Abstract: The evaluation of the convective heat transfer of flow in passages with rectangular cross section is still of interest for the heat transfer investigators, as in the air heater solar collectors. The aim of this paper is to present investigation results on the natural convection heat transfer in a solar air heater. The effect of the channel length as heat transfer surface and the inclination of the passage were investigated. The results were obtained experimentally and theoretically. For that, an experimental test rig was fabricated with channel lengths of 1m, 1.5m, and 2m. For each length, the air outlet and inlet temperatures, absorber and cover temperatures, solar radiation intensity and air flow rate were measured at 10o, 30o, 50o, 70o, and 90o tilt angles. Measurements were recorded every 2 hours interval to investigate the transient behavior of the system. The experimental and theoretical results are presented in terms of Nu number versus Ra number and discussed. The percentages of differences between experimental and theoretical results are within the margin of 6% to 13%, effectively. It is recommended to extend the investigation to study the same configurations with different artificial surface roughing by ribs or pins.
Abstract: This research work examines the effect of variations of metrological parameters on the tropospheric radio refractivity during dry and raining seasons for Akure in 2013. The daily averages of radio refractivity during dry (January) and raining (August) seasons were calculated from the data obtained from the Nigeria Metrological Agency (NIMET). The data that was used for the computation of radio refractivity is a daily interval of the variations of metrological parameters for each day in the troposphere for Akure. Consequently, the daily averages of radio refractivity during raining season (August) were greater than the results in dry season (January) as a result of the variations in meteorological parameters such as temperature, humidity and atmospheric pressure in the lower troposphere.
Abstract: Most empirical studies have analyzed how liquidity risks faced by individual institutions turn into systemic risk. Recent banking crisis has highlighted the importance of grasping and controlling the systemic risk, and the acceptance by Central Banks to ease their monetary policies for saving default or illiquid banks. This last point shows that banks would pay less attention to liquidity risk which, in turn, can become a new important channel of loss. The financial regulation focuses on the most important and “systemic” banks in the global network. However, to quantify the expected loss associated with liquidity risk, it is worth to analyze sensitivity to this channel for the various elements of the global bank network. A small bank is not considered as potentially systemic; however the interaction of small banks all together can become a systemic element. This paper analyzes the impact of medium and small banks interaction on a set of banks which is considered as the core of the network. The proposed method uses the structure of agent-based model in a two-class environment. In first class, the data from actual balance sheets of 22 large and systemic banks (such as BNP Paribas or Barclays) are collected. In second one, to model a network as closely as possible to actual interbank market, 578 fictitious banks smaller than the ones belonging to first class have been split into two groups of small and medium ones. All banks are active on the European interbank network and have deposit and market activity. A simulation of 12 three month periods representing a midterm time interval three years is projected. In each period, there is a set of behavioral descriptions: repayment of matured loans, liquidation of deposits, income from securities, collection of new deposits, new demands of credit, and securities sale. The last two actions are part of refunding process developed in this paper. To strengthen reliability of proposed model, random parameters dynamics are managed with stochastic equations as rates the variations of which are generated by Vasicek model. The Central Bank is considered as the lender of last resort which allows banks to borrow at REPO rate and some ejection conditions of banks from the system are introduced.
Liquidity crunch due to exogenous crisis is simulated in the first class and the loss impact on other bank classes is analyzed though aggregate values representing the aggregate of loans and/or the aggregate of borrowing between classes. It is mainly shown that the three groups of European interbank network do not have the same response, and that intermediate banks are the most sensitive to liquidity risk.
Abstract: This paper addresses the robust stability problem of a class of delayed neutral Lur’e systems. Combined with the property of convex function and double integral Jensen inequality, a new tripe integral Lyapunov functional is constructed to derive some new stability criteria. Compared with some related results, the new criteria established in this paper are less conservative. Finally, two numerical examples are presented to illustrate the validity of the main results.
Abstract: The author proposes an extension of particle swarm optimization (PSO) for solving interval-valued optimization problems and applies the extended PSO to evolutionary training of neural networks (NNs) with interval weights. In the proposed PSO, values in the genotypes are not real numbers but intervals. Experimental results show that interval-valued NNs trained by the proposed method could well approximate hidden target functions despite the fact that no training data was explicitly provided.
Abstract: The author previously proposed an extension of differential evolution. The proposed method extends the processes of DE to handle interval numbers as genotype values so that DE can be applied to interval-valued optimization problems. The interval DE can employ either of two interval models, the lower and upper model or the center and width model, for specifying genotype values. Ability of the interval DE in searching for solutions may depend on the model. In this paper, the author compares the two models to investigate which model contributes better for the interval DE to find better solutions. Application of the interval DE is evolutionary training of interval-valued neural networks. A result of preliminary study indicates that the CW model is better than the LU model: the interval DE with the CW model could evolve better neural networks.
Abstract: Support vector clustering (SVC) is an important kernelbased clustering algorithm in multi applications. It has got two main bottle necks, the high computation price and labeling piece. In this paper, we presented a modified SVC method, named Grid–SVC, to improve the original algorithm computationally. First we normalized and then we parted the interval, where the SVC is processing, using a novel Grid–based clustering algorithm. The algorithm parts the intervals, based on the density function of the data set and then applying the cartesian multiply makes multi-dimensional grids. Eliminating many outliers and noise in the preprocess, we apply an improved SVC method to each parted grid in a parallel way. The experimental results show both improvement in time complexity order and the accuracy.
Abstract: The paper deals with the maximum likelihood estimation of the parameters of the Burr type V distribution based on left censored samples. The maximum likelihood estimators (MLE) of the parameters have been derived and the Fisher information matrix for the parameters of the said distribution has been obtained explicitly. The confidence intervals for the parameters have also been discussed. A simulation study has been conducted to investigate the performance of the point and interval estimates.
Abstract: Study on corrosion propensity of welded mild steel- bar in soil media around the coastal area of University of Lagos has been carried out using gravimetric method. Six (6) samples each for welded and unwelded mild steels were cut, their initial weights were recorded and buried in two selected soil. The weight losses of these coupons were measured at regular intervals for a period of six months (180 days).
The corrosiveness of the soil media varied widely depending on the potency level of its constituents. The results revealed that soil in the studied area have marked variations in composition and contents. Soil medium with a lower pH and higher chloride ion concentration aggressively attacked the coupons with the welded steel coupon corroding faster than unwelded one. The medium resistivity to the flow of current is another strong factor affecting corrosion rate.
Abstract: Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotiv EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.
Abstract: In this paper we proposed the new confidence interval for the normal population mean with known coefficient of variation. In practice, this situation occurs normally in environment and agriculture sciences where we know the standard deviation is proportional to the mean. As a result, the coefficient of variation of is known. We propose the new confidence interval based on the recent work of Khan [3] and this new confidence interval will compare with our previous work, see, e.g. Niwitpong [5]. We derive analytic expressions for the coverage probability and the expected length of each confidence interval. A numerical method will be used to assess the performance of these intervals based on their expected lengths.
Abstract: In many practical applications in various areas, such as engineering, science and social science, it is known that there exist bounds on the values of unknown parameters. For example, values of some measurements for controlling machines in an industrial process, weight or height of subjects, blood pressures of patients and retirement ages of public servants. When interval estimation is considered in a situation where the parameter to be estimated is bounded, it has been argued that the classical Neyman procedure for setting confidence intervals is unsatisfactory. This is due to the fact that the information regarding the restriction is simply ignored. It is, therefore, of significant interest to construct confidence intervals for the parameters that include the additional information on parameter values being bounded to enhance the accuracy of the interval estimation. Therefore in this paper, we propose a new confidence interval for the coefficient of variance where the population mean and standard deviation are bounded. The proposed interval is evaluated in terms of coverage probability and expected length via Monte Carlo simulation.
Abstract: A method is proposed to extract faithful representative patterns from data set of observations when they are suffering from non-negligible fluctuations. Supposing time interval between measurements to be extremely small compared to observation time, it consists in defining first a subset of intermediate time intervals characterizing coherent behavior. Data projection on these intervals gives a set of curves out of which an ideally “perfect” one is constructed by taking the sup limit of them. Then comparison with average real curve in corresponding interval gives an efficiency parameter expressing the degradation consecutive to fluctuation effect. The method is applied to sunlight data collected in a specific place, where ideal sunlight is the one resulting from direct exposure at location latitude over the year, and efficiency is resulting from action of meteorological parameters, mainly cloudiness, at different periods of the year. The extracted information already gives interesting element of decision, before being used for analysis of plant control.
Abstract: In this paper, we propose two new confidence intervals for the inverse of a normal mean with a known coefficient of variation. One of new confidence intervals for the inverse of a normal mean with a known coefficient of variation is constructed based on the pivotal statistic Z where Z is a standard normal distribution and another confidence interval is constructed based on the generalized confidence interval, presented by Weerahandi. We examine the performance of these confidence intervals in terms of coverage probabilities and average lengths via Monte Carlo simulation.
Abstract: Grasslands of Iran are encountered with a vast
desertification and destruction. Some legumes are plants of forage
importance with high palatability. Studied legumes in this project are
Onobrychis, Medicago sativa (alfalfa) and Trifolium repens. Seeds
were cultivated in research field of Kaboutarabad (33 km East of
Isfahan, Iran) with an average 80 mm. annual rainfall. Plants were
cultivated in a split plot design with 3 replicate and two water
treatments (weekly irrigation, and under stress with same amount per
15 days interval). Water entrance to each plots were measured by
Partial flow. This project lasted 20 weeks. Destructive samplings
(1m2 each time) were done weekly. At each sampling plants were
gathered and weighed separately for each vegetative parts. An Area
Meter (Vista) was used to measure root surface and leaf area. Total
shoot and root fresh and dry weight, leaf area index and soil coverage
were evaluated too. Dry weight was achieved in 750c oven after 24
hours. Statgraphic and Harvard Graphic software were used to
formulate and demonstrate the parameters curves due to time. Our
results show that Trifolium repens has affected 60 % and Medicago
sativa 18% by water stress. Onobrychis total fresh weight was
reduced 45%. Dry weight or Biomass in alfalfa is not so affected by
water shortage. This means that in alfalfa fields we can decrease the
irrigation amount and have some how same amount of Biomass.
Onobrychis show a drastic decrease in Biomass. The increases in
total dry matter due to time in studied plants are formulated. For
Trifolium repens if removal or cattle entrance to meadows do not
occurred at perfect time, it will decrease the palatability and water
content of the shoots. Water stress in a short period could develop the
root system in Trifolium repens, but if it last more than this other
ecological and soil factors will affect the growth of this plant. Low
level of soil water is not so important for studied legume forges. But
water shortage affect palatability and water content of aerial parts.
Leaf area due to time in studied legumes is formulated. In fact leaf
area is decreased by shortage in available water. Higher leaf area
means higher forage and biomass production. Medicago and
Onobrychis reach to the maximum leaf area sooner than Trifolium
and are able to produce an optimum soil cover and inhibit the
transpiration of soil water of meadows. Correlation of root surface to
Total biomass in studied plants is formulated. Medicago under water
stress show a 40% decrease in crown cover while at optimum
condition this amount reach to 100%. In order to produce forage in
areas without soil erosion Medicago is the best choice even with a
shortage in water resources. It is tried to represent the growth
simulation of three famous Forage Legumes. By growth simulation
farmers and range managers could better decide to choose best plant
adapted to water availability without designing different time and
labor consuming field experiments.
Abstract: Reliable water level forecasts are particularly
important for warning against dangerous flood and inundation. The
current study aims at investigating the suitability of the adaptive
network based fuzzy inference system for continuous water level
modeling. A hybrid learning algorithm, which combines the least
square method and the back propagation algorithm, is used to
identify the parameters of the network. For this study, water levels
data are available for a hydrological year of 2002 with a sampling
interval of 1-hour. The number of antecedent water level that should
be included in the input variables is determined by two statistical
methods, i.e. autocorrelation function and partial autocorrelation
function between the variables. Forecasting was done for 1-hour until
12-hour ahead in order to compare the models generalization at
higher horizons. The results demonstrate that the adaptive networkbased
fuzzy inference system model can be applied successfully and
provide high accuracy and reliability for river water level estimation.
In general, the adaptive network-based fuzzy inference system
provides accurate and reliable water level prediction for 1-hour ahead
where the MAPE=1.15% and correlation=0.98 was achieved. Up to
12-hour ahead prediction, the model still shows relatively good
performance where the error of prediction resulted was less than
9.65%. The information gathered from the preliminary results
provide a useful guidance or reference for flood early warning
system design in which the magnitude and the timing of a potential
extreme flood are indicated.
Abstract: Mammalian genomes contain large number of
retroelements (SINEs, LINEs and LTRs) which could affect
expression of protein coding genes through associated transcription
factor binding sites (TFBS). Activity of the retroelement-associated
TFBS in many genes is confirmed experimentally but their global
functional impact remains unclear. Human SINEs (Alu repeats) and
mouse SINEs (B1 and B2 repeats) are known to be clustered in GCrich
gene rich genome segments consistent with the view that they
can contribute to regulation of gene expression. We have shown
earlier that Alu are involved in formation of cis-regulatory modules
(clusters of TFBS) in human promoters, and other authors reported
that Alu located near promoter CpG islands have an increased
frequency of CpG dinucleotides suggesting that these Alu are
undermethylated. Human Alu and mouse B1/B2 elements have an
internal bipartite promoter for RNA polymerase III containing
conserved sequence motif called B-box which can bind basal
transcription complex TFIIIC. It has been recently shown that TFIIIC
binding to B-box leads to formation of a boundary which limits
spread of repressive chromatin modifications in S. pombe. SINEassociated
B-boxes may have similar function but conservation of
TFIIIC binding sites in SINEs located near mammalian promoters
has not been studied earlier. Here we analysed abundance and
distribution of retroelements (SINEs, LINEs and LTRs) in annotated
sequences of the Database of mammalian transcription start sites
(DBTSS). Fractions of SINEs in human and mouse promoters are
slightly lower than in all genome but >40% of human and mouse
promoters contain Alu or B1/B2 elements within -1000 to +200 bp
interval relative to transcription start site (TSS). Most of these SINEs
is associated with distal segments of promoters (-1000 to -200 bp
relative to TSS) indicating that their insertion at distances >200 bp
upstream of TSS is tolerated during evolution. Distribution of SINEs
in promoters correlates negatively with the distribution of CpG
sequences. Using analysis of abundance of 12-mer motifs from the
B1 and Alu consensus sequences in genome and DBTSS it has been
confirmed that some subsegments of Alu and B1 elements are poorly
conserved which depends in part on the presence of CpG
dinucleotides. One of these CpG-containing subsegments in B1
elements overlaps with SINE-associated B-box and it shows better
conservation in DBTSS compared to genomic sequences. It has been
also studied conservation in DBTSS and genome of the B-box
containing segments of old (AluJ, AluS) and young (AluY) Alu
repeats and found that CpG sequence of the B-box of old Alu is
better conserved in DBTSS than in genome. This indicates that Bbox-
associated CpGs in promoters are better protected from
methylation and mutation than B-box-associated CpGs in genomic
SINEs. These results are consistent with the view that potential
TFIIIC binding motifs in SINEs associated with human and mouse
promoters may be functionally important. These motifs may protect
promoters from repressive histone modifications which spread from
adjacent sequences. This can potentially explain well known
clustering of SINEs in GC-rich gene rich genome compartments and
existence of unmethylated CpG islands.
Abstract: The interaction between respiration and low-frequency rhythms of the cardiovascular system is studied. The obtained results count in favor of the hypothesis that low-frequency rhythms in blood pressure and R-R intervals are generated in different central neural structures involved in the autonomic control of the cardiovascular systems.
Abstract: Motivated by the recent work of Herbert, Hayen, Macaskill and Walter [Interval estimation for the difference of two independent variances. Communications in Statistics, Simulation and Computation, 40: 744-758, 2011.], we investigate, in this paper, new confidence intervals for the difference between two normal population variances based on the generalized confidence interval of Weerahandi [Generalized Confidence Intervals. Journal of the American Statistical Association, 88(423): 899-905, 1993.] and the closed form method of variance estimation of Zou, Huo and Taleban [Simple confidence intervals for lognormal means and their differences with environmental applications. Environmetrics 20: 172-180, 2009]. Monte Carlo simulation results indicate that our proposed confidence intervals give a better coverage probability than that of the existing confidence interval. Also two new confidence intervals perform similarly based on their coverage probabilities and their average length widths.
Abstract: A block backward differentiation formula of uniform
order eight is proposed for solving first order stiff initial value
problems (IVPs). The conventional 8-step Backward Differentiation
Formula (BDF) and additional methods are obtained from the same
continuous scheme and assembled into a block matrix equation which
is applied to provide the solutions of IVPs on non-overlapping
intervals. The stability analysis of the method indicates that the
method is L0-stable. Numerical results obtained using the proposed
new block form show that it is attractive for solutions of stiff problems
and compares favourably with existing ones.