Abstract: In this paper an extensive verification of the extraction
method (published earlier) that consistently accounts for self-heating
and Early effect to accurately extract both base and thermal resistance
of bipolar junction transistors is presented. The method verification is
demonstrated on advanced RF SiGe HBTs were the extracted results
for the thermal resistance are compared with those from another
published method that ignores the effect of Early effect on internal
base-emitter voltage and the extracted results of the base resistance
are compared with those determined from noise measurements. A
self-consistency of our method in the extracted base resistance and
thermal resistance using compact model simulation results is also
carried out in order to study the level of accuracy of the method.
Abstract: Regarding previous research studies it was concluded
that thin-walled fiber-cement composites are able to conduct electric
current under specific conditions. This property is ensured by using
of various kinds of carbon materials. Though carbon fibers are less
conductive than metal fibers, composites with carbon fibers were
evaluated as better current conductors than the composites with metal
fibers. The level of electric conductivity is monitored by the means of
impedance measurement of designed samples. These composites
could be used for a range of applications such as heating of
trafficable surfaces or shielding of electro-magnetic fields.
The aim of the present research was to design an element with the
ability to monitor internal processes in building structures and
prevent them from collapsing. As a typical element for laboratory
testing there was chosen a concrete column, which was repeatedly
subjected to load by simple pressure with continual monitoring of
changes in electrical properties.
Abstract: There are many expand of Wi-Fi zones provided
mobile careers and usage of wireless access point at home as increase
of usage of wireless internet caused by the use of smart phone. This
paper shows wireless local area network status, security threats of
WLAN and functionality of major wireless access point in Korea. We
propose security countermeasures concerned with life cycle of access
point from manufacturing to installation, using and finally disposal.
There needed to releasing with configured secure at access point.
Because, it is most cost effective resolution than stage of installation or
other life cycle of access point.
Abstract: In the field of concepts, the measure of Wu and Palmer [1] has the advantage of being simple to implement and have good performances compared to the other similarity measures [2]. Nevertheless, the Wu and Palmer measure present the following disadvantage: in some situations, the similarity of two elements of an IS-A ontology contained in the neighborhood exceeds the similarity value of two elements contained in the same hierarchy. This situation is inadequate within the information retrieval framework. To overcome this problem, we propose a new similarity measure based on the Wu and Palmer measure. Our objective is to obtain realistic results for concepts not located in the same way. The obtained results show that compared to the Wu and Palmer approach, our measure presents a profit in terms of relevance and execution time.
Abstract: Greenhouse gases (GHG) emissions impose major
threat to global warming potential (GWP). Unfortunately
manufacturing sector is one of the major sources that contribute
towards the rapid increase in greenhouse gases (GHG) emissions. In
manufacturing sector electric power consumption is the major driver
that influences CO2 emission. Titanium alloys are widely utilized in
aerospace, automotive and petrochemical sectors because of their
high strength to weight ratio and corrosion resistance. Titanium
alloys are termed as difficult to cut materials because of their poor
machinability rating. The present study analyzes energy consumption
during cutting with reference to material removal rate (MRR).
Surface roughness was also measured in order to optimize energy
consumption.
Abstract: Water quality and freshwater fish diversity from nine
waterfalls at Khao Luang National Park, Thailand was examined.
Streams were shallow, fast flowing with clear water and rocky and
sandy substrate. The mean water quality of waterfalls at Khao Luang
National Park were as following pH 7.50, air temperature 24.27 °C,
water temperature 26.37 °C, dissolved oxygen 7.88 mg/l, hardness
4.44-21.33 mg/l, alkalinity 3.55-11.88 mg/(as CaCO3). Twenty fish
species were found at Khao Luang National Park belonging to nine
families. A cluster analysis of water quality at Khao Luang National
Park revealed that waterfalls at Khao Luang National Park were
divided into two groups: A and B. Group A composed of two
waterfalls (i.e. Aie Kaew and Wangmaipak) that flew to the Gulf of
Thailand side. Group B composed of seven waterfalls (i.e. Promlok,
Kalom, Nuafa, Suankun, Soidaw, Suanhai, and Thapae) that flew to
the Andaman Sea side (Fig. 2) .The Cyprinids represented the major
species in all the waterfalls comprising of 45%.
Abstract: Nowadays, obtaining traditional statistics and reports
is not adequate for the needs of organizational managers. The
managers need to analyze and to transform the raw data into
knowledge in the world filled with information. Therefore in this
regard various processes have been developed. In the meantime the
artificial intelligence-based processes are used and the new topics
such as business intelligence and knowledge discovery have
emerged. In the current paper it is sought to study the business
intelligence and its applications in the organizations.
Abstract: This paper discusses on the use of Spline Interpolation
and Mean Square Error (MSE) as tools to process data acquired from
the developed simulator that shall replicate sea bed logging environment.
Sea bed logging (SBL) is a new technique that uses marine
controlled source electromagnetic (CSEM) sounding technique and is
proven to be very successful in detecting and characterizing hydrocarbon
reservoirs in deep water area by using resistivity contrasts. It uses
very low frequency of 0.1Hz to 10 Hz to obtain greater wavelength.
In this work the in house built simulator was used and was provided
with predefined parameters and the transmitted frequency was varied
for sediment thickness of 1000m to 4000m for environment with and
without hydrocarbon. From series of simulations, synthetics data were
generated. These data were interpolated using Spline interpolation
technique (degree of three) and mean square error (MSE) were
calculated between original data and interpolated data. Comparisons
were made by studying the trends and relationship between frequency
and sediment thickness based on the MSE calculated. It was found
that the MSE was on increasing trends in the set up that has the
presence of hydrocarbon in the setting than the one without. The MSE
was also on decreasing trends as sediment thickness was increased
and with higher transmitted frequency.
Abstract: The mitigation of crop loss due to damaging freezes
requires accurate air temperature prediction models. Previous work
established that the Ward-style artificial neural network (ANN) is a
suitable tool for developing such models. The current research
focused on developing ANN models with reduced average prediction
error by increasing the number of distinct observations used in
training, adding additional input terms that describe the date of an
observation, increasing the duration of prior weather data included in
each observation, and reexamining the number of hidden nodes used
in the network. Models were created to predict air temperature at
hourly intervals from one to 12 hours ahead. Each ANN model,
consisting of a network architecture and set of associated parameters,
was evaluated by instantiating and training 30 networks and
calculating the mean absolute error (MAE) of the resulting networks
for some set of input patterns. The inclusion of seasonal input terms,
up to 24 hours of prior weather information, and a larger number of
processing nodes were some of the improvements that reduced
average prediction error compared to previous research across all
horizons. For example, the four-hour MAE of 1.40°C was 0.20°C, or
12.5%, less than the previous model. Prediction MAEs eight and 12
hours ahead improved by 0.17°C and 0.16°C, respectively,
improvements of 7.4% and 5.9% over the existing model at these
horizons. Networks instantiating the same model but with different
initial random weights often led to different prediction errors. These
results strongly suggest that ANN model developers should consider
instantiating and training multiple networks with different initial
weights to establish preferred model parameters.
Abstract: Elastic light single-scattering spectroscopy system
with a single optical fiber probe was employed to differentiate cancerous prostate tissue from non-cancerous prostate tissue ex-vivo just after radical prostatectomy. First, ELSSS spectra were acquired
from cancerous prostate tissue to define its spectral features. Then,
spectra were acquired from normal prostate tissue to define difference in spectral features between the cancerous and normal
prostate tissues. Of the total 66 tissue samples were evaluated from
nine patients by ELSSS system. Comparing of histopathology results
and ELSSS measurements revealed that sign of the spectral slopes of
cancerous prostate tissue is negative and non-cancerous tissue is positive in the wavelength range from 450 to 750 nm. Based on the
correlation between histopathology results and sign of the spectral
slopes, ELSSS system differentiates cancerous prostate tissue from
non- cancerous with a sensitivity of 0.95 and a specificity of 0.94.
Abstract: More and more natural disasters are happening every
year: floods, earthquakes, volcanic eruptions, etc. In order to reduce
the risk of possible damages, governments all around the world are
investing into development of Early Warning Systems (EWS) for
environmental applications. The most important task of the EWS is
identification of the onset of critical situations affecting environment
and population, early enough to inform the authorities and general
public. This paper describes an approach for monitoring of flood
protections systems based on machine learning methods. An
Artificial Intelligence (AI) component has been developed for
detection of abnormal dike behaviour. The AI module has been
integrated into an EWS platform of the UrbanFlood project (EU
Seventh Framework Programme) and validated on real-time
measurements from the sensors installed in a dike.
Abstract: In this paper, a field oriented control (FOC) induction motor drive is presented. In order to eliminate the speed sensor, an adaptation algorithm for tuning the rotor speed is proposed. Based on the Model Reference Adaptive System (MRAS) scheme, the rotor speed is tuned to obtain an exact FOC induction motor drive. The reference and adjustable models, developed in stationary stator reference frame, are used in the MRAS scheme to estimate induction rotor speed from measured terminal voltages and currents. The Integral Proportional (IP) gains speed controller are tuned by a modern approach that is the Particle Swarm Optimization (PSO) algorithm in order to optimize the parameters of the IP controller. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. The proposed algorithm has been tested by numerical simulation, showing the capability of driving load.
Abstract: In the various working field, vibration may cause injurious to human body. Especially, in case of the vibration which is constantly and repeatedly transferred to the human. That gives serious physical problem, so called, Reynaud phenomenon. In this paper, we propose a vibration transmissibility reduction module with flexure mechanism for personal tools. At first, we select a target personal tool, grass cutter, and measure the level of vibration transmissibility on the hand. And then, we develop the concept design of the module that has stiffness for reduction the vibration transmissibility more than 20%, where the vibration transmissibility is measured with an accelerometer. In addition, the vibration reduction can be enhanced when the interior gap between inner and outer body is filled with silicone gel. This will be verified by the further experiment.
Abstract: During last decades, worldwide researchers dedicated
efforts to develop machine-based seismic Early Warning systems,
aiming at reducing the huge human losses and economic damages.
The elaboration time of seismic waveforms is to be reduced in order
to increase the time interval available for the activation of safety
measures. This paper suggests a Data Mining model able to correctly
and quickly estimate dangerousness of the running seismic event.
Several thousand seismic recordings of Japanese and Italian
earthquakes were analyzed and a model was obtained by means of a
Bayesian Network (BN), which was tested just over the first
recordings of seismic events in order to reduce the decision time and
the test results were very satisfactory.
The model was integrated within an Early Warning System
prototype able to collect and elaborate data from a seismic sensor
network, estimate the dangerousness of the running earthquake and
take the decision of activating the warning promptly.
Abstract: Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Therefore, this paper provides a model which supports the selection of measures by applying multi-objective analysis to find an optimal solution. Additionally, a list of measures is also provided to make the selection easier and more effective without any leakage of measures.
Abstract: As the latest advancement and trend in IT field, Green
& Smart IT has attracted more and more attentions from researchers.
This study focuses on the development of assessing tools which can be
used for evaluating Green & Smart IT level within an organization. In
order to achieve meaningful results, a comprehensive review of
relevant literature was performed in advance, then, Delphi survey and
other processes were also employed to develop the assessment tools
for Green & Smart IT level. Two rounds of Delphi questionnaire
survey were conducted with 20 IT experts in public sector. The results
reveal that the top five weighted KPIs to evaluate maturity of Green &
Smart IT were: (1) electronic execution of business process; (2)
shutdown of unused IT devices; (3) virtualization of severs; (4)
automation of constant temperature and humidity; and (5) introduction
of smart-work system. Finally, these tools were applied to case study
of a public research institute in Korea. The findings presented in this
study provide organizations with useful implications for the
introduction and promotion of Green & Smart IT in the future
Abstract: This paper aims to fabricated high quality anodic
aluminum oxide (AAO) film by anodization method. AAO pore size,
pore density, and film thickness can be controlled in 10~500 nm,
108~1011 pore．cm-2, and 1~100 μm. AAO volume and surface area can
be computed based on structural parameters such as thickness, pore
size, pore density, and sample size. Base on the thetorical calculation,
AAO has 100 μm thickness with 15 nm, 60 nm, and 500 nm pore
diameters AAO surface areas are 1225.2 cm2, 3204.4 cm2, and 549.7
cm2, respectively. The large unit surface area which is useful for
adsorption application. When AAO adsorbed pH indictor of
bromphenol blue presented a sensitive pH detection of solution
change. This testing method can further be used for the precise
measurement of biotechnology, convenience measurement of
industrial engineering.
Abstract: The need for reputation assessment is particularly strong in peer-to-peer (P2P) systems because the peers' personal site autonomy is amplified by the inherent technological decentralization of the environment. However, the decentralization notion makes the problem of designing a peer-to-peer based reputation assessment substantially harder in P2P networks than in centralized settings.Existing reputation systems tackle the reputation assessment process in an ad-hoc manner. There is no systematic and coherent way to derive measures and analyze the current reputation systems. In this paper, we propose a reputation assessment process and use it to classify the existing reputation systems. Simulation experiments are conducted and focused on the different methods in selecting the recommendation sources and retrieving the recommendations. These two phases can contribute significantly to the overall performance due to communication cost and coverage.
Abstract: Increased physical fitness participation has been
paralleled by increasedoveruse injuries such as insertional Achilles
tendinosis (AT). Treatment has provided inconsistentresults. The use
of extracorporeal shockwave therapy (ECSWT) offers a new
treatment consideration.The purpose of this study was to assess the
effects of ECSWTon pain, function, range of motion (ROM), joint
mobility and strength in patients with AT. Thirty subjects were
treated with ECSWT and measures were takenbefore and three
months after treatment. There was significant differences in visual
analog scale (VAS) scores for pain at rest (p=0.002); after activity
(p= 0.0001); overall improvement(p=0.0001); Lower Extremity
Functional Scale (LEFS) scores (p=0.002); dorsiflexion range of
motion (ROM) (p=0.0001); plantarflexion strength (p=0.025);
talocrural joint anterior glide (p=0.046); and subtalar joint medial and
lateral glide (p=0.025).ECSWT offers a new intervention that may
limit the progression of the disorder and the long term healthcare
costs associated with AT.
Abstract: The after–sales activities are nowadays acknowledged
as a relevant source of revenue, profit and competitive advantage in
most manufacturing industries. Top and middle management,
therefore, should focus on the definition of a structured business
performance measurement system for the after-sales business. The
paper aims at filling this gap, and presents an integrated methodology
for the after-sales network performance measurement, and provides
an empirical application to automotive case companies and their
official service network. This is the first study that presents an
integrated multivariate approach for total assessment and
improvement of after-sale services.