Computer Sciences Commons^™

A Framework For Collecting, Extracting And Managing Event Identity Information From Textual Content In Social Media, Debanjan Mahata

Theses and Dissertations

With the popularity of social media platforms such as Facebook, Twitter and Google Plus, there has been voluminous growth in the digital footprints of real-life events on the Internet. The user-generated colloquial and concise textual content related to different types of real-life events, available in these websites, acts as an extremely useful source for researchers and organizations for extracting valuable and insightful information. There has been significant improvement in natural language processing techniques for mining formal and long textual content commonly found in newspapers. It is still a challenging task to mine textual information from the social media channels producing …

Vision-Based Motion For A Humanoid Robot, Khalid Abdullah Alkhulayfi

Dissertations and Theses

The overall objective of this thesis is to build an integrated, inexpensive, human-sized humanoid robot from scratch that looks and behaves like a human. More specifically, my goal is to build an android robot called Marie Curie robot that can act like a human actor in the Portland Cyber Theater in the play Quantum Debate with a known script of every robot behavior. In order to achieve this goal, the humanoid robot need to has degrees of freedom (DOF) similar to human DOFs. Each part of the Curie robot was built to achieve the goal of building a complete humanoid …

A Model-Free Localization Method For Sensor Networks With Sparse Anchors, Maggie Xiaoyan Cheng, Wei Biao Wu

Computer Science Faculty Research & Creative Works

This paper considers the problem of sensor node localization, where a total of an anchor nodes is used to determine the locations of other nodes based on the received signal strengths. Challenges arise when anchor nodes are sparse and locations of them are not at grid positions. A range-based machine learning algorithm is developed to tackle the challenges. Instead of using samples to calibrate the parameters of a chosen signal model, we use machine learning to estimate the signal propagation function and its parameters at the same time. It overcomes the model dependency issue of existing range-based algorithms and avoids …

Maximizing Coding Gain In Wireless Networks With Decodable Network Coding, Maggie Cheng, Quanmin Ye, Xiaochun Cheng, Lin Cai

Computer Science Faculty Research & Creative Works

Network coding improves transmission efficiency by combining packets at relay nodes and thus reduces the number of packets sent to the network. It is a network layer solution to improve network throughput and transmission efficiency. However, a coded packet must be decodable by the destination, otherwise it is a waste of resource to combine them together and to deliver the coded packet. This paper addresses how to find the coding solution that guarantees decodability at the destination. We first quantify the coding gain as the number of transmissions reduced and then provide a method for runtime check whether a coding …

In-Band Wormhole Detection In Wireless Ad Hoc Networks Using Change Point Detection Method, Maggie Xiaoyan Cheng, Yi Ling, Wei Biao Wu

Computer Science Faculty Research & Creative Works

This paper addresses detecting in-band wormholes in wireless ad hoc networks. The detection scheme requires collecting the end-to-end delay of packets at the receiver and then applying a sequential change point detection algorithm to detect abrupt changes in the delay time series. A new change point detection algorithm, named SW-CLT, is proposed. The algorithm is based on the Central Limit Theorem (CLT) and does not involve using a preset detecting threshold. The algorithm is compared with the non-parametric cumulative sum (NP-CUSUM) because the non-parametric version is believed to be more robust to highly dynamic data than the parametric version. SW-CLT …

Analyzing Clustered Web Concepts With Homology, Eric Nam

Master's Projects

As data is being mined more and more from the Internet today, Data Science has become an important field of computing to make that data useful. Data Science allows people to turn all of that data into structured knowledge that is easily utilized, validated, and understandable. There are many known theories to analyze data, but this project will focus on a recently introduced method: analyzing text data with homology from mathematics to understand relationships between keyword-sets.

Using structures of algebraic topology as a starting point, keyword-sets in the text are represented by simplexes based on what they are and what …

Tools And Techniques For Computational Reproducibility, Stephen Piccolo, Michael B. Frampton

Faculty Publications

When reporting research findings, scientists document the steps they followed so that others can verify and build upon the research. When those steps have been described in sufficient detail that others can retrace the steps and obtain similar results, the research is said to be reproducible. Computers play a vital role in many research disciplines and present both opportunities and challenges for reproducibility. Computers can be programmed to execute analysis tasks, and those programs can be repeated and shared with others. The deterministic nature of most computer programs means that the same analysis tasks, applied to the same data, will …

A Genetic Algorithmic Approach To Automated Auction Mechanism Design, Jinzhong Niu, Simon Parsons

Publications and Research

In this paper, we present a genetic algorithmic approach to automated auction mechanism design in the context of \cat games. This is a follow-up to one piece of our prior work in the domain, the reinforcement learning-based grey-box approach. Our experiments show that given the same search space the grey-box approach is able to produce better auction mechanisms than the genetic algorithmic approach. The comparison can also shed light on the design and evaluation of similar search solutions to other domain problems.

On Understanding Preference For Agile Methods Among Software Developers, David Brian Bishop, Amit V. Deokar, Surendra Sarnikar

Research & Publications

Agile methods are gaining widespread use in industry. Although management is keen on adopting agile, not all developers exhibit preference for agile methods. The literature is sparse in regard to why developers may show preference for agile. Understanding the factors informing the preference for agile can lead to more effective formation of teams, better training approaches, and optimizing software development efforts by focusing on key desirable components of agile. This study, using a grounded theory methodology, finds a variety of categories of factors that influence software developer preference for agile methods including self-efficacy, affective response, interpersonal response, external contingencies, and …

Context-Aware Collaborative Storage And Programming For Mobile Users, Mohammad A. Khan

Dissertations

Since people generate and access most digital content from mobile devices, novel innovative mobile apps and services are possible. Most people are interested in sharing this content with communities defined by friendship, similar interests, or geography in exchange for valuable services from these innovative apps. At the same time, they want to own and control their content. Collaborative mobile computing is an ideal choice for this situation. However, due to the distributed nature of this computing environment and the limited resources on mobile devices, maintaining content availability and storage fairness as well as providing efficient programming frameworks are challenging.

This …

Why Cannot We Have A Strongly Consistent Family Of Skew Normal (And Higher Order) Distributions, Thongchai Dumrongpokaphan, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, the only information that we have about the probability distribution is its first few moments. Since many statistical techniques requires us to select a single distribution, it is therefore desirable to select, out of all possible distributions with these moments, a single "most representative" one. When we know the first two moments, a natural idea is to select a normal distribution. This selection is strongly consistent in the sense that if a random variable is a sum of several independent ones, then selecting normal distribution for all of the terms in the sum leads to a …

Automated Detection Of Deep-Sea Animals, Dallas J. Hollis, Duane Edgington, Danelle Cline

STAR Program Research Presentations

The Monterey Bay Aquarium Research Institute routinely deploys remotely operated underwater vehicles equipped with high definition cameras for use in scientific studies. Utilizing a video collection of over 22,000 hours and the Video Annotation and Reference System, we have set out to automate the detection and classification of deep-sea animals. This paper serves to explore the pitfalls of automation and suggest possible solutions to automated detection in diverse ecosystems with varying field conditions. Detection was tested using a saliency-based neuromorphic selective attention algorithm. The animals that were not detected were then used to tune saliency parameters. Once objects are detected, …

Why Ragin's Fuzzy Techniques Lead To Successful Social Science Applications: An Explanation, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

To find the relation between two concepts, social scientists traditionally look for correlations between the numerical quantities describing these concepts. Sometimes this help, but sometimes, while we are clear that there is a relation, statistical analysis does not show any correlation. Charles Ragin has shown that often, in such situations, we can find statistically significant correlation between the degrees to which experts estimate the corresponding concepts to be applicable to given situations. In this paper, we provide a simple explanation for this empirical success.

Interpolation Sometimes Enhances And Sometimes Impedes Spatial Correlation: Simple Pedagogical Examples, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

A natural way to check whether there is a dependence between two quantities is to estimate their correlation. For spatial quantities, such an estimation is complicated by the fact that, in general, we measure the values of the two quantities of interest in somewhat different locations. In this case, one possibility is to correlate each value of the first quantity with the value of the second quantity measured at a nearby point. An alternative idea is to first apply an appropriate interpolation to each of the quantities, and then look for the correlation between the resulting spatial maps. Empirical results …

How To Explain Ubiquity Of Constant Elasticity Of Substitution (Ces) Production And Utility Functions Without Explicitly Postulating Ces, Olga Kosheleva, Vladik Kreinovich, Thongchai Dumrongpokaphan

Departmental Technical Reports (CS)

In many situations, the dependence of the production or utility on the corresponding factors is described by the CES (Constant Elasticity of Substitution) functions. These functions are usually explained by postulating two requirements: an economically reasonable postulate of homogeneity (that the formulas should not change if we change a measuring unit) and a less convincing CSE requirement. In this paper, we show that the CES requirement can be replaced by a more convincing requirement -- that the combined effect of all the factors should not depend on the order in which we combine these factors.

Econometric Models Of Probabilistic Choice: Beyond Mcfadden's Formulas, Olga Kosheleva, Vladik Kreinovich, Songsak Sriboonchitta

Departmental Technical Reports (CS)

Traditional decision theory assumes that for every two alternatives, people always make the same (deterministic) choice. In practice, people's choices are often probabilistic, especially for similar alternatives: the same decision maker can sometimes select one of them and sometimes the other one. In many practical situations, an adequate description of this probabilistic choice can be provided by a logit model proposed by 2001 Nobelist D. McFadden. In this model, the probability of selecting an alternative a is proportional to exp(β * u(a)), where u(a) is the alternative's utility. Recently, however, empirical evidence appeared that shows that in some situations, we …

Report On The Roundtable At The Computing Alliance For Hispanic-Serving Institutions (Cahsi) Summit, San Juan, Puerto Rico, September 12, 2015, Ann Q. Gates, Claudia Casas, Andrea Tirres

Departmental Technical Reports (CS)

No abstract provided.

Geometric Symmetries Partially Explain Why Some Paleolithic Signs Are More Frequent, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

A recent analysis of Paleolithic signs have described which signs are more frequent and which are less frequent. In this paper, we show that this relative frequency can be (at least partially) explained by the symmetries of the signs: in general, the more symmetries, the more frequent the sign.

What Motivates High School Students To Take Precautions Against The Spread Of Influenza? A Data Science Approach To Latent Modeling Of Compliance With Preventative Practice, William L. Romine, Tanvi Banerjee, William R. Folk, Lloyd H. Barrow

Kno.e.sis Publications

– This study focuses on a central question: What key behavioral factors influence high school students’ compliance with preventative measures against the transmission of influenza? We use multilevel logistic regression to equate logit measures for eight precautions to students’ latent compliance levels on a common scale. Using linear regression, we explore the efficacy of knowledge of influenza, affective perceptions about influenza and its prevention, prior illness, and gender in predicting compliance. Hand washing and respiratory etiquette are the easiest precautions for students, and hand sanitizer use and keeping the hands away from the face are the most difficult. Perceptions of …

Direct And Inverse Scattering Problems For Domains With Multiple Corners, Jiang Yihong

Doctoral Dissertations

Direct and inverse scattering problems have wide applications in geographical exploration, radar, sonar, medical imaging and non-destructive testing. In many applications, the obstacles are not smooth. Corner singularity challenges the design of a forward solver. Also, the nonlinearity and ill-posedness of the inverse problem challenge the design of an efficient, robust and accurate imaging method.

This dissertation presents numerical methods for solving the direct and inverse scattering problems for domains with multiple corners. The acoustic wave is sent from the transducers, scattered by obstacles and received by the transducers. This forms the response matrix data. The goal for the direct …

Which Interval Is The Closest To A Given Set?, Vladik Kreinovich, Olga Kosheleva

Departmental Technical Reports (CS)

In some practical situations, we know a set of possible values of a physical quantity -- a set which is not an interval. Since computing with sets is often complicated, it is desirable to approximate this set by an easier-to-process set: namely, with an interval. In this paper, we describe intervals which are the closest approximations to a given set.

Rotation-Invariance Can Further Improve State-Of-The-Art Blind Deconvolution Techniques, Fernando Cervantes, Bryan E. Usevitch, Vladik Kreinovich

Departmental Technical Reports (CS)

In many real-life situations, we need to reconstruct a blurred image in situations when no information about the blurring is available. This problem is known as the problem of blind deconvolution. There exist techniques for solving this problem, but these techniques are not rotation-invariant. Thus, the result of using this technique may change with rotation. So, if we rotate the image a little bit, the method, in general, leads to a different deconvolution result. Therefore, even when the original reconstruction is optimal, the reconstruction of a rotated image will be different and, thus, not optimal. To improve the quality of …

How To Make Plausibility-Based Forecasting More Accurate, Kongliang Zhu, Nantiworn Thianpaen, Vladik Kreinovich

Departmental Technical Reports (CS)

In recent papers, a new plausibility-based forecasting method was proposed. While this method has been empirically successful, one of its steps -- selecting a uniform probability distribution for the plausibility level -- is heuristic. It is therefore desirable to check whether this selection is optimal or whether a modified selection would like to a more accurate forecast. In this paper, we show that the uniform distribution does not always lead to (asymptotically) optimal estimates, and we show how to modify the uniform-distribution step so that the resulting estimates become asymptotically optimal.

When We Know The Number Of Local Maxima, Then We Can Compute All Of Them, Olga Kosheleva, Martine Ceberio, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, we need to compute local maxima. In general, it is not algorithmically possible, given a computable function, to compute the locations of all its local maxima. We show, however, that if we know the number of local maxima, then such an algorithm is already possible. Interestingly, for global maxima, the situation is different: even if we only know the number of locations where the global maximum is attained, then, in general, it is not algorithmically possible to find all these locations. A similar impossibility result holds for local maxima if instead of knowing their exact number, …

How Neural Networks (Nn) Can (Hopefully) Learn Faster By Taking Into Account Known Constraints, Chitta Baral, Martine Ceberio, Vladik Kreinovich

Departmental Technical Reports (CS)

Neural networks are a very successful machine learning technique. At present, deep (multi-layer) neural networks are the most successful among the known machine learning techniques. However, they still have some limitations, One of their main limitations is that their learning process still too slow. The major reason why learning in neural networks is slow is that neural networks are currently unable to take prior knowledge into account. As a result, they simple ignore this knowledge and simulate learning "from scratch". In this paper, we show how neural networks can take prior knowledge into account and thus, hopefully, learn faster.

Why 3-D Space? Why 10-D Space? A Possible Simple Geometric Explanation, Vladik Kreinovich

Departmental Technical Reports (CS)

In physics, the number of observed spatial dimensions (three) is usually taken as an empirical fact, without a deep theoretical explanation. In this paper, we provide a possible simple geometric explanation for the 3-D character of the proper space. We also provide a simple geometric explanation for the number of additional spatial dimensions that some physical theories use. Specifically, it is known that for some physical quantities, the 3-D space model with point-wise particles leads to meaningless infinities. To avoid these infinities, physicists have proposed that particles are more adequately described not as 0-D points, but rather as 1-D strings …

Active Object Localization In Visual Situations, Max H. Quinn, Anthony Rhodes, Melanie Mitchell

Computer Science Faculty Publications and Presentations

—We describe a method for performing active localization of objects in instances of visual situations. A visual situation is an abstract concept—e.g., “a boxing match”, “a birthday party”, “walking the dog”, “waiting for a bus”—whose image instantiations are linked more by their common spatial and semantic structure than by low-level visual similarity. Our system combines given and learned knowledge of the structure of a particular situation, and adapts that knowledge to a new situation instance as it actively searches for objects. More specifically, the system learns a set of probability distributions describing spatial and other relationships among relevant objects. The …

Vertical Implementation Of Cloud For Education (V.I.C.E.), Travis S. Brummett

Masters Theses & Specialist Projects

There are several different implementations of open source cloud software that organizations can utilize when deploying their own private cloud. Some possible solutions are OpenNebula, Nimbus, and Eucalyptus. These are Infrastructure-as-a-Service (IaaS) cloud implementations that ultimately gives users virtual machines to undefined job types. A typical IaaS cloud is composed of a front-end cloud controller node, a cluster controller node for controlling compute nodes, a virtual machine image repository node, and many persistent storage nodes and compute nodes. These architectures are built for ease of scalability and availability.

Interestingly, the potential of such architectures could have in the educational field …

Augmented Reality Vs Virtual Reality, Atdhe Mahmuti

Theses and Dissertations

Në këtë punim diplome janë shpjeguar shume koncepte të realitetit virtual (VR) dhe realitetit të shtuar (AR), janë analizuar dy teknologjitë që edhe pse janë gjysme shekulli të vjetra kohëve të fundit kanë marr vëmendje dhe përmasa të gjera të zhvillimit dhe aplikimit në jetën reale dhe në përmasimin e produktivitetit të njerëzve, edhe pse këto dy teknologji janë të ngjashme njëra me tjetrën ato kanë edhe dallime. Si pika kryesore që janë shtjelluar në ketë punim diplome janë duke filluar nga një historik për realitetin virtual dhe realitetin e shtuar, duke u nisur që nga shekulli XX-të e deri …

Mekanizmat E Siguris Në Voip Dhe Efekti I Tyre, Bajram Quka

Theses and Dissertations

Voice over Internet Protocol (VoIP) është duke u bërë një mënyrë më e vlefshme dhe më e popullarizuar e komunikimit të përdorur në internet.VoIP është një teknologji me një rritje të shpejtë që mundëson transportin e zërit mbi rrjetin e të dhënave. Kjo rritje rezulton edhe në fokusin e integrimit të zërit dhe të trafikut të të dhënave, mbi infrastrukturen ekzistuese të rrjetave me një kosto të ultë, dhe menagjim të rrjetit të ofruar nga kjo teknologji.

Megjithat me suksesin e VoIP, kërcnimet dhe sfidat qëndrojnë mbrapa kësaj teknologjie, ku nevoja për një siguri me të lartë, disponushmeri me te …