Abstract: The basic aim of our study is to give a possible model for handling uncertain information. This model is worked out in the framework of DATALOG. The concept of multivalued knowledgebase will be defined as a quadruple of any background knowledge; a deduction mechanism; a connecting algorithm, and a function set of the program, which help us to determine the uncertainty levels of the results. At first the concept of fuzzy Datalog will be summarized, then its extensions for intuitionistic- and interval-valued fuzzy logic is given and the concept of bipolar fuzzy Datalog is introduced. Based on these extensions the concept of multivalued knowledge-base will be defined. This knowledge-base can be a possible background of a future agent-model.
Abstract: In this paper, a single period inventory model with resalable returns has been analyzed in an imprecise and uncertain mixed environment. Demand has been introduced as a fuzzy random variable. In this model, a single order is placed before the start of the selling season. The customer, for a full refund, may return purchased products within a certain time interval. Returned products are resalable, provided they arrive back before the end of the selling season and are found to be undamaged. Products remaining at the end of the season are salvaged. All demands not met directly are lost. The probabilities that a sold product is returned and that a returned product is resalable, both imprecise in a real situation, have been assumed to be fuzzy in nature.
Abstract: In this paper effects of inclination angle on natural
convection flow in an open cavity has been analyzed with Lattice
Boltzmann Method (LBM).The angle of inclination varied from θ= -
45° to 45° with 15° intervals. Study has been conducted for Rayleigh
numbers (Ra) 104 to 106. The comparisons show that the average
Nusselt number increases with growth of Rayleigh number and the
average Nusselt number increase as inclination angles increases at
Ra=104.At Ra=105 and Ra=106 the average Nusselt number enhance
as inclination angels varied from θ= -45° to θ= 0° and decrease as
inclination angels increase in θ= 0° to θ= 45°.
Abstract: Spatial understanding and the understanding of
dynamic change in the spatial structure of molecules during a
reaction is essential for designing new molecules. Knowing the
physical processes in the reactions helps to speed up the designing
process. To support the designer with the correct representation of
the designed molecule as well as showing the dynamic behavior of
the whole reacting system is the goal of our application. Our system
shows the spatial deformation of the molecules at every time interval
by minimizing the energy level of the molecules. The position and
orientation of the molecules can be intuitively controlled by
manipulating objects of the real world using Augmented Reality
techniques. Our approach has the potential to speed up the design of
new molecules and help students to understand the chemical
processes better.
Abstract: In this article, we consider the estimation of P[Y < X], when strength, X and stress, Y are two independent variables of Burr Type XII distribution. The MLE of the R based on one simple iterative procedure is obtained. Assuming that the common parameter is known, the maximum likelihood estimator, uniformly minimum variance unbiased estimator and Bayes estimator of P[Y < X] are discussed. The exact confidence interval of the R is also obtained. Monte Carlo simulations are performed to compare the different proposed methods.
Abstract: In this work, new experimental data for slugging
frequency in inclined gas-liquid flow are reported, and a new
correlation is proposed. Scale experiments were carried out using a
mixture of air and water in a 6 m long pipe. Two different pipe
diameters were used, namely, 38 and 67 mm. The data were taken
with capacitance type sensors at a data acquisition frequency of 200
Hz over an interval of 60 seconds. For the range of flow conditions
studied, the liquid superficial velocity is observed to influence the
frequency strongly. A comparison of the present data with
correlations available in the literature reveals a lack of agreement. A
new correlation for slug frequency has been proposed for the inclined
flow, which represents the main contribution of this work.
Abstract: This article demonstrated development of
controlled release system of an NSAID drug, Diclofenac
sodium employing different ratios of Ethyl cellulose.
Diclofenac sodium and ethyl cellulose in different proportions
were processed by microencapsulation based on phase
separation technique to formulate microcapsules. The
prepared microcapsules were then compressed into tablets to
obtain controlled release oral formulations. In-vitro evaluation
was performed by dissolution test of each preparation was
conducted in 900 ml of phosphate buffer solution of pH 7.2
maintained at 37 ± 0.5 °C and stirred at 50 rpm. At predetermined
time intervals (0, 0.5, 1.0, 1.5, 2, 3, 4, 6, 8, 10, 12,
16, 20 and 24 hrs). The drug concentration in the collected
samples was determined by UV spectrophotometer at 276 nm.
The physical characteristics of diclofenac sodium
microcapsules were according to accepted range. These were
off-white, free flowing and spherical in shape. The release
profile of diclofenac sodium from microcapsules was found to
be directly proportional to the proportion of ethylcellulose and
coat thickness. The in-vitro release pattern showed that with
ratio of 1:1 and 1:2 (drug: polymer), the percentage release of
drug at first hour was 16.91 and 11.52 %, respectively as
compared to 1:3 which is only 6.87 % with in this time. The
release mechanism followed higuchi model for its release
pattern. Tablet Formulation (F2) of present study was found
comparable in release profile the marketed brand Phlogin-SR,
microcapsules showed an extended release beyond 24 h.
Further, a good correlation was found between drug release
and proportion of ethylcellulose in the microcapsules.
Microencapsulation based on coacervation found as good
technique to control release of diclofenac sodium for making
the controlled release formulations.
Abstract: Water level forecasting using records of past time series is of importance in water resources engineering and management. For example, water level affects groundwater tables in low-lying coastal areas, as well as hydrological regimes of some coastal rivers. Then, a reliable prediction of sea-level variations is required in coastal engineering and hydrologic studies. During the past two decades, the approaches based on the Genetic Programming (GP) and Artificial Neural Networks (ANN) were developed. In the present study, the GP is used to forecast daily water level variations for a set of time intervals using observed water levels. The measurements from a single tide gauge at Urmia Lake, Northwest Iran, were used to train and validate the GP approach for the period from January 1997 to July 2008. Statistics, the root mean square error and correlation coefficient, are used to verify model by comparing with a corresponding outputs from Artificial Neural Network model. The results show that both these artificial intelligence methodologies are satisfactory and can be considered as alternatives to the conventional harmonic analysis.
Abstract: We present a method for the selection of students
in interdisciplinary studies based on the hybrid averaging
operator. We assume that the available information given in
the problem is uncertain so it is necessary to use interval
numbers. Therefore, we suggest a new type of hybrid
aggregation called uncertain induced generalized hybrid
averaging (UIGHA) operator. It is an aggregation operator
that considers the weighted average (WA) and the ordered
weighted averaging (OWA) operator in the same formulation.
Therefore, we are able to consider the degree of optimism of
the decision maker and grades of importance in the same
approach. By using interval numbers, we are able to represent
the information considering the best and worst possible results
so the decision maker gets a more complete view of the
decision problem. We develop an illustrative example of the
proposed scheme in the selection of students in
interdisciplinary studies. We see that with the use of the
UIGHA operator we get a more complete representation of the
selection problem. Then, the decision maker is able to
consider a wide range of alternatives depending on his
interests. We also show other potential applications that could
be used by using the UIGHA operator in educational problems
about selection of different types of resources such as
students, professors, etc.
Abstract: Obstructive sleep apnea in patients, between 70 and 80
percent, can be cured with just a posture correcting. The most import
thing to do this is detection of obstructive sleep apnea. Detection of
obstructive sleep apnea can be performed through heart rate variability
analysis using power spectrum density analysis. After HRV analysis
we needed to know the current position information for correcting the
position. The pressure sensors of the array type were used to obtain
position information. These sensors can obtain information from the
experimenter about position. In addition, air cylinder corrected the
position of the experimenter by lifting the bed. The experimenter can
be changed position without breaking during sleep by the system.
Polysomnograph recording were obtained from 10 patients. The
results of HRV analysis were that NLF and LF/HF ratio increased,
while NHF decreased during OSA. Position change had to be done the
periods.
Abstract: In this paper, a uniform calculus-based approach for
synthesizing monitors checking correctness properties specified by a
large variety of logics at runtime is provided, including future and past
time logics, interval logics, state machine and parameterized temporal
logics. We present a calculus mechanism to synthesize monitors from
the logical specification for the incremental analysis of execution
traces during test and real run. The monitor detects both good and bad
prefix of a particular kind, namely those that are informative for the
property under investigation. We elaborate the procedure of calculus
as monitors.
Abstract: In this paper, a new learning algorithm based on a
hybrid metaheuristic integrating Differential Evolution (DE) and
Reduced Variable Neighborhood Search (RVNS) is introduced to train
the classification method PROAFTN. To apply PROAFTN, values of
several parameters need to be determined prior to classification. These
parameters include boundaries of intervals and relative weights for
each attribute. Based on these requirements, the hybrid approach,
named DEPRO-RVNS, is presented in this study. In some cases, the
major problem when applying DE to some classification problems
was the premature convergence of some individuals to local optima.
To eliminate this shortcoming and to improve the exploration and
exploitation capabilities of DE, such individuals were set to iteratively
re-explored using RVNS. Based on the generated results on
both training and testing data, it is shown that the performance of
PROAFTN is significantly improved. Furthermore, the experimental
study shows that DEPRO-RVNS outperforms well-known machine
learning classifiers in a variety of problems.
Abstract: Most papers model Joint Replenishment Problem
(JRP) as a (kT,S) where kT is a multiple value for a common review
period T,and S is a predefined order up to level. In general the (T,S)
policy is characterized by a long out of control period which requires
a large amount of safety stock compared to the (R,Q) policy. In this
paper a probabilistic model is built where an item, call it item(i),
with the shortest order time between interval (T)is modeled under
(R,Q) policy and its inventory is continuously reviewed, while the
rest of items (j) are periodically reviewed at a definite time
corresponding to item
Abstract: In recent years multi-agent systems have emerged as one of the interesting architectures facilitating distributed collaboration and distributed problem solving. Each node (agent) of the network might pursue its own agenda, exploit its environment, develop its own problem solving strategy and establish required communication strategies. Within each node of the network, one could encounter a diversity of problem-solving approaches. Quite commonly the agents can realize their processing at the level of information granules that is the most suitable from their local points of view. Information granules can come at various levels of granularity. Each agent could exploit a certain formalism of information granulation engaging a machinery of fuzzy sets, interval analysis, rough sets, just to name a few dominant technologies of granular computing. Having this in mind, arises a fundamental issue of forming effective interaction linkages between the agents so that they fully broadcast their findings and benefit from interacting with others.
Abstract: In this paper, an automatic detecting algorithm for
QRS complex detecting was applied for analyzing ECG recordings
and five criteria for dangerous arrhythmia diagnosing are applied for a
protocol type of automatic arrhythmia diagnosing system. The
automatic detecting algorithm applied in this paper detected the
distribution of QRS complexes in ECG recordings and related
information, such as heart rate and RR interval. In this investigation,
twenty sampled ECG recordings of patients with different pathologic
conditions were collected for off-line analysis. A combinative
application of four digital filters for bettering ECG signals and
promoting detecting rate for QRS complex was proposed as
pre-processing. Both of hardware filters and digital filters were
applied to eliminate different types of noises mixed with ECG
recordings. Then, an automatic detecting algorithm of QRS complex
was applied for verifying the distribution of QRS complex. Finally,
the quantitative clinic criteria for diagnosing arrhythmia were
programmed in a practical application for automatic arrhythmia
diagnosing as a post-processor. The results of diagnoses by automatic
dangerous arrhythmia diagnosing were compared with the results of
off-line diagnoses by experienced clinic physicians. The results of
comparison showed the application of automatic dangerous
arrhythmia diagnosis performed a matching rate of 95% compared
with an experienced physician-s diagnoses.
Abstract: The objective of current study is to investigate the
differences of winning and losing teams in terms of goal scoring and
passing sequences. Total of 31 matches from UEFA-EURO 2012
were analyzed and 5 matches were excluded from analysis due to
matches end up drawn. There are two groups of variable used in the
study which is; i. the goal scoring variable and: ii. passing sequences
variable. Data were analyzed using Wilcoxon matched pair rank test
with significant value set at p < 0.05. Current study found the timing
of goal scored was significantly higher for winning team at 1st half
(Z=-3.416, p=.001) and 2nd half (Z=-3.252, p=.001). The scoring
frequency was also found to be increase as time progressed and the
last 15 minutes of the game was the time interval the most goals
scored. The indicators that were significantly differences between
winning and losing team were the goal scored (Z=-4.578, p=.000),
the head (Z=-2.500, p=.012), the right foot (Z=-3.788,p=.000),
corner (Z=-.2.126,p=.033), open play (Z=-3.744,p=.000), inside the
penalty box (Z=-4.174, p=.000) , attackers (Z=-2.976, p=.003) and
also the midfielders (Z=-3.400, p=.001). Regarding the passing
sequences, there are significance difference between both teams in
short passing sequences (Z=-.4.141, p=.000). While for the long
passing, there were no significance difference (Z=-.1.795, p=.073).
The data gathered in present study can be used by the coaches to
construct detailed training program based on their objectives.
Abstract: Phase error in communications systems degrades error
performance. In this paper, we present a simple approximation for the
average error probability of the binary phase shift keying (BPSK) in
the presence of phase error having a uniform distribution on arbitrary
intervals. For the simple approximation, we use symmetry and
periodicity of a sinusoidal function. Approximate result for the
average error probability is derived, and the performance is verified
through comparison with simulation result.
Abstract: The log periodogram regression is widely used in empirical
applications because of its simplicity, since only a least squares
regression is required to estimate the memory parameter, d, its good
asymptotic properties and its robustness to misspecification of the
short term behavior of the series. However, the asymptotic distribution
is a poor approximation of the (unknown) finite sample distribution
if the sample size is small. Here the finite sample performance of different
nonparametric residual bootstrap procedures is analyzed when
applied to construct confidence intervals. In particular, in addition to
the basic residual bootstrap, the local and block bootstrap that might
adequately replicate the structure that may arise in the errors of the
regression are considered when the series shows weak dependence in
addition to the long memory component. Bias correcting bootstrap
to adjust the bias caused by that structure is also considered. Finally,
the performance of the bootstrap in log periodogram regression based
confidence intervals is assessed in different type of models and how
its performance changes as sample size increases.
Abstract: This study was conducted to examine the effects of ketum extract on development of Chrysomya rufifacies and to analyze the presence of mitragynine in the larvae samples. 110 newly emerged first instar larvae of C. rufifacies were introduced on ketum extract-mixed cow liver at doses of 0, 20, 40 and 60g. Blowfly development rate was determined with 12 hour intervals and
mitragynine in larvae was extracted and quantitated. C. rufifacies in control group took about 192 hours to complete their development from first instar larvae to adult blowfly; meanwhile blowfly form from the highest dose of ketum was 264 hours. Mitragynine was detected in all groups of treatment, except for control. In conclusion, the presence of mitragynine in C. rufifacies is affected in delaying development rates of the blowfly for up to 62 hours or 3 days. Chemical analysis of mitragynine from larvae samples showed that this alkaloid present in all specimens analyzed.
Abstract: The efficiency of an image watermarking technique depends on the preservation of visually significant information. This is attained by embedding the watermark transparently with the maximum possible strength. The current paper presents an approach for still image digital watermarking in which the watermark embedding process employs the wavelet transform and incorporates Human Visual System (HVS) characteristics. The sensitivity of a human observer to contrast with respect to spatial frequency is described by the Contrast Sensitivity Function (CSF). The strength of the watermark within the decomposition subbands, which occupy an interval on the spatial frequencies, is adjusted according to this sensitivity. Moreover, the watermark embedding process is carried over the subband coefficients that lie on edges where distortions are less noticeable. The experimental evaluation of the proposed method shows very good results in terms of robustness and transparency.