Data Storage Systems Commons^™

Is Data To Knowledge As The Wasp Is To The Fig Tree? Reconsidering Licklider’S Intergalactic Network In The Days Of Data Deluge., Christine L. Borgman

Christine L. Borgman

No abstract provided.

An Exploration Of Knowledge And Skills Transfer From A Formal Software Engineering Curriculum To A Capstone Practicum Project, Ray Bareiss, Ed Katz

Ray Bareiss

Students at Carnegie Mellon Silicon Valley complete a team-based practicum project for an industrial sponsor as the capstone of their master’s education in software engineering. Over time, the faculty member who typically serves as advisor for such projects has been disturbed by the failure of several student teams to transfer some relevant knowledge and skills from the formal curriculum to the relatively unstructured practicum project environment. We conducted a survey of all 2010 software engineering students to ascertain the most significant selfreported shortcomings. This paper presents the survey data and then discusses the results in terms of a theory of …

Fusing Heterogeneous Modalities For Video And Image Re-Ranking, Hung-Khoon Tan, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Multimedia documents in popular image and video sharing websites such as Flickr and Youtube are heterogeneous documents with diverse ways of representations and rich user-supplied information. In this paper, we investigate how the agreement among heterogeneous modalities can be exploited to guide data fusion. The problem of fusion is cast as the simultaneous mining of agreement from different modalities and adaptation of fusion weights to construct a fused graph from these modalities. An iterative framework based on agreement-fusion optimization is thus proposed. We plug in two well-known algorithms: random walk and semi-supervised learning to this framework to illustrate the idea …

Cloud Computing: Architectural And Policy Implications, Christopher S. Yoo

All Faculty Scholarship

Cloud computing has emerged as perhaps the hottest development in information technology. Despite all of the attention that it has garnered, existing analyses focus almost exclusively on the issues that surround data privacy without exploring cloud computing’s architectural and policy implications. This article offers an initial exploratory analysis in that direction. It begins by introducing key cloud computing concepts, such as service-oriented architectures, thin clients, and virtualization, and discusses the leading delivery models and deployment strategies that are being pursued by cloud computing providers. It next analyzes the economics of cloud computing in terms of reducing costs, transforming capital expenditures …

Imirok: Real-Time Imitative Robotic Arm Control For Home Robot Applications, Heng-Tze Cheng, Zheng Sun, Pei Zhang

Zheng Sun

Training home robots to behave like human can help people with their daily chores and repetitive tasks. In this paper, we present Imirok, a system to remotely control robotic arms by user motion using low-cost, off-the-shelf mobile devices and webcam. The motion tracking algorithm detects user motion in real-time, without classifier training or predefined action set. Experimental results show that the system achieves 90% precision and recall rate on motion detection with blank background, and is robust under the change of cluttered background and user-to-camera distance.

Leveraging Mobile Context For Effective Collaboration And Task Management In Disaster Response, Faisal Luqman, Martin L. Griss

Martin L Griss

Collaboration and task management is challenging in distributed, dynamically-formed teams, typical in large scale disaster response scenarios. Ineffective collaboration may result in poor performance and possible loss of life. In this paper, we present Overseer, an agent-based system that exploits context information from mobile devices to facilitate collaboration and task allocation. We describe our system architecture and show how mobile context can be used to create dynamic role-based assignments to support collaboration and effective task management.

Anubis: An Attestation Protocol For Distributed Context-Aware Applications, Senaka Buthpitiya, Feng-Tso Sun, Heng-Tze Chen, Patrick Tague, Martin L. Griss, Anind K. Dey

Martin L Griss

Sharing sensitive context information among multiple distributed components in mobile environments introduces major security concerns. The distributed sensing, processing and actuating components of these applications can be compromised and modified or impersonated to extract private and confidential information or to inject false information. In this paper we present the Anubis protocol for remote code attestation and access control of distributed components using remote execution of trusted code. Our Anubis protocol leverages previous work in the fields of wireless sensor networks and secure web browsing. Anubis allows new components to be introduced to the environment without updating existing components. Our implementation …

Mobile Context-Aware Personal Messaging Assistant, Senaka Buthpitiya, Deepthi Madamanchi, Sumalatha Kommaraju, Martin L. Griss

Martin L Griss

A previous study shows that busy professionals receive in excess of 50 emails per day of which approximately 23% require immediate attention, 13% require attention later and 64% are unimportant and typically ignored. The flood of emails impact mobile users even more heavily. Flooded inboxes cause busy professionals to spend considerable amounts of time searching for important messages, and there has been much research into automating the process using email content for classification; but we find email priority depends also on user context. In this paper we describe the Personal Messaging Assistant (PMA), an advanced rule-based email management system which …

Sensorchestra: Collaborative Sensing For Symbolic Location Recognition, Heng-Tze Cheng, Feng-Tso Sun, Senaka Buthpitiya, Martin L. Griss

Martin L Griss

"Symbolic location of a user, like a store name in a mall, is essential for context-based mobile advertising. Existing fingerprint- based localization using only a single phone is susceptible to noise, and has a major limitation in that the phone has to be held in the hand at all times. In this paper, we present SensOrchestra, a col- laborative sensing framework for symbolic location recognition that groups nearby phones to recognize ambient sounds and images of a location collaboratively. We investigated audio and image features, and designed a classifier fusion model to integrate estimates from diff erent phones. We also …

Activity-Aware Mental Stress Detection Using Physiological Sensors, Feng-Tso Sun, Cynthia Kuo, Heng-Tze Cheng, Senaka Buthpitiya, Patricia Collins, Martin Griss

Martin L Griss

"Continuous stress monitoring may help users better understand their stress patterns and provide physicians with more reliable data for interventions. Previously, studies on mental stress detection were limited to a laboratory environment where participants generally rested in a sedentary position. However, it is impractical to exclude the effects of physical activity while developing a pervasive stress monitoring application for everyday use. The physiological responses caused by mental stress can be masked by variations due to physical activity. We present an activity-aware mental stress detection scheme. Electrocardiogram (ECG), galvanic skin response (GSR), and accelerometer data were gathered from 20 participants across …

Omnisense: A Collaborative Sensing Framework For User Context Recognition Using Mobile Phones, Heng-Tze Cheng, Senaka Buthpitiya, Feng-Tso Sun, Martin L. Griss

Martin L Griss

Context information, including a user’s locations and activities, is indispensable for context-aware applications such as targeted advertising and disaster response. Inferring user context from sensor data is intrinsically challenging due to the semantic gap between low-level signals and high-level human activities. When implemented on mobile phones, more challenges on resource limitations are present. While most existing work focuses on context recognition using a single mobile phone, collaboration among multiple phones has received little attention, and the recognition accuracy is susceptible to phone position and ambient changes. Simply putting a phone in one’s pocket can render the microphone muffled and the …

Room-Level Wi-Fi Location Tracking, Joshua Correa, Ed Katz, Patricia Collins, Martin Griss

Martin L Griss

Context-aware applications for indoor intelligent environments require an appropriately accurate and stable interior positioning system to adapt services to the location of a mobile user or mobile device in a building. Different technologies provide a varying mix of resolution, accuracy, stability and challenges. In this paper we report on our experience using an existing Wi-Fi infrastructure without specialized hardware added to support location tracking. There are several approaches to track the location of Wi-Fi enabled devices within a building such as signal propagation models and signature matching. We found signature matching most effective in our environment. Signature matching is accomplished …

Investigations Into Library Web Scale Discovery Services, Jason Vaughan

Library Faculty Publications

Web scale discovery services for libraries provide deep discovery to a library’s local and licensed content, and represent an evolution, perhaps a revolution, for end user information discovery as pertains to library collections. This article frames the topic of Web scale discovery, and begins by illuminating Web scale discovery from an academic library’s perspective – that is, the internal perspective seeking widespread staff participation in the discovery conversation. This included the creation of a Discovery Task Force, a group which educated library staff, conducted internal staff surveys, and gathered observations from early adopters. The article next addresses the substantial research …

Development Of Visualization Facility At The Gis And Remote Sensing Core Lab, University Of Nevada, Las Vegas, Haroon Stephen, William J. Smith, Zhongwei Liu

Public Policy and Leadership Faculty Presentations

Visualization using advanced computational and graphic equipment has become a standard way of present day research. Availability of low cost and fast processing units, high resolution displays with graphic processing units, and specialized software has brought complex visualization capabilities to an office desktop. Nevertheless, when dealing with large datasets such as, global climate, geospatial, and social data the office desktop falls short and calls for a centralized visualization facility with high end computing and graphics equipment.

Visualization Facility at GIS and Remote Sensing Core Lab would be a useful and important addition to the UNLV IT infrastructure. It would provide …

Freeing Space For Nasa: Incorporating A Lossless Compression Algorithm Into Nasa's Fiber Optic Strain Sensing System, Kaitlyn Fiechtner, Allen Parker

STAR Program Research Presentations

NASA’s Fiber Optic Strain Sensing (FOSS) system can gather and store up to 1,536,000 bytes (1.46 megabytes) per second. Since the FOSS system typically acquires hours—or even days—of data, the system can gather hundreds of gigabytes of data for a given test event. To store such large quantities of data more effectively, NASA is modifying a Lempel-Ziv-Oberhumer (LZO) lossless data compression program to compress data as it is being acquired in real time. After proving that the algorithm is capable of compressing the data from the FOSS system, the LZO program will be modified and incorporated into the FOSS system. …

Mining Event Structures From Web Videos, Xiao Wu, Yi-Jie Lu, Qiang Peng, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

The article is discussing the issues of mining event structures from Web video search results using text analysis, burst detection, and clustering as with the proliferation of social media, the volume of Web videos have grown exponentially.

Semi-Automatic Management Of Knowledge Bases Using Formal Ontologies, Andreas Textor

Theses

This thesis presents an approach that deals with the ever-growing amount of data in knowledge bases, especially concerning knowledge interoperability and formal representation of domain knowledge. There arc multiple issues that must be addressed with current systems. A multitude of different formats, sources and tools exist in a domain, and it is desirable to develop their use further towards a standardised environment. Such an environment should support both the representation and processing of data from this domain, and the connection to other domains, where necessary. In order to manage large amounts of data, it should be possible to perform whatever …

Concept-Driven Multi-Modality Fusion For Video Search, Xiao-Yong Wei, Yu-Gang Jiang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

As it is true for human perception that we gather information from different sources in natural and multi-modality forms, learning from multi-modalities has become an effective scheme for various information retrieval problems. In this paper, we propose a novel multi-modality fusion approach for video search, where the search modalities are derived from a diverse set of knowledge sources, such as text transcript from speech recognition, low-level visual features from video frames, and high-level semantic visual concepts from supervised learning. Since the effectiveness of each search modality greatly depends on specific user queries, prompt determination of the importance of a modality …

Parallelizing Scale Invariant Feature Transform On A Distributed Memory Cluster, Stanislav Bobovych

Inquiry: The University of Arkansas Undergraduate Research Journal

Scale Invariant Feature Transform (SIFT) is a computer vision algorithm that is widely-used to extract features from images. We explored accelerating an existing implementation of this algorithm with message passing in order to analyze large data sets. We successfully tested two approaches to data decomposition in order to parallelize SIFT on a distributed memory cluster.

Evidence Supporting Measure Of Similarity For Reducing The Complexity In Information Fusion, Florentin Smarandache, Jean Dezert, Xinde Li, Xinhan Huang

Branch Mathematics and Statistics Faculty and Staff Publications

This paper presents a new method for reducing the number of sources of evidence to combine in order to reduce the complexity of the fusion processing. Such a complexity reduction is often required in many applications where the real-time constraint and limited computing resources are of prime importance. The basic idea consists in selecting, among all sources available, only a subset of sources of evidence to combine. The selection is based on an evidence supporting measure of similarity (ESMS) criterion which is an efficient generic tool for outlier sources identification and rejection. The ESMS between two sources of evidence can …