Computer Sciences Commons^™

Quasinovo: Algorithms For De Novo Peptide Sequencing, James Paul Cleveland

Theses and Dissertations

High-throughput proteomics analysis involves the rapid identification and characterization of large sets of proteins in complex biological samples. Tandem mass spectrometry (MS/MS) has become the leading approach for the experimental identification of proteins. Accurate analysis of the data produced is a computationally challenging process that relies on a complex understanding of molecular dynamics, signal processing, and pattern classification. In this work we address these modeling and classification problems, and introduce an additional data-driven evolutionary information source into the analysis pipeline.

The particular problem being solved is peptide sequencing via MS/MS. The objective in solving this problem is to decipher the …

Hyperspectral Image Classification Using A Spectral-Spatial Sparse Coding Model, Ender Oguslu, Guoqing Zhou, Jiang Li, Lorenzo Bruzzone (Ed.)

Electrical & Computer Engineering Faculty Publications

We present a sparse coding based spectral-spatial classification model for hyperspectral image (HSI) datasets. The proposed method consists of an efficient sparse coding method in which the l₁/l_q regularized multi-class logistic regression technique was utilized to achieve a compact representation of hyperspectral image pixels for land cover classification. We applied the proposed algorithm to a HSI dataset collected at the Kennedy Space Center and compared our algorithm to a recently proposed method, Gaussian process maximum likelihood (GP-ML) classifier. Experimental results show that the proposed method can achieve significantly better performances than the GP-ML classifier when training data …

Prevention And Detection Of Intrusions In Wireless Sensor Networks, Ismail Butun

USF Tampa Graduate Theses and Dissertations

Wireless Sensor Networks (WSNs) continue to grow as one of the most exciting and challenging research areas of engineering. They are characterized by severely constrained computational and energy

resources and also restricted by the ad-hoc network operational

environment. They pose unique challenges, due to limited power

supplies, low transmission bandwidth, small memory sizes and limited energy. Therefore, security techniques used in traditional networks cannot be directly adopted. So, new ideas and approaches are needed, in order to increase the overall security of the network. Security applications in such resource constrained WSNs with minimum overhead provides significant challenges, and is the …

Toward More Composable Software-Security Policies: Tools And Techniques, Daniel Lomsak

USF Tampa Graduate Theses and Dissertations

Complex software-security policies are dicult to specify, understand, and update. The

same is true for complex software in general, but while many tools and techniques exist

for decomposing complex general software into simpler reusable modules (packages, classes,

functions, aspects, etc.), few tools exist for decomposing complex security policies into simpler

reusable modules. The tools that do exist for modularizing policies either encapsulate

entire policies as atomic modules that cannot be decomposed or allow ne-grained policy

modularization but require expertise to use correctly.

This dissertation presents a policy-composition tool called PoliSeer [27, 26] and the

PoCo policy-composition software-security language. PoliSeer is …

Automated Color Calibration Of Display Devices, Andrew Shulman

All Computer Science and Engineering Research

If you compare two identical images on two different monitors, they will likely appear different. Every display device is supposed to adhere to a particular set of standards regulating the color and intensity of the image it outputs. However, in practice, very few do. Color calibration is the practice of modifying the signal path such that the colors produced more closely match reference standards. This is essential for graphics professionals who are mastering original content. They must ensure that the source material appears correct when viewed on a reference monitor. When viewed on a consumer panel, however, some error will …

Efficient Parallel Real-Time Upsampling Of Ultrasound Vectors, William D. Richard Ph.D.

All Computer Science and Engineering Research

Upsampling is required prior to the summation step in most receive digital beamforming implementations to produce an accurate summed RF line or vector. This is true in both annular and linear array systems where receive echos are digitized first and then time delayed in the digital domain to achieve proper signal alignment. The efficient, parallel, real-time upsampling circuit presented here produces M upsampled values per ADC clock, where M is the desired upsampling factor. A circuit implementation that upsamples by a factor of M=4 is presented as an example of the more general technique.

Adding Data Parallelism To Streaming Pipelines For Throughput Optimization, Peng Li, Kunal Agrawal, Jeremy Buhler, Roger D. Chamberlain

All Computer Science and Engineering Research

The streaming model is a popular model for writing high-throughput parallel applications. A streaming application is represented by a graph of computation stages that communicate with each other via FIFO channels. In this report, we consider the problem of mapping streaming pipelines — streaming applications where the graph is a linear chain — in order to maximize throughput. In a parallel setting, subsets of stages, called components can be mapped onto different computing resources. The through-put of an application is determined by the throughput of the slowest component. Therefore, if some stage is much slower than others, then it may …

Creating Scalable Location-Based Games: Lessons From Geocaching, Carman Neustaedter, Anthony Tang, Tejinder K. Judge

Research Collection School Of Computing and Information Systems

Location-based games seek to move computer gaming out from behind the PC and into the “real world” of cities, streets, parks, and other locations. This real-world physicality makes the experience fun for game players, yet it brings the unique challenge of creating and orchestrating such a game. That is, location-based games are often difficult to create, grow, and maintain over long periods of time. Our research investigates how location-based games can be designed to overcome this challenge of scalability. We studied the well-established location-based game of Geocaching through active participation and an online survey to better understand how it has …

Moving Object Detection With Laser Scanners, Christoph Mertz, Luis E. Navarro-Serment, Robert Maclachlan, Paul Rybski, Aaron Steinfeld, Arne Suppe, Christopher Urmson, Nicolas Vandapel, Martial Hebert, Chuck Thorpe, David Duggins, Jay Gowdy

Research Collection School Of Computing and Information Systems

The detection and tracking of moving objects is an essential task in robotics. The CMU-RI Navlab group has developed such a system that uses a laser scanner as its primary sensor. We will describe our algorithm and its use in several applications. Our system worked successfully on indoor and outdoor platforms and with several different kinds and configurations of two-dimensional and three-dimensional laser scanners. The applications vary from collision warning systems, people classification, observing human tracks, and input to a dynamic planner. Several of these systems were evaluated in live field tests and shown to be robust and reliable. (C) …

Technology Investment Decision-Making Under Uncertainty: The Case Of Mobile Payment Systems, Robert J. Kauffman, Jun Liu, Dan Ma

Research Collection School Of Computing and Information Systems

The recent launch of Google Wallet has brought the issue of technology solutions in mobile payments (m-payments) to the forefront. In deciding whether and when to adopt m-payments, senior managers in banks are concerned about uncertainties regarding future market conditions, technology standards, and consumer and merchant responses, especially their willingness to adopt. This study applies economic theory and modeling for decision-making under uncertainty to bank investments in m-payment systems technology. We assess the projected benefits and costs of investment as a continuous-time stochastic process to determine optimal investment timing. We find that the value of waiting to adopt jumps when …

Decision Support For Assorted Populations In Uncertain And Congested Environments, Pradeep Reddy Varakantham, Asrar Ahmed, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

This research is motivated by large scale problems in urban transportation and labor mobility where there is congestion for resources and uncertainty in movement. In such domains, even though the individual agents do not have an identity of their own and do not explicitly interact with other agents, they effect other agents. While there has been much research in handling such implicit effects, it has primarily assumed deterministic movements of agents. We address the issue of decision support for individual agents that are identical and have involuntary movements in dynamic environments. For instance, in a taxi fleet serving a city, …

Automated Parameter Tuning Framework For Heterogeneous And Large Instances: Case Study In Quadratic Assignment Problem, Linda Lindawati, Zhi Yuan, Hoong Chuin Lau, Feida Zhu

Research Collection School Of Computing and Information Systems

This paper is concerned with automated tuning of parameters of algorithms to handle heterogeneous and large instances. We propose an automated parameter tuning framework with the capability to provide instance-specific parameter configurations. We report preliminary results on the Quadratic Assignment Problem (QAP) and show that our framework provides a significant improvement on solutions qualities with much smaller tuning computational time.

Competition Between Software-As-A-Service Vendors, Robert J. Kauffman, Dan Ma

Research Collection School Of Computing and Information Systems

No abstract provided.

The Pricing Model Of Cloud Computing Services, Jianhui Huang, Dan Ma

Research Collection School Of Computing and Information Systems

Cloud computing service providers offer computing resource as a utility and software as a service over network. Many believe that Cloud computing is making an industry-wise paradigm shift for IT use. Besides its technique issues, the business feature of Cloud computing attracts our interests. Specifically the practice of Amazon EC2 introduces an interesting pricing scheme. Amazon provides users with virtual computing instances as a combination of interruptible service (i.e., spot instance) and uninterruptible service (i.e., on-demand and reserved instance). Spot instance is charged at a per use price which is dynamically changing over time; users of spot instance face the …

Towards Efficient Sparse Coding For Scalable Image Annotation, Junshi Huang, Hairong Liu, Jialie Shen, Shuicheng Yan

Research Collection School Of Computing and Information Systems

Nowadays, content-based retrieval methods are still the development trend of the traditional retrieval systems. Image labels, as one of the most popular approaches for the semantic representation of images, can fully capture the representative information of images. To achieve the high performance of retrieval systems, the precise annotation for images becomes inevitable. However, as the massive number of images in the Internet, one cannot annotate all the images without a scalable and flexible (i.e., training-free) annotation method. In this paper, we particularly investigate the problem of accelerating sparse coding based scalable image annotation, whose off-the-shelf solvers are generally inefficient on …

Regret Based Robust Solutions For Uncertain Markov Decision Processes, Asrar Ahmed, Pradeep Reddy Varakantham, Yossiri Adulyasak, Patrick Jaillet

Research Collection School Of Computing and Information Systems

In this paper, we seek robust policies for uncertain Markov Decision Processes (MDPs). Most robust optimization approaches for these problems have focussed on the computation of maximin policies which maximize the value corresponding to the worst realization of the uncertainty. Recent work has proposed minimax regret as a suitable alternative to the maximin objective for robust optimization. However, existing algorithms for handling minimax regret are restricted to models with uncertainty over rewards only. We provide algorithms that employ sampling to improve across multiple dimensions: (a) Handle uncertainties over both transition and reward models; (b) Dependence of model uncertainties across state, …

Business Intelligence And Analytics: Research Directions, Ee Peng Lim, Hsinchun Chen, Guoqing Chen

Research Collection School Of Computing and Information Systems

Business intelligence and analytics (BIA) is about the development of technologies, systems, practices, and applications to analyze critical business data so as to gain new insights about business and markets. The new insights can be used for improving products and services, achieving better operational efficiency, and fostering customer relationships. In this article, we will categorize BIA research activities into three broad research directions: (a) big data analytics, (b) text analytics, and (c) network analytics. The article aims to review the state-of-the-art techniques and models and to summarize their use in BIA applications. For each research direction, we will also determine …

Verifiable And Private Top-K Monitoring, Xuhua Ding, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

In a data streaming model, records or documents are pushed from a data owner, via untrusted third-party servers, to a large number of users with matching interests. The match in interest is calculated from the correlation between each pair of document and user query. For scalability and availability reasons, this calculation is delegated to the servers, which gives rise to the need to protect the privacy of the documents and user queries. In addition, the users need to guard against the eventuality of a server distorting the correlation score of the documents to manipulate which documents are highlighted to certain …

Engagingness And Responsiveness Behavior Models On The Enron Email Network And Its Application To Email Reply Order Prediction, Byung-Won On, Ee Peng Lim, Jing Jiang, Loo Nin Teow

Research Collection School Of Computing and Information Systems

In email networks, user behaviors affect the way emails are sent and replied. While knowing these user behaviors can help to create more intelligent email services, there has not been much research into mining these behaviors. In this paper, we investigate user engagingness and responsiveness as two interaction behaviors that give us useful insights into how users email one another. Engaging users are those who can effectively solicit responses from other users. Responsive users are those who are willing to respond to other users. By modeling such behaviors, we are able to mine them and to identify engaging or responsive …

A Secure Platform For Information Sharing In Epcglobal Network, Jie Shi, Yingjiu Li, Robert H. Deng, Wei He, Eng Wah Lee

Research Collection School Of Computing and Information Systems

With the rapid development of RFID technology, the EPCglobal network has drawn considerable attention from both research and industry communities, which enables supply chain partners to automatically share information and improve the visibility of supply chains. As the information shared in the EPCglobal network is usually sensitive and valuable, security mechanisms should be provided. In this paper, we aim at designing and implementing a secure information sharing platform in the EPCglobal network with a focus on authorization mechanism. We also design and implement a track and trace application based on the proposed secure platform so as to demonstrate its feasibility …

Improving Public Transit Accessibility For Blind Riders By Crowdsourcing Bus Stop Landmark Locations With Google Street View, Kotaro Hara, Shiri Azenkot, Megan Campbell, Cynthia L. Bennett, Vicki Le, Sean Pannella, Robert Moore, Kelly Minckler, Rochelle H. Ng, Jon E. Froehlich

Research Collection School Of Computing and Information Systems

Low-vision and blind bus riders often rely on known physicallandmarks to help locate and verify bus stop locations (e.g., bysearching for a shelter, bench, newspaper bin). However, there arecurrently few, if any, methods to determine this information apriori via computational tools or services. In this paper, weintroduce and evaluate a new scalable method for collecting busstop location and landmark descriptions by combining onlinecrowdsourcing and Google Street View (GSV). We conduct andreport on three studies in particular: (i) a formative interviewstudy of 18 people with visual impairments to inform the designof our crowdsourcing tool; (ii) a comparative study examiningdifferences between physical …

An Initial Study Of Automatic Curb Ramp Detection With Crowdsourced Verification Using Google Street View Images, Kotaro Hara, Jin Sun, Jonah Chazan, David Jacobs, Jin Froehlich

Research Collection School Of Computing and Information Systems

In our previous research, we examined whether minimallytrained crowd workers could find, categorize, and assesssidewalk accessibility problems using Google Street View(GSV) images. This poster paper presents a first step towardscombining automated methods (e.g., machine visionbasedcurb ramp detectors) in concert with human computationto improve the overall scalability of our approach.

Analyzing The Impact Of Cloud Services Brokers On Cloud Computing Markets, Richard D. Shang, Jianhui Huang, Yinping Yang, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

This research offers a theoretical model of brokered services and provides an analysis of their impact on the cloud computing market with risk preference-based stratification of client segments. The model structures the decision problem that clients face when they choose among spot, reserved and brokered services. Although all the three types of services do not indemnify the cloud services client against other kinds of service outages, due to changes in market demand, service interruptions occur most frequently in the spot market, and are lower when brokered services are offered, and no risk of inter-ruption is involved in reserved services. Based …

Cqarank: Jointly Model Topics And Expertise In Community Question Answering, Liu Yang, Minghui Qiu, Swapna Gottopati, Feida Zhu, Jing Jiang, Huiping Sun, Zhong Chen

Research Collection School Of Computing and Information Systems

Community Question Answering (CQA) websites, where people share expertise on open platforms, have become large repositories of valuable knowledge. To bring the best value out of these knowledge repositories, it is critically important for CQA services to know how to find the right experts, retrieve archived similar questions and recommend best answers to new questions. To tackle this cluster of closely related problems in a principled approach, we proposed Topic Expertise Model (TEM), a novel probabilistic generative model with GMM hybrid, to jointly model topics and expertise by integrating textual content model and link structure analysis. Based on TEM results, …

Sensor Feature Selection And Combination For Stress Identification Using Combinatorial Fusion, Yong Deng, Zhonghai Wu, Chao-Hsien Chu, Qixun Zhang, D. Frank Hsu

Research Collection School Of Computing and Information Systems

The identification of stressfulness under certain driving condition is an important issue for safety, security and health. Sensors and systems have been placed or implemented as wearable devices for drivers. Features are extracted from the data collected and combined to predict symptoms. The challenge is to select the feature set most relevant for stress. In this paper, we propose a feature selection method based on the performance and the diversity between two features. The feature sets selected are then combined using a combinatorial fusion. We also compare our results with other combination methods such as naïve Bayes, support vector machine, …

Not All That Glitters Is Gold: The Effect Of Attention And Blogs On The Investors' Investing Behaviors, Nan Hu, Yi Dong, Ling Liu, Lee J. Yao

Research Collection School Of Computing and Information Systems

This article investigates the relationship between a firm’s visibility in blogspaces, termed blog exposure, and the cross-sectional stock returns. We show that blog exposure is fundamentally different from the traditional media coverage, and securities with low blog exposure earn higher returns than stocks with high blog exposure. We further illustrate that such an effect is more prominent for stocks with low institutional ownership. Contrary to traditional media coverage, the return premium associated with blog exposure cannot be explained by either the illiquidity hypothesis or the investor recognition hypothesis based on the rational-agent framework. Instead, our results suggest that blog effect …

Dynamic Two-Sided Pricing Under Sequential Innovation, Mei Lin, Xiajun Pan

Research Collection School Of Computing and Information Systems

Many two-sided platforms offer innovative hardware products that improve in quality and enter the market sequentially. We analyze the impact of the decrease in the production cost on a monopoly platform owner's dynamic two-sided pricing problem, in which buyers are strategic and exert a cross-side network effect to the seller side. Our findings show that a greater decrease in cost raises the optimal price of the low-quality product and allocates more buyer-side demand to the future market. Furthermore, such decrease in cost may also lead to a higher optimal price for the future higher-quality product, given a sufficiently significant quality …

Artificial Immunity-Based Induction Motor Bearing Fault Diagnosis, Hakan Çaliş, Abdülkadi̇r Çakir, Emre Dandil

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, the artificial immunity of the negative selection algorithm is used for bearing fault detection. It is implemented in MATLAB-based graphical user interface software. The developed software uses amplitudes of the vibration signal in the time and frequency domains. Outer, inner, and ball defects in the bearings of the induction motor are detected by anomaly monitoring. The time instants of the fault occurrence and fault level are determined according to the number of activated detectors. Anomaly detection in the frequency domain is implemented by monitoring the fault indicator bearing frequencies and harmonics, calculated using the bearing dimensions and …

The Vortex Effect Of Francis Turbine In Electric Power Generation, Veli̇ Türkmenoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, the vibration effects of a vortex that occurred in high-head Francis turbines and an alternator are examined. The vortex effect, which directly affects the efficiency and the quality of the energy, was tested at the DarÔøΩca-1 hydroelectric power plant (HPP) located in Ordu Province, Turkey. Formed by undissolved oxygen in the water, the vortex effect, which is parallel to the alternator load, causes tremendous vibration within the alternator and Francis turbine bearings. This problem, which has a direct negative effect on the alternator capacity, was solved by adding an air-admission system. In doing so, power production was …

Circulating Current Analysis Between Strands In Armature Winding Of A Turbo-Generator Using Analytical Model, Karim Abbaszadeh, Farhad Rezaee Alam

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, the circulating current analysis between strands is studied while considering the different transpositions in the active part and without considering the transposition in the end winding region. First, this analysis is done while only considering the slot region, and then the end winding region is added to the model. The model used for this analysis is a circuit model, including the resistance and inductance of the strands and their induced back-electromotive force (EMF). The back-EMF sources and inductances are calculated through a 2D finite element analysis (FEA) of the active part and a 3D FEA for the …