Computer Sciences Commons^™

On The K-Mer Frequency Spectra Of Organism Genome And Proteome Sequences With A Preliminary Machine Learning Assessment Of Prime Predictability, Nathan O. Schmidt

Boise State University Theses and Dissertations

A regular expression and region-specific filtering system for biological records at the National Center for Biotechnology database is integrated into an object oriented sequence counting application, and a statistical software suite is designed and deployed to interpret the resulting k-mer frequencies|with a priority focus on nullomers. The proteome k-mer frequency spectra of ten model organisms and the genome k-mer frequency spectra of two bacteria and virus strains for the coding and non-coding regions are comparatively scrutinized. We observe that the naturally-evolved (NCBI/organism) and the artificially-biased (randomly-generated) sequences exhibit a clear deviation from the artificially-unbiased (randomly-generated) histogram distributions. …

A Mathematical Framework For Volume Modeling And Simulation, Brandon Pelfrey

All Theses

Rendering, modeling, and simulating processes in spatially-varying media are complex tasks
which typically require tedious mathematical derivations and long development and programming.
In this thesis, a framework is presented which allows for fast and casual exploration of ideas for
volume-based simulation and modeling. Several applications of the framework are shown, including
the simulation of fluid dynamics for computer graphics applications. A procedure for automatically
generating OpenCL code from these is given, along with rudimentary examples.

Hedonic Valuation Of Online Game Participation, Robert J. Kauffman, Kwansoo Kim, Byungjoon Yoo

Research Collection School Of Computing and Information Systems

We use hedonic valuation to establish a basis for valuing the time a user participates in an online gaming community. We distinguish between utilitarian and hedonic value. Our application involves elements of both utilitarian and hedonic value, however, the latter is much more important. We use an extensive data set involving a massive multi-player online role-playing game (MMORPG) from Korea. We specify and test econometric models that reflect the appropriate empirical structure for the setting, based on information about the players and the activities they engage in. The results permit us to estimate the hedonic value in monetary terms for …

From Clickstreams To Searchstreams: Search Network Graph Evidence From A B2b E-Market, Mei Lin, M. F. Lin, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

Consumers in e-commerce acquire information through search engines, yet to date there has been little empirical study on how users interact with the results produced by search engines. This is analogous to, but different from, the ever-expanding research on clickstreams, where users interact with static web pages. We propose a new network approach to analyzing search engine server log data. We call this searchstream data. We create graph representations based on the web pages that users traverse as they explore the search results that their use of search engines generates. We then analyze the graph-level properties of these search network …

Valuation Of Benchmark Provisions On It Services Contracts, Robert J. Kauffman, Ryan Sougstad

Research Collection School Of Computing and Information Systems

Information technology (IT) services are often subject to downward price pressures due to improvements in technology and business processes in a competitive market. When clients enter into IT services contracts, they are faced with the future risk that their services will be overpriced relative to the broader IT services market. To mitigate this risk, clients often add benchmark provisions, whereby a neutral third party assesses the prevailing market price for services. It will support fair price adjustments if the market prices are lower than the current prices. We model the decision to benchmark in order to provide managerial information on …

Dynamic Stochastic Orienteering Problems For Risk-Aware Applications, Hoong Chuin Lau, William Yeoh, Pradeep Varakantham, Duc Thien Nguyen

Research Collection School Of Computing and Information Systems

Orienteering problems (OPs) are a variant of the well-known prize-collecting traveling salesman problem, where the salesman needs to choose a subset of cities to visit within a given deadline. OPs and their extensions with stochastic travel times (SOPs) have been used to model vehicle routing problems and tourist trip design problems. However, they suffer from two limitations travel times between cities are assumed to be time independent and the route provided is independent of the risk preference (with respect to violating the deadline) of the user. To address these issues, we make the following contributions: We introduce (1) a dynamic …

A Secure And Efficient Discovery Service System In Epcglobal Network, Jie Shi, Yingjiu Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

In recent years, the Internet of Things (IOT) has drawn considerable attention from the industrial and research communities. Due to the vast amount of data generated through IOT devices and users, there is an urgent need for an effective search engine to help us make sense of this massive amount of data. With this motivation, we begin our initial works on developing a secure and efficient search engine (SecDS) based on EPC Discovery Services (EPCDS) for EPCglobal network, an integral part of IOT. SecDS is designed to provide a bridge between different partners of supply chains to share information while …

Modeling Concept Dynamics For Large Scale Music Search, Jialie Shen, Hwee Hwa Pang, Meng Wang, Shuicheng Yan

Research Collection School Of Computing and Information Systems

Continuing advances in data storage and communication technologies have led to an explosive growth in digital music collections. To cope with their increasing scale, we need effective Music Information Retrieval (MIR) capabilities like tagging, concept search and clustering. Integral to MIR is a framework for modelling music documents and generating discriminative signatures for them. In this paper, we introduce a multimodal, layered learning framework called DMCM. Distinguished from the existing approaches that encode music as an ensemble of order-less feature vectors, our framework extracts from each music document a variety of acoustic features, and translates them into low-level encodings over …

Consumer Micro-Behavior And Tv Viewership Patterns: Data Analytics For The Two-Way Set-Top Box, Ray M. Chang, Robert J. Kauffman, Insoo Son

Research Collection School Of Computing and Information Systems

Consumer behavior patterns related to home digital media use are changing due to technological innovations. We examine them in the presence of two-way cable television (CATV) settop boxes. They permit viewers to change channels, switch to the Internet, and order paid programming, among other functions. We focus on micro-level data that are generated from consumer CATV viewing behavior. We capture clickstreams of channel-changing behavior when consumer use a remote control handset to interact with the set-top box in their home. We explore a variety of data analytics results that characterize patterns of consumer channel-switching behavior, as a basis for suggesting …

Collective Churn Prediction In Social Network, Richard J. Oentaryo, Ee-Peng Lim, David Lo, Feida Zhu, Philips K. Prasetyo

Research Collection School Of Computing and Information Systems

In service-based industries, churn poses a significant threat to the integrity of the user communities and profitability of the service providers. As such, research on churn prediction methods has been actively pursued, involving either intrinsic, user profile factors or extrinsic, social factors. However, existing approaches often address each type of factors separately, thus lacking a comprehensive view of churn behaviors. In this paper, we propose a new churn prediction approach based on collective classification (CC), which accounts for both the intrinsic and extrinsic factors by utilizing the local features of, and dependencies among, individuals during prediction steps. We evaluate our …

An Approach In Defining Information Assurance Patterns Based On Security Ontology And Meta-Modeling, Aniruddha Bhaumik

Student Work

We have to realizing that information is the most important asset. We are at a stage where the information is not only becoming a valuable asset but also the volume of it is increasing at a rapid rate. Modern Enterprises are now working hard to ensure the proper storage, availability and integrity of this information. So we are having the information assurance discipline which is focusing on preservation of information confidentiality, integrity and availability in all of the informations’ various state. We have the information security patterns. But we have to realize that we have to design the Information assurance …

A Semantic Approach For Keyword Search On Relational Databases, Rajvardhan Patil

Student Work

Today’s search engines make it easier for the user to browse and query the online available data. But when it comes to structured data, the queries have to be structured too, in order to retrieve the data. This makes it difficult for novice users, with no knowledge of the underlying schema or query language, to access the relational data. Therefore, to query the structured data in an unstructured language of web, there is a need to map the user keyword queries to their equivalent SQL format. This research is intended to bridge the gap by introducing a framework named STRUCT. …

Understanding The Adaptive Use Of Virtual World Technology Capabilities And Trust In Virtual Teams, Dawn Owens

Student Work

In an environment of global competition and constant technological change, the use of virtual teams has become commonplace for many organizations. Virtual team members are geographically and temporally dispersed, experience cultural diversity, and lack shared social context and face-to-face encounters considered as irreplaceable for building and maintaining trust. Previous research has established that higher trusting teams have better cooperation and experience improved outcomes; however, trust building in a team where members are from different backgrounds, time zones and cultures is a considerable challenge. Virtual teams (VTs) rely heavily on technology to facilitate coordination, communication, and control in the team. One …

Sampling And Ontologically Pooling Web Images For Visual Concept Learning, Shiai Zhu, Chong-Wah Ngo, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Sufficient training examples are essential for effective learning of semantic visual concepts. In practice, however, acquiring noise-free training examples has always been expensive. Recently the rapid popularization of social media websites, such as Flickr, has made it possible to collect training exemplars without human assistance. This paper proposes a novel and efficient approach to collect training samples from the noisily tagged Web images for visual concept learning, where we try to maximize two important criteria, relevancy and coverage, of the automatically generated training sets. For the former, a simple method named semantic field is introduced to handle the imprecise and …

Uncertain Congestion Games With Assorted Human Agent Populations, Asrar Ahmed, Pradeep Reddy Varakantham, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

Congestion games model a wide variety of real-world resource congestion problems, such as selfish network routing, traffic route guidance in congested areas, taxi fleet optimization and crowd movement in busy areas. However, existing research in congestion games assumes: (a) deterministic movement of agents between resources; and (b) perfect rationality (i.e. maximizing their own expected value) of all agents. Such assumptions are not reasonable in dynamic domains where decision support has to be provided to humans. For instance, in optimizing the performance of a taxi fleet serving a city, movement of taxis can be involuntary or nondeterministic (decided by the specific …

The Patrol Scheduling Problem, Hoong Chuin Lau, Aldy Gunawan

Research Collection School Of Computing and Information Systems

This paper presents the problem of scheduling security teams to patrol a mass rapid transit rail network of a large urban city. The main objective of patrol scheduling is to deploy security teams to stations at varying time periods of the network subject to rostering as well as security-related constraints. We present a mathematical programming model for this problem. We then discuss the aspect of injecting randomness by varying the start times, the break times for each team as well as the number of visits required for each station according to their reported vulnerability. Finally, we present results for the …

Routing Over The Interplanetary Internet, Joyeeta Mukherjee

School of Computing: Dissertations, Theses, and Student Research

Future space exploration demands a Space Network that will be able to connect spacecrafts with one another and in turn with Earth's terrestrial Internet and hence efficiently transfer data back and forth. The feasibility of this technology would enable common people to directly access telemetric data from distant planets and satellites. The concept of an Interplanetary Internet (IPN) is only in its incubation stage and considerable amount of common standards and research is required before widespread deployment can occur to make IPN feasible.

We provide a comprehensive survey that presents a picture of the current space networking technologies and architectures. …

Statistical Software Properties: Definition, Inference And Monitoring, Javier A. Darsie

School of Computing: Dissertations, Theses, and Student Research

Software properties define how software systems should operate. Specifying correct properties, however, can be difficult and expensive as it requires deep knowledge of the system's expected behavior and the environment in which it operates. Automated analysis techniques to infer properties from code or code executions can mitigate that cost, but are still unable to go beyond state properties and the simplest patterns of temporal properties. This limitation renders properties that sacrifice fault detection power.

To address this problem, we introduce a new type of software properties called \textit{statistical properties}, which characterize significant statistical relationships among the values of variables across …

Non-Blocking Concurrent Operations On Heap, Mahesh Acharya

UNLV Theses, Dissertations, Professional Papers, and Capstones

We present a non-blocking implementation for the concurrent Heap data structure in the asynchronous shared memory system. The system may be a traditional one with a single processor with multiple threads, or it may be the one with multiple processors each possibly with multiple threads. Our implementation supports readMin, deleteMin, and insert operations on the heap. The deleteMin and insert operations are non-blocking operations, whereas the readMin is wait-free. One easy approach of using a heap in multi-threading environment could be by locking the entire heap before performing any operation. This would make the implementation very slow to have any …

Degree Constrained Triangulation, Roshan Gyawali

UNLV Theses, Dissertations, Professional Papers, and Capstones

Triangulation of simple polygons or sets of points in two dimensions is a widely investigated problem in computational geometry. Some researchers have considered variations of triangulation problems that include minimum weight triangulation, de-launay triangulation and triangulation refinement. In this thesis we consider a constrained version of the triangulation problem that asks for triangulating a given domain (polygon or point sites) so that the resulting triangulation has an increased number of even degree vertices. This problem is called Degree Constrained Triangulation (DCT). We propose four algorithms to solve DCT problems. We also present experimental results based on the implementation of the …

Modeling Of Cellular Automata And Agent-Based Complex Systems, Sara Pallekonda

UNLV Theses, Dissertations, Professional Papers, and Capstones

The term 'complex systems' may sound terrifying whenever you come across it as it depicts an overall collective structure which indeed can live up to its name; but when you comprehend the system at its fundamental level by stripping to its simpler multiple- interacting individual parts, the insights it provides may be used to describe and understand different problems ranging from atomic particles to the economics of societies and evolution. The simple laws can be used to simulate the behaviors of disparate complex systems.

In this thesis, a brief study is done emulating few such complex systems through programming techniques …

Eliciting A Sensemaking Process From Verbal Protocols Of Reverse Engineers, Adam R. Bryant, Robert F. Mills, Gilbert L. Peterson, Michael R. Grimaila

Faculty Publications

A process of sensemaking in reverse engineering was elicited from verbal protocols of reverse engineers as they investigated the assembly code of executable programs. Four participants were observed during task performance and verbal protocols were collected and analyzed from two of the participants to determine their problem-solving states and characterize likely transitions between those states. From this analysis, a high-level process of sensemaking is described which represents hypothesis generation and information-seeking behaviors in reverse engineering within a framework of goal-directed planning. Future work in validation and application of the process is discussed.

Online Feature Selection For Mining Big Data, Steven C. H. Hoi, Jialei Wang, Peilin Zhao, Rong Jin

Research Collection School Of Computing and Information Systems

Most studies of online learning require accessing all the attributes/features of training instances. Such a classical setting is not always appropriate for real-world applications when data instances are of high dimensionality or the access to it is expensive to acquire the full set of attributes/features. To address this limitation, we investigate the problem of Online Feature Selection (OFS) in which the online learner is only allowed to maintain a classifier involved a small and fixed number of features. The key challenge of Online Feature Selection is how to make accurate prediction using a small and fixed number of active features. …

Confidence-Aware Graph Regularization With Heterogeneous Pairwise Features, Yuan Fang, Bo-June Paul Hsu, Kevin Chen-Chuan Chang

Research Collection School Of Computing and Information Systems

Conventional classification methods tend to focus on features of individual objects, while missing out on potentially valuable pairwise features that capture the relationships between objects. Although recent developments on graph regularization exploit this aspect, existing works generally assume only a single kind of pairwise feature, which is often insufficient. We observe that multiple, heterogeneous pairwise features can often complement each other and are generally more robust in modeling the relationships between objects. Furthermore, as some objects are easier to classify than others, objects with higher initial classification confidence should be weighed more towards classifying related but more ambiguous objects, an …

Improving Patient Flow In Emergency Department Through Dynamic Priority Queue, Kar Way Tan, Chao Wang, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Most queuing problems are based on FIFO, LIFO, or static priority queues; very few address dynamic priority queues. In this paper, we present a case in a hospital’s emergency department (ED) where the queuing process can be modeled as a time-varying M/M/s queue with re-entrant patients. In order to improve patient flow in the department, we propose the use of a dynamic priority queue to dispatch patients to consultation with doctors. We test our proposed model using simulation and our experimental results show that a dynamic priority queue is effective in reducing the length of stay (LOS) of patients and …

Measurement-Driven Performance Analysis Of Indoor Femtocellular Networks, Trung-Tuan Luong, Vigneshwaran Subbaraju, Archan Misra, Srinivasan Seshan

Research Collection School Of Computing and Information Systems

This paper describes initial empirical studies, performed on a 6-node 3G indoor femtocellular testbed, that investigate the impact of pedestrian mobility on network parameters, such as handoff behavior and data throughput. The studies establish that, owing to the small radii of cells, even modest changes in movement speed can have disproportionately large impact on handoff patterns and network throughput. By also revealing a strong temporal dependency effect, the studies motivate the need for algorithms to accurately predict RF signal strength distributions in dynamic indoor environments. We present such an RF prediction algorithm, based on crowd-sourced signal strength readings, and show …

Shortest Path Computation With No Information Leakage, Kyriakos Mouratidis, Man Lung Yiu

Research Collection School Of Computing and Information Systems

Shortest path computation is one of the most common queries in location-based services (LBSs). Although particularly useful, such queries raise serious privacy concerns. Exposing to a (potentially untrusted) LBS the client’s position and her destination may reveal personal information, such as social habits, health condition, shopping preferences, lifestyle choices, etc. The only existing method for privacy-preserving shortest path computation follows the obfuscation paradigm; it prevents the LBS from inferring the source and destination of the query with a probability higher than a threshold. This implies, however, that the LBS still deduces some information (albeit not exact) about the client’s location …

Bidder Behaviors In Repeated B2b Procurement Auctions, Jong Han Park, Jae Kyu Lee, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

B2B auctions play a key role in a firm's procurement process. Even though it is known that repetition is a key characteristic of procurement auctions, traditional auctioneers typically have not put in place a suitable mechanism that supports repetitive auctions effectively. In this paper, we empirically investigate what has taken place in repeated procurement auctions based on real world data from a major outsourcing company of MRO (Maintenance, Repair and Operations) items in Korea. From this empirical study, we discovered the followings. First, we discovered that the repeated bidders contribute majority of all bids, and that the number of new …

Adaptive Display Power Management For Oled Displays, Kiat Wee Tan, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Mobile gaming has become increasingly popular in the past few years with the proliferation of smartphones that have the increased CPU, memory, and network (3.5G etc.) capabilities to support a vast range of interesting games. In addition, these phones also have high quality displays, such as Organic Light Emitting Diodes (OLED) displays, that allow the intricate details in games to be shown in vivid detail to end users. Unfortunately, these displays tend to consume a lot of energy which in turn limits the amount of time that a user can spend actually playing games on these devices. In this paper, …

Adapting Video Delivery Based On Motion Triggered Visual Attention, Hari Kalva, V. Adzic, Lai-Tee Cheok

Research Collection School Of Computing and Information Systems

Cues from human visual system (HVS) can be used for further optimization of compression in modern hybrid video coding platforms. We present work that explores and exploits motion related attentional limitations. Algorithms for exploiting motion triggered attention were developed and compared with MPEG AVC/H.264 encoder with various settings for different bitrate levels. For the sequences with high motion activity our algorithm provides up to 8% bitrate savings.