Strong Limit Theorems for Dependent Random Variables
In This Article We establish moment inequality of
dependent random variables,furthermore some theorems of strong law
of large numbers and complete convergence for sequences of dependent
random variables. In particular, independent and identically
distributed Marcinkiewicz Law of large numbers are generalized to
the case of m0-dependent sequences.
Lacunary System, Generalized Gaussian, NA sequences, strong law of large numbers.
Extracting Road Signs using the Color Information
In this paper, we propose a method to extract the road
signs. Firstly, the grabbed image is converted into the HSV color space
to detect the road signs. Secondly, the morphological operations are
used to reduce noise. Finally, extract the road sign using the geometric
property. The feature extraction of road sign is done by using the color
information. The proposed method has been tested for the real
situations. From the experimental results, it is seen that the proposed
method can extract the road sign features effectively.
Color information, image processing, road sign.
Beam Orientation Optimization Using Ant Colony Optimization in Intensity Modulated Radiation Therapy
In intensity modulated radiation therapy (IMRT)
treatment planning, beam angles are usually preselected on the basis of
experience and intuition. Therefore, getting an appropriate beam
configuration needs a very long time. Based on the present situation,
the paper puts forward beam orientation optimization using ant colony
optimization (ACO). We use ant colony optimization to select the
beam configurations, after getting the beam configuration using
Conjugate Gradient (CG) algorithm to optimize the intensity profiles.
Combining with the information of the effect of pencil beam, we can
get the global optimal solution accelerating. In order to verify the
feasibility of the presented method, a simulated and clinical case was
tested, compared with dose-volume histogram and isodose line
between target area and organ at risk. The results showed that the
effect was improved after optimizing beam configurations. The
optimization approach could make treatment planning meet clinical
requirements more efficiently, so it had extensive application
intensity modulated radiation therapy, ant colonyoptimization, Conjugate Gradient algorithm
Storytelling for Business Blogging: Position and Navigation
Truly successful bloggers, navigating the public to know them, often use their blogs as a way to better communicate with customers. Integrating with marketing tools, storytelling can be regarded as one of the most effective ways that businesses can follow to gain competitive edge. Even though the literature on marketing contains much discussion of traditional vehicles, the issue of business blogs applying storytelling has, as yet, received little attention. In the exploration stage, this paper identifies four storytelling disciplines and then presents a road map to business blogging. This paper also provides a two-path framework for blog storytelling and initiates an issue for further study.
Storytelling, business blog, blog content, blog position, blog navigation.
A Dynamic Hybrid Option Pricing Model by Genetic Algorithm and Black- Scholes Model
Unlike this study focused extensively on trading
behavior of option market, those researches were just taken their
attention to model-driven option pricing. For example, Black-Scholes
(B-S) model is one of the most famous option pricing models.
However, the arguments of B-S model are previously mentioned by
some pricing models reviewing. This paper following suggests the
importance of the dynamic character for option pricing, which is also
the reason why using the genetic algorithm (GA). Because of its
natural selection and species evolution, this study proposed a hybrid
model, the Genetic-BS model which combining GA and B-S to
estimate the price more accurate. As for the final experiments, the
result shows that the output estimated price with lower MAE value
than the calculated price by either B-S model or its enhanced one,
Gram-Charlier garch (G-C garch) model. Finally, this work would
conclude that the Genetic-BS pricing model is exactly practical.
genetic algorithm, Genetic-BS, option pricing model.
Production of H5N1 Hemagglutinin inTrichoplusia ni Larvae by a Novel Bi-cistronic Baculovirus Expression Vector
Highly pathogenic avian influenza (HPAI) H5N1 viruses have created demand for a cost-effective vaccine to prevent a pandemic of the disease. Here, we report that Trichoplusia ni (T. ni) larvae can act as a cost-effective bioreactor to produce recombinant HA5 (rH5HA) proteins as an potential effective vaccine for chickens. To facilitate the recombinant virus identification, virus titer determination and access the infected larvae, we employed the internal ribosome entry site (IRES) derived from Perina nuda virus (PnV, belongs to insect picorna like Iflavirus genus) to construct a bi-cistronic baculovirus expression vector that can express the rH5HA protein and enhanced green fluorescent protein (EGFP) simultaneously. Western blot analysis revealed that the 70 kDa rH5HA protein and partially cleaved products (40 kDa H5HA1) were generated in T. ni larvae infected with recombinant baculovirus carrying the H5HA gene. These data suggest that the baculovirus-larvae recombinant protein expression system could be a cost-effective platform for H5N1 vaccine production.
Avian Influenza, baculovirus, hemagglutinin, Trichoplusia ni larvae
Benchmarking: Performance on ALPS and Formosa Clusters
This paper presents the benchmarking results and
performance evaluation of differentclustersbuilt atthe National Center
for High-Performance Computingin Taiwan. Performance of
processor, memory subsystem andinterconnect is a critical factor in the
overall performance of high performance computing platforms. The
evaluation compares different system architecture and software
platforms. Most supercomputer used HPL to benchmark their system
performance, in accordance with the requirement of the TOP500 List.
In this paper we consider system memory access factors that affect
benchmark performance, such as processor and memory
performance.We hope these works will provide useful information for
future development and construct cluster system.
Performance Evaluation, Benchmarking and
Knowledge Acquisition, Absorptive Capacity, and Innovation Capability: An Empirical Study of Taiwan's Knowledge-Intensive Industries
This study investigates the roles of knowledge
acquisition, absorptive capacity, and innovation capability in finance
and manufacturing industries. With 362 valid questionnaires from
manufactures and financial industries in Taiwan, we examine the
relationships between absorptive capacity, knowledge acquisition and
innovation capability using a structural equation model. The results
indicate that absorptive capacity is the mediator between knowledge
acquisition and innovation capability, and that knowledge acquisition
has a positive effect on absorptive capacity.
Absorptive capacity, knowledge acquisition,
Stochastic Resonance in Nonlinear Signal Detection
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.
Probability of detection error, signal detection,stochastic resonance.
Influencing Attitude Change for Sustainability through Persuasion
Food mileage is one of the important issues concerning environmental sustainability. In this research we have utilized a prototype platform with iterative user-centered testing. With these findings we successfully demonstrate the use of the context of persuasive methods to influence users- attitudes towards the sustainable concept.
Behavior change, food mileage, persuasive technology, sustainability.
Effect of Sintering Temperature Curve in Wick Manufactured for Loop Heat Pipe
This investigation examines the effect of the sintering
temperature curve in manufactured nickel powder capillary structure
(wick) for a loop heat pipe (LHP). The sintering temperature curve is
composed of a region of increasing temperature; a region of constant
temperature and a region of declining temperature. The most important
region is that in which the temperature increases, as an index in the
stage in which the temperature increases. The wick of nickel powder is
manufactured in the stage of fixed sintering temperature and the time
between the stage of constant temperature and the stage of falling
temperature. When the slope of the curve in the region of increasing
temperature is unity (equivalent to 10 °C/min), the structure of the
wick is complete and the heat transfer performance is optimal. The
result of experiment test demonstrates that the heat transfer
performance is optimal at 320W; the minimal total thermal resistance
is approximately 0.18°C/W, and the heat flux is 17W/cm2; the internal
parameters of the wick are an effective pore radius of 3.1 μm, a
permeability of 3.25×10-13m2 and a porosity of 71%.
Loop heat pipe (LHP), capillary structure (wick),
sintered temperature curve.
Computational Intelligence Hybrid Learning Approach to Time Series Forecasting
Time series forecasting is an important and widely
popular topic in the research of system modeling. This paper
describes how to use the hybrid PSO-RLSE neuro-fuzzy learning
approach to the problem of time series forecasting. The PSO
algorithm is used to update the premise parameters of the
proposed prediction system, and the RLSE is used to update the
consequence parameters. Thanks to the hybrid learning (HL)
approach for the neuro-fuzzy system, the prediction performance
is excellent and the speed of learning convergence is much faster
than other compared approaches. In the experiments, we use the
well-known Mackey-Glass chaos time series. According to the
experimental results, the prediction performance and accuracy in
time series forecasting by the proposed approach is much better
than other compared approaches, as shown in Table IV. Excellent
prediction performance by the proposed approach has been
forecasting, hybrid learning (HL), Neuro-FuzzySystem (NFS), particle swarm optimization (PSO), recursiveleast-squares estimator (RLSE), time series
Current Density Effect on Nickel Electroplating Using Post Supercritical CO2 Mixed Watts Electrolyte
In this study, a nickel film with nano-crystalline grains,
high hardness and smooth surface was electrodeposited using a post
supercritical carbon dioxide (CO2) mixed Watts electrolyte. Although
the hardness was not as high as its Sc-CO2 counterpart, the thin coating
contained significantly less number of nano-sized pinholes. By
measuring the escape concentration of the dissolved CO2 in post
Sc-CO2 mixed electrolyte with the elapsed time, it was believed that
the residue of dissolved CO2 bubbles should closely relate to the
improvement in hardness and surface roughness over its conventional
plating counterpart. Therefore, shortening the duration of
electroplating with the raise of current density up to 0.5 A/cm2 could
effectively retain more post Sc-CO2 mixing effect. This study not only
confirms the roles of dissolved CO2 bubbles in electrolyte but also
provides a potential process to overcome most issues associated with
the cost in building high-pressure chamber for large size products and
continuous plating using supercritical method.
Additive-free electrolyte, electroplating, nickel,
Evaluation of the Immunoregulatory Activity of rFip-gts Purified from Baculovirus-infected Insect Cells
Fip-gts, an immunomodulatory protein purified from Ganoderma tsugae, has been reported to possess therapeutic effects in the treatment of cancer and autoimmune disease. For medicinal application, a recombinant Fip-gts was successfully expressed and purified in Sf21 insect cells by our previously work. It is important to evaluate the immunomodulatory activity of the rFip-gts. To assess the immunomodulatory potential of rFip-gts, the T lymphocytes of murine splenocytes were used in the present study. Results revealed that rFip-gts induced cellular aggregation formation. Additionally, the expression of IL-2 and IFN-r were up-regulated after the treatment of rFip-gts, and a corresponding increased production of IL-2 and IFN-r in a dose-dependent manner. The results showed that rFip-gts has an immunomodulatory activity in inducing Th1 lymphocytes from murine splenocytes released IL-2 and IFN-γ, thus suggest that rFip-gts may have therapeutic potential in vivo as an immune modulator.
Fungal immunomodulatory protein, Ganodermatsugae, Interleukin 2, Interferon γ, Lingzhi.
Synthesis and Characterization of PEG-Silane Functionalized Iron Oxide Nanoparticle as MRI T2 Contrast Agent
Iron oxide nanoparticle was synthesized by reactive-precipitation method followed by high speed centrifuge and phase transfer in order to stabilized nanoparticles in the solvent. Particle size of SPIO was 8.2 nm by SEM, and the hydraulic radius was 17.5 nm by dynamic light scattering method. Coercivity and saturated magnetism were determined by VSM (vibrating sample magnetometer), coercivity of nanoparticle was lower than 10 Hc, and the saturated magnetism was higher than 65 emu/g. Stabilized SPIO was then transferred to aqueous phase by reacted with excess amount of poly (ethylene glycol) (PEG) silane. After filtration and dialysis, the SPIO T2 contrast agent was ready to use. The hydraulic radius of final product was about 70~100 nm, the relaxation rates R2 (1/T2) measured by magnetic resonance imaging (MRI) was larger than 200(sec-1).
Contrast Agent, Iron Oxide Nanoparticle, Magnetic Resonance Imaging, Nanoparticle Stabilization
The Framework of Termination Mechanism in Modern Emergency Management
Termination Mechanism is an indispensible part of the
emergency management mechanism. Despite of its importance in both
theory and practice, it is almost a brand new field for researching. The
concept of termination mechanism is proposed firstly in this paper,
and the design and implementation which are helpful to guarantee the
effect and integrity of emergency management are discussed secondly.
Starting with introduction of the problems caused by absent
termination and incorrect termination, the essence of termination
mechanism is analyzed, a model based on Optimal Stopping Theory is
constructed and the termination index is given. The model could be
applied to find the best termination time point.. Termination decision
should not only be concerned in termination stage, but also in the
whole emergency management process, which makes it a dynamic
decision making process. Besides, the main subjects and the procedure
of termination are illustrated after the termination time point is given.
Some future works are discussed lastly.
Emergency management, Termination Mechanism,Optimal Termination Model, Decision Making, Optimal StoppingTheory.
Mitigating the Clipping Noise by Using the Oversampling Scheme in OFDM Systems
In an Orthogonal Frequency Division Multiplexing (OFDM) systems, the Peak to Average power Ratio (PAR) is high. The clipping signal scheme is a useful and simple method to reduce the PAR. However, it introduces additional noise that degrades the systems performance. We propose an oversampling scheme to deal with the received signal in order to reduce the clipping noise by using Finite Impulse Response (FIR) filter. Coefficients of filter are obtained by correlation function of the received signal and the oversampling information at receiver. The performance of the proposed technique is evaluated for frequency selective channel. Results show that the proposed scheme can mitigate the clipping noise significantly for OFDM systems and in order to maintain the system's capacity, the clipping ratio should be larger than 2.5.
Orthogonal frequency division multiplexing, peak-to-average power ratio, oversampling.
Region-Based Image Fusion with Artificial Neural Network
For most image fusion algorithms separate
relationship by pixels in the image and treat them more or less
independently. In addition, they have to be adjusted different
parameters in different time or weather. In this paper, we propose a
region–based image fusion which combines aspects of feature and
pixel-level fusion method to replace only by pixel. The basic idea is
to segment far infrared image only and to add information of each
region from segmented image to visual image respectively. Then we
determine different fused parameters according different region. At
last, we adopt artificial neural network to deal with the problems of
different time or weather, because the relationship between fused
parameters and image features are nonlinear. It render the fused
parameters can be produce automatically according different states.
The experimental results present the method we proposed indeed
have good adaptive capacity with automatic determined fused
parameters. And the architecture can be used for lots of applications.
Image fusion, Region-based fusion, Segmentation,
Neural network, Multi-sensor.
Modeling and Design of an Active Leg Orthosis for Tumble Protection
The design of an active leg orthosis for tumble
protection is proposed in this paper. The orthosis would be applied to
assist elders or invalids in rebalancing while they fall unexpectedly.
We observe the regain balance motion of healthy and youthful people,
and find the difference to elders or invalids. First, the physical model
of leg would be established, and we consider the leg motions are
achieve through four joints (phalanx stem, ankle, knee, and hip joint)
and five links (phalanges, talus, tibia, femur, and hip bone). To
formulate the dynamic equations, the coordinates which can clearly
describe the position in 3D space are first defined accordance with the
human movement of leg, and the kinematics and dynamics of the leg
movement can be formulated based on the robotics. For the purpose,
assisting elders and invalids in avoiding tumble, the posture variation
of unbalance and regaining balance motion are recorded by the
motion-capture image system, and the trajectory is taken as the desire
one. Then we calculate the force and moment of each joint based on
the leg motion model through programming MATLAB code. The
results would be primary information of the active leg orthosis design
for tumble protection.
Active leg orthosis, Tumble protection
Dynamic Performance Indicators for Aged-Care Construction Projects
Key performance indicators (KPIs) are used for post
result evaluation in the construction industry, and they normally do
not have provisions for changes. This paper proposes a set of
dynamic key performance indicators (d-KPIs) which predicts the
future performance of the activity being measured and presents the
opportunity to change practice accordingly. Critical to the
predictability of a construction project is the ability to achieve
automated data collection. This paper proposes an effective way to
collect the process and engineering management data from an
integrated construction management system. The d-KPI matrix,
consisting of various indicators under seven categories, developed
from this study can be applied to close monitoring of the
development projects of aged-care facilities. The d-KPI matrix also
enables performance measurement and comparison at both project
and organization levels.
Aged-care project, construction, dynamic KPI,
Pro-inflammatory Phenotype of COPD Fibroblasts not Compatible with Repair in COPD Lung
COPD is characterized by loss of elastic fibers from
small airways and alveolar walls, with the decrease in elastin
increasing with disease severity. It is unclear why there is a lack of
repair of elastic fibers. We have examined fibroblasts cultured from
lung tissue from normal and COPD subjects to determine if the
secretory profile explains lack of tissue repair. In this study,
fibroblasts were cultured from lung parenchyma of bronchial
carcinoma patients with varying degrees of COPD; controls
(non-COPD, n=5), mild COPD (GOLD 1, n=5) and moderate-severe
COPD (GOLD 2-3, n=12). Measurements were made of proliferation,
senescence-associated beta-galactosidase-1, mRNA expression of
IL-6, IL-8, MMP-1, tropoelastin and versican, and protein levels for
IL-6, IL-8, PGE2, tropoelastin, insoluble elastin, and versican. It was
found that GOLD 2-3 fibroblasts proliferated more slowly (p
COPD,pulmonary fibroblasts,pro-inflammatory phenotype, versican, elastin
Data Mining Applied to the Predictive Model of Triage System in Emergency Department
The Emergency Department of a medical center in
Taiwan cooperated to conduct the research. A predictive model of
triage system is contracted from the contract procedure, selection of
parameters to sample screening. 2,000 pieces of data needed for the
patients is chosen randomly by the computer. After three
categorizations of data mining (Multi-group Discriminant Analysis,
Multinomial Logistic Regression, Back-propagation Neural
Networks), it is found that Back-propagation Neural Networks can
best distinguish the patients- extent of emergency, and the accuracy
rate can reach to as high as 95.1%. The Back-propagation Neural
Networks that has the highest accuracy rate is simulated into the triage
acuity expert system in this research. Data mining applied to the
predictive model of the triage acuity expert system can be updated
regularly for both the improvement of the system and for education
training, and will not be affected by subjective factors.
Back-propagation Neural Networks, Data Mining, Emergency Department, Triage System.
Active Power Filtering Implementation Using Photovoltaic System with Reduced Energy Storage Capacitor
A novel three-phase active power filter (APF) circuit with photovoltaic (PV) system to improve the quality of service and to reduce the capacity of energy storage capacitor is presented. The energy balance concept and sampling technique were used to simplify the calculation algorithm for the required utility source current and to control the voltage of the energy storage capacitor. The feasibility was verified by using the Pspice simulations and experiments. When the APF mode was used during non-operational period, not only the utilization rate, power factor and power quality could be improved, but also the capacity of energy storage capacitor could sparing. As the results, the advantages of the APF circuit are simplicity of control circuits, low cost, and good transient response.
active power filter, sampling, energy-storagecapacitor, harmonic current, energy balance.
Join and Meet Block Based Default Definite Decision Rule Mining from IDT and an Incremental Algorithm
Using maximal consistent blocks of tolerance relation
on the universe in incomplete decision table, the concepts of join block
and meet block are introduced and studied. Including tolerance class,
other blocks such as tolerant kernel and compatible kernel of an object
are also discussed at the same time. Upper and lower approximations
based on those blocks are also defined. Default definite decision rules
acquired from incomplete decision table are proposed in the paper. An
incremental algorithm to update default definite decision rules is
suggested for effective mining tasks from incomplete decision table
into which data is appended. Through an example, we demonstrate
how default definite decision rules based on maximal consistent
blocks, join blocks and meet blocks are acquired and how optimization
is done in support of discernibility matrix and discernibility function
in the incomplete decision table.
rough set, incomplete decision table, maximalconsistent block, default definite decision rule, join and meet block.
A Security Module for Car Appliances
In this paper we discuss on the security module for the
car appliances to prevent stealing and illegal use on other cars. We
proposed an open structure including authentication and encryption by
embed a security module in each to protect car appliances. Illegal
moving and use a car appliance with the security module without
permission will lead the appliance to useless. This paper also presents
the component identification and deal with relevant procedures. It is at
low cost to recover from destroys by the burglar. Expect this paper to
offer the new business opportunity to the automotive and technology
Automotive, component identification, electronic
immobilizer, key management.
Applications of Rough Set Decompositions in Information Retrieval
This paper proposes rough set models with three
different level knowledge granules in incomplete information system
under tolerance relation by similarity between objects according to
their attribute values. Through introducing dominance relation on the
discourse to decompose similarity classes into three subclasses: little
better subclass, little worse subclass and vague subclass, it dismantles
lower and upper approximations into three components. By using
these components, retrieving information to find naturally hierarchical
expansions to queries and constructing answers to elaborative queries
can be effective. It illustrates the approach in applying rough set
models in the design of information retrieval system to access different
granular expanded documents. The proposed method enhances rough
set model application in the flexibility of expansions and elaborative
queries in information retrieval.
Incomplete information system, Rough set model,tolerance relation, dominance relation, approximation, decomposition,elaborative query.
A Design of Array Transcranial Magnetic Stimulation Coil System
This research proposed a new design of helmet-shaped
array transcranial magnetic stimulation coil system. It was constructed
using several sagittal directional wires and several coronal directional
wires. By varying the current direction and strength on each wire, this
array coil system could be constructed into the circular coil and
figure-eight coil of different size. Also, this proposed coil system can
flexibly not only change the stimulation location, range, type and
strength, but also change the shape and the channel number of coil
TMS, circular coils, figure-eight coil, array coil
Recovering the Clipped OFDM Figurebased on the Conic Function
In Orthogonal Frequency Division Multiplexing (OFDM) systems, the peak to average power ratio (PAR) is much high. The clipping signal scheme is a useful method to reduce PAR. Clipping the OFDM signal, however, increases the overall noise level by introducing clipping noise. It is necessary to recover the figure of the original signal at receiver in order to reduce the clipping noise. Considering the continuity of the signal and the figure of the peak, we obtain a certain conic function curve to replace the clipped signal module within the clipping time. The results of simulation show that the proposed scheme can reduce the systems? BER (bit-error rate) 10 times when signal-to-interference-and noise-ratio (SINR) equals to 12dB. And the BER performance of the proposed scheme is superior to that of kim's scheme, too.
Orthogonal Frequency Division Multiplexing, Peak-to-Average Power Ratio, clipping time, conic function.
An Efficient Data Mining Approach on Compressed Transactions
In an era of knowledge explosion, the growth of data
increases rapidly day by day. Since data storage is a limited resource,
how to reduce the data space in the process becomes a challenge issue.
Data compression provides a good solution which can lower the
required space. Data mining has many useful applications in recent
years because it can help users discover interesting knowledge in large
databases. However, existing compression algorithms are not
appropriate for data mining. In [1, 2], two different approaches were
proposed to compress databases and then perform the data mining
process. However, they all lack the ability to decompress the data to
their original state and improve the data mining performance. In this
research a new approach called Mining Merged Transactions with the
Quantification Table (M2TQT) was proposed to solve these problems.
M2TQT uses the relationship of transactions to merge related
transactions and builds a quantification table to prune the candidate
itemsets which are impossible to become frequent in order to improve
the performance of mining association rules. The experiments show
that M2TQT performs better than existing approaches.
Association rule, data mining, merged transaction,quantification table.
Automatic 2D/2D Registration using Multiresolution Pyramid based Mutual Information in Image Guided Radiation Therapy
Medical image registration is the key technology in image guided radiation therapy (IGRT) systems. On the basis of the previous work on our IGRT prototype with a biorthogonal x-ray imaging system, we described a method focused on the 2D/2D rigid-body registration using multiresolution pyramid based mutual information in this paper. Three key steps were involved in the method ： firstly, four 2D images were obtained including two x-ray projection images and two digital reconstructed radiographies（DRRs ） as the input for the registration ； Secondly, each pair of the corresponding x-ray image and DRR image were matched using multiresolution pyramid based mutual information under the ITK registration framework ； Thirdly, we got the final couch offset through a coordinate transformation by calculating the translations acquired from the two pairs of the images. A simulation example of a parotid gland tumor case and a clinical example of an anthropomorphic head phantom were employed in the verification tests. In addition, the influence of different CT slice thickness were tested. The simulation results showed that the positioning errors were 0.068±0.070, 0.072±0.098, 0.154±0.176mm along three axes which were lateral, longitudinal and vertical. The clinical test indicated that the positioning errors of the planned isocenter were 0.066, 0.07, 2.06mm on average with a CT slice thickness of 2.5mm. It can be concluded that our method with its verified accuracy and robustness can be effectively used in IGRT systems for patient setup.
2D/2D registration, image guided radiation therapy, multi resolution pyramid, mutual information.
Noise-Improved Signal Detection in Nonlinear Threshold Systems
We discuss the signal detection through nonlinear
threshold systems. The detection performance is assessed by the
probability of error Per . We establish that: (1) when the signal is
complete suprathreshold, noise always degrades the signal detection
both in the single threshold system and in the parallel array of
threshold devices. (2) When the signal is a little subthreshold, noise
degrades signal detection in the single threshold system. But in the
parallel array, noise can improve signal detection, i.e., stochastic
resonance (SR) exists in the array. (3) When the signal is predominant
subthreshold, noise always can improve signal detection and SR
always exists not only in the single threshold system but also in the
parallel array. (4) Array can improve signal detection by raising the
number of threshold devices. These results extend further the
applicability of SR in signal detection.
Probability of error, signal detection, stochasticresonance, threshold system.
Transform-Domain Rate-Distortion Optimization Accelerator for H.264/AVC Video Encoding
In H.264/AVC video encoding, rate-distortion
optimization for mode selection plays a significant role to achieve
outstanding performance in compression efficiency and video quality.
However, this mode selection process also makes the encoding
process extremely complex, especially in the computation of the ratedistortion
cost function, which includes the computations of the sum
of squared difference (SSD) between the original and reconstructed
image blocks and context-based entropy coding of the block. In this
paper, a transform-domain rate-distortion optimization accelerator
based on fast SSD (FSSD) and VLC-based rate estimation algorithm
is proposed. This algorithm could significantly simplify the hardware
architecture for the rate-distortion cost computation with only
ignorable performance degradation. An efficient hardware structure
for implementing the proposed transform-domain rate-distortion
optimization accelerator is also proposed. Simulation results
demonstrated that the proposed algorithm reduces about 47% of total
encoding time with negligible degradation of coding performance.
The proposed method can be easily applied to many mobile video
application areas such as a digital camera and a DMB (Digital
Multimedia Broadcasting) phone.
Context-adaptive variable length coding (CAVLC),H.264/AVC, rate-distortion optimization (RDO), sum of squareddifference (SSD).
Flow Visualization of Angled Supersonic Jets into a Supersonic Cross Flow
This paper describes Nano-particle based Planar Laser
Scattering (NPLS) flow visualization of angled supersonic jets into a
supersonic cross flow based on the HYpersonic Low TEmperature
(HYLTE) nozzle which was widely used in DF chemical laser. In
order to investigate the non-reacting flowfield in the HYLTE nozzle, a
testing section with windows was designed and manufactured. The
impact of secondary fluids orifice separation on mixing was examined.
For narrow separation of orifices, the secondary fuel penetration
increased obviously compared to diluent injection, which means
smaller separation of diluent and fuel orifices would enhance the
mixing of fuel and oxidant. Secondary injections with angles of 30, 40
and 50 degrees were studied. It was found that the injectant
penetration increased as the injection angle increased, while the
interfacial surface area to entrain the freestream fluid is largest when
the injection angle is 40 degree.
HYLTE nozzle, NPLS, supersonic mixing, transverse
A Study of the Lighting Control System for a Daylit Office
Increasing user comfort and reducing operation costs
have always been primary objectives of lighting control strategies in a
building. This paper proposes an architecture of the lighting control
system for a daylit office. The system consists of the lighting
controller, A/D & D/A converter, dimmable LED lights, and the
lighting management software. Verification tests are conducted using
the proposed system specialized for the interior lighting of a open-plan
office. The results showed the proposed architecture of the lighting
system would improve the overall system reliability, lower the system
cost, and provide ease of installation and maintenance.
control, dimming, LED, lighting.
Subpixel Detection of Circular Objects Using Geometric Property
In this paper, we propose a method for detecting
circular shapes with subpixel accuracy. First, the geometric properties
of circles have been used to find the diameters as well as the
circumference pixels. The center and radius are then estimated by the
circumference pixels. Both synthetic and real images have been tested
by the proposed method. The experimental results show that the new
method is efficient.
Subpixel, least squares estimation, circle detection,
Development of Perez-Du Mortier Calibration Algorithm for Ground-Based Aerosol Optical Depth Measurement with Validation using SMARTS Model
Aerosols are small particles suspended in air that have wide varying spatial and temporal distributions. The concentration of aerosol in total columnar atmosphere is normally measured using aerosol optical depth (AOD). In long-term monitoring stations, accurate AOD retrieval is often difficult due to the lack of frequent calibration. To overcome this problem, a near-sea-level Langley calibration algorithm is developed using the combination of clear-sky detection model and statistical filter. It attempts to produce a dataset that consists of only homogenous and stable atmospheric condition for the Langley calibration purposes. In this paper, a radiance-based validation method is performed to further investigate the feasibility and consistency of the proposed algorithm at different location, day, and time. The algorithm is validated using SMARTS model based n DNI value. The overall results confirmed that the proposed calibration algorithm feasible and consistent for measurements taken at different sites and weather conditions.
Aerosol optical depth, direct normal irradiance, Langley calibration, radiance-based validation, SMARTS.
Tumor Necrosis Factor-α Regulates Heme Oxygenase-1 Expression in Endothelial Cells via the Phosphorylation of JNK/p38
Heme oxygenase-1 (HO-1), an enzyme degrading heme to carbon monoxide, iron, and biliverdin, has been recognized as playing a crucial role in cellular defense against stressful conditions, not only related to heme release. In the present study, the effects of TNF-a on the expression of heme oxygenase-1 (HO-1) in human aortic endothelial cells (HAECs) as well as the related mechanisms were investigated. 10 ng/mL TNF-α treatment significantly increased HO-1 expression after 6h, then a further increase at 12h and declined at 24h. Treatment with 2 ng/mL of TNF-a after 12 h resulted in a significant increase in HO-1 expression, which peaked at 10 ng/mL, then declined at 20 ng/mL. TNF-α induced HO-1 expression and then HO-1 expression reduced vascular cell adhesion molecule-1 (VCAM-1) expression. Phosphorylation studies of ERK1/2, JNK, and p38, three subgroups of mitogen-activated protein kinases (MAPKs) demonstrated TNF-α-induced ERK1/2, JNK, and p38 phosphorylation. The increase in HO-1 expression in response to TNF-α treatment was affected by pretreatment with SP600125 (a JNK inhibitor) and SB203580 (a p38 inhibitor), not with PD98059 (an ERK1/2 inhibitor). The expression of HO-1 was stronger in aortas of TNF-α-treated apo-E deficient mice when compared with control mice. These results suggest that low dose of TNF-α treatment notably induced HO-1 expression was mediated through JNK/p38 phosphorylation and may have a protective potential in cardiovascular diseases and inflammatory response through the regulation of HO-1 expression.
Heme oxygenase-1 inflammation, endothelial cells, mitogen-activated protein kinases (MAPKs).
Guidelines for Selecting the Appropriate Heel Insert for Long-Standing Ladies
Feet and ankles are parts of human body that receive high-pressure in every day. Feet disorders such as ankle sprain, achilles tendonitis, heel pain, and plantar fasciitis are very common. There are many causes for these feet disorders such as wearing high heels, obesity, sports activity, and standing for a long time. There are many reliefs for feet disorders such as heel insert. However, they come in various shapes and use different materials. There are no specifications in which type is suitable for specific user. This has led to the proposed research to provide guidelines for selecting the appropriate heel insert for ladies who face with long-standing carriers. This research uses contact-measuring techniques to test forces, contact area, and pressure acting on a person’s feet in various standing positions with different insert materials and shapes. The proper material for making insert will be presented and discussed.
Heel inserts, Long-standing person, Contact-data acquisition, Finite element analysis, Ethylene-vinyl acetate (EVA).
The Automated Selective Acquisition System
To support design process for launching the product on time, reverse engineering (RE) process has been introduced for quickly generating 3D CAD model from its physical object. The accuracy of the 3D CAD model depends upon the data acquisition technique selected, contact or non-contact methods. In order to reduce times used for acquiring surface and eliminating noises, the automated selective acquisition system has been developed and presented in this research as the alternative channel for non-contact acquisition technique where the data is selectively and locally scanned contour by contour without performing data reduction process. The results present as the organized contour points which are directly used to generate 3D virtual model. The comparison between the proposed technique and another non-contact scanning technique has been presented and discussed.
Automated selective acquisition system, Non-contact acquisition, Reverse engineering, 3D scanners.
The Effects of NaF Concentration on the Zinc Coating Electroplated in Supercritical CO2 Mixed Zinc Chloride Bath
This research studies the electroplating of zinc coating
in the zinc chloride bath mixed with supercritical CO2. The sodium
fluoride (NaF) was used as the bath additive to change the structure
and property of the coating, and therefore the roughness and corrosion
resistance of the zinc coating was investigated. The surface
characterization was performed using optical microscope (OM), X-ray
diffractometer (XRD), and α-step profilometer. Moreover, the
potentiodynamic polarization measurement in 3% NaCl solution was
employed in the corrosion resistance evaluation. Because of the
emulsification of the electrolyte mixed in Sc-CO2, the electroplated
zinc produced the coating with smoother surface, smaller grain, better
throwing power and higher corrosion resistance. The main role played
by the NaF was to reduce the coating’s roughness and grain size. In
other words, the CO2 mixed with the electrolyte under the supercritical
condition performed the similar function as brighter and leveler in zinc
electroplating to enhance the throwing power and corrosion resistance
of the coating.
Supercritical CO2, zinc-electroplating, sodium
A Study of Semantic Analysis of LED Illustrated Traffic Directional Arrow in Different Style
In the past, the most comprehensively adopted light
source was incandescent light bulbs, but with the appearance of LED
light sources, traditional light sources have been gradually replaced by
LEDs because of its numerous superior characteristics. However,
many of the standards do not apply to LEDs as the two light sources
are characterized differently. This also intensifies the significance of
studies on LEDs. As a Kansei design study investigating the visual
glare produced by traffic arrows implemented with LEDs, this study
conducted a semantic analysis on the styles of traffic arrows used in
domestic and international occasions. The results will be able to
reduce drivers’ misrecognition that results in the unsuccessful arrival
at the destination, or in traffic accidents. This study started with a
literature review and surveyed the status quo before conducting
experiments that were divided in two parts. The first part involved a
screening experiment of arrow samples, where cluster analysis was
conducted to choose five representative samples of LED displays. The
second part was a semantic experiment on the display of arrows using
LEDs, where the five representative samples and the selected ten
adjectives were incorporated. Analyzing the results with
Quantification Theory Type I, it was found that among the
composition of arrows, fletching was the most significant factor that
influenced the adjectives. In contrast, a “no fletching” design was
more abstract and vague. It lacked the ability to convey the intended
message and might bear psychological negative connotation including
“dangerous,” “forbidden,” and “unreliable.” The arrow design
consisting of “> shaped fletching” was found to be more concrete and
definite, showing positive connotation including “safe,” “cautious,”
and “reliable.” When a stimulus was placed at a farther distance, the
glare could be significantly reduced; moreover, the visual evaluation
scores would be higher. On the contrary, if the fletching and the shaft
had a similar proportion, looking at the stimuli caused higher
evaluation at a closer distance. The above results will be able to be
applied to the design of traffic arrows by conveying information
definitely and rapidly. In addition, drivers’ safety could be enhanced
by understanding the cause of glare and improving visual
LED, arrow, Kansei research, preferred imagery.
Substantial Fatigue Similarity of a New Small-Scale Test Rig to Actual Wheel-Rail System
The substantial similarity of fatigue mechanism in a
new test rig for rolling contact fatigue (RCF) has been investigated. A
new reduced-scale test rig is designed to perform controlled RCF
tests in wheel-rail materials. The fatigue mechanism of the rig is
evaluated in this study using a combined finite element-fatigue
prediction approach. The influences of loading conditions on fatigue
crack initiation have been studied. Furthermore, the effects of some
artificial defects (squat-shape) on fatigue lives are examined. To
simulate the vehicle-track interaction by means of the test rig, a threedimensional
finite element (FE) model is built up. The nonlinear
material behaviour of the rail steel is modelled in the contact
interface. The results of FE simulations are combined with the critical
plane concept to determine the material points with the greatest
possibility of fatigue failure. Based on the stress-strain responses, by
employing of previously postulated criteria for fatigue crack initiation
(plastic shakedown and ratchetting), fatigue life analysis is carried
out. The results are reported for various loading conditions and
different defect sizes. Afterward, the cyclic mechanism of the test rig
is evaluated from the operational viewpoint. The results of fatigue
life predictions are compared with the expected number of cycles of
the test rig by its cyclic nature. Finally, the estimative duration of the
experiments until fatigue crack initiation is roughly determined.
Fatigue, test rig, crack initiation, life, rail, squats.
Two Kinds of Self-Oscillating Circuits Mechanically Demonstrated
This study introduces two types of self-oscillating
circuits that are frequently found in power electronics applications.
Special effort is made to relate the circuits to the analogous mechanical
systems of some important scientific inventions: Galileo’s pendulum
clock and Coulomb’s friction model. A little touch of related history
and philosophy of science will hopefully encourage curiosity, advance
the understanding of self-oscillating systems and satisfy the aspiration
of some students for scientific literacy. Finally, the two self-oscillating
circuits are applied to design a simple class-D audio amplifier.
Self-oscillation, sigma-delta modulator, pendulum
clock, Coulomb friction, class-D amplifier.
A Combined Neural Network Approach to Soccer Player Prediction
An artificial neural network is a mathematical model
inspired by biological neural networks. There are several kinds of
neural networks and they are widely used in many areas, such as:
prediction, detection, and classification. Meanwhile, in day to day life,
people always have to make many difficult decisions. For example,
the coach of a soccer club has to decide which offensive player
to be selected to play in a certain game. This work describes a
novel Neural Network using a combination of the General Regression
Neural Network and the Probabilistic Neural Networks to help a
soccer coach make an informed decision.
General Regression Neural Network, Probabilistic Neural Networks, Neural function.
Bioinformatics and Molecular Biological Characterization of a Hypothetical Protein SAV1226 as a Potential Drug Target for Methicillin/Vancomycin- Staphylococcus aureus Infections
Methicillin/multiple-resistant Staphylococcus aureus
(MRSA) are infectious bacteria that are resistant to common
antibiotics. A previous in silico study in our group has identified a
hypothetical protein SAV1226 as one of the potential drug targets. In
this study, we reported the bioinformatics characterization, as well as
cloning, expression, purification and kinetic assays of hypothetical
protein SAV1226 from methicillin/vancomycin-resistant
Staphylococcus aureus Mu50 strain. MALDI-TOF/MS analysis
revealed a low degree of structural similarity with known proteins.
Kinetic assays demonstrated that hypothetical protein SAV1226 is
neither a domain of an ATP dependent dihydroxyacetone kinase nor
of a phosphotransferase system (PTS) dihydroxyacetone kinase,
suggesting that the function of hypothetical protein SAV1226 might
be misannotated on public databases such as UniProt and
Dihydroxyacetone kinase, essential genes,
Methicillin-resistant Staphylococcus aureus, drug target.
The Mechanical and Electrochemical Properties of DC-Electrodeposited Ni-Mn Alloy Coating with Low Internal Stress
The nickel-manganese (Ni-Mn) alloy coating prepared
from DC electrodeposition process in sulphamate bath was studied.
The effects of process parameters, such as current density and
electrolyte composition, on the cathodic current efficiency,
microstructure, internal stress and mechanical properties were
investigated. Because of its crucial effect on the application to the
electroforming of microelectronic components, the development of
low internal stress coating with high leveling power was emphasized.
It was found that both the coating’s manganese content and the
cathodic current efficiency increased with the raise in current density.
In addition, the internal stress of the deposited coating showed
compressive nature at low current densities while changed to tensile
one at higher current densities. Moreover, the metallographic
observation, X-ray diffraction measurement, and polarization curve
measurement were conducted. It was found that the Ni-Mn coating
consisted of nano-sized columnar grains and the maximum hardness of
the coating was associated with (111) preferred orientation in the
microstructure. The grain size was refined along with the increase in
the manganese content of the coating, which accordingly, raised its
hardness and resistance to annealing softening. In summary, the
Ni-Mn coating prepared at lower current density of 1-2 A/dm2 had low
internal stress, high leveling power, and better corrosion resistance.
DC plating, internal stress, leveling power, Ni-Mn
Angle of Arrival Estimation Using Maximum Likelihood Method
Multiple-input multiple-output (MIMO) radar has
received increasing attention in recent years. MIMO radar has many
advantages over conventional phased array radar such as target
detection,resolution enhancement, and interference suppression. In
this paper, the results are presented from a simulation study of MIMO
uniformly-spaced linear array (ULA) antennas. The performance is
investigated under varied parameters, including varied array size,
pseudo random (PN) sequence length, number of snapshots, and
signal to noise ratio (SNR). The results of MIMO are compared to a
traditional array antenna.
Multiple-input multiple-output (MIMO) radar,
phased array antenna, target detection, radar signal processing.
Uniformly Strong Persistence for a Predator-Prey Model with Modified Leslie-Gower and Holling-Type II Schemes
In this paper, a asymptotically periodic predator-prey
model with Modified Leslie-Gower and Holling-Type II schemes
is investigated. Some sufficient conditions for the uniformly strong
persistence of the system are established. Our result is an important
complementarity to the earlier results.
Predator-prey model, uniformly strong persistence,
asymptotically periodic, Holling-type II.
An Augmented-Reality Interactive Card Game for Teaching Elementary School Students
Game-based learning can enhance the learning
motivation of students and provide a means for them to learn through
playing games. This study used augmented reality technology to
develop an interactive card game as a game-based teaching aid for
delivering elementary school science course content with the aim of
enhancing student learning processes and outcomes. Through playing
the proposed card game, students can familiarize themselves with
appearance, features, and foraging behaviors of insects. The system
records the actions of students, enabling teachers to determine their
students’ learning progress. In this study, 37 students participated in an
assessment experiment and provided feedback through questionnaires.
Their responses indicated that they were significantly more motivated
to learn after playing the game, and their feedback was mostly
Game-based learning, learning motivation, teaching
aid, augmented reality.
Recycling of Sclareolide in the Crystallization Mother Liquid of Sclareolide by Adsorption and Chromatography
Sclareolide is made from sclareol by oxidiative synthesis and subsequent crystallization, while the crystallization mother liquor still contains 15%~30%wt of sclareolide to be reclaimed. With the reaction material of sclareol is provided as plant extract, many sorts of complex impurities exist in the mother liquor. Due to the difficulty in recycling sclareolide after solvent recovery, it is common practice for the factories to discard the mother liquor, which not only results in loss of sclareolide, but also contributes extra environmental burden. In this paper, a process based on adsorption and elution has been presented for recycling of sclareolide from mother liquor. After pretreatment of the crystallization mother liquor by HZ-845 resin to remove parts of impurities, sclareolide is adsorbed by HZ-816 resin. The HZ-816 resin loaded with sclareolide is then eluted by elution solvent. Finally, the eluent containing sclareolide is concentrated and fed into the crystallization step in the process. By adoption of the recycle from mother liquor, total yield of sclareolide increases from 86% to 90% with a stable purity of the final sclareolide products maintained.
Sclareolide, resin, adsorption, chromatography.
A Study on the Effect of Design Factors of Slim Keyboard’s Tactile Feedback
With the rapid development of computer technology,
the design of computers and keyboards moves towards a trend of
slimness. The change of mobile input devices directly influences
users’ behavior. Although multi-touch applications allow entering
texts through a virtual keyboard, the performance, feedback, and
comfortableness of the technology is inferior to traditional keyboard,
and while manufacturers launch mobile touch keyboards and
projection keyboards, the performance has not been satisfying.
Therefore, this study discussed the design factors of slim
pressure-sensitive keyboards. The factors were evaluated with an
objective (accuracy and speed) and a subjective evaluation
(operability, recognition, feedback, and difficulty) depending on the
shape (circle, rectangle, and L-shaped), thickness (flat, 3mm, and
6mm), and force (35±10g, 60±10g, and 85±10g) of the keyboard.
Moreover, MANOVA and Taguchi methods (regarding
signal-to-noise ratios) were conducted to find the optimal level of each
design factor. The research participants, by their typing speed (30
words/ minute), were divided in two groups. Considering the
multitude of variables and levels, the experiments were implemented
using the fractional factorial design. A representative model of the
research samples were established for input task testing. The findings
of this study showed that participants with low typing speed primarily
relied on vision to recognize the keys, and those with high typing
speed relied on tactile feedback that was affected by the thickness and
force of the keys. In the objective and subjective evaluation, a
combination of keyboard design factors that might result in higher
performance and satisfaction was identified (L-shaped, 3mm, and
60±10g) as the optimal combination. The learning curve was analyzed
to make a comparison with a traditional standard keyboard to
investigate the influence of user experience on keyboard operation.
The research results indicated the optimal combination provided input
performance to inferior to a standard keyboard. The results could serve
as a reference for the development of related products in industry and
for applying comprehensively to touch devices and input interfaces
which are interacted with people.
Input performance, mobile device, slim keyboard,
Frequency Domain Analysis for Hopf Bifurcation in a Delayed Competitive Web-site Model
In this paper, applying frequency domain approach, a
delayed competitive web-site system is investigated. By choosing
the parameter α as a bifurcation parameter, it is found that Hopf
bifurcation occurs as the bifurcation parameter α passes a critical
values. That is, a family of periodic solutions bifurcate from the
equilibrium when the bifurcation parameter exceeds a critical value.
Some numerical simulations are included to justify the theoretical
analysis results. Finally, main conclusions are given.
Web-site system, stability, Nyquist criterion, Hopf
bifurcation, frequency domain.
Active Islanding Detection Method Using Intelligent Controller
An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results.
Distributed generators, probabilistic fuzzy neural network, islanding detection, non-detection zone.
Numerical Simulations of Electronic Cooling with In-Line and Staggered Pin Fin Heat Sinks
Three-dimensional incompressible turbulent fluid flow and heat transfer of pin fin heat sinks using air as a cooling fluid are numerically studied in this study. Two different kinds of pin fins are compared in the thermal performance, including circular and square cross sections, both are in-line and staggered arrangements. The turbulent governing equations are solved using a control-volume- based finite-difference method. Subsequently, numerical computations are performed with the realizable k - ԑ turbulence for the parameters studied, the fin height H, fin diameter D, and Reynolds number (Re) in the range of 7 ≤ H ≤ 10, 0.75 ≤ D ≤ 2, 2000 ≤ Re ≤ 126000 respectively. The numerical results are validated with available experimental data in the literature and good agreement has been found. It indicates that circular pin fins are streamlined in comparing with the square pin fins, the pressure drop is small than that of square pin fins, and heat transfer is not as good as the square pin fins. The thermal performance of the staggered pin fins is better than that of in-line pin fins because the staggered arrangements produce large disturbance. Both in-line and staggered arrangements show the same behavior for thermal resistance, pressure drop, and the entropy generation.
Pin-fin, heat sinks, simulations, turbulent flow.
An Improved Variable Tolerance RSM with a Proportion Threshold
In rough set models, tolerance relation, similarity
relation and limited tolerance relation solve different situation
problems for incomplete information systems in which there exists a
phenomenon of missing value. If two objects have the same few
known attributes and more unknown attributes, they cannot
distinguish them well. In order to solve this problem, we presented two
improved limited and variable precision rough set models. One is
symmetric, the other one is non-symmetric. They all use more
stringent condition to separate two small probability equivalent objects
into different classes. The two models are needed to engage further
study in detail. In the present paper, we newly form object classes with
a different respect comparing to the first suggested model. We
overcome disadvantages of non-symmetry regarding to the second
suggested model. We discuss relationships between or among several
models and also make rule generation. The obtained results by
applying the second model are more accurate and reasonable.
Incomplete information system, rough set, symmetry,
Indoor Mobile Robot Positioning Based on Wireless Fingerprint Matching
This paper discusses the design of an indoor mobile robot positioning system. The problem of indoor positioning is solved through Wi-Fi fingerprint positioning to implement a low cost deployment. A wireless fingerprint matching algorithm based on the similarity of unequal length sequences is presented. Candidate sequences selection is defined as a set of mappings, and detection errors caused by wireless hotspot stability and the change of interior pattern can be corrected by transforming the unequal length sequences into equal length sequences. The presented scheme was verified experimentally to achieve the accuracy requirements for an indoor positioning system with low deployment cost.
Fingerprint match, indoor positioning, mobile robot positioning system, Wi-Fi, wireless fingerprint.
Design and Implementation of a Memory Safety Isolation Method Based on the Xen Cloud Environment
In view of the present cloud security problem has increasingly become one of the major obstacles hindering the development of the cloud computing, put forward a kind of memory based on Xen cloud environment security isolation technology implementation. And based on Xen virtual machine monitor system, analysis of the model of memory virtualization is implemented, using Xen memory virtualization system mechanism of super calls and grant table, based on the virtual machine manager internal implementation of access control module (ACM) to design the security isolation system memory. Experiments show that, the system can effectively isolate different customer domain OS between illegal access to memory data.
Cloud security, memory isolation, Xen, virtual machine.
Dependence of Shaft Stiffness on the Crack Location
In this study, an analytical model is developed to study crack breathing behavior under the effect of crack location and unbalance force. Crack breathing behavior is determined using effectual bending angle by studying the transient change in closed area of the crack. The status of the crack of a balanced shaft is symmetrical about shaft rotational angle and the duration of each crack status remains unchanged. The global stiffness of the balanced shaft is independent of crack location. Different crack breathing behavior for the unbalanced shaft has been observed. The influence of crack location on the unbalanced shaft stiffness can be divided into three regions. When the crack is located between 0.3L and 0.8335L, where L is the total length of the shaft, the unbalanced shaft is less stiff and when located outside this region it is stiffer than the balanced shaft. It was also found that unbalanced shaft stiffness has a maximum value with a crack at 0.1946L, a minimum value at 0.8053L and same value as balanced shaft at 0.3L and 0.8335L.
Cracked shaft, crack location, shaft stiffness, unbalanced force.
High Sensitivity Crack Detection and Locating with Optimized Spatial Wavelet Analysis
In this study, a spatial wavelet-based crack localization technique for a thick beam is presented. Wavelet scale in spatial wavelet transformation is optimized to enhance crack detection sensitivity. A windowing function is also employed to erase the edge effect of the wavelet transformation, which enables the method to detect and localize cracks near the beam/measurement boundaries. Theoretical model and vibration analysis considering the crack effect are first proposed and performed in MATLAB based on the Timoshenko beam model. Gabor wavelet family is applied to the beam vibration mode shapes derived from the theoretical beam model to magnify the crack effect so as to locate the crack. Relative wavelet coefficient is obtained for sensitivity analysis by comparing the coefficient values at different positions of the beam with the lowest value in the intact area of the beam. Afterward, the optimal wavelet scale corresponding to the highest relative wavelet coefficient at the crack position is obtained for each vibration mode, through numerical simulations. The same procedure is performed for cracks with different sizes and positions in order to find the optimal scale range for the Gabor wavelet family. Finally, Hanning window is applied to different vibration mode shapes in order to overcome the edge effect problem of wavelet transformation and its effect on the localization of crack close to the measurement boundaries. Comparison of the wavelet coefficients distribution of windowed and initial mode shapes demonstrates that window function eases the identification of the cracks close to the boundaries.
Edge effect, scale optimization, small crack locating, spatial wavelet.
Decision Making under Strict Uncertainty: Case Study in Sewer Network Planning
In decision making under strict uncertainty, decision makers have to choose a decision without any information about the states of nature. The classic criteria of Laplace, Wald, Savage, Hurwicz and Starr are introduced and compared in a case study of sewer network planning. Furthermore, results from different criteria are discussed and analyzed. Moreover, this paper discusses the idea that decision making under strict uncertainty (DMUSU) can be viewed as a two-player game and thus be solved by a solution concept in game theory: Nash equilibrium.
Decision criteria, decision making, sewer network planning, strict uncertainty.
An Improved Limited Tolerance Rough Set Model
Some extended rough set models in incomplete information system cannot distinguish the two objects that have few known attributes and more unknown attributes; some cannot make a flexible and accurate discrimination. In order to solve this problem, this paper suggests an improved limited tolerance rough set model using two thresholds to control what two objects have a relationship between them in limited tolerance relation and to classify objects. Our practical study case shows the model can get fine and reasonable decision results.
Decision rule, incomplete information system, limited tolerance relation, rough set model.
Numerical Analysis of Effect of Crack Location on the Crack Breathing Behavior
In this work, a three-dimensional finite element model was developed to investigate the crack breathing behavior at different crack locations considering the effect of unbalance force. A two-disk rotor with a crack is simulated using ABAQUS. The duration of each crack status (open, closed and partially open/closed) during a full shaft rotation was examined to analyse the crack breathing behavior. Unbalanced shaft crack breathing behavior was found to be different at different crack locations. The breathing behavior of crack along the shaft length is divided into different regions depending on the unbalance force and crack location. The simulated results in this work can be further utilised to obtain the time-varying stiffness matrix of the cracked shaft element under the influence of unbalance force.
Crack breathing, crack location, slant crack, unbalance force, rotating shaft.
Invariant Characters of Tolerance Class and Reduction under Homomorphism in IIS
Some invariant properties of incomplete information systems homomorphism are studied in this paper. Demand conditions of tolerance class, attribute reduction, indispensable attribute and dispensable attribute being invariant under homomorphism in incomplete information system are revealed and discussed. The existing condition of endohomomorphism on an incomplete information system is also explored. It establishes some theoretical foundations for further investigations on incomplete information systems in rough set theory, like in information systems.
Attribute reduction, homomorphism, incomplete information system, rough set, tolerance relation.
Studies on Properties of Knowledge Dependency and Reduction Algorithm in Tolerance Rough Set Model
Relation between tolerance class and indispensable attribute and knowledge dependency in rough set model with tolerance relation is explored. After giving definitions and concepts of knowledge dependency and knowledge dependency degree for incomplete information system in tolerance rough set model by distinguishing decision attribute containing missing attribute value or not, the result of maintaining reflectivity, transitivity, augmentation, decomposition law and merge law for complete knowledge dependency is proved. Knowledge dependency degrees (not complete knowledge dependency degrees) only satisfy some laws after transitivity, augmentation and decomposition operations. An algorithm to solve attribute reduction in an incomplete decision table is designed. The correctness is checked by an example.
Incomplete information system, rough set, tolerance relation, knowledge dependence, attribute reduction.
A Tuning Method for Microwave Filter via Complex Neural Network and Improved Space Mapping
This paper presents an intelligent tuning method of
microwave filter based on complex neural network and improved
space mapping. The tuning process consists of two stages: the initial
tuning and the fine tuning. At the beginning of the tuning, the return
loss of the filter is transferred to the passband via the error of phase.
During the fine tuning, the phase shift caused by the transmission line
and the higher order mode is removed by the curve fitting. Then, an
Cauchy method based on the admittance parameter (Y-parameter) is
used to extract the coupling matrix. The influence of the resonant
cavity loss is eliminated during the parameter extraction process. By
using processed data pairs (the amount of screw variation and the
variation of the coupling matrix), a tuning model is established by
the complex neural network. In view of the improved space mapping
algorithm, the mapping relationship between the actual model and
the ideal model is established, and the amplitude and direction of the
tuning is constantly updated. Finally, the tuning experiment of the
eight order coaxial cavity filter shows that the proposed method has
a good effect in tuning time and tuning precision.
Microwave filter, scattering parameter (s-parameter),
coupling matrix, intelligent tuning.
Impact of Positive Psychology Education and Interventions on Well-Being: A Study of Students Engaged in Pastoral Care
Positive psychology investigates human strengths and virtues and promotes well-being. Relying on this assumption, positive interventions have been continuously designed to build pleasure and happiness, joy and contentment, engagement and meaning, hope and optimism, satisfaction and gratitude, spirituality, and various other positive measures of well-being. In line with this model of positive psychology and interventions, this study investigated certain measures of well-being in a group of 45 students enrolled in an 18-week positive psychology course and simultaneously engaged in service-oriented interventions that they chose for themselves based on the course content and individual interests. Students’ well-being was measured at the beginning and end of the course. The well-being indicators included positive automatic thoughts, optimism and hope, satisfaction with life, and spirituality. A paired-samples t-test conducted to evaluate the impact of class content and service-oriented interventions on students’ scores of well-being indicators indicated statistically significant increase from pre-class to post-class scores. There were also significant gender differences in post-course well-being scores, with females having higher levels of well-being than males. A two-way between groups analysis of variance indicated a significant interaction effect of age by gender on the post-course well-being scores, with females in the age group of 56-65 having the highest scores of well-being in comparison to the males in the same age group. Regression analyses indicated that positive automatic thought significantly predicted hope and satisfaction with life in the pre-course analysis. In the post-course regression analysis, spiritual transcendence made a significant contribution to optimism, and positive automatic thought made a significant contribution to both hope and satisfaction with life. Finally, a significant test between pre-course and post-course regression coefficients indicated that the regression coefficients at pre-course were significantly different from post-course coefficients, suggesting that the positive psychology course and the interventions were helpful in raising the levels of well-being. The overall results suggest a substantial increase in the participants’ well-being scores after engaging in the positive-oriented interventions, implying a need for designing more positive interventions in education to promote well-being.
Hope, optimism, positive automatic thoughts, satisfaction with life, spirituality, well-being.
An Improved Adaptive Dot-Shape Beamforming Algorithm Research on Frequency Diverse Array
Frequency diverse array (FDA) beamforming is a technology developed in recent years, and its antenna pattern has a unique angle-distance-dependent characteristic. However, the beam is always required to have strong concentration, high resolution and low sidelobe level to form the point-to-point interference in the concentrated set. In order to eliminate the angle-distance coupling of the traditional FDA and to make the beam energy more concentrated, this paper adopts a multi-carrier FDA structure based on proposed power exponential frequency offset to improve the array structure and frequency offset of the traditional FDA. The simulation results show that the beam pattern of the array can form a dot-shape beam with more concentrated energy, and its resolution and sidelobe level performance are improved. However, the covariance matrix of the signal in the traditional adaptive beamforming algorithm is estimated by the finite-time snapshot data. When the number of snapshots is limited, the algorithm has an underestimation problem, which leads to the estimation error of the covariance matrix to cause beam distortion, so that the output pattern cannot form a dot-shape beam. And it also has main lobe deviation and high sidelobe level problems in the case of limited snapshot. Aiming at these problems, an adaptive beamforming technique based on exponential correction for multi-carrier FDA is proposed to improve beamforming robustness. The steps are as follows: first, the beamforming of the multi-carrier FDA is formed under linear constrained minimum variance (LCMV) criteria. Then the eigenvalue decomposition of the covariance matrix is performed to obtain the diagonal matrix composed of the interference subspace, the noise subspace and the corresponding eigenvalues. Finally, the correction index is introduced to exponentially correct the small eigenvalues of the noise subspace, improve the divergence of small eigenvalues in the noise subspace, and improve the performance of beamforming. The theoretical analysis and simulation results show that the proposed algorithm can make the multi-carrier FDA form a dot-shape beam at limited snapshots, reduce the sidelobe level, improve the robustness of beamforming, and have better performance.
Multi-carrier frequency diverse array, adaptive beamforming, correction index, limited snapshot, robust.
Simulation-Based Optimization of a Non-Uniform Piezoelectric Energy Harvester with Stack Boundary
This research presents an analytical model for the development of an energy harvester with piezoelectric rings stacked at the boundary of the structure based on the Adomian decomposition method. The model is applied to geometrically non-uniform beams to derive the steady-state dynamic response of the structure subjected to base motion excitation and efficiently harvest the subsequent vibrational energy. The in-plane polarization of the piezoelectric rings is employed to enhance the electrical power output. A parametric study for the proposed energy harvester with various design parameters is done to prepare the dataset required for optimization. Finally, simulation-based optimization technique helps to find the optimum structural design with maximum efficiency. To solve the optimization problem, an artificial neural network is first trained to replace the simulation model, and then, a genetic algorithm is employed to find the optimized design variables. Higher geometrical non-uniformity and length of the beam lowers the structure natural frequency and generates a larger power output.
Piezoelectricity, energy harvesting, simulation-based optimization, artificial neural network, genetic algorithm.