Computer Sciences Commons^™

Saberlytics Software Suite, Dylan Hallagan, Cody Thomas

Computer Science Undergraduate

No abstract provided.

Superhero Camp, Ben Fennell, Matthew Czajka

Computer Science Undergraduate

No abstract provided.

Network Inventory Application, Aaron M. Resch, Matthew Begley

Computer Science Undergraduate

No abstract provided.

Garbage Collector, Greg Lohrman, Alexis Zakala

Computer Science Undergraduate

No abstract provided.

Demand Bidding Program And Its Application In Hotel Energy Management, Manikanta Perumalla

All Capstone Projects

Demand bidding program (DBP) is recently adopted in practice by some energy operators. DBP is a risk-free demand response program targeting large energy consumers. In this paper, we consider DBP with the application in hotel energy management. For DBP, optimization problem is formulated with the objective of maximizing expected reward, which is received when the amount of energy saving satisfies the contract. For a general distribution of energy consumption, we give a general condition for the optimal bid and outline an algorithm to find the solution without numerical integration. Furthermore, for Gaussian distribution, we derive closed-form expressions of the optimal …

Instamapp, Andrew Dicosmo, Preethi Reddy, Venkat Nischey

All Capstone Projects

InstaMapp is a web application we started building in fall 2014. This application is intended for anyone who wants to locate a product from a department store. Anyone who would like to print or view a shopping list with aisle or department locations. Currently there isn’t a reliable application out that that exist in the technology space. InstaMapp currently integrates with Walmart’s API and supports a responsive design for mobile devices.

During fall 2014, we built a proof of concept on Microsoft Windows Azure websites integrating with Intel Mashery Services for the API. We used the following Languages: PHP, JQuery, …

Governance And Organizational Sponsorship As Success Factors In Free/Libre And Open Source Software Development: An Empirical Investigation Using Structural Equation Modeling, Aleksandr Blekh

CCAC Theses and Dissertations

Recent advances in information technologies and subsequent explosive growth of computer software use in practically all aspects of everyday life provide tremendous opportunities and benefits for improving people's lives. However, significant proportion of software projects represents cancelled, abandoned or otherwise failed projects. This situation exists not only in commercial software products or government information systems, but also in an increasingly popular and important domain of free/libre and open source software (FLOSS).

The problem of failures in software development projects requires identification and understanding of the factors of success and their interrelationships. Practice and previous research suggest that governance of software …

Sensorem – An Efficient Mobile Platform For Wireless Sensor Network Visualization, Jin Ming Koh, Marcus Sak, Hwee Xian Tan, Huiguang Liang, Fachmin Folianto, Tony Quek

Research Collection School Of Computing and Information Systems

No abstract provided.

Queuevadis: Queuing Analytics Using Smartphones, Tadashi Okoshii, Lu Yu, Chetna Vig, Youngki Lee, Rajesh Krishna Balan, Archan Misra

Research Collection School Of Computing and Information Systems

We present QueueVadis, a system that addresses the problem of estimating, in real-time, the properties of queues at commonplace urban locations, such as coffee shops, taxi stands and movie theaters. Abjuring the use of any queuing-specific infrastructure sensors, QueueVadis uses participatory mobile sensing to detect both (i) the individual-level queuing episodes for any arbitrarily-shaped queue (by a characteristic locomotive signature of short bursts of "shuffling forward" between periods of "standing") and (ii) the aggregate-level queue properties (such as expected wait or service times) via appropriate statistical aggregation of multi-person data. Moreover, for venues where multiple queues are too close …

High-Throughput Reliable Multicast In Multi-Hop Wireless Mesh Networks, Xin Zhao, Jun Guo, Chun Tung Chou, Archan Misra, Sanjay K. Jha

Research Collection School Of Computing and Information Systems

This paper presents a cross-layer approach for enabling high-throughput reliable multicast in multi-hop wireless mesh networks. The building block of our approach is a multicast routing metric, called the expected multicast transmission count (EMTX). EMTX is designed to capture the combined effects of MAC-layer retransmission-based reliability, wireless broadcast advantage, and link quality awareness. The EMTX of single-hop transmission of a multicast packet from a sender is the expected number of multicast transmissions (including retransmissions) required for its next-hop recipients to receive the packet successfully. We formulate the EMTX-based multicast problem with the objective of minimizing the sum of EMTX over …

Mobility Increases Localizability: A Survey On Wireless Indoor Localization Using Inertial Sensors, Zheng Yang, Chenshu Wu, Zimu Zhou, Xinglin Zhang, Xu Wang, Yunhao Liy

Research Collection School Of Computing and Information Systems

Wireless indoor positioning has been extensively studied for the past two decades and continuously attracted growing research efforts in mobile computing context. As the integration of multiple inertial sensors (e.g., accelerometer, gyroscope, and magnetometer) to nowadays smartphones in recent years, human-centric mobility sensing is emerging and coming into vogue. Mobility information, as a new dimension in addition to wireless signals, can benefit localization in a number of ways, since location and mobility are by nature related in physical world. In this article, we survey this new trend of mobility enhancing smartphone-based indoor localization. Specifically, we first study how to measure …

Effect Of Machine Translation In Interlingual Conversation: Lessons From A Formative Study, Kotaro Hara, Shamsi T. Iqbal

Research Collection School Of Computing and Information Systems

Language barrier is the primary challenge for effectivecross-lingual conversations. Spoken language translation(SLT) is perceived as a cost-effective alternative to lessaffordable human interpreters, but little research has beendone on how people interact with such technology. Using aprototype translator application, we performed a formativeevaluation to elicit how people interact with the technologyand adapt their conversation style. We conducted two setsof studies with a total of 23 pairs (46 participants).Participants worked on storytelling tasks to simulate naturalconversations with 3 different interface settings. Ourfindings show that collocutors naturally adapt their style ofspeech production and comprehension to compensate forinadequacies in SLT. We conclude the paper …

An Empirical Assessment Of Bellon's Clone Benchmark, Alan Charpentier, Jean-Rémy Falleri, David Lo, Laurent Reveillere

Research Collection School Of Computing and Information Systems

Context: Clone benchmarks are essential to the assessment and improvement of clone detection tools and algorithms. Among existing benchmarks, Bellon's benchmark is widely used by the research community. However, a serious threat to the validity of this benchmark is that reference clones it contains have been manually validated by Bellon alone. Other persons may disagree with Bellon's judgment. Objective: In this paper, we perform an empirical assessment of Bellon's benchmark. Method: We seek the opinion of eighteen participants on a subset of Bellon's benchmark to determine if researchers should trust the reference clones it contains. Results: Our experiment shows that …

Exploring Discriminative Features For Anomaly Detection In Public Spaces, Shriguru Nayak, Archan Misra, Kasthuri Jeyarajah, Philips Kokoh Prasetyo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Context data, collected either from mobile devices or from user-generated social media content, can help identify abnormal behavioural patterns in public spaces (e.g., shopping malls, college campuses or downtown city areas). Spatiotemporal analysis of such data streams provides a compelling new approach towards automatically creating real-time urban situational awareness, especially about events that are unanticipated or that evolve very rapidly. In this work, we use real-life datasets collected via SMU's LiveLabs testbed or via SMU's Palanteer software, to explore various discriminative features (both spatial and temporal - e.g., occupancy volumes, rate of change in topic{specific tweets or probabilistic distribution of …

Maximizing Lifetime In Clustered Wsns With Energy Harvesting Relay: Profiling And Modeling, Pengfei Zhang, Hwee-Pink Tan, Gaoxi Xiao, Yi Yu

Research Collection School Of Computing and Information Systems

Inspired by clustering and energy harvesting techniques, we study multiple-cluster wireless sensor networks with energy harvesting (EH) sensors serving as relay for cluster heads. In this paper, we derive the model for realistic energy harvesting rate. Then we propose distributed matching algorithm for EHs to serve as relay for CHs. The proposed algorithm could find optimal/near-optimal CH-EH matching in short time and still achieve good performance. We evaluate the performance of our method through theoretical analysis as well as simulation.

Markov Decision Processes With Applications In Wireless Sensor Networks: A Survey, Abu Mohammad Alsheikh, Dinh Thai Hoang, Dusit Niyato, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are used to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process …

Evaluating Defect Prediction Using A Massive Set Of Metrics, Xiao Xuan, David Lo, Xin Xia, Yuan Tian

Research Collection School Of Computing and Information Systems

To evaluate the performance of a within-project defect prediction approach, people normally use precision, recall, and F-measure scores. However, in machine learning literature, there are a large number of evaluation metrics to evaluate the performance of an algorithm, (e.g., Matthews Correlation Coefficient, G-means, etc.), and these metrics evaluate an approach from different aspects. In this paper, we investigate the performance of within-project defect prediction approaches on a large number of evaluation metrics. We choose 6 state-of-the-art approaches including naive Bayes, decision tree, logistic regression, kNN, random forest and Bayesian network which are widely used in defect prediction literature. And we …

Interpreting Multitouch Gestures, Michael Schuweiler

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

Interpreting multitouch interactions can be as simple as understanding code that handles these multitouches and this code's associated actions. As more touch events are added to an input, inputs become more complex. There are multiple approaches to interpreting these inputs between users and touchscreens. Researchers in this field find answers to common problems and provide developers with tools that make interactions with multitouch devices easier to describe and incorporate into their systems. These tools are then used to create gestures through different approaches, specifically through demonstration and by declaration. In this paper, these researchers' tools are described and compared.

How To Speed Up Software Migration And Modernization: Successful Strategies Developed By Precisiating Expert Knowledge, Francisco Zapata, Octavio Lerma, Leobardo Valera, Vladik Kreinovich

Departmental Technical Reports (CS)

Computers are getting faster and faster; the operating systems are getting more sophisticated. Often, these improvements necessitate that we migrate the existing software to the new platform. In the ideal world, the migrated software should run perfectly well on a new platform; however, in reality, when we try that, thousands of errors appear, errors that need correcting. As a result, software migration is usually a very time-consuming process. A natural way to speed up this process is to take into account that errors naturally fall into different categories, and often, a common correction can be applied to all error from …

Leading Undergraduate Students To Big Data Generation, Jianjun Yang, Ju Shen

Computer Science Faculty Publications

People are facing a flood of data today. Data are being collected at unprecedented scale in many areas, such as networking, image processing, virtualization, scientific computation, and algorithms. The huge data nowadays are called Big Data. Big data is an all encompassing term for any collection of data sets so large and complex that it becomes difficult to process them using traditional data processing applications. In this article, the authors present a unique way which uses network simulator and tools of image processing to train students abilities to learn, analyze, manipulate, and apply Big Data. Thus they develop students hands-on …

Improving Public Transit Accessibility For Blind Riders By Crowdsourcing Bus Stop Landmark Locations With Google Street View: An Extended Analysis, 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 physical landmarks to help locate and verify bus stoplocations (e.g., by searching for an expected shelter, bench, or newspaper bin). However, there are currentlyfew, if any, methods to determine this information a priori via computational tools or services. In thisarticle, we introduce and evaluate a new scalable method for collecting bus stop location and landmarkdescriptions by combining online crowdsourcing and Google Street View (GSV). We conduct and report onthree studies: (i) a formative interview study of 18 people with visual impairments to inform the designof our crowdsourcing tool, (ii) a comparative …

Code Coverage And Test Suite Effectiveness: Empirical Study With Real Bugs In Large Systems, Pavneet Singh Kochhar, Ferdian Thung, David Lo

Research Collection School Of Computing and Information Systems

During software maintenance, testing is a crucial activity to ensure the quality of program code as it evolves over time. With the increasing size and complexity of software, adequate software testing has become increasingly important. Code coverage is often used as a yardstick to gauge the comprehensiveness of test cases and the adequacy of testing. A test suite quality is often measured by the number of bugs it can find (aka. kill). Previous studies have analysed the quality of a test suite by its ability to kill mutants, i.e., artificially seeded faults. However, mutants do not necessarily represent real bugs. …

The Case For Smartwatch-Based Diet Monitoring, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

We explore the use of gesture recognition on a wrist-worn smartwatch as an enabler of an automated eating activity (and diet monitoring) system. We show, using small-scale user studies, how it is possible to use the accelerometer and gyroscope data from a smartwatch to accurately separate eating episodes from similar non-eating activities, and to additionally identify the mode of eating (i.e., using a spoon, bare hands or chopsticks). Additionally, we investigate the likelihood of automatically triggering the smartwatch's camera to capture clear images of the food being consumed, for possible offline analysis to identify what (and how much) the user …

Using Infrastructure-Provided Context Filters For Efficient Fine-Grained Activity Sensing, Vigneshwaran Subbaraju, Sougata Sen, Archan Misra, Satyadip Chakraborty, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

While mobile and wearable sensing can capture unique insights into fine-grained activities (such as gestures and limb-based actions) at an individual level, their energy overheads are still prohibitive enough to prevent them from being executed continuously. In this paper, we explore practical alternatives to addressing this challenge-by exploring how cheap infrastructure sensors or information sources (e.g., BLE beacons) can be harnessed with such mobile/wearable sensors to provide an effective solution that reduces energy consumption without sacrificing accuracy. The key idea is that many fine-grained activities that we desire to capture are specific to certain location, movement or background context: infrastructure …

A Web-Based Temperature Monitoring System For The College Of Arts And Letters, Rigoberto Solorio

Electronic Theses, Projects, and Dissertations

In general, server rooms have restricted access requiring that staff possess access codes, keys, etc. Normally, only administrators are provided access to protect the physical hardware and the data stored in the servers. Servers also have firewalls to restrict outsiders from accessing them via the Internet. Servers also cost a lot of money. For this reason, server rooms also need to be protected against overheating. This will prolong the lifecycle of the units and can prevent data loss from hardware failure.

The California State University San Bernardino (CSUSB), Specifically the College of Arts and Letters server room has faced power …

Sensorless Sensing With Wifi, Zimu Zhou, Chenshu Wu, Zheng Yang, Yunhao Liu

Research Collection School Of Computing and Information Systems

Can WiFi signals be used for sensing purpose? The growing PHY layer capabilities of WiFi has made it possible to reuse WiFi signals for both communication and sensing. Sensing via WiFi would enable remote sensing without wearable sensors, simultaneous perception and data transmission without extra communication infrastructure, and contactless sensing in privacypreserving mode. Due to the popularity of WiFi devices and the ubiquitous deployment of WiFi networks, WiFi-based sensing networks, if fully connected, would potentially rank as one of the world’s largest wireless sensor networks. Yet the concept of wireless, sensorless and contactless sensing is no simple combination of WiFi …

Hole Detection And Shape-Free Representation And Double Landmarks Based Geographic Routing In Wireless Sensor Networks, Jianjun Yang, Zongming Fei, Ju Shen

Computer Science Faculty Publications

In wireless sensor networks, an important issue of geographic routing is “local minimum” problem, which is caused by a “hole” that blocks the greedy forwarding process. Existing geographic routing algorithms use perimeter routing strategies to find a long detour path when such a situation occurs. To avoid the long detour path, recent research focuses on detecting the hole in advance, then the nodes located on the boundary of the hole advertise the hole information to the nodes near the hole. Hence the long detour path can be avoided in future routing. We propose a heuristic hole detecting algorithm which identifies …

Will This Be Quick? A Case Study Of Bug Resolution Times Across Industrial Projects, Subhajit Datta, Prasanth Lade

Research Collection School Of Computing and Information Systems

Resolution of problem tickets is a source of significant revenue in the worldwide software services industry. Due to the high volume of problem tickets in any large scale customer engagement, automated techniques are necessary to segregate related incoming tickets into groups. Existing techniques focus on this classification problem. In this paper, we present a case study built around the position that predicting the category of resolution times within a class of tickets and also the actual resolution times, is strongly beneficial to ticket resolution. We present an approach based on topic analysis to predict the category of resolution times of …

Mapping Legume Roots Can Determine Best Performing Crops, Frédérique C. Guinel

Clear Language Summaries

Legume plants have a mutually beneficial relationship with bacteria. These beneficial bacteria live in nodules found on plant roots. Until recently there was no way to systematically measure the roots the nodules are found on and to place accurately the nodules on these roots. The research team created software and a method to measure multiple root parameters which were not available previously. This allows different plant varieties to be compared with precise measurements of the root structure in order to figure out which plants will grow better.

Optimizing Pred(25) Is Np-Hard, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Usually, in data processing, to find the parameters of the models that best fits the data, people use the Least Squares method. One of the advantages of this method is that for linear models, it leads to an easy-to-solve system of linear equations. A limitation of this method is that even a single outlier can ruin the corresponding estimates; thus, more robust methods are needed. In particular, in software engineering, often, a more robust pred(25) method is used, in which we maximize the number of cases in which the model's prediction is within the 25% range of the observations. In …