Abstract: Postmenopausal osteoporosis is a disorder
characterized by the progressive bone loss induced by estrogen
deficiency in postmenopausal women. This imbalance affects
calcium–phosphate metabolism and results in secondary
hyperparathyroidism. Purariae Radix (PR), the root of P. lobata
(Wild.) Ohwi, is one of the earliest medicinal herbs employed in
ancient China. PR contains a high quantity of isoflavones and their
glycosides, which are regarded as phytoestrogen. Few investigations
of PR are related to its osteoprotective effects. The present study is
designed to administer PR water extract to ovariectomized (OVX)
female rats, for the investigation of its possibly protective actions on
bone and to delineate the potential mechanisms involved. Our results
demonstrated that long-term treatment of PR could not significantly
improve bone properties, whereas it greatly ameliorated the condition
of secondary hyperparathyroidism induced by ovariectomy in those
animals. PR might be useful as alternative regimen for protecting
against postmenopausal bone loss.
Abstract: Ultrasound is useful in demonstrating bone mineral
density of regenerating osseous tissue as well as structural alterations.
A proposed ultrasound method, which included ultrasonography and
acoustic parameters measurement, was employed to evaluate its
efficacy in monitoring the bone callus changes in a rabbit tibial
distraction osteogenesis (DO) model.
The findings demonstrated that ultrasonographic images depicted
characteristic changes of the bone callus, typical of histology findings,
during the distraction phase. Follow-up acoustic parameters
measurement of the bone callus, including speed of sound, reflection
and attenuation, showed significant linear changes over time during
the distraction phase. The acoustic parameters obtained during the
distraction phase also showed moderate to strong correlation with
consolidated bone callus density and micro-architecture measured by
micro-computed tomography at the end of the consolidation phase.
The results support the preferred use of ultrasound imaging in the
early monitoring of bone callus changes during DO treatment.
Abstract: To simulate expected climate change, we implemented a two-factor (temperature and soil moisture) field design in a forest in Ontario, Canada. To manipulate moisture input, we erected rain-exclusion structures. Under each structure, plots were watered with one of three treatments and thermally controlled with three heat treatments to simulate changes in air temperature and rainfall based on the climate model (GCM) predictions for the study area. Environmental conditions (including untreated controls) were monitored tracking air temperature, soil temperature, soil moisture, and photosynthetically active radiation. We measured rainfall and relative humidity at the site outside the rain-exclusion structures. Analyses of environmental conditions demonstrates that the temperature manipulation was most effective at maintaining target temperature during the early part of the growing season, but it was more difficult to keep the warmest treatment at 5º C above ambient by late summer. Target moisture regimes were generally achieved however incoming solar radiation was slightly attenuated by the structures.
Abstract: An array of piezoelectric micro actuators can be used
for radiation of an ultrasonic carrier signal modulated in amplitude
with an acoustic signal, which yields audio frequency applications as
the air acts as a self-demodulating medium. This application is
known as the parametric array. We propose a parametric array with
array elements based on existing piezoelectric micro ultrasonic
transducer (pMUT) design techniques. In order to reach enough
acoustic output power at a desired operating frequency, a proper ratio
between number of array elements and array size needs to be used,
with an array total area of the order of one cm square. The
transducers presented are characterized via impedance, admittance,
noise figure, transducer gain and frequency responses.
Abstract: This paper presents a highly efficient algorithm for detecting and tracking humans and objects in video surveillance sequences. Mean shift clustering is applied on backgrounddifferenced image sequences. For efficiency, all calculations are performed on integral images. Novel corresponding exponential integral kernels are introduced to allow the application of nonuniform kernels for clustering, which dramatically increases robustness without giving up the efficiency of the integral data structures. Experimental results demonstrating the power of this approach are presented.
Abstract: Much has been written about the difficulties students
have with producing traditional dissertations. This includes both
native English speakers (L1) and students with English as a second
language (L2). The main emphasis of these papers has been on the
structure of the dissertation, but in all cases, even when electronic
versions are discussed, the dissertation is still in what most would
regard as a traditional written form.
Master of Science Degrees in computing disciplines require
students to gain technical proficiency and apply their knowledge to a
range of scenarios. The basis of this paper is that if a dissertation is a
means of showing that such a student has met the criteria for a pass,
which should be based on the learning outcomes of the dissertation
module, does meeting those outcomes require a student to
demonstrate their skills in a solely text based form, particularly in a
highly technical research project? Could it be possible for a student
to produce a series of related artifacts which form a cohesive package
that meets the learning out comes of the dissertation?
Abstract: Structural and UV/Visible optical properties can be
useful to describe a material for the CIGS solar cell active layer,
therefore, this work demonstrates the properties like surface
morphology, X-ray Photoelectron Spectroscopy (XPS) bonding
energy (EB) core level spectra, UV/Visible absorption spectra,
refractive index (n), optical energy band (Eg), reflection spectra for
the Cu25 (In16Ga9) Se40Te10 (CIGST-1) and Cu20 (In14Ga9) Se45Te12
(CIGST-2) chalcogenide compositions. Materials have been
exhibited homogenous surface morphologies, broading /-or diffusion
of bonding energy peaks relative elemental values and a high
UV/Visible absorption tendency in the wave length range 400 nm-
850 nm range with the optical energy band gaps 1.37 and 1.42
respectively. Subsequently, UV/Visible reflectivity property in the
wave length range 250 nm to 320 nm for these materials has also
been discussed.
Abstract: The analysis is mainly concentrating on the knowledge
management literatures productivity trend which subjects as
“knowledge management" in SSCI database. The purpose what the
analysis will propose is to summarize the trend information for
knowledge management researchers since core knowledge will be
concentrated in core categories. The result indicated that the literature
productivity which topic as “knowledge management" is still
increasing extremely and will demonstrate the trend by different
categories including author, country/territory, institution name,
document type, language, publication year, and subject area. Focus on
the right categories, you will catch the core research information. This
implies that the phenomenon "success breeds success" is more
common in higher quality publications.
Abstract: Text categorization - the assignment of natural language documents to one or more predefined categories based on their semantic content - is an important component in many information organization and management tasks. Performance of neural networks learning is known to be sensitive to the initial weights and architecture. This paper discusses the use multilayer neural network initialization with decision tree classifier for improving text categorization accuracy. An adaptation of the algorithm is proposed in which a decision tree from root node until a final leave is used for initialization of multilayer neural network. The experimental evaluation demonstrates this approach provides better classification accuracy with Reuters-21578 corpus, one of the standard benchmarks for text categorization tasks. We present results comparing the accuracy of this approach with multilayer neural network initialized with traditional random method and decision tree classifiers.
Abstract: As the Social network game(SNG) is rising
dramatically worldwide, an interesting aspect has appeared in the
demographic analysis. That is the ratio of the game users by gender.
Although the ratio of male and female users in online game was
60:40% previously, the ratio of male and female users in SNG stood at
47:53% which shows that the ratio of female users is higher than that
of male users. Here, it should be noted that 35% in those 53% female
users are the first-time users of game. This fact suggests that women
who were not interested in game previously has taken an interest in
SNG. Notwithstanding this issue, there have been little studies on the
female users of SNG although there are many studies that analyzed the
tendency of female users- online game play. This study conducted the
analyzed how the game-playing tendency of SNG gamers was
manifested in the game by gender. For that, this study will identify the
tendency of SNG users by gender based on the preceding studies that
analyzed the online game users by gender. The subject of this study
was confined to the farm and urban construction simulation games
which were offered based on the mobile application platform.
Regarding the methodology of study, the first focus group
interview(FGI) was conducted with the male and female users who
had played games on Social network service(SNS) until recently. Later,
the second one-on-one in-depth interview was conducted to gain an
insight into the psychological state of the subjects.
Abstract: Two completely different approaches for a Gigabit
Ethernet compliant stream transmission over 50m of 1mm PMMA SI-POF have been experimentally demonstrated and are compared in this paper. The first solution is based on a commercial RC-LED
transmission and a careful optimization of the physical layer architecture, realized during the POF-PLUS EU Project. The second solution exploits the performance of an edge-emitting laser at the
transmitter side in order to avoid any sort of electrical equalization at the receiver side.
Abstract: In this work, we present a novel active learning approach
for learning a visual object detection system. Our system
is composed of an active learning mechanism as wrapper around
a sub-algorithm which implement an online boosting-based learning
object detector. In the core is a combination of a bootstrap procedure
and a semi automatic learning process based on the online boosting
procedure. The idea is to exploit the availability of classifier during
learning to automatically label training samples and increasingly
improves the classifier. This addresses the issue of reducing labeling
effort meanwhile obtain better performance. In addition, we propose
a verification process for further improvement of the classifier.
The idea is to allow re-update on seen data during learning for
stabilizing the detector. The main contribution of this empirical study
is a demonstration that active learning based on an online boosting
approach trained in this manner can achieve results comparable or
even outperform a framework trained in conventional manner using
much more labeling effort. Empirical experiments on challenging data
set for specific object deteciton problems show the effectiveness of
our approach.
Abstract: Direct Torque Control is a control technique in AC
drive systems to obtain high performance torque control. The
conventional DTC drive contains a pair of hysteresis comparators.
DTC drives utilizing hysteresis comparators suffer from high torque
ripple and variable switching frequency. The most common solution
to those problems is to use the space vector depends on the reference
torque and flux. In this Paper The space vector modulation technique
(SVPWM) is applied to 2 level inverter control in the proposed
DTC-based induction motor drive system, thereby dramatically
reducing the torque ripple. Then the controller based on space vector
modulation is designed to be applied in the control of Induction
Motor (IM) with a three-level Inverter. This type of Inverter has
several advantages over the standard two-level VSI, such as a greater
number of levels in the output voltage waveforms, Lower dV/dt, less
harmonic distortion in voltage and current waveforms and lower
switching frequencies. This paper proposes a general SVPWM
algorithm for three-level based on standard two-level SVPWM. The
proposed scheme is described clearly and simulation results are
reported to demonstrate its effectiveness. The entire control scheme is
implemented with Matlab/Simulink.
Abstract: In this research, the researchers have managed to
design a model to investigate the current trend of stock price of the
"IRAN KHODRO corporation" at Tehran Stock Exchange by
utilizing an Adaptive Neuro - Fuzzy Inference system. For the Longterm
Period, a Neuro-Fuzzy with two Triangular membership
functions and four independent Variables including trade volume,
Dividend Per Share (DPS), Price to Earning Ratio (P/E), and also
closing Price and Stock Price fluctuation as an dependent variable are
selected as an optimal model. For the short-term Period, a neureo –
fuzzy model with two triangular membership functions for the first
quarter of a year, two trapezoidal membership functions for the
Second quarter of a year, two Gaussian combination membership
functions for the third quarter of a year and two trapezoidal
membership functions for the fourth quarter of a year were selected
as an optimal model for the stock price forecasting. In addition, three
independent variables including trade volume, price to earning ratio,
closing Stock Price and a dependent variable of stock price
fluctuation were selected as an optimal model. The findings of the
research demonstrate that the trend of stock price could be forecasted
with the lower level of error.
Abstract: To determine the presence and location of faults in a transmission by the adaptation of protective distance relay based on the measurement of fixed settings as line impedance is achieved by several different techniques. Moreover, a fast, accurate and robust technique for real-time purposes is required for the modern power systems. The appliance of radial basis function neural network in transmission line protection is demonstrated in this paper. The method applies the power system via voltage and current signals to learn the hidden relationship presented in the input patterns. It is experiential that the proposed technique is competent to identify the particular fault direction more speedily. System simulations studied show that the proposed approach is able to distinguish the direction of a fault on a transmission line swiftly and correctly, therefore suitable for the real-time purposes.
Abstract: This paper investigates the performance of Multiple- Input Multiple-Output (MIMO) feedback system combined with Orthogonal Frequency Division Multiplexing (OFDM). Two types of codebook based channel feedback techniques are used in this work. The first feedback technique uses a combination of both the long-term and short-term channel state information (CSI) at the transmitter, whereas the second technique uses only the short term CSI. The long-term and short-term CSI at the transmitter is used for efficient channel utilization. OFDM is a powerful technique employed in communication systems suffering from frequency selectivity. Combined with multiple antennas at the transmitter and receiver, OFDM proves to be robust against delay spread. Moreover, it leads to significant data rates with improved bit error performance over links having only a single antenna at both the transmitter and receiver. The effectiveness of these techniques has been demonstrated through the simulation of a MIMO-OFDM feedback system. The results have been evaluated for 4x4 MIMO channels. Simulation results indicate the benefits of the MIMO-OFDM channel feedback system over the one without incorporating OFDM. Performance gain of about 3 dB is observed for MIMO-OFDM feedback system as compared to the one without employing OFDM. Hence MIMO-OFDM becomes an attractive approach for future high speed wireless communication systems.
Abstract: In this paper we propose segmentation approach based
on Vector Quantization technique. Here we have used Kekre-s fast
codebook generation algorithm for segmenting low-altitude aerial
image. This is used as a preprocessing step to form segmented
homogeneous regions. Further to merge adjacent regions color
similarity and volume difference criteria is used. Experiments
performed with real aerial images of varied nature demonstrate that
this approach does not result in over segmentation or under
segmentation. The vector quantization seems to give far better results
as compared to conventional on-the-fly watershed algorithm.
Abstract: Dredging activities inevitably cause sediment
dispersion. In certain locations, where there are important ecological
areas such as mangroves or coral reefs, carefully planning the
dredging can significantly reduce negative impacts. This article
utilizes the dredging at Phuket port, Thailand, as a case study to
demonstrate how computer simulations can be helpful to protect
existing coral reefs. A software package named MIKE21 was
applied. Necessary information required by the simulations was
gathered. After calibrating and verifying the model, various dredging
scenario were simulated to predict spoil movement. The simulation
results were used as guidance to setting up an environmental
measure. Finally, the recommendation to dredge during flood tide
with silt curtains installed was made.
Abstract: This study links up the theories of social psychology,
economics and sport management to assess the impact of sport
participation on subjective well-being (SWB) and use a simple statistic
method to estimate the relative monetary value that sport participation
derives SWB for Taiwan-s college students. By constructing proper
measurements on sport participation and SWB respectively, a
structural equation model (SEM) is developed to perform a
confirmatory factory analysis, and the causal relationship between
sport participation and SWB as well as the effect of the demographic
variables on these two concepts are also discussed.
Abstract: 17α-ethinylestradiol (EE2) is a recalcitrant micropollutant which is found in small amounts in municipal wastewater. But these small amounts still adversely affect for the reproductive function of aquatic organisms. Evidence in the past suggested that full-scale WWTPs equipped with nitrification process enhanced the removal of EE2 in the municipal wastewater. EE2 has been proven to be able to be transformed by ammonia oxidizing bacteria (AOB) via co-metabolism. This research aims to clarify the EE2 degradation pattern by different consortium of ammonia oxidizing microorganism (AOM) including AOA (ammonia oxidizing archaea) and investigate contribution between the existing ammonia monooxygenase (AMO) and new synthesized AOM. The result showed that AOA or AOB of N. oligotropha cluster in enriched nitrifying activated sludge (NAS) from 2mM and 5mM, commonly found in municipal WWTPs, could degrade EE2 in wastewater via co-metabolism. Moreover, the investigation of the contribution between the existing ammonia monooxygenase (AMO) and new synthesized AOM demonstrated that the new synthesized AMO enzyme may perform ammonia oxidation rather than the existing AMO enzyme or the existing AMO enzyme may has a small amount to oxidize ammonia.