Computer Sciences Commons^™

‘Tweetboard’ – A Case Study Of Developing A Micro-Blogging Platform For Higher Education, Shao Cheh Joyce Hsu, Gan, Benjamin, Jin Lee, Shu Hui Sheryl Lim, Xie Yan Jeremy Lim, Thomas Menkhoff, Si Xian Sherman Tan, Charles Jason Woodard, Qiu Cheng Yap

Research Collection School Of Computing and Information Systems

This paper reports experiences made at an Asian university in developing a social media platform based on Twitter in the context of a final year capstone project where information systems management students get an opportunity to solve ‘a real-world problem for a real client’. In this case study, the challenge was provided by a faculty member’s request for an interactive social media application which engages less outspoken students in class via a social medium they are familiar with: Twitter. We reconstruct the project’s evolution; describe the main features of the application called ‘TweetBoard’ and share lessons learned in developing a …

Pairwise Relation Classification With Mirror Instances And A Combined Convolutional Neural Network, Jianfei Yu, Jing Jiang

Research Collection School Of Computing and Information Systems

Relation classification is the task of classifying the semantic relations between entity pairs in text. Observing that existing work has not fully explored using different representations for relation instances, especially in order to better handle the asymmetry of relation types, in this paper, we propose a neural network based method for relation classification that combines the raw sequence and the shortest dependency path representations of relation instances and uses mirror instances to perform pairwise relation classification. We evaluate our proposed models on two widely used datasets: SemEval-2010 Task 8 and ACE-2005. The empirical results show that our combined model together …

Hashtag Recommendation With Topical Attention-Based Lstm, Yang Li, Ting Liu, Jing Jiang, Liang Zhang

Research Collection School Of Computing and Information Systems

Microblogging services allow users to create hashtags to categorize their posts. In recent years,the task of recommending hashtags for microblogs has been given increasing attention. However,most of existing methods depend on hand-crafted features. Motivated by the successful use oflong short-term memory (LSTM) for many natural language processing tasks, in this paper, weadopt LSTM to learn the representation of a microblog post. Observing that hashtags indicatethe primary topics of microblog posts, we propose a novel attention-based LSTM model whichincorporates topic modeling into the LSTM architecture through an attention mechanism. Weevaluate our model using a large real-world dataset. Experimental results show that …

Efficient Online Summarization Of Large-Scale Dynamic Networks, Qiang Qu, Siyuan Liu, Feida Zhu, Christian S. Jensen

Research Collection School Of Computing and Information Systems

Information diffusion in social networks is often characterized by huge participating communities and viral cascades of high dynamicity. To observe, summarize, and understand the evolution of dynamic diffusion processes in an informative and insightful way is a challenge of high practical value. However, few existing studies aim to summarize networks for interesting dynamic patterns. Dynamic networks raise new challenges not found in static settings, including time sensitivity, online interestingness evaluation, and summary traceability, which render existing techniques inadequate. We propose dynamic network summarization to summarize dynamic networks with millions of nodes by only capturing the few most interesting nodes or …

Careermapper: An Automated Resume Evaluation Tool, Vivian Lai, Kyong Jin Shim, Richard J. Oentaryo, Philips K. Prasetyo, Casey Vu, Ee-Peng Lim, David Lo

Research Collection School Of Computing and Information Systems

The advent of the Web brought about major changes in the way people search for jobs and companies look for suitable candidates. As more employers and recruitment firms turn to the Web for job candidate search, an increasing number of people turn to the Web for uploading and creating their online resumes. Resumes are often the first source of information about candidates and also the first item of evaluation in candidate selection. Thus, it is imperative that resumes are complete, free of errors and well-organized. We present an automated resume evaluation tool called 'CareerMapper'. Our tool is designed to conduct …

Ciphertext-Policy Attribute-Based Encryption With Partially Hidden Access Structure And Its Application To Privacy-Preserving Electronic Medical Record System In Cloud Environment, Lixian Liu, Junzuo Lai, Robert H. Deng, Yingjiu Li

Research Collection School Of Computing and Information Systems

With the development of cloud computing, more and more sensitive data are uploaded to cloud by companies or individuals, which brings forth new challenges for outsourced data security and privacy. Ciphertext-policy attribute-based encryption (CP-ABE) provides fine-grained access control of encrypted data in the cloud; in a CP-ABE scheme, an access structure, also referred to as ciphertext-policy, is sent along with a ciphertext explicitly, and anyone who obtains a ciphertext can know the access structure associated with the ciphertext. In certain applications, access structures contain very sensitive information and must be protected from everyone except the users whose private key attributes …

Collective Personalized Change Classification With Multiobjective Search, Xin Xia, David Lo, Xinyu Wang, Xiaohu Yang

Research Collection School Of Computing and Information Systems

Many change classification techniques have been proposed to identify defect-prone changes. These techniques consider all developers' historical change data to build a global prediction model. In practice, since developers have their own coding preferences and behavioral patterns, which causes different defect patterns, a separate change classification model for each developer can help to improve performance. Jiang, Tan, and Kim refer to this problem as personalized change classification, and they propose PCC+ to solve this problem. A software project has a number of developers; for a developer, building a prediction model not only based on his/her change data, but also on …

Demystifying And Puncturing The Inflated Delay In Smartphone-Based Wifi Network Measurement, Weichao Li, Daoyuan Wu, Rocky K. C. Chang, Ricky K. P. Mok

Research Collection School Of Computing and Information Systems

Using network measurement apps has become a very effective approach to crowdsourcing WiFi network performance data. However, these apps usually measure the user-level performancemetrics instead of the network-level performance which is important for diagnosing performance problems. In this paper we report for the first time that a major source of measurement noises comes from the periodical SDIO (Secure Digital Input Output) bus sleep inside the phone. The additional latency introduced by SDIO and Power Saving Mode can inflate and unstablize network delay measurement significantly. We carefully design and implement a scheme to wake up the phone for delay measurement by …

Domain Identification For Intention Posts On Online Social Media, Thai Le Luong, Quoc Tuan Truong, Hai-Trieu Dang, Xuan Hieu Phan

Research Collection School Of Computing and Information Systems

Today, more and more Internet users are willing to share their feeling, activities, and even their intention about what they plan to do on online social media. We can easily see posts like "I plan to buy an apartment this year", or "We are looking for a tour for 3 people to Nha Trang" on online forums or social networks. Recognizing those user intents on online social media is really useful for targeted advertising. However fully understanding user intents is a complicated and challenging process which includes three major stages: user intent filtering, intent domain identification, and intent parsing and …

Semi-Automated Tool For Providing Effective Feedback On Programming Assignments, Min Yan Beh, Swapna Gottipati, David Lo, Venky Shankararaman

Research Collection School Of Computing and Information Systems

Human grading of introductory programming assignments is tedious and error-prone, hence researchers have attempted to develop tools that support automatic assessment of programming code. However, most such efforts often focus only on scoring solutions, rather than assessing whether students correctly understand the problems. To aid the students improve programming skills, effective feedback on programming assignments plays an important role. Individual feedback generation is tedious and painstaking process. We present a tool that not only automatically generates the static and dynamic program analysis outcomes, but also clusters similar code submissions to provide scalable and effective feedback to the students. We studied …

Gbann-V: Genetically Based Artificial Neural Network With Validation For Optimal Feature Selection And Data Mining, Eric W. Worden

Theses and Dissertations

In data mining and machine learning systems, highly predictive feature attributes help researchers and data analysts classify the problem space in the most optimal way. In this thesis paper, a feature subset selection classifier system for data mining and machine learning will be presented. This feature subset selection system will test data from the PIMA Indian Diabetes Data and the Breiman Waveform Data Set. The system collects the input features and then processes them through an evolutionary search process in order to reduce the feature space into an optimal feature set. Reducing irrelevant attributes can decrease the complexity and processing …

Cross-Spectral Biometric Performance Analysis On High-Resolution Face Images, Praveen Kumar Pandian Shanmuganathan

Theses and Dissertations

Biometrics is increasingly being used to authenticate the identity of individuals in critical use case devices like smart phones, laptops, and several other access-control systems in our day-to-day lives. Additionally, biometrics is also used in forensic and security sensitive areas to detect and identify suspects involved in bombings, robberies, and several police investigations. In each of these critical scenarios, the high-quality full-frontal face images of the subjects are not accurately captured as those subjects do not intend to register their identity to the Closed-Circuit Cameras. Hence in such cases, identification of the suspects becomes difficult even though we have the …

Statistical Techniques To Model And Optimize Performance Of Scientific, Numerically Intensive Workloads, Steena Dominica Steven Monteiro

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Projecting performance of applications and hardware is important to several market segments—hardware designers, software developers, supercomputing centers, and end users. Hardware designers estimate performance of current applications on future systems when designing new hardware. Software developers make performance estimates to evaluate performance of their code on different architectures and input datasets. Supercomputing centers try to optimize the process of matching computing resources to computing needs. End users requesting time on supercomputers must provide estimates of their application’s run time, and incorrect estimates can lead to wasted supercomputing resources and time. However, application performance is challenging to predict because it is …

Improvement Of Security In Uas Communication And Navigation Using Ads-B, Vedadatta Gouripeddi

UNLV Theses, Dissertations, Professional Papers, and Capstones

In this thesis, we congregate the security threats on UAS and suggest solutions using ADS-B device. UAS ground and intercommunication is prone to availability, confidentiality and integrity attacks. UAS communication has three layered wireless Ad-Hock network which comprises of Complex group key exchange. Loss of one layer in the Ad-hock network leads to a complete loss of communication in the network. Current UAS navigation methods include complete reliance on on-board sensors, radars and GPS. This research proposes solutions for UAS communication, navigation and collision avoidance using ADS-B. ADS-B acts as a back-up when there is a loss in any one …

An Interview With The Scorpion: Walter O’Brien, Walter O'Brien

The Transdisciplinary STEAM+ Journal

An interview with Walter O'Brien (hacker handle: "Scorpion"), known as a businessman, information technologist, executive producer, and media personality who is the founder and CEO of Scorpion Computer Services, Inc. O'Brien is also the inspiration for and executive producer of the CBS television series, Scorpion.

Museum 4.0 As The Future Of Steam In Museums, Mark Walhimer

The Transdisciplinary STEAM+ Journal

Informal STEAM (Science, Technology, Engineering, Art and Math) activities (programs) and exhibits are common in science centers, children’s museums and natural history museums. As museums change to Museum 4.0 models (1), the STEAM exhibits and programs in museums also change. Museums 4.0 is the transformation of museums from a monolithic fixed location institution to a nimble community driven event driven organization. The Museum 4.0 becomes personalized to the visitor without fixed outcomes and without the physical restrictions of a single fixed location. As museums evolve to a Museum 4.0 model with visitor lead activities, STEAM activities within museums also change …

Eeg Analysis Of Evoked Potentials Of The Brain To Develop A Mathematical Model For Classifying Tinnitus Datasets, Yasaman Emami

Theses and Dissertations

Tinnitus is hearing a sound of buzzing, ringing, whooshing, pulsing, whistling, hissing, when there are no actual sounds existing. The individual can hear ocean waves, dial tones, crickets and even music or other sounds specially when the background is quiet. According to the statistics from the American Tinnitus Association (ATA) [1], these symptoms affect twenty percent of populations life. It could affect the quality of the individual’s life in couple of ways, the person may have difficulty concentrating and may suffer from insomnia. Due to the complexity of the problem, there is no Food and Drug Administration (FDA) approved treatment …

Inferred Error Rates For Entity Resolution, Melody Lynn Penning

Theses and Dissertations

This dissertation is focused on the methodology of determining the quality of the results of entity resolution. Entity resolution methodologies results in different success rates. Until now these success rates have been measured by counting all of the correctly and incorrectly matched results. This is quickly becoming an intractable task as datasets grow in size. In order to address this problem this research tests and describes the results of count based measures as compared with inferred measures borrowed from the information retrieval community. The key contribution of this research is a proof of concept in a controlled environment that demonstrates …

An Application Programming Interface For Parliamentary Procedure, Grant David Bourque

Honors Capstones

No abstract provided.

Towards A Computational Model Of Frame Of Reference Alignment In Swedish Dialogue, Simon Dobnik, Christine Howes, Kim Demaret, John D. Kelleher

Conference papers

In this paper we examine how people negotiate, interpret and repair the frame of reference (FoR) in online text based dialogues discussing spatial scenes in Swedish. We describe work-in-progress in which participants are given different perspectives of the same scene and asked to locate several objects that are only shown on one of their pictures. This task requires participants to coordinate on FoR in order to identify the missing objects. This study has implications for situated dialogue systems.

Towards Computational Human Behavior Modeling For Just-In-Time Adaptive Interventions, Tylar Murray

USF Tampa Graduate Theses and Dissertations

The advent of powerful wearable devices and smartphones has enabled a new generation of “in-the-wild” user studies, adaptive behavioral intervention strategies, and context measurement. Though numerous proof-of-concept studies continue to push the limitations of what a behavioral scientist can do with these technologies, there remains a major methodological roadblock separating behavioral theory and application. Avatar-user interaction theory, for example, is not well defined in its formulation, and thus guidelines for intervention designers depend on heuristic methods and designer intuition. Computational modeling has been slow to move into behavioral science in general, but a growing population of behavioral scientists recognize this …

Network Inference Driven Drug Discovery, Gergely Zahoránszky-Kőhalmi, Tudor I. Oprea, Cristian G. Bologa, Subramani Mani, Oleg Ursu

Biomedical Sciences ETDs

The application of rational drug design principles in the era of network-pharmacology requires the investigation of drug-target and target-target interactions in order to design new drugs. The presented research was aimed at developing novel computational methods that enable the efficient analysis of complex biomedical data and to promote the hypothesis generation in the context of translational research. The three chapters of the Dissertation relate to various segments of drug discovery and development process.

The first chapter introduces the integrated predictive drug discovery platform „SmartGraph”. The novel collaborative-filtering based algorithm „Target Based Recommender (TBR)” was developed in the framework of this …

Theory And Practice Of Computing With Excitable Dynamics, Alireza Goudarzi

Computer Science ETDs

Reservoir computing (RC) is a promising paradigm for time series processing. In this paradigm, the desired output is computed by combining measurements of an excitable system that responds to time-dependent exogenous stimuli. The excitable system is called a reservoir and measurements of its state are combined using a readout layer to produce a target output. The power of RC is attributed to an emergent short-term memory in dynamical systems and has been analyzed mathematically for both linear and nonlinear dynamical systems. The theory of RC treats only the macroscopic properties of the reservoir, without reference to the underlying medium it …

Towards Deeper Understanding In Neuroimaging, Rex Devon Hjelm

Computer Science ETDs

Neuroimaging is a growing domain of research, with advances in machine learning having tremendous potential to expand understanding in neuroscience and improve public health. Deep neural networks have recently and rapidly achieved historic success in numerous domains, and as a consequence have completely redefined the landscape of automated learners, giving promise of significant advances in numerous domains of research. Despite recent advances and advantages over traditional machine learning methods, deep neural networks have yet to have permeated significantly into neuroscience studies, particularly as a tool for discovery. This dissertation presents well-established and novel tools for unsupervised learning which aid in …

Using Timing-Based Side Channels For Anomaly Detection In Industrial Control Systems, Stephen Dunlap, Jonathan W. Butts, Juan L. Lopez Jr., Mason J. Rice, Barry E. Mullins

Faculty Publications

The critical infrastructure, which includes the electric power grid, railroads and water treatment facilities, is dependent on the proper operation of industrial control systems. However, malware such as Stuxnet has demonstrated the ability to alter industrial control system parameters to create physical effects. Of particular concern is malware that targets embedded devices that monitor and control system functionality, while masking the actions from plant operators and security analysts. Indeed, system security relies on guarantees that the assurance of these devices can be maintained throughout their lifetimes. This paper presents a novel approach that uses timing-based side channel analysis to establish …

The Amulet Wearable Platform: Demo Abstract, Josiah Hester, Travis Peters, Tianlong Yun, Ronald Peterson, Joseph Skinner, Bhargav Golla, Kevin Storer, Steven Hearndon, Sarah Lord, Ryan Halter, David Kotz, Jacob Sorber

Dartmouth Scholarship

In this demonstration we present the Amulet Platform; a hardware and software platform for developing energy- and resource-efficient applications on multi-application wearable devices. This platform, which includes the Amulet Firmware Toolchain, the Amulet Runtime, the ARP-View graphical tool, and open reference hardware, efficiently protects applications from each other without MMU support, allows developers to interactively explore how their implementation decisions impact battery life without the need for hardware modeling and additional software development, and represents a new approach to developing long-lived wearable applications. We envision the Amulet Platform enabling long-duration experiments on human subjects in a wide variety of studies.

Personal Privacy: A Study To Determine Views On Privacy As It Relates To Technology Acceptance, Keith A. Wuotinen

Master's Theses and Doctoral Dissertations

This descriptive correlation study sought to learn the relationships, if any, between a person’s concern for privacy and their acceptance of technology, in conjunction with the control factors of the Big Five personality factors. The study employed a modified Concern for Information Privacy (CFIP) scale and a modified Technology Acceptance Model (TAM) approach in conjunction with the Big Five personality factors using a 51-question survey.

The study surveyed students at Eastern Michigan University in Ypsilanti, Michigan, who were enrolled in the College of Technology. The results indicated that there was a significant positive relationship between the CFIP and the TAM. …

Constraint Cnf: Sat And Csp Language Under One Roof, Broes De Cat, Yuliya Lierler

Computer Science Faculty Proceedings & Presentations

A new language, called constraint CNF, is proposed. It integrates propositional logic with constraints stemming from constraint programming. A family of algorithms is designed to solve problems expressed in constraint CNF. These algorithms build on techniques from both propositional satisfiability and constraint programming. The result is a uniform language and an algorithmic framework, which allow us to gain a deeper understanding of the relation between the solving techniques used in propositional satisfiability and in constraint programming and apply them together.

Towards Concolic Testing For Hybrid Systems, Pingfan Kong, Yi Li, Xiaohong Chen, Jun Sun, Meng Sun, Jingyi Wang

Research Collection School Of Computing and Information Systems

Hybrid systems exhibit both continuous and discrete behavior. Analyzing hybrid systems is known to be hard. Inspired by the idea of concolic testing (of programs), we investigate whether we can combine random sampling and symbolic execution in order to effectively verify hybrid systems. We identify a sufficient condition under which such a combination is more effective than random sampling. Furthermore, we analyze different strategies of combining random sampling and symbolic execution and propose an algorithm which allows us to dynamically switch between them so as to reduce the overall cost. Our method has been implemented as a web-based checker named …

Automated Verification Of Timed Security Protocols With Clock Drift, Li Li, Jun Sun

Research Collection School Of Computing and Information Systems

Time is frequently used in security protocols to provide better security. For instance, critical credentials often have limited lifetime which improves the security against brute-force attacks. However, it is challenging to correctly use time in protocol design, due to the existence of clock drift in practice. In this work, we develop a systematic method to formally specify as well as automatically verify timed security protocols with clock drift. We first extend the previously proposed timed applied ππ -calculus as a formal specification language for timed protocols with clock drift. Then, we define its formal semantics based on timed logic rules, …