We explore how to improve machine translation systems by adding more translation data in situations where we already have substantial resources. The main challenge is how to buck the trend of diminishing returns that is commonly encountered. We present an active learning-style data solicitation algorithm to meet this challenge. We test it, gathering annotations via Amazon Mechanical Turk, and f...

It has been a practice in control system design to provide certain means of control in any control system by using different techniques such as adding compensators like PI, PD, and PID, with the incorporation of machine intelligence techniques such as fuzzy logic, artificial neural networks, and evolutionary computation. This paper presents a design approach in the development of compensators f...

By adding re exion to the chemical machine of Berry and Boudol we obtain a formal model of concurrency that is consistent with mobility and distribution Our model provides the foundations of a programming language with functional and object oriented features It can also be seen as a process calculus the join calculus which we prove equivalent to the calculus of Milner Parrow and Walker

We investigate methods that add syntactically motivated features to a statistical machine translation system in a reranking framework. The goal is to analyze whether shallow parsing techniques help in identifying ungrammatical hypotheses. We show that improvements are possible by utilizing supertagging, lightweight dependency analysis, a link grammar parser and a maximum-entropy based chunk par...

The ecological effects of accidental or malicious radioactive contamination are insufficiently understood because of the hazards and difficulties associated with conducting studies in radioactively-polluted areas. Data sets from severely contaminated locations can therefore be small. Moreover, many potentially important factors, such as soil concentrations of toxic chemicals, pH, and temperatur...

Machine Learning is concerned with the making of calculations and methods that use PCs to learn acquire insight, using related knowledge available.This work focused on machine learning approaches for predicting diabetic disorders, datasets from Predict Diabetic Diseases. A web-based comparative analysis multiple algorithms (Decision Tree, Support Vector Machine, K-Nearest Neighbor, Logistic Reg...

We built an automated essay scoring system to score approximately 13,000 essay from an online Machine Learning competition Kaggle.com. There are 8 different essay topics and as such, the essays were divided into 8 sets which differed significantly in their responses to the our features and evaluation. Our focus for this essay grading was the style of the essay, which is an extension on the stud...

We consider several parallel machine scheduling settings with the objective to minimize the schedule makespan. The most general of these settings is unrelated parallel machine scheduling. We assume that, in addition to its machine dependence, the processing time of any job is dependent on the usage of a scarce renewable resource. A given amount of that resource, e.g. workers, can be distributed...