Computer Sciences Commons^™

Distributed Gibbs: A Memory-Bounded Sampling-Based Dcop Algorithm, Duc Thien Nguyen, William Yeoh, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Researchers have used distributed constraint optimization problems (DCOPs) to model various multi-agent coordination and resource allocation problems. Very recently, Ottens et al. proposed a promising new approach to solve DCOPs that is based on confidence bounds via their Distributed UCT (DUCT) sampling-based algorithm. Unfortunately, its memory requirement per agent is exponential in the number of agents in the problem, which prohibits it from scaling up to large problems. Thus, in this paper, we introduce a new sampling-based DCOP algorithm called Distributed Gibbs, whose memory requirements per agent is linear in the number of agents in the problem. Additionally, we show …

Implementation Of Slowly Changing Dimension To Data Warehouse To Manage Marketing Campaigns In Banks, Lihui Wang, Junyu Choy, Michelle L. F. Cheong

Research Collection School Of Computing and Information Systems

Management of updating and recording campaign leads in data warehouse of any banking environment is complex especially with multiple campaigns are active simultaneously. As a way to avoid overly contacting customers for sales-based marketing contacts, the concept of Recency Frame is introduced to “lock” the customers who are targeted in Sales-based campaign for a specified time period. During this Recency Frame, the customer cannot be targeted by other Sales-based campaign under the same channel. This approach increased the difficulties of managing the customers’ data with proper data updating and storing and procedures have to be placed and made sufficiently robust …

Your Love Is Public Now: Questioning The Use Of Personal Information In Authentication, Payas Gupta, Swapna Gottipati, Jing Jiang, Debin Gao

Research Collection School Of Computing and Information Systems

Most social networking platforms protect user's private information by limiting access to it to a small group of members, typically friends of the user, while allowing (virtually) everyone's access to the user's public data. In this paper, we exploit public data available on Facebook to infer users' undisclosed interests on their profile pages. In particular, we infer their undisclosed interests from the public data fetched using Graph APIs provided by Facebook. We demonstrate that simply liking a Facebook page does not corroborate that the user is interested in the page. Instead, we perform sentiment-oriented mining on various attributes of a …

It Is Not Just What We Say, But How We Say Them: Lda-Based Behavior-Topic Model, Minghui Qiu, Feida Zhu, Jing Jiang

Research Collection School Of Computing and Information Systems

Textual information exchanged among users on online social network platforms provides deep understanding into users' interest and behavioral patterns. However, unlike traditional text-dominant settings such as o ine publishing, one distinct feature for online social network is users' rich interactions with the textual content, which, unfortunately, has not yet been well incorporated in the existing topic modeling frameworks. In this paper, we propose an LDA-based behavior-topic model (B-LDA) which jointly models user topic interests and behavioral patterns. We focus the study of the model on online social network settings such as microblogs like Twitter where the textual content is relatively …

Designing Leakage-Resilient Password Entry On Touchscreen Mobile Devices, Qiang Yan, Jin Han, Yingjiu Li, Jianying Zhou, Robert H. Deng

Research Collection School Of Computing and Information Systems

Touchscreen mobile devices are becoming commodities as the wide adoption of pervasive computing. These devices allow users to access various services at anytime and anywhere. In order to prevent unauthorized access to these services, passwords have been pervasively used in user authentication. However, password-based authentication has intrinsic weakness in password leakage. This threat could be more serious on mobile devices, as mobile devices are widely used in public places. Most prior research on improving leakage resilience of password entry focuses on desktop computers, where specific restrictions on mobile devices such as small screen size are usually not addressed. Meanwhile, additional …

Expressive Search On Encrypted Data, Junzuo Lai, Xuhua Zhou, Robert H. Deng, Yingjiu Li, Kefei Chen

Research Collection School Of Computing and Information Systems

Different from the traditional public key encryption, searchable public key encryption allows a data owner to encrypt his data under a user’s public key in such a way that the user can generate search token keys using her secret key and then query an encryption storage server. On receiving such a search token key, the server filters all or related stored encryptions and returns matched ones as response. Searchable pubic key encryption has many promising applications. Unfortunately, existing schemes either only support simple query predicates, such as equality queries and conjunctive queries, or have a superpolynomial blowup in ciphertext size …

Anonymous Authentication Of Visitors For Mobile Crowd Sensing At Amusement Parks, Divyan Konidala, Robert H. Deng, Yingjiu Li, Hoong Chuin Lau, Stephen Fienberg

Research Collection School Of Computing and Information Systems

In this paper we focus on authentication and privacy aspects of an application scenario that utilizes mobile crowd sensing for the benefit of amusement park operators and their visitors. The scenario involves a mobile app that gathers visitors’ demographic details, preferences, and current location coordinates, and sends them to the park’s sever for various analyses. These analyses assist the park operators to efficiently deploy their resources, estimate waiting times and queue lengths, and understand the behavior of individual visitors and groups. The app server also offers visitors optimal recommendations on routes and attractions for an improved dynamic experience and minimized …

Retweeting: An Act Of Viral Users, Susceptible Users, Or Viral Topics?, Tuan-Anh Hoang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

When a user retweets, there are three behavioral factors that cause the actions. They are the topic virality, user virality and user susceptibility. Topic virality captures the degree to which a topic attracts retweets by users. For each topic, user virality and susceptibility refer to the likelihood that a user attracts retweets and performs retweeting respectively. To model a set of observed retweet data as a result of these three topic specific factors, we first represent the retweets as a three-dimensional tensor of the tweet authors, their followers, and the tweets themselves. We then propose the V 2S model, a …

Dynamic Synthesis Of Local Time Requirement For Service Composition, Tian Huat Tan, Étienne André, Jun Sun, Yang Liu, Jin Song Dong, Manman Chen

Research Collection School Of Computing and Information Systems

Service composition makes use of existing servicebased applications as components to achieve a business goal. In time critical business environments, the response time of a service is crucial, which is also reflected as a clause in service level agreements (SLAs) between service providers and service users. To allow the composite service to fulfill the response time requirement as promised, it is important to find a feasible set of component services, such that their response time could collectively allow the satisfaction of the response time of the composite service. In this work, we propose a fully automated approach to synthesize the …

Disclosing Climate Change Patterns Using An Adaptive Markov Chain Pattern Detection Method, Zhaoxia Wang, Gary Lee, Hoong Maeng Chan, Reuben Li, Xiuju Fu, Rick Goh, Pauline A. W. Poh Kim, Martin L. Hibberd, Hoong Chor Chin

Research Collection School Of Computing and Information Systems

This paper proposes an adaptive Markov chain pattern detection (AMCPD) method for disclosing the climate change patterns of Singapore through meteorological data mining. Meteorological variables, including daily mean temperature, mean dew point temperature, mean visibility, mean wind speed, maximum sustained wind speed, maximum temperature and minimum temperature are simultaneously considered for identifying climate change patterns in this study. The results depict various weather patterns from 1962 to 2011 in Singapore, based on the records of the Changi Meteorological Station. Different scenarios with varied cluster thresholds are employed for testing the sensitivity of the proposed method. The robustness of the proposed …

Personal Informatics In Chronic Illness Management, Haley Macleod, Anthony Tang, Sheelagh Carpendale

Research Collection School Of Computing and Information Systems

Many people with chronic illness suffer from debilitating symptoms or episodes that inhibit normal day-to-day function. Pervasive tools offer the possibility to help manage these conditions, particularly by helping people understand their conditions. But, it is unclear how to design these tools, as prior designs have focused on effortful tracking and many see those tools as a burden to use. We report here on an interview study with 12 individuals with chronic illnesses who collect personal data. We learn that these people are motivated through self-discovery and curiosity. We explore how these concepts may support the design of tools that …

Enhancing Robot Perception Using Human Teammates, Jean Oh, Arne Suppe, Anthony Stentz, Martial Hebert

Research Collection School Of Computing and Information Systems

In robotics research, perception is one of the most challenging tasks. In contrast to existing approaches that rely only on computer vision, we propose an alternative method for improving perception by learning from human teammates. To evaluate, we apply this idea to a door detection problem. A set of preliminary experiments has been completed using software agents with real vision data. Our results demonstrate that information inferred from teammate observations significantly improves the perception precision.

Behind The Magical Numbers: Hierarchical Chunking And The Human Working Memory Capacity, Guoqi Li, Ning Ning, Kiruthika Ramanathan, Wei He, Li Pan, Luping Shi

Research Collection School Of Computing and Information Systems

To explore the influence of chunking on the capacity limits of working memory, a model for chunking in sequential working memory is proposed, using hierarchical bidirectional inhibition-connected neural networks with winnerless competition. With the assumption of the existence of an upper bound to the inhibitory weights in neurobiological networks, it is shown that chunking increases the number of memorized items in working memory from the "magical number 7" to 16 items. The optimal number of chunks and the number of the memorized items in each chunk are the "magical number 4".

Leakage Resilient Authenticated Key Exchange Secure In The Auxiliary Input Model, Guomin Yang, Yi Mu, Willy Susilo, Duncan S. Wong

Research Collection School Of Computing and Information Systems

Authenticated key exchange (AKE) protocols allow two parties communicating over an insecure network to establish a common secret key. They are among the most widely used cryptographic protocols in practice. In order to resist key-leakage attacks, several leakage resilient AKE protocols have been proposed recently in the bounded leakage model. In this paper, we initiate the study on leakage resilient AKE in the auxiliary input model. A promising way to construct such a protocol is to use a digital signature scheme that is entropically-unforgeable under chosen message and auxiliary input attacks. However, to date we are not aware of any …

Enabling Generative, Emergent Artificial Culture, Jaroslaw Kochanowicz, Ah-Hwee Tan, Daniel Thalmann

Research Collection School Of Computing and Information Systems

Despite the demand for culturally placed agent models, an adequate simulation approach to the relationship between group-cultural and individual-psychological qualities, including culture emergence, is just appearing. It could be argued that we are at the beginning of a domain forming process, a dawn of generative, emergent artificial culture. In this context we discuss current limitations and argue e.g. that too far reaching agent simplicity within Agent Based Modeling limits the emergence of realistic cultural-conventional level and we advocate psychologically rich models of culture forming mechanisms. We propose an approach to cultural phenomena modeling based on the interaction of habitual, affective …

Context-Driven Image Annotation Using Imagenet, George E. Noel, Gilbert L. Peterson

Faculty Publications

Image annotation research has demonstrated success on test data for focused domains. Unfortunately, extending these techniques to the broader topics found in real world data often results in poor performance. This paper proposes a novel approach that leverages WordNet and ImageNet capabilities to annotate images based on local text and image features. Signatures generated from ImageNet images based on WordNet synonymous sets are compared using Earth Mover's Distance against the query image and used to rank order surrounding words by relevancy. The results demonstrate effective image annotation, producing higher accuracy and improved specificity over the ALIPR image annotation system. Abstract …

Eyes-Free Vision-Based Scanning Of Aligned Barcodes And Information Extraction From Aligned Nutrition Tables, Aliasgar Kutiyanawala

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Independent grocery shopping is one of the biggest challenges faced by visually impaired (VI) individuals. VI individuals may be able to get to a store on their own by using public transportation or by walking but are unable to shop there independently. Some of the problems that they face after getting to the store include long wait times to get an employee to assist them or getting a store employee who is not familiar with the store layout, gets irritated with long searches, or does not possess the required English skills. These problems ultimately result in VI shoppers having to …

Knowledge Extraction In Video Through The Interaction Analysis Of Activities, Omar Ulises Florez

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

A video is a growing stream of unstructured data that significantly increases the amount of information transmitted and stored on the Internet. For example, every minute YouTube users upload 72 GB of information. Some of the best applications for video analysis include the monitoring of activities in defense and security scenarios such as the autonomous planes that collect video and images at reduced risk and the surveillance cameras in public places like traffic lights, airports, and schools.

Some of the challenges in the analysis of video correspond to implement complex operations such as searching of activities, understanding of scenes, and …

A Qualitative And Evaluative Study On Recruiting And Retaining Students In College Computer Science Programs, Matthew Gardner

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Computer science is a discipline that is increasing in importance and value in our society, yet we are still failing to graduate a sufficient number of students to keep up with the demand required in the United States economy. We research several ways to retain students. We also discuss ways to increase students’ interest in the major, i.e., those who normally would not know about computer science. We discuss ways to increase female participation as well as overall participation in the major.

The Effects Of Abstraction On Best Nblock First Search, Justin R. Redd

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Search is an important aspect of Artificial Intelligence. Efficiently searching for solutions to large problems is important. One way to scale search large in problems quickly is to divide the work between multiple processors. There are many ways to divide this work using abstractions. This thesis examines the previous way this has been done in the past and introduces other ways to more efficiently divide the work and search in parallel.

A Digital Image Processing Method For Detecting Pollution In The Atmosphere From Camera Video, Amrita Nikhil Amritphale

UNLV Theses, Dissertations, Professional Papers, and Capstones

In this thesis we examine the use of digital cameras to detect the magnitude of atmospheric pollution present in the atmosphere. Digital cameras are inexpensive and are being used in countless areas, many of which are outdoors and very public. For example, we see digital cameras located at street intersections, city and state parks, and recreation areas. The theory presented in this paper could help agencies to monitor air quality at any of these sites. Our theory is based on certain molecules and particles that are present in clean air absorb, luminesce, refract, reflect, or scatter the red, green, and …

Real Time Pattern Recognition In Digital Video With Applications To Safety In Construction Sites, Dinesh Bajracharya

UNLV Theses, Dissertations, Professional Papers, and Capstones

In construction sites, various guidelines are provided for the correct use of safety equipment. Many fatalities and injuries occur to people because of the lack of exercise of these guidelines and proper monitoring of the violations. In order to improve these standards and amend the cause, a video based monitoring tool will be created for a construction site.

Based on the real time video obtained from cameras on the site, a classification algorithm will be created which has the intelligence to recognize if any safety rules have been violated. A classification vector will be created based on the different classifiers, …

An Online Algorithm For The 2-Server Problem On The Line With Improved Competitiveness, Lucas Adam Bang

UNLV Theses, Dissertations, Professional Papers, and Capstones

In this thesis we present a randomized online algorithm for the 2-server problem on the line, named R-LINE (for Randomized Line). This algorithm achieves the lowest competitive ratio of any known randomized algorithm for the 2-server problem on the line.

The competitiveness of R-LINE is less than 1.901. This result provides a significant improvement over the previous known competitiveness of 155/78 (approximately 1.987), by Bartal, Chrobak, and Larmore, which was the first randomized algorithm for the 2-server problem one the line with competitiveness less than 2. Taking inspiration from this algorithm,we improve this result by utilizing ideas from T-theory, game …

Simulation And Analysis Of Insider Attacks, Christopher Blake Clark

UNLV Theses, Dissertations, Professional Papers, and Capstones

An insider is an individual (usually an employee, contractor, or business partner) that has been trusted with access to an organization's systems and sensitive data for legitimate purposes. A malicious insider abuses this access in a way that negatively impacts the company, such as exposing, modifying, or defacing software and data.

Many algorithms, strategies, and analyses have been developed with the intent of detecting and/or preventing insider attacks. In an academic setting, these tools and approaches show great promise. To be sure of their effectiveness, however, these analyses need to be tested. While real data is available on insider attacks …

The Distributed Application Debugger, Michael Quinn Jones

UNLV Theses, Dissertations, Professional Papers, and Capstones

Developing parallel programs which run on distributed computer clusters introduces additional challenges to those present in traditional sequential programs. Debugging parallel programs requires not only inspecting the sequential code executing on each node but also tracking the flow of messages being passed between them in order to infer where the source of a bug actually lies.

This thesis focuses on a debugging too called The Distributed Application Debugger which targets a popular distributed C programming library called MPI (Message Passing Interface). The tool is composed of multiple components which run together seamlessly to provide its users an effective way to …

Real Time Digital Night Vision Using Nonlinear Contrast Enhancement, Nishikar Sapkota

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis describes a nonlinear contrast enhancement technique to implement night vision in digital video. It is based on the global histogram equalization algorithm. First, the effectiveness of global histogram equalization is examined for images taken in low illumination environments in terms of Peak signal to noise ratio (PSNR) and visual inspection of images. Our analysis establishes the existence of an optimum intensity for which histogram equalization yields the best results in terms of output image quality in the context of night vision. Based on this observation, an incremental approach to histogram equalization is developed which gives better results than …

Simulated Annealing Approach To Flow Shop Scheduling, Sadhana Yellanki

UNLV Theses, Dissertations, Professional Papers, and Capstones

Flow Shop Scheduling refers to the process of allotting various jobs to the machines given, such that every job starts to process on a machine n only after it has finished processing on machine n-1, with each job having n operations to be performed one per machine. To find a schedule that leads to the optimal utilization of resources, expects the schedule to finish in a minimum span of time, and also satisfy the optimality criterion set for the related scheduling problem is NP-Hard, if n > 2. In this thesis, we have developed an algorithm adopting a heuristic called Simulated …

Novel Algorithms And Software For Biological Sequence Analysis, William Casey Bullock

Boise State University Theses and Dissertations

Bioinformatics is a broad realm of research in which Computer Science has much to offer. Collecting, sorting, and analyzing statistical information for DNA and protein sequences is difficult due to the sheer amount of available data. Tools have been created to do this, but they have generally been limited by speed or robustness.

In addition to analyzing the statistical properties of biological sequences, it is also important to model and understand their chemical and physical properties. A number of valuable software tools are available for modeling and predicting the properties of biological sequences in Computational Chemistry, including molecular docking, and …

Document Classification, Shane K. Panter

Boise State University Theses and Dissertations

We present an overview of the document classification process and present research conducted against the newly constructed SBIR-STTR corpus. Specifically, the current methods in use for annotation, corpus construction, feature construction, feature weighting, and classifier algorithms are surveyed. We introduce a new dataset derived from public data downloaded from sbir.gov and the Text Annotation Toolkit (TAT) ₁ for use in classification research.

TAT is a collection of independent components packaged together into one open source software application. TAT was engineered to support the document classification process and workflow. Tracking of changes in a working corpus, saving data used in the …

Gesture Based Home Automation For The Physically Disabled, Alexander Hugh Nelson

Graduate Theses and Dissertations

Paralysis and motor-impairments can greatly reduce the autonomy and quality of life of a patient while presenting a major recurring cost in home-healthcare. Augmented with a non-invasive wearable sensor system and home-automation equipment, the patient can regain a level of autonomy at a fraction of the cost of home nurses. A system which utilizes sensor fusion, low-power digital components, and smartphone cellular capabilities can extend the usefulness of such a system to allow greater adaptivity for patients with various needs. This thesis develops such a system as a Bluetooth enabled glove device which communicates with a remote web server to …