Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Databases and Information Systems (239)
- Programming Languages and Compilers (198)
- Artificial Intelligence and Robotics (142)
- Engineering (142)
- Computer Engineering (126)
-
- Information Security (109)
- OS and Networks (80)
- Graphics and Human Computer Interfaces (78)
- Social and Behavioral Sciences (76)
- Numerical Analysis and Scientific Computing (59)
- Theory and Algorithms (46)
- Business (43)
- Computer and Systems Architecture (39)
- Digital Communications and Networking (39)
- Medicine and Health Sciences (33)
- Communication (30)
- Education (28)
- Systems Architecture (21)
- Health Information Technology (20)
- Sociology (18)
- Finance and Financial Management (15)
- Gerontology (15)
- Public Affairs, Public Policy and Public Administration (15)
- Higher Education (13)
- Social Media (13)
- Transportation (12)
- Technology and Innovation (11)
- Keyword
-
- Deep learning (54)
- Software engineering (49)
- Empirical study (43)
- Machine learning (35)
- Software (30)
-
- Android (29)
- Model Check (29)
- Collaboration (26)
- Deep Learning (24)
- GitHub (22)
- Stack Overflow (22)
- Fuzzing (21)
- Security (21)
- Testing (20)
- Data mining (19)
- Large language models (18)
- Programming (18)
- Software Engineering (18)
- Code search (17)
- Computer bugs (17)
- Codes (16)
- Empirical Study (16)
- Information retrieval (16)
- Large Language Models (16)
- Large language model (16)
- Software testing (15)
- Large Language Model (14)
- Linear Temporal Logic (14)
- Software maintenance (14)
- Vulnerability detection (14)
- Publication Year
- Publication
- Publication Type
Articles 991 - 1020 of 2211
Full-Text Articles in Software Engineering
Sensitive Behavior Analysis Of Android Applications On Unrooted Devices In The Wild, Xiaoxiao Tang
Sensitive Behavior Analysis Of Android Applications On Unrooted Devices In The Wild, Xiaoxiao Tang
Dissertations and Theses Collection (Open Access)
Dynamic analysis is widely used in malware detection, taint analysis, vulnerability detection, and other areas for enhancing the security of Android. Compared to static analysis, dynamic analysis is immune to common code obfuscation techniques and dynamic code loading. Existing dynamic analysis techniques rely on in-lab running environment (e.g., modified systems, rooted devices, or emulators) and require automatic input generators to execute the target app. However, these techniques could be bypassed by anti-analysis techniques that allow apps to hide sensitive behavior when an in-lab environment is detected through predefined heuristics (e.g., IMEI number of the device is invalid). Meanwhile, current input …
Making Sense Of Crowd-Generated Content In Domain-Specific Settings, Agus Sulistya
Making Sense Of Crowd-Generated Content In Domain-Specific Settings, Agus Sulistya
Dissertations and Theses Collection (Open Access)
The rapid advances of the Web have changed the ways information is distributed and exchanged among individuals and organizations. Various content from different domains are generated daily and contributed by users' daily activities, such as posting messages in a microblog platform, or collaborating in a question and answer site. To deal with such tremendous volume of user generated content, there is a need for approaches that are able to handle the mass amount of available data and to extract knowledge hidden in the user generated content. This dissertation attempts to make sense of the generated content to help in three …
Stressmon: Large Scale Detection Of Stress And Depression In Campus Environment Using Passive Coarse-Grained Location Data, Camellia Zakaria
Stressmon: Large Scale Detection Of Stress And Depression In Campus Environment Using Passive Coarse-Grained Location Data, Camellia Zakaria
Dissertations and Theses Collection (Open Access)
The rising mental health illnesses of severe stress and depression is of increasing concern worldwide. Often associated by similarities in symptoms, severe stress can take a toll on a person’s productivity and result in depression if the stress is left unmanaged. Unfortunately, depression can occur without any feelings of stress. With depression growing as a leading cause of disability in economic productivity, there has been a sharp rise in mental health initiatives to improve stress and depression management. To offer such services conveniently and discreetly, recent efforts have focused on using mobile technologies. However, these initiatives usually require users to …
Applying Case-Based Learning For A Postgraduate Software Architecture Course, Eng Lieh Ouh, Yunghans Irawan
Applying Case-Based Learning For A Postgraduate Software Architecture Course, Eng Lieh Ouh, Yunghans Irawan
Research Collection School Of Computing and Information Systems
Software architecture remains a difficult subject for learners to grasp and for educators to teach given its level of abstraction. On the other hand, case-based learning (CBL) is a popular teaching approach used across disciplines especially in business, medicine and law where students work in groups apply their knowledge to solve real-world case studies, or scenarios using their reasoning skills and existing theoretical knowledge. In this paper, we provide how we apply case-based learning to address the challenge in teaching a postgraduate software architecture course. Our learners are postgraduate students taking a master’s program in software engineering. We first describe …
Eugene: Towards Deep Intelligence As A Service, Shuochao Yao, Yifan Hao, Yiran Zhao, Ailing Piao, Huajie Shao, Dongxin Liu, Shengzhong Liu, Shaohan Hu, Dulanga Weerakoon, Kasthuri Jayarajah, Archan Misra, Tarek Abdelzaher
Eugene: Towards Deep Intelligence As A Service, Shuochao Yao, Yifan Hao, Yiran Zhao, Ailing Piao, Huajie Shao, Dongxin Liu, Shengzhong Liu, Shaohan Hu, Dulanga Weerakoon, Kasthuri Jayarajah, Archan Misra, Tarek Abdelzaher
Research Collection School Of Computing and Information Systems
The paper discusses an emerging suite of machine intelligence services that are of increasing importance in the highly instrumented world of the Internet of Things (IoT). The suite, called Eugene, would offer a form of intelligent behavior (based on deep neural networks) to otherwise simple embedded devices; the clients of the service. These devices would benefit from service resources to learn from data and to perform intelligent inference, classification, prediction, and estimation tasks that they are too limited to carry out on their own. The paper discusses the taxonomy of such services and the state of implementation, as well as …
Towards Understanding Android System Vulnerabilities: Techniques And Insights, Daoyuan Wu, Debin Gao, Eric K. T. Cheng, Yichen Cao, Jintao Jiang, Robert H. Deng
Towards Understanding Android System Vulnerabilities: Techniques And Insights, Daoyuan Wu, Debin Gao, Eric K. T. Cheng, Yichen Cao, Jintao Jiang, Robert H. Deng
Research Collection School Of Computing and Information Systems
As a common platform for pervasive devices, Android has been targeted by numerous attacks that exploit vulnerabilities in its apps and the operating system. Compared to app vulnerabilities, systemlevel vulnerabilities in Android, however, were much less explored in the literature. In this paper, we perform the first systematic study of Android system vulnerabilities by comprehensively analyzing all 2,179 vulnerabilities on the Android Security Bulletin program over about three years since its initiation in August 2015. To this end, we propose an automatic analysis framework, upon a hierarchical database structure, to crawl, parse, clean, and analyze vulnerability reports and their publicly …
Deephunter: A Coverage-Guided Fuzz Testing Framework For Deep Neural Networks, Xiaofei Xie, Lei Ma, Felix Juefei-Xu, Minhui Xue, Hongxu Chen, Yang Liu, Jianjun Zhao, Bo Li, Jianxiong Yin, Simon See
Deephunter: A Coverage-Guided Fuzz Testing Framework For Deep Neural Networks, Xiaofei Xie, Lei Ma, Felix Juefei-Xu, Minhui Xue, Hongxu Chen, Yang Liu, Jianjun Zhao, Bo Li, Jianxiong Yin, Simon See
Research Collection School Of Computing and Information Systems
The past decade has seen the great potential of applying deep neural network (DNN) based software to safety-critical scenarios, such as autonomous driving. Similar to traditional software, DNNs could exhibit incorrect behaviors, caused by hidden defects, leading to severe accidents and losses. In this paper, we propose DeepHunter, a coverage-guided fuzz testing framework for detecting potential defects of general-purpose DNNs. To this end, we first propose a metamorphic mutation strategy to generate new semantically preserved tests, and leverage multiple extensible coverage criteria as feedback to guide the test generation. We further propose a seed selection strategy that combines both diversity-based …
Semantic Patches For Java Program Transformation, Hong Jin Kang, Ferdian Thung, Julia Lawall, Gilles Muller, Lingxiao Jiang, David Lo
Semantic Patches For Java Program Transformation, Hong Jin Kang, Ferdian Thung, Julia Lawall, Gilles Muller, Lingxiao Jiang, David Lo
Research Collection School Of Computing and Information Systems
Developing software often requires code changes that are widespread and applied to multiple locations.There are tools for Java that allow developers to specify patterns for program matching and source-to-source transformation. However, to our knowledge, none allows for transforming code based on its control-flow context. We prototype Coccinelle4J, an extension to Coccinelle, which is a program transformation tool designed for widespread changes in C code, in order to work on Java source code. We adapt Coccinelle to be able to apply scripts written in the Semantic Patch Language (SmPL), a language provided by Coccinelle, to Java source files. As a case …
Compositional Coding For Collaborative Filtering, Chenghao Liu, Tao Lu, Xin Wang, Zhiyong Cheng, Jianling Sun, Steven C. H. Hoi
Compositional Coding For Collaborative Filtering, Chenghao Liu, Tao Lu, Xin Wang, Zhiyong Cheng, Jianling Sun, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Efficiency is crucial to the online recommender systems, especially for the ones which needs to deal with tens of millions of users and items. Because representing users and items as binary vectors for Collaborative Filtering (CF) can achieve fast user-item affinity computation in the Hamming space, in recent years, we have witnessed an emerging research effort in exploiting binary hashing techniques for CF methods. However, CF with binary codes naturally suffers from low accuracy due to limited representation capability in each bit, which impedes it from modeling complex structure of the data. In this work, we attempt to improve the …
Toward Human-Like Summaries Generated From Heterogeneous Software Artefacts, Mahfouth Alghamdi, Christoph Treude, Markus Wagner
Toward Human-Like Summaries Generated From Heterogeneous Software Artefacts, Mahfouth Alghamdi, Christoph Treude, Markus Wagner
Research Collection School Of Computing and Information Systems
Automatic text summarisation has drawn considerable interest in the field of software engineering. It can improve the efficiency of software developers, enhance the quality of products, and ensure timely delivery. In this paper, we present our initial work towards automatically generating human-like multi-document summaries from heterogeneous software artefacts. Our analysis of the text properties of 545 human-written summaries from 15 software engineering projects will ultimately guide heuristics searches in the automatic generation of human-like summaries.
Redpc: A Residual Error-Based Density Peak Clustering Algorithm, Milan Parmar, Di Wang, Xiaofeng Zhang, Ah-Hwee Tan, Chunyan Miao, You Zhou
Redpc: A Residual Error-Based Density Peak Clustering Algorithm, Milan Parmar, Di Wang, Xiaofeng Zhang, Ah-Hwee Tan, Chunyan Miao, You Zhou
Research Collection School Of Computing and Information Systems
The density peak clustering (DPC) algorithm was designed to identify arbitrary-shaped clusters by finding density peaks in the underlying dataset. Due to its aptitudes of relatively low computational complexity and a small number of control parameters in use, DPC soon became widely adopted. However, because DPC takes the entire data space into consideration during the computation of local density, which is then used to generate a decision graph for the identification of cluster centroids, DPC may face difficulty in differentiating overlapping clusters and in dealing with low-density data points. In this paper, we propose a residual error-based density peak clustering …
Evaluating The Readability Of Force Directed Graph Layouts: A Deep Learning Approach, Hammad Haleem, Yong Wang, Abishek Puri, Sahil Wadhwa, Huamin Qu
Evaluating The Readability Of Force Directed Graph Layouts: A Deep Learning Approach, Hammad Haleem, Yong Wang, Abishek Puri, Sahil Wadhwa, Huamin Qu
Research Collection School Of Computing and Information Systems
Existing graph layout algorithms are usually not able to optimize all the aesthetic properties desired in a graph layout. To evaluate how well the desired visual features are reflected in a graph layout, many readability metrics have been proposed in the past decades. However, the calculation of these readability metrics often requires access to the node and edge coordinates and is usually computationally inefficient, especially for dense graphs. Importantly, when the node and edge coordinates are not accessible, it becomes impossible to evaluate the graph layouts quantitatively. In this paper, we present a novel deep learning-based approach to evaluate the …
Resilient Collaborative Intelligence For Adversarial Iot Environments, Dulanga Weerakoon, Kasthuri Jayarajah, Randy Tandriansyah, Archan Misra
Resilient Collaborative Intelligence For Adversarial Iot Environments, Dulanga Weerakoon, Kasthuri Jayarajah, Randy Tandriansyah, Archan Misra
Research Collection School Of Computing and Information Systems
Many IoT networks, including for battlefield deployments, involve the deployment of resource-constrained sensors with varying degrees of redundancy/overlap (i.e., their data streams possess significant spatiotemporal correlation). Collaborative intelligence, whereby individual nodes adjust their inferencing pipelines to incorporate such correlated observations from other nodes, can improve both inferencing accuracy and performance metrics (such as latency and energy overheads). Using realworld data from a multicamera deployment, we first demonstrate the significant performance gains (up to 14% increase in accuracy) from such collaborative intelligence, achieved through two different approaches: (a) one involving statistical fusion of outputs from different nodes, and (b) another involving …
Decentralizing Air Traffic Flow Management With Blockchain Based Reinforcement Learning, Nguyen Binh Duong Ta, Umang Chaudhary, Hong-Linh Truong
Decentralizing Air Traffic Flow Management With Blockchain Based Reinforcement Learning, Nguyen Binh Duong Ta, Umang Chaudhary, Hong-Linh Truong
Research Collection School Of Computing and Information Systems
We propose and implement a decentralized, intelligent air traffic flow management (ATFM) solution to improve the efficiency of air transportation in the ASEAN region as a whole. Our system, named BlockAgent, leverages the inherent synergy between multi-agent reinforcement learning (RL) for air traffic flow optimization; and the rising blockchain technology for a secure, transparent and decentralized coordination platform. As a result, BlockAgent does not require a centralized authority for effective ATFM operations. We have implemented several novel distributed coordination approaches for RL in BlockAgent. Empirical experiments with real air traffic data concerning regional airports have demonstrated the feasibility and effectiveness …
Semantic Patches For Java Program Transformation (Artifact), Hong Jin Kang, Thung Ferdian, Julia Lawall, Gilles Muller, Lingxiao Jiang, David Lo
Semantic Patches For Java Program Transformation (Artifact), Hong Jin Kang, Thung Ferdian, Julia Lawall, Gilles Muller, Lingxiao Jiang, David Lo
Research Collection School Of Computing and Information Systems
The program transformation tool Coccinelle is designed for making changes that is required in many locations within a software project. It has been shown to be useful for C code and has been been adopted for use in the Linux kernel by many developers. Over 6000 commits mentioning the use of Coccinelle have been made in the Linux kernel. Our artifact, Coccinelle4J, is an extension to Coccinelle in order for it to apply program transformations to Java source code. This artifact accompanies our experience report “Semantic Patches for Java Program Transformation”, in which we show a case study of applying …
Decentralise Me, Paul Robert Griffin
Decentralise Me, Paul Robert Griffin
MITB Thought Leadership Series
If you are in need of a reminder of the levels of hype surrounding blockchain, then look no further than Japan’s J-Pop sensation Kasotsuka Shojo, otherwise known as the Virtual Currency Girls who, with their debut track “The Moon and Cryptocurrencies and Me”, aim to educate fans about cryptocurrencies in an entertaining way.
Why Is My Code Change Abandoned?, Qingye Wang, Xin Xia, David Lo, Shanping Li
Why Is My Code Change Abandoned?, Qingye Wang, Xin Xia, David Lo, Shanping Li
Research Collection School Of Computing and Information Systems
Software developers contribute numerous changes every day to the code review systems. However, not all submitted changes are merged into a codebase because they might not pass the code review process. Some changes would be abandoned or be asked for resubmission after improvement, which results in more workload for developers and reviewers, and more delays to deliverables. To understand the underlying reasons why changes are abandoned, we conduct an empirical study on the code review of four open source projects (Eclipse, LibreOffice, OpenStack, and Qt).First, we manually analyzed 1459 abandoned changes. Second, we leveraged the open card sorting method to …
Buscope: Fusing Individual & Aggregated Mobility Behavior For “Live” Smart City Services, Lakmal Buddika Meegahapola, Thivya Kandappu, Kasthuri Jayarajah, Leman Akoglu, Shili Xiang, Archan Misra
Buscope: Fusing Individual & Aggregated Mobility Behavior For “Live” Smart City Services, Lakmal Buddika Meegahapola, Thivya Kandappu, Kasthuri Jayarajah, Leman Akoglu, Shili Xiang, Archan Misra
Research Collection School Of Computing and Information Systems
While analysis of urban commuting data has a long and demonstrated history of providing useful insights into human mobility behavior, such analysis has been performed largely in offline fashion and to aid medium-to-long term urban planning. In this work, we demonstrate the power of applying predictive analytics on real-time mobility data, specifically the smart-card generated trip data of millions of public bus commuters in Singapore, to create two novel and "live" smart city services. The key analytical novelty in our work lies in combining two aspects of urban mobility: (a) conformity: which reflects the predictability in the aggregated flow of …
Single Image Reflection Removal Beyond Linearity, Qiang Wen, Yinjie Tan, Jing Qin, Wenxi Liu, Guoqiang Han, Shengfeng He
Single Image Reflection Removal Beyond Linearity, Qiang Wen, Yinjie Tan, Jing Qin, Wenxi Liu, Guoqiang Han, Shengfeng He
Research Collection School Of Computing and Information Systems
Due to the lack of paired data, the training of image reflection removal relies heavily on synthesizing reflection images. However, existing methods model reflection as a linear combination model, which cannot fully simulate the real-world scenarios. In this paper, we inject non-linearity into reflection removal from two aspects. First, instead of synthesizing reflection with a fixed combination factor or kernel, we propose to synthesize reflection images by predicting a non-linear alpha blending mask. This enables a free combination of different blurry kernels, leading to a controllable and diverse reflection synthesis. Second, we design a cascaded network for reflection removal with …
Exploratory Analysis Of Individuals' Mobility Patterns And Experienced Conflicts In Workgroup, Nur Camellia Binte Zakaria, Kenneth T. Goh, Youngki Lee, Rajesh Krishna Balan
Exploratory Analysis Of Individuals' Mobility Patterns And Experienced Conflicts In Workgroup, Nur Camellia Binte Zakaria, Kenneth T. Goh, Youngki Lee, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Much research argues the importance of supporting social interactions in teams and communities. The field of mobile sensing alone offers significant advances in recording and understanding human and group behaviours. However, little is known about behavioural changes as a consequence of in-group phenomena. One prominent example is intra-group conflict, which naturally arises between diverse groups of people. We demonstrate the feasibility of our approach to extract mobility patterns of individual's group behaviours sensed from a WiFi indoor localisation system and explore how these patterns relate to their team processes. 62 students enrolled in a project-intensive module, Software Engineering, were tracked …
Corrn: Cooperative Reflection Removal Network, Renjie Wen, Boxin Shi, Haoliang Li, Ling-Yu Duan, Ah-Hwee Tan, Alex C. Kot
Corrn: Cooperative Reflection Removal Network, Renjie Wen, Boxin Shi, Haoliang Li, Ling-Yu Duan, Ah-Hwee Tan, Alex C. Kot
Research Collection School Of Computing and Information Systems
Removing the undesired reflections from images taken through the glass is of broad application to various computer vision tasks. Non-learning based methods utilize different handcrafted priors such as the separable sparse gradients caused by different levels of blurs, which often fail due to their limited description capability to the properties of real-world reflections. In this paper, we propose a network with the feature-sharing strategy to tackle this problem in a cooperative and unified framework, by integrating image context information and the multi-scale gradient information. To remove the strong reflections existed in some local regions, we propose a statistic loss by …
Deep Ecg Estimation Using A Bed-Attached Geophone, Jae Yeon Park, Hyeon Cho, Wonjun Hwang, Rajesh Krishna Balan, Jeong Gil Ko
Deep Ecg Estimation Using A Bed-Attached Geophone, Jae Yeon Park, Hyeon Cho, Wonjun Hwang, Rajesh Krishna Balan, Jeong Gil Ko
Research Collection School Of Computing and Information Systems
Electrocardiogram (ECG) signals offer rich information for analyzing and understanding the cardiac activity of a person. The continuous monitoring of ECG can help diagnose cardiac disorders, such as arrhythmia, effectively. While many wearable healthcare platforms offer continuous ECG monitoring, these devices are cumbersome in the fact that they need to be continuously attached to the human body, which causes uncomfortableness, and limits their usage when monitoring a person's ECG throughout the night as they sleep. In this work, we propose a fully non-intrusive sensing system for monitoring the ECG of a person while in bed. Specifically, we present Heartquake, a …
Automatic Loop Summarization Via Path Dependency Analysis, Xiaofei Xie, Bihuan Chen, Liang Zou, Yang Liu, Wei Le, Xiaohong Li
Automatic Loop Summarization Via Path Dependency Analysis, Xiaofei Xie, Bihuan Chen, Liang Zou, Yang Liu, Wei Le, Xiaohong Li
Research Collection School Of Computing and Information Systems
Analyzing loops is very important for various software engineering tasks such as bug detection, test case generation and program optimization. However, loops are very challenging structures for program analysis, especially when (nested) loops contain multiple paths that have complex interleaving relationships. In this paper, we propose the path dependency automaton (PDA) to capture the dependencies among the multiple paths in a loop. Based on the PDA, we first propose a loop classification to understand the complexity of loop summarization. Then, we propose a loop analysis framework, named Proteus, which takes a loop program and a set of variables of interest …
An Empirical Study Of Mobile Network Behavior And Application Performance In The Wild, Shiwei Zhang, Weichao Li, Daoyuan Wu, Bo Jin, Rocky K. C. Chang, Debin Gao, Yi Wang, Ricky K. P. Mok
An Empirical Study Of Mobile Network Behavior And Application Performance In The Wild, Shiwei Zhang, Weichao Li, Daoyuan Wu, Bo Jin, Rocky K. C. Chang, Debin Gao, Yi Wang, Ricky K. P. Mok
Research Collection School Of Computing and Information Systems
Monitoring mobile network performance is critical for optimizing the QoE of mobile apps. Until now, few studies have considered the actual network performance that mobile apps experience in a per-app or per-server granularity. In this paper, we analyze a two-year-long dataset collected by a crowdsourcing per-app measurement tool to gain new insights into mobile network behavior and application performance. We observe that only a small portion of WiFi networks can work in high-speed mode, and more than one-third of the observed ISPs still have not deployed 4G networks. For cellular networks, the DNS settings on smartphones can have a significant …
Lpgl: Low-Power Graphics Library For Mobile Ar Headsets, Choi Jaewon, Hyeonjung Park, Jeongyeup Paek, Rajesh Krishna Balan, Jeonggil Ko
Lpgl: Low-Power Graphics Library For Mobile Ar Headsets, Choi Jaewon, Hyeonjung Park, Jeongyeup Paek, Rajesh Krishna Balan, Jeonggil Ko
Research Collection School Of Computing and Information Systems
We present LpGL, an OpenGL API compatible Low-power Graphics Library for energy efficient AR headset applications. We first characterize the power consumption patterns of a state of the art AR headset, Magic Leap One, and empirically show that its internal GPU is the most impactful and controllable energy consumer. Based on the preliminary studies, we design LpGL so that it uses the device's gaze/head orientation information and geometry data to infer user perception information, intercepts application-level graphics API calls, and employs frame rate control, mesh simplification, and culling techniques to enhance energy efficiency of AR headsets without detriment of user …
Importance Sampling Of Interval Markov Chains, Cyrille Jegourel, Jingyi Wang, Jun Sun
Importance Sampling Of Interval Markov Chains, Cyrille Jegourel, Jingyi Wang, Jun Sun
Research Collection School Of Computing and Information Systems
In real-world systems, rare events often characterize critical situations like the probability that a system fails within some time bound and they are used to model some potentially harmful scenarios in dependability of safety-critical systems. Probabilistic Model Checking has been used to verify dependability properties in various types of systems but is limited by the state space explosion problem. An alternative is the recourse to Statistical Model Checking (SMC) that relies on Monte Carlo simulations and provides estimates within predefined error and confidence bounds. However, rare properties require a large number of simulations before occurring at least once. To tackle …
Examining Augmented Virtuality Impairment Simulation For Mobile App Accessibility Design, Tsu Wei, Kenny (Zhu Shuwei, Kenny) Choo, Rajesh Krishna Balan, Rajesh Krishna Balan
Examining Augmented Virtuality Impairment Simulation For Mobile App Accessibility Design, Tsu Wei, Kenny (Zhu Shuwei, Kenny) Choo, Rajesh Krishna Balan, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
With mobile apps rapidly permeating all aspects of daily living with use by all segments of the population, it is crucial to support the evaluation of app usability for specific impaired users to improve app accessibility. In this work, we examine the effects of using our augmented virtuality impairment simulation system–Empath-D–to support experienced designer-developers to redesign a mockup of commonly used mobile application for cataract-impaired users, comparing this with existing tools that aid designing for accessibility. We show that the use of augmented virtuality for assessing usability supports enhanced usability challenge identification, finding more defects and doing so more accurately …
Celltrademap: Delineating Trade Areas For Urban Commercial Districts With Cellular Networks, Yi Zhao, Zimu Zhou, Xu Wang, Tongtong Liu, Yunhao Liu, Zheng Yang
Celltrademap: Delineating Trade Areas For Urban Commercial Districts With Cellular Networks, Yi Zhao, Zimu Zhou, Xu Wang, Tongtong Liu, Yunhao Liu, Zheng Yang
Research Collection School Of Computing and Information Systems
Understanding customer mobility patterns to commercial districts is crucial for urban planning, facility management, and business strategies. Trade areas are a widely applied measure to quantity where the visitors are from. Traditional trade area analysis is limited to small-scale or store-level studies because information such as visits to competitor commercial entities and place of residence is collected by labour-intensive questionnaires or heavily biased location-based social media data. In this paper, we propose CellTradeMap, a novel district-level trade area analysis framework using mobile flow records (MFRs), a type of fine-grained cellular network data. CellTradeMap extracts robust location information from the irregularly …
Peerlens: Peer-Inspired Interactive Learning Path Planning In Online Question Pool, Meng Xia, Mingfei Sun, Huan Wei, Qing Chen, Yong Wang, Lei Shi, Huamin Qu, Xiaojuan Ma
Peerlens: Peer-Inspired Interactive Learning Path Planning In Online Question Pool, Meng Xia, Mingfei Sun, Huan Wei, Qing Chen, Yong Wang, Lei Shi, Huamin Qu, Xiaojuan Ma
Research Collection School Of Computing and Information Systems
Online question pools like LeetCode provide hands-on exercises of skills and knowledge. However, due to the large volume of questions and the intent of hiding the tested knowledge behind them, many users find it hard to decide where to start or how to proceed based on their goals and performance. To overcome these limitations, we present PeerLens, an interactive visual analysis system that enables peer-inspired learning path planning. PeerLens can recommend a customized, adaptable sequence of practice questions to individual learners, based on the exercise history of other users in a similar learning scenario. We propose a new way to …
Concluding Remarks, Lei Meng, Ah-Hwee Tan, Donald C. Wunsch
Concluding Remarks, Lei Meng, Ah-Hwee Tan, Donald C. Wunsch
Research Collection School Of Computing and Information Systems
This chapter summarizes the major contributions in this book and discusses their possible positions and requirements in some future scenarios. Section 8.1 follows the book structure to revisit the key contributions of this book in both theories and applications. The developed algorithms, such as the VA-ARTs for hyperparameter adaptation and the GHF-ART for multimedia representation and fusion, and the four applications, such as clustering and retrieving socially enriched multimedia data, are concentrated using one paragraph and three paragraphs, respectively. In Sect. 8.2, the roles of the proposed ART-embodied algorithms in social media clustering tasks are highlighted, and their possible evolutions …