In agricultural domain research, image processing and machine learning techniques play an important role. This paper provides a unique solution for classifying the good defective arecanuts based on their color, texture, density value. market different varieties of arecanut are available. Usually, qualitative sorting is done manually, this can be replaced by applying vision to grade arecanut. Cl...

Wireless communication systems play a very crucial role in modern society for entertainment, business, commercial, health and safety applications. These keep evolving from one generation to next currently we are seeing deployment of fifth (5G) wireless around the world. Academics industries already discussing beyond 5G which will be sixth (6G) evolution. One main key components 6G use Artificia...

Software project management is one of the significant activates in the software development process. Software Development Effort Estimation (SDEE) is a challenging task in the software project management. SDEE is an old activity in computer industry from 1940s and has been reviewed several times. A SDEE model is appropriate if it provides the accuracy and confidence simultaneously before softwa...

Stock market forecasting has attracted so many researchers and investors that ‎many studies have been done in this field. These studies have led to the ‎development of many predictive methods, the most widely used of which are ‎machine learning-based methods. In machine learning-based methods, loss ‎function has a key role in determining the model weights. In this study a new loss ‎function is ...

Fault diagnosis has always been an essential aspect of control system design. This is necessary due to the growing demand for increased performance and safety of industrial systems is discussed. Support vector machine classifier is a new technique based on statistical learning theory and is designed to reduce structural bias. Support vector machine classification in many applications in v...

In this work, we evaluate a number of machine learning techniques for the purpose of ranking answers to why-questions. We use a set of 37 linguistically motivated features that characterize questions and answers. We experiment with a number of machine learning techniques in various settings. The purpose of the experiments is to assess how the different machine learning techniques can cope with ...

Machine learning techniques can be used to analyse data from different perspectives and enable developers to retrieve useful information. Machine learning techniques are proven to be useful in terms of software bug prediction. In this paper, a comparative performance analysis of different machine learning techniques is explored for software bug prediction on public available data sets. Results ...