Electrodynamical Modeling For Light Transport Simulation,
2017
East Tennessee State University
Electrodynamical Modeling For Light Transport Simulation, Michael G. Saunders
Undergraduate Honors Theses
Modernity in the computer graphics community is characterized by a burgeoning interest in physically based rendering techniques. That is to say that mathematical reasoning from first principles is widely preferred to ad hoc, approximate reasoning in blind pursuit of photorealism. Thereby, the purpose of our research is to investigate the efficacy of explicit electrodynamical modeling by means of the generalized Jones vector given by Azzam [1] and the generalized Jones matrix given by Ortega-Quijano & Arce-Diego [2] in the context of stochastic light transport simulation for computer graphics. To augment the status quo path tracing framework with such a modeling …
Molecular Dynamics Simulations Of Dna-Functionalized Nanoparticle Building Blocks On Gpus,
2017
University of Arkansas, Fayetteville
Molecular Dynamics Simulations Of Dna-Functionalized Nanoparticle Building Blocks On Gpus, Tyler Landon Fochtman
Graduate Theses and Dissertations
This thesis discusses massively parallel molecular dynamics simulations of nBLOCKs using graphical processing units. nBLOCKs are nanoscale building blocks composed of gold nanoparticles functionalized with single-stranded DNA molecules. To explore greater simulation time scales we implement our nBLOCK computational model as an extension to the coarse grain molecular simulator oxDNA. oxDNA is parameterized to match the thermodynamics of DNA strand hybridization as well as the mechanics of single stranded DNA and double stranded DNA. In addition to an in-depth review of our implementation details we also provide results of the model validation and performance tests. These validation and performance tests …
Evaluating A Personal Stress Monitoring System,
2017
Columbus State University
Evaluating A Personal Stress Monitoring System, Sneha Gogineni
Theses and Dissertations
Now-a-days, Life is generally much more stressful than in the past. "Stress" is the word that we use when we feel that we are overloaded mentally in our thoughts and wonder whether we can really cope with those placed upon us. Sometimes, stress gets us going and they are good for us but at other times, it could be the cause to undermine both our mental and physical health. The way we respond to a challenge can be considered as a kind of stress. Part of our response to a challenge is physiological and affects our own physical state. When …
A Comparative Study Of Cognitive Systems For Learning,
2017
Columbus State University
A Comparative Study Of Cognitive Systems For Learning, Praneetha Mandava
Theses and Dissertations
Learning is the modification of a behavioral tendency by experience. Memory and reasoning are the most important aspects for learning in humans; information is temporarily stored in the short-term memory and processed, compared with existing memories and stored in long-term memory, and can be re-used when needed. One way to describe an organized pattern of thought or behavior and the categories of information along with their relationships is by using schemas. A cognitive script is one form of a schema that evolves over multiple exposures to the same set of stimuli and/or repeated enactment of a particular behavior. This research …
Continuous Top-K Monitoring On Document Streams,
2017
University of Macau
Continuous Top-K Monitoring On Document Streams, Leong Hou U, Junjie Zhang, Kyriakos Mouratidis, Ye Li
Research Collection School Of Computing and Information Systems
The efficient processing of document streams plays an important role in many information filtering systems. Emerging applications, such as news update filtering and social network notifications, demand presenting end-users with the most relevant content to their preferences. In this work, user preferences are indicated by a set of keywords. A central server monitors the document stream and continuously reports to each user the top-k documents that are most relevant to her keywords. Our objective is to support large numbers of users and high stream rates, while refreshing the top-k results almost instantaneously. Our solution abandons the traditional frequency-ordered indexing approach. …
Who Will Leave The Company?: A Large-Scale Industry Study Of Developer Turnover By Mining Monthly Work Report,
2017
Zhejiang University
Who Will Leave The Company?: A Large-Scale Industry Study Of Developer Turnover By Mining Monthly Work Report, Lingfeng Bao, Zhenchang Xing, Xin Xia, David Lo, Shanping Li
Research Collection School Of Computing and Information Systems
Software developer turnover has become a big challenge for information technology (IT) companies. The departure of key software developers might cause big loss to an IT company since they also depart with important business knowledge and critical technical skills. Understanding developer turnover is very important for IT companies to retain talented developers and reduce the loss due to developers' departure. Previous studies mainly perform qualitative observations or simple statistical analysis of developers' activity data to understand developer turnover. In this paper, we investigate whether we can predict the turnover of software developers in non-open source companies by automatically analyzing monthly …
A Neural Network Model For Semi-Supervised Review Aspect Identification,
2017
Singapore Management University
A Neural Network Model For Semi-Supervised Review Aspect Identification, Ying Ding, Changlong Yu, Jing Jiang
Research Collection School Of Computing and Information Systems
Aspect identification is an important problem in opinion mining. It is usually solved in an unsupervised manner, and topic models have been widely used for the task. In this work, we propose a neural network model to identify aspects from reviews by learning their distributional vectors. A key difference of our neural network model from topic models is that we do not use multinomial word distributions but instead embedding vectors to generate words. Furthermore, to leverage review sentences labeled with aspect words, a sequence labeler based on Recurrent Neural Networks (RNNs) is incorporated into our neural network. The resulting model …
Persona Generation From Aggregated Social Media Data,
2017
Singapore Management University
Persona Generation From Aggregated Social Media Data, Soon-Gyo Jung, Jisun An, Haewoon Kwak, Moeed Ahmad, Lene Nielsen, Bernard J. Jansen
Research Collection School Of Computing and Information Systems
We develop a methodology for persona generation using real time social media data for the distribution of products via online platforms. From a large social media account containing more than 30 million interactions from users from 181 countries engaging with more than 4,200 digital products produced by a global media corporation, we demonstrate that our methodology can first identify both distinct and impactful user segments and then create persona descriptions by automatically adding pertinent features, such as names, photos, and personal attributes. We validate our approach by implementing the methodology into an actual working system that leverages large scale online …
A Parallelized Method For Solving Large Scale Integer Linear Optimization Problems Using Cut-And-Solve With Applications To Cgwas,
2017
University of Missouri-St. Louis
A Parallelized Method For Solving Large Scale Integer Linear Optimization Problems Using Cut-And-Solve With Applications To Cgwas, John Brandenburg
Theses
The commercial solver CPLEX has been one of the top solvers of mixed-integer and purely integer linear problems for some time. Its method of solving, Branch-and-Cut, has been shown to be highly effective, but has its limits in terms of input sizes which are tractable, and cannot be effectively parallelized beyond a small number. Here we present a different method of solution, Cut-and-Solve, which utilizes the power of CPLEX to effectively parallelize any mixed-integer or integer linear problem. We have utilized Cut-and-Solve in a novel way to offer optimal solution guarantees more quickly. We will show comparisons of Cut-and-Solve to …
Network Exploration Of Correlated Multivariate Protein Data For Alzheimer's Disease Association,
2017
University of Missouri-St. Louis
Network Exploration Of Correlated Multivariate Protein Data For Alzheimer's Disease Association, Matthew J. Lane
Theses
Alzheimer Disease (AD) is difficult to diagnose by using genetic testing or other traditional methods. Unlike diseases with simple genetic risk components, there exists no single marker determining as to whether someone will develop AD. Furthermore, AD is highly heterogeneous and different subgroups of individuals develop the disease due to differing factors. Traditional diagnostic methods using perceivable cognitive deficiencies are often too little too late due to the brain having suffered damage from decades of disease progression. In order to observe AD at early stages prior to the observation of cognitive deficiencies, biomarkers with greater accuracy are required. By using …
Inelastic Rate Coefficients For Collisions Of C₆Hˉ With H₂ And He,
2017
Missouri University of Science and Technology
Inelastic Rate Coefficients For Collisions Of C₆Hˉ With H₂ And He, Kyle M. Walker, François Lique, Fabien Dumouchel, Richard Dawes
Chemistry Faculty Research & Creative Works
The recent detection of anions in the interstellar medium has shown that they exist in a variety of astrophysical environments -- circumstellar envelopes, cold dense molecular clouds and star-forming regions. Both radiative and collisional processes contribute to molecular excitation and de-excitation in these regions so that the ‘local thermodynamic equilibrium’ approximation, where collisions cause the gas to behave thermally, is not generally valid. Therefore, along with radiative coefficients, collisional excitation rate coefficients are needed to accurately model the anionic emission from these environments. We focus on the calculation of state-to-state rate coefficients of the C6H- molecule in …
A Robust And Secure Video Steganography Method In Dwt-Dct Domains Based On Multiple Object Tracking And Ecc,
2017
University of Bridgeport
A Robust And Secure Video Steganography Method In Dwt-Dct Domains Based On Multiple Object Tracking And Ecc, Ramadhan J. Mstafa, Khaled M. Elleithy, Eman Abdelfattah
School of Computer Science & Engineering Faculty Publications
Over the past few decades, the art of secretly embedding and communicating digital data has gained enormous attention because of the technological development in both digital contents and communication. The imperceptibility, hiding capacity, and robustness against attacks are three main requirements that any video steganography method should take into consideration. In this paper, a robust and secure video steganographic algorithm in discrete wavelet transform (DWT) and discrete cosine transform (DCT) domains based on the multiple object tracking (MOT) algorithm and error correcting codes is proposed. The secret message is preprocessed by applying both Hamming and Bose, Chaudhuri, and Hocquenghem codes …
Predicting The Impact Of Software Engineering Topics: An Empirical Study,
2017
Singapore Management University
Predicting The Impact Of Software Engineering Topics: An Empirical Study, Santonu Sarkar, Rumana Lakdawala, Subhajit Datta
Research Collection School Of Computing and Information Systems
Predicting the future is hard, more so in active research areas. In this paper, we customize an established model for citation prediction of research papers and apply it on research topics. We argue that research topics, rather than individual publications, have wider relevance in the research ecosystem, for individuals as well as organizations. In this study, topics are extracted from a corpus of software engineering publications covering 55,000+ papers written by more than 70,000 authors across 56 publication venues, over a span of 38 years, using natural language processing techniques. We demonstrate how critical aspects of the original paper-based prediction …
Modeling Topics And Behavior Of Microbloggers: An Integrated Approach,
2017
Singapore Management University
Modeling Topics And Behavior Of Microbloggers: An Integrated Approach, Tuan Anh Hoang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Microblogging encompasses both user-generated content and behavior. When modeling microblogging data, one has to consider personal and background topics, as well as how these topics generate the observed content and behavior. In this article, we propose the Generalized Behavior-Topic (GBT) model for simultaneously modeling background topics and users' topical interest in microblogging data. GBT considers multiple topical communities (or realms) with different background topical interests while learning the personal topics of each user and the user's dependence on realms to generate both content and behavior. This differentiates GBT from other previous works that consider either one realm only or content …
Assessing The Language Of Chat For Teamwork Dialogue,
2017
Nanyang Technological University
Assessing The Language Of Chat For Teamwork Dialogue, Antonette Shibani, Elizabeth Koh, Vivian Lai, Kyong Jin Shim
Research Collection School Of Computing and Information Systems
In technology enhanced language learning, many pedagogical activities involve students in online discussion such as synchronous chat, in order to help them practice their language skills. Besides developing the language competency of students, it is also crucial to nurture their teamwork competencies for today's global and complex environment. Language communication is an important glue of teamwork. In order to assess the language of chat for teamwork dimensions, several text mining methods are pos sible. However, difficulties arise such as pre-processing being a black box and classification approaches and algorithms being dependent on the context. To address these issues, the study …
Characterizing Malicious Android Apps By Mining Topic-Specific Data Flow Signatures,
2017
Zhejiang University
Characterizing Malicious Android Apps By Mining Topic-Specific Data Flow Signatures, Xinli Yang, David Lo, Li Li, Xin Xia, Tegawendé F. Bissyande, Jacques Klein
Research Collection School Of Computing and Information Systems
Context: State-of-the-art works on automated detection of Android malware have leveraged app descriptions to spot anomalies w.r.t the functionality implemented, or have used data flow information as a feature to discriminate malicious from benign apps. Although these works have yielded promising performance,we hypothesize that these performances can be improved by a better understanding of malicious behavior. Objective: To characterize malicious apps, we take into account both information on app descriptions,which are indicative of apps’ topics, and information on sensitive data flow, which can be relevant todiscriminate malware from benign apps. Method: In this paper, we propose a topic-specific approach to …
Comparative Relation Generative Model,
2017
Singapore Management University
Comparative Relation Generative Model, Maksim Tkachenko, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Online reviews are important decision aids to consumers. Other than helping users to evaluate individual products, reviews also support comparison shopping by comparing two (or more) products based on a specific aspect. However, making a comparison across two different reviews, written by different authors, is not always equitable due to the different standards and preferences of authors. Therefore, we focus on comparative sentences, whereby two products are compared directly by a review author within a sentence. We study the problem of comparative relation mining. Given a set of comparative sentences, each relating a pair of entities, our objective is three-fold: …
Ten Simple Rules For Responsible Big Data Research,
2017
University of Kentucky
Ten Simple Rules For Responsible Big Data Research, Matthew Zook, Solon Barocas, Danah Boyd, Kate Crawford, Emily Keller, Seeta Peña Gangadharan, Alyssa Goodman, Rachelle Hollander, Barbara A. Koenig, Jacob Metcalf, Arvind Narayanan, Alondra Nelson, Frank Pasquale
Geography Faculty Publications
No abstract provided.
Designing Novel Nanostructured Permanent Magnets,
2017
University of Nebraska at Omaha
Designing Novel Nanostructured Permanent Magnets, Ali Al Kadhim
UNO Student Research and Creative Activity Fair
Rare earth element based alloys have been the source of high performance magnetic alloys, and have played a paramount role in the development of various technologies, including: memory devices (such as credit cards, random-access memory), sensors, and various biomedical applications. However, there is a tremendous need to replace rare earth metals with material with powerful magnetic properties. Our group recently found CrTe-based materials that show very promising magnetic properties in nanostructured form. The magnetic modeling of such material in nanostructured form prior to their fabrication demonstrates their magnetic properties in bulk form. In this project, we investigate the behavior of …
Optimizing Campus Mobility With A Focus On Sustainability: A Graph Theory Approach To Intra-Campus Transportation Networks,
2017
Quinn Nelson
Optimizing Campus Mobility With A Focus On Sustainability: A Graph Theory Approach To Intra-Campus Transportation Networks, Quinn M. Nelson
UNO Student Research and Creative Activity Fair
The idea of public transportation is supported by most in theory but often heavily criticized by users when put into application. There are common tensions that are related to public transportation, as described by frequent users: unreliable, too crowded, and slow. The University of Nebraska-Omaha (UNO) is a growing metropolitan institution that uses a shuttle system to transport students among their three campuses daily. As of 2015, the current total student enrollment is approximately 16,000; UNO plans to enroll 20,000 students by 2020. The expected student growth is also reflected by the current construction of new buildings and expansion of …
