order temporal approximation to the exact solution of the original problem. Numerical tests verify the results of the theoretical analysis, and show the Picard-Newton iteration is more efficient than the Picard iteration.
Abstract: In the last few years, several steps were taken in order
to improve the quality of corporate governance for Romanian listed
companies. Higher standards of corporate governance is documented
in the literature to lead to a better information environment, and,
consequently, to increase analysts forecast accuracy. Accordingly, the
purpose of this paper is to investigate the extent to which corporate
governance policies affect analysts forecasts for companies listed on
Bucharest Stock Exchange. The results showed that there is indeed a
negative correlation between a corporate governance index – used as
a proxy for the quality of corporate governance practices - and
analysts forecast errors.
Abstract: Three similar negative differential resistance (NDR)
profiles with both high peak to valley current density ratio (PVCDR)
value and high peak current density (PCD) value in unity resonant
tunneling electronic circuit (RTEC) element is developed in this paper.
The PCD values and valley current density (VCD) values of the three
NDR curves are all about 3.5 A and 0.8 A, respectively. All PV values
of NDR curves are 0.40 V, 0.82 V, and 1.35 V, respectively. The VV
values are 0.61 V, 1.07 V, and 1.69 V, respectively. All PVCDR
values reach about 4.4 in three NDR curves. The PCD value of 3.5 A
in triple PVCDR RTEC element is better than other resonant
tunneling devices (RTD) elements. The high PVCDR value is
concluded the lower VCD value about 0.8 A. The low VCD value is
achieved by suitable selection of resistors in triple PVCDR RTEC
element. The low PV value less than 1.35 V possesses low power
dispersion in triple PVCDR RTEC element. The designed multiple
value logical level (MVLL) system using triple PVCDR RTEC
element provides equidistant logical level. The logical levels of
MVLL system are about 0.2 V, 0.8 V, 1.5 V, and 2.2 V from low
voltage to high voltage and then 2.2 V, 1.3 V, 0.8 V, and 0.2 V from
high voltage back to low voltage in half cycle of sinusoid wave. The
output level of four levels MVLL system is represented in 0.3 V, 1.1 V,
1.7 V, and 2.6 V, which satisfies the NMP condition of traditional
two-bit system. The remarkable logical characteristic of improved
MVLL system with paralleled capacitor are with four significant
stable logical levels about 220 mV, 223 mV, 228 mV, and 230 mV.
The stability and articulation of logical levels of improved MVLL
system are outstanding. The average holding time of improved MVLL
system is approximately 0.14 μs. The holding time of improved
MVLL system is fourfold than of basic MVLL system. The function of
additional capacitor in the improved MVLL system is successfully
discovered.
Abstract: This paper presents a simple and effective method for approximate indexing of instances for instance based learning. The method uses an interval tree to determine a good starting search point for the nearest neighbor. The search stops when an early stopping criterion is met. The method proved to be very effective especially when only the first nearest neighbor is required.
Abstract: New regulations and standards for noise emission increasingly compel the automotive firms to make some improvements about decreasing the engine noise. Nowadays, the perforated reactive mufflers which have an effective damping capability are specifically used for this purpose. New designs should be analyzed with respect to both acoustics and back pressure. In this study, a reactive perforated muffler is investigated numerically and experimentally. For an acoustical analysis, the transmission loss which is independent of sound source of the present cross flow, the perforated muffler was analyzed by COMSOL. To be able to validate the numerical results, transmission loss was measured experimentally. Back pressure was obtained based on the flow field analysis and was also compared with experimental results. Numerical results have an approximate error of 20% compared to experimental results.
Abstract: The Far From Most Strings Problem (FFMSP) is to obtain a string which is far from as many as possible of a given set of strings. All the input and the output strings are of the same length, and two strings are said to be far if their hamming distance is greater than or equal to a given positive integer. FFMSP belongs to the class of sequences consensus problems which have applications in molecular biology. The problem is NP-hard; it does not admit a constant-ratio approximation either, unless P = NP. Therefore, in addition to exact and approximate algorithms, (meta)heuristic algorithms have been proposed for the problem in recent years. On the other hand, in the recent years, hybrid algorithms have been proposed and successfully used for many hard problems in a variety of domains. In this paper, a new metaheuristic algorithm, called Constructive Beam and Local Search (CBLS), is investigated for the problem, which is a hybridization of constructive beam search and local search algorithms. More specifically, the proposed algorithm consists of two phases, the first phase is to obtain several candidate solutions via the constructive beam search and the second phase is to apply local search to the candidate solutions obtained by the first phase. The best solution found is returned as the final solution to the problem. The proposed algorithm is also similar to memetic algorithms in the sense that both use local search to further improve individual solutions. The CBLS algorithm is compared with the most recent published algorithm for the problem, GRASP, with significantly positive results; the improvement is by order of magnitudes in most cases.
Abstract: The paper presents a new hybridization methodology involving Neural, Fuzzy and Rough Computing. A Rough Sets based approximation technique has been proposed based on a certain Neuro – Fuzzy architecture. A New Rough Neuron composition consisting of a combination of a Lower Bound neuron and a Boundary neuron has also been described. The conventional convergence of error in back propagation has been given away for a new framework based on 'Output Excitation Factor' and an inverse input transfer function. The paper also presents a brief comparison of performances, of the existing Rough Neural Networks and ANFIS architecture against the proposed methodology. It can be observed that the rough approximation based neuro-fuzzy architecture is superior to its counterparts.
Abstract: This paper developed the c-Chart based on a Zero- Inflated Poisson (ZIP) processes that approximated by a geometric distribution with parameter p. The p estimated that fit for ZIP distribution used in calculated the mean, median, and variance of geometric distribution for constructed the c-Chart by three difference methods. For cg-Chart, developed c-Chart by used the mean and variance of the geometric distribution constructed control limits. For cmg-Chart, the mean used for constructed the control limits. The cme- Chart, developed control limits of c-Chart from median and variance values of geometric distribution. The performance of charts considered from the Average Run Length and Average Coverage Probability. We found that for an in-control process, the cg-Chart is superior for low level of mean at all level of proportion zero. For an out-of-control process, the cmg-Chart and cme-Chart are the best for mean = 2, 3 and 4 at all level of parameter.
Abstract: Since 2004, we have been developing an in-situ storage image sensor (ISIS) that captures more than 100 consecutive images at a frame rate of 10 Mfps with ultra-high sensitivity as well as the video camera for use with this ISIS. Currently, basic research is continuing in an attempt to increase the frame rate up to 100 Mfps and above. In order to suppress electro-magnetic noise at such high frequency, a digital-noiseless imaging transfer scheme has been developed utilizing solely sinusoidal driving voltages. This paper presents highly efficient-yet-accurate expressions to estimate attenuation as well as phase delay of driving voltages through RC networks of an ultra-high-speed image sensor. Elmore metric for a fundamental RC chain is employed as the first-order approximation. By application of dimensional analysis to SPICE data, we found a simple expression that significantly improves the accuracy of the approximation. Similarly, another simple closed-form model to estimate phase delay through fundamental RC networks is also obtained. Estimation error of both expressions is much less than previous works, only less 2% for most of the cases . The framework of this analysis can be extended to address similar issues of other VLSI structures.
Abstract: Dichotomization of the outcome by a single cut-off point is an important part of various medical studies. Usually the relationship between the resulted dichotomized dependent variable and explanatory variables is analyzed with linear regression, probit regression or logistic regression. However, in many real-life situations, a certain cut-off point dividing the outcome into two groups is unknown and can be specified only approximately, i.e. surrounded by some (small) uncertainty. It means that in order to have any practical meaning the regression model must be robust to this uncertainty. In this paper, we show that neither the beta in the linear regression model, nor its significance level is robust to the small variations in the dichotomization cut-off point. As an alternative robust approach to the problem of uncertain medical categories, we propose to use the linear regression model with the fuzzy membership function as a dependent variable. This fuzzy membership function denotes to what degree the value of the underlying (continuous) outcome falls below or above the dichotomization cut-off point. In the paper, we demonstrate that the linear regression model of the fuzzy dependent variable can be insensitive against the uncertainty in the cut-off point location. In the paper we present the modeling results from the real study of low hemoglobin levels in infants. We systematically test the robustness of the binomial regression model and the linear regression model with the fuzzy dependent variable by changing the boundary for the category Anemia and show that the behavior of the latter model persists over a quite wide interval.
Abstract: The paper deals with a mathematical model for fluid dynamic flows on road networks which is based on conservation laws. This nonlinear framework is based on the conservation of cars. We focus on traffic circle, which is a finite number of roads that meet at some junctions. The traffic circle with junctions having either one incoming and two outgoing or two incoming and one outgoing roads. We describe the numerical schemes with the particular boundary conditions used to produce approximated solutions of the problem.
Abstract: Our aim in this piece of work is to demonstrate the
power of the Laplace Adomian decomposition method (LADM) in
approximating the solutions of nonlinear differential equations
governing the two-dimensional viscous flow induced by a shrinking
sheet.
Abstract: Semiconductor nanomaterials like TiO2 nanoparticles
(TiO2-NPs) approximately less than 100 nm in diameter have become
a new generation of advanced materials due to their novel and
interesting optical, dielectric, and photo-catalytic properties. With the
increasing use of NPs in commerce, to date few studies have
investigated the toxicological and environmental effects of NPs.
Motivated by the importance of TiO2-NPs that may contribute to the
cancer research field especially from the treatment prospective
together with the fractal analysis technique, we have investigated the
effect of TiO2-NPs on colony morphology in the dark condition
using fractal dimension as a key morphological characterization
parameter. The aim of this work is mainly to investigate the cytotoxic
effects of TiO2-NPs in the dark on the growth of human cervical
carcinoma (HeLa) cell colonies from morphological aspect. The in
vitro studies were carried out together with the image processing
technique and fractal analysis. It was found that, these colonies were
abnormal in shape and size. Moreover, the size of the control
colonies appeared to be larger than those of the treated group. The
mean Df +/- SEM of the colonies in untreated cultures was
1.085±0.019, N= 25, while that of the cultures treated with TiO2-NPs
was 1.287±0.045. It was found that the circularity of the control
group (0.401±0.071) is higher than that of the treated group
(0.103±0.042). The same tendency was found in the diameter
parameters which are 1161.30±219.56 μm and 852.28±206.50 μm
for the control and treated group respectively. Possible explanation of
the results was discussed, though more works need to be done in
terms of the for mechanism aspects. Finally, our results indicate that
fractal dimension can serve as a useful feature, by itself or in
conjunction with other shape features, in the classification of cancer
colonies.
Abstract: Ability of accurate and reliable location estimation in
indoor environment is the key issue in developing great number of
context aware applications and Location Based Services (LBS).
Today, the most viable solution for localization is the Received
Signal Strength (RSS) fingerprinting based approach using wireless
local area network (WLAN). This paper presents two RSS
fingerprinting based approaches – first we employ widely used
WLAN based positioning as a reference system and then investigate
the possibility of using GSM signals for positioning. To compare
them, we developed a positioning system in real world environment,
where realistic RSS measurements were collected. Multi-Layer
Perceptron (MLP) neural network was used as the approximation
function that maps RSS fingerprints and locations. Experimental
results indicate advantage of WLAN based approach in the sense of
lower localization error compared to GSM based approach, but GSM
signal coverage by far outreaches WLAN coverage and for some
LBS services requiring less precise accuracy our results indicate that
GSM positioning can also be a viable solution.
Abstract: A new numerical method for simultaneously updating mass and stiffness matrices based on incomplete modal measured data is presented. By using the Kronecker product, all the variables that are to be modified can be found out and then can be updated directly. The optimal approximation mass matrix and stiffness matrix which satisfy the required eigenvalue equation and orthogonality condition are found under the Frobenius norm sense. The physical configuration of the analytical model is preserved and the updated model will exactly reproduce the modal measured data. The numerical example seems to indicate that the method is quite accurate and efficient.
Abstract: In this paper, the energy performance of a selected
UHDE Ammonia plant is optimized by conducting heat integration through waste heat recovery and the synthesis of a heat exchange
network (HEN). Minimum hot and cold utility requirements were estimated through IChemE spreadsheet. Supporting simulation was
carried out using HYSYS software. The results showed that there is
no need for heating utility while the required cold utility was found to
be around 268,714 kW. Hence a threshold pinch case was faced. Then, the hot and cold streams were matched appropriately. Also,
waste heat recovered resulted with savings in HP and LP steams of
approximately 51.0% and 99.6%, respectively. An economic analysis
on proposed HEN showed very attractive overall payback period not
exceeding 3 years. In general, a net saving approaching 35% was
achieved in implementing heat optimization of current studied UHDE Ammonia process.