Abstract: Stick models are widely used in studying the
behaviour of straight as well as skew bridges and viaducts subjected
to earthquakes while carrying out preliminary studies. The
application of such models to highly curved bridges continues to
pose challenging problems. A viaduct proposed in the foothills of the
Himalayas in Northern India is chosen for the study. It is having 8
simply supported spans @ 30 m c/c. It is doubly curved in horizontal
plane with 20 m radius. It is inclined in vertical plane as well. The
superstructure consists of a box section. Three models have been
used: a conventional stick model, an improved stick model and a 3D
finite element model. The improved stick model is employed by
making use of body constraints in order to study its capabilities. The
first 8 frequencies are about 9.71% away in the latter two models.
Later the difference increases to 80% in 50th mode. The viaduct was
subjected to all three components of the El Centro earthquake of May
1940. The numerical integration was carried out using the Hilber-
Hughes-Taylor method as implemented in SAP2000. Axial forces
and moments in the bridge piers as well as lateral displacements at
the bearing levels are compared for the three models. The maximum
difference in the axial forces and bending moments and
displacements vary by 25% between the improved and finite element
model. Whereas, the maximum difference in the axial forces,
moments, and displacements in various sections vary by 35%
between the improved stick model and equivalent straight stick
model. The difference for torsional moment was as high as 75%. It is
concluded that the stick model with body constraints to model the
bearings and expansion joints is not desirable in very sharp S curved
viaducts even for preliminary analysis. This model can be used only
to determine first 10 frequency and mode shapes but not for member
forces. A 3D finite element analysis must be carried out for
meaningful results.
Abstract: This research paper presents the CFD analysis of
oscillating airfoil during pitch cycle. Unsteady subsonic flow is
simulated for pitching airfoil at Mach number 0.283 and Reynolds
number 3.45 millions. Turbulent effects are also considered for this
study by using K-ω SST turbulent model. Two-dimensional unsteady
compressible Navier-Stokes code including two-equation turbulence
model and PISO pressure velocity coupling is used. Pressure based
implicit solver with first order implicit unsteady formulation is used.
The simulated pitch cycle results are compared with the available
experimental data. The results have a good agreement with the
experimental data. Aerodynamic characteristics during pitch cycles
have been studied and validated.
Abstract: The paper presents a complete discrete statistical framework, based on a novel vector quantization (VQ) front-end process. This new VQ approach performs an optimal distribution of VQ codebook components on HMM states. This technique that we named the distributed vector quantization (DVQ) of hidden Markov models, succeeds in unifying acoustic micro-structure and phonetic macro-structure, when the estimation of HMM parameters is performed. The DVQ technique is implemented through two variants. The first variant uses the K-means algorithm (K-means- DVQ) to optimize the VQ, while the second variant exploits the benefits of the classification behavior of neural networks (NN-DVQ) for the same purpose. The proposed variants are compared with the HMM-based baseline system by experiments of specific Arabic consonants recognition. The results show that the distributed vector quantization technique increase the performance of the discrete HMM system.
Abstract: A self tuning PID control strategy using reinforcement
learning is proposed in this paper to deal with the control of wind
energy conversion systems (WECS). Actor-Critic learning is used to
tune PID parameters in an adaptive way by taking advantage of the
model-free and on-line learning properties of reinforcement learning
effectively. In order to reduce the demand of storage space and to
improve the learning efficiency, a single RBF neural network is used
to approximate the policy function of Actor and the value function of
Critic simultaneously. The inputs of RBF network are the system
error, as well as the first and the second-order differences of error.
The Actor can realize the mapping from the system state to PID
parameters, while the Critic evaluates the outputs of the Actor and
produces TD error. Based on TD error performance index and
gradient descent method, the updating rules of RBF kernel function
and network weights were given. Simulation results show that the
proposed controller is efficient for WECS and it is perfectly
adaptable and strongly robust, which is better than that of a
conventional PID controller.
Abstract: The aim of this study was to investigate the effect of blood viscosity on the radial pulse wave. For this, we obtained the radial pulse wave of 15 males with abnormal high hematocrit level and 47 males with normal hematocrit level at the age of thirties and forties. Various variables of the radial pulse wave between two groups were analyzed and compared by Student's T test. There are significant differences in several variables about height, time and area of the pulse wave. The first peak of the radial pulse wave was higher in abnormal high hematocrit group, but the third peak was higher and longer in normal hematocrit group. Our results suggest that the radial pulse wave can be used for diagnosis of high blood viscosity and more clinical application.
Abstract: This paper examines two policy spaces–the ARC and TVA–and their spatialized politics. The research observes that the regional concept informs public policy and can contribute to the formation of stable policy initiatives. Using the subsystem framework to understand the political viability of policy regimes, the authors conclude policy geographies that appeal to traditional definitions of regions are more stable over time. In contrast, geographies that fail to reflect pre-existing representations of space are engaged in more competitive subsystem politics. The paper demonstrates that the spatial practices of policy regions and their directional politics influence the political viability of programs. The paper concludes that policy spaces should institutionalize pre-existing geographies–not manufacture new ones.
Abstract: Based on experimental data using accelerometry technology there was developed an analytical model that approximates human induced ground reaction forces in vertical, longitudinal and lateral directions ascending and descending the stairs. Proposed dynamic loading factors and corresponding phase shifts for the first five harmonics of continuous walking force history in case of stair ascend and descend. Into account is taken imperfectness of individual footfall forcing functions, differences between continuous walking force histories among individuals. There is proposed mean synthetic continuous walking force history that can be used in numerical simulations of human movement on the stairs.
Abstract: Gas turbine air inlet cooling is a useful method for
increasing output for regions where significant power demand and
highest electricity prices occur during the warm months. Inlet air
cooling increases the power output by taking advantage of the gas
turbine-s feature of higher mass flow rate when the compressor inlet
temperature decreases. Different methods are available for reducing
gas turbine inlet temperature. There are two basic systems currently
available for inlet cooling. The first and most cost-effective system is
evaporative cooling. Evaporative coolers make use of the evaporation
of water to reduce the gas turbine-s inlet air temperature. The second
system employs various ways to chill the inlet air. In this method, the
cooling medium flows through a heat exchanger located in the inlet
duct to remove heat from the inlet air. However, the evaporative
cooling is limited by wet-bulb temperature while the chilling can cool
the inlet air to temperatures that are lower than the wet bulb
temperature. In the present work, a thermodynamic model of a gas
turbine is built to calculate heat rate, power output and thermal
efficiency at different inlet air temperature conditions. Computational
results are compared with ISO conditions herein called "base-case".
Therefore, the two cooling methods are implemented and solved for
different inlet conditions (inlet temperature and relative humidity).
Evaporative cooler and absorption chiller systems results show that
when the ambient temperature is extremely high with low relative
humidity (requiring a large temperature reduction) the chiller is the
more suitable cooling solution. The net increment in the power output
as a function of the temperature decrease for each cooling method is
also obtained.
Abstract: Palm shell obtained from coastal part of southern
India was studied for the removal for the adsorption of Hg (II) ions.
Batch adsorption experiments were carried out as a function of pH,
concentration of Hg (II) ions, time, temperature and adsorbent dose.
Maximum removal was seen in the range pH 4.0- pH 7.0. The palm
shell powder used as adsorbent was characterized for its surface area,
SEM, PXRD, FTIR, ion exchange capacity, moisture content, and
bulk density, soluble content in water and acid and pH. The
experimental results were analyzed using Langmuir I, II, III, IV and
Freundlich adsorption isotherms. The batch sorption kinetics was
studied for the first order reversible reaction, pseudo first order;
pseudo second order reaction and the intra-particle diffusion reaction.
The biomass was successfully used for removal Hg (II) from
synthetic and industrial effluents and the technique appears
industrially applicable and viable.
Abstract: Natural disasters, including earthquake, kill many people around the world every year. Society rescue actions, which start after the earthquake and are called LAST in abbreviation, include locating, access, stabilization and transportation. In the present article, we have studied the process of local accessibility to the injured and transporting them to health care centers. With regard the heavy traffic load due to earthquake, the destruction of connecting roads and bridges and the heavy debris in alleys and street, which put the lives of the injured and the people buried under the debris in danger, accelerating the rescue actions and facilitating the accessibilities are of great importance, obviously. Tehran, the capital of Iran, is among the crowded cities in the world and is the center of extensive economic, political, cultural and social activities. Tehran has a population of about 9.5 millions and because of the immigration of people from the surrounding cities. Furthermore, considering the fact that Tehran is located on two important and large faults, a 6 Richter magnitude earthquake in this city could lead to the greatest catastrophe during the entire human history. The present study is a kind of review and a major part of the required information for it, has been obtained from libraries all of the rescue vehicles around the world, including rescue helicopters, ambulances, fire fighting vehicles and rescue boats, and their applied technology, and also the robots specifically designed for the rescue system and the advantages and disadvantages of them, have been investigated. The studies show that there is a significant relationship between the rescue team-s arrival time at the incident zone and the number of saved people; so that, if the duration of burial under debris 30 minutes, the probability of survival is %99.3, after a day is %81, after 2days is %19 and after 5days is %7.4. The exiting transport systems all have some defects. If these defects are removed, more people could be saved each hour and the preparedness against natural disasters is increased. In this study, transport system has been designed for the rescue team and the injured; which could carry the rescue team to the incident zone and the injured to the health care centers. In addition, this system is able to fly in the air and move on the earth as well; so that the destruction of roads and the heavy traffic load could not prevent the rescue team from arriving early at the incident zone. The system also has the equipment required firebird for debris removing, optimum transport of the injured and first aid.
Abstract: The literature reports a large number of approaches for
measuring the similarity between protein sequences. Most of these
approaches estimate this similarity using alignment-based techniques
that do not necessarily yield biologically plausible results, for two
reasons.
First, for the case of non-alignable (i.e., not yet definitively aligned
and biologically approved) sequences such as multi-domain, circular
permutation and tandem repeat protein sequences, alignment-based
approaches do not succeed in producing biologically plausible results.
This is due to the nature of the alignment, which is based on the
matching of subsequences in equivalent positions, while non-alignable
proteins often have similar and conserved domains in non-equivalent
positions.
Second, the alignment-based approaches lead to similarity measures
that depend heavily on the parameters set by the user for the alignment
(e.g., gap penalties and substitution matrices). For easily alignable
protein sequences, it's possible to supply a suitable combination of
input parameters that allows such an approach to yield biologically
plausible results. However, for difficult-to-align protein sequences,
supplying different combinations of input parameters yields different
results. Such variable results create ambiguities and complicate the
similarity measurement task.
To overcome these drawbacks, this paper describes a novel and
effective approach for measuring the similarity between protein
sequences, called SAF for Substitution and Alignment Free. Without
resorting either to the alignment of protein sequences or to substitution
relations between amino acids, SAF is able to efficiently detect the
significant subsequences that best represent the intrinsic properties of
protein sequences, those underlying the chronological dependencies of
structural features and biochemical activities of protein sequences.
Moreover, by using a new efficient subsequence matching scheme,
SAF more efficiently handles protein sequences that contain similar
structural features with significant meaning in chronologically
non-equivalent positions. To show the effectiveness of SAF, extensive
experiments were performed on protein datasets from different
databases, and the results were compared with those obtained by
several mainstream algorithms.
Abstract: With data centers, end-users can realize the pervasiveness of services that will be one day the cornerstone of our lives. However, data centers are often classified as computing systems that consume the most amounts of power. To circumvent such a problem, we propose a self-adaptive weighted sum methodology that jointly optimizes the performance and power consumption of any given data center. Compared to traditional methodologies for multi-objective optimization problems, the proposed self-adaptive weighted sum technique does not rely on a systematical change of weights during the optimization procedure. The proposed technique is compared with the greedy and LR heuristics for large-scale problems, and the optimal solution for small-scale problems implemented in LINDO. the experimental results revealed that the proposed selfadaptive weighted sum technique outperforms both of the heuristics and projects a competitive performance compared to the optimal solution.
Abstract: We study in this paper the effect of the scene
changing on image sequences coding system using Embedded
Zerotree Wavelet (EZW). The scene changing considered here is the
full motion which may occurs. A special image sequence is generated
where the scene changing occurs randomly. Two scenarios are
considered: In the first scenario, the system must provide the
reconstruction quality as best as possible by the management of the
bit rate (BR) while the scene changing occurs. In the second scenario,
the system must keep the bit rate as constant as possible by the
management of the reconstruction quality. The first scenario may be
motivated by the availability of a large band pass transmission
channel where an increase of the bit rate may be possible to keep the
reconstruction quality up to a given threshold. The second scenario
may be concerned by the narrow band pass transmission channel
where an increase of the bit rate is not possible. In this last case,
applications for which the reconstruction quality is not a constraint
may be considered. The simulations are performed with five scales
wavelet decomposition using the 9/7-tap filter bank biorthogonal
wavelet. The entropy coding is performed using a specific defined
binary code book and EZW algorithm. Experimental results are
presented and compared to LEAD H263 EVAL. It is shown that if
the reconstruction quality is the constraint, the system increases the
bit rate to obtain the required quality. In the case where the bit rate
must be constant, the system is unable to provide the required quality
if the scene change occurs; however, the system is able to improve
the quality while the scene changing disappears.
Abstract: A basic conceptual study of TCSC device on Simulink is a teaching aid and helps in understanding the rudiments of the topic. This paper thus stems out from basics of TCSC device and analyzes the impedance characteristics and associated single & multi resonance conditions. The Impedance characteristics curve is drawn for different values of inductance in MATLAB using M-files. The study is also helpful in estimating the appropriate inductance and capacitance values which have influence on multi resonance point in TCSC device. The capacitor voltage, line current, thyristor current and capacitor current waveforms are discussed briefly as simulation results. Simulink model of TCSC device is given and corresponding waveforms are analyzed. The subsidiary topics e.g. power oscillation damping, SSR mitigation and transient stability is also brought out.
Abstract: To learn about China-s future energy demand, this paper first proposed GM(1,1) model group based on recursive solutions of parameters estimation, setting up a general solving-algorithm of the model group. This method avoided the problems occurred on the past researches that remodeling, loss of information and large amount of calculation. This paper established respectively all-data-GM(1,1), metabolic GM(1,1) and new information GM (1,1)model according to the historical data of energy consumption in China in the year 2005-2010 and the added data of 2011, then modeling, simulating and comparison of accuracies we got the optimal models and to predict. Results showed that the total energy demand of China will be 37.2221 billion tons of equivalent coal in 2012 and 39.7973 billion tons of equivalent coal in 2013, which are as the same as the overall planning of energy demand in The 12th Five-Year Plan.
Abstract: This study is designed to investigate errors emerged in written texts produced by 30 Turkish EFL learners with an explanatory, and thus, qualitative perspective. Erroneous language elements were identified by the researcher first and then their grammaticality and intelligibility were checked by five native speakers of English. The analysis of the data showed that it is difficult to claim that an error stems from only one single factor since different features of an error are triggered by different factors. Our findings revealed two different types of errors: those which stem from the interference of L1 with L2 and those which are developmental ones. The former type contains more global errors whereas the errors in latter type are more intelligible.
Abstract: Data mining uses a variety of techniques each of which is useful for some particular task. It is important to have a deep understanding of each technique and be able to perform sophisticated analysis. In this article we describe a tool built to simulate a variation of the Kohonen network to perform unsupervised clustering and support the entire data mining process up to results visualization. A graphical representation helps the user to find out a strategy to optmize classification by adding, moving or delete a neuron in order to change the number of classes. The tool is also able to automatically suggest a strategy for number of classes optimization.The tool is used to classify macroeconomic data that report the most developed countries? import and export. It is possible to classify the countries based on their economic behaviour and use an ad hoc tool to characterize the commercial behaviour of a country in a selected class from the analysis of positive and negative features that contribute to classes formation.
Abstract: EDF (Early Deadline First) algorithm is a very important scheduling algorithm for real- time systems . The EDF algorithm assigns priorities to each job according to their absolute deadlines and has good performance when the real-time system is not overloaded. When the real-time system is overloaded, many misdeadlines will be produced. But these misdeadlines are not uniformly distributed, which usually focus on some tasks. In this paper, we present an adaptive fuzzy control scheduling based on EDF algorithm. The improved algorithm can have a rectangular distribution of misdeadline ratios among all real-time tasks when the system is overloaded. To evaluate the effectiveness of the improved algorithm, we have done extensive simulation studies. The simulation results show that the new algorithm is superior to the old algorithm.
Abstract: Chaos and fractals are novel fields of physics and mathematics showing up a new way of universe viewpoint and creating many ideas to solve several present problems. In this paper, a novel algorithm based on the chaotic sequence generator with the highest ability to adapt and reach the global optima is proposed. The adaptive ability of proposal algorithm is flexible in 2 steps. The first one is a breadth-first search and the second one is a depth-first search. The proposal algorithm is examined by 2 functions, the Camel function and the Schaffer function. Furthermore, the proposal algorithm is applied to optimize training Multilayer Neural Networks.
Abstract: Human identification at a distance has recently gained
growing interest from computer vision researchers. Gait recognition
aims essentially to address this problem by identifying people based
on the way they walk [1]. Gait recognition has 3 steps. The first step
is preprocessing, the second step is feature extraction and the third
one is classification. This paper focuses on the classification step that
is essential to increase the CCR (Correct Classification Rate).
Multilayer Perceptron (MLP) is used in this work. Neural Networks
imitate the human brain to perform intelligent tasks [3].They can
represent complicated relationships between input and output and
acquire knowledge about these relationships directly from the data
[2]. In this paper we apply MLP NN for 11 views in our database and
compare the CCR values for these views. Experiments are performed
with the NLPR databases, and the effectiveness of the proposed
method for gait recognition is demonstrated.