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Full-Text Articles in Entire DC Network
Crowdsourcing: A Building Block For Smart Cities, Archan Misra
Crowdsourcing: A Building Block For Smart Cities, Archan Misra
Research Collection School Of Computing and Information Systems
This talk will present a vision, and real-world examples, of the use of mobile crowdsourcing for building a variety of smart-city applications and services. I will first describe the paradigm of centrally-coordinated crowdsourcing, where the crowdsourcing platform intelligently recommends different tasks to different candidate workers, and contrast it with today's prevalent paradigm, where workers select and perform tasks in an uncoordinated, opportunistic fashion. I will then describe real-world examples of such crowdsourcing (and participatory sensing) for two applications: (a) smart campus monitoring and (b) last-mile urban logistics (package pickup and delivery). The talk will also describe the opportunities and open …
Quality And Context-Aware Smart Health Care: Evaluating The Cost-Quality Dynamics, Nirmalya Roy, Christine Julien, Archan Misra, Sajal Das
Quality And Context-Aware Smart Health Care: Evaluating The Cost-Quality Dynamics, Nirmalya Roy, Christine Julien, Archan Misra, Sajal Das
Research Collection School Of Computing and Information Systems
Many emerging pervasive health-care applications require the determination of a variety of context attributes of an individual's activities and medical parameters and her surrounding environment. Context is a high-level representation of an entity's state, which captures activities, relationships, capabilities, etc. In practice, high-level context measures are often difficult to sense from a single data source and must instead be inferred using multiple sensors embedded in the environment. A key challenge in deploying context-driven health-care applications involves energy-efficient determination or inference of high-level context information from low-level sensor data streams. Because this abstraction has the potential to reduce the quality of …
Ontology-Aided Feature Correlation For Multi-Modal Urban Sensing, Archan Misra, Zaman Lantra, Kasthuri Jayarajah
Ontology-Aided Feature Correlation For Multi-Modal Urban Sensing, Archan Misra, Zaman Lantra, Kasthuri Jayarajah
Research Collection School Of Computing and Information Systems
The paper explores the use of correlation across features extracted from different sensing channels to help in urban situational understanding. We use real-world datasets to show how such correlation can improve the accuracy of detection of city-wide events by combining metadata analysis with image analysis of Instagram content. We demonstrate this through a case study on the Singapore Haze. We show that simple ontological relationships and reasoning can significantly help in automating such correlation-based understanding of transient urban events.
Personal Credit Profiling Via Latent User Behavior Dimensions On Social Media, Guangming Guo, Feida Zhu, Enhong Chen, Le Wu, Qi Liu, Yingling Liu, Minghui Qiu
Personal Credit Profiling Via Latent User Behavior Dimensions On Social Media, Guangming Guo, Feida Zhu, Enhong Chen, Le Wu, Qi Liu, Yingling Liu, Minghui Qiu
Research Collection School Of Computing and Information Systems
Consumer credit scoring and credit risk management have been the core research problem in financial industry for decades. In this paper, we target at inferring this particular user attribute called credit, i.e., whether a user is of the good credit class or not, from online social data. However, existing credit scoring methods, mainly relying on financial data, face severe challenges when tackling the heterogeneous social data. Moreover, social data only contains extremely weak signals about users’ credit label. To that end, we put forward a Latent User Behavior Dimension based Credit Model (LUBD-CM) to capture these small signals for personal …
Understanding The Determinants Of Human Computation Game Acceptance: The Effects Of Aesthetic Experience And Output Quality, Xiaohui Wang, Dion Hoe-Lian Goh, Ee-Peng Lim, Wei Liang Adrian Vu
Understanding The Determinants Of Human Computation Game Acceptance: The Effects Of Aesthetic Experience And Output Quality, Xiaohui Wang, Dion Hoe-Lian Goh, Ee-Peng Lim, Wei Liang Adrian Vu
Research Collection School Of Computing and Information Systems
Purpose: Human computation games (HCGs) that blend gaming with utilitarian purposes are a potentially effective channel for content creation. The purpose of this paper is to investigate the driving factors behind players’ adoption of HCGs through a music video tagging game. The effects of perceived aesthetic experience (PAE) and perceived output quality (POQ) on HCG acceptance are empirically examined. Design/methodology/approach: An integrative structural model is developed to explain how hedonic and utilitarian factors, including PAE and POQ, working with another salient factor – perceived usefulness (PU) – affect the acceptance of HCGs. The structural equation modeling method is used to …
Mercury Isotopes Of Atmospheric Particle Bound Mercury For Source Apportionment Study In Urban Kolkata, India, Reshmi Das, Xianfeng Wang, Bahareh Khezri, Richard D. Webster, Pradip Kumar Sikdar, Subhajit Datta
Mercury Isotopes Of Atmospheric Particle Bound Mercury For Source Apportionment Study In Urban Kolkata, India, Reshmi Das, Xianfeng Wang, Bahareh Khezri, Richard D. Webster, Pradip Kumar Sikdar, Subhajit Datta
Research Collection School Of Computing and Information Systems
The particle bound mercury (PBM) in urban-industrial areas is mainly of anthropogenic origin, and is derived from two principal sources: Hg bound to particulate matter directly emitted by industries and power generation plants, and adsorption of gaseous elemental mercury (GEM) and gaseous oxidized mercury (GOM) on air particulates from gas or aqueous phases. Here, we measured the Hg isotope composition of PBM in PM10 samples collected from three locations, a traffic junction, a waste incineration site and an industrial site in Kolkata, the largest metropolis in Eastern India. Sampling was carried out in winter and monsoon seasons between 2013–2015. …
Patrol Scheduling In An Urban Rail Network, Hoong Chuin Lau, Zhi Yuan, Aldy Gunawan
Patrol Scheduling In An Urban Rail Network, Hoong Chuin Lau, Zhi Yuan, Aldy Gunawan
Research Collection School Of Computing and Information Systems
This paper presents the problem of scheduling security teams to patrol a mass rapid transit rail network of a large urban city. The main objective of patrol scheduling is to deploy security teams to stations of the network at varying time periods subject to rostering as well as security-related constraints. We present several mathematical programming models for different variants of this problem. To generate randomized schedules on a regular basis, we propose injecting randomness by varying the start time and break time for each team as well as varying the visit frequency and visit time for each station according to …
Incentive Mechanism Design For Crowdsourcing: An All-Pay Auction Approach, Tie Luo, Sajal K. Das, Hwee-Pink Tan, Lirong Xia
Incentive Mechanism Design For Crowdsourcing: An All-Pay Auction Approach, Tie Luo, Sajal K. Das, Hwee-Pink Tan, Lirong Xia
Research Collection School Of Computing and Information Systems
Crowdsourcing can be modeled as a principal-agent problem in which the principal (crowdsourcer) desires to solicit maximal contribution from a group of agents (participants) while agents are only motivated to act to their own respective advantages. To reconcile this tension, we propose an all-pay auction approach to incentivize agents to act in the principal's interst, i.e., maximizing profit, while allowing agents to reap strictly positive utility. Our rationale for advocating all-pay auctions is based on two merits that we identify, namely all-pay auctions (i) compress the common, two-stage "bid-contribute" crowdsourcing process into a single "bid-cum-contribute" stage, and (ii) eliminate the …
Dual-Server Public-Key Encryption With Keyword Search For Secure Cloud Storage, Rongmao Chen, Yi Mu, Guomin Yang, Fuchun Guo, Xiaofen Wang
Dual-Server Public-Key Encryption With Keyword Search For Secure Cloud Storage, Rongmao Chen, Yi Mu, Guomin Yang, Fuchun Guo, Xiaofen Wang
Research Collection School Of Computing and Information Systems
Searchable encryption is of increasing interest for protecting the data privacy in secure searchable cloud storage. In this paper, we investigate the security of a well-known cryptographic primitive, namely, public key encryption with keyword search (PEKS) which is very useful in many applications of cloud storage. Unfortunately, it has been shown that the traditional PEKS framework suffers from an inherent insecurity called inside keyword guessing attack (KGA) launched by the malicious server. To address this security vulnerability, we propose a new PEKS framework named dual-server PEKS (DS-PEKS). As another main contribution, we define a new variant of the smooth projective …
Anonymous Proxy Signature With Hierarchical Traceability, Jiannan Wei, Guomin Yang, Yi Mu, Kaitai Liang
Anonymous Proxy Signature With Hierarchical Traceability, Jiannan Wei, Guomin Yang, Yi Mu, Kaitai Liang
Research Collection School Of Computing and Information Systems
Anonymous proxy signatures are very useful in the construction of anonymous credential systems such as anonymous voting and anonymous authentication protocols. As a basic requirement, we should ensure an honest proxy signer is anonymous. However, in order to prevent the proxy signer from abusing the signing right, we should also allow dishonest signers to be traced. In this paper, we present three novel anonymous proxy signature schemes with different levels of (namely, public, internal and original signer) traceability. We define the formal definitions and security models for these three different settings, and prove the security of our proposed schemes under …
Foreword To Special Section On Graphics Interface 2015, Hao Zhang, Anthony Tang
Foreword To Special Section On Graphics Interface 2015, Hao Zhang, Anthony Tang
Research Collection School Of Computing and Information Systems
This special section of the Computers & Graphics (C&G) Journal features expanded versions of five of the top graphics and interactions papers [1–5] that were originally presented at Graphics Interface (GI) 2015, which took place in Halifax, Nova Scotia, Canada, between June 3rd and 5th. GI, sponsored by the Canadian Human–Computer Communications Society, is an annual international conference devoted to computer graphics and human– computer interaction (HCI). With a graphics track and an HCI track having equal weights in the conference, GI offers a unique venue for a meeting of minds working on computer graphics and interactive techniques. GI is …
Strongly Leakage-Resilient Authenticated Key Exchange, Rongmao Chen, Yi Mu, Guomin Yang, Willy Susilo, Fuchun Guo
Strongly Leakage-Resilient Authenticated Key Exchange, Rongmao Chen, Yi Mu, Guomin Yang, Willy Susilo, Fuchun Guo
Research Collection School Of Computing and Information Systems
Authenticated Key Exchange (AKE) protocols have been widely deployed in many real-world applications for securing communication channels. In this paper, we make the following contributions. First, we revisit the security modelling of leakage-resilient AKE protocols, and show that the existing models either impose some unnatural restrictions or do not sufficiently capture leakage attacks in reality. We then introduce a new strong yet meaningful security model, named challenge-dependent leakage-resilient eCK (CLR- eCKCLR- eCK) model, to capture challenge-dependent leakage attacks on both long-term secret key and ephemeral secret key (i.e., randomness). Second, we propose a general framework for constructing one-round CLR- eCKCLR- …
An Adaptive Wireless Passive Human Detection Via Fine-Grained Physical Layer Information, Liangyi Gong, Wu Yang, Zimu Zhou, Dapeng Man, Haibin Cai, Xiancun Zhou, Zheng Yang
An Adaptive Wireless Passive Human Detection Via Fine-Grained Physical Layer Information, Liangyi Gong, Wu Yang, Zimu Zhou, Dapeng Man, Haibin Cai, Xiancun Zhou, Zheng Yang
Research Collection School Of Computing and Information Systems
Wireless device-free passive human detection is a key enabler for a range of indoor location-based services such as asset security, emergency responses, privacy-preserving children and elderly monitoring, etc. Since the feature of received signal varies with different multipath propagation conditions, an labor-intensive on-site calibration procedure is almost indispensable to decide the optimal scenario-specific threshold for human detection. Such overhead, however, impedes readily and fast deployment of wireless device-free human detection systems in practical indoor environments. In this work, we explore PHY layer multipath profiling information to extract a novel quantitative metric Ks as an indicator for link sensitivity, and further …
A Business Zone Recommender System Based On Facebook And Urban Planning Data, Jovian Lin, Richard Jayadi Oentaryo, Ee Peng Lim, Casey Vu, Adrian Wei Liang Vu, Philips Kokoh And Prasetyo
A Business Zone Recommender System Based On Facebook And Urban Planning Data, Jovian Lin, Richard Jayadi Oentaryo, Ee Peng Lim, Casey Vu, Adrian Wei Liang Vu, Philips Kokoh And Prasetyo
Research Collection School Of Computing and Information Systems
We present ZoneRec—a zone recommendation system for physical businesses in an urban city,which uses both public business data from Facebook and urban planning data. The systemconsists of machine learning algorithms that take in a business’ metadata and outputs a list ofrecommended zones to establish the business in. We evaluate our system using data of foodbusinesses in Singapore and assess the contribution of different feature groups to therecommendation quality.
History Driven Program Repair, Xuan-Bach D. Le, David Lo, Claire Le Goues
History Driven Program Repair, Xuan-Bach D. Le, David Lo, Claire Le Goues
Research Collection School Of Computing and Information Systems
Effective automated program repair techniques have great potential to reduce the costs of debugging and maintenance. Previously proposed automated program repair (APR) techniques often follow a generate-and-validate and test- case-driven procedure: They first randomly generate a large pool of fix candidates and then exhaustively validate the quality of the candidates by testing them against existing or provided test suites. Unfortunately, many real-world bugs cannot be repaired by existing techniques even after more than 12 hours of computation in a multi-core cloud environment. More work is needed to advance the capabilities of modern APR techniques. We propose a new technique that …
Interactive Teachable Cognitive Agents: Smart Building Blocks For Multiagent Systems, Budhitama Subagdja, Ah-Hwee Tan
Interactive Teachable Cognitive Agents: Smart Building Blocks For Multiagent Systems, Budhitama Subagdja, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Developing a complex intelligent system by abstracting their behaviors, functionalities, and reasoning mechanisms can be tedious and time consuming. In this paper, we present a framework for developing an application or software system based on smart autonomous components that collaborate with the developer or user to realize the entire system. Inspired by teachable approaches and programming-by-demonstration methods in robotics and end-user development, we treat intelligent agents as teachable components that make up the system to be built. Each agent serves different functionalities and may have prebuilt operations to accomplish its own design objectives. However, each agent may also be equipped …
Semantic Memory Modeling And Memory Interaction In Learning Agents, Wenwen Wang, Ah-Hwee Tan, Loo-Nin Teow
Semantic Memory Modeling And Memory Interaction In Learning Agents, Wenwen Wang, Ah-Hwee Tan, Loo-Nin Teow
Research Collection School Of Computing and Information Systems
Semantic memory plays a critical role in reasoning and decision making. It enables an agent to abstract useful knowledge learned from its past experience. Based on an extension of fusion adaptive resonance theory network, this paper presents a novel self-organizing memory model to represent and learn various types of semantic knowledge in a unified manner. The proposed model, called fusion adaptive resonance theory for multimemory learning, incorporates a set of neural processes, through which it may transfer knowledge and cooperate with other long-term memory systems, including episodic memory and procedural memory. Specifically, we present a generic learning process, under which …
Sinabro: A Smartphone-Integrated Opportunistic Electrocardiogram Monitoring System, Sungjun Kwon, Dongseok Lee, Jeehoon Kim, Youngki Lee, Seungwoo Kang, Sangwon Seo, Kwangsuk Park
Sinabro: A Smartphone-Integrated Opportunistic Electrocardiogram Monitoring System, Sungjun Kwon, Dongseok Lee, Jeehoon Kim, Youngki Lee, Seungwoo Kang, Sangwon Seo, Kwangsuk Park
Research Collection School Of Computing and Information Systems
In our preliminary study, we proposed a smartphone-integrated, unobtrusive electrocardiogram (ECG) monitoring system, Sinabro, which monitors a user's ECG opportunistically during daily smartphone use without explicit user intervention. The proposed system also monitors ECG-derived features, such as heart rate (HR) and heart rate variability (HRV), to support the pervasive healthcare apps for smartphones based on the user's high-level contexts, such as stress and affective state levels. In this study, we have extended the Sinabro system by: (1) upgrading the sensor device; (2) improving the feature extraction process; and (3) evaluating extensions of the system. We evaluated these extensions with a …
Campus-Scale Mobile Crowd-Tasking: Deployment And Behavioral Insights, Thivya Kandappu, Archan Misra, Shih-Fen Cheng, Nikita Jaiman, Randy Tandriansiyah, Cen Chen, Hoong Chuin Lau, Deepthi Chander, Koustuv Dasgupta
Campus-Scale Mobile Crowd-Tasking: Deployment And Behavioral Insights, Thivya Kandappu, Archan Misra, Shih-Fen Cheng, Nikita Jaiman, Randy Tandriansiyah, Cen Chen, Hoong Chuin Lau, Deepthi Chander, Koustuv Dasgupta
Research Collection School Of Computing and Information Systems
Mobile crowd-tasking markets are growing at an unprecedented rate with increasing number of smartphone users. Such platforms differ from their online counterparts in that they demand physical mobility and can benefit from smartphone processors and sensors for verification purposes. Despite the importance of such mobile crowd-tasking markets, little is known about the labor supply dynamics and mobility patterns of the users. In this paper we design, develop and experiment with a realwporld mobile crowd-tasking platform, called TA$Ker. Our contributions are two-fold: (a) We develop TA$Ker, a system that allows us to empirically study the worker responses to push vs. pull …
Learning To Find Topic Experts In Twitter Via Different Relations, Wei Wei, Gao Cong, Chunyan Miao, Feida Zhu, Guohui Li
Learning To Find Topic Experts In Twitter Via Different Relations, Wei Wei, Gao Cong, Chunyan Miao, Feida Zhu, Guohui Li
Research Collection School Of Computing and Information Systems
Expert finding has become a hot topic along with the flourishing of social networks, such as micro-blogging services like Twitter. Finding experts in Twitter is an important problem because tweets from experts are valuable sources that carry rich information (e.g., trends) in various domains. However, previous methods cannot be directly applied to Twitter expert finding problem. Recently, several attempts use the relations among users and Twitter Lists for expert finding. Nevertheless, these approaches only partially utilize such relations. To this end, we develop a probabilistic method to jointly exploit three types of relations (i.e., follower relation, user-list relation and list-list …
Iris: Tapping Wearable Sensing To Capture In-Store Retail Insights On Shoppers, Meera Radhakrishnan, Sharanya Eswaran, Archan Misra, Deepthi Chander, Koustuv Dasgupta
Iris: Tapping Wearable Sensing To Capture In-Store Retail Insights On Shoppers, Meera Radhakrishnan, Sharanya Eswaran, Archan Misra, Deepthi Chander, Koustuv Dasgupta
Research Collection School Of Computing and Information Systems
We investigate the possibility of using a combination of a smartphone and a smartwatch, carried by a shopper, to get insights into the shopper’s behavior inside a retail store. The proposed IRIS framework uses standard locomotive and gestural micro-activities as building blocks to define novel composite features that help classify different facets of a shopper’s interaction/experience with individual items, as well as attributes of the overall shopping episode or the store. Besides defining such novel features, IRIS builds a novel segmentation algorithm, which partitions the duration of an entire shopping episode into atomic item-level interactions, by using a combination of …
Magi: Enabling Multi-Device Gestural Applications, Tran Huy Vu, Choo Tsu Wei, Kenny, Youngki Lee, Richard Christopher Davis, Archan Misra
Magi: Enabling Multi-Device Gestural Applications, Tran Huy Vu, Choo Tsu Wei, Kenny, Youngki Lee, Richard Christopher Davis, Archan Misra
Research Collection School Of Computing and Information Systems
We describe our vision of a multiple mobile or wearable device environment and share our initial exploration of our vision in multi-wrist gesture recognition. We explore how multi-device input and output might look, giving four scenarios of everyday multi-device use that show the technical challenges that need to be addressed. We describe our system which allows for recognition to be distributed between multiple devices, fusing recognition streams on a resource-rich device (e.g., mobile phone). An Interactor layer recognises common gestures from the fusion engine, and provides abstract input streams (e.g., scrolling and zooming) to user interface components called Midgets. These …
Improving The Sensitivity Of Unobtrusive Inactivity Detection In Sensor-Enabled Homes For The Elderly, Alvin C. Valera, Hwee-Pink Tan, Liming Bai
Improving The Sensitivity Of Unobtrusive Inactivity Detection In Sensor-Enabled Homes For The Elderly, Alvin C. Valera, Hwee-Pink Tan, Liming Bai
Research Collection School Of Computing and Information Systems
Unobtrusive in-home monitoring systems are gaining acceptability and are being deployed to enable relatives and caregivers to remotely monitor and provide timely care to their elderly loved ones or senior clients, respectively, who are living independently. Such systems can provide information about nonmovement or inactivity of the elderly resident. As prolonged inactivity could mean potential danger, several algorithms have been proposed to automatically detect unusually long durations of inactivity. Such schemes, however, suffer from low sensitivity due to their high detection latency. In this paper, we propose Dwell Time-enhanced Dynamic Threshold (DTDT), a scheme for computing adaptive alert thresholds that …
Value-Inspired Service Design In Elderly Home-Monitoring Systems, Na Liu, Sandeep Purao, Hwee-Pink Tan
Value-Inspired Service Design In Elderly Home-Monitoring Systems, Na Liu, Sandeep Purao, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
The provision of elderly home-monitoring systems to enhance aging-in-place requires the service to meet the needs of both the elderly and their caregivers. The design of such IT services requires interdisciplinary efforts to look beyond the technical requirements. Taking a value-inspired design perspective, the study argues that service design for promoting aging-in-place needs to reconcile the values of both the elderly and caregivers. Drawn from the framework of basic human values and the unique experience of the SHINESeniors project, the study extracts the core values for elderly and caregivers using a multi-method case analysis. We suggest that both system and …
Elderly Medication Adherence Monitoring With The Internet Of Things, Xiaoping Toh, Hwee Xian Tan, Huiguang Liang, Hwee-Pink Tan
Elderly Medication Adherence Monitoring With The Internet Of Things, Xiaoping Toh, Hwee Xian Tan, Huiguang Liang, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
With the growth in elderly population in Singapore, healthcare expenditure and prevalence of age-related illnesses are expected to increase. Non-adherence among the elderly is a common issue that leads to adverse health complications, particularly among those with chronic conditions. However, existing studies typically focus on identifying predictors of medication adherence, and provide neither user-friendly nor actionable solutions that can be easily adopted by the elderly.In this paper, we use the Internet of Things to monitor medication adherence and detect changes in medication consumption patterns among the elderly, thus enabling timely interventions by caregivers to take place. Sensor-enabled medication boxes are …
Cca-Secure Keyed-Fully Homomorphic Encryption, Junzuo Lai, Deng, Robert H., Changshe Ma, Kouichi Sakurai, Jian Weng
Cca-Secure Keyed-Fully Homomorphic Encryption, Junzuo Lai, Deng, Robert H., Changshe Ma, Kouichi Sakurai, Jian Weng
Research Collection School Of Computing and Information Systems
To simultaneously achieve CCA security and homomorphic property for encryption, Emura et al. introduced a new cryptographic primitive named keyed-homomorphic encryption, in which homomorphic ciphertext manipulations can only be performed by someone holding a devoted evaluation key which, by itself, does not enable decryption. A keyed-homomorphic encryption scheme should provide CCA2 security when the evaluation key is unavailable to the adversary and remain CCA1-secure when the evaluation key is exposed. While existing keyed-homomorphic encryption schemes only allow simple computations on encrypted data, our goal is to construct CCA-secure keyed-fully homomorphic encryption (keyed-FHE) capable of evaluating any functions on encrypted data …
Scrum-X: An Interactive And Experiential Learning Platform For Teaching Scrum, Wee Leong Lee
Scrum-X: An Interactive And Experiential Learning Platform For Teaching Scrum, Wee Leong Lee
Research Collection School Of Computing and Information Systems
Motivating and engaging thecurrent generation of technology-savvy students and improving the quality oflearning is becoming more challenging with traditional instructional methods.Educational games and simulations are gaining more ground, both in formal andinformal learning environments. With experiential learning, learners canenhance their management skills and ability to make decisions by analyzingdifferent scenarios and paths that the project could have taken if specificdecisions were made during the project. This paper presents Scrum-X, acomputer-based simulation game to teach Scrum, an agile project managementmethodology, to graduates and professionals with IT background. In the game,players plan, execute and manage a software development project using Scrummethodology. Players …
Scenario-Based Simulation Game For Hospital Beds Capacity Planning In Singapore, Cheong, Michelle L. F., Li Siong Lim
Scenario-Based Simulation Game For Hospital Beds Capacity Planning In Singapore, Cheong, Michelle L. F., Li Siong Lim
Research Collection School Of Computing and Information Systems
A complete learning object with scenario-based simulation game and accompanying materials, which allows self-directed learners to learn and apply the theory, concepts and calculations for capacity planning, in the hospital beds capacity planning scenario in Singapore, was designed, developed and immplemented. It guides the learners through the key considerations for capacity planning, the computation of actual capacity needed, deciding the time for capacity increments, as well as the economies and diseconomies of scale when adding capacity. All the learnings are applied in a scenario where the learners make decision on how much and when to add hospital beds to existing …
Did You Take A Break Today? Detecting Playing Foosball Using Your Smartwatch, Sougata Sen, Kiran K. Rachuri, Abhishek Mukherji, Archan Misra
Did You Take A Break Today? Detecting Playing Foosball Using Your Smartwatch, Sougata Sen, Kiran K. Rachuri, Abhishek Mukherji, Archan Misra
Research Collection School Of Computing and Information Systems
Prolonged working hours are a primary cause of stress, work related injuries (e.g, RSIs), and work-life imbalance in employees at a workplace. As reported by some studies, taking timely breaks from continuous work not only reduces stress and exhaustion but also improves productivity, employee bonding, and camaraderie. Our goal is to build a system that automatically detects breaks thereby assisting in maintaining healthy work-break balance. In this paper, we focus on detecting foosball breaks of employees at a workplace using a smartwatch. We selected foosball as it is one of the most commonly played games at many workplaces in the …
Rack: Automatic Api Recommendation Using Crowdsourced Knowledge, Mohammad M. Rahman, Chanchal K. Roy, David Lo
Rack: Automatic Api Recommendation Using Crowdsourced Knowledge, Mohammad M. Rahman, Chanchal K. Roy, David Lo
Research Collection School Of Computing and Information Systems
Traditional code search engines often do not perform well with natural language queries since they mostly apply keyword matching. These engines thus need carefully designed queries containing information about programming APIs for code search. Unfortunately, existing studies suggest that preparing an effective code search query is both challenging and time consuming for the developers. In this paper, we propose a novel API recommendation technique -- RACK that recommends a list of relevant APIs for a natural language query for code search by exploiting keyword-API associations from the crowdsourced knowledge of Stack Overflow. We first motivate our technique using an exploratory …