Data classification is one of the investment research areas in the field of data mining. Machine learning algorithms such as naive bayes, neural network, and support vector machine are most regularly used for performing the classification task. Supervised learning is one of its kinds where the datasets consist of class labels and the machine learning classifier are trained first using that. It ...

In this paper we study experimentally four remedies to overcome inefficiencies that arise from the incompleteness of contracts. These remedies are reciprocity, repeated game effects, social embeddedness, and incentive contracts. In our baseline treatment we find that reciprocity is a powerful contract enforcement device. A second experiment establishes that repeated game effects interact with r...

Evaluation and prediction of performance of diamond wire saw is one of the most important factors involved in planning the dimension stone quarries. The wear rate of diamond wire saw can be investigated as a major criterion to evaluate its performance. The wear rate of diamond wire saw depends upon non-controlled parameters related to rock characteristics and controlled parameters related to ch...

Computational expressive music performance studies the analysis and characterisation of the deviations that a musician introduces when performing a musical piece. It has been studied in a classical context where timing and dynamic deviations are modeled using machine learning techniques. In jazz music, work has been done previously on the study of ornament prediction in guitar performance, as w...

We consider the machine-supported verification of a code generator computing machine code from WHILE-programs, i.e. abstract syntax trees which may be obtained by a parser from programs of an imperative programming language. We motivate the representation of states developed for the verification, which is crucial for success, as the interpretation of tree-structured WHILE-programs differs signi...

In this project, we applied two machine learning techniques: CNN (Convolutional Neural Network) and SVM (Support Vector machine) to build an image aesthetic evaluating system. And we have achieved an 5-folder cross validation accuracy of above 99% by using CNN implemented in Torch. In the ‘Introduction’ section, a brief background of the problem and an introduction of our system are given. In t...

Tweet sentiment analysis has been an effective and valuable technique in the sentiment analysis domain. As the most widely used approach for tweet sentiment analysis, machine learning algorithms work well on the sentiment classification, just as they have been successfully applied for many other purposes. In this thesis, we conduct a systematic and thorough empirical study on the machine learni...

Unlike the existing views that was introduced the existence of delay caused by the transmission of wide area measurement system data (WAMS) into the controllers input of the power oscilation damping (POD) by communication networks as a reason for poor performance of the POD controllers. This paper shows that the presence of time delay in the feedback loop may improve the performance of a POD co...

This paper discusses the initial efforts to implement simulation modeling as a visual management and analysis tool at an automotive foundry plant manufacturing engine blocks. The foundry process was modeled using Pro Model to identify bottlenecks and evaluate machine performance, cycle times and production data (total parts, rejects, throughput, products/hr) essential for efficient production c...