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The Elder Scrolls V: Skyrim Stamina Combat Overhaul, Richard Rattner 2016 California Polytechnic State University, San Luis Obispo

The Elder Scrolls V: Skyrim Stamina Combat Overhaul, Richard Rattner

Liberal Arts and Engineering Studies

No abstract provided.


Deepsense: A Gpu-Based Deep Convolutional Neural Network Framework On Commodity Mobile Devices, HUYNH NGUYEN LOC, Rajesh Krishna BALAN, Youngki LEE 2016 Singapore Management University

Deepsense: A Gpu-Based Deep Convolutional Neural Network Framework On Commodity Mobile Devices, Huynh Nguyen Loc, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

Recently, a branch of machine learning algorithms called deep learning gained huge attention to boost up accuracy of a variety of sensing applications. However, execution of deep learning algorithm such as convolutional neural network on mobile processor is non-trivial due to intensive computational requirements. In this paper, we present our early design of DeepSense - a mobile GPU-based deep convolutional neural network (CNN) framework. For its design, we first explored the differences between server-class and mobile-class GPUs, and studied effectiveness of various optimization strategies such as branch divergence elimination and memory vectorization. Our results show that DeepSense is able to …


Demo: Drumming Application Using Commodity Wearable Devices, Bharat DWIVEDI, Archan MISRA, Youngki LEE 2016 Singapore Management University

Demo: Drumming Application Using Commodity Wearable Devices, Bharat Dwivedi, Archan Misra, Youngki Lee

Research Collection School Of Computing and Information Systems

We aim to develop a drumming application in which individual can play drums using multiple wearable and mobile devices. Our vision is to tap out different rythms in the air using smart watches as a virtual drum stick and smart phone would act as a drum kit. Same user interface can be visualized in smart glasses. Here, our prime target is to use multiple commodity wearable devices (non-commodity i.e. Myo arm band) and smart phones for recognizing new (or same type of here) types of multi limb gestural context and building an adaptive application interface and allow such gesture recognition …


Demo: Gpu-Based Image Recognition And Object Detection On Commodity Mobile Devices, Loc Nguyen HUYNH, Rajesh Krishna BALAN, Youngki LEE 2016 Singapore Management University

Demo: Gpu-Based Image Recognition And Object Detection On Commodity Mobile Devices, Loc Nguyen Huynh, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

In this demo, we show that it is feasible to execute CNN for vision sensing tasks directly on mobile devices by leveraging integrated GPU. We propose our design of DeepSense framework based on OpenCL to execute deep learning algorithms in energy-efficient and fast manner.


Livelabs: Building In-Situ Mobile Sensing And Behavioural Experimentation Testbeds, Kasthuri JAYARAJAH, Rajesh Krishna BALAN, Meera RADHAKRISHNAN, Archan MISRA, Youngki LEE 2016 Singapore Management University

Livelabs: Building In-Situ Mobile Sensing And Behavioural Experimentation Testbeds, Kasthuri Jayarajah, Rajesh Krishna Balan, Meera Radhakrishnan, Archan Misra, Youngki Lee

Research Collection School Of Computing and Information Systems

In this paper, we present LiveLabs, a first-of-its-kind testbed that isdeployed across a university campus, convention centre, and resortisland and collects real-time attributes such as location, group contextetc., from hundreds of opt-in participants. These venues, data,and participants are then made available for running rich humancentricbehavioural experiments that could test new mobile sensinginfrastructure, applications, analytics, or more social-sciencetype hypotheses that influence and then observe actual user behaviour.We share case studies of how researchers from aroundthe world have and are using LiveLabs, and our experiences andlessons learned from building, maintaining, and expanding LiveLabsover the last three years.


Jasper: Sensing Gamers' Emotions Using Physiological Sensors, Sinh HUYNH, Youngki LEE, Taiwoo PARK, Rajesh Krishna BALAN 2016 Singapore Management University

Jasper: Sensing Gamers' Emotions Using Physiological Sensors, Sinh Huynh, Youngki Lee, Taiwoo Park, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

This paper aims to develop a system that evaluates the emotional experience of gamers based on physiological changes. A within-subject experiment with 22 participants has been designed to investigate the effects of difficulty level and social playing mode on player emotions and to examine the correlation between each emotion and the physiological changes. We demonstrate the feasibility of using commodity wearable physiological sensing devices to recognize mobile gamer's emotion. Specifically, our system performs 3-level excitement classification at an accuracy of 77.38% and binary classification of happiness state at an accuracy of 73.21%. These classification results show the potential of using …


Small Scale Deployment Of Seat Occupancy Detectors, Nguyen Huy Hoang HUY, Gihan HETTIARACHCHI, Youngki LEE, Rajesh Krishna BALAN 2016 Singapore Management University

Small Scale Deployment Of Seat Occupancy Detectors, Nguyen Huy Hoang Huy, Gihan Hettiarachchi, Youngki Lee, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

In this paper, we present the results of a small-scale field deployment of our capacitance-based seat occupancy detector. We deployed our sensors to 36 seats in our university library and measured the performance of our system over a period of 8 weeks. As part of this deployment, we had to tackle numerous real-world deployment issues such as hardware failure, variations in signal quality, and interference caused by multiple objects in near proximity. We present our overall system design, along with the modifications we made to tackle various real-world problems. Finally, we present the results of our deployment which showed that …


Poster: A Device-Free Evaluation System For Gymnastics Using Passive Rfid Tags, Binbin XIE, Jie XIONG, Dingyi FANG, Xiaojiang CHEN, Anwen WANG, Zhanyong TANG 2016 Singapore Management University

Poster: A Device-Free Evaluation System For Gymnastics Using Passive Rfid Tags, Binbin Xie, Jie Xiong, Dingyi Fang, Xiaojiang Chen, Anwen Wang, Zhanyong Tang

Research Collection School Of Computing and Information Systems

No abstract provided.


Poster: Sonicnect: Accurate Hands-Free Gesture Input System With Smart Acoustic Sensing, Maotian CHANG, Ping LI, Panlong YANG, Jie XIONG, Chang TIAN 2016 Singapore Management University

Poster: Sonicnect: Accurate Hands-Free Gesture Input System With Smart Acoustic Sensing, Maotian Chang, Ping Li, Panlong Yang, Jie Xiong, Chang Tian

Research Collection School Of Computing and Information Systems

This work presents Sonicnect, an acoustic sensing system with smartphone that enables accurate hands-free gesture input. Sonicnect leverages the embedded microphone in the smartphone to capture the subtle audio signals generated with fingers touching on the table. It supports 9 commonly used gestures (click, flip, scroll and zoom, etc) with above 92% recognition accuracy, and the minimum gesture movement could be 2cm. Distinguishable features are then extracted by exploiting spatio-temporal and frequency properties of the subtle audio signals. We conduct extensive real environment experiments to evaluate its performance. The results validate the effectiveness and robustness of Sonicnect.


Efficient Multi-Class Selective Sampling On Graphs, Peng YANG, Peilin ZHAO, Zhen HAI, Wei LIU, HOI, Steven C. H., Xiao-Li LI 2016 Singapore Management University

Efficient Multi-Class Selective Sampling On Graphs, Peng Yang, Peilin Zhao, Zhen Hai, Wei Liu, Hoi, Steven C. H., Xiao-Li Li

Research Collection School Of Computing and Information Systems

A graph-based multi-class classification problem is typically converted into a collection of binary classification tasks via the one-vs.-all strategy, and then tackled by applying proper binary classification algorithms. Unlike the one-vs.-all strategy, we suggest a unified framework which operates directly on the multi-class problem without reducing it to a collection of binary tasks. Moreover, this framework makes active learning practically feasible for multi-class problems, while the one-vs.-all strategy cannot. Specifically, we employ a novel randomized query technique to prioritize the informative instances. This query technique based on the hybrid criterion of "margin" and "uncertainty" can achieve a comparable mistake bound …


Demo: Wearable Application To Manage Problem Behavior In Children With Neurodevelopmental Disorders, Camellia ZAKARIA, Richard C. DAVIS 2016 Singapore Management University

Demo: Wearable Application To Manage Problem Behavior In Children With Neurodevelopmental Disorders, Camellia Zakaria, Richard C. Davis

Research Collection School Of Computing and Information Systems

Managing problem behaviors in children with neurodevelopmental disorders can be challenging. Such behaviors may discourage social participation and learning. Many of these behaviors warrant intervention, however, are challenging for caregivers to constantly supervise. Previous work focused on developing recognition systems for stereotypical and aggressive behaviors. Researchers also developed visualization interface for caregivers to better understand their child’s needs. Our goal however, is to design an independent behavior management application to help children manage problem behaviors with minimal supervision.We conducted a field study at a school for children with special needs in Singapore, and interviewed ten teachers. This study helped us …


Demo: Ta$Ker: Campus-Scale Mobile Crowd-Tasking Platform, Nikita JAIMAN, Thivya KANDAPPU, Randy TANDRIANSYAH, Archan MISRA 2016 Singapore Management University

Demo: Ta$Ker: Campus-Scale Mobile Crowd-Tasking Platform, Nikita Jaiman, Thivya Kandappu, Randy Tandriansyah, Archan Misra

Research Collection School Of Computing and Information Systems

We design and develop TA$Ker, a real-world mobile crowd- sourcing platform to empirically study the worker responses to various task recommendation and selection strategies.


Automated Identification Of High Impact Bug Reports Leveraging Imbalanced Learning Strategies, Xinli YANG, David LO, Qiao HUANG, Xin XIA, Jianling SUN 2016 Zhejiang University

Automated Identification Of High Impact Bug Reports Leveraging Imbalanced Learning Strategies, Xinli Yang, David Lo, Qiao Huang, Xin Xia, Jianling Sun

Research Collection School Of Computing and Information Systems

In practice, some bugs have more impact than others and thus deserve more immediate attention. Due to tight schedule and limited human resource, developers may not have enough time to inspect all bugs. Thus, they often concentrate on bugs that are highly impactful. In the literature, high impact bugs are used to refer to the bugs which appear in unexpected time or locations and bring more unexpected effects, or break pre-existing functionalities and destroy the user experience. Unfortunately, identifying high impact bugs from the thousands of bug reports in a bug tracking system is not an easy feat. Thus, an …


Cace: Exploiting Behavioral Interactions For Improved Activity Recognition In Multi-Inhabitant Smart Homes, Mohammad Arif Ul Alam, Nirmalya ROY, Archan MISRA, Joseph TAYLOR 2016 Singapore Management University

Cace: Exploiting Behavioral Interactions For Improved Activity Recognition In Multi-Inhabitant Smart Homes, Mohammad Arif Ul Alam, Nirmalya Roy, Archan Misra, Joseph Taylor

Research Collection School Of Computing and Information Systems

We propose CACE (Constraints And Correlations mining Engine) which investigates the challenges of improving the recognition of complex daily activities in multi-inhabitant smart homes, by better exploiting the spatiotemporal relationships across the activities of different individuals. We first propose and develop a loosely-coupled Hierarchical Dynamic Bayesian Network (HDBN), which both (a) captures the hierarchical inference of complex (macro-activity) contexts from lower-layer microactivity context (postural and improved oral gestural context), and (b) embeds the various types of behavioral correlations and constraints (at both micro-and macro-activity contexts) across the individuals. While this model is rich in terms of accuracy, it is computationally …


Poster: Air Quality Friendly Route Recommendation System, Savina SINGLA, Divya BANSAL, Archan MISRA 2016 PEC University of Technology

Poster: Air Quality Friendly Route Recommendation System, Savina Singla, Divya Bansal, Archan Misra

Research Collection School Of Computing and Information Systems

To model the overall personal inhalation of hazardous gases through the air (both indoor and outdoor) by an individual, provide air quality friendly route recommendations, thus raising the overall quality of urban movement and living healthy life.


Demo: Smartwatch Based Shopping Gesture Recognition, Meeralakshmi RADHAKRISHNAN, Sharanya ESWARAN, Sougata SEN, Vigneshwaran SUBBARAJU, Archan MISRA, Rajesh Krishna BALAN 2016 Singapore Management University

Demo: Smartwatch Based Shopping Gesture Recognition, Meeralakshmi Radhakrishnan, Sharanya Eswaran, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

In the current retail segment, the retail store owners are keen to understand the browsing behavior and purchase pattern of the shoppers inside the physical stores. Profiling the behavior of the shopper is key to success for any marketing strategies that can optimize or personalize shopping-related services in real-time. We envision that exploiting the knowledge of real-time behavior of shopper’s in-store activities enables novel applications such as: (a) targeted advertising or recommendations: based on longer term shopper profiles, (b) proactive retail help to assist the shoppers who are confused in choosing between two items, (c) smart reminders that can remind …


Value-Inspired Elderly Care Service Design For Aging-In-Place, Na LIU, Sandeep PURAO, Hwee-Pink TAN 2016 Singapore Management University

Value-Inspired Elderly Care Service Design For Aging-In-Place, Na Liu, Sandeep Purao, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

Most current projects aimed at in-home monitoring for the elderly appear to focus on demonstrating technical feasibility and ensuring safety. In doing so, they often overlook the complexity of the interactions between the elderly and the caregivers. This study explores this complexity by adopting a value-inspired design perspective. Following an action design method, we describe the (re)design of the system and service protocol for an elderly-home monitoring effort. The work requires that we leverage the capabilities (of the technological infrastructure system as well as the service providers) to reconcile the values held by the participants (the elderly and their caregivers). …


Fusing Wifi And Video Sensing For Accurate Group Detection In Indoor Spaces, Kasthuri JAYARAJAH, Zaman LANTRA, Archan MISRA 2016 Singapore Management University

Fusing Wifi And Video Sensing For Accurate Group Detection In Indoor Spaces, Kasthuri Jayarajah, Zaman Lantra, Archan Misra

Research Collection School Of Computing and Information Systems

Understanding one's group context in indoor spaces is useful for many reasons - e.g., at a shopping mall, knowing a customer's group context can help in offering context-specific incentives, or estimating taxi demand for customers exiting the mall. Group detection and monitoring using WiFi-based indoor location traces fails when users are invisible (either because they don't carry smartphones, or because their WiFi is turned OFF) or when location tracking is inaccurate. In this paper, we propose a multi-modal group detection system that fuses two independent modes: video and WiFi, for detecting groups with low latency and high accuracy. We present …


Indoor Location Error-Detection Via Crowdsourced Multi-Dimensional Mobile Data, Savina SINGLA, Archan MISRA 2016 PEC University of Technology, India

Indoor Location Error-Detection Via Crowdsourced Multi-Dimensional Mobile Data, Savina Singla, Archan Misra

Research Collection School Of Computing and Information Systems

We explore the use of multi-dimensional mobile sensing data as a means of identifying errors in one or more of those data streams. More specifically, we look at the possibility of identifying indoor locations with likely incorrect/stale Wi-Fi fingerprints, by using concurrent readings from Wi-Fi and barometer sensors from a collection of mobile devices. Our key contribution is a novel two-step process: (i) using longitudinal, crowd-sourced readings of (possibly incorrect) Wi-Fi location estimates to statistically estimate the barometer calibration offset of individual mobile devices, and (ii) then, using such offset-corrected barometer readings from devices (that are supposedly collocated) to identify …


Cdrep: Automatic Repair Of Cryptographic-Misuses In Android Applications, Siqi MA, David LO, Teng LI, Robert H. DENG 2016 Singapore Management University

Cdrep: Automatic Repair Of Cryptographic-Misuses In Android Applications, Siqi Ma, David Lo, Teng Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

Cryptography is increasingly being used in mobile applications to provide various security services; from user authentication, data privacy, to secure communications. However, there are plenty of mistakes that developers could accidentally make when using cryptography in their mobile apps and such mistakes can lead to a false sense of security. Recent research efforts indeed show that a significant portion of mobile apps in both Android and iOS platforms misused cryptographic APIs. In this paper, we present CDRep, a tool for automatically repairing cryptographic misuse defects in Android apps. We classify such defects into seven types and manually assemble the corresponding …


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