CLASSIFICATION AND ANALYSIS OF BLOOD PRESSURE CHARACTERISTICS USING FUZZY LOGIC APPROACH

The idea of Fuzzy Expert System (FES) used in this research work is proposed to assist the medical experts to make right diagnosis for patients that are suffering from hypertension. The only sure way to monitor high blood pressure is through regular checkups. Majority of the researchers that have worked in this field only focused on using fuzzy expert system for classification of hypertension data, while few of them dealt with data analysis. This research work further checked for the efficacy of medication on the patients and the exact time the effect began to have impact on the patients using secondary data collected from questionnaire. It was gathered from the sampled respondents that the antihypertensive medication (Dieuretic) has been reliable in the treatment of hypertension.

EXPERT SYSTEM FOR REFRIGERATION UNIT DIAGNOSIS

Functional diagram of the compression refrigeration unit is considered. Facts and classic pro-duction rules for the knowledgebase are compiled. The expert system for this electrical equip-ment functional diagram diagnosis is realized.

TECHNOLOGIES OF EXPERT SYSTEMSCONSTRUCTION FOR ELECTRIC POWER

The technologies of construction diagnostic expert systems is considered. The strategy of the knowledge base structuring by diagnostic expert system is described

Using parallel pre-trained types of DCNN model to predict breast cancer with color normalization

Objective Breast cancer is the most common among women, and it causes many deaths every year. Early diagnosis increases the chance of cure through treatment. The traditional manual diagnosis requires effort and time from pathological experts, as it needs a joint experience of a number of pathologists. Diagnostic mistakes can lead to catastrophic results and endanger the lives of patients. The presence of an expert system that is able to specify whether the examined tissue is healthy or not, thus improves the quality of diagnosis and saves the time of experts. In this paper, a model capable of classifying breast cancer anatomy by making use of a pre-trained DCNN has been proposed. To build this model, first of all the image should be color stained by using Vahadane algorithm, then the model which combines three pre-trained DCNN (Xception, NASNet and Inceptoin_Resnet_V2) should be built in parallel, then the three branches should be aggregated to take advantage of each other. The suggested model was tested under different values of threshold ratios and also compared with other models. Results The proposed model on the BreaKHis dataset achieved 98% accuracy, which is better than the accuracy of other models used in this field.

Subjectivity reducing in software version criticality classification with the support of an expert system

In the software version release management process, there is a need, on the part of human specialists, to classify the criticality of each software version. However, the subjectivity of this classification may be present according to the experience acquired by specialists over the years. To reduce subjectivity in the process, an Artificial Intelligence technique called Expert System (ES) can be applied to represent the knowledge of human specialists and use it in problem solving. Thus, the aim of this paper was to reduce the subjectivity in the criticality classification of the software version with the support of the Expert System. To this end, a questionnaire was developed with the objective of obtaining the criticality opinions classified as High, Medium and Low in each specialist's software version to assist in the preparation of the ES production rules. ES generated 17 production rules with a 100% confidence level applied to a production database. The results of the classification carried out by the ES corresponded to the classification carried out by the specialists in the production base, that is, the ES was able to represent their knowledge. Then, another questionnaire was applied to the specialists to verify the perception of satisfaction regarding the use of the ES with a result obtained of 4.8, considered satisfactory. It was concluded, then, that the ES supported the reduction of subjectivity in the classification of the criticality of software version.

An Expert System-Based Automation in Indian Traction System for a One Way Single Platform Station by Introducing PLC

Nowadays, it is very often that some portion of the Indian traction system is still suffering from a single line railway transportation. This in turn creates a havoc disturbance in maintaining the proper sequence of traction control system. Also, passengers are taking risk to catch the train which is already in motion but no such action has been taken to eliminate these consequences. It has been found that more or less various works have been done on Automation in Railway Crossing Gate using Microcontroller and IR Sensor. Thus, it is often decided to develop an idea for the Indian traction system to ensure better controlling action by introducing Limit Switches as Tactile Sensors and by introducing HMI using PLC. The purpose here to take control over various controlling domains, including Railway crossing gate are as follows: Track signal, crossing level signal, alarm notification, and platform edge fence. The proper sequencing needs to be operated via a 128 I/O module with 2 KB memory size small PLC kit.