Search results for: cumulative probability.

Authors: U.A.A. Niroshika, Ravinda G.N. Meegama

Abstract:

Deformable active contours are widely used in computer vision and image processing applications for image segmentation, especially in biomedical image analysis. The active contour or “snake" deforms towards a target object by controlling the internal, image and constraint forces. However, if the contour initialized with a lesser number of control points, there is a high probability of surpassing the sharp corners of the object during deformation of the contour. In this paper, a new technique is proposed to construct the initial contour by incorporating prior knowledge of significant corners of the object detected using the Harris operator. This new reconstructed contour begins to deform, by attracting the snake towards the targeted object, without missing the corners. Experimental results with several synthetic images show the ability of the new technique to deal with sharp corners with a high accuracy than traditional methods.

Keywords: Active Contours, Image Segmentation, Harris Operator, Snakes

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Authors: F. Rahnamay Roodposhti, M. Falah Shams, H. Kordlouie

Abstract:

The aim of the article is extending and developing econometrics and network structure based methods which are able to distinguish price manipulation in Tehran stock exchange. The principal goal of the present study is to offer model for approximating price manipulation in Tehran stock exchange. In order to do so by applying separation method a sample consisting of 397 companies accepted at Tehran stock exchange were selected and information related to their price and volume of trades during years 2001 until 2009 were collected and then through performing runs test, skewness test and duration correlative test the selected companies were divided into 2 sets of manipulated and non manipulated companies. In the next stage by investigating cumulative return process and volume of trades in manipulated companies, the date of starting price manipulation was specified and in this way the logit model, artificial neural network, multiple discriminant analysis and by using information related to size of company, clarity of information, ratio of P/E and liquidity of stock one year prior price manipulation; a model for forecasting price manipulation of stocks of companies present in Tehran stock exchange were designed. At the end the power of forecasting models were studied by using data of test set. Whereas the power of forecasting logit model for test set was 92.1%, for artificial neural network was 94.1% and multi audit analysis model was 90.2%; therefore all of the 3 aforesaid models has high power to forecast price manipulation and there is no considerable difference among forecasting power of these 3 models.

Keywords: Price Manipulation, Liquidity, Size of Company, Floating Stock, Information Clarity

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Authors: Pa Pa Lin

Abstract:

This research work is concerned with the eigenvalue problem for the integral operators which are obtained by linearization of a nonlocal evolution equation. The purpose of section II.A is to describe the nature of the problem and the objective of the project. The problem is related to the “stable solution" of the evolution equation which is the so-called “instanton" that describe the interface between two stable phases. The analysis of the instanton and its asymptotic behavior are described in section II.C by imposing the Green function and making use of a probability kernel. As a result , a classical Theorem which is important for an instanton is proved. Section III devoted to a study of the integral operators related to interface dynamics which concern the analysis of the Cauchy problem for the evolution equation with initial data close to different phases and different regions of space.

Keywords: Evolution, Green function, instanton, integral operators.

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Authors: Phyu Phyu Mar, Khin Maung Latt

Abstract:

S-boxes (Substitution boxes) are keystones of modern symmetric cryptosystems (block ciphers, as well as stream ciphers). S-boxes bring nonlinearity to cryptosystems and strengthen their cryptographic security. They are used for confusion in data security An S-box satisfies the strict avalanche criterion (SAC), if and only if for any single input bit of the S-box, the inversion of it changes each output bit with probability one half. If a function (cryptographic transformation) is complete, then each output bit depends on all of the input bits. Thus, if it were possible to find the simplest Boolean expression for each output bit in terms of the input bits, each of these expressions would have to contain all of the input bits if the function is complete. From some important properties of S-box, the most interesting property SAC (Strict Avalanche Criterion) is presented and to analyze this property three analysis methods are proposed.

Keywords: S-boxes, cryptosystems, strict avalanche criterion, function, analysis methods.

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Authors: Yan Ma, ShunBao Li

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A new approach is adopted in this paper based on Turk and Pentland-s eigenface method. It was found that the probability density function of the distance between the projection vector of the input face image and the average projection vector of the subject in the face database, follows Rayleigh distribution. In order to decrease the false acceptance rate and increase the recognition rate, the input face image has been recognized using two thresholds including the acceptance threshold and the rejection threshold. We also find out that the value of two thresholds will be close to each other as number of trials increases. During the training, in order to reduce the number of trials, the projection vectors for each subject has been averaged. The recognition experiments using the proposed algorithm show that the recognition rate achieves to 92.875% whilst the average number of judgment is only 2.56 times.

Keywords: Eigenface, Face Recognition, Threshold, Rayleigh Distribution, Feature Extraction

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Authors: Afaf Alharbi, Qianni Zhang

Abstract:

The identification of malignant tissue in histopathological slides holds significant importance in both clinical settings and pathology research. This paper presents a methodology aimed at automatically categorizing cancerous tissue through the utilization of a multiple instance learning framework. This framework is specifically developed to acquire knowledge of the Bernoulli distribution of the bag label probability by employing neural networks. Furthermore, we put forward a neural network-based permutation-invariant aggregation operator, equivalent to attention mechanisms, which is applied to the multi-instance learning network. Through empirical evaluation on an openly available colon cancer histopathology dataset, we provide evidence that our approach surpasses various conventional deep learning methods.

Keywords: Attention Multiple Instance Learning, Multiple Instance Learning, transfer learning, histopathological slides, cancer tissue classification.

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Authors: M. A. Torkamani, S. Mahmoodzadeh, S. Pourroostaei, C. Lucas

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Daily production of information and importance of the sequence of produced data in forecasting future performance of market causes analysis of data behavior to become a problem of analyzing time series. But time series that are very complicated, usually are random and as a result their changes considered being unpredictable. While these series might be products of a deterministic dynamical and nonlinear process (chaotic) and as a result be predictable. Point of Chaotic theory view, complicated systems have only chaotically face and as a result they seem to be unregulated and random, but it is possible that they abide by a specified math formula. In this article, with regard to test of strange attractor and biggest Lyapunov exponent probability of chaos on several foreign exchange rates vs. IRR (Iranian Rial) has been investigated. Results show that data in this market have complex chaotic behavior with big degree of freedom.

Keywords: Chaos, Exchange Rate, Nonlinear Models.

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Authors: Karina Zaccari, Ernesto Cordeiro Marujo

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This paper presents a Machine Learning (ML) approach to support Meningitis diagnosis in patients at a children’s hospital in Sao Paulo, Brazil. The aim is to use ML techniques to reduce the use of invasive procedures, such as cerebrospinal fluid (CSF) collection, as much as possible. In this study, we focus on predicting the probability of Meningitis given the results of a blood and urine laboratory tests, together with the analysis of pain or other complaints from the patient. We tested a number of different ML algorithms, including: Adaptative Boosting (AdaBoost), Decision Tree, Gradient Boosting, K-Nearest Neighbors (KNN), Logistic Regression, Random Forest and Support Vector Machines (SVM). Decision Tree algorithm performed best, with 94.56% and 96.18% accuracy for training and testing data, respectively. These results represent a significant aid to doctors in diagnosing Meningitis as early as possible and in preventing expensive and painful procedures on some children.

Keywords: Machine learning, medical diagnosis, meningitis detection, gradient boosting.

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Authors: Ch.V.Rama Rao, Gowthami., Harsha., Rajkumar., M.B.Rama Murthy, K.Srinivasa Rao, K.AnithaSheela

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This paper presents a new method for estimating the nonstationary noise power spectral density given a noisy signal. The method is based on averaging the noisy speech power spectrum using time and frequency dependent smoothing factors. These factors are adjusted based on signal-presence probability in individual frequency bins. Signal presence is determined by computing the ratio of the noisy speech power spectrum to its local minimum, which is updated continuously by averaging past values of the noisy speech power spectra with a look-ahead factor. This method adapts very quickly to highly non-stationary noise environments. The proposed method achieves significant improvements over a system that uses voice activity detector (VAD) in noise estimation.

Keywords: Noise estimation, Non-stationary noise, Speechenhancement.

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Authors: B. Salmasian, A. Rabiee, T. Yousefzadeh

Abstract:

In this research, the risk assessment of radiation hazard for the Research Nuclear Reactor has been studied. In the current study, the MCNPx computational code has been used and coupled with a developed program using MATLAB software to evaluate Total Effective Dose Equivalent (TEDE) and cancer risk according to the BEIR equations for various human organs. In this study, the risk assessment of cancer has been calculated for ten years after exposure, in each of body organs of different ages and sexes. Also, the risk assessment of cancer has been calculated in each of body organs of different ages and sexes due to exposure after the retirement of the reactor staff. According to obtained results, a conservative whole-body dose rate, during a year, is 0.261 Sv and the probability the cancer risk for women is more than men and for children is more than adults. It has been shown that thyroid cancer was more possible than others.

Keywords: MCNPx code, BEIR equation, equivalent dose, risk analysis.

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Authors: Wararit Panichkitkosolkul

Abstract:

The unit root tests based on the robust estimator for the first-order autoregressive process are proposed and compared with the unit root tests based on the ordinary least squares (OLS) estimator. The percentiles of the null distributions of the unit root test are also reported. The empirical probabilities of Type I error and powers of the unit root tests are estimated via Monte Carlo simulation. Simulation results show that all unit root tests can control the probability of Type I error for all situations. The empirical power of the unit root tests based on the robust estimator are higher than the unit root tests based on the OLS estimator.

Keywords: Autoregressive, Ordinary least squares, Type I error, Power of the test, Monte Carlo simulation.

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Authors: Andrey V. Timofeev

Abstract:

This paper introduces an original method for guaranteed estimation of the accuracy for an ensemble of Lipschitz classifiers. The solution was obtained as a finite closed set of alternative hypotheses, which contains an object of classification with probability of not less than the specified value. Thus, the classification is represented by a set of hypothetical classes. In this case, the smaller the cardinality of the discrete set of hypothetical classes is, the higher is the classification accuracy. Experiments have shown that if cardinality of the classifiers ensemble is increased then the cardinality of this set of hypothetical classes is reduced. The problem of the guaranteed estimation of the accuracy for an ensemble of Lipschitz classifiers is relevant in multichannel classification of target events in C-OTDR monitoring systems. Results of suggested approach practical usage to accuracy control in C-OTDR monitoring systems are present.

Keywords: Lipschitz classifiers, confidence set, C-OTDR monitoring, classifiers accuracy, classifiers ensemble.

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Authors: Muhammad Sameer Ahmed, Piotr Remlein, Tansal Gucluoglu

Abstract:

The technique called as Generalized frequency division multiplexing (GFDM) used in the free space optical channel can be a good option for implementation free space optical communication systems. This technique has several strengths e.g. good spectral efficiency, low peak-to-average power ratio (PAPR), adaptability and low co-channel interference. In this paper, the impact of weather conditions such as haze, rain and fog on GFDM over the gamma-gamma channel model is discussed. A Trade off between link distance and system performance under intense weather conditions is also analysed. The symbol error probability (SEP) of GFDM over the gamma-gamma turbulence channel is derived and verified with the computer simulations.

Keywords: Free space optics, generalized frequency division multiplexing, weather conditions, gamma gamma distribution.

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Authors: Suparat Niwitpong

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.

Keywords: Confidence interval, generalized confidence interval, the closed form method of variance estimation, variance.

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Authors: Azam Bayat, Aref Khalkhali, Ali Reza Mahjoub

Abstract:

Healthy and viable herbal supplement were prepared from wheat by a green route. This organic biomaterial was named Nutrition Bio-shield Superfood (NBS). The NBS supplement had various vitamins, macro and micro molecules, and ingredients. In this study, 20 small Balb/C labile specimens were used in a weighing 30 ± 5 range. The samples were randomly divided into different groups, then the groups were divided into 5 groups. According to the results of this study, the mean number of white blood cells and neutrophil percentage in the experimental group receiving healthy and live dietary supplement showed a significant increase at the 5% probability level in all three groups received 50, 100 and 150 mg/ kg body weight of the mouse compared to the control group. In general, the dietary supplement increases the level of immunity.

Keywords: Healthy and live herbal supplement, biomaterial, immune system, enhancement.

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Authors: Eman S. El-Din, Hesham M. El-Badawy, Salwa H. Elramly

Abstract:

Whereas cellular wireless communication systems are subject to short-and long-term fading. The effect of wireless channel has largely been ignored in most of the teletraffic assessment researches. In this paper, a mathematical teletraffic model is proposed to estimate blocking and forced termination probabilities of cellular wireless networks as a result of teletraffic behavior as well as the outage of the propagation channel. To evaluate the proposed teletraffic model, gamma inter-arrival and general service time distributions have been considered based on wireless channel fading effect. The performance is evaluated and compared with the classical model. The proposed model is dedicated and investigated in different operational conditions. These conditions will consider not only the arrival rate process, but also, the different faded channels models.

Keywords: Cellular wireless networks, outage probability, traffic model, gamma inter-arrival distribution.

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Authors: Yi Zhang, Quan Zhou, Jun Li, Yanlang Hu

Abstract:

Scheduling algorithm is a key technology in satellite switching system with input-buffer. In this paper, a new scheduling algorithm and its realization are proposed. Based on Crossbar switching fabric, the algorithm adopts serial scheduling strategy and adjusts the output port arbitrating strategy for the better equity of every port. Consequently, it increases the matching probability. The algorithm can greatly reduce the scheduling delay and cell loss rate. The analysis and simulation results by OPNET show that the proposed algorithm has the better performance than others in average delay and cell loss rate, and has the equivalent complexity. On the basis of these results, the hardware realization and simulation based on FPGA are completed, which validate the feasibility of the new scheduling algorithm.

Keywords: Scheduling algorithm, input-buffer, serial scheduling, hardware design.

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Authors: Sh. A. Yousif, M. Bhave

Abstract:

There is strong evidence that water channel proteins 'aquaporins (AQPs)' are central components in plant-water relations as well as a number of other physiological parameters. We had previously reported the isolation of 24 plasma membrane intrinsic protein (PIP) type AQPs. However, the gene numbers in rice and the polyploid nature of bread wheat indicated a high probability of further genes in the latter. The present work focused on identification of further AQP isoforms in bread wheat. With the use of altered primer design, we identified five genes homologous, designated PIP1;5b, PIP2;9b, TaPIP2;2, TaPIP2;2a, TaPIP2;2b. Sequence alignments indicate PIP1;5b, PIP2;9b are likely to be homeologues of two previously reported genes while the other three are new genes and could be homeologs of each other. The results indicate further AQP diversity in wheat and the sequence data will enable physical mapping of these genes to identify their genomes as well as genetic to determine their association with any quantitative trait loci (QTLs) associated with plant-water relation such as salinity or drought tolerance.

Keywords: Aquaporins, homeologues, PIP, wheat

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Authors: Andre A. Keller

Abstract:

The optimal control is one of the possible controllers for a dynamic system, having a linear quadratic regulator and using the Pontryagin-s principle or the dynamic programming method . Stochastic disturbances may affect the coefficients (multiplicative disturbances) or the equations (additive disturbances), provided that the shocks are not too great . Nevertheless, this approach encounters difficulties when uncertainties are very important or when the probability calculus is of no help with very imprecise data. The fuzzy logic contributes to a pragmatic solution of such a problem since it operates on fuzzy numbers. A fuzzy controller acts as an artificial decision maker that operates in a closed-loop system in real time. This contribution seeks to explore the tracking problem and control of dynamic macroeconomic models using a fuzzy learning algorithm. A two inputs - single output (TISO) fuzzy model is applied to the linear fluctuation model of Phillips and to the nonlinear growth model of Goodwin.

Keywords: fuzzy control, macroeconomic model, multiplier - accelerator, nonlinear accelerator, stabilization policy.

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Authors: M. Farshbaf, M. R. Feizi-Derakhshi

Abstract:

Graph partitioning is a NP-hard problem with multiple conflicting objectives. The graph partitioning should minimize the inter-partition relationship while maximizing the intra-partition relationship. Furthermore, the partition load should be evenly distributed over the respective partitions. Therefore this is a multiobjective optimization problem (MOO). One of the approaches to MOO is Pareto optimization which has been used in this paper. The proposed methods of this paper used to improve the performance are injecting best solutions of previous runs into the first generation of next runs and also storing the non-dominated set of previous generations to combine with later generation's non-dominated set. These improvements prevent the GA from getting stuck in the local optima and increase the probability of finding more optimal solutions. Finally, a simulation research is carried out to investigate the effectiveness of the proposed algorithm. The simulation results confirm the effectiveness of the proposed method.

Keywords: Graph partitioning, Genetic algorithm, Multiobjective optimization, Pareto front.

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Authors: Peristera A. Baziana

Abstract:

The idea of the asynchronous transmission in wavelength division multiplexing (WDM) ring MANs is studied in this paper. Especially, we present an efficient access technique to coordinate the collisions-free transmission of the variable sizes of IP traffic in WDM ring core networks. Each node is equipped with a tunable transmitter and a tunable receiver. In this way, all the wavelengths are exploited for both transmission and reception. In order to evaluate the performance measures of average throughput, queuing delay and packet dropping probability at the buffers, a simulation model that assumes symmetric access rights among the nodes is developed based on Poisson statistics. Extensive numerical results show that the proposed protocol achieves apart from high bandwidth exploitation for a wide range of offered load, fairness of queuing delay and dropping events among the different packets size categories.

Keywords: Asynchronous transmission, collision avoidance, wavelength division multiplexing.

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Authors: Mohamad Mahdavi

Abstract:

Most of the real queuing systems include special properties and constraints, which can not be analyzed directly by using the results of solved classical queuing models. Lack of Markov chains features, unexponential patterns and service constraints, are the mentioned conditions. This paper represents an applied general algorithm for analysis and optimizing the queuing systems. The algorithm stages are described through a real case study. It is consisted of an almost completed non-Markov system with limited number of customers and capacities as well as lots of common exception of real queuing networks. Simulation is used for optimizing this system. So introduced stages over the following article include primary modeling, determining queuing system kinds, index defining, statistical analysis and goodness of fit test, validation of model and optimizing methods of system with simulation.

Keywords: Estimation, queuing system, simulation model, probability distribution, non-Markov chain.

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Authors: Rana Soltani-Zarrin, Sohrab Khanmohammadi

Abstract:

In this paper, a new method for multi criteria decision making is represented whichspecifies a trajectory satisfying desired criteria including minimization of time. A rescue robot is defined to perform certain tasks before the arrival of rescue team, including evaluation of the probability of explosion in the area, detecting human-beings, and providing preliminary aidsin case of identifying signs of life, so that the security of the surroundings will have enhanced significantly for the individuals inside the disaster zone as well as the rescue team. The main idea behind our technique is using the Program Evaluation and Review Technique analysis along with Critical Path Method and use the Multi Criteria Decision Making (MCDM) method to decidewhich set of activities must be performed first. Since the disastrous event in one area may be well contagious to others, it is one of the robot's priorities to evaluate the relative adversity of the situation, using the above methods and prioritize its mission.

Keywords: PERT, CPM, MCDM.

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Authors: Dalanya Asaad Mohammed, Dara Abdul Razaq

Abstract:

A total of twenty tensile biopsies were collected from children undergoing tonsillectomy from teaching hospital ENT department and Kurdistan private hospital in sulaimani city. All biopsies were homogenized and cultured; the obtained bacterial isolates were purified and identified by biochemical tests and VITEK 2 compact system. Among the twenty studied samples, only one Pseudomonas putida with probability of 99% was isolated. Antimicrobial susceptibility was carried out by disk diffusion method, Pseudomonas putida showed resistance to all antibiotics used except vancomycin. The isolate further subjected to PCR and DNA sequence analysis of blaVIM gene using different set of primers for different regions of VIM gene. The results were found to be PCR positive for the blaVIM gene. To determine the sequence of blaVIM gene, DNA sequencing performed. Sequence alignment of blaVIM gene with previously recorded blaVIM gene in NCBI- database showed that P. putida isolate have different blaVIM gene.

Keywords: Clinical isolates, Putida, Sulaimani, Vim gene.

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Authors: Lavkush Kumar Brahman, Ramesh Chandra

Abstract:

Experiments were carried out on the survival and growth of Rasbora daniconius, Puntius ticto and Puntius conchonius. The motivation of the study was to obtain information for growing the fish on a commercial scale for their use as biological control agents against mosquito larvae. The effects of temperature, total hardness, DO, pH and feed on the growth of fish were also investigated. Excessive value of total hardness was found because very rich calcium ion is present in Chitrakoot area. There was significant increases in growth rates of fish as temperature was increased from 28⁰C to 30⁰C. Further increases in temperature up to 32⁰C, did not further affect growth. The positive and highly significant correlations 0.991488, 0.9581 and 0.9935 were found between length and weight of P. ticto, P. conchonius and R. daniconius respectively. The regression was significant at 5% level of probability.

Keywords: Indigenous fish, DO, larvae, mosquito, pH, Temperature, total hardness.

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Authors: Rashid S S, Alam M Z, Karim M I A, Salleh, M H

Abstract:

A statistical optimization was studied to design a media composition to produce optimum cellulolytic enzyme where palm oil mill effluent (POME) as a basal medium and filamentous fungus, Trichoderma reesei RUT-C30 were used in the liquid state bioconversion(LSB). 2% (w/v) total suspended solid, TSS, of the POME supplemented with 1% (w/v) cellulose, 0.5%(w/v) peptone and 0.02% (v/v) Tween 80 was estimated to produce the optimum CMCase activity of 18.53 U/ml through the statistical analysis followed by the faced centered central composite design(FCCCD). The probability values of cellulose (<0.0011) and peptone (0.0021) indicated the significant effect on the production of cellulase with the determination coefficient (R2) of 0.995.

Keywords: Face centered central composite design (FCCCD), Liquid state bioconversion (LSB), Palm oil mill effluent, Trichoderma reesei RUT C-30.

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Authors: F. I. Belheouane, M. Bensaibi

Abstract:

The seismic feedback experiences in Algeria have shown higher percentage of damages for non-code conforming reinforced concrete (RC) buildings. Furthermore, the vulnerability of these buildings was further aggravated due to presence of many factors (e.g. weak the seismic capacity of these buildings, shorts columns, Pounding effect, etc.). Consequently Seismic risk assessments were carried out on populations of buildings to identify the buildings most likely to undergo losses during an earthquake. The results of such studies are important in the mitigation of losses under future seismic events as they allow strengthening intervention and disaster management plans to be drawn up. Within this paper, the state of the existing structures is assessed using "the vulnerability index" method. This method allows the classification of RC constructions taking into account both, structural and non structural parameters, considered to be ones of the main parameters governing the vulnerability of the structure. Based on seismic feedback from past earthquakes DPM (damage probability matrices) were developed too.

Keywords: Seismic vulnerability, Reinforced concrete buildings, Earthquake, DPM, Algeria.

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Authors: Maros Barabas, Michal Drozd, Petr Hanacek

Abstract:

A novel behavioral detection framework is proposed to detect zero day buffer overflow vulnerabilities (based on network behavioral signatures) using zero-day exploits, instead of the signature-based or anomaly-based detection solutions currently available for IDPS techniques. At first we present the detection model that uses shadow honeypot. Our system is used for the online processing of network attacks and generating a behavior detection profile. The detection profile represents the dataset of 112 types of metrics describing the exact behavior of malware in the network. In this paper we present the examples of generating behavioral signatures for two attacks – a buffer overflow exploit on FTP server and well known Conficker worm. We demonstrated the visualization of important aspects by showing the differences between valid behavior and the attacks. Based on these metrics we can detect attacks with a very high probability of success, the process of detection is however very expensive.

Keywords: behavioral signatures, metrics, network, security design

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Authors: R K Sinha

Abstract:

The statistical distributions are modeled in explaining nature of various types of data sets. Although these distributions are mostly uni-modal, it is quite common to see multiple modes in the observed distribution of the underlying variables, which make the precise modeling unrealistic. The observed data do not exhibit smoothness not necessarily due to randomness, but could also be due to non-randomness resulting in zigzag curves, oscillations, humps etc. The present paper argues that trigonometric functions, which have not been used in probability functions of distributions so far, have the potential to take care of this, if incorporated in the distribution appropriately. A simple distribution (named as, Sinoform Distribution), involving trigonometric functions, is illustrated in the paper with a data set. The importance of trigonometric functions is demonstrated in the paper, which have the characteristics to make statistical distributions exotic. It is possible to have multiple modes, oscillations and zigzag curves in the density, which could be suitable to explain the underlying nature of select data set.

Keywords: Exotic Statistical Distributions, Kurtosis, Mixture Distributions, Multi-modal

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Authors: Yanhua Jin, Won Suk Lee

Abstract:

The two-dimensional gel electrophoresis method (2-DE) is widely used in Proteomics to separate thousands of proteins in a sample. By comparing the protein expression levels of proteins in a normal sample with those in a diseased one, it is possible to identify a meaningful set of marker proteins for the targeted disease. The major shortcomings of this approach involve inherent noises and irregular geometric distortions of spots observed in 2-DE images. Various experimental conditions can be the major causes of these problems. In the protein analysis of samples, these problems eventually lead to incorrect conclusions. In order to minimize the influence of these problems, this paper proposes a partition based pair extension method that performs spot-matching on a set of gel images multiple times and segregates more reliable mapping results which can improve the accuracy of gel image analysis. The improved accuracy of the proposed method is analyzed through various experiments on real 2-DE images of human liver tissues.

Keywords: Proteomics, spot-matching, two-dimensionalelectrophoresis.

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