Computer Sciences Commons^™

Design And Implementation Of Fast Motion Estimation In Modern Video Compression On Gpu, Zhaohua Yi

Electronic Theses and Dissertations

Motion estimation is the most compute expensive part of high definition video compression. It accounts for more than 50\% of overall execution. Therefore, improving the performance of motion estimation can make significant impact on the overall performance of video compression. The performance of motion estimation can be improved in two aspects: algorithm and implementation. This thesis touches both aspects. We first propose an innovative motion estimation algorithm by replacing the traditional block matching method which comparing blocks pixel by pixel with a brand new method which based on lbp (local binary pattern) code. Our new method first encodes the original …

Synthetic Steganography: Methods For Generating And Detecting Covert Channels In Generated Media, Philip Carson Ritchey

Open Access Dissertations

Issues of privacy in communication are becoming increasingly important. For many people and businesses, the use of strong cryptographic protocols is sufficient to protect their communications. However, the overt use of strong cryptography may be prohibited or individual entities may be prohibited from communicating directly. In these cases, a secure alternative to the overt use of strong cryptography is required. One promising alternative is to hide the use of cryptography by transforming ciphertext into innocuous-seeming messages to be transmitted in the clear. ^ In this dissertation, we consider the problem of synthetic steganography: generating and detecting covert channels in generated …

Advanced Wireless Communications Using Large Numbers Of Transmit Antennas And Receive Nodes, Junil Choi

Open Access Dissertations

The concept of deploying a large number of antennas at the base station, often called massive multiple-input multiple-output (MIMO), has drawn considerable interest because of its potential ability to revolutionize current wireless communication systems. Most literature on massive MIMO systems assumes time division duplexing (TDD), although frequency division duplexing (FDD) dominates current cellular systems. Due to the large number of transmit antennas at the base station, currently standardized approaches would require a large percentage of the precious downlink and uplink resources in FDD massive MIMO be used for training signal transmissions and channel state information (CSI) feedback. First, we propose …

The Cyber Simulation Terrain: Towards An Open Source Cyber Effects Simulation Ontology, Kent O'Sullivan, Benjamin Turnbull

Australian Information Warfare and Security Conference

Cyber resilience is characterised by an ability to understand and adapt to changing network conditions, including cyber attacks. Cyber resilience may be characterised by an effects-based approach to missions or processes. One of the fundamental preconditions underpinning cyber resilience is an accurate representation of current network and machine states and what missions they are supporting. This research outlines the need for an ontological network representation, drawing on existing literature and implementations in the domain. This work then introduces an open-source ontological representation for modelling cyber assets for the purposes of Computer Network Defence. This representation encompasses computers, network connectivity, users, …

Automated Medication Dispensing Cabinet And Medication Errors, Marie Helen Walsh

Walden Dissertations and Doctoral Studies

The number of deaths due to medical errors in hospitals ranges from 44,000 to 98,000 yearly. More than 7,000 of these deaths have taken place due to medication errors. This project evaluated the implementation of an automated medication dispensing cabinet or PYXIS machine in a 25-bed upper Midwestern critical access hospital. Lewin's stage theory of organizational change and Roger's diffusion of innovations theory supported the project. Nursing staff members were asked to complete an anonymous, qualitative survey approximately 1 month after the implementation of the PYXIS and again 1 year later. Questions were focused on the device and its use …

Monitoring Student Engagement And Improving Performance, Brian Keegan, Bianca Schoen-Phelan

Conference papers

No abstract provided.

Impact Of Eu Medical Device Directive On Medical Device Software, Guy Foe Owono

Walden Dissertations and Doctoral Studies

Directive 2007/47/EC of the European Parliament amending Medical Device Directive (MDD) provides medical device manufacturers with a compliance framework. However, the effects of the amendments to the MDD on competition in the U.S. medical device software industry are unknown. This study examined the impact of this directive on the competitiveness of U.S. medical device software companies, the safety and efficacy of medical device software, employee training, and recruitment. The conceptual framework for this study included 3 dimensions of medical device regulations: safety, performance, and reliability. The overall research design was a concurrent mixed method study using both quantitative and qualitative …

Effects Of Investor Sentiment Using Social Media On Corporate Financial Distress, Tarek Hoteit

Walden Dissertations and Doctoral Studies

The mainstream quantitative models in the finance literature have been ineffective in detecting possible bankruptcies during the 2007 to 2009 financial crisis. Coinciding with the same period, various researchers suggested that sentiments in social media can predict future events. The purpose of the study was to examine the relationship between investor sentiment within the social media and the financial distress of firms Grounded on the social amplification of risk framework that shows the media as an amplified channel for risk events, the central hypothesis of the study was that investor sentiments in the social media could predict t he level …

Rice Blast Disease Forecasting For Northern Philippines, Proceso L. Fernandez Jr, Alvin R. Malicdem

Department of Information Systems & Computer Science Faculty Publications

Rice blast disease has become an enigmatic problem in several rice growing ecosystems of both tropical and temperate regions of the world. In this study, we develop models for predicting the occurrence and severity of rice blast disease, with the aim of helping to prevent or at least mitigate the spread of such disease. Data from 2 government agencies in selected provinces from northern Philippines were gathered, cleaned and synchronized for the purpose of building the predictive models. After the data synchronization, dimensionality reduction of the feature space was done, using Principal Component Analysis (PCA), to determine the most important …

Choice Of Human–Computer Interaction Mode In Stroke Rehabilitation, Hossein Mousavi Hondori, Maryam Khademi, Lucy Dodakian, Alison Mackenzie, Cristina V. Lopes, Steven C. Cramer

Physical Therapy Faculty Articles and Research

Background and Objective. Advances in technology are providing new forms of human–computer interaction. The current study examined one form of human–computer interaction, augmented reality (AR), whereby subjects train in the real-world workspace with virtual objects projected by the computer. Motor performances were compared with those obtained while subjects used a traditional human–computer interaction, that is, a personal computer (PC) with a mouse. Methods. Patients used goal-directed arm movements to play AR and PC versions of the Fruit Ninja video game. The 2 versions required the same arm movements to control the game but had different cognitive demands. With …

Physical Engagement As A Way To Increase Emotional Rapport In Interactions With Embodied Conversational Agents, Ivan Gris Sepulveda

Open Access Theses & Dissertations

One of the major goals in research on embodied conversational agents (ECAs) is to increase the believability and perceived trustworthiness of agents. To improve the efficacy of the interaction between humans and ECAs, I focus on the development of rapport, which is a complex and extensive behavioral state of affinity, synchronicity, coordination and mutual understanding that is difficult to model, measure and interpret. I present our AGENT Framework and our ECA, Adriana, which is capable of speech recognition and gesture recognition over long periods of time. Our current system provides up to 60 minutes of human-ECA interaction in a jungle-survival …

Multi-Expert Multi-Criteria Decision Making, Joel Henderson

Open Access Theses & Dissertations

Expert analysis and decisions are highly valued assets in a wide variety of fields, from social services to grant funding committees. However, the use of experts can be prohibitive due to either lack of availability or cost. As such, it is desirable to be able to replicate such decisions. However, there are many obstacles that impede an accurate simulation of expert decisions. For example, despite looking at the same information, two experts may disagree on the decisions. In addition, a single expert may make inconsistent decisions across similar scenarios.

In this work, we focus on multi-criteria decision making and in …

Iso-Power-Efficiency: An Approach To Scaling Application Codes With A Power Budget, Rogelio Long

Open Access Theses & Dissertations

For many applications, speedup saturates and parallel efficiency decreases if the problem size is held fixed while increasing the number of processors. For some problems, it is possible to maintain a fixed parallel efficiency by increasing both the problem size and the number of processing elements. The rate at which the problem size must increase to maintain constant efficiency for a given rate of increase of the number of processors is given by the iso-efficiency function. We have developed a new scalability function called iso-power-efficiency that determines the rate at which the problem size must increase to maintain constant efficiency …

Bounded Rationality In Decision Making Under Uncertainty: Towards Optimal Granularity, Joseph Anthony Lorkowski

Open Access Theses & Dissertations

Starting from well-known studies by Kahmenan and Tversky, researchers have found many examples when our decision making seems to be irrational. We show that this seemingly irrational decision making can be explained if we take into account that human abilities to process information are limited. As a result, instead of the exact values of different quantities, we operate with granules that contain these values. On several examples, we show that optimization under such granularity restriction indeed leads to observed human decision making. Thus, granularity helps explain seemingly irrational human decision making.

Similar arguments can be used to explain the success …

Computation Offloading Decisions For Reducing Completion Time, Salvador Melendez

Open Access Theses & Dissertations

Mobile devices are being widely used in many applications such as image processing, computer vision (e.g. face detection and recognition), wearable computing, language translation, and battlefield operations. However, mobile devices are constrained in terms of their battery life, processor performance, storage capacity, and network bandwidth. To overcome these issues, there is an approach called Computation Offloading, also known as cyber-foraging and surrogate computing. Computation offloading consists of migrating computational jobs from a mobile device to more powerful remote computing resources. Upon completion of the job, the results are sent back to the mobile device. However, a decision must be made; …

Enhancing Workplace Productivity And Competitiveness In Trinidad And Tobago Through Ict Adoption, Kennedy Jerome Swaratsingh

Walden Dissertations and Doctoral Studies

The productivity of Trinidad and Tobago's public sector workplaces is related to their absorptive capacity for technological adoption. Guided by the technology acceptance model, which suggests that individuals' and institutions' use of technology increases in relation to perceived ease of use and apparent value, this case study explored how Trinidad and Tobago used information and communications technology from 2001 - 2010 to improve public sector workplace productivity. Study data were collected from 22 individual interviews with senior executives from the government of Trinidad and Tobago, members of the e-business roundtable, and local industry experts, and from reviewing the archives of …

Project Maelstrom: Forensic Analysis Of The Bittorrent-Powered Browser, Jason Farina, M-Tahar Kechadi, Mark Scanlon

Journal of Digital Forensics, Security and Law

In April 2015, BitTorrent Inc. released their distributed peer-to-peer powered browser, Project Maelstrom, into public beta. The browser facilitates a new alternative website distribution paradigm to the traditional HTTP-based, client-server model. This decentralised web is powered by each of the visitors accessing each Maelstrom hosted website. Each user shares their copy of the website;s source code and multimedia content with new visitors. As a result, a Maelstrom hosted website cannot be taken offline by law enforcement or any other parties. Due to this open distribution model, a number of interesting censorship, security and privacy considerations are raised. This paper explores …

The Subject Librarian Newsletter, Engineering And Computer Science, Fall 2015, Ven Basco

Libraries' Newsletters

No abstract provided.

Features For Ranking Tweets Based On Credibility And Newsworthiness, Jacob W. Ross

Browse all Theses and Dissertations

We create a robust and general feature set for learning to rank algorithms that rank tweets based on credibility and newsworthiness. In previous works, it has been demonstrated that when the training and testing data are from two distinct time periods, the ranker performs poorly. We improve upon previous work by creating a feature set that does not over fit a particular year or set of topics. This is critical given how people utilize social media changes as time progresses, and the topics discussed vary. In addition, we are constantly gaining new tweet data. Thus, it is important to be …

Domain-Specific Document Retrieval Framework For Near Real-Time Social Health Data, Swapnil Soni

Browse all Theses and Dissertations

With the advent of web search and microblogging, the percentage of Online Health Information Seekers (OHIS) using these services to share and seek health information in real-time has increased exponentially. Recently, Twitter has emerged as one of the primary mediums for sharing and seeking of the latest information related to a variety of topics, including health information. Although Twitter is an excellent information source, the identification of useful information from the deluge of tweets is one of the major challenges. Twitter search is limited to keyword-based techniques to retrieve information for a given query and sometimes the results do not …

Automatic Emotion Identification From Text, Wenbo Wang

Browse all Theses and Dissertations

People's emotions can be gleaned from their text using machine learning techniques to build models that exploit large self-labeled emotion data from social media. Further, the self-labeled emotion data can be effectively adapted to train emotion classifiers in different target domains where training data are sparse.

Emotions are both prevalent in and essential to most aspects of our lives. They influence our decision-making, affect our social relationships and shape our daily behavior. With the rapid growth of emotion-rich textual content, such as microblog posts, blog posts, and forum discussions, there is a growing need to develop algorithms and techniques for …

Knowledge Enabled Location Prediction Of Twitter Users, Revathy Krishnamurthy

Browse all Theses and Dissertations

As the popularity of online social networking sites such as Twitter and Facebook continues to rise, the volume of textual content generated on the web is increasing rapidly. The mining of user generated content in social media has proven effective in domains ranging from personalization and recommendation systems to crisis management. These applications stand to be further enhanced by incorporating information about the geo-position of social media users in their analysis. Due to privacy concerns, users are largely reluctant to share their location information. As a consequence of this, researchers have focused on automatic inferencing of location information from the …

A Language For Inconsistency-Tolerant Ontology Mapping, Kunal Sengupta

Browse all Theses and Dissertations

Ontology alignment plays a key role in enabling interoperability among various data sources present in the web. The nature of the world is such, that the same concepts differ in meaning, often so slightly, which makes it difficult to relate these concepts. It is the omni-present heterogeneity that is at the core of the web. The research work presented in this dissertation, is driven by the goal of providing a robust ontology alignment language for the semantic web, as we show that description logics based alignment languages are not suitable for aligning ontologies.

The adoption of the semantic web technologies …

Orthogonal Moment-Based Human Shape Query And Action Recognition From 3d Point Cloud Patches, Huaining Cheng

Browse all Theses and Dissertations

With the recent proliferation of 3D sensors such as Light Detection and Ranging (LIDAR), it is essential to develop feature representation methods that can best characterize the point clouds produced by these devices. When these devices are employed in targeting and surveillance of human actions from both ground and aerial platforms, the corresponding point clouds of body shape often comprise low-resolution, disjoint, and irregular patches of points resulted from self-occlusions and viewing angle variations. The prevailing method of depth image analysis has the limitation of relying on 2D features that are not native representation of 3D spatial relationships. On the …

Ontology Pattern-Based Data Integration, Adila Alfa Krisnadhi

Browse all Theses and Dissertations

Data integration is concerned with providing a unified access to data residing at multiple sources. Such a unified access is realized by having a global schema and a set of mappings between the global schema and the local schemas of each data source, which specify how user queries at the global schema can be translated into queries at the local schemas. Data sources are typically developed and maintained independently, and thus, highly heterogeneous. This causes difficulties in integration because of the lack of interoperability in the aspect of architecture, data format, as well as syntax and semantics of the data. …

Learning To Rank Algorithms And Their Application In Machine Translation, Tian Xia

Browse all Theses and Dissertations

In this thesis, we discuss two issues in the learning to rank area, choosing effective objective loss function, constructing effective regresstion trees in the gradient boosting framework, as well as a third issus, applying learning to rank models into statistcal machine translation. First, list-wise based learning to rank methods either directly optimize performance measures or optimize surrogate functions of performance measures that have smaller gaps between optimized losses and performance measures, thus it is generally believed that they should be able to lead to better performance than point-and pair-wise based learning to rank methods. However, in real-world applications, state-of-the-art practical …

Extracting Flow Features Using Bag-Of-Features And Supervised Learning Techniques, Yifei Li

Dissertations, Master's Theses and Master's Reports

Measuring the similarity between two streamlines is fundamental to many important flow data analysis and visualization tasks such as feature detection, pattern querying and streamline clustering. This dissertation presents a novel streamline similarity measure inspired by the bag-of-features concept from computer vision. Different from other streamline similarity measures, the proposed one considers both the distribution of and the distances among features along a streamline. The proposed measure is tested in two common tasks in vector field exploration: streamline similarity query and streamline clustering. Compared with a recent streamline similarity measure, the proposed measure allows users to see the interesting features …

Enabling Techniques For Expressive Flow Field Visualization And Exploration, Jun Tao

Dissertations, Master's Theses and Master's Reports

Flow visualization plays an important role in many scientific and engineering disciplines such as climate modeling, turbulent combustion, and automobile design. The most common method for flow visualization is to display integral flow lines such as streamlines computed from particle tracing. Effective streamline visualization should capture flow patterns and display them with appropriate density, so that critical flow information can be visually acquired. In this dissertation, we present several approaches that facilitate expressive flow field visualization and exploration. First, we design a unified information-theoretic framework to model streamline selection and viewpoint selection as symmetric problems. Two interrelated information channels are …

Adaptive Duty Cycling In Sensor Networks With Energy Harvesting Using Continuous-Time Markov Chain And Fluid Models, Wai Hong Ronald Chan, Pengfei Zhang, Ido Nevat, Sai Ganesh Nagarajan, Alvin C. Valera, Hwee Xian Tan, Natarajan Gautam

Research Collection School Of Computing and Information Systems

Abstract:The dynamic and unpredictable nature of energy harvesting sources available for wireless sensor networks, and the time variation in network statistics like packet transmission rates and link qualities, necessitate the use of adaptive duty cycling techniques. Such adaptive control allows sensor nodes to achieve long-run energy neutrality, where energy supply and demand are balanced in a dynamic environment such that the nodes function continuously. In this paper, we develop a new framework enabling an adaptive duty cycling scheme for sensor networks that takes into account the node battery level, ambient energy that can be harvested, and application-level QoS requirements. We …

Low Effort Crowdsourcing: Leveraging Peripheral Attention For Crowd Work, Vaish Rajan, Peter Organisciak, Kotaro Hara, Jeffrey P. Bigham, Haoqi Zhang

Research Collection School Of Computing and Information Systems

Crowdsourcing systems leverage short bursts of focusedattention from many contributors to achieve a goal. Byrequiring people’s full attention, existing crowdsourcingsystems fail to leverage people’s cognitive surplus in themany settings for which they may be distracted, performingor waiting to perform another task, or barely payingattention. In this paper, we study opportunities for loweffortcrowdsourcing that enable people to contribute toproblem solving in such settings. We discuss the designspace for low-effort crowdsourcing, and through a seriesof prototypes, demonstrate interaction techniques, mechanisms,and emerging principles for enabling low-effortcrowdsourcing.