Abstract: Photoplethysmography is a simple measurement of the
variation in blood volume in tissue. It detects the pulse signal of heart
beat as well as the low frequency signal of vasoconstriction and
vasodilation. The transmission type measurement is limited to only a
few specific positions for example the index finger that have a short
path length for light. The reflectance type measurement can be
conveniently applied on most parts of the body surface. This study
analyzed the factors that determine the quality of reflectance
photoplethysmograph signal including the emitter-detector distance,
wavelength, light intensity, and optical properties of skin tissue.
Light emitting diodes (LEDs) with four different visible
wavelengths were used as the light emitters. A phototransistor was
used as the light detector. A micro translation stage adjusts the
emitter-detector distance from 2 mm to 15 mm.
The reflective photoplethysmograph signals were measured on
different sites. The optimal emitter-detector distance was chosen to
have a large dynamic range for low frequency drifting without signal
saturation and a high perfusion index. Among these four wavelengths,
a yellowish green (571nm) light with a proper emitter-detection
distance of 2mm is the most suitable for obtaining a steady and reliable
reflectance photoplethysmograph signal
Abstract: This paper is focused on issues of nonlinear dynamic process modeling and model-based predictive control of a fed-batch sugar crystallization process applying the concept of artificial neural networks as computational tools. The control objective is to force the operation into following optimal supersaturation trajectory. It is achieved by manipulating the feed flow rate of sugar liquor/syrup, considered as the control input. A feed forward neural network (FFNN) model of the process is first built as part of the controller structure to predict the process response over a specified (prediction) horizon. The predictions are supplied to an optimization procedure to determine the values of the control action over a specified (control) horizon that minimizes a predefined performance index. The control task is rather challenging due to the strong nonlinearity of the process dynamics and variations in the crystallization kinetics. However, the simulation results demonstrated smooth behavior of the control actions and satisfactory reference tracking.
Abstract: Global environmental changes lead to increased frequency and scale of natural disaster, Taiwan is under the influence of global warming and extreme weather. Therefore, the vulnerability was increased and variability and complexity of disasters is relatively enhanced. The purpose of this study is to consider the source and magnitude of hazard characteristics on the tourism industry. Using modern risk management concepts, integration of related domestic and international basic research, this goes beyond the Taiwan typhoon disaster risk assessment model and evaluation of loss. This loss evaluation index system considers the impact of extreme weather, in particular heavy rain on the tourism industry in Taiwan. Consider the extreme climate of the compound impact of disaster for the tourism industry; we try to make multi-hazard risk assessment model, strategies and suggestions. Related risk analysis results are expected to provide government department, the tourism industry asset owners, insurance companies and banking include tourist disaster risk necessary information to help its tourism industry for effective natural disaster risk management.
Abstract: In order to study of hydropriming and halopriming on
germination and early growth stage of wheat (Triticum aestivum) an
experiment was carried out in laboratory of the Department of
Agronomy and Plant breeding, Shahrood University of Technology.
Seed treatments consisted of T1: control (untreated seeds), T2:
soaking in distilled water for 18 h (hydropriming). T3: soaking in -
1.2 MPa solution of CaSO4 for 36 h (halopriming). Germination and
early seedling growth were studied using distilled water (control) and
under osmotic potentials of -0.4, -0.8 and -1.2 MPa for NaCl and
polyethylene glycol (PEG 6000), respectively. Results showed that
Hydroprimed seeds achieved maximum germination seedling dry
weight, especially during the higher osmotic potentials. Minimum
germination was recorded at untreated seeds (control) followed by
osmopriming. Under high osmotic potentials, hydroprimed seeds had
higher GI (germination index) as compared to haloprimed or
untreated seeds. Interaction effect of seed treatment and osmotic
potential significantly affected the seedling vigour index (SVI).
Abstract: Many studies have shown that Artificial Neural
Networks (ANN) have been widely used for forecasting financial
markets, because of many financial and economic variables are nonlinear,
and an ANN can model flexible linear or non-linear
relationship among variables.
The purpose of the study was to employ an ANN models to
predict the direction of the Istanbul Stock Exchange National 100
Indices (ISE National-100).
As a result of this study, the model forecast the direction of the
ISE National-100 to an accuracy of 74, 51%.
Abstract: Reliability Centered Maintenance(RCM) is one of
most widely used methods in the modern power system to schedule a
maintenance cycle and determine the priority of inspection. In order
to apply the RCM method to the Smart Grid, a precedence study for
the new structure of rearranged system should be performed due to
introduction of additional installation such as renewable and
sustainable energy resources, energy storage devices and advanced
metering infrastructure. This paper proposes a new method to
evaluate the priority of maintenance and inspection of the power
system facilities in the Smart Grid using the Risk Priority Number. In
order to calculate that risk index, it is required that the reliability
block diagram should be analyzed for the Smart Grid system. Finally,
the feasible technical method is discussed to estimate the risk
potential as part of the RCM procedure.
Abstract: This paper presents a systematic approach for designing Unified Power Flow Controller (UPFC) based supplementary damping controllers for damping low frequency oscillations in a single-machine infinite-bus power system. Detailed investigations have been carried out considering the four alternatives UPFC based damping controller namely modulating index of series inverter (mB), modulating index of shunt inverter (mE), phase angle of series inverter (δB ) and phase angle of the shunt inverter (δE ). The design problem of the proposed controllers is formulated as an optimization problem and Real- Coded Genetic Algorithm (RCGA) is employed to optimize damping controller parameters. Simulation results are presented and compared with a conventional method of tuning the damping controller parameters to show the effectiveness and robustness of the proposed design approach.
Abstract: In this paper we propose new method for
simultaneous generating multiple quantiles corresponding to given
probability levels from data streams and massive data sets. This
method provides a basis for development of single-pass low-storage
quantile estimation algorithms, which differ in complexity, storage
requirement and accuracy. We demonstrate that such algorithms may
perform well even for heavy-tailed data.
Abstract: As increasing importance of symbiosis and cooperation among mobile communication industries, the mobile ecosystem has been especially highlighted in academia and practice. The structure of mobile ecosystem is quite complex and the ecological role of actors is important to understand that structure. In this respect, this study aims to explore structure of mobile ecosystem in the case of Korea using inter-industry network analysis. Then, the ecological roles in mobile ecosystem are identified using centrality measures as a result of network analysis: degree of centrality, closeness, and betweenness. The result shows that the manufacturing and service industries are separate. Also, the ecological roles of some actors are identified based on the characteristics of ecological terms: keystone, niche, and dominator. Based on the result of this paper, we expect that the policy makers can formulate the future of mobile industry and healthier mobile ecosystem can be constructed.
Abstract: This paper presents a novel approach to assessing textile porosity by the application of the image analysis techniques. The images of different types of sample fabrics, taken through a microscope when the fabric is placed over a constant light source,transfer the problem into the image analysis domain. Indeed, porosity can thus be expressed in terms of a brightness percentage index calculated on the digital microscope image. Furthermore, it is meaningful to compare the brightness percentage index with the air permeability and the tightness indices of each fabric type. We have experimentally shown that there exists an approximately linear relation between brightness percentage and air permeability indices.
Abstract: Brassinosteroids (BRs) regulate cell elongation,
vascular differentiation, senescence, and stress responses. BRs signal
through the BES1/BZR1 family of transcription factors, which
regulate hundreds of target genes involved in this pathway. In this
research a comprehensive genome-wide analysis was carried out in
BES1/BZR1 gene family in Arabidopsis thaliana, Cucumis sativus,
Vitis vinifera, Glycin max and Brachypodium distachyon.
Specifications of the desired sequences, dot plot and hydropathy plot
were analyzed in the protein and genome sequences of five plant
species. The maximum amino acid length was attributed to protein
sequence Brdic3g with 374aa and the minimum amino acid length
was attributed to protein sequence Gm7g with 163aa. The maximum
Instability index was attributed to protein sequence AT1G19350
equal with 79.99 and the minimum Instability index was attributed to
protein sequence Gm5g equal with 33.22. Aliphatic index of these
protein sequences ranged from 47.82 to 78.79 in Arabidopsis
thaliana, 49.91 to 57.50 in Vitis vinifera, 55.09 to 82.43 in Glycin
max, 54.09 to 54.28 in Brachypodium distachyon 55.36 to 56.83 in
Cucumis sativus. Overall, data obtained from our investigation
contributes a better understanding of the complexity of the
BES1/BZR1 gene family and provides the first step towards directing
future experimental designs to perform systematic analysis of the
functions of the BES1/BZR1 gene family.
Abstract: Selected Mapping (SLM) is a PAPR reduction technique, which converts the OFDM signal into several independent signals by multiplication with the phase sequence set and transmits one of the signals with lowest PAPR. But it requires the index of the selected signal i.e. side information (SI) to be transmitted with each OFDM symbol. The PAPR reduction capability of the SLM scheme depends on the selection of phase sequence set. In this paper, we have proposed a new phase sequence set generation scheme based on M-ary chaotic sequence and a mapping scheme to map quaternary data to concentric circle constellation (CCC) is used. It is shown that this method does not require SI and provides better SER performance with good PAPR reduction capability as compared to existing SLMOFDM methods.
Abstract: This paper presents a new technique for generating sets of synthetic classifiers to evaluate abstract-level combination methods. The sets differ in terms of both recognition rates of the individual classifiers and degree of similarity. For this purpose, each abstract-level classifier is considered as a random variable producing one class label as the output for an input pattern. From the initial set of classifiers, new slightly different sets are generated by applying specific operators, which are defined at the purpose. Finally, the sets of synthetic classifiers have been used to estimate the performance of combination methods for abstract-level classifiers. The experimental results demonstrate the effectiveness of the proposed approach.
Abstract: This paper emphasizes on the application of genetic algorithm (GA) to optimize the parameters of the TMD for achieving the best results in the reduction of the building response under earthquake excitations. The Integral of the Time multiplied Absolute value of the Error (ITAE) based on relative displacement of all floors in the building is taken as a performance index of the optimization criterion. The problem of robustly TMD controller design is formatted as an optimization problem based on the ITAE performance index to be solved using GA that has a story ability to find the most optimistic results. An 11–story realistic building, located in the city of Rasht, Iran is considered as a test system to demonstrate effectiveness of the proposed GA based TMD (GATMD) controller without specifying which mode should be controlled. The results of the proposed GATMD controller are compared with the uncontrolled structure through timedomain simulation and some performance indices. The results analysis reveals that the designed GA based TMD controller has an excellent capability in reduction of the seismically excited example building and the ITAE performance, that is so for remains as unknown, can be introduced a new criteria - method for structural dynamic design.
Abstract: This paper presents an efficient algorithm for
optimization of radial distribution systems by a network
reconfiguration to balance feeder loads and eliminate overload
conditions. The system load-balancing index is used to determine the
loading conditions of the system and maximum system loading
capacity. The index value has to be minimum in the optimal network
reconfiguration of load balancing. A method based on Tabu search
algorithm, The Tabu search algorithm is employed to search for the
optimal network reconfiguration. The basic idea behind the search is
a move from a current solution to its neighborhood by effectively
utilizing a memory to provide an efficient search for optimality. It
presents low computational effort and is able to find good quality
configurations. Simulation results for a radial 69-bus system with
distributed generations and capacitors placement. The study results
show that the optimal on/off patterns of the switches can be identified
to give the best network reconfiguration involving balancing of
feeder loads while respecting all the constraints.
Abstract: Buildings with floating column are highly undesirable built in seismically active areas. Many urban multi-storey buildings today have floating column buildings which are adopted to accommodate parking at ground floor or reception lobbies in the first storey. The earthquake forces developed at different floor levels in a building need to be brought down along the height to the ground by the shortest path; any deviation or discontinuity in this load transfer path results in poor performance of the building. Floating column buildings are severely damaged during earthquake. Damage on this structure can be reduce by taking the effect of infill wall. This paper presents the effect of stiffness of infill wall to the damage occurred in floating column building when ground shakes. Modelling and analysis are carried out by non linear analysis programme IDARC-2D. Damage occurred in beams, columns, storey are studied by formulating modified Park & Ang model to evaluate damage indices. Overall structural damage indices in buildings due to shaking of ground are also obtained. Dynamic response parameters i.e. lateral floor displacement, storey drift, time period, base shear of buildings are obtained and results are compared with the ordinary moment resisting frame buildings. Formation of cracks, yield, plastic hinge, are also observed during analysis.
Abstract: The objective of this paper is to develop a neural
network-based residual generator to detect the fault in the actuators
for a specific communication satellite in its attitude control system
(ACS). First, a dynamic multilayer perceptron network with dynamic
neurons is used, those neurons correspond a second order linear
Infinite Impulse Response (IIR) filter and a nonlinear activation
function with adjustable parameters. Second, the parameters from the
network are adjusted to minimize a performance index specified by
the output estimated error, with the given input-output data collected
from the specific ACS. Then, the proposed dynamic neural network
is trained and applied for detecting the faults injected to the wheel,
which is the main actuator in the normal mode for the communication
satellite. Then the performance and capabilities of the proposed
network were tested and compared with a conventional model-based
observer residual, showing the differences between these two
methods, and indicating the benefit of the proposed algorithm to
know the real status of the momentum wheel. Finally, the application
of the methods in a satellite ground station is discussed.
Abstract: One year (November 2009-October 2010) sediment monitoring was used to evaluate pollution status, concentration and distribution of heavy metals (As, Cu, Cd, Cr, Hg, Ni, Pb and Zn) in West Port of Malaysia. Sediment sample were collected from nine stations every four months. Geo-accumulation factor and Pollution Load Index (PLI) were estimated to better understand the pollution level in study area. The heavy metal concentration (Mg/g dry weight) were ranged from 20.2 to 162 for As, 7.4 to 27.6 for Cu, 0.244 to 3.53 for Cd, 11.5 to 61.5 for Cr, 0.11 to 0.409 for Hg, 7.2 to 22.2 for Ni, 22.3 to 80 for Pb and 23 to 98.3 for Zn. In general, concentration some metals (As,Cd, Hg and Pb) was higher than background values that are considered as serious concern for aquatic life and the human health.
Abstract: The paper proposes a unified model for multimedia data retrieval which includes data representatives, content representatives, index structure, and search algorithms. The multimedia data are defined as k-dimensional signals indexed in a multidimensional k-tree structure. The benefits of using the k-tree unified model were demonstrated by running the data retrieval application on a six networked nodes test bed cluster. The tests were performed with two retrieval algorithms, one that allows parallel searching using a single feature, the second that performs a weighted cascade search for multiple features querying. The experiments show a significant reduction of retrieval time while maintaining the quality of results.
Abstract: In this paper an algorithm based on the adaptive
neuro-fuzzy controller is provided to enhance the tipover stability of
mobile manipulators when they are subjected to predefined
trajectories for the end-effector and the vehicle. The controller
creates proper configurations for the manipulator to prevent the robot
from being overturned. The optimal configuration and thus the most
favorable control are obtained through soft computing approaches
including a combination of genetic algorithm, neural networks, and
fuzzy logic. The proposed algorithm, in this paper, is that a look-up
table is designed by employing the obtained values from the genetic
algorithm in order to minimize the performance index and by using
this data base, rule bases are designed for the ANFIS controller and
will be exerted on the actuators to enhance the tipover stability of the
mobile manipulator. A numerical example is presented to
demonstrate the effectiveness of the proposed algorithm.