in this paper the design, implementation, and evaluation of an experimental-scale potato yield monitoring system is presented. the main objective of this research was to develop a method for accurate mapping of potato yield. at the first stage an instantaneous yield monitoring system was mounted on a potato harvesting machine. this system consisted of a weighing tray, two load cells, a shaft rp...

This paper presents two strong baselines for the BioNLP 2009 shared task on event extraction. First we re-implement a rulebased approach which allows us to explore the task and the effect of domainadapted parsing on it. We then replace the rule-based component with support vector machine classifiers and achieve performance near the state-of-the-art without using any external resources. The good...

This paper describes the MIRACL statistical Machine Translation system and the improvements that were developed during the IWSLT 2010 evaluation campaign. We participated to the Arabic to English BTEC tasks using a phrase-based statistical machine translation approach. In this paper, we first discuss some challenges in translating from Arabic to English and we explore various techniques to impr...

Method inlining is one of the most important optimizations in method-based just-in-time (JIT) compilers. It widens the compilation scope and therefore allows optimizing multiple methods as a whole, which increases the performance. However, if method inlining is used too frequently, the compilation time increases and too much machine code is generated. This has negative effects on the performanc...

Compound splitting is an important problem in many NLP applications which must be solved in order to address issues of data sparsity. Previous work has shown that linguistic approaches for German compound splitting produce a correct splitting more often, but corpus-driven approaches work best for phrase-based statistical machine translation from German to English, a worrisome contradiction. We ...

This paper describes the work we conducted for building a statistical machine translation (SMT) system for the ChineseEnglish sub-task of the NTCIR-9 patent machine translation (MT) evaluation [17]. We first applied the various techniques on patent data that we had developed for improving SMT performance on other types of data. Our results show that most of the techniques work on patent documen...

Convoulutional Neural Networks (CNNs) exhibit extraordinary performance on a variety of machine learning tasks. However, their mathematical properties and behavior are quite poorly understood. There is some work, in the form of a framework, for analyzing the operations that they perform. The goal of this project is to present key results from this theory, and provide intuition for why CNNs work.

Compound splitting is an important problem in many NLP applications which must be solved in order to address issues of data sparsity. Previous work has shown that linguistic approaches for German compound splitting produce a correct splitting more often, but corpus-driven approaches work best for phrase-based statistical machine translation from German to English, a worrisome contradiction. We ...

Configuration problem in storage system is one of the well recognized issues in today’s enterprise environment. Traditional approaches usually reply on deep knowledge of the underlying system. However, such solution usually cannot scale up when the system become large and complex. Recent research work has started using machine learning techniques to improve the overall performance of the diagno...

The goal of this paper is how to build cloud IaaS environment for operation, and integrate KVM and OpenNebula open sources to provide a cloud virtual environment for users. In the user interface part, this work can reduce the complexity of cloud resources accessing for the user part. This paper uses the web interface that is easy to understand, accessible for users in the operations. In the exp...