Abstract: Analysis and visualization of microarraydata is veryassistantfor biologists and clinicians in the field of diagnosis and treatment of patients. It allows Clinicians to better understand the structure of microarray and facilitates understanding gene expression in cells. However, microarray dataset is a complex data set and has thousands of features and a very small number of observations. This very high dimensional data set often contains some noise, non-useful information and a small number of relevant features for disease or genotype. This paper proposes a non-linear dimensionality reduction algorithm Local Principal Component (LPC) which aims to maps high dimensional data to a lower dimensional space. The reduced data represents the most important variables underlying the original data. Experimental results and comparisons are presented to show the quality of the proposed algorithm. Moreover, experiments also show how this algorithm reduces high dimensional data whilst preserving the neighbourhoods of the points in the low dimensional space as in the high dimensional space.
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: The influence of copper promoters and reaction
conditions on the formation of alcohols byproducts of a common
Fischer-Tropsch synthesis used iron-based catalysts were investigated.
A good compromise of 28%Cu/FeKLaSiO2 can lead to the
optimization of an improved Fischer-Tropsch catalyst. The product
distribution shifts towards hydrocarbons with increasing the reaction
temperature, while pressure promotes the formation of alcohols. It was
found that the production of either alcohols or hydrocarbons followed
A-S-F distributions, and their α parameters were essentially different
which indicated a competition in the growing chain between the two
species. TPD after acetaldehyde adsorption gave strong evidence of
the insertion of a C1 oxygen-containing species into an alkyl chain.
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: Among the technologies available to reduce methane
emitted from the pig industry, biofiltration seems to be an effective
and inexpensive solution. In methane (CH4) biofiltration, nitrogen is
an important macronutrient for the microorganisms growth. The
objective of this research project was to study the effect of
ammonium (NH4
+) on the performance, the biomass production and
the nitrogen conversion of a biofilter treating methane. For NH4
+
concentrations ranging from 0.05 to 0.5 gN-NH4
+/L, the CH4 removal
efficiency and the dioxide carbon production rate decreased linearly
from 68 to 11.8 % and from 7.1 to 0.5 g/(m3-h), respectively. The dry
biomass content varied from 4.1 to 5.8 kg/(m3 filter bed). For the
same range of concentrations, the ammonium conversion decreased
while the specific nitrate production rate increased. The specific
nitrate production rate presented negative values indicating
denitrification in the biofilter.
Abstract: One of the most important secrets of succesful companies is the fact that cooperation with NGOs will create a good reputation for them so that they can be immunized to economic crisis. The performance of the most admired companies in the world based on the ratings of Forbes and Fortune show us that most of these firms also have close relationships with their NGOs. Today, if companies do something wrong this information spreads very quickly to do the society. If people do not like the activities of a company, it can find itself in public relations nightmare that can threaten its repuation. Since the cost of communication has dropped dramatically due to the vast use of internet, the increase in communication among stakeholders via internet makes companies more visible. These multiple and interdependent interactions among the network of stakeholders is called as the network relationships. NGOs play the role of catalyst among the stakeholders of a firm to enhance the awareness. Succesful firms are aware of this fact that NGOs have a central role in today-s business world. Firms are also aware of the fact that they can enhance their corporate reputation via cooperation with the NGOs. This fact will be illustrated in this paper by examining some of the actions of the most succesful companies in terms of their cooperations with the NGOs.
Abstract: The objective of this research intends to create a suitable model of distance training for community leaders in the upper northeastern region of Thailand. The implementation of the research process is divided into four steps: The first step is to analyze relevant documents. The second step deals with an interview in depth with experts. The third step is concerned with constructing a model. And the fourth step takes aim at model validation by expert assessments. The findings reveal the two important components for constructing an appropriate model of distance training for community leaders in the upper northeastern region. The first component consists of the context of technology management, e.g., principle, policy and goals. The second component can be viewed in two ways. Firstly, there are elements comprising input, process, output and feedback. Secondly, the sub-components include steps and process in training. The result of expert assessments informs that the researcher-s constructed model is consistent and suitable and overall the most appropriate.
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: 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: 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: 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: During the process of compaction in Hot-Mix Asphalt
(HMA) mixtures, the distance between aggregate particles decreases
as they come together and eliminate air-voids. By measuring the
inter-particle distances in a cut-section of a HMA sample the degree
of compaction can be estimated. For this, a calibration curve is
generated by computer simulation technique when the gradation and
asphalt content of the HMA mixture are known. A two-dimensional
cross section of HMA specimen was simulated using the mixture
design information (gradation, asphalt content and air-void content).
Nearest neighbor distance methods such as Delaunay triangulation
were used to study the changes in inter-particle distance and area
distribution during the process of compaction in HMA. Such
computer simulations would enable making several hundreds of
repetitions in a short period of time without the necessity to compact
and analyze laboratory specimens in order to obtain good statistics on
the parameters defined. The distributions for the statistical
parameters based on computer simulations showed similar trends as
those of laboratory specimens.
Abstract: In this paper, we consider the analysis of the
acquisition process for a hybrid double-dwell system with antenna
diversity for DS-CDMA (direct sequence-code division multiple
access) using an adaptive threshold. Acquisition systems with a fixed
threshold value are unable to adapt to fast varying mobile
communications environments and may result in a high false alarm
rate, and/or low detection probability. Therefore, we propose an
adaptively varying threshold scheme through the use of a cellaveraging
constant false alarm rate (CA-CFAR) algorithm, which is
well known in the field of radar detection. We derive exact
expressions for the probabilities of detection and false alarm in
Rayleigh fading channels. The mean acquisition time of the system
under consideration is also derived. The performance of the system is
analyzed and compared to that of a hybrid single dwell system.
Abstract: In this paper, enhanced ground proximity warning simulation and validation system is designed and implemented. First, based on square grid and sub-grid structure, the global digital terrain database is designed and constructed. Terrain data searching is implemented through querying the latitude and longitude bands and separated zones of global terrain database with the current aircraft position. A combination of dynamic scheduling and hierarchical scheduling is adopted to schedule the terrain data, and the terrain data can be read and delete dynamically in the memory. Secondly, according to the scope, distance, approach speed information etc. to the dangerous terrain in front, and using security profiles calculating method, collision threat detection is executed in real-time, and provides caution and warning alarm. According to this scheme, the implementation of the enhanced ground proximity warning simulation system is realized. Simulations are carried out to verify a good real-time in terrain display and alarm trigger, and the results show simulation system is realized correctly, reasonably and stable.