Hallmark professionalism in probabilistic analysis is to quantify the uncertainties involved in construction materials subject to intrinsic randomness in its physical and mechanical properties and is now gaining popularity in civil engineering arena. As well, knowledge of behaviour of materials is continuously evolving and its statistical descriptors are also changing when more and more data collected or even data updated and hence reliability analysis has to be carried out with the updated data as a continuous process. As per the committee report ACI 544.2R, it is found that there is no attempt made for probabilistic relation between cube compressive strength and cylinder compressive strength for fiber reinforced concrete. In consequence of this report, a robust relation between cube and cylinder of experimentally conducted compressive strength was established by Monte-Carlo simulation technique for different types of fibrous concrete like steel, alkali resistant glass and polyester fibrous concrete before and after thermoshock considering various uncertainties. Nevertheless simulated probabilistic modals, characteristic modals, optimized factor of safety and allowable designed cylinder compressive strength have been developed from the drawn probability of failure graph, which exhibits robust performance in realistic Civil Engineering materials and structures.
The objective of this paper is to present a probabilistic method of analyzing the combinations of snow and wind loads using meteorological data and to determine their combination factors. Calculations are based on data measured at twelve Polish meteorological stations operated by the Institute for Meteorology and Water Management. Data provided are from the years 1966 - 2010. Five combinations of snow load and 10-minute mean wind velocity pressure have been considered. Gumbel probability distribution has been used to fit the empirical distributions of the data. As a result, the interdependence between wind velocity pressure and snow load on the ground for a return period of 50 years has been provided, and the values of the combination factors for snow loads and wind actions are proposed.
The paper presents an analysis of the voicing of the phoneme /v/ in modern spoken Macedonian. The phoneme /v/ in the standard Macedonian language is classifi ed as a fricative, but some of its characteristics separate it from the other phonemes in this group. This is due to the fact that this phoneme was once a sonorant. In a part of the Macedonian dialects this phoneme is pronounced with marked voicing to this day. This phenomenon is then refl ected in the pronunciation of standard Macedonian. Our analysis is based on a selected corpus of examples that have been spoken by speakers from various dialect origins, in order to assess the any differences in pronouncing of the phoneme /v/ when placed in different phoneme contexts in the word.
The paper formulates some objections to the methods of evaluation of uncertainty in noise measurement which are presented in two standards: ISO 9612 (2009) and DIN 45641 (1990). In particular, it focuses on approximation of an equivalent sound level by a function which depends on the arithmetic average of sound levels. Depending on the nature of a random sample the exact value of the equivalent sound level may be significantly different from an approximate one, which might lead to erroneous estimation of the uncertainty of noise indicators. The article presents an analysis of this problem and the adequacy of the solution depending on the type of a random sample.
To reliably calibrate suitable partial safety factors, useful for the specification of global condition describing structural safety level in considered design case, usually the evaluation of adequate failure probability is necessary. In accidental fire situation, not only probability of the collapse of load-bearing structure, but also another probability related to the people staying in a building at the moment of fire occurence should be assessed. Those values are different one from another in qualitative sense but they are coupled because they are determined by similar factors. The first one is the conditional probability with the condition that fire has already occured, whereas the second is the probability of failure in case of a potential fire, which can take place in the examined building compartment, but its ignition has not yet appeared. An engineering approach to estimate such both probabilities is presented and widely discussed in the article.
In this paper we present the Bayesian model selection procedure within the class of cointegrated processes. In order to make inference about the cointegration space we use the class of Matrix Angular Central Gaussian distributions. To carry out posterior simulations we use an alorithm based on the collapsed Gibbs sampler. The presented methods are applied to the analysis of the price – wage mechanism in the Polish economy.
From the theory of reliability it follows that the greater the observational redundancy in a network, the higher is its level of internal reliability. However, taking into account physical nature of the measurement process one may notice that the planned additional observations may increase the number of potential gross errors in a network, not raising the internal reliability to the theoretically expected degree. Hence, it is necessary to set realistic limits for a sufficient number of observations in a network. An attempt to provide principles for finding such limits is undertaken in the present paper. An empirically obtained formula (Adamczewski 2003) called there the law of gross errors, determining the chances that a certain number of gross errors may occur in a network, was taken as a starting point in the analysis. With the aid of an auxiliary formula derived on the basis of the Gaussian law, the Adamczewski formula was modified to become an explicit function of the number of observations in a network. This made it possible to construct tools necessary for the analysis and finally, to formulate the guidelines for determining the upper-bounds for internal reliability indices. Since the Adamczewski formula was obtained for classical networks, the guidelines should be considered as an introductory proposal requiring verification with reference to modern measuring techniques.
This article investigates and evaluates a handover exchange scheme between two secondary users (SUs) moving in different directions across the handover region of neighboring cell in a cognitive radio network. More specifically, this investigation compares the performance of SUs in a cellular cognitive radio network with and without channel exchange scheme. The investigation shows reduced handover failure, blocking, forced and access probabilities respectively, for handover exchange scheme with buffer as compared to exchange scheme without buffer. It also shows transaction within two cognitive nodes within a network region. The system setup is evaluated through system simulation.
In the paper, the Hasofer-Lind index is applied for determining the probability of stability loss oftruss structure under random load. In 1974 Hasofer-Lind proposed a modified reliability index thatdid not exhibit the invariance problem. The “correction” is the evaluation the limit state functionat a point known as the “design point”, instead of the mean values. The design point is generallynot known a priori, an iteration technique must be used to find out the reliability index. The papershows how the reliability index changes under the influence of different variables mean value,standard deviation, and probability density function.
Despite various speech enhancement techniques have been developed for different applications, existing methods are limited in noisy environments with high ambient noise levels. Speech presence probability (SPP) estimation is a speech enhancement technique to reduce speech distortions, especially in low signalto-noise ratios (SNRs) scenario. In this paper, we propose a new two-dimensional (2D) Teager-energyoperators (TEOs) improved SPP estimator for speech enhancement in time-frequency (T-F) domain. Wavelet packet transform (WPT) as a multiband decomposition technique is used to concentrate the energy distribution of speech components. A minimum mean-square error (MMSE) estimator is obtained based on the generalized gamma distribution speech model in WPT domain. In addition, the speech samples corrupted by environment and occupational noises (i.e., machine shop, factory and station) at different input SNRs are used to validate the proposed algorithm. Results suggest that the proposed method achieves a significant enhancement on perceptual quality, compared with four conventional speech enhancement algorithms (i.e., MMSE-84, MMSE-04, Wiener-96, and BTW).
A novel non-orthogonal multiple access (NOMA) scheme is proposed to improve the throughput and the outage probability of the cognitive radio (CR) inspired system which has been implemented to adapt multiple services in the nextgeneration network (5G). In the proposed scheme, the primary source (PS) had sent a superposition code symbol with a predefined power allocation to relays, it decoded and forwarded (DF) a new superposition coded symbol to the destination with the other power allocation. By using a dual antenna at relays, it will be improved the bandwidth efficiency in such CR NOMA scheme. The performance of the system is evaluated based on the outage probability and the throughput with the assumption of the Rayleigh fading channels. According to the results obtained, it is shown that the outage probability and throughput of the proposed full-duplex (FD) in CR-NOMA with reasonable parameters can be able deploy in practical design as illustration in numerical results section.
In the present paper, we investigate a multi-server Erlang queueing system with heterogeneous servers, non-homogeneous customers and limited memory space. The arriving customers appear according to a stationary Poisson process and are additionally characterized by some random volume. The service time of the customer depends on his volume and the joint distribution function of the customer volume and his service time can be different for different servers. The total customers volume is limited by some constant value. For the analyzed model, steady-state distribution of number of customers present in the system and loss probability are calculated. An analysis of some special cases and some numerical examples are attached as well.
An embedded time interval data acquisition system (DAS) is developed for zero power reactor (ZPR) noise experiments. The system is capable of measuring the correlation or probability distribution of a random process. The design is totally implemented on a single Field Programmable Gate Array (FPGA). The architecture is tested on different FPGA platforms with different speed grades and hardware resources. Generic experimental values for time resolution and inter-event dead time of the system are 2.22 ns and 6.67 ns respectively. The DAS can record around 48-bit x 790 kS/s utilizing its built-in fast memory. The system can measure very long time intervals due to its 48-bit timing structure design. As the architecture can work on a typical FPGA, this is a low cost experimental tool and needs little time to be established. In addition, revisions are easily possible through its reprogramming capability. The performance of the system is checked and verified experimentally.
Together with the dynamic development of modern computer systems, the possibilities of applying refined methods of nonparametric estimation to control engineering tasks have grown just as fast. This broad and complex theme is presented in this paper for the case of estimation of density of a random variable distribution. Nonparametric methods allow here the useful characterization of probability distributions without arbitrary assumptions regarding their membership to a fixed class. Following an illustratory description of the fundamental procedures used to this end, results will be generalized and synthetically presented of research on the application of kernel estimators, dominant here, in problems of Bayes parameter estimation with asymmetrical polynomial loss function, as well as for fault detection in dynamical systems as objects of automatic control, in the scope of detection, diagnosis and prognosis of malfunctions. To this aim the basics of data analysis and exploration tasks - recognition of outliers, clustering and classification - solved using uniform mathematical apparatus based on the kernel estimators methodology were also investigated