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Articles 2131 - 2160 of 4404

Full-Text Articles in Software Engineering

Technology-Enabled Medication Adherence For Seniors Living In The Community: Experiences, Lessons, And The Road Ahead, Hwee Xian Tan, Hwee-Pink Tan, Huiguang Liang Jul 2018

Technology-Enabled Medication Adherence For Seniors Living In The Community: Experiences, Lessons, And The Road Ahead, Hwee Xian Tan, Hwee-Pink Tan, Huiguang Liang

Research Collection School Of Computing and Information Systems

Medication non-adherence in seniors can lead to severe health complications, including morbidity, mortality and decreased quality of life. In view of ageing populations worldwide, there is significant interest among the healthcare sector and researchers to improve medication adherence rates for seniors. However, existing studies in the literature focus primarily on identifying the predictors of medication non-adherence. In this paper, we present our work on technology-enabled medication adherence for 24 community-dwelling seniors over a period of more than 2 years. We leverage Internet of Things (IoT) devices to track inferred medication consumption in the seniors’ homes, and provide quasi real-time alerts …

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Experiences & Challenges With Server-Side Wifi Indoor Localization Using Existing Infrastructure, Dheryta Jaisinghani, Rajesh Krishna Balan, Vinayak Naik, Archan Misra, Youngki Lee Jul 2018

Experiences & Challenges With Server-Side Wifi Indoor Localization Using Existing Infrastructure, Dheryta Jaisinghani, Rajesh Krishna Balan, Vinayak Naik, Archan Misra, Youngki Lee

Research Collection School Of Computing and Information Systems

Real-world deployments of WiFi-based indoor localization in large public venues are few and far between as most state-of-the-art solutions require either client or infrastructure-side changes. Hence, even though high location accuracy is possible with these solutions, they are not practical due to cost and/or client adoption reasons. Majority of the public venues use commercial controller-managed WLAN solutions, that neither allow client changes nor infrastructure changes. In fact, for such venues we have observed highly heterogeneous devices with very low adoption rates for client-side apps. In this paper, we present our experiences in deploying a scalable location system for such venues. …

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Deep Specification Mining, Tien-Duy B. Le, David Lo Jul 2018

Deep Specification Mining, Tien-Duy B. Le, David Lo

Research Collection School Of Computing and Information Systems

Formal specifications are essential but usually unavailable in software systems. Furthermore, writing these specifications is costly and requires skills from developers. Recently, many automated techniques have been proposed to mine specifications in various formats including finite-state automaton (FSA). However, more works in specification mining are needed to further improve the accuracy of the inferred specifications. In this work, we propose Deep Specification Miner (DSM), a new approach that performs deep learning for mining FSA-based specifications. Our proposed approach uses test case generation to generate a richer set of execution traces for training a Recurrent Neural Network Based Language Model (RNNLM). …

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Summarizing Source Code With Transferred Api Knowledge, Xing Hu, Ge Li, Xin Xia, David Lo, Shuai Lu, Zhi Jin Jul 2018

Summarizing Source Code With Transferred Api Knowledge, Xing Hu, Ge Li, Xin Xia, David Lo, Shuai Lu, Zhi Jin

Research Collection School Of Computing and Information Systems

Code summarization, aiming to generate succinct natural language description of source code, is extremely useful for code search and code comprehension. It has played an important role in software maintenance and evolution. Previous approaches generate summaries by retrieving summaries from similar code snippets. However, these approaches heavily rely on whether similar code snippets can be retrieved, how similar the snippets are, and fail to capture the API knowledge in the source code, which carries vital information about the functionality of the source code. In this paper, we propose a novel approach, named TL-CodeSum, which successfully uses API knowledge learned in …

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A Survey On Sensor Calibration In Air Pollution Monitoring Deployments, Balz Maah, Zimu Zhou, Lothar Thiele Jul 2018

A Survey On Sensor Calibration In Air Pollution Monitoring Deployments, Balz Maah, Zimu Zhou, Lothar Thiele

Research Collection School Of Computing and Information Systems

Air pollution is a major concern for public health and urban environments. Conventional air pollution monitoring systems install a few highly accurate, expensive stations at representative locations. Their sparse coverage and low spatial resolution are insufficient to quantify urban air pollution and its impacts on human health and environment. Advances in lowcost portable air pollution sensors have enabled air pollution monitoring deployments at scale to measure air pollution at high spatiotemporal resolution. However, it is challenging to ensure the accuracy of these low-cost sensor deployments because the sensors are more error-prone than high-end sensing infrastructures and they are often deployed …

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Kbase: The United States Department Of Energy Systems Biology Knowledgebase, Adam P. Arkin, Robert W. Cottingham, Christopher S. Henry, Nomi L. Harris, Rick L. Stevens, Sergei Maslov, Doreen Ware, Fernando Perez, Shane Canon, Michael W. Sneddon, Matthew L. Henderson, William J. Riehl, Dan Murphy-Olson, Stephen Y. Chan, Roy T. Kamimura, Sunita Kumari, Meghan M. Drake, Thomas S. Brettin, Elizabeth M. Glass, Dylan Chivian, Dan Gunter, David J. Weston, Benjamin H. Allen, Jason Baumohl, Nathan L. Tintle Jul 2018

Kbase: The United States Department Of Energy Systems Biology Knowledgebase, Adam P. Arkin, Robert W. Cottingham, Christopher S. Henry, Nomi L. Harris, Rick L. Stevens, Sergei Maslov, Doreen Ware, Fernando Perez, Shane Canon, Michael W. Sneddon, Matthew L. Henderson, William J. Riehl, Dan Murphy-Olson, Stephen Y. Chan, Roy T. Kamimura, Sunita Kumari, Meghan M. Drake, Thomas S. Brettin, Elizabeth M. Glass, Dylan Chivian, Dan Gunter, David J. Weston, Benjamin H. Allen, Jason Baumohl, Nathan L. Tintle

Faculty Work Comprehensive List

No abstract provided.

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Identifying Elderlies At Risk Of Becoming More Depressed With Internet-Of-Things, Jiajue Ou, Huiguang Liang, Hwee Xian Tan Jul 2018

Identifying Elderlies At Risk Of Becoming More Depressed With Internet-Of-Things, Jiajue Ou, Huiguang Liang, Hwee Xian Tan

Research Collection School Of Computing and Information Systems

Depression in the elderly is common and dangerous. Current methods to monitor elderly depression, however, are costly, time-consuming and inefficient. In this paper, we present a novel depression-monitoring system that infers an elderly’s changes in depression level based on his/her activity patterns, extracted from wireless sensor data. To do so, we build predictive models to learn the relationship between depression level changes and behaviors using historical data. We also deploy the system for a group of elderly, in their homes, and run the experiments for more than one year. Our experimental study gives encouraging results, suggesting that our IoT system …

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Unobtrusive Detection Of Frailty In Older Adults, Nadee Goonawardene, Hwee-Pink Tan, Lee Buay Tan Jul 2018

Unobtrusive Detection Of Frailty In Older Adults, Nadee Goonawardene, Hwee-Pink Tan, Lee Buay Tan

Research Collection School Of Computing and Information Systems

Sensor technologies have gained attention as an effective means to monitor physical and mental wellbeing of elderly. In this study, we examined the possibility of using passive in-home sensors to detect frailty in older adults based on their day-to-day in-home living pattern. The sensor-based elderly monitoring system consists of PIR motion sensors and a door contact sensor attached to the main door. A set of pre-defined features associated with elderly’s day-to-day living patterns were derived based on sensor data of 46 elderly gathered over two different time periods. A series of feature vectors depicting different behavioral aspects were derived to …

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Characterizing Common And Domain-Specific Package Bugs: A Case Study On Ubuntu, Xiaoxue Ren, Qiao Huang, Xin Xia, Zhenchang Xing, Lingfeng Bao, David Lo Jul 2018

Characterizing Common And Domain-Specific Package Bugs: A Case Study On Ubuntu, Xiaoxue Ren, Qiao Huang, Xin Xia, Zhenchang Xing, Lingfeng Bao, David Lo

Research Collection School Of Computing and Information Systems

Ubuntu is an open source software platform that runs everywhere from the smartphone, the tablet and the PC to the server and the cloud. In Ubuntu, there are many self-contained or third-party software packages for different use, and a bug report in Ubuntu could affect one or more packages simultaneously. Identifying the common package bugs in Ubuntu can help both developers and users better understand the packages they are developing or using, and also provide further guidelines to developers of similar packages in the future. In this paper, we perform a large-scale empirical study of common package bugs on Ubuntu …

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A Unified Approach To Route Planning For Shared Mobility, Yongxin Tong, Yuxiang Zeng, Zimu Zhou, Lei Chen, Jieping Ye, Ke Xu Jul 2018

A Unified Approach To Route Planning For Shared Mobility, Yongxin Tong, Yuxiang Zeng, Zimu Zhou, Lei Chen, Jieping Ye, Ke Xu

Research Collection School Of Computing and Information Systems

There has been a dramatic growth of shared mobility applications such as ride-sharing, food delivery and crowdsourced parcel delivery. Shared mobility refers to transportation services that are shared among users, where a central issue is route planning. Given a set of workers and requests, route planning finds for each worker a route, i.e., a sequence of locations to pick up and drop off passengers/parcels that arrive from time to time, with different optimization objectives. Previous studies lack practicability due to their conflicted objectives and inefficiency in inserting a new request into a route, a basic operation called insertion. In this …

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Using Eeg-Validated Music Emotion Recognition Techniques To Classify Multi-Genre Popular Music For Therapeutic Purposes, Dejoy Shastikk Kumaran Jun 2018

Using Eeg-Validated Music Emotion Recognition Techniques To Classify Multi-Genre Popular Music For Therapeutic Purposes, Dejoy Shastikk Kumaran

The International Student Science Fair 2018

Music is observed to possess significant beneficial effects to human mental health, especially for patients undergoing therapy and older adults. Prior research focusing on machine recognition of the emotion music induces by classifying low-level music features has utilized subjective annotation to label data for classification. We validate this approach by using an electroencephalography-based approach to cross-check the predictions of music emotion made with the predictions from low-level music feature data as well as collected subjective annotation data. Collecting 8-channel EEG data from 10 participants listening to segments of 40 songs from 5 different genres, we obtain a subject-independent classification accuracy …

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Using Eeg-Validated Music Emotion Recognition Techniques To Classify Multi-Genre Popular Music For Therapeutic Purposes, Dejoy Shastikk Kumaran Jun 2018

Using Eeg-Validated Music Emotion Recognition Techniques To Classify Multi-Genre Popular Music For Therapeutic Purposes, Dejoy Shastikk Kumaran

The International Student Science Fair 2018

Music is observed to possess significant beneficial effects to human mental health, especially for patients undergoing therapy and older adults. Prior research focusing on machine recognition of the emotion music induces by classifying low-level music features has utilized subjective annotation to label data for classification. We validate this approach by using an electroencephalography-based approach to cross-check the predictions of music emotion made with the predictions from low-level music feature data as well as collected subjective annotation data. Collecting 8-channel EEG data from 10 participants listening to segments of 40 songs from 5 different genres, we obtain a subject-independent classification accuracy …

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An Integrated Approach For Effective Injection Vulnerability Analysis Of Web Applications Through Security Slicing And Hybrid Constraint Solving, Julian Thome, Lwin Khin Shar, Domenico Bianculli, Lionel Briand Jun 2018

An Integrated Approach For Effective Injection Vulnerability Analysis Of Web Applications Through Security Slicing And Hybrid Constraint Solving, Julian Thome, Lwin Khin Shar, Domenico Bianculli, Lionel Briand

Research Collection School Of Computing and Information Systems

Malicious users can attack Web applications by exploiting injection vulnerabilities in the source code. This work addresses the challenge of detecting injection vulnerabilities in the server-side code of Java Web applications in a scalable and effective way. We propose an integrated approach that seamlessly combines security slicing with hybrid constraint solving; the latter orchestrates automata-based solving with meta-heuristic search. We use static analysis to extract minimal program slices relevant to security from Web programs and to generate attack conditions. We then apply hybrid constraint solving to determine the satisfiability of attack conditions and thus detect vulnerabilities. The experimental results, using …

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Towards Optimal Concolic Testing, Xinyu Wang, Jun Sun, Zhenbang Chen, Peixin Zhang, Jingyi Wang, Yun Lin Jun 2018

Towards Optimal Concolic Testing, Xinyu Wang, Jun Sun, Zhenbang Chen, Peixin Zhang, Jingyi Wang, Yun Lin

Research Collection School Of Computing and Information Systems

Concolic testing integrates concrete execution (e.g., random testing) and symbolic execution for test case generation. It is shown to be more cost-effective than random testing or symbolic execution sometimes. A concolic testing strategy is a function which decides when to apply random testing or symbolic execution, and if it is the latter case, which program path to symbolically execute. Many heuristics-based strategies have been proposed. It is still an open problem what is the optimal concolic testing strategy. In this work, we make two contributions towards solving this problem. First, we show the optimal strategy can be defined based on …

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Static Analysis Of Context Leaks In Android Applications, Flavio Toffalini, Jun Sun, Martín Cohoa Jun 2018

Static Analysis Of Context Leaks In Android Applications, Flavio Toffalini, Jun Sun, Martín Cohoa

Research Collection School Of Computing and Information Systems

Android native applications, written in Java and distributed in APK format, are widely used in mobile devices. Their specific pattern of use lets the operating system control the creation and destruction of key resources, such as activities and services (contexts). Programmers are not supposed to interfere with such lifecycle events. Otherwise contexts might be leaked, i.e. they will never be deallocated from memory, or be deallocated too late, leading to memory exhaustion and frozen applications. In practice, it is easy to write incorrect code, which hinders garbage collection of contexts and subsequently leads to context leakage.In this work, we present …

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Analysing Popularity Of Software Testing Careers In Canada, Luiz Fernando Capretz, Pradeep Waychal, Sachin Pardeshi Jun 2018

Analysing Popularity Of Software Testing Careers In Canada, Luiz Fernando Capretz, Pradeep Waychal, Sachin Pardeshi

Electrical and Computer Engineering Publications

Software testing is critical to prevent software failures. Therefore, research has been carried out in testing but that is largely limited to the processand technology dimensions and has not sufficiently addressed the human dimension. Even though there are reports about inadequacies of testing professionals and their skills, only a few studies have tackled the problem. Therefore, we decided to explore the human dimension. We started with the basic problem that plagues the testing profession, the shortage of talent, by asking why do students and professionals are reluctant to consider testing careers, what can be done about that, and is the …

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Funqual: User-Defined, Statically-Checked Call Graph Constraints In C++, Andrew P. Nelson Jun 2018

Funqual: User-Defined, Statically-Checked Call Graph Constraints In C++, Andrew P. Nelson

Master's Theses

Static analysis tools can aid programmers by reporting potential programming mistakes prior to the execution of a program. Funqual is a static analysis tool that reads C++17 code ``in the wild'' and checks that the function call graph follows a set of rules which can be defined by the user. This sort of analysis can help the programmer to avoid errors such as accidentally calling blocking functions in time-sensitive contexts or accidentally allocating memory in heap-sensitive environments. To accomplish this, we create a type system whereby functions can be given user-defined type qualifiers and where users can define their own …

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The Effect Of Endgame Tablebases On Modern Chess Engines, Christopher D. Peterson Jun 2018

The Effect Of Endgame Tablebases On Modern Chess Engines, Christopher D. Peterson

Computer Engineering

Modern chess engines have the ability to augment their evaluation by using massive tables containing billions of positions and their memorized solutions. This report examines the importance of these tables to better understand the circumstances under which they should be used. The analysis conducted in this paper empirically examines differences in size and speed of memorized positions and their impacts on engine strength. Using this technique, situations where memorized tables improve play (and situations where they do not) are discovered.

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Analysing Multi-Point Multi-Frequency Machine Vibrations Using Optical Sampling, Dibyendu Roy, Avik Ghose, Tapas Chakravarty, Sushovan Mukherjee, Arpan Pal, Archan Misra Jun 2018

Analysing Multi-Point Multi-Frequency Machine Vibrations Using Optical Sampling, Dibyendu Roy, Avik Ghose, Tapas Chakravarty, Sushovan Mukherjee, Arpan Pal, Archan Misra

Research Collection School Of Computing and Information Systems

Vibration analysis is a key troubleshooting methodology for assessing the health of factory machinery. We propose an unobtrusive framework for at-a-distance visual estimation of such (possibly high frequency) vibrations, using a low fps (frames-per-second) camera that may, for example, be mounted on a worker's smart-glass. Our key innovation is to use an external stroboscopic light source (that, for example, may be provided by an assistive robot), to illuminate the machine with multiple mutually-prime strobing frequencies, and use the resulting aliased signals to efficiently estimate the different vibration frequencies via an enhanced version of the Chinese Remainder Theorem. Experimental results show …

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Advanced Malware Detection For Android Platform, Ke Xu Jun 2018

Advanced Malware Detection For Android Platform, Ke Xu

Dissertations and Theses Collection (Open Access)

In the first quarter of 2018, 75.66% of smartphones sales were devices running An- droid. Due to its popularity, cyber-criminals have increasingly targeted this ecosys- tem. Malware running on Android severely violates end users security and privacy, allowing many attacks such as defeating two factor authentication of mobile bank- ing applications, capturing real-time voice calls and leaking sensitive information. In this dissertation, I describe the pieces of work that I have done to effectively de- tect malware on Android platform, i.e., ICC-based malware detection system (IC- CDetector), multi-layer malware detection system (DeepRefiner), and self-evolving and scalable malware detection system (DroidEvolver) …

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On-Demand Deep Model Compression For Mobile Devices: A Usage-Driven Model Selection Framework, Sicong Liu, Yingyan Lin, Zimu Zhou, Kaiming Nan, Hui Liu, Junzhao Du Jun 2018

On-Demand Deep Model Compression For Mobile Devices: A Usage-Driven Model Selection Framework, Sicong Liu, Yingyan Lin, Zimu Zhou, Kaiming Nan, Hui Liu, Junzhao Du

Research Collection School Of Computing and Information Systems

Recent research has demonstrated the potential of deploying deep neural networks (DNNs) on resource-constrained mobile platforms by trimming down the network complexity using different compression techniques. The current practice only investigate stand-alone compression schemes even though each compression technique may be well suited only for certain types of DNN layers. Also, these compression techniques are optimized merely for the inference accuracy of DNNs, without explicitly considering other application-driven system performance (e.g. latency and energy cost) and the varying resource availabilities across platforms (e.g. storage and processing capability). In this paper, we explore the desirable tradeoff between performance and resource constraints …

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Region-Aware Reflection Removal With Unified Content And Gradient Priors, Renjie Wan, Boxin Shi, Ling-Yu Duan, Ah-Hwee Tan, Wen Gao, Alex C. Kot Jun 2018

Region-Aware Reflection Removal With Unified Content And Gradient Priors, Renjie Wan, Boxin Shi, Ling-Yu Duan, Ah-Hwee Tan, Wen Gao, Alex C. Kot

Research Collection School Of Computing and Information Systems

Removing the undesired reflections in images taken through the glass is of broad application to various image processing and computer vision tasks. Existing single image-based solutions heavily rely on scene priors such as separable sparse gradients caused by different levels of blur, and they are fragile when such priors are not observed. In this paper, we notice that strong reflections usually dominant a limited region in the whole image, and propose a region-aware reflection removal approach by automatically detecting and heterogeneously processing regions with and without reflections. We integrate content and gradient priors to jointly achieve missing contents restoration, as …

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Inference Of Development Activities From Interaction With Uninstrumented Applications, Lingfeng Bao, Zhenchang Xing, Xin Xia, David Lo, Ahmed E. Hassan Jun 2018

Inference Of Development Activities From Interaction With Uninstrumented Applications, Lingfeng Bao, Zhenchang Xing, Xin Xia, David Lo, Ahmed E. Hassan

Research Collection School Of Computing and Information Systems

Studying developers’ behavior in software development tasks is crucial for designing effective techniques and tools to support developers’ daily work. In modern software development, developers frequently use different applications including IDEs, Web Browsers, documentation software (such as Office Word, Excel, and PDF applications), and other tools to complete their tasks. This creates significant challenges in collecting and analyzing developers’ behavior data. Researchers usually instrument the software tools to log developers’ behavior for further studies. This is feasible for studies on development activities using specific software tools. However, instrumenting all software tools commonly used in real work settings is difficult and …

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Empath-D: Vr-Based Empathetic App Design For Accessibility, Wonjung Kim, Kenny Tsu Wei Choo, Youngki Lee, Archan Misra, Rajesh Krishna Balan Jun 2018

Empath-D: Vr-Based Empathetic App Design For Accessibility, Wonjung Kim, Kenny Tsu Wei Choo, Youngki Lee, Archan Misra, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

With app-based interaction increasingly permeating all aspects of daily living, it is essential to ensure that apps are designed to be inclusive and are usable by a wider audience such as the elderly, with various impairments (e.g., visual, audio and motor). We propose Empath-D, a system that fosters empathetic design, by allowing app designers, in-situ, to rapidly evaluate the usability of their apps, from the perspective of impaired users. To provide a truly authentic experience, Empath-D carefully orchestrates the interaction between a smartphone and a VR device, allowing the user to experience simulated impairments in a virtual world while interacting …

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Poster: Understanding The Role Of Reporting In Work Item Tracking Systems For Software Development: An Industrial Case Study, Kochhar Pavneet Singh, Stanislaw Swierc, Trevor Carnahan, Hitesh S. Sajnani, Meiyappan Nagappan Jun 2018

Poster: Understanding The Role Of Reporting In Work Item Tracking Systems For Software Development: An Industrial Case Study, Kochhar Pavneet Singh, Stanislaw Swierc, Trevor Carnahan, Hitesh S. Sajnani, Meiyappan Nagappan

Research Collection School Of Computing and Information Systems

Work item tracking systems such as Visual Studio Team Services, JIRA, and GitHub issue tracker are widely used by software engineers. They help in managing different kinds of deliverables (e.g.features, user stories, bugs), plan sprints, distribute tasks across the team and prioritize the work. While these tools provide reporting capabilities there has been little research into the role these reports play in the overall software development process. In this study, we conduct an empirical investigation on the usage of Analytics Service-A reporting service provided by Visual Studio Team Services (VSTS) to build dashboards and reports out of their work item …

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Libraryguru: Api Recommendation For Android Developers, Weizhao Yuan, Hoang H. Nguyen, Lingxiao Jiang, Yuting Chen Jun 2018

Libraryguru: Api Recommendation For Android Developers, Weizhao Yuan, Hoang H. Nguyen, Lingxiao Jiang, Yuting Chen

Research Collection School Of Computing and Information Systems

Developing modern mobile applications often require the uses of many libraries specific for the mobile platform, which can be overwhelmingly too many for application developers to find what are needed for a functionality and where and how to use them properly. This paper presents a tool, named LibraryGuru, to recommend suitable Android APIs for given functionality descriptions. It not only recommends functional APIs that can be invoked for implementing the functionality, but also recommends event callback APIs that are inherent in the Android framework and need to be overridden in the application. LibraryGuru internally builds correlation databases among various functionality …

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D-Pruner: Filter-Based Pruning Method For Deep Convolutional Neural Network, Nguyen Loc Huynh, Youngki Lee, Rajesh Krishna Balan Jun 2018

D-Pruner: Filter-Based Pruning Method For Deep Convolutional Neural Network, Nguyen Loc Huynh, Youngki Lee, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

The emergence of augmented reality devices such as Google Glass and Microsoft Hololens has opened up a new class of vision sensing applications. Those applications often require the ability to continuously capture and analyze contextual information from video streams. They often adopt various deep learning algorithms such as convolutional neural networks (CNN) to achieve high recognition accuracy while facing severe challenges to run computationally intensive deep learning algorithms on resource-constrained mobile devices. In this paper, we propose and explore a new class of compression technique called D-Pruner to efficiently prune redundant parameters within a CNN model to run the model …

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D-Pruner: Filter-Based Pruning Method For Deep Convolutional Neural Network, Nguyen Loc Huynh, Youngki Lee, Rajesh Krishna Balan Jun 2018

D-Pruner: Filter-Based Pruning Method For Deep Convolutional Neural Network, Nguyen Loc Huynh, Youngki Lee, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

The emergence of augmented reality devices such as Google Glass and Microsoft Hololens has opened up a new class of vision sensing applications. Those applications often require the ability to continuously capture and analyze contextual information from video streams. They often adopt various deep learning algorithms such as convolutional neural networks (CNN) to achieve high recognition accuracy while facing severe challenges to run computationally intensive deep learning algorithms on resource-constrained mobile devices. In this paper, we propose and explore a new class of compression technique called D-Pruner to efficiently prune redundant parameters within a CNN model to run the model …

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Annapurna: Building A Real-World Smartwatch-Based Automated Food Journal, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan, Youngki Lee Jun 2018

Annapurna: Building A Real-World Smartwatch-Based Automated Food Journal, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

We describe the design and implementation of a smartwatch-based, completely unobtrusive, food journaling system, where the smartwatch helps to intelligently capture useful images of food that an individual consumes throughout the day. The overall system, called Annapurna, is based on three key components: (a) a smartwatch-based gesture recognizer to identify eating gestures, (b) a smartwatch-based image capturer that obtains a small set of relevant and useful images with a low energy overhead, and (c) a server-based image filtering engine that removes irrelevant uploaded images, and then catalogs them through a portal. Our primary challenge is to make the system robust …

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Jupyterlab_Voyager: A Data Visualization Enhancement In Jupyterlab, Ji Zhang Jun 2018

Jupyterlab_Voyager: A Data Visualization Enhancement In Jupyterlab, Ji Zhang

Master's Theses

With the emergence of big data, scientific data analysis and visualization (DAV) tools are critical components of the data science software ecosystem; the usability of these tools is becoming extremely important to facilitate next-generation scientific discoveries. JupyterLab has been considered as one of the best polyglot, web-based, open-source data science tools. As the next phase of extensible interface for the classic iPython Notebooks, this tool supports interactive data science and scientific computing across multiple programming languages with great performances. Despite these advantages, previous heuristics evaluation studies have shown that JupyterLab has some significant flaws in the data visualization side. The …

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