Identification of transfer function to model brush temperature of a small DC machine at no-load

Using temperature measurement to provide insight into the health condition of an electrical machine at any operating point could be possible if a baseline temperature of the machine could be modelled in real-time and compared to the actual current temperature. In this study, transfer functions are being identified to be used as a baseline temperature response model for a small DC machine. As a preliminary study, the transfer functions are identified using experimental data of temperature responses at several no-load speed step inputs. The order of transfer function tested was between a range from 0 to 4. The third order transfer function was found to be the best followed by the first order transfer function with a model MSE error of less than 0.41 and 0.65 respectively. The slight variation on the poles of the system indicates that the thermal system of the electrical machine does not obey exactly the LTI hypothesis

Features extraction of capsicum frutescens (C.F) NDVI values using image processing

There is yet an application for monitoring plant condition using the Normalized Difference Vegetation Index (NDVI) method for Capsicum Frutescens (C.F) or chili. This study was carried out in three phases, where the first and second phases are to create NDVI images and recognize and extract features from NDVI images. The last stage is to assess the efficiency of Neural Network (N.N.), Naïve Bayes (N.B.), and Logistic Regression (L.R.) models on the classification of chili plant health. The images of the chili plant will be captured using two types of cameras, which can be differentiated by whether or not they have an infrared filter. The images were collected to create datasets, and the NDVI images' features were extracted. The 120 NDVI images of the chili plant were divided into training and test datasets, with 70.0% training and 30.0% test. The extracted data was used to test the classification accuracy of classifiers on datasets. Finally, the N.N. model was found to have the highest classification accuracy, with 96.4 % on the training dataset and 88.9 % on the test dataset. The state of the chili plant can be predicted based on feature extraction from NDVI images by the end of the study

Classification of plant health (capsicum frutescens) normalize differences vegetation index using image processing

The evolution of food manufacturer in global contribute in national income of the country. Agriculture has been a part of everyone’s life which result in providing food become the building block of every human being. Malaysia is only country experiencing deteriorating development contribute (25.9%) agriculture in Gross Deficient Domestics Product (GDP) while others are fishing (12%), rubber (3.0%) and forestry & logging (6.3%), livestock (15.3%). In line with the development of technology in present century, a lot of methods and technique introduced to upgrowth agriculture sector by focusing to the plant health. The aims of this study are to classify of agriculture plant health through NDVI using image processing. Image processing is a technique representing operations and observation on an image. The images of plant will be captured in this investigation to obtain a photo without (Infra-Red) IR imaging filter. Some of steps must be perform which also include of using multi-function software to gain NDVI values of plant. The main objective in this study is to classify plant health by performing the vegetation index of plant and identify the best machine learning to be applied

A comparative evaluation of state-of-the-art web service composition testing approaches

More and more Web based systems are being developed by composing other single or even composite services. This is due to the fact that not all available services are able to satisfy the needs of a user. The process of composing Web services involves discovering the appropriate services, selecting the best services, combining those services together, and finally executing them. Although much research efforts have been dedicated to the discovery, selection, and composition of services, the process of testing the Web service composition has not been given the same attention. This paper discusses the importance of Web services composition testing, provides a classification of the most prominent approaches in that area, presents several criteria for comparison of those approaches, and conducts a comparative evaluation of the approaches. The results of the paper give an essential perspective to do research work on Web services composition testing

Pengaturcaraan COBOL Berstruktur

Bahasa COBOL merupakan salah satu bahasa komputer yang popular dan digunakan secara meluas. Keistimewaan bahasa COBOL dari segi penggunaannya yang mudah, bahasa yang berstruktur dan sesuai dengan pelbagai bidang terutamanya bidang perniagaan menjadikannya unik berbanding dengan bahasa-bahasa lain. Sintaksnya yang ramah guna dan kemudahan sistem sokongan COBOL yang luas menjadikan penggunaannya dominan di organisasi-organisasi kerajaan mahupun swasta. Buku ini dihasilkan atas kesedaran dan keperluan para pensyarah serta pelajar sains komputer, Fakulti Sains Komputer Dan Sistem Maklumat, UTM. Ia merupakan pengumpulan nota-nota pensyarah yang telah diteliti dengan contoh-contoh yang telah dipermudahkan serta mendapat maklum balas yang baik daripada para pelajar. Isi kandungan buku ini diasaskan kepada reka bentuk dan pengaturcaraan COBOL berstruktur. Pelajar didedahkan kepada dua persekitaran iaitu persekitaran PC dan persekitaran kerangka utama IBM. Dengan lain perkataan, pelajar dapat menguasai cara bagaimana mengkompil dan melaksanakan atur cara COBOL pada kedua-dua persekitaran tersebut. Buku ini disesuaikan kepada pelajar tahun satu universiti atau orang perseorangan yang ingin mempelajari bahasa COBOL dengan baik