Hybrid expert system of rough set and neural network

The combination of neural network and expert system can accelerate the process of inference, and then rapidly produce associated facts and consequences. However, neural network still has some problems such as providing explanation facilities, managing the architecture of network and accelerating the training time. Thus to address these issues we develop a new method for pre-processing based on rough set and merge it with neural network and expert system. The resulting system is a hybrid expert system model called a Hybrid Rough Neural Expert System (HRNES)

Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model

In a conventional competing risk s model, the time to failure of a particular experimental unit might be censored and the cause of failure can be known or unknown. In this thesis the analysis of this particular model was based on the cause-specific hazard of Cox model. The Expectation Maximization (EM) was considered to obtain the estimate of the parameters. These estimates were then compared to the Newton-Raphson iteration method. A generated data where the failure times were taken as exponentially distributed was used to further compare these two methods of estimation. From the simulation study for this particular case, we can conclude that the EM algorithm proved to be more superior in terms of mean value of parameter estimates, bias and root mean square error. To detect irregularities and peculiarities in the data set, the residuals, Cook distance and the likelihood distance were computed. Unlike the residuals, the perturbation method of Cook's distance and the likelihood distance were effective in the detection of observations that have influenced on the parameter estimates. We considered both the EM approach and the ordinary maximum likelihood estimation (MLE) approach in the computation of the influence measurements. For the ultimate results of influence measurements we utilized the approach of the one step . The EM one-step and the maximum likelihood (ML) one-step gave conclusions that are analogous to the full iteration distance measurements. In comparison, it was found that EM one-step gave better results than the ML one step with respect to the value of Cook's distance and likelihood distance. It was also found that Cook's distance i s better than the likelihood distance with respect to the number of observations detected

Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis

The work in this thesis is concerned with the development of techniques for the assessment of statistical process control in data that include censored observations. Various regression models with censored data are presented and we concentrate on four competing risks models namely, two parametric Cox’s model that is, Cox’s with Weibull distribution, Cox’s with exponential distribution and two semiparametric Cox’s model with subdistribution function that is, the weighted score function (W) and censoring complete (CC). The Expectation Maximization (EM) algorithm is utilized to obtain the estimate of the parameters in the models. A generated data where the failure times are taken as exponentially distributed are used to further compare these two parametric models. From the simulation study for this particular case, we can conclude that Weibull distribution describes well the nature of the model concerned as compared to the exponential distribution in terms of the mean value of parameter estimates, bias, and the root means square error. Plots of survival distribution function against failure time are used to examine the predicted survival patterns for the two types of failures. In this thesis we develop a modified Fine and Gray methods to increase the sensitivity of the models and these methods are tested and compared. A simulation data using subdistribution function for the two types of failure are carried out to compare the performance of the modified model. The results of the study indicate the models show better result compared to Fine and Gray models. However, the weighted score function (W) shows better result compared to the censored complete data (CC). Residual-based approaches are used to assess the validity of the two models (MW, CC) assumptions. Plots of this residual against failure time are used to investigate whether important explanatory variables have been omitted from the model. The study also carries out an investigation of the causes of failure for statistical process control. The x chart, R chart and Cp, and Cpk are examined for the possibility of being used to detect the state of control of the covariates in the two competing risks models (Cox’s with Weibull distribution (PHW2) and modification of weighted score function (MW)). The result of this study indicates that both models are successful in investigating the causes of failure for statistical process control. However, the results from the real data sets which involves the measurement of stress against three covariates (aluminum, wood and plastic) showed that the tubes wrapped on plastic mandrel have excellent crashworthiness performance with respect to the x chart, R chart, Cp, and Cpk

Competing risks for reliability analysis using Cox’s model

Purpose – Cox’s model with Weibull distribution and Cox’s with exponential distribution are the most important models in reliability analysis. This paper seeks to show that, with a large sample size based on expectation maximization (EM) algorithm, both models give similar results. Design/methodology/approach – The parameters of the models have been estimated by method of maximum likelihood based on EM algorithm. The objective of this analysis is to fit the modification of Cox’s model with Weibull distribution and Cox’s with exponential distribution, examine its performance and compare their results with Crowder et al. Findings – A simulation study indicates that the parametric Cox’s model with Weibull distribution gives similar results to Cox’s with exponential distribution, especially for a large sample size. Also, the modification of the two models showed better results compared with Crowder et al., especially for the second causes of failure. Originality/value – A modification of the two competing risk models has mostly been applied in failure time data and simulation data. The results of the simulation study indicate that the Weibull and exponential are suitable for Cox’s model as they are easy to use and it can achieve even higher accuracy compared with other distribution models

Shrinkage of Plastic Raw Materials (A Comparative Study of Mould)

In plastic engineering, the mould design is considered a complex process or an art, due to the polymers used their differences and changes in properties, as well as other factors like shrinkage of the materials. An Important point in mould design considerations is to use real and actual values of shrinkage in the early stages of design to avoid any design errors and produce an economic template. Some containers produced locally leaks the liquids, which causes inconveniences for the users. This problem is attributed to unspecified data of raw material shrinkage. In this work, five samples made of polypropylene PP113 bought from the local market (Khartoum petrochemical company), and another five samples made of low-density polyethylene (LDPE), produced by SABIC of Saudi Arabia were moulded using ISO 294 test mould of dimension 60x60x2mm. The shrinkage for the test samples was measured according to test specifications. The averages shrinkage for samples made of PP113 was found to be 1.88, and that for LDPE was found to be 0.84. The experimental results were compared to a simulation results obtained using Visi-12.2, and MoldFlow-Mpi Ver. 5.1 software, which often used for studying and analyzing the behavior of plastic materials in moulds cavities. For Visi-12.2 software, the longitudinal shrinkage was found to amount of 1.25, for PP113 material, and 2.50 for LDPE material. For MoldFlow- Mpi Ver. 5.1 software, the longitudinal shrinkage was found to be 1.003 for PP113 material, and 2.21 for LDPE material. The study concluded that, there is a notable difference between the values of shrinkage obtained practically and that built in the software’s libraries, and thus for precision parts practical shrinkage tests are inevitable

Training the next generation of Sudanese immunologists: a case for mentorship

Lack of well-trained Sudanese immunologists hampers the ability of next generation of Sudanese students to get quality immunology training. By narrating my personal story, I highlight the challenges faced by students at home and argue for the importance of mentorship in helping them realize their dreams

Adaptation Conflicts of Heterogeneous Devices in Iot Smart-Home

A promising technology such as Internet-of-Things have been introduced into traditional homes, buildings and cities to become smart and offer a wide range of services to simplify and enhance people’s lifestyle, a complex rule structure with a large number of sensing and actuating devices increases the chances of creating rules with faulty behaviors. Detection of sophisticated conflicts in an IoT system is one example of such faulty systems. In this paper, a mechanism is presented to detect such sophisticated conflicts among multi-resident smart-home services. Formally a model considering the functional properties of devices to distinguish a specific new kind of conflicts among the other basic types. Service User Regularity (SUR) conflict detection algorithm is proposed to trace resident habitual usage and behaviour conflicts and regulate them within the rules of the smart-home IoT-system. The system achieved good result; it could detect a reasonable number of targeted type conflicts within a synthesized data set

Genitourinary syndrome of menopause exploring the history, updates and treatment

The biological factors and physiological functions fundamental to the female anatomy delineate the complexity of reproductive phenomenon in this population. When women experience menopausal transition, genital, sexual, and urinary signs and symptoms materialize often. These longstanding signs and symptoms, presently referred to as the genitourinary syndrome (GUS) of menopause, a relatively new term, impact their quality of life and sexual health with the emergence of vulvovaginal and urogenital atrophy, typical of irritation, soreness, dryness, dyspareunia, and itching. Despite its prevalence, GUS of menopause often goes unreported due to embarrassment, leading to underdiagnoses, diminished intervention, and under-treatment. Moreover, the rising life expectancy is also emerging as a contributing factor to the increasing prevalence of GUS of menopause, directly affecting women's health. While there are notable awareness, education, and healthcare frameworks in place aimed at addressing the unique needs of menopausal women, there is a need to explore further GUS’ prevalence, pathophysiology, risk factors, clinical features, diagnosis, and treatment to understand, diagnose, and effectively manage this condition

Adenosine-5′-phosphosulfate - a multifaceted modulator of bifunctional 3′-phospho-adenosine-5′-phosphosulfate synthases and related enzymes

All sulfation reactions rely on active sulfate in the form of 3′-phosphoadenosine-5′-phosphosulfate (PAPS). In fungi, bacteria, and plants, the enzymes responsible for PAPS synthesis, ATP sulfurylase and adenosine-5′-phosphosulfate (APS) kinase, reside on separate polypeptide chains. In metazoans, however, bifunctional PAPS synthases catalyze the consecutive steps of sulfate activation by converting sulfate to PAPS via the intermediate APS. This intricate molecule and the related nucleotides PAPS and 3′-phospho-adenosine-5′-phosphate modulate the function of various enzymes from sulfation pathways, and these effects are summarized in this review. On the ATP sulfurylase domain that initially produces APS from sulfate and ATP, APS acts as a potent product inhibitor, being competitive with both ATP and sulfate. For the APS kinase domain that phosphorylates APS to PAPS, APS is an uncompetitive substrate inhibitor that can bind both at the ATP/ADP binding site and the PAPS/APS-binding site. For human PAPS synthase 1, the steady-state concentration of APS has been modelled to be 1.6 lM, but this may increase up to 60 lM under conditions of sulfate excess. It is noteworthy that the APS concentration for maximal APS kinase activity is 15 lM. Finally, we recognized APS as a highly specific stabilizer of bifunctional PAPS synthases. APS most likely stabilizes the APS kinase part of these proteins by forming a dead-end enzyme–ADP–APS complex at APS concentrations between 0.5 and 5 lM; at higher concentrations, APS may bind to the catalytic centers of ATP sulfurylase. Based on the assumption that cellular concentrations of APS fluctuate within this range, APS can therefore be regarded as a key modulator of PAPS synthase functions

Automation of Database Normalization Process.

As the volume of information available on the internet and corporate internet continues to increase, there is growing interest in helping people better organize and manage all this database resources. Database normalization is one of the techniques that can be applied to manage and organize the database. This project looks to enhance this technique by automating this process. The aim of this project is to minimize the times of manual database normalization process, which can improve the performance of the database's developer