Introducing People With Asd To Crowd Work,
2017
Singapore Management University
Introducing People With Asd To Crowd Work, Kotaro Hara, Jeffrey P. Bigham
Research Collection School Of Computing and Information Systems
Adults with Autism Spectrum Disorders (ASD) are unemployed at a high rate, in part because the constraints and expectations of traditional employment can be difficult for them. In this paper, we report on our work in introducing people with ASD to remote work on a crowdsourcing platform and a prototype tool we developed by working with participants. We conducted a six-week long user-centered design study with three participants with ASD. The early stage of the study focused on assessing the abilities of our participants to search and work on micro-tasks available on the crowdsourcing market. Based on our preliminary findings, …
Temporal Understanding Of Human Mobility: A Multi-Time Scale Analysis,
2017
Tsinghua University
Temporal Understanding Of Human Mobility: A Multi-Time Scale Analysis, Tongtong Liu, Zheng Yang, Yi Zhao, Chenshu Wu, Zimu Zhou, Yunhao Liu
Research Collection School Of Computing and Information Systems
The recent availability of digital traces generated by cellphone calls has significantly increased the scientific understanding of human mobility. Until now, however, based on low time resolution measurements, previous works have ignored to study human mobility under various time scales due to sparse and irregular calls, particularly in the era of mobile Internet. In this paper, we introduced Mobile Flow Records, flow-level data access records of online activity of smartphone users, to explore human mobility. Mobile Flow Records collect high-resolution information of large populations. By exploiting this kind of data, we show the models and statistics of human mobility at …
Language Inclusion Checking Of Timed Automata With Non-Zenoness,
2017
Singapore Management University
Language Inclusion Checking Of Timed Automata With Non-Zenoness, Xinyu Wang, Jun Sun, Ting Wang, Shengchao Qin
Research Collection School Of Computing and Information Systems
Given a timed automaton P modeling an implementation and a timed automaton S as a specification, the problem of language inclusion checking is to decide whether the language of P is a subset of that of S. It is known to be undecidable. The problem gets more complicated if non-Zenoness is taken into consideration. A run is Zeno if it permits infinitely many actions within finite time. Otherwise it is non-Zeno. Zeno runs might present in both P and S. It is necessary to check whether a run is Zeno or not so as to avoid presenting Zeno runs as …
Anomaly Detection For A Water Treatment System Using Unsupervised Machine Learning,
2017
National Institute of Advanced Industrial Science and Technology
Anomaly Detection For A Water Treatment System Using Unsupervised Machine Learning, Jun Inoue, Yoriyuki Yamagata, Yuqi Chen, Christopher M. Poskitt, Jun Sun
Research Collection School Of Computing and Information Systems
In this paper, we propose and evaluate the application of unsupervised machine learning to anomaly detection for a Cyber-Physical System (CPS). We compare two methods: Deep Neural Networks (DNN) adapted to time series data generated by a CPS, and one-class Support Vector Machines (SVM). These methods are evaluated against data from the Secure Water Treatment (SWaT) testbed, a scaled-down but fully operational raw water purification plant. For both methods, we first train detectors using a log generated by SWaT operating under normal conditions. Then, we evaluate the performance of both methods using a log generated by SWaT operating under 36 …
Classification-Based Parameter Synthesis For Parametric Timed Automata,
2017
Singapore University of Technology and Design
Classification-Based Parameter Synthesis For Parametric Timed Automata, Jiaying Li, Jun Sun, Bo Gao, Étienne Andre
Research Collection School Of Computing and Information Systems
Parametric timed automata are designed to model timed systems with unknown parameters, often representing design uncertainties of external environments. In order to design a robust system, it is crucial to synthesize constraints on the parameters, which guarantee the system behaves according to certain properties. Existing approaches suffer from scalability issues. In this work, we propose to enhance existing approaches through classification-based learning. We sample multiple concrete values for parameters and model check the corresponding non-parametric models. Based on the checking results, we form conjectures on the constraint through classification techniques, which can be subsequently confirmed by existing model checkers for …
Defaultification Refactoring: A Tool For Automatically Converting Java Methods To Default,
2017
CUNY Hunter College
Defaultification Refactoring: A Tool For Automatically Converting Java Methods To Default, Raffi Khatchadourian, Hidehiko Masuhara
Publications and Research
Enabling interfaces to declare (instance) method implementations, Java 8 default methods can be used as a substitute for the ubiquitous skeletal implementation software design pattern. Performing this transformation on legacy software manually, though, may be non-trivial. The refactoring requires analyzing complex type hierarchies, resolving multiple implementation inheritance issues, reconciling differences between class and interface methods, and analyzing tie-breakers (dispatch precedence) with overriding class methods. All of this is necessary to preserve type-correctness and confirm semantics preservation. We demonstrate an automated refactoring tool called Migrate Skeletal Implementation to Interface for transforming legacy Java code to use the new default construct. The …
Finding An Effective Classification Technique To Develop A Software Team Composition Model,
2017
Sukkur Institute of Business Admnistration
Finding An Effective Classification Technique To Develop A Software Team Composition Model, Abdul Rehman Gilal, Jafrezal Jaafar, Luiz Fernando Capretz, Mazni Omar, Shuib Basri
Electrical and Computer Engineering Publications
Ineffective software team composition has become recognized as a prominent aspect of software project failures. Reports from results extracted from different theoretical personality models have produced contradicting fits, validity challenges, and missing guidance during software development personnel selection. It is also believed that the technique/s used while developing a model can impact the overall results. Thus, this study aims to: 1) discover an effective classification technique to solve the problem, and 2) develop a model for composition of the software development team. The model developed was composed of three predictors: team role, personality types, and gender variables; it also contained …
Design And Implementation Of A Csi-Based Ubiquitous Smoking Detection System,
2017
Singapore Management University
Design And Implementation Of A Csi-Based Ubiquitous Smoking Detection System, Xiaolong Zheng, Jilian Wang, Longfei Shangguan, Zimu Zhou, Yunhao Liu
Research Collection School Of Computing and Information Systems
Even though indoor smoking ban is being put into practice in civilized countries, existing vision or sensor-based smoking detection methods cannot provide ubiquitous detection service. In this paper, we take the first attempt to build a ubiquitous passive smoking detection system, Smokey, which leverages the patterns smoking leaves on WiFi signal to identify the smoking activity even in the non-line-of-sight and throughwall environments. We study the behaviors of smokers and leverage the common features to recognize the series of motions during smoking, avoiding the target-dependent training set to achieve the high accuracy. We design a foreground detectionbased motion acquisition method …
Efficient And Robust Emergence Of Norms Through Heuristic Collective Learning,
2017
Singapore Management University
Efficient And Robust Emergence Of Norms Through Heuristic Collective Learning, Jianye Hao, Jun Sun, Guangyong Chen, Zan Wang, Chao Yu, Zhong Ming
Research Collection School Of Computing and Information Systems
In multiagent systems, social norms serves as an important technique in regulating agents’ behaviors to ensure effective coordination among agents without a centralized controlling mechanism. In such a distributed environment, it is important to investigate how a desirable social norm can be synthesized in a bottom-up manner among agents through repeated local interactions and learning techniques. In this article, we propose two novel learning strategies under the collective learning framework, collective learning EV-l and collective learning EV-g, to efficiently facilitate the emergence of social norms. Extensive simulations results show that both learning strategies can support the emergence of desirable …
On Negative Results When Using Sentiment Analysis Tools For Software Engineering Research,
2017
Singapore Management University
On Negative Results When Using Sentiment Analysis Tools For Software Engineering Research, Robbert Jongeling, Proshanta Sarkar, Subhajit Datta, Alexander Serebrenik
Research Collection School Of Computing and Information Systems
Recent years have seen an increasing attention to social aspects of software engineering, including studies of emotions and sentiments experienced and expressed by the software developers. Most of these studies reuse existing sentiment analysis tools such as SentiStrength and NLTK. However, these tools have been trained on product reviews and movie reviews and, therefore, their results might not be applicable in the software engineering domain. In this paper we study whether the sentiment analysis tools agree with the sentiment recognized by human evaluators (as reported in an earlier study) as well as with each other. Furthermore, we evaluate the impact …
Fastshrinkage: Perceptually-Aware Retargeting Toward Mobile Platforms,
2017
Singapore Management University
Fastshrinkage: Perceptually-Aware Retargeting Toward Mobile Platforms, Zhenguang Liu, Zepeng Wang, Luming Zhang, Rajiv Ratn Shah, Yingjie Xia, Yi Yang, Wei Liu
Research Collection School Of Computing and Information Systems
Retargeting aims at adapting an original high-resolution photo/video to a low-resolution screen with an arbitrary aspect ratio. Conventional approaches are generally based on desktop PCs, since the computation might be intolerable for mobile platforms (especially when retargeting videos). Besides, only low-level visual features are exploited typically, whereas human visual perception is not well encoded. In this paper, we propose a novel retargeting framework which fast shrinks photo/video by leveraging human gaze behavior. Specifically, we first derive a geometry-preserved graph ranking algorithm, which efficiently selects a few salient object patches to mimic human gaze shifting path (GSP) when viewing each scenery. …
Tagscan: Simultaneous Target Imaging And Material Identification With Commodity Rfid Devices,
2017
Northwest University
Tagscan: Simultaneous Target Imaging And Material Identification With Commodity Rfid Devices, Ju Wang, Jie Xiong, Xiaojiang Chen, Hongbo Jiang, Rajesh Krishna Balan, Dingyi Fang
Research Collection School Of Computing and Information Systems
Target imaging and material identification play an important role in many real-life applications. This paper introduces TagScan, a system that can identify the material type and image the horizontal cut of a target simultaneously with cheap commercial of-the-shelf (COTS) RFID devices. The key intuition is that different materials and target sizes cause different amounts of phase and RSS (Received Signal Strength) changes when radio frequency (RF) signal penetrates through the target. Multiple challenges need to be addressed before we can turn the idea into a functional system including (i) indoor environments exhibit rich multipath which breaks the linear relationship between …
Which Packages Would Be Affected By This Bug Report?,
2017
Singapore Management University
Which Packages Would Be Affected By This Bug Report?, Qiao Huang, David Lo, Xin Xia, Qingye Wang, Shanping Li
Research Collection School Of Computing and Information Systems
A large project (e.g., Ubuntu) usually contains a large number of software packages. Sometimes the same bug report in such project would affect multiple packages, and developers of different packages need to collaborate with one another to fix the bug. Unfortunately, the total number of packages involved in a project like Ubuntu is relatively large, which makes it time-consuming to manually identify packages that are affected by a bug report. In this paper, we propose an approach named PkgRec that consists of 2 components: a name matching component and an ensemble learning component. In the name matching component, we assign …
Target Material Identification With Commodity Rfid Devices,
2017
Singapore Management University
Target Material Identification With Commodity Rfid Devices, Xinyi Li, Chao Feng, Nana Ding, Ju Wang, Jie Xiong, Yuhui Ren, Xiaojiang Chen, Dingyi Fang
Research Collection School Of Computing and Information Systems
Target material identification plays an important role in many reallife applications. This paper introduces a system that can identify the material type with cheap commercial off-the-shelf (COTS) RFID devices. The key intuition is that different materials cause different amounts of phase and RSS (Received Signal Strength) changes when radio frequency (RF) signal penetrates through the target. However, without knowing either material type, trying to obtain the information is challenging. We propose a method to address this challenge and evaluate the method's performance in real-world environment. The results show that we achieve higher than 94% material identification accuracies for 10 liquids …
A Validated Set Of Smells In Model-View-Controller Architectures,
2017
Singapore Management University
A Validated Set Of Smells In Model-View-Controller Architectures, Maurício Aniche, Gabriele Bavota, Christoph Treude, Arie Van Deursen, Marco Aurélio Gerosa
Research Collection School Of Computing and Information Systems
Code smells are symptoms of poor design and implementation choices that may hinder code comprehension, and possibly increase change-and defect-proneness. A vast catalogue of smells has been defined in the literature, and it includes smells that can be found in any kind of system (e.g., God Classes), regardless of their architecture. On the other hand, software systems adopting specific architectures (e.g., the Model-View-Controller pattern) can be also affected by other types of poor practices. We surveyed and interviewed 53 MVC developers to collect bad practices to avoid while working on Web MVC applications. Then, we followed an open coding procedure …
O2o Service Composition With Social Collaboration,
2017
Singapore Management University
O2o Service Composition With Social Collaboration, Wenyi Qian, Xin Peng, Jun Sun, Yijun Yu, Bashar Nuseibeh, Wenyun Zhao
Research Collection School Of Computing and Information Systems
In Online-to-Offline (O2O) commerce, customer services may need to be composed from online and offline services. Such composition is challenging, as it requires effective selection of appropriate services that, in turn, support optimal combination of both online and offline services. In this paper, we address this challenge by proposing an approach to O2O service composition which combines offline route planning and social collaboration to optimize service selection. We frame general O2O service composition problems using timed automata and propose an optimization procedure that incorporates: (1) a Markov Chain Monte Carlo (MCMC) algorithm to stochastically select a concrete composite service, and …
Spatio-Temporal Analysis And Prediction Of Cellular Traffic In Metropolis,
2017
Singapore Management University
Spatio-Temporal Analysis And Prediction Of Cellular Traffic In Metropolis, Xu Wang, Zimu Zhou, Zheng Yang, Yunhao Liu, Chunyi Peng
Research Collection School Of Computing and Information Systems
Understanding and predicting cellular traffic at large-scale and fine-granularity is beneficial and valuable to mobile users, wireless carriers and city authorities. Predicting cellular traffic in modern metropolis is particularly challenging because of the tremendous temporal and spatial dynamics introduced by diverse user Internet behaviours and frequent user mobility citywide. In this paper, we characterize and investigate the root causes of such dynamics in cellular traffic through a big cellular usage dataset covering 1.5 million users and 5,929 cell towers in a major city of China. We reveal intensive spatio-temporal dependency even among distant cell towers, which is largely overlooked in …
A Tree Locality-Sensitive Hash For Secure Software Testing,
2017
Air Force Institute of Technology
A Tree Locality-Sensitive Hash For Secure Software Testing, Camdon J. Cady
Theses and Dissertations
Bugs in software that make it through testing can cost tens of millions of dollars each year, and in some cases can even result in the loss of human life. In order to eliminate bugs, developers may use symbolic execution to search through possible program states looking for anomalous states. Most of the computational effort to search through these states is spent solving path constraints in order to determine the feasibility of entering each state. State merging can make this search more efficient by combining program states, allowing multiple execution paths to be analyzed at the same time. However, a …
Graphh: High Performance Big Graph Analytics In Small Clusters,
2017
Singapore Management University
Graphh: High Performance Big Graph Analytics In Small Clusters, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Xiaokui Xiao
Research Collection School Of Computing and Information Systems
It is common for real-world applications to analyze big graphs using distributed graph processing systems. Popular in-memory systems require an enormous amount of resources to handle big graphs. While several out-of-core approaches have been proposed for processing big graphs on disk, the high disk I/O overhead could significantly reduce performance. In this paper, we propose GraphH to enable highperformance big graph analytics in small clusters. Specifically, we design a two-stage graph partition scheme to evenly divide the input graph into partitions, and propose a GAB (GatherApply-Broadcast) computation model to make each worker process a partition in memory at a time. …
Joanaudit: A Tool For Auditing Common Injection Vulnerabilities,
2017
Singapore Management University
Joanaudit: A Tool For Auditing Common Injection Vulnerabilities, Julian Thome, Lwin Khin Shar, Domenico Bianculli, Lionel Briand
Research Collection School Of Computing and Information Systems
JoanAudit is a static analysis tool to assist security auditors in auditing Web applications and Web services for common injection vulnerabilities during software development. It automatically identifies parts of the program code that are relevant for security and generates an HTML report to guide security auditors audit the source code in a scalable way. JoanAudit is configured with various security-sensitive input sources and sinks relevant to injection vulnerabilities and standard sanitization procedures that prevent these vulnerabilities. It can also automatically fix some cases of vulnerabilities in source code — cases where inputs are directly used in sinks without any form …
