Abstract: In this study, a high accuracy protein-protein interaction
prediction method is developed. The importance of the proposed
method is that it only uses sequence information of proteins while
predicting interaction. The method extracts phylogenetic profiles of
proteins by using their sequence information. Combining the phylogenetic
profiles of two proteins by checking existence of homologs
in different species and fitting this combined profile into a statistical
model, it is possible to make predictions about the interaction status
of two proteins.
For this purpose, we apply a collection of pattern recognition
techniques on the dataset of combined phylogenetic profiles of protein
pairs. Support Vector Machines, Feature Extraction using ReliefF,
Naive Bayes Classification, K-Nearest Neighborhood Classification,
Decision Trees, and Random Forest Classification are the methods
we applied for finding the classification method that best predicts
the interaction status of protein pairs. Random Forest Classification
outperformed all other methods with a prediction accuracy of 76.93%
Abstract: This paper describes a 2.4 GHz passive switch mixer
and a 5/2.5 GHz voltage-controlled negative Gm oscillator (VCO)
with an inversion-mode MOS varactor. Both circuits are implemented
using a 1P8M 0.13 μm process. The switch mixer has an input
referred 1 dB compression point of -3.89 dBm and a conversion
gain of -0.96 dB when the local oscillator power is +2.5 dBm.
The VCO consumes only 1.75 mW, while drawing 1.45 mA from a
1.2 V supply voltage. In order to reduce the passives size, the VCO
natural oscillation frequency is 5 GHz. A clocked CMOS divideby-
two circuit is used for frequency division and quadrature phase
generation. The VCO has a -109 dBc/Hz phase noise at 1 MHz
frequency offset and a 2.35-2.5 GHz tuning range (after the frequency
division), thus complying with ZigBee requirements.
Abstract: Different techniques for estimating seasonal water
use from soil profile water depletion frequently do not account for
flux below the root zone. Shallow water table contribution to supply
crop water use may be important in arid and semi-arid regions.
Development of predictive root uptake models, under influence of
shallow water table makes it possible for planners to incorporate
interaction between water table and root zone into design of irrigation
projects. A model for obtaining soil moisture depletion from root
zone and water movement below it is discussed with the objective to
determine impact of shallow water table on seasonal moisture
depletion patterns under water table depth variation, up to the bottom
of root zone. The role of different boundary conditions has also been
considered. Three crops: Wheat (Triticum aestivum), Corn (Zea
mays) and Potato (Solanum tuberosum), common in arid & semi-arid
regions, are chosen for the study. Using experimentally obtained soil
moisture depletion values for potential soil moisture conditions,
moisture depletion patterns using a non linear root uptake model have
been obtained for different water table depths. Comparative analysis
of the moisture depletion patterns under these conditions show a wide
difference in percent depletion from different layers of root zone
particularly top and bottom layers with middle layers showing
insignificant variation in moisture depletion values. Moisture
depletion in top layer, when the water table rises to root zone
increases by 19.7%, 22.9% & 28.2%, whereas decrease in bottom
layer is 68.8%, 61.6% & 64.9% in case of wheat, corn & potato
respectively. The paper also discusses the causes and consequences
of increase in moisture depletion from top layers and exceptionally
high reduction in bottom layer, and the possible remedies for the
same. The numerical model developed for the study can be used to
help formulating irrigation strategies for areas where shallow
groundwater of questionable quality is an option for crop production.
Abstract: As a result of the ever-changing environment and the demands of rganisations- customers, it is important to recognise the importance of some important managerial challenges. It is the sincere belief that failure to meet these challenges, will ultimately contribute to inevitable problems for organisations. This recognition
requires from managers and by implication organisations to be engaged in ethical behaviour, identity awareness and learning organisational behaviour. All these aspects actually reflect on the
importance of intellectual capital as the competitive weapons for
organisations in the future.
Abstract: In this article has been analyzed Kazakhstani
experience in organizing the system after the institute of higher education, legislative-regulative assurance of master preparation, and
statistic data in the republic. Have been the features of projecting the master programs, a condition of realization of studying credit system, have been analyzed the technologies of research teaching masters. In
conclusion have been given some recommendation on creating personal-oriented environment of research teaching masters.
Abstract: Skip cycle is a working strategy for spark ignition
engines, which allows changing the effective stroke of an engine
through skipping some of the four stroke cycles. This study proposes
a new mechanism to achieve the desired skip-cycle strategy for
internal combustion engines. The air and fuel leakage, which occurs
through the gas exchange, negatively affects the efficiency of the
engine at high speeds and loads. An absolute sealing is assured by
direct use of poppet valves, which are kept in fully closed position
during the skipped mode. All the components of the mechanism were
designed according to the real dimensions of the Anadolu Motor's
gasoline engine and modeled in 3D by means of CAD software. As
the mechanism operates in two modes, two dynamically equivalent
models are established to obtain the force and strength analysis for
critical components.
Abstract: Currently in many major cities, public transit schedules
are disseminated through lists of routes, grids of stop times and
static maps. This paper describes a web based geographic information
system which disseminates the same schedule information through
intuitive GIS techniques. Using data from Calgary, Canada, an map
based interface has been created to allow users to see routes, stops and
moving buses all at once. Zoom and pan controls as well as satellite
imagery allows users to apply their personal knowledge about the
local geography to achieve faster, and more pertinent transit results.
Using asynchronous requests to web services, users are immersed
in an application where buses and stops can be added and removed
interactively, without the need to wait for responses to HTTP requests.
Abstract: Trust management is one of the drawbacks in Peer-to-Peer (P2P) system. Lack of centralized control makes it difficult to control the behavior of the peers. Reputation system is one approach to provide trust assessment in P2P system. In this paper, we use fuzzy logic to model trust in a P2P environment. Our trust model combines first-hand (direct experience) and second-hand (reputation)information to allow peers to represent and reason with uncertainty regarding other peers' trustworthiness. Fuzzy logic can help in handling the imprecise nature and uncertainty of trust. Linguistic labels are used to enable peers assign a trust level intuitively. Our fuzzy trust model is flexible such that inference rules are used to weight first-hand and second-hand accordingly.
Abstract: The theory of rough sets is generalized by using a
filter. The filter is induced by binary relations and it is used to
generalize the basic rough set concepts. The knowledge
representations and processing of binary relations in the style of
rough set theory are investigated.
Abstract: Hypertension is characterized with stress on the heart and blood vessels thus increasing the risk of heart attack and renal diseases. The Renin angiotensin system (RAS) plays a major role in blood pressure control. Renin is the enzyme that controls the RAS at the rate-limiting step. Our aim is to develop new drug-like leads which can inhibit renin and thereby emerge as therapeutics for hypertension. To achieve this, molecular dynamics (MD) simulation and receptor-based pharmacophore modeling were implemented, and three rennin-inhibitor complex structures were selected based on IC50 value and scaffolds of inhibitors. Three pharmacophore models were generated considering conformations induced by inhibitor. The compounds mapped to these models were selected and subjected to drug-like screening. The identified hits were docked into the active site of renin. Finally, hit1 satisfying the binding mode and interaction energy was selected as possible lead candidate to be used in novel renin inhibitors.
Abstract: Information society is an absolutely new public formation at which the infrastructure and the social relations correspond to the socialized essence of «information genotype» mankind. Information society is a natural social environment which allows the person to open completely the information nature, to use intelligence for joint creation with other people of new information on the basis of knowledge earlier saved up by previous generations.
Abstract: We constructed a method of noise reduction for
JPEG-compressed image based on Bayesian inference using the
maximizer of the posterior marginal (MPM) estimate. In this method,
we tried the MPM estimate using two kinds of likelihood, both of
which enhance grayscale images converted into the JPEG-compressed
image through the lossy JPEG image compression. One is the
deterministic model of the likelihood and the other is the probabilistic
one expressed by the Gaussian distribution. Then, using the Monte
Carlo simulation for grayscale images, such as the 256-grayscale
standard image “Lena" with 256 × 256 pixels, we examined the
performance of the MPM estimate based on the performance measure
using the mean square error. We clarified that the MPM estimate via
the Gaussian probabilistic model of the likelihood is effective for
reducing noises, such as the blocking artifacts and the mosquito noise,
if we set parameters appropriately. On the other hand, we found that
the MPM estimate via the deterministic model of the likelihood is not
effective for noise reduction due to the low acceptance ratio of the
Metropolis algorithm.
Abstract: The given work is devoted to the description of
Information Technologies NAS of Azerbaijan created and
successfully maintained in Institute. On the basis of the decision of
board of the Supreme Certifying commission at the President of the
Azerbaijan Republic and Presidium of National Academy of
Sciences of the Azerbaijan Republic, the organization of training
courses on Computer Sciences for all post-graduate students and
dissertators of the republic, taking of examinations of candidate
minima, it was on-line entrusted to Institute of Information
Technologies of the National Academy of Sciences of Azerbaijan.
Therefore, teaching the computer sciences to post-graduate
students and dissertators a scientific - methodological manual on
effective application of new information technologies for research
works by post-graduate students and dissertators and taking of
candidate minima is carried out in the Educational Center.
Information and communication technologies offer new
opportunities and prospects of their application for teaching and
training. The new level of literacy demands creation of essentially
new technology of obtaining of scientific knowledge. Methods of
training and development, social and professional requirements,
globalization of the communicative economic and political projects
connected with construction of a new society, depends on a level of
application of information and communication technologies in the
educational process. Computer technologies develop ideas of
programmed training, open completely new, not investigated
technological ways of training connected to unique opportunities of
modern computers and telecommunications. Computer technologies
of training are processes of preparation and transfer of the
information to the trainee by means of computer. Scientific and
technical progress as well as global spread of the technologies
created in the most developed countries of the world is the main
proof of the leading role of education in XXI century. Information
society needs individuals having modern knowledge. In practice, all
technologies, using special technical information means (computer,
audio, video) are called information technologies of education.
Abstract: Most integrated inertial navigation systems (INS) and
global positioning systems (GPS) have been implemented using the
Kalman filtering technique with its drawbacks related to the need for
predefined INS error model and observability of at least four
satellites. Most recently, a method using a hybrid-adaptive network
based fuzzy inference system (ANFIS) has been proposed which is
trained during the availability of GPS signal to map the error
between the GPS and the INS. Then it will be used to predict the
error of the INS position components during GPS signal blockage.
This paper introduces a genetic optimization algorithm that is used to
update the ANFIS parameters with respect to the INS/GPS error
function used as the objective function to be minimized. The results
demonstrate the advantages of the genetically optimized ANFIS for
INS/GPS integration in comparison with conventional ANFIS
specially in the cases of satellites- outages. Coping with this problem
plays an important role in assessment of the fusion approach in land
navigation.
Abstract: The comparative analysis of different taxonomic
groups of microorganisms isolated from dark chernozem soils under
different agricultures (alfalfa, melilot, sainfoin, soybean, rapeseed) at
Almaty region of Kazakhstan was conducted. It was shown that the
greatest number of micromycetes was typical to the soil planted with
alfalfa and canola. Species diversity of micromycetes markedly
decreases as it approaches the surface of the root, so that the species
composition in the rhizosphere is much more uniform than in the
virgin soil. Promising strains of microscopic fungi and yeast with
plant growth-promoting activity to agricultures were selected. Among
the selected fungi there are representatives of Penicillium bilaiae,
Trichoderma koningii, Fusarium equiseti, Aspergillus ustus. The
highest rates of growth and development of seedlings of plants
observed under the influence of yeasts Aureobasidium pullulans,
Rhodotorula mucilaginosa, Metschnikovia pulcherrima. Using
molecular - genetic techniques confirmation of the identification
results of selected micromycetes was conducted.
Abstract: In this paper the optimal control strategy for
Permanent Magnet Synchronous Motor (PMSM) based drive system
is presented. The designed full optimal control is available for speed
operating range up to base speed. The optimal voltage space-vector
assures input energy reduction and stator loss minimization,
maintaining the output energy in the same limits with the
conventional PMSM electrical drive. The optimal control with three
components is based on the energetically criteria and it is applicable
in numerical version, being a nonrecursive solution. The simulation
results confirm the increased efficiency of the optimal PMSM drive.
The properties of the optimal voltage space vector are shown.
Abstract: Like any sentient organism, a smart environment
relies first and foremost on sensory data captured from the real
world. The sensory data come from sensor nodes of different
modalities deployed on different locations forming a Wireless Sensor
Network (WSN). Embedding smart sensors in humans has been a
research challenge due to the limitations imposed by these sensors
from computational capabilities to limited power. In this paper, we
first propose a practical WSN application that will enable blind
people to see what their neighboring partners can see. The challenge
is that the actual mapping between the input images to brain pattern
is too complex and not well understood. We also study the
connectivity problem in 3D/2D wireless sensor networks and propose
distributed efficient algorithms to accomplish the required
connectivity of the system. We provide a new connectivity algorithm
CDCA to connect disconnected parts of a network using cooperative
diversity. Through simulations, we analyze the connectivity gains
and energy savings provided by this novel form of cooperative
diversity in WSNs.
Abstract: The main issue of interest here is whether individuals
who differ in arithmetical reasoning ability and levels of imagery ability display different brain activity during the conduct of mental
arithmetical reasoning tasks. This was a case study of four
participants who represented four extreme combinations of Maths –Imagery abilities: ie., low-low, high-high, high-low, low-high respectively. As the Ps performed a series of 60 arithmetical reasoning tasks, 128-channel EEG recordings were taken and the
pre-response interval subsequently analysed using EGI GeosourceTM
software. The P who was high in both imagery and maths ability
showed peak activity prior to response in BA7 (superior parietal cortex) but other Ps did not show peak activity in this region. The
results are considered in terms of the diverse routes that may be employed by individuals during the conduct of arithmetical reasoning
tasks and the possible implications of this for mathematics education.
Abstract: An on chip low drop out voltage regulator that
employs elegant compensation scheme is presented in this paper. The
novelty in this design is that the device parasitic capacitances are
exploited for compensation at different loads. The proposed LDO is
designed to provide a constant voltage of 1.2V and is implemented in
UMC 180 nano meter CMOS technology. The voltage regulator
presented improves stability even at lighter loads and enhances line
and load regulation.
Abstract: This paper investigates the problem of sampling from transactional data streams. We introduce CFISDS as a content based sampling algorithm that works on a landmark window model of data streams and preserve more informed sample in sample space. This algorithm that work based on closed frequent itemset mining tasks, first initiate a concept lattice using initial data, then update lattice structure using an incremental mechanism.Incremental mechanism insert, update and delete nodes in/from concept lattice in batch manner. Presented algorithm extracts the final samples on demand of user. Experimental results show the accuracy of CFISDS on synthetic and real datasets, despite on CFISDS algorithm is not faster than exist sampling algorithms such as Z and DSS.