Abstract: Complex assemblies of interacting proteins carry out
most of the interesting jobs in a cell, such as metabolism, DNA
synthesis, mitosis and cell division. These physiological properties
play out as a subtle molecular dance, choreographed by underlying
regulatory networks that control the activities of cyclin-dependent
kinases (CDK). The network can be modeled by a set of nonlinear
differential equations and its behavior predicted by numerical
simulation. In this paper, an innovative approach has been proposed
that uses genetic algorithms to mine a set of behavior data output by
a biological system in order to determine the kinetic parameters of
the system. In our approach, the machine learning method is
integrated with the framework of existent biological information in a
wiring diagram so that its findings are expressed in a form of system
dynamic behavior. By numerical simulations it has been illustrated
that the model is consistent with experiments and successfully shown
that such application of genetic algorithms will highly improve the
performance of mathematical model of the cell division cycle to
simulate such a complicated bio-system.
Abstract: The issue of real-time and reliable report delivery is extremely important for taking effective decision in a real world mission critical Wireless Sensor Network (WSN) based application. The sensor data behaves differently in many ways from the data in traditional databases. WSNs need a mechanism to register, process queries, and disseminate data. In this paper we propose an architectural framework for data placement and management. We propose a reliable and real time approach for data placement and achieving data integrity using self organized sensor clusters. Instead of storing information in individual cluster heads as suggested in some protocols, in our architecture we suggest storing of information of all clusters within a cell in the corresponding base station. For data dissemination and action in the wireless sensor network we propose to use Action and Relay Stations (ARS). To reduce average energy dissipation of sensor nodes, the data is sent to the nearest ARS rather than base station. We have designed our architecture in such a way so as to achieve greater energy savings, enhanced availability and reliability.
Abstract: Image clustering is a process of grouping images
based on their similarity. The image clustering usually uses the color
component, texture, edge, shape, or mixture of two components, etc.
This research aims to explore image clustering using color
composition. In order to complete this image clustering, three main
components should be considered, which are color space, image
representation (feature extraction), and clustering method itself. We
aim to explore which composition of these factors will produce the
best clustering results by combining various techniques from the
three components. The color spaces use RGB, HSV, and L*a*b*
method. The image representations use Histogram and Gaussian
Mixture Model (GMM), whereas the clustering methods use KMeans
and Agglomerative Hierarchical Clustering algorithm. The
results of the experiment show that GMM representation is better
combined with RGB and L*a*b* color space, whereas Histogram is
better combined with HSV. The experiments also show that K-Means
is better than Agglomerative Hierarchical for images clustering.
Abstract: Gliding during night without electric power is an efficient method to enhance endurance performance of solar aircrafts. The properties of maximum gliding endurance path are studied in this paper. The problem is formulated as an optimization problem about maximum endurance can be sustained by certain potential energy storage with dynamic equations and aerodynamic parameter constrains. The optimal gliding path is generated based on gauss pseudo-spectral method. In order to analyse relationship between altitude, velocity of solar UAVs and its endurance performance, the lift coefficient in interval of [0.4, 1.2] and flight envelopes between 0~30km are investigated. Results show that broad range of lift coefficient can improve solar aircrafts- long endurance performance, and it is possible for a solar aircraft to achieve the aim of long endurance during whole night just by potential energy storage.
Abstract: In this paper we propose a method which improves the efficiency of video coding. Our method combines an adaptive GOP (group of pictures) structure and the shot cut detection. We have analyzed different approaches for shot cut detection with aim to choose the most appropriate one. The next step is to situate N frames to the positions of detected cuts during the process of video encoding. Finally the efficiency of the proposed method is confirmed by simulations and the obtained results are compared with fixed GOP structures of sizes 4, 8, 12, 16, 32, 64, 128 and GOP structure with length of entire video. Proposed method achieved the gain in bit rate from 0.37% to 50.59%, while providing PSNR (Peak Signal-to-Noise Ratio) gain from 1.33% to 0.26% in comparison to simulated fixed GOP structures.
Abstract: Real world Speaker Identification (SI) application
differs from ideal or laboratory conditions causing perturbations that
leads to a mismatch between the training and testing environment
and degrade the performance drastically. Many strategies have been
adopted to cope with acoustical degradation; wavelet based Bayesian
marginal model is one of them. But Bayesian marginal models
cannot model the inter-scale statistical dependencies of different
wavelet scales. Simple nonlinear estimators for wavelet based
denoising assume that the wavelet coefficients in different scales are
independent in nature. However wavelet coefficients have significant
inter-scale dependency. This paper enhances this inter-scale
dependency property by a Circularly Symmetric Probability Density
Function (CS-PDF) related to the family of Spherically Invariant
Random Processes (SIRPs) in Log Gabor Wavelet (LGW) domain
and corresponding joint shrinkage estimator is derived by Maximum
a Posteriori (MAP) estimator. A framework is proposed based on
these to denoise speech signal for automatic speaker identification
problems. The robustness of the proposed framework is tested for
Text Independent Speaker Identification application on 100 speakers
of POLYCOST and 100 speakers of YOHO speech database in three
different noise environments. Experimental results show that the
proposed estimator yields a higher improvement in identification
accuracy compared to other estimators on popular Gaussian Mixture
Model (GMM) based speaker model and Mel-Frequency Cepstral
Coefficient (MFCC) features.
Abstract: We study different types of aggregation operators and
the decision making process with minimization of regret. We analyze
the original work developed by Savage and the recent work
developed by Yager that generalizes the MMR method creating a
parameterized family of minimal regret methods by using the ordered
weighted averaging (OWA) operator. We suggest a new method that
uses different types of geometric operators such as the weighted
geometric mean or the ordered weighted geometric operator (OWG)
to generalize the MMR method obtaining a new parameterized family
of minimal regret methods. The main result obtained in this method
is that it allows to aggregate negative numbers in the OWG operator.
Finally, we give an illustrative example.
Abstract: This paper presents a new and efficient approach for capacitor placement in radial distribution systems that determine the optimal locations and size of capacitor with an objective of improving the voltage profile and reduction of power loss. The solution methodology has two parts: in part one the loss sensitivity factors are used to select the candidate locations for the capacitor placement and in part two a new algorithm that employs Plant growth Simulation Algorithm (PGSA) is used to estimate the optimal size of capacitors at the optimal buses determined in part one. The main advantage of the proposed method is that it does not require any external control parameters. The other advantage is that it handles the objective function and the constraints separately, avoiding the trouble to determine the barrier factors. The proposed method is applied to 9, 34, and 85-bus radial distribution systems. The solutions obtained by the proposed method are compared with other methods. The proposed method has outperformed the other methods in terms of the quality of solution.
Abstract: A new, combinatorial model for analyzing and inter-
preting an electrocardiogram (ECG) is presented. An application of
the model is QRS peak detection. This is demonstrated with an
online algorithm, which is shown to be space as well as time efficient.
Experimental results on the MIT-BIH Arrhythmia database show that
this novel approach is promising. Further uses for this approach are
discussed, such as taking advantage of its small memory requirements
and interpreting large amounts of pre-recorded ECG data.
Abstract: Promoting critical thinking (CT) in an educational
setting has been appraised in order to enhance learning and
intellectual skills. In this study, a pedagogical course in a vocational
teacher education program in Turkey was designed by integrating CT
skill-based strategies/activities into the course content and CT skills
were means leading to intended course objectives. The purpose of the
study was to evaluate the importance of the course objectives, the
attainment of the objectives, and the effectiveness of teachinglearning
strategies/activities from prospective teachers- points of
view. The results revealed that although the students mostly
considered the course objectives important, they did not feel
competent in the attainment of all objectives especially in those
related to the main topic of Learning and those requiring higher order
thinking skills. On the other hand, the students considered the course
activities effective for learning and for the development of thinking
skills, especially, in interpreting, comparing, questioning,
contrasting, and forming relationships.
Abstract: Using quantum hydrodynamical (QHD) model the linear dispersion relation for the electron plasma waves propagating in a cylindrical waveguide filled with a dense plasma containing streaming electron, hole and stationary charged dust particles has been derived. It is shown that the effect of finite boundary and stream velocity of electrons and holes make some of the possible modes of propagation linearly unstable. The growth rate of this instability is shown to depend significantly on different plasma parameters.
Abstract: Today, Hydroforming technology provides an
attractive alternative to conventional matched die forming, especially
for cost-sensitive, lower volume production, and for parts with
irregular contours. In this study the critical fluid pressures which lead
to rupture in the workpiece has been investigated by theoretical and
finite element methods. The axisymmetric analysis was developed to
investigate the tearing phenomenon in cylindrical Hydroforming
Deep Drawing (HDD). By use of obtained equations the effect of
anisotropy, drawing ratio, sheet thickness and strain hardening
exponent on tearing diagram were investigated.
Abstract: At the time where electronic books, or e-Books, offer
students a fun way of learning , teachers who are used to the paper
text books may find it as a new challenge to use it as a part of
learning process. Precisely, there are various types of e-Books
available to suit students- knowledge, characteristics, abilities, and
interests. The paper discusses teachers- perceptions on the use of ebooks
as a paper text book in the classroom. A survey was conducted
on 72 teachers who use e-books as textbooks. It was discovered that a
majority of these teachers had good perceptions on the use of ebooks.
However, they had little problems using the devices. It can be
overcome with some strategies and a suggested framework.
Abstract: A key aspect of the design of any software system is
its architecture. An architecture description provides a formal model
of the architecture in terms of components and connectors and how
they are composed together. COSA (Component-Object based
Software Structures), is based on object-oriented modeling and
component-based modeling. The model improves the reusability by
increasing extensibility, evolvability, and compositionality of the
software systems. This paper presents the COSA modelling tool
which help architects the possibility to verify the structural coherence
of a given system and to validate its semantics with COSA approach.
Abstract: The effects of commercial or bovine yeasts on the
performance and blood variables of broiler chickens intoxicated with
aflatoxin were investigated in broilers. Four hundred eighty broilers
(Arbor Acres; 3-wk-old) were randomly assigned to 4 groups. Each
group (120 broiler chickens) was further randomly divided into 6
replicates of 20 chickens. The treatments were control diet without
additives (treatment 1), 250 ppb AFB1 (treatment 2), commercial
yeast, Saccharomyces cerevisiae, (CY 2.5 x 107 CFU/g) + 250 ppb
AFB1 (treatment 3) and bovine yeast, Saccharomyces cerevisiae,
(BY 2.5 x 107 CFU/g + 250 ppb AFB1 (treatment 4). Complete
randomized design (CRD) was used in the experiment. Feed
consumption and body weight were recorded at every five-day
period. On day 42, carcass compositions were determined from 30
birds per treatment. While chicks were sacrificed, 3-4 ml blood
sample was taken and stored frozen at (-20°C) for serum chemical
analysis to determine effects of consumption of diets on blood
chemistry (total protein, albumin, glucose, urea, cholesterol and
triglycerides). There were no significant differences in ADFI among
the treatments(P>0.05). However, BWG, FCR and mortality were
highly significantly different (P
Abstract: As the fossil fuels kept on depleting, intense research in developing hydrogen (H2) as the alternative fuel has been done to cater our tremendous demand for fuel. The potential of H2 as the ultimate clean fuel differs with the fossil fuel that releases significant amounts of carbon dioxide (CO2) into the surrounding and leads to the global warming. The experimental work was carried out to study the production of H2 from palm kernel shell steam gasification at different variables such as heating rate, steam to biomass ratio and adsorbent to biomass ratio. Maximum H2 composition which is 61% (volume basis) was obtained at heating rate of 100oCmin-1, steam/biomass of 2:1 ratio, and adsorbent/biomass of 1:1 ratio. The commercial adsorbent had been modified by utilizing the alcoholwater mixture. Characteristics of both adsorbents were investigated and it is concluded that flowability and floodability of modified CaO is significantly improved.
Abstract: we propose a new normalized LMS (NLMS) algorithm, which gives satisfactory performance in certain applications in comaprison with con-ventional NLMS recursion. This new algorithm can be treated as a block based simplification of NLMS algorithm with significantly reduced number of multi¬ply and accumulate as well as division operations. It is also shown that such a recursion can be easily implemented in block floating point (BFP) arithmetic, treating the implementational issues much efficiently. In particular, the core challenges of a BFP realization to such adaptive filters are mainly considered in this regard. A global upper bound on the step size control parameter of the new algorithm due to BFP implementation is also proposed to prevent overflow in filtering as well as weight updating operations jointly.
Abstract: Data Envelopment Analysis (DEA) is one of the most
widely used technique for evaluating the relative efficiency of a set
of homogeneous decision making units. Traditionally, it assumes that
input and output variables are known in advance, ignoring the critical
issue of data uncertainty. In this paper, we deal with the problem
of efficiency evaluation under uncertain conditions by adopting the
general framework of the stochastic programming. We assume that
output parameters are represented by discretely distributed random
variables and we propose two different models defined according to a
neutral and risk-averse perspective. The models have been validated
by considering a real case study concerning the evaluation of the
technical efficiency of a sample of individual firms operating in
the Italian leather manufacturing industry. Our findings show the
validity of the proposed approach as ex-ante evaluation technique
by providing the decision maker with useful insights depending on
his risk aversion degree.
Abstract: Despite extensive study on wireless sensor network
security, defending internal attacks and finding abnormal behaviour
of the sensor are still difficult and unsolved task. The conventional
cryptographic technique does not give the robust security or detection
process to save the network from internal attacker that cause by
abnormal behavior. The insider attacker or abnormally behaved
sensor identificationand location detection framework using false
massage detection and Time difference of Arrival (TDoA) is
presented in this paper. It has been shown that the new framework
can efficiently identify and detect the insider attacker location so that
the attacker can be reprogrammed or subside from the network to
save from internal attack.
Abstract: Service innovations are central concerns in fast
changing environment. Due to the fitness in customer demands and
advances in information technologies (IT) in service management, an
expanded conceptualization of e-service innovation is required.
Specially, innovation practices have become increasingly more
challenging, driving managers to employ a different open innovation
model to maintain competitive advantages. At the same time, firms
need to interact with external and internal customers in innovative
environments, like the open innovation networks, to co-create values.
Based on these issues, an important conceptual framework of e-service
innovation is developed. This paper aims to examine the contributing
factors on e-service innovation and firm performance, including
financial and non-financial aspects. The study concludes by showing
how e-service innovation will play a significant role in growing the
overall values of the firm. The discussion and conclusion will lead to a
stronger understanding of e-service innovation and co-creating values
with customers within open innovation networks.