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Quantitative Fine-Grained Human Evaluation Of Machine Translation Systems: A Case Study On English To Croatian, Filip Klubicka, Antonio Toral, Victor Manuel Sanchez-Cartagena 2018 University of Groningen

Quantitative Fine-Grained Human Evaluation Of Machine Translation Systems: A Case Study On English To Croatian, Filip Klubicka, Antonio Toral, Victor Manuel Sanchez-Cartagena

Articles

This paper presents a quantitative fine-grained manual evaluation approach to comparing the performance of different machine translation (MT) systems. We build upon the well-established Multidimensional Quality Metrics (MQM) error taxonomy and implement a novel method that assesses whether the differences in performance for MQM error types between different MT systems are statistically significant. We conduct a case study for English-to- Croatian, a language direction that involves translating into a morphologically rich language, for which we compare three MT systems belonging to different paradigms: pure phrase-based, factored phrase-based and neural. First, we design an MQM-compliant error taxonomy tailored to the relevant ...


Is It Worth It? Budget-Related Evaluation Metrics For Model Selection, Filip Klubicka, Giancarlo Salton, John Kelleher 2018 Dublin Institute of Technology

Is It Worth It? Budget-Related Evaluation Metrics For Model Selection, Filip Klubicka, Giancarlo Salton, John Kelleher

Conference papers

Projects that set out to create a linguistic resource often do so by using a machine learning model that pre-annotates or filters the content that goes through to a human annotator, before going into the final version of the resource. However, available budgets are often limited, and the amount of data that is available exceeds the amount of annotation that can be done. Thus, in order to optimize the benefit from the invested human work, we argue that the decision on which predictive model one should employ depends not only on generalized evaluation metrics, such as accuracy and F-score, but ...


Adapt At Semeval-2018 Task 9: Skip-Gram Word Embeddings For Unsupervised Hypernym Discovery In Specialised Corpora, Alfredo Maldonado, Filip Klubicka 2018 Trinity College Dublin, Ireland

Adapt At Semeval-2018 Task 9: Skip-Gram Word Embeddings For Unsupervised Hypernym Discovery In Specialised Corpora, Alfredo Maldonado, Filip Klubicka

Other resources

This paper describes a simple but competitive unsupervised system for hypernym discovery. The system uses skip-gram word embeddings with negative sampling, trained on specialised corpora. Candidate hypernyms for an input word are predicted based on cosine similar- ity scores. Two sets of word embedding mod- els were trained separately on two specialised corpora: a medical corpus and a music indus- try corpus. Our system scored highest in the medical domain among the competing unsu- pervised systems but performed poorly on the music industry domain. Our approach does not depend on any external data other than raw specialised corpora.


Developing A Recurrent Neural Network With High Accuracy For Binary Sentiment Analysis, Kevin Cunanan 2018 Claremont Colleges

Developing A Recurrent Neural Network With High Accuracy For Binary Sentiment Analysis, Kevin Cunanan

CMC Senior Theses

Sentiment analysis has taken on various machine learning approaches in order to optimize accuracy, precision, and recall. However, Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNNs) account for the context of a sentence by using previous predictions as additional input for future sentence predictions. Our approach focused on developing an LSTM RNN that could perform binary sentiment analysis for positively and negatively labeled sentences. In collaboration with Mariam Salloum, I developed a collection of programs to classify individual sentences as either positive or negative. This paper additionally looks into machine learning, neural networks, data preprocessing, implementation, and resulting comparisons.


Anomaly Inference Based On Heterogeneous Data Sources In An Electrical Distribution System, Yachen Tang 2018 Michigan Technological University

Anomaly Inference Based On Heterogeneous Data Sources In An Electrical Distribution System, Yachen Tang

Dissertations, Master's Theses and Master's Reports

Harnessing the heterogeneous data sets would improve system observability. While the current metering infrastructure in distribution network has been utilized for the operational purpose to tackle abnormal events, such as weather-related disturbance, the new normal we face today can be at a greater magnitude. Strengthening the inter-dependencies as well as incorporating new crowd-sourced information can enhance operational aspects such as system reconfigurability under extreme conditions. Such resilience is crucial to the recovery of any catastrophic events. In this dissertation, it is focused on the anomaly of potential foul play within an electrical distribution system, both primary and secondary networks as ...


A Simple Moving Target Defense For Power Grid Security Using Network Address Translation, Jacob Ulrich 2018 Iowa State University

A Simple Moving Target Defense For Power Grid Security Using Network Address Translation, Jacob Ulrich

Creative Components

No abstract provided.


Iseman: A Management And Deployment Interface For Lab-Based Activities Within Iserink, Alex Luehm 2018 Iowa State University

Iseman: A Management And Deployment Interface For Lab-Based Activities Within Iserink, Alex Luehm

Creative Components

ISERink is an isolated virtual environment built within the vSphere virtualization platform in which users can safely perform various cyber security exercises without fear of damaging real-world machines. In the past it has been successfully used in cyber defense competitions to provide a network setting similar to that of the real Internet, while safely containing any rogue malicious traffic. Recently the ISERink environment has been deployed within the academic setting alongside ISELab to provide students with a safe and controlled environment in which to practice building, securing, and attacking networks in a structured lab setting in conjunction with guided lectures ...


Real-Time Assessment And Visual Feedback For Patient Rehabilitation Using Inertial Sensors, Deepa Adinarayanan 2018 Cleveland State University

Real-Time Assessment And Visual Feedback For Patient Rehabilitation Using Inertial Sensors, Deepa Adinarayanan

ETD Archive

Rehabilitation exercises needs have been continuously increasing and have been projected to increase in future as well based on its demand for aging population, recovering from surgery, injury and illness and the living and working lifestyle of the people. This research aims to tackle one of the most critical issues faced by the exercise administers-Adherence or Non-Adherence to Home Exercise problems especially has been a significant issue resulting in extensive research on the psychological analysis of people involved. In this research, a solution is provided to increase the adherence of such programs through an automated real-time assessment with constant visual ...


Continuous Human Activity Tracking Over A Large Area With Multiple Kinect Sensors, Akshat C. Hans 2018 Cleveland State University

Continuous Human Activity Tracking Over A Large Area With Multiple Kinect Sensors, Akshat C. Hans

ETD Archive

In recent years, researchers had been inquisitive about the use of technology to enhance the healthcare and wellness of patients with dementia. Dementia symptoms are associated with the decline in thinking skills and memory severe enough to reduce a person’s ability to pay attention and perform daily activities. Progression of dementia can be assessed by monitoring the daily activities of the patients. This thesis encompasses continuous localization and behavioral analysis of patient’s motion pattern over a wide area indoor living space using multiple calibrated Kinect sensors connected over the network. The skeleton data from all the sensor is ...


Green Roof Policy Optimization Algorithms And Microsimulations Benefits And Downsides Of Green Roof Incentives And Mandates In San Francisco, Harrison Freund 2018 University of Iowa

Green Roof Policy Optimization Algorithms And Microsimulations Benefits And Downsides Of Green Roof Incentives And Mandates In San Francisco, Harrison Freund

Honors Theses at the University of Iowa

As the 21st Century progresses, developers are becoming more aware of their environmental footprint. As the Green Economy slowly gains its footing, developers will be expected to change current building practices to reflect the increasing demand to adapt to sustainability challenges. One such methodology used by LEED to evaluate the sustainability of a building is the implementation of a green roof, the installment of vegetation on the top of a building. There are many socioecological benefits that justify the implementation of a green roof, which explain why in recent years municipalities have enacted new policies to mandate or incentivize their ...


Blockchain Scalability And Security, Tuyet Duong 2018 Virginia Commonwealth University

Blockchain Scalability And Security, Tuyet Duong

Theses and Dissertations

Cryptocurrencies like Bitcoin have proven to be a phenomenal success. The underlying techniques hold huge promise to change the future of financial transactions, and eventually the way people and companies compute, collaborate, and interact. At the same time, the current Bitcoin-like proof-of-work based blockchain systems are facing many challenges. In more detail, a huge amount of energy/electricity is needed for maintaining the Bitcoin blockchain. In addition, their security holds if the majority of the computing power is under the control of honest players. However, this assumption has been seriously challenged recently and Bitcoin-like systems will fail when this assumption ...


Security Attacks On Reckless-Apps: "Remote Car Keyless Applications" For New Semi Autonomous Vehicles, Mohamed El-Tawab 2018 James Madison University

Security Attacks On Reckless-Apps: "Remote Car Keyless Applications" For New Semi Autonomous Vehicles, Mohamed El-Tawab

Masters Theses

Rapid technological advancements of vehicle manufacturing and the modern wireless technology opens the door for several new Intelligent Transportation applications. Remote Keyless system in vehicles is considered one of the famous applications that has been developed recently, which is susceptible to many cyberattacks. Remote Keyless applications on smartphones were developed in the past few years to perform the functionality of keyless fob and are expected to replace the physical keyless fobs in the next few years, which can open the door to many cyberattacks. In this research, we implemented a simulation that represents the REmote Car KeyLESS Applications (RECKLESS-apps) on ...


Real Time Traffic Congestion Detection Using Images, Revanth Ayala Somayajula 2018 Iowa State University

Real Time Traffic Congestion Detection Using Images, Revanth Ayala Somayajula

Creative Components

There is an increasing demand to utilize modern technology in the eld of transportation to help decrease congestion on roads so that proper measures can be pursued to facilitate lower travel times and an effective utilization of the transportation network. This project aims to develop a solution for real time detection of traffic congestion on a road. The solution captures images from the live feed of traffic cameras situated at various locations and runs a deep learning algorithm to detect whether an image shows traffic congestion. Using a set of these images and a persistence check, the application identifies the ...


Power Laws In Complex Graphs: Parsimonious Generative Models, Similarity Testing Algorithms, And The Origins, Shan Lu 2018 University of Massachusetts, Amherst

Power Laws In Complex Graphs: Parsimonious Generative Models, Similarity Testing Algorithms, And The Origins, Shan Lu

Doctoral Dissertations

This dissertation mainly discussed topics related to power law graphs, including graph similarity testing algorithms and power law generative models.

For graph similarity testing, we proposed a method based on the mathematical theory of diffusion over manifolds using random walks over graphs. We show that our method not only distinguishes between graphs with different degree distributions, but also graphs with the same degree distributions. We compare the undirected power law graphs generated by Barabasi-Albert model and directed power law graphs generated by Krapivsky's model to the random graphs generated by Erdos-Renyi model. We also compare power law graphs generated ...


Transiency-Driven Resource Management For Cloud Computing Platforms, Prateek Sharma 2018 University of Massachusetts Amherst

Transiency-Driven Resource Management For Cloud Computing Platforms, Prateek Sharma

Doctoral Dissertations

Modern distributed server applications are hosted on enterprise or cloud data centers that provide computing, storage, and networking capabilities to these applications. These applications are built using the implicit assumption that the underlying servers will be stable and normally available, barring for occasional faults. In many emerging scenarios, however, data centers and clouds only provide transient, rather than continuous, availability of their servers. Transiency in modern distributed systems arises in many contexts, such as green data centers powered using renewable intermittent sources, and cloud platforms that provide lower-cost transient servers which can be unilaterally revoked by the cloud operator.

Transient ...


Optimal Decomposition Strategy For Tree Edit Distance, Shaofeng Jiang 2017 The University of Western Ontario

Optimal Decomposition Strategy For Tree Edit Distance, Shaofeng Jiang

Electronic Thesis and Dissertation Repository

An ordered labeled tree is a tree where the left-to-right order among siblings is significant. Given two ordered labeled trees, the edit distance between them is the minimum cost edit operations that convert one tree to the other.

In this thesis, we present an algorithm for the tree edit distance problem by using the optimal tree decomposition strategy. By combining the vertical compression of trees with optimal decomposition we can significantly reduce the running time of the algorithm. We compare our method with other methods both theoretically and experimentally. The test results show that our strategies on compressed trees are ...


A Data Hiding Scheme Based On Chaotic Map And Pixel Pairs, Sengul DOGAN SD 2017 Firat University

A Data Hiding Scheme Based On Chaotic Map And Pixel Pairs, Sengul Dogan Sd

Journal of Digital Forensics, Security and Law

Information security is one of the most common areas of study today. In the literature, there are many algorithms developed in the information security. The Least Significant Bit (LSB) method is the most known of these algorithms. LSB method is easy to apply however it is not effective on providing data privacy and robustness. In spite of all its disadvantages, LSB is the most frequently used algorithm in literature due to providing high visual quality. In this study, an effective data hiding scheme alternative to LSB, 2LSBs, 3LSBs and 4LSBs algorithms (known as xLSBs), is proposed. In this method, random ...


Pubwc Bathroom Review App, Clay Jacobs 2017 California Polytechnic State University, San Luis Obispo

Pubwc Bathroom Review App, Clay Jacobs

Computer Science

For my senior project, I developed an iOS application to allow

users to find, rate, and review nearby public restrooms. The app takes

advantage of crowdsourced data to collect bathroom and review

information. I also created a REST API to interface with the backend

database that could be used to port the application to other platforms.


Streaming Mysql Database Activity To Aws Kinesis, Chris I. Voncina 2017 California Polytechnic State University, San Luis Obispo

Streaming Mysql Database Activity To Aws Kinesis, Chris I. Voncina

Computer Engineering

No abstract provided.


Real Time And High Fidelity Quadcopter Tracking System, Tyler McKay Hall 2017 California Polytechnic State University, San Luis Obispo

Real Time And High Fidelity Quadcopter Tracking System, Tyler Mckay Hall

Computer Engineering

This project was conceived as a desired to have an affordable, flexible and physically compact tracking system for high accuracy spatial and orientation tracking. Specifically, this implementation is focused on providing a low cost motion capture system for future research. It is a tool to enable the further creation of systems that would require the use of accurate placement of landing pads, payload acquires and delivery. This system will provide the quadcopter platform a coordinate system that can be used in addition to GPS.

Field research with quadcopter manufacturers, photographers, agriculture and research organizations were contact and interviewed for information ...


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