Abstract: Student-s movements have been going increasing in
last decades. International students can have different psychological
and sociological problems in their adaptation process. Depression is
one of the most important problems in this procedure. This research
purposed to reveal level of foreign students- depression, kinds of
interpersonal communication networks (host/ethnic interpersonal
communication) and media usage (host/ethnic media usage).
Additionally study aimed to display the relationship between
depression and communication (host/ethnic interpersonal
communication and host/ethnic media usage) among foreign
university students. A field research was performed among 283
foreign university students who have been attending 8 different
universities in Turkey. A purposeful sampling technique was used in
this research cause of data collect facilities. Results indicated that
58.3% of foreign students- depression stage was “intermediate" while
33.2% of foreign students- depression level was “low". Add to this,
host interpersonal communication behaviors and Turkish web sites
usages were negatively and significantly correlated with depression.
Abstract: This paper proposes a novel approach to the question of lithofacies classification based on an assessment of the uncertainty in the classification results. The proposed approach has multiple neural networks (NN), and interval neutrosophic sets (INS) are used to classify the input well log data into outputs of multiple classes of lithofacies. A pair of n-class neural networks are used to predict n-degree of truth memberships and n-degree of false memberships. Indeterminacy memberships or uncertainties in the predictions are estimated using a multidimensional interpolation method. These three memberships form the INS used to support the confidence in results of multiclass classification. Based on the experimental data, our approach improves the classification performance as compared to an existing technique applied only to the truth membership. In addition, our approach has the capability to provide a measure of uncertainty in the problem of multiclass classification.
Abstract: The passive electrical properties of a tissue depends
on the intrinsic constituents and its structure, therefore by measuring
the complex electrical impedance of the tissue it might be possible to
obtain indicators of the tissue state or physiological activity [1].
Complete bio-impedance information relative to physiology and
pathology of a human body and functional states of the body tissue or
organs can be extracted by using a technique containing a fourelectrode
measurement setup. This work presents the estimation
measurement setup based on the four-electrode technique. First, the
complex impedance is estimated by three different estimation
techniques: Fourier, Sine Correlation and Digital De-convolution and
then estimation errors for the magnitude, phase, reactance and
resistance are calculated and analyzed for different levels of
disturbances in the observations. The absolute values of relative
errors are plotted and the graphical performance of each technique is
compared.
Abstract: Sedimentation in reservoirs lowers the quality of
consumed water, reduce the volume of reservoir, lowers the
controllable amount of flood, increases the risk of water overflow
during possible floods and the risk of reversal and reduction of dam's
useful life. So in all stages of dam establishment such as cognitive
studies, phase-1 studies of design, control, construction and
maintenance, the problem of sedimentation in reservoir should be
considered. What engineers need to do is examine and develop the
methods to keep effective capacity of a reservoir, however engineers
should also consider the influences of the methods on the flood
disaster, functions of water use facilities and environmental
issues.This article first examines the sedimentation in reservoirs and
shows how to control it and then discusses the studies about the
sedimens in Siazakh Dam.
Abstract: To investigate some relations between higher mathe¬matics scores in Chinese graduate student entrance examination and calculus (resp. linear algebra, probability statistics) scores in subject's completion examination of Chinese university, we select 20 students as a sample, take higher mathematics score as a decision attribute and take calculus score, linear algebra score, probability statistics score as condition attributes. In this paper, we are based on rough-set theory (Rough-set theory is a logic-mathematical method proposed by Z. Pawlak. In recent years, this theory has been widely implemented in the many fields of natural science and societal science.) to investigate importance of condition attributes with respective to decision attribute and strength of condition attributes supporting decision attribute. Results of this investigation will be helpful for university students to raise higher mathematics scores in Chinese graduate student entrance examination.
Abstract: A higher order spline interpolated contour obtained
with up-sampling of homogenously distributed coordinates for
segmentation of kidney region in different classes of ultrasound
kidney images has been developed and presented in this paper. The
performance of the proposed method is measured and compared with
modified snake model contour, Markov random field contour and
expert outlined contour. The validation of the method is made in
correspondence with expert outlined contour using maximum coordinate
distance, Hausdorff distance and mean radial distance
metrics. The results obtained reveal that proposed scheme provides
optimum contour that agrees well with expert outlined contour.
Moreover this technique helps to preserve the pixels-of-interest
which in specific defines the functional characteristic of kidney. This
explores various possibilities in implementing computer-aided
diagnosis system exclusively for US kidney images.
Abstract: In this study the integration of an absorption heat
pump (AHP) with the concentration section of an industrial pulp and
paper process is investigated using pinch technology. The optimum
design of the proposed water-lithium bromide AHP is then achieved
by minimizing the total annual cost. A comprehensive optimization is
carried out by relaxation of all stream pressure drops as well as heat
exchanger areas involving in AHP structure. It is shown that by
applying genetic algorithm optimizer, the total annual cost of the
proposed AHP is decreased by 18% compared to one resulted from
simulation.
Abstract: This paper describes a low-power second-order filter
for a continuous-time chopper stabilized capacitive sensor interface,
integrated with a fully differential post-CMOS surface-micromachined
MEMS pressure sensor. The circuit uses a single-ended
folded-cascode operational amplifier and two GM-C filters connected
in cascade. The circuit is realized in a 0.18 μm CMOS process and
offers differential to single-ended conversion. The novelty of the
scheme is the cascade of two GM-C filters to achieve a second-order
filter while minimizing power dissipation. The simulated filter cutoff
frequency is 1.14 kHz at common-mode voltage 1.65 V,
operating from a 3.3 V supply while dissipating 172μW of power.
The filter achieves an operating range of 1V for an output load of
1MOhm and 10pF.
Abstract: The paper investigates downtrend algorithm and
trading strategy based on chart pattern recognition and technical
analysis in futures market. The proposed chart formation is a pattern
with the lowest low in the middle and one higher low on each side.
The contribution of this paper lies in the reinforcement of statements
about the profitability of momentum trend trading strategies.
Practical benefit of the research is a trading algorithm in falling
markets and back-test analysis in futures markets. When based on
daily data, the algorithm has generated positive results, especially
when the market had downtrend period. Downtrend algorithm can be
applied as a hedge strategy against possible sudden market crashes.
The proposed strategy can be interesting for futures traders, hedge
funds or scientific researchers performing technical or algorithmic
market analysis based on momentum trend trading.
Abstract: There has been a growing interest in implementing humanoid avatars in networked virtual environment. However, most existing avatar communication systems do not take avatars- social backgrounds into consideration. This paper proposes a novel humanoid avatar animation system to represent personalities and facial emotions of avatars based on culture, profession, mood, age, taste, and so forth. We extract semantic keywords from the input text through natural language processing, and then the animations of personalized avatars are retrieved and displayed according to the order of the keywords. Our primary work is focused on giving avatars runtime instruction from multiple natural languages. Experiments with Chinese, Japanese and English input based on the prototype show that interactive avatar animations can be displayed in real time and be made available online. This system provides a more natural and interesting means of human communication, and therefore is expected to be used for cross-cultural communication, multiuser online games, and other entertainment applications.
Abstract: With a development of Hybrid Electric Vehicle(HEV),
A photovoltaic(PV) generation system is used for charging batteries in many cases. A dc/dc converter using PV power for a battery charger
requires a high efficiency. In this paper, A ZVS boost converter using the renewable energies for HEV charger is proposed. Through the theoretical analysis and experimental result, operation modes and characteristics of the proposed topology are verified.
Abstract: Lateral expansion is a factor defining the level of
confinement in reinforced concrete columns. Therefore, predicting
the lateral strain relationship with axial strain becomes an important
issue. Measuring lateral strains in experiments is difficult and only
few report experimental lateral strains. Among the existing analytical
formulations, two recent models are compared with available test
results in this paper with shortcomings highlighted. A new analytical
model is proposed here for lateral strain axial strain relationship and
is based on the supposition that the concrete behaves linear elastic in
the early stages of loading and then nonlinear hardening up to the
peak stress and then volumetric expansion. The proposal for the
lateral strain axial strain relationship after the peak stress is mainly
based on the hypothesis that the plastic lateral strain varies linearly
with the plastic axial strain and it is shown that this is related to the
lateral confinement level.
Abstract: This paper presents a perturbation based search method
to solve the unconstrained binary quadratic programming problem.
The proposed algorithm was tested with some of the standard test
problems and the results are reported for 10 instances of 50, 100, 250,
& 500 variable problems. A comparison of the performance of the
proposed algorithm with other heuristics and optimization software is
made. Based on the results, it was found that the proposed algorithm
is computationally inexpensive and the solutions obtained match the
best known solutions for smaller sized problems. For larger instances,
the algorithm is capable of finding a solution within 0.11% of the
best known solution. Apart from being used as a stand-alone method,
this algorithm could also be incorporated with other heuristics to find
better solutions.
Abstract: The 4G front-end transceiver needs a high
performance which can be obtained mainly with an optimal
architecture and a multi-band Local Oscillator. In this study, we
proposed and presented a new architecture of multi-band frequency
synthesizer based on an Inverse Sine Phase Detector Phase Locked
Loop (ISPD PLL) without any filters and any controlled gain block
and associated with adapted multi band LC tuned VCO using a
several numeric controlled capacitive branches but not binary
weighted. The proposed architecture, based on 0.35μm CMOS
process technology, supporting Multi-band GSM/DCS/DECT/
UMTS/WiMax application and gives a good performances: a phase
noise @1MHz -127dBc and a Factor Of Merit (FOM) @ 1MHz -
186dB and a wide band frequency range (from 0.83GHz to 3.5GHz),
that make the proposed architecture amenable for monolithic
integration and 4G multi-band application.
Abstract: Magnetic carbon nanotubes composites were obtained
by filling carbon nanotubes with paramagnetic iron oxide particles.
Detailed investigation of magnetic behaviour of resulting composites
was done at different temperatures. Measurements indicate that these
functionalized nanotubes are superparamagnetic at room temperature;
however, no superparamagnetism was observed at 125 K and 80 K.
The blocking temperature TB was estimated at 145 K. These magnetic
carbon nanotubes have the potential of being used in a wide range of
applications, in particular, the production of nanofluids, which can be
controlled and steered by appropriate magnetic fields.
Abstract: Predicting protein-protein interactions represent a key step in understanding proteins functions. This is due to the fact that proteins usually work in context of other proteins and rarely function alone. Machine learning techniques have been applied to predict protein-protein interactions. However, most of these techniques address this problem as a binary classification problem. Although it is easy to get a dataset of interacting proteins as positive examples, there are no experimentally confirmed non-interacting proteins to be considered as negative examples. Therefore, in this paper we solve this problem as a one-class classification problem using one-class support vector machines (SVM). Using only positive examples (interacting protein pairs) in training phase, the one-class SVM achieves accuracy of about 80%. These results imply that protein-protein interaction can be predicted using one-class classifier with comparable accuracy to the binary classifiers that use artificially constructed negative examples.
Abstract: Question answering (QA) aims at retrieving precise information from a large collection of documents. Most of the Question Answering systems composed of three main modules: question processing, document processing and answer processing. Question processing module plays an important role in QA systems to reformulate questions. Moreover answer processing module is an emerging topic in QA systems, where these systems are often required to rank and validate candidate answers. These techniques aiming at finding short and precise answers are often based on the semantic relations and co-occurrence keywords. This paper discussed about a new model for question answering which improved two main modules, question processing and answer processing which both affect on the evaluation of the system operations. There are two important components which are the bases of the question processing. First component is question classification that specifies types of question and answer. Second one is reformulation which converts the user's question into an understandable question by QA system in a specific domain. The objective of an Answer Validation task is thus to judge the correctness of an answer returned by a QA system, according to the text snippet given to support it. For validating answers we apply candidate answer filtering, candidate answer ranking and also it has a final validation section by user voting. Also this paper described new architecture of question and answer processing modules with modeling, implementing and evaluating the system. The system differs from most question answering systems in its answer validation model. This module makes it more suitable to find exact answer. Results show that, from total 50 asked questions, evaluation of the model, show 92% improving the decision of the system.
Abstract: The chatter is one of the major limitations of the productivity in the ball end milling process. It affects the surface roughness, the dimensional accuracy and the tool life. The aim of this research is to propose the new system to detect the chatter during the ball end milling process by using the wavelet transform. The proposed method is implemented on the 5-axis CNC machining center and the new three parameters are introduced from three dynamic cutting forces, which are calculated by taking the ratio of the average variances of dynamic cutting forces to the absolute variances of themselves. It had been proved that the chatter can be easier to detect during the in-process cutting by using the new parameters which are proposed in this research. The experimentally obtained results showed that the wavelet transform can provide the reliable results to detect the chatter under various cutting conditions.
Abstract: Knowledge management (KM) is generally
considered to be a positive process in an organisation, facilitating
opportunities to achieve competitive advantage via better quality
information handling, compilation of expert know-how and rapid
response to fluctuations in the business environment. The KM
paradigm as portrayed in the literature informs the processes that can
increase intangible assets so that corporate knowledge is preserved.
However, in some instances, knowledge management exists in a
universe of dynamic tension among the conflicting needs to respect
privacy and intellectual property (IP), to guard against data theft, to
protect national security and to stay within the laws. While the
Knowledge Management literature focuses on the bright side of the
paradigm, there is also a different side in which knowledge is
distorted, suppressed or misappropriated due to personal or
organisational motives (the paradox). This paper describes the ethical
paradoxes that occur within the taxonomy and deontology of
knowledge management and suggests that recognising both the
promises and pitfalls of KM requires wisdom.
Abstract: Given a bivariate normal sample of correlated variables,
(Xi, Yi), i = 1, . . . , n, an alternative estimator of Pearson’s correlation
coefficient is obtained in terms of the ranges, |Xi − Yi|.
An approximate confidence interval for ρX,Y is then derived, and
a simulation study reveals that the resulting coverage probabilities
are in close agreement with the set confidence levels. As well, a
new approximant is provided for the density function of R, the
sample correlation coefficient. A mixture involving the proposed
approximate density of R, denoted by hR(r), and a density function
determined from a known approximation due to R. A. Fisher is shown
to accurately approximate the distribution of R. Finally, nearly exact
density approximants are obtained on adjusting hR(r) by a 7th degree
polynomial.