Abstract: Oral health is particular important to the hospitalized
patients with chronic schizophrenia for an extreme high potential of the respiratory infections. Due to the degeneration of physical capability, patients of this kind typically fall dependent in the activity of daily living (ADL). A very high percentage of patients had dental
problems of which mostly could be easily avoid by easy regular tooth brushing. Purpose of the project is to develop a mechanism in helping the schizophrenia patients in rebuilding a tooth-cleaning habit. The
project observed and evaluated the tooth-cleaning behavior of 100
male patients in a psychiatric hospital, and found the majority of them
ignored such an activity in a three-month period of time. In the meantime, the primary care-givers were not aware or not convinced
the importance of such a need of dental hygiene, and thus few if any
tooth cleaning training or knowledge on dental hygiene were given to
the patients. The project then developed a program based on the numerous observations and discussions. The improvement program
included patients- group education, care-givers- training, and a
tool-kit for tooth-brush holding was erected. The project launched
with some incentive package. The outcomes were encouraging with
87% of the patients had rebuilt their tooth-brushing habits against
previous 22%, and the tooth cleaning kits were 100% kept against 22%
in the past. This project had significantly improved the oral health of
the patients. The project, included the procedure and the tool-kit
holder specific for this purpose, was a good examples for psychiatric
hospitals.
Abstract: The protein domain structure has been widely used as the most informative sequence feature to computationally predict protein-protein interactions. However, in a recent study, a research group has reported a very high accuracy of 94% using hydrophobicity feature. Therefore, in this study we compare and verify the usefulness of protein domain structure and hydrophobicity properties as the sequence features. Using the Support Vector Machines (SVM) as the learning system, our results indicate that both features achieved accuracy of nearly 80%. Furthermore, domains structure had receiver operating characteristic (ROC) score of 0.8480 with running time of 34 seconds, while hydrophobicity had ROC score of 0.8159 with running time of 20,571 seconds (5.7 hours). These results indicate that protein-protein interaction can be predicted from domain structure with reliable accuracy and acceptable running time.
Abstract: Basel III (or the Third Basel Accord) is a global
regulatory standard on bank capital adequacy, stress testing and
market liquidity risk agreed upon by the members of the Basel
Committee on Banking Supervision in 2010-2011, and scheduled to
be introduced from 2013 until 2018. Basel III is a comprehensive set
of reform measures. These measures aim to; (1) improve the banking
sector-s ability to absorb shocks arising from financial and economic
stress, whatever the source, (2) improve risk management and
governance, (3) strengthen banks- transparency and disclosures.
Similarly the reform target; (1) bank level or micro-prudential,
regulation, which will help raise the resilience of individual banking
institutions to periods of stress. (2) Macro-prudential regulations,
system wide risk that can build up across the banking sector as well
as the pro-cyclical implication of these risks over time. These two
approaches to supervision are complementary as greater resilience at
the individual bank level reduces the risk system wide shocks.
Macroeconomic impact of Basel III; OECD estimates that the
medium-term impact of Basel III implementation on GDP growth is
in the range -0,05 percent to -0,15 percent per year. On the other hand
economic output is mainly affected by an increase in bank lending
spreads as banks pass a rise in banking funding costs, due to higher
capital requirements, to their customers. Consequently the estimated
effects on GDP growth assume no active response from monetary
policy. Basel III impact on economic output could be offset by a
reduction (or delayed increase) in monetary policy rates by about 30
to 80 basis points. The aim of this paper is to create a framework
based on the recent regulations in order to prevent financial crises.
Thus the need to overcome the global financial crisis will contribute
to financial crises that may occur in the future periods. In the first
part of the paper, the effects of the global crisis on the banking
system examine the concept of financial regulations. In the second
part; especially in the financial regulations and Basel III are analyzed.
The last section in this paper explored the possible consequences of
the macroeconomic impacts of Basel III.
Abstract: Embedded systems need to respect stringent real
time constraints. Various hardware components included in such
systems such as cache memories exhibit variability and therefore
affect execution time. Indeed, a cache memory access from an
embedded microprocessor might result in a cache hit where the
data is available or a cache miss and the data need to be fetched
with an additional delay from an external memory. It is therefore
highly desirable to predict future memory accesses during
execution in order to appropriately prefetch data without incurring
delays. In this paper, we evaluate the potential of several artificial
neural networks for the prediction of instruction memory
addresses. Neural network have the potential to tackle the nonlinear
behavior observed in memory accesses during program
execution and their demonstrated numerous hardware
implementation emphasize this choice over traditional forecasting
techniques for their inclusion in embedded systems. However,
embedded applications execute millions of instructions and
therefore millions of addresses to be predicted. This very
challenging problem of neural network based prediction of large
time series is approached in this paper by evaluating various neural
network architectures based on the recurrent neural network
paradigm with pre-processing based on the Self Organizing Map
(SOM) classification technique.
Abstract: The organic farmers use wider range of crop varieties than the conventional farming. Bread wheat is the most favorite and the most common food crop. The organic bread wheat is usually of worse technological quality. Therefore, it is supposed to be an attractive alternative to the hulled wheat species (einkorn, emmer wheat and spelt). Twenty-five hulled bread wheat varieties and control bread wheat ones were grown on the certified organic parcel in České Budějovice (the Czech Republic) between 2009 and 2012. Their baking quality was measured and evaluated with standard methods, and in accordance with ICC. The results have shown that the grain of hulled wheat varieties contain a lot of proteins in grains (up to 18 percent); even the organic hulled bread wheat varieties are characterized by such good baking quality. Einkorn and emmer wheat are of worse technological quality of proteins (low values of gluten index and Zeleny test), which is a disadvantage of these two wheat species. On the other hand, spelt wheat is of better technological quality and is similar to the control bread wheat varieties. Mixtures consisting of bread wheat, among others, are considered good alternatives; they may contribute to wider range of use of the hulled wheat species. It is one of the possibilities which may increase the proportion of proteins in bread wheat grains; the nutrition-rich hulled wheat grains may be also used in such way at the same time.
Abstract: Content-based music retrieval generally involves analyzing, searching and retrieving music based on low or high level features of a song which normally used to represent artists, songs or music genre. Identifying them would normally involve feature extraction and classification tasks. Theoretically the greater features analyzed, the better the classification accuracy can be achieved but with longer execution time. Technique to select significant features is important as it will reduce dimensions of feature used in classification and contributes to the accuracy. Artificial Immune System (AIS) approach will be investigated and applied in the classification task. Bio-inspired audio content-based retrieval framework (B-ACRF) is proposed at the end of this paper where it embraces issues that need further consideration in music retrieval performances.
Abstract: Wireless Sensor Networks (WSNs) are used to monitor/observe vast inaccessible regions through deployment of large number of sensor nodes in the sensing area. For majority of WSN applications, the collected data needs to be combined with geographic information of its origin to make it useful for the user; information received from remote Sensor Nodes (SNs) that are several hops away from base station/sink is meaningless without knowledge of its source. In addition to this, location information of SNs can also be used to propose/develop new network protocols for WSNs to improve their energy efficiency and lifetime. In this paper, range free localization protocols for WSNs have been proposed. The proposed protocols are based on weighted centroid localization technique, where the edge weights of SNs are decided by utilizing fuzzy logic inference for received signal strength and link quality between the nodes. The fuzzification is carried out using (i) Mamdani, (ii) Sugeno, and (iii) Combined Mamdani Sugeno fuzzy logic inference. Simulation results demonstrate that proposed protocols provide better accuracy in node localization compared to conventional centroid based localization protocols despite presence of unintentional radio frequency interference from radio frequency (RF) sources operating in same frequency band.
Abstract: The optimization problem using time scales is studied.
Time scale is a model of time. The language of time scales seems to
be an ideal tool to unify the continuous-time and the discrete-time
theories. In this work we present necessary conditions for a solution
of an optimization problem on time scales. To obtain that result we
use properties and results of the partial diamond-alpha derivatives for
continuous-multivariable functions. These results are also presented
here.
Abstract: In this work, several ASP solutions were flooded into
fractured models initially saturated with heavy oil at a constant flow
rate and different geometrical characteristics of fracture. The ASP
solutions are constituted from 2 polymers i.e. a synthetic polymer,
hydrolyzed polyacrylamide as well as a biopolymer, a surfactant and
2types of alkaline. The results showed that using synthetic
hydrolyzed polyacrylamide polymer increases ultimate oil recovery;
however, type of alkaline does not play a significant rule on oil
recovery. In addition, position of the injection well respect to the
fracture system has remarkable effects on ASP flooding. For instance
increasing angle of fractures with mean flow direction causes more
oil recovery and delays breakthrough time. This work can be
accounted as a comprehensive survey on ASP flooding which
considers most of effective factors in this chemical EOR method.
Abstract: The aim of this paper is to determine the stress levels
at the end of a long slender shaft such as a drilling assembly used in
the oil or gas industry using a mathematical model in real-time. The
torsional deflection experienced by this type of drilling shaft (about 4
KM length and 20 cm diameter hollow shaft with a thickness of 1
cm) can only be determined using a distributed modeling technique.
The main objective of this project is to calculate angular velocity and
torque at the end of the shaft by TLM method and also analyzing of
the behavior of the system by transient response. The obtained result
is compared with lumped modeling technique the importance of these
results will be evident only after the mentioned comparison. Two
systems have different transient responses and in this project because
of the length of the shaft transient response is very important.
Abstract: Power consumption is rapidly increased in data centers
because the number of data center is increased and more the scale of
data center become larger. Therefore, it is one of key research items to
reduce power consumption in data center. The peak power of a typical
server is around 250 watts. When a server is idle, it continues to use
around 60% of the power consumed when in use, though vendors are
putting effort into reducing this “idle" power load. Servers tend to
work at only around a 5% to 20% utilization rate, partly because of
response time concerns. An average of 10% of servers in their data
centers was unused. In those reason, we propose dynamic power
management system to reduce power consumption in green data
center. Experiment result shows that about 55% power consumption is
reduced at idle time.
Abstract: Automatic Extraction of Event information from
social text stream (emails, social network sites, blogs etc) is a vital
requirement for many applications like Event Planning and
Management systems and security applications. The key information
components needed from Event related text are Event title, location,
participants, date and time. Emails have very unique distinctions over
other social text streams from the perspective of layout and format
and conversation style and are the most commonly used
communication channel for broadcasting and planning events.
Therefore we have chosen emails as our dataset. In our work, we
have employed two statistical NLP methods, named as Finite State
Machines (FSM) and Hidden Markov Model (HMM) for the
extraction of event related contextual information. An application
has been developed providing a comparison among the two methods
over the event extraction task. It comprises of two modules, one for
each method, and works for both bulk as well as direct user input.
The results are evaluated using Precision, Recall and F-Score.
Experiments show that both methods produce high performance and
accuracy, however HMM was good enough over Title extraction and
FSM proved to be better for Venue, Date, and time.
Abstract: A method to determine experimentally the melting
rate, rm, and the heat transfer coefficients, αv (W/(m3K)), at
convective melting in a fixed bed of particles under adiabatic regime
is established in this paper. The method lies in the determining of the
melting rate by measuring the fixed bed height in time. Experimental
values of rm, α and α v were determined using cylindrical particles of
ice (d = 6.8 mm, h = 5.5 mm) and, as a melting agent, aqueous NaCl
solution with a temperature of 283 K at different values of the liquid
flow rate (11.63·10-6, 28.83·10-6, 38.83·10-6 m3/s).
Our experimental results were compared with those existing in
literature being noticed a good agreement for Re values higher than
50.
Abstract: A parallel computational fluid dynamics code has been
developed for the study of aerodynamic heating problem in hypersonic
flows. The code employs the 3D Navier-Stokes equations as the basic
governing equations to simulate the laminar hypersonic flow. The cell
centered finite volume method based on structured grid is applied for
spatial discretization. The AUSMPW+ scheme is used for the inviscid
fluxes, and the MUSCL approach is used for higher order spatial
accuracy. The implicit LU-SGS scheme is applied for time integration
to accelerate the convergence of computations in steady flows. A
parallel programming method based on MPI is employed to shorten
the computing time. The validity of the code is demonstrated by
comparing the numerical calculation result with the experimental data
of a hypersonic flow field around a blunt body.
Abstract: In recent years, the research in wireless sensor
network has increased steadily, and many studies were focusing on
reducing energy consumption of sensor nodes to extend their lifetimes.
In this paper, the issue of energy consumption is investigated and two
adaptive mechanisms are proposed to extend the network lifetime.
This study uses high-energy-first scheme to determine cluster heads
for data transmission. Thus, energy consumption in each cluster is
balanced and network lifetime can be extended. In addition, this study
uses cluster merging and dynamic routing mechanisms to further
reduce energy consumption during data transmission. The simulation
results show that the proposed method can effectively extend the
lifetime of wireless sensor network, and it is suitable for different base
station locations.
Abstract: This work presents a novel means of extracting fixedlength parameters from voice signals, such that words can be recognized
in linear time. The power and the zero crossing rate are first
calculated segment by segment from a voice signal; by doing so, two
feature sequences are generated. We then construct an FIR system
across these two sequences. The parameters of this FIR system, used
as the input of a multilayer proceptron recognizer, can be derived by
recursive LSE (least-square estimation), implying that the complexity of overall process is linear to the signal size. In the second part of
this work, we introduce a weighting factor λ to emphasize recent
input; therefore, we can further recognize continuous speech signals.
Experiments employ the voice signals of numbers, from zero to nine, spoken in Mandarin Chinese. The proposed method is verified to
recognize voice signals efficiently and accurately.
Abstract: The present study is concerned with the effect of
exciting boundary layer on cooling process in a gas-turbine blades.
The cooling process is numerically investigated. Observations show
cooling the first row of moving or stable blades leads to increase
their life-time. Results show that minimum temperature in cooling
line with exciting boundary layer is lower than without exciting.
Using block in cooling line of turbines' blade causes flow pattern and
stability in boundary layer changed that causes increase in heat
transfer coefficient. Results show at the location of block,
temperature of turbines' blade is significantly decreased. The k-ε
turbulence model is used.
Abstract: Optimization of filter banks based on the knowledge of input statistics has been of interest for a long time. Finite impulse response (FIR) Compaction filters are used in the design of optimal signal adapted orthonormal FIR filter banks. In this paper we discuss three different approaches for the design of interpolated finite impulse response (IFIR) compaction filters. In the first method, the magnitude squared response satisfies Nyquist constraint approximately. In the second and third methods Nyquist constraint is exactly satisfied. These methods yield FIR compaction filters whose response is comparable with that of the existing methods. At the same time, IFIR filters enjoy significant saving in the number of multipliers and can be implemented efficiently. Since eigenfilter approach is used here, the method is less complex. Design of IFIR filters in the least square sense is presented.
Abstract: Integration of process planning and scheduling
functions is necessary to achieve superior overall system
performance. This paper proposes a methodology for integration of
process planning and scheduling for prismatic component that can be
implemented in a company with existing departments. The developed
model considers technological constraints whereas available time for
machining in shop floor is the limiting factor to produce multiple
process plan (MPP). It takes advantage of MPP while guarantied the
fulfillment of the due dates via using overtime. This study has been
proposed to determinate machining parameters, tools, machine and
amount of over time within the minimum cost objective while
overtime is considered for this. At last the illustration shows that the
system performance is improved by as measured by cost and
compatible with due date.
Abstract: Drying characteristics of rough rice (variety of lenjan) with an initial moisture content of 25% dry basis (db) was studied in a hot air dryer assisted by infrared heating. Three arrival air temperatures (30, 40 and 500C) and four infrared radiation intensities (0, 0.2 , 0.4 and 0.6 W/cm2) and three arrival air speeds (0.1, 0.15 and 0.2 m.s-1) were studied. Bending strength of brown rice kernel, percentage of cracked kernels and time of drying were measured and evaluated. The results showed that increasing the drying arrival air temperature and radiation intensity of infrared resulted decrease in drying time. High bending strength and low percentage of cracked kernel was obtained when paddy was dried by hot air assisted infrared dryer. Between this factors and their interactive effect were a significant difference (p