Reliability estimation for the randomly censored pareto distribution

Widespread applications of random censoring in life testing experiments to estimate reliability of engineering products or systems are avialable. Different parametric statistical models such as exponential, Rayleigh, Weibull and Maxwell distributions are used under random censoring scheme. In this paper, random censoring under Pareto distribution is considered. The maximum likelihood estimators (MLE’s) of the model parameters and survival function were derived along with Fisher information matrix and asymptotic confidence intervals. A simulation study was performed to observe the behavior of the MLE’s. The simulation results showed that the bias and MSE were reasonably small in all cases

A Fuzzy Approach for Feature Evaluation and Dimensionality Reduction to Improve the Quality of Web Usage Mining Results

The explosive growth in the information available on the Web has necessitated the need for developing Web personalization systems that understand user preferences to dynamically serve customized content to individual users. Web server access logs contain substantial data about the accesses of users to a Web site. Hence, if properly exploited, the log data can reveal useful information about the navigational behaviour of users in a site. In order to reveal the information about user preferences from, Web Usage Mining is being performed. Web Usage Mining is the application of data mining techniques to web usage log repositories in order to discover the usage patterns that can be used to analyze the user’s navigational behavior. WUM contains three main steps: preprocessing, knowledge extraction and results analysis. During the preprocessing stage, raw web log data is transformed into a set of user profiles. Each user profile captures a set of URLs representing a user session. Clustering can be applied to this sessionized data in order to capture similar interests and trends among users’ navigational patterns. Since the sessionized data may contain thousands of user sessions and each user session may consist of hundreds of URL accesses, dimensionality reduction is achieved by eliminating the low support URLs. Very small sessions are also removed in order to filter out the noise from the data. But direct elimination of low support URLs and small sized sessions may results in loss of a significant amount of information especially when the count of low support URLs and small sessions is large. We propose a fuzzy solution to deal with this problem by assigning weights to URLs and user sessions based on a fuzzy membership function. After assigning the weights we apply a "Fuzzy c-Mean Clustering" algorithm to discover the clusters of user profiles. In this paper, we describe our fuzzy set theoretic approach to perform feature selection (or dimensionality reduction) and session weight assignment. Finally we compare our soft computing based approach of dimensionality reduction with the traditional approach of direct elimination of small sessions and low support count URLs. Our results show that fuzzy feature evaluation and dimensionality  reduction results in better performance and validity indices for the discovered clusters

Simulation Analysis of a Power System Protection using Artificial Neural Network

There has been significant development in the area of neural network based power system protection in the previous decade. Neural network technology has been applied for various protective relaying functions including distance protection. The aim of this Paper is to develop a software module acting as a protective relay using neural network techniques. The Artificial Neural Network (ANN) software developed module employs the back-propagation method to recognize the waveform patterns of impedance in a transmission line. The input waveforms are generated using PSCAD. The generated waveforms then are used as training and testing data for the ANN software. The ANN software is simulated using the Neural Network Toolbox. The design has been tested for different fault conditions including different fault resistances and fault inception angles. The test results show that the relay is able to detect faults in lesser time as compared to conventional relay algorithms.DOI:http://dx.doi.org/10.11591/ijece.v3i1.193

Assessment of the Effect of two Different Digital Fabrication Techniques on Marginal and Internal Fit of Interim Fixed Dental Prothesis

Aim: The aim of that study was to evaluate the marginal and internal fit of a 3-unit, and 6-unit interim fixed dental prosthesis manufactured through milling and 3D printing technologies. Materials and Methods: Forty-eight interim fixed dental prostheses (FDP) were equally divided into two groups according to the fabrication technique. In group (MT), specimens were fabricated through milling technology while in group (PT), specimens were obtained by 3D printing. Each group was subdivided equally according to the FDP span length into 3-unit FDP (SFDP), and 6-unit FDP (LFDP). Marginal and internal fit were measured through the superimposition of the digital master model data and data of the fitting surfaces of the milled and printed FDPs using the “best-fit” alignment feature of a 3D evaluation superimposition software. The Mann-Whitney U test was used to compare the two fabrication techniques as well as the two span lengths. The significance level was set at P \u3c 0.05. Results: Results showed that 3D printing showed statistically significantly higher overall marginal gap distance (MGD) than the milling technique for the (SFDP) subgroup while milling showed higher overall (MGD) values than 3D printing for the (LFDP) subgroup. For internal fit, 3D printing showed lower overall internal gap distance values than milling. Conclusions: Milling technology was able to produce restorations with better marginal fit compared to 3D printing only in 3-unit FDPs. However, the opposite was true when the internal fit of the restorations was considered where 3D printing surpassed the milling technique in both the short-span and long-span FDPs. Consequently, 3D printing could be the technique of preference for fabricating provisional restorations especially when it comes to complex long span FDPs

Immune boosting and anti-influenza effects of an Unani decoction in influenza like illness and COVID-19 like epidemics: a rationale approach

The Unani system of medicine is one of the traditional systems of medicine practised since centuries in many parts of the world including India. At a time when the coronavirus disease 2019 (COVID-19) pandemic is still raging across the globe and there is still no appreciable satisfactory management available with vaccination being the only panacea in the near future, unani medicine chiefly composed of herbal drugs is replete with many classical references for the management of influenza like illness and COVID-19 like epidemics. In Unani medicine, nazla-i-wabāi is referred as influenza for which a decoction containing Behidana (Cydonia oblonga), Unnab (Ziziphus jujuba) and Sapistan (Cordia myxa) are recommended to relieve the clinical features of nazla-i-wabāi and other COVID-19 like epidemics. All the three ingredients of this formulation are also individually used for the treatment of sore throat, cough, septicaemia, fever, dyspnoea, pharyngitis, chest pain etc. Certain scientific studies have validated various pharmacological actions of these drugs as claimed by unani physicians. A concerted rational approach has been attempted to highlight the effect of the unani decoction as to its immune boosting property both as prophylactic and therapeutic use in the treatment of influenza like illness and COVID-19 like epidemics in the light of ancient Unani classics and recent scientific studies

Abaqus Simulation of the Fire's Impact on Reinforced Concrete Bubble Deck Slabs

The use of Bubble Deck in modern prefabricated construction methods has recently become widespread in industrial projects worldwide. In the middle of a typical slab, Bubble Deck places hollow plastic balls that do not improve structural performance but significantly reduce structural weight. This study analyzes the behavior of self-uniting bidirectional concrete slabs with plastic spherical voids under high temperatures and for different periods. Six simply supported bidirectional plates, five of which contained bubbles and one solid, were numerically tested using the finite element method and the commercial ABAQUS software to investigate the behavior of bidirectional plates fired at various temperatures and for various amounts of time. Each slab has the following measurements: (1500*1500*150) mm. These slabs were fired at different temperatures (600 and 800) °C and for different periods (one and two hours). The slabs were classified into four groups depending on the kind of slab (solid or bubble), the degree of burning (600 and 800) °C, and the duration of the burning (one and two hours). The loading strength of concrete was found to be up to 65% less than the maximum capacity of a slab that was bubbled and fired at high temperatures. The length of the firing time also had a significant effect on reducing the strength of the concrete. The longer the firing period, the lower the load resistance of the concrete. The ball would melt and scorch in an intense, protracted fire without noticeable effects. The ability of the steel to maintain adequate strength during a fire, when it will be burned and lose significant strength as the temperature rises, determines the slab’s ability to withstand fire. Bubble deck slabs produce between 17% and 39% stronger thermal resistance than an equivalent solid slab of the same depth, even though they are not intended to provide thermal insulation due to the encapsulation of the air bubbles within the center of the concrete slab