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Context-Driven Automatic Subgraph Creation For Literature-Based Discovery, Delroy H. Cameron, Ramakanth Kavuluru, Thomas Rindflesch, Amit P. Sheth, Krishnaprasad Thirunarayan, Olivier Bodenreider 2015 Wright State University - Main Campus

Context-Driven Automatic Subgraph Creation For Literature-Based Discovery, Delroy H. Cameron, Ramakanth Kavuluru, Thomas Rindflesch, Amit P. Sheth, Krishnaprasad Thirunarayan, Olivier Bodenreider

Kno.e.sis Publications

Background: Literature-based discovery (LBD) is characterized by uncovering hidden associations in non-interacting scientific literature. Prior approaches to LBD include use of: 1) domain expertise and structured background knowledge to manually filter and explore the literature, 2) distributional statistics and graph-theoretic measures to rank interesting connections and 3) heuristics to help eliminate spurious connections. However, manual approaches to LBD are not scalable and purely distributional approaches may not be sufficient to obtain insights into the meaning of poorly understood associations. While several graph-based approaches have the potential to elucidate associations, their effectiveness has not been fully demonstrated. A considerable degree of …


Towards An Integrated Model Of The Mental Lexicon, Natawut Monaikul 2015 Governors State University

Towards An Integrated Model Of The Mental Lexicon, Natawut Monaikul

All Student Theses

Several models have been proposed attempting to describe the mental lexicon-the abstract organization of words in the human mind. Numerous studies have shown that by representing the mental lexicon as a network, where nodes represent words and edges connect similar words using a metric based on some word feature, a small-world structure is formed. This property, pervasive in many real-world networks, implies processing efficiency and resiliency to node deletion within the system, explaining the need for such a robust network as the mental lexicon. However, each model considered a single word feature at a time, such as semantic or phonological …


Memory Dynamics In Attractor Networks, Guoqi LI, Kiruthika RAMANATHAN, Ning NING, Luping SHI, Changyun WEN 2015 Singapore Management University

Memory Dynamics In Attractor Networks, Guoqi Li, Kiruthika Ramanathan, Ning Ning, Luping Shi, Changyun Wen

Research Collection School Of Computing and Information Systems

As can be represented by neurons and their synaptic connections, attractor networks are widely believed to underlie biological memory systems and have been used extensively in recent years to model the storage and retrieval process of memory. In this paper, we propose a new energy function, which is nonnegative and attains zero values only at the desired memory patterns. An attractor network is designed based on the proposed energy function. It is shown that the desired memory patterns are stored as the stable equilibrium points of the attractor network. To retrieve a memory pattern, an initial stimulus input is presented …


Trust Based Privacy Policy Enforcement In Cloud Computing, Karthick Ramachandran 2015 The University of Western Ontario

Trust Based Privacy Policy Enforcement In Cloud Computing, Karthick Ramachandran

Electronic Thesis and Dissertation Repository

Cloud computing offers opportunities for organizations to reduce IT costs by using the computation and storage of a remote provider. Despite the benefits offered by cloud computing paradigm, organizations are still wary of delegating their computation and storage to a cloud service provider due to trust concerns. The trust issues with the cloud can be addressed by a combination of regulatory frameworks and supporting technologies. Privacy Enhancing Technologies (PET) and remote attestation provide the technologies for addressing the trust concerns. PET provides proactive measures through cryptography and selective dissemination of data to the client. Remote attestation mechanisms provides reactive measures …


Effectiveness Of Cloud Services For Scientific And Vod Applications, Dilip Kumar Krishnappa 2015 University of Massachusetts Amherst

Effectiveness Of Cloud Services For Scientific And Vod Applications, Dilip Kumar Krishnappa

Doctoral Dissertations

Cloud platforms have emerged as the primary data warehouse for a variety of applications, such as DropBox, iCloud, Google Music, etc. These applications allow users to store data in the cloud and access it from anywhere in the world. Commercial clouds are also well suited for providing high-end servers for rent to execute applications that require computation resources sporadically. Cloud users only pay for the time they actually use the hardware and the amount of data that is transmitted to and from the cloud, which has the potential to be more cost effective than purchasing, hosting, and maintaining dedicated hardware. …


An Overview Of The Openorbiter Autonomous Operating Software, Dayln Limesand, Timothy Whitney, Jeremy Straub, Ronald Marsh 2015 SelectedWorks

An Overview Of The Openorbiter Autonomous Operating Software, Dayln Limesand, Timothy Whitney, Jeremy Straub, Ronald Marsh

Jeremy Straub

The OpenOrbiter spacecraft aims to demonstrate the efficacy of the Open Prototype for Educational Nanosats (OPEN) framework. Software is an important part of this framework. This paper discusses the operating software for the spacecraft (which runs on top of the Linux operating system to command spacecraft operations). It presents an overview of this software and then pays particular attention to the aspects of software design that enable onboard autonomy. It also discusses the messaging scheme that is used onboard and the testing and validation plan. Finally, it discusses system extensibility, before concluding.


Leading Undergraduate Students To Big Data Generation, Jianjun Yang, Ju Shen 2015 University of North Georgia

Leading Undergraduate Students To Big Data Generation, Jianjun Yang, Ju Shen

Computer Science Faculty Publications

People are facing a flood of data today. Data are being collected at unprecedented scale in many areas, such as networking, image processing, virtualization, scientific computation, and algorithms. The huge data nowadays are called Big Data. Big data is an all encompassing term for any collection of data sets so large and complex that it becomes difficult to process them using traditional data processing applications. In this article, the authors present a unique way which uses network simulator and tools of image processing to train students abilities to learn, analyze, manipulate, and apply Big Data. Thus they develop students hands-on …


A Web-Based Temperature Monitoring System For The College Of Arts And Letters, Rigoberto Solorio 2015 California State University - San Bernardino

A Web-Based Temperature Monitoring System For The College Of Arts And Letters, Rigoberto Solorio

Electronic Theses, Projects, and Dissertations

In general, server rooms have restricted access requiring that staff possess access codes, keys, etc. Normally, only administrators are provided access to protect the physical hardware and the data stored in the servers. Servers also have firewalls to restrict outsiders from accessing them via the Internet. Servers also cost a lot of money. For this reason, server rooms also need to be protected against overheating. This will prolong the lifecycle of the units and can prevent data loss from hardware failure.

The California State University San Bernardino (CSUSB), Specifically the College of Arts and Letters server room has faced power …


Smart Data - How You And I Will Exploit Big Data For Personalized Digital Health And Many Other Activities, Amit P. Sheth 2015 Wright State University - Main Campus

Smart Data - How You And I Will Exploit Big Data For Personalized Digital Health And Many Other Activities, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.


Hole Detection And Shape-Free Representation And Double Landmarks Based Geographic Routing In Wireless Sensor Networks, Jianjun Yang, Zongming Fei, Ju Shen 2015 University of North Georgia

Hole Detection And Shape-Free Representation And Double Landmarks Based Geographic Routing In Wireless Sensor Networks, Jianjun Yang, Zongming Fei, Ju Shen

Computer Science Faculty Publications

In wireless sensor networks, an important issue of geographic routing is “local minimum” problem, which is caused by a “hole” that blocks the greedy forwarding process. Existing geographic routing algorithms use perimeter routing strategies to find a long detour path when such a situation occurs. To avoid the long detour path, recent research focuses on detecting the hole in advance, then the nodes located on the boundary of the hole advertise the hole information to the nodes near the hole. Hence the long detour path can be avoided in future routing. We propose a heuristic hole detecting algorithm which identifies …


On Using Synthetic Social Media Stimuli In An Emergency Preparedness Functional Exercise, Andrew Hampton, Shreyansh Bhatt, Gary Alan Smith, Jeremy S. Brunn, Hemant Purohit, Valerie L. Shalin, John M. Flach, Amit P. Sheth 2015 Wright State University - Main Campus

On Using Synthetic Social Media Stimuli In An Emergency Preparedness Functional Exercise, Andrew Hampton, Shreyansh Bhatt, Gary Alan Smith, Jeremy S. Brunn, Hemant Purohit, Valerie L. Shalin, John M. Flach, Amit P. Sheth

Kno.e.sis Publications

This paper details the creation and use of a massive (over 32,000 messages) artificially constructed 'Twitter' microblog stream for a regional emergency preparedness functional exercise. By combining microblog conversion, manual production, and a control set, we created a web based information stream providing valid, misleading, and irrelevant information to public information officers (PIOs) representing hospitals, fire departments, the local Red Cross, and city and county government officials. PIOs searched, monitored, and (through conventional channels) verified potentially actionable information that could then be redistributed through a personalized screen name. Our case study of a key PIO reveals several capabilities that social …


Exposing Potential Privacy Issues With Ipv6 Address Construction, Clinton Carpene, Andrew Woodward 2015 Edith Cowan University

Exposing Potential Privacy Issues With Ipv6 Address Construction, Clinton Carpene, Andrew Woodward

Clinton Carpene

The usage of 128 bit addresses with hexadecimal representation in IPv6 poses significant potential privacy issues. This paper discusses the means of allocating IPv6 addresses, along with the implications each method may have upon privacy in different usage scenarios. The division of address space amongst the global registries in a hierarchal fashion can provide geographical information about the location of an address, and its originating device. Many IPv6 address configuration methods are available, including DHCPv6, SLAAC (with or without privacy extensions), and Manual assignment. These assignment techniques are dissected to expose the identifying characteristics of each technique. It is seen …


On Static And Dynamic Partitioning Behavior Of Large-Scale Networks, Zhongmei Yao, Derek Leonard, Xiaoming Wang, Dmitri Loguinov 2015 University of Dayton

On Static And Dynamic Partitioning Behavior Of Large-Scale Networks, Zhongmei Yao, Derek Leonard, Xiaoming Wang, Dmitri Loguinov

Zhongmei Yao

In this paper, we analyze the problem of network disconnection in the context of large-scale P2P networks and understand how both static and dynamic patterns of node failure affect the resilience of such graphs. We start by applying classical results from random graph theory to show that a large variety of deterministic and random P2P graphs almost surely (i.e., with probability 1 − o(1)) remain connected under random failure if and only if they have no isolated nodes. This simple, yet powerful, result subsequently allows us to derive in closed-form the probability that a P2P network develops isolated nodes, and …


Residual-Based Measurement Of Peer And Link Lifetimes In Gnutella Networks, Xiaoming Wang, Zhongmei Yao, Dmitri Loguinov 2015 Texas A & M University - College Station

Residual-Based Measurement Of Peer And Link Lifetimes In Gnutella Networks, Xiaoming Wang, Zhongmei Yao, Dmitri Loguinov

Zhongmei Yao

Existing methods of measuring lifetimes in P2P systems usually rely on the so-called create-based method (CBM), which divides a given observation window into two halves and samples users "created" in the first half every Delta time units until they die or the observation period ends. Despite its frequent use, this approach has no rigorous accuracy or overhead analysis in the literature. To shed more light on its performance, we flrst derive a model for CBM and show that small window size or large Delta may lead to highly inaccurate lifetime distributions. We then show that create-based sampling exhibits an inherent …


On Node Isolation Under Churn In Unstructured P2p Networks With Heavy-Tailed Lifetimes, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov 2015 University of Dayton

On Node Isolation Under Churn In Unstructured P2p Networks With Heavy-Tailed Lifetimes, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov

Zhongmei Yao

Previous analytical studies [12], [18] of unstructured P2P resilience have assumed exponential user lifetimes and only considered age-independent neighbor replacement. In this paper, we overcome these limitations by introducing a general node-isolation model for heavy-tailed user lifetimes and arbitrary neighbor-selection algorithms. Using this model, we analyze two age-biased neighbor-selection strategies and show that they significantly improve the residual lifetimes of chosen users, which dramatically reduces the probability of user isolation and graph partitioning compared to uniform selection of neighbors. In fact, the second strategy based on random walks on age-weighted graphs demonstrates that for lifetimes with infinite variance, the system …


Modeling Heterogeneous User Churn And Local Resilience Of Unstructured P2p Networks, Zhongmei Yao, Derek Leonard, Dmitri Loguinov, Xiaoming Wang 2015 University of Dayton

Modeling Heterogeneous User Churn And Local Resilience Of Unstructured P2p Networks, Zhongmei Yao, Derek Leonard, Dmitri Loguinov, Xiaoming Wang

Zhongmei Yao

Previous analytical results on the resilience of unstructured P2P systems have not explicitly modeled heterogeneity of user churn (i.e., difference in online behavior) or the impact of in-degree on system resilience. To overcome these limitations, we introduce a generic model of heterogeneous user churn, derive the distribution of the various metrics observed in prior experimental studies (e.g., lifetime distribution of joining users, joint distribution of session time of alive peers, and residual lifetime of a randomly selected user), derive several closed-form results on the transient behavior of in-degree, and eventually obtain the joint in/out degree isolation probability as a simple …


Link Lifetimes And Randomized Neighbor Selection In Dhts, Zhongmei Yao, Dmitri Loguinov 2015 University of Dayton

Link Lifetimes And Randomized Neighbor Selection In Dhts, Zhongmei Yao, Dmitri Loguinov

Zhongmei Yao

Several models of user churn, resilience, and link lifetime have recently appeared in the literature [12], [13], [34], [35]; however, these results do not directly apply to classical Distributed Hash Tables (DHTs) in which neighbor replacement occurs not only when current users die, but also when new user arrive into the system, and where replacement choices are often restricted to the successor of the failed zone in the DHT space. To understand neighbor churn in such networks, this paper proposes a simple, yet accurate, model for capturing link dynamics in structured P2P systems and obtains the distribution of link lifetimes …


Residual-Based Estimation Of Peer And Link Lifetimes In P2p Networks, Xiaoming Wang, Zhongmei Yao, Dmitri Loguinov 2015 Texas A & M University - College Station

Residual-Based Estimation Of Peer And Link Lifetimes In P2p Networks, Xiaoming Wang, Zhongmei Yao, Dmitri Loguinov

Zhongmei Yao

Existing methods of measuring lifetimes in P2P systems usually rely on the so-called Create-BasedMethod (CBM), which divides a given observation window into two halves and samples users ldquocreatedrdquo in the first half every Delta time units until they die or the observation period ends. Despite its frequent use, this approach has no rigorous accuracy or overhead analysis in the literature. To shed more light on its performance, we first derive a model for CBM and show that small window size or large Delta may lead to highly inaccurate lifetime distributions. We then show that create-based sampling exhibits an inherent tradeoff …


Robust Lifetime Measurement In Large-Scale P2p Systems With Non-Stationary Arrivals, Xiaoming Wang, Zhongmei Yao, Yueping Zhang, Dmitri Loguinov 2015 Texas A & M University - College Station

Robust Lifetime Measurement In Large-Scale P2p Systems With Non-Stationary Arrivals, Xiaoming Wang, Zhongmei Yao, Yueping Zhang, Dmitri Loguinov

Zhongmei Yao

Characterizing user churn has become an important topic in studying P2P networks, both in theoretical analysis and system design. Recent work has shown that direct sampling of user lifetimes may lead to certain bias (arising from missed peers and round-off inconsistencies) and proposed a technique that estimates lifetimes based on sampled residuals. In this paper, however, we show that under non-stationary arrivals, which are often present in real systems, residual-based sampling does not correctly reconstruct user lifetimes and suffers a varying degree of bias, which in some cases makes estimation completely impossible. We overcome this problem using two contributions: a …


Stochastic Analysis Of Horizontal Ip Scanning, Derek Leonard, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov 2015 Texas A & M University - College Station

Stochastic Analysis Of Horizontal Ip Scanning, Derek Leonard, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov

Zhongmei Yao

Intrusion Detection Systems (IDS) have become ubiquitous in the defense against virus outbreaks, malicious exploits of OS vulnerabilities, and botnet proliferation. As attackers frequently rely on host scanning for reconnaissance leading to penetration, IDS is often tasked with detecting scans and preventing them. However, it is currently unknown how likely an IDS is to detect a given Internet-wide scan pattern and whether there exist sufficiently fast scan techniques that can remain virtually undetectable at large-scale. To address these questions, we propose a simple analytical model for the window-expiration rules of popular IDS tools (i.e., Snort and Bro) and utilize a …


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