Abstract: Artificial Immune System is applied as a Heuristic
Algorithm for decades. Nevertheless, many of these applications
took advantage of the benefit of this algorithm but seldom proposed
approaches for enhancing the efficiency. In this paper, a
Self-evolving Artificial Immune System is proposed via developing
the T and B cell in Immune System and built a self-evolving
mechanism for the complexities of different problems. In this
research, it focuses on enhancing the efficiency of Clonal selection
which is responsible for producing Affinities to resist the invading of
Antigens. T and B cell are the main mechanisms for Clonal
Selection to produce different combinations of Antibodies.
Therefore, the development of T and B cell will influence the
efficiency of Clonal Selection for searching better solution.
Furthermore, for better cooperation of the two cells, a co-evolutional
strategy is applied to coordinate for more effective productions of
Antibodies. This work finally adopts Flow-shop scheduling
instances in OR-library to validate the proposed algorithm.
Abstract: In recent years, Radio Frequency Identification (RFID)
is followed with interest by many researches, especially for the
purpose of indoor positioning as the innate properties of RFID are
profitable for achieving it. A lot of algorithms or schemes are proposed
to be used in the RFID-based positioning system, but most of them are
lack of environmental consideration and it induces inaccuracy of
application. In this research, a lot of algorithms and schemes of RFID
indoor positioning are discussed to see whether effective or not on
application, and some rules are summarized for achieving accurate
positioning. On the other hand, a new term “Noise Factor" is involved
to describe the signal loss between the target and the obstacle. As a
result, experimental data can be obtained but not only simulation; and
the performance of the positioning system can be expressed
substantially.
Abstract: Due to the coexistence of different Radio Access
Technologies (RATs), Next Generation Wireless Networks (NGWN)
are predicted to be heterogeneous in nature. The coexistence of
different RATs requires a need for Common Radio Resource
Management (CRRM) to support the provision of Quality of Service
(QoS) and the efficient utilization of radio resources. RAT selection
algorithms are part of the CRRM algorithms. Simply, their role is to
verify if an incoming call will be suitable to fit into a heterogeneous
wireless network, and to decide which of the available RATs is most
suitable to fit the need of the incoming call and admit it.
Guaranteeing the requirements of QoS for all accepted calls and at
the same time being able to provide the most efficient utilization of
the available radio resources is the goal of RAT selection algorithm.
The normal call admission control algorithms are designed for
homogeneous wireless networks and they do not provide a solution
to fit a heterogeneous wireless network which represents the NGWN.
Therefore, there is a need to develop RAT selection algorithm for
heterogeneous wireless network. In this paper, we propose an
approach for RAT selection which includes receiving different
criteria, assessing and making decisions, then selecting the most
suitable RAT for incoming calls. A comprehensive survey of
different RAT selection algorithms for a heterogeneous wireless
network is studied.
Abstract: Mobile robots are used in a large field of scenarios,
like exploring contaminated areas, repairing oil rigs under water,
finding survivors in collapsed buildings, etc. Currently, there is no
unified intuitive user interface (UI) to control such complex mobile
robots. As a consequence, some scenarios are done without the
exploitation of experience and intuition of human teleoperators.
A novel framework has been developed to embed a flexible and
modular UI into a complete 3-D virtual reality simulation system.
This new approach wants to access maximum benefits of human
operators. Sensor information received from the robot is prepared for
an intuitive visualization. Virtual reality metaphors support the
operator in his decisions. These metaphors are integrated into a real
time stereo video stream. This approach is not restricted to any
specific type of mobile robot and allows for the operation of different
robot types with a consistent concept and user interface.
Abstract: Our study is concerned with the development of an Emergency Medical Services (EMS) ambulance location and allocation model called the Time-based Ambulance Zoning Optimization Model (TAZ_OPT). This paper presents the framework of the study. The model is formulated using the goal programming (GP), where the goals are to determine the satellite locations of ambulances and the number of ambulances to be allocated at these locations. The model aims at maximizing the expected demand coverage based on probability of reaching the emergency location within targetted time, and minimizing the ambulance busyness likelihood value. Among the benefits of the model is the increased accessibility and availability of ambulances, thus, enhanced quality of the EMS ambulance services.
Abstract: Nowaday-s, many organizations use systems that
support business process as a whole or partially. However, in some
application domains, like software development and health care
processes, a normative Process Aware System (PAS) is not suitable,
because a flexible support is needed to respond rapidly to new
process models. On the other hand, a flexible Process Aware System
may be vulnerable to undesirable and fraudulent executions, which
imposes a tradeoff between flexibility and security. In order to make
this tradeoff available, a genetic-based anomaly detection model for
logs of Process Aware Systems is presented in this paper. The
detection of an anomalous trace is based on discovering an
appropriate process model by using genetic process mining and
detecting traces that do not fit the appropriate model as anomalous
trace; therefore, when used in PAS, this model is an automated
solution that can support coexistence of flexibility and security.
Abstract: Scolothrips longicornis Priesner is one of the
important predators of tetranychid mites with a wide distribution
throughout Iran. Life table and population growth parameters of S.
longicornis feeding on two-spotted spider mite, Tetranychus
turkestani Ugarov & Nikolski were investigated under laboratory
condition (26±1ºC, 65±5% R.H. and 16L: 8D). To carry of these
experiments, S. longicornis collections reared on cowpea infested
with T. turkestani were prepared. The eggs with less than 24 hours
old were selected and reared. The emerged larvae feeding directly on
cowpea leaf discs which were infested with T. turkestani. Thirty
females of S. longicornis with 24 hours age were selected and
released on infested leaf discs. They replaced daily to a new leaf disc
and the laying eggs have counted. The experiment continued till the
last thrips had died. The result showed that the mean age mortality of
the adult female thrips were between 21-25 days which is nearly
equal life expectancy (ex) at the time of adult eclosion. Parameters
related to reproductive table including gross reproductive rate, net
reproductive rate, intrinsic rate of natural increase and finite rate of
increase were 48.91, 37.63, 0.26 and 2.3, respectively. Mean age per
female/day, mean fertile egg per female/day, gross hatch rate, mean
net age fertility, mean net age fecundity, net fertility rate and net
fecundity rate were 2.23, 1.76, 0.87, 13.87, 14.26, 69.1 and 78.5,
respectively. Sex ratio of offspring also recorded daily. The highest
sex ratio for females was 0.88 in first day of oviposition. The sex
ratio decreased gradually and reached under 0.46 after the day 26 and
the oviposition rate declined. Then it seems that maintenance of
rearing culture of predatory thrips for mass rearing later than 26 days
after egg-laying commence is not profitable.
Abstract: Understanding patient factors related to physical activity behavior is important in the management of Type 2 Diabetes. This study applied the Theory of Planned Behavior model to understand physical activity behavior among sampled Type 2 diabetics in Kenya. The study was conducted within the diabetic clinic at Kisii Level 5 Hospital and adopted sequential mixed methods design beginning with qualitative phase and ending with quantitative phase. Qualitative data was analyzed using grounded theory analysis method. Structural equation modeling using maximum likelihood was used to analyze quantitative data. The common fit indices revealed that the theory of planned behavior fitted the data acceptably well among the Type 2 diabetes and within physical activity behavior {¤ç2 = 213, df = 84, n=230, p = .061, ¤ç2/df = 2.53; TLI = .97; CFI =.96; RMSEA (90CI) = .073(.029, .08)}. This theory proved to be useful in understanding physical activity behavior among Type 2 diabetics.
Abstract: The genetic algorithm (GA) based solution techniques
are found suitable for optimization because of their ability of
simultaneous multidimensional search. Many GA-variants have been
tried in the past to solve optimal power flow (OPF), one of the
nonlinear problems of electric power system. The issues like
convergence speed and accuracy of the optimal solution obtained
after number of generations using GA techniques and handling
system constraints in OPF are subjects of discussion. The results
obtained for GA-Fuzzy OPF on various power systems have shown
faster convergence and lesser generation costs as compared to other
approaches. This paper presents an enhanced GA-Fuzzy OPF (EGAOPF)
using penalty factors to handle line flow constraints and load
bus voltage limits for both normal network and contingency case
with congestion. In addition to crossover and mutation rate
adaptation scheme that adapts crossover and mutation probabilities
for each generation based on fitness values of previous generations, a
block swap operator is also incorporated in proposed EGA-OPF. The
line flow limits and load bus voltage magnitude limits are handled by
incorporating line overflow and load voltage penalty factors
respectively in each chromosome fitness function. The effects of
different penalty factors settings are also analyzed under contingent
state.
Abstract: In this paper, the potential security issues brought by the virtualization of a Software Defined Networks (SDN) would be analyzed. The virtualization of SDN is achieved by FlowVisor (FV). With FV, a physical network is divided into multiple isolated logical networks while the underlying resources are still shared by different slices (isolated logical networks). However, along with the benefits brought by network virtualization, it also presents some issues regarding security. By examining security issues existing in an OpenFlow network, which uses FlowVisor to slice it into multiple virtual networks, we hope we can get some significant results and also can get furtherdiscussions among the security of SDN virtualization.
Abstract: A two-parameter fatigue model explicitly accounting for the cyclic as well as the mean stress was used to fit static and fatigue data available in literature concerning carbon fiber reinforced composite laminates subjected tension-tension fatigue. The model confirms the strength–life equal rank assumption and predicts reasonably the probability of failure under cyclic loading. The model parameters were found by best fitting procedures and required a minimum of experimental tests.
Abstract: Nano-MgO was successfully deposited on titania using deposition-precipitation method. The catalyst produced was characterised using FTIR, XRD, BET and XRF and its activity was tested on the transesterification reaction of soybean oil to biodiesel. The catalyst activity improved when the reaction temperature was increasedfrom 150 and 225 OC. It was also observed that increasing the reaction time above 1h had no significant benefit on conversion. The stability fixed MgO on TiO2 was investigated using XRF and ICP-OES. It was observed that MgO loss during the reaction was between 0.5-2.3 percent and that there was no correlation between the reaction temperature and the MgO loss.
Abstract: Semnan is a city in semnan province, northern Iran
with a population estimated at 119,778 inhabitants. It is the
provincial capital of semnan province. Iran is a developing country
and construction is a basic factor of developing too. Hence, Semnan
city needs to a special programming for construction of buildings,
structures and infrastructures. Semnan municipality tries to begin this
program. In addition to, city has some historical monuments which
can be interesting for tourists. Hence, Semnan inhabitants can benefit
from tourist industry. Optimization of Energy in construction
industry is another activity of this municipality and the inhabitants
who execute these regulations receive some discounts. Many parts of
Iran such as semnan are located in highly seismic zones and
structures must be constructed safe e.g., according to recent seismic
codes. In this paper opportunities of IT in construction industry of
Iran are investigated in three categories. Pre-construction phase,
construction phase and earthquake disaster mitigation are studied.
Studies show that information technology can be used in these items
for reducing the losses and increasing the benefits. Both government
and private sectors must contribute to this strategic project for
obtaining the best result.
Abstract: Extreme temperature of several stations in Malaysia is
modelled by fitting the monthly maximum to the Generalized
Extreme Value (GEV) distribution. The Mann-Kendall (MK) test
suggests a non-stationary model. Two models are considered for
stations with trend and the Likelihood Ratio test is used to determine
the best-fitting model. Results show that half of the stations favour a
model which is linear for the location parameters. The return level is
the level of events (maximum temperature) which is expected to be
exceeded once, on average, in a given number of years, is obtained.
Abstract: Beta-spline is built on G2 continuity which guarantees
smoothness of generated curves and surfaces using it. This curve is
preferred to be used in object design rather than reconstruction. This
study however, employs the Beta-spline in reconstructing a 3-
dimensional G2 image of the Stanford Rabbit. The original data
consists of multi-slice binary images of the rabbit. The result is then
compared with related works using other techniques.
Abstract: Edge detection is usually the first step in medical
image processing. However, the difficulty increases when a
conventional kernel-based edge detector is applied to ultrasonic
images with a textural pattern and speckle noise. We designed an
adaptive diffusion filter to remove speckle noise while preserving the
initial edges detected by using a Sobel edge detector. We also propose
a genetic algorithm for edge selection to form complete boundaries of
the detected entities. We designed two fitness functions to evaluate
whether a criterion with a complex edge configuration can render a
better result than a simple criterion such as the strength of gradient.
The edges obtained by using a complex fitness function are thicker and
more fragmented than those obtained by using a simple fitness
function, suggesting that a complex edge selecting scheme is not
necessary for good edge detection in medical ultrasonic images;
instead, a proper noise-smoothing filter is the key.
Abstract: The next generation wireless systems, especially the
cognitive radio networks aim at utilizing network resources more
efficiently. They share a wide range of available spectrum in an
opportunistic manner. In this paper, we propose a quality
management model for short-term sub-lease of unutilized spectrum
bands to different service providers. We built our model on
competitive secondary market architecture. To establish the
necessary conditions for convergent behavior, we utilize techniques
from game theory. Our proposed model is based on potential game
approach that is suitable for systems with dynamic decision making.
The Nash equilibrium point tells the spectrum holders the ideal price
values where profit is maximized at the highest level of customer
satisfaction. Our numerical results show that the price decisions of
the network providers depend on the price and QoS of their own
bands as well as the prices and QoS levels of their opponents- bands.
Abstract: Sickle cell anemia is a recessive genetic disease
caused by the presence in the red blood cell, of abnormal hemoglobin
called hemoglobin S. It results from the replacement in the beta chain
of the acid glutamic acid by valin at position 6. Topics may be
homozygous (SS) or heterozygous (AS) most often
asymptomatic. Other mutations result in compound heterozygous:
- Synthesis of hemoglobin C mutation in the sixth leucin codon
(heterozygous SC);
- ß-thalassemia (heterozygous S-ß thalassemia).
SS homozygous, heterozygous SC and S- ß -thalassemia are grouped
under the major sickle cell syndromes.
To make a laboratory diagnosis of hemoglobinopathies in a
portion of the population in region of Batna, our study was
conducted on 115 patients with suspected sickle cell anemia, all cases
have benefited from hematological tests as blood count (count RBC,
calculated erythrocyte indices, MCV and MCHC, measuring the
hemoglobin concentration) and a biochemical test in this case
electrophoresis CAPILLARYS HEMOGLOBIN (E).
The results showed:
27 cases of sickle cell anemia were found on 115 suspected cases,
73,03% homozygous sickle cell disease and 59,25% sickle cell trait.
Finally, the double heterozygous S/C, represent the incidence rate of
3, 70%.
Abstract: An evolutionary computing technique for solving initial value problems in Ordinary Differential Equations is proposed in this paper. Neural network is used as a universal approximator while the adaptive parameters of neural networks are optimized by genetic algorithm. The solution is achieved on the continuous grid of time instead of discrete as in other numerical techniques. The comparison is carried out with classical numerical techniques and the solution is found with a uniform accuracy of MSE ≈ 10-9 .
Abstract: There is limited evidence from various countries
about the possible impact of various criteria to be used to determine
the scope of the IFRS for SMEs issued in 2009 and, research is
needed in this area. We provide evidence from Romania, an
emerging economy member of the European Union. The aim of this
paper is to analyze in a local setting if size is a relevant factor for
deciding between local and global standards for SMEs. Our results
indicate that size is a moderate indicator of the existence of possible
users interested in financial statements and that there is a difference
between the scopes of the standard determined on various criteria..
Also, we suggest that the international exposure is quite reduced in
the case of SMEs, but is sufficient to suggest that at least some SMEs
would benefit from international comparability of financial
statements