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Articles 5461 - 5490 of 9024

Full-Text Articles in Computer Sciences

Edit Distance Based Encryption And Its Application, Tran Viet Xuan Phuong, Guomin Yang, Willy Susilo, Kaitai Liang Jul 2016

Edit Distance Based Encryption And Its Application, Tran Viet Xuan Phuong, Guomin Yang, Willy Susilo, Kaitai Liang

Research Collection School Of Computing and Information Systems

Edit distance, also known as Levenshtein distance, is a very useful tool to measure the similarity between two strings. It has been widely used in many applications such as natural language processing and bioinformatics. In this paper, we introduce a new type of fuzzy public key encryption called Edit Distance-based Encryption (EDE). In EDE, the encryptor can specify an alphabet string and a threshold when encrypting a message, and a decryptor can obtain a decryption key generated from another alphabet string, and the decryption will be successful if and only if the edit distance between the two strings is within …

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One-Round Strong Oblivious Signature-Based Envelope, Rongmao Chen, Yi Mu, Willy Susilo, Guomin Yang, Fuchun Guo, Mingwu Zhang Jul 2016

One-Round Strong Oblivious Signature-Based Envelope, Rongmao Chen, Yi Mu, Willy Susilo, Guomin Yang, Fuchun Guo, Mingwu Zhang

Research Collection School Of Computing and Information Systems

Oblivious Signature-Based Envelope (OSBE) has been widely employed for anonymity-orient and privacy-preserving applications. The conventional OSBE execution relies on a secure communication channel to protect against eavesdroppers. In TCC 2012, Blazy, Pointcheval and Vergnaud proposed a framework of OSBE (BPV-OSBE) without requiring any secure channel by clarifying and enhancing the OSBE security notions. They showed how to generically build an OSBE scheme satisfying the new strong security in the standard model with a common-reference string. Their framework requires 2-round interactions and relies on the smooth projective hash function (SPHF) over special languages, i.e., languages from encryption of signatures. In this …

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The Impact Of Nasd Rule 2711 And Nyse Rule 472 On Analyst Behavior: The Strategic Timing Of Recommendations Issued On Weekends, Yi Dong, Nan Hu Jul 2016

The Impact Of Nasd Rule 2711 And Nyse Rule 472 On Analyst Behavior: The Strategic Timing Of Recommendations Issued On Weekends, Yi Dong, Nan Hu

Research Collection School Of Computing and Information Systems

Amendments to NASD Rule 2711 and NYSE Rule 472, enacted in May 2002, mandate that sell-side analysts disclose the distribution of their security recommendations by buy, hold and sell category. This regulation enhances the transparency of analysts' information and mitigates the long-recognized optimistic bias in their recommendations. However, we find that analysts are more likely to issue sell recommendations or downgrade revisions on weekends when investors have limited attention after these rule changes. This pattern is more pronounced for prestigious analysts, who are more likely to influence stock prices. Market reaction tests reveal an incomplete immediate response and a greater …

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Real-Time Salient Object Detection With A Minimum Spanning Tree, Wei-Chih Tu, Shengfeng He, Qingxiong Yang, Shao-Yi Chien Jul 2016

Real-Time Salient Object Detection With A Minimum Spanning Tree, Wei-Chih Tu, Shengfeng He, Qingxiong Yang, Shao-Yi Chien

Research Collection School Of Computing and Information Systems

In this paper, we present a real-time salient object detection system based on the minimum spanning tree. Due to the fact that background regions are typically connected to the image boundaries, salient objects can be extracted by computing the distances to the boundaries. However, measuring the image boundary connectivity efficiently is a challenging problem. Existing methods either rely on superpixel representation to reduce the processing units or approximate the distance transform. Instead, we propose an exact and iteration free solution on a minimum spanning tree. The minimum spanning tree representation of an image inherently reveals the object geometry information in …

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Generic Anonymous Identity-Based Broadcast Encryption With Chosen-Ciphertext Security, Kai He, Jian Weng, Man Ho Au, Yijun Mao, Deng, Robert H. Jul 2016

Generic Anonymous Identity-Based Broadcast Encryption With Chosen-Ciphertext Security, Kai He, Jian Weng, Man Ho Au, Yijun Mao, Deng, Robert H.

Research Collection School Of Computing and Information Systems

In a broadcast encryption system, a broadcaster can encrypt a message to a group of authorized receivers S and each authorized receiver can use his/her own private key to correctly decrypt the broadcast ciphertext, while the users outside S cannot. Identity-based broadcast encryption (IBBE) system is a variant of broadcast encryption system where any string representing the user’s identity (e.g., email address) can be used as his/her public key. IBBE has found many applications in real life, such as pay-TV systems, distribution of copyrighted materials, satellite radio communications. When employing an IBBE system, it is very important to protect the …

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Word Clouds With Latent Variable Analysis For Visual Comparison Of Documents, Tuan M. V. Le, Hady W. Lauw Jul 2016

Word Clouds With Latent Variable Analysis For Visual Comparison Of Documents, Tuan M. V. Le, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Word cloud is a visualization form for text that is recognized for its aesthetic, social, and analytical values. Here, we are concerned with deepening its analytical value for visual comparison of documents. To aid comparative analysis of two or more documents, users need to be able to perceive similarities and differences among documents through their word clouds. However, as we are dealing with text, approaches that treat words independently may impede accurate discernment of similarities among word clouds containing different words of related meanings. We therefore motivate the principle of displaying related words in a coherent manner, and propose to …

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A Feasible No-Root Approach On Android, Yao Cheng, Yingjiu Li, Robert H. Deng Jul 2016

A Feasible No-Root Approach On Android, Yao Cheng, Yingjiu Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

Root is the administrative privilege on Android, which is however inaccessible on stock Android devices. Due to the desire for privileged functionalities and the reluctance of rooting their devices, Android users seek for no-root approaches, which provide users with part of root privileges without rooting their devices. In this paper, we newly discover a feasible no-root approach based on the ADB loopback. To ensure such no-root approach is not misused proactively, we examine its dark side, including privacy leakage via logs and user input inference. Finally, we discuss the solutions and suggestions from different perspectives.

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Robust Median Reversion Strategy For Online Portfolio Selection, Dingjiang Huang, Junlong Zhou, Bin Li, Hoi, Steven C. H., Shuigeng Zhou Jul 2016

Robust Median Reversion Strategy For Online Portfolio Selection, Dingjiang Huang, Junlong Zhou, Bin Li, Hoi, Steven C. H., Shuigeng Zhou

Research Collection School Of Computing and Information Systems

On-line portfolio selection has been attracting increasing interests from artificial intelligence community in recent decades. Mean reversion, as one most frequent pattern in financial markets, plays an important role in some state-of-the-art strategies. Though successful in certain datasets, existing mean reversion strategies do not fully consider noises and outliers in the data, leading to estimation error and thus non-optimal portfolios, which results in poor performance in practice. To overcome the limitation, we propose to exploit the reversion phenomenon by robust L1-median estimator, and design a novel on-line portfolio selection strategy named "Robust Median Reversion" (RMR), which makes optimal portfolios based …

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On Effective Personalized Music Retrieval Via Exploring Online User Behaviors, Zhiyong Cheng, Jialie Shen, Steven C. H. Hoi Jul 2016

On Effective Personalized Music Retrieval Via Exploring Online User Behaviors, Zhiyong Cheng, Jialie Shen, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

In this paper, we study the problem of personalized text based music retrieval which takes users' music preferences on songs into account via the analysis of online listening behaviours and social tags. Towards the goal, a novel Dual-Layer Music Preference Topic Model (DL-MPTM) is proposed to construct latent music interest space and characterize the correlations among (user, song, term). Based on the DL-MPTM, we further develop an effective personalized music retrieval system. To evaluate the system's performance, extensive experimental studies have been conducted over two test collections to compare the proposed method with the state-of-the-art music retrieval methods. The results …

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Where Is The Goldmine? Finding Promising Business Locations Through Facebook Data Analytics, Jovian Lin, Richard Oentaryo, Ee-Peng Lim, Casey Vu, Adrian Vu, Agus Kwee Jul 2016

Where Is The Goldmine? Finding Promising Business Locations Through Facebook Data Analytics, Jovian Lin, Richard Oentaryo, Ee-Peng Lim, Casey Vu, Adrian Vu, Agus Kwee

Research Collection School Of Computing and Information Systems

If you were to open your own cafe, would you not want to effortlessly identify the most suitable location to set up your shop? Choosing an optimal physical location is a critical decision for numerous businesses, as many factors contribute to the final choice of the location. In this paper, we seek to address the issue by investigating the use of publicly available Facebook Pages data-which include user "check-ins", types of business, and business locations-to evaluate a user-selected physical location with respect to a type of business. Using a dataset of 20,877 food businesses in Singapore, we conduct analysis of …

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A Learning-To-Rank Based Fault Localization Approach Using Likely Invariants, Tien-Duy B. Le, David Lo, Claire Le Goues, Lars Grunske Jul 2016

A Learning-To-Rank Based Fault Localization Approach Using Likely Invariants, Tien-Duy B. Le, David Lo, Claire Le Goues, Lars Grunske

Research Collection School Of Computing and Information Systems

Debugging is a costly process that consumes much of developer time and energy. To help reduce debugging effort, many studies have proposed various fault localization approaches. These approaches take as input a set of test cases (some failing, some passing) and produce a ranked list of program elements that are likely to be the root cause of the failures (i.e., failing test cases). In this work, we propose Savant, a new fault localization approach that employs a learning-to-rank strategy, using likely invariant diffs and suspiciousness scores as features, to rank methods based on their likelihood to be a root cause …

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Robust Repositioning To Counter Unpredictable Demand In Bike Sharing Systems, Supriyo Ghosh, Michael Trick, Pradeep Varakantham Jul 2016

Robust Repositioning To Counter Unpredictable Demand In Bike Sharing Systems, Supriyo Ghosh, Michael Trick, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Bike Sharing Systems (BSSs) experience a significant loss in customer demand due to starvation (empty base stations precluding bike pickup) or congestion (full base stations precluding bike return). Therefore, BSSs operators reposition bikes between stations with the help of carrier vehicles. Due to unpredictable and dynamically changing nature of the demand, myopic reasoning typically provides a below par performance. We propose an online and robust repositioning approach to minimise the loss in customer demand while considering the possible uncertainty in future demand. Specifically, we develop a scenario generation approach based on an iterative two player game to compute a strategy …

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On Very Large Scale Test Collection For Landmark Image Search Benchmarking, Zhiyong Cheng, Jialie Shen Jul 2016

On Very Large Scale Test Collection For Landmark Image Search Benchmarking, Zhiyong Cheng, Jialie Shen

Research Collection School Of Computing and Information Systems

High quality test collections have been becoming more and more important for the technological advancement in geo-referenced image retrieval and analytics. In this paper, we present a large scale test collection to support robust performance evaluation of landmark image search and corresponding construction methodology. Using the approach, we develop a very large scale test collection consisting of three key components: (1) 355,141 images of 128 landmarks in five cities across three continents crawled from Flickr; (2) different kinds of textual features for each image, including surrounding text (e.g. tags), contextual data (e.g. geo-location and upload time), and metadata (e.g. uploader …

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Which Information Sources Are More Effective And Reliable In Video Search, Cheng Zhiyong, Xuanchong Li, Jialie Shen, Alexander G. Hauptmann Jul 2016

Which Information Sources Are More Effective And Reliable In Video Search, Cheng Zhiyong, Xuanchong Li, Jialie Shen, Alexander G. Hauptmann

Research Collection School Of Computing and Information Systems

It is common that users are interested in finding video segments, which contain further information about the video contents in a segment of interest. To facilitate users to find and browse related video contents, video hyperlinking aims at constructing links among video segments with relevant information in a large video collection. In this study, we explore the effectiveness of various video features on the performance of video hyperlinking, including subtitle, metadata, content features (i.e., audio and visual), surrounding context, as well as the combinations of those features. Besides, we also test different search strategies over different types of queries, which …

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Learning Compact Visual Representation With Canonical Views For Robust Mobile Landmark Search, Lei Zhu, Jialie Shen, Xiaobai Liu, Liang Xie, Liqiang Nie Jul 2016

Learning Compact Visual Representation With Canonical Views For Robust Mobile Landmark Search, Lei Zhu, Jialie Shen, Xiaobai Liu, Liang Xie, Liqiang Nie

Research Collection School Of Computing and Information Systems

Mobile Landmark Search (MLS) recently receives increasing attention. However, it still remains unsolved due to two important issues. One is high bandwidth consumption of query transmission, and the other is the huge visual variations of query images. This paper proposes a Canonical View based Compact Visual Representation (2CVR) to handle these problems via novel three-stage learning. First, a submodular function is designed to measure visual representativeness and redundancy of a view set. With it, canonical views, which capture key visual appearances of landmark with limited redundancy, are efficiently discovered with an iterative mining strategy. Second, multimodal sparse coding is applied …

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A Survey On Future Internet Security Architectures, Wenxiu Ding, Zheng Yan, Robert H. Deng Jul 2016

A Survey On Future Internet Security Architectures, Wenxiu Ding, Zheng Yan, Robert H. Deng

Research Collection School Of Computing and Information Systems

Current host-centric Internet Protocol (IP) networks are facing unprecedented challenges, such as network attacks and the exhaustion of IP addresses. Motivated by emerging demands for security, mobility, and distributed networking, many research projects have been initiated to design the future Internet from a clean slate. In order to obtain a thorough knowledge of security in future Internet architecture, we review a number of well-known projects, including named data networking, Content Aware Searching Retrieval and sTreaming, MobilityFirst Future Internet Architecture Project (MobilityFirst), eXpressive Internet Architecture, and scalability, control, and isolation on next-generation network. These projects aim to move away from the …

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Passively Testing Routing Protocols In Wireless Sensor Networks, Xiaoping Che, Stephane Maag, Hwee-Xian Tan, Hwee-Pink Tan Jul 2016

Passively Testing Routing Protocols In Wireless Sensor Networks, Xiaoping Che, Stephane Maag, Hwee-Xian Tan, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

Smart systems are today increasingly developed with the number of wireless sensor devices that drastically increases. They are implemented within several contexts through our environment. Thus, sensed data transported in ubiquitous systems are important and the way to carry them must be efficient and reliable. For that purpose, several routing protocols have been proposed to wireless sensor networks (WSN). However, one stage that is often neglected before their deployment, is the conformance testing process, a crucial and challenging step. Active testing techniques commonly used in wired networks are not suitable to WSN and passive approaches are needed. While some works …

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Practitioners' Expectations On Automated Fault Localization, Pavneet Singh Kochhar, Xin Xia, David Lo, Shanping Li Jul 2016

Practitioners' Expectations On Automated Fault Localization, Pavneet Singh Kochhar, Xin Xia, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Software engineering practitioners often spend significant amount of time and effort to debug. To help practitioners perform this crucial task, hundreds of papers have proposed various fault localization techniques. Fault localization helps practitioners to find the location of a defect given its symptoms (e.g., program failures). These localization techniques have pinpointed the locations of bugs of various systems of diverse sizes, with varying degrees of success, and for various usage scenarios. Unfortunately, it is unclear whether practitioners appreciate this line of research. To fill this gap, we performed an empirical study by surveying 386 practitioners from more than 30 countries …

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Cross-Modal Self-Taught Hashing For Large-Scale Image Retrieval, Liang Xie, Lei Zhu, Peng Pan, Yansheng Lu Jul 2016

Cross-Modal Self-Taught Hashing For Large-Scale Image Retrieval, Liang Xie, Lei Zhu, Peng Pan, Yansheng Lu

Research Collection School Of Computing and Information Systems

Cross-modal hashing integrates the advantages of traditional cross-modal retrieval and hashing, it can solve large-scale cross-modal retrieval effectively and efficiently. However, existing cross-modal hashing methods rely on either labeled training data, or lack semantic analysis. In this paper, we propose Cross-Modal Self-Taught Hashing (CMSTH) for large-scale cross-modal and unimodal image retrieval. CMSTH can effectively capture the semantic correlation from unlabeled training data. Its learning process contains three steps: first we propose Hierarchical Multi-Modal Topic Learning (HMMTL) to detect multi-modal topics with semantic information. Then we use Robust Matrix Factorization (RMF) to transfer the multi-modal topics to hash codes which are …

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Scalable Greedy Algorithms For Task/Resource Constrained Multi-Agent Stochastic Planning, Pritee Agrawal, Pradeep Varakantham, William Yeoh Jul 2016

Scalable Greedy Algorithms For Task/Resource Constrained Multi-Agent Stochastic Planning, Pritee Agrawal, Pradeep Varakantham, William Yeoh

Research Collection School Of Computing and Information Systems

Synergistic interactions between task/resource allocation and stochastic planning exist in many environments such as transportation and logistics, UAV task assignment and disaster rescue. Existing research in exploiting these synergistic interactions between the two problems have either only considered domains where tasks/resources are completely independent of each other or have focussed on approaches with limited scalability. In this paper, we address these two limitations by introducing a generic model for task/resource constrained multi-agent stochastic planning, referred to as TasC-MDPs. We provide two scalable greedy algorithms, one of which provides posterior quality guarantees. Finally, we illustrate the high scalability and solution performance …

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Sequential Decision Making For Improving Efficiency In Urban Environments, Pradeep Varakantham Jul 2016

Sequential Decision Making For Improving Efficiency In Urban Environments, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Rapid "urbanization" (more than 50% of world's population now resides in cities) coupled with the natural lack of coordination in usage of common resources (ex: bikes, ambulances, taxis, traffic personnel, attractions) has a detrimental effect on a wide variety of response (ex: waiting times, response time for emergency needs) and coverage metrics (ex: predictability of traffic/security patrols) in cities of today. Motivated by the need to improve response and coverage metrics in urban environments, my research group is focussed on building intelligent agent systems that make sequential decisions to continuously match available supply of resources to an uncertain demand for …

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Can Instagram Posts Help Characterize Urban Micro-Events?, Kasthuri Jayarajah, Archan Misra Jul 2016

Can Instagram Posts Help Characterize Urban Micro-Events?, Kasthuri Jayarajah, Archan Misra

Research Collection School Of Computing and Information Systems

Social media content, from platforms such as Twitter and Foursquare, has enabled an exciting new field of social sensing, where participatory content generated by users has been used to identify unexpected emerging or trending events. In contrast to such text-based channels, we focus on image-sharing social applications (specifically Instagram), and investigate how such urban social sensing can leverage upon the additional multi-modal, multimedia content. Given the significantly higher fraction of geotagged content on Instagram, we aim to use such channels to go beyond identification of long-lived events (e.g., a marathon) to achieve finer-grained characterization of multiple micro-events (e.g., a person …

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An Adaptability-Driven Model And Tool For Analysis Of Service Profitability, Eng Lieh Ouh, Jarzabek Stan Jul 2016

An Adaptability-Driven Model And Tool For Analysis Of Service Profitability, Eng Lieh Ouh, Jarzabek Stan

Research Collection School Of Computing and Information Systems

Profitability of adopting Software-as-a-Service (SaaS) solutions forexisting applications is currently analyzed mostly in informal way. Informalanalysis is unreliable because of the many conflicting factors that affect costs andbenefits of offering applications on the cloud. We propose a quantitative economicmodel for evaluating profitability of migrating to SaaS that enables potentialservice providers to evaluate costs and benefits of various migration strategiesand choices of target service architectures. In previous work, we presented arudimentary conceptual SaaS economic model enumerating factors that have todo with service profitability, and defining qualitative relations among them. Aquantitative economic model presented in this paper extends the conceptualmodel with equations …

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From Offline To Online: How Health Insurance Policies Drive The Demand For Online Healthcare Service?, Yue Yu, Qiu-Yan Mei, Qiu-Hong Wang Jul 2016

From Offline To Online: How Health Insurance Policies Drive The Demand For Online Healthcare Service?, Yue Yu, Qiu-Yan Mei, Qiu-Hong Wang

Research Collection School Of Computing and Information Systems

Online healthcare service has gradually become a significant part of healthcare services, especially in emerging economy with shortage in medical resources and wide coverage in the Internet usage. This paper studies how health insurance policies affect the demand for online healthcare consultation by using longitudinal online healthcare and offline medical services datasets of a major city in China. The two policies we study are the integration of health insurance systems in urban and rural regions and the integration of health insurance systems between pairwise-cities. The empirical results show that both policies significantly affected the demand for online consultation. Our study …

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Response To Sbp-Brims Data Challenge: Agent-Based Approach To Human Migration Movement, Lin Junjie, Larry, Kathleen M. Carley Jul 2016

Response To Sbp-Brims Data Challenge: Agent-Based Approach To Human Migration Movement, Lin Junjie, Larry, Kathleen M. Carley

Research Collection School Of Computing and Information Systems

In this work, we attempt to address the social question of international migration, and the resulting shifts in country populations. This is achieved through the development of a country-level agent-based dynamic network model to examine shifts in population given network relations among countries, which inuences overall population change.

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Hci Testing In Laboratory Or Field Settings, Chuan-Hoo Tan, Austin Silva, Rich Lee, Kanliang Wang, Fiona Fui-Hoon Nah Jul 2016

Hci Testing In Laboratory Or Field Settings, Chuan-Hoo Tan, Austin Silva, Rich Lee, Kanliang Wang, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

This paper presents perspectives from both academia and practice on how an HCI testing is to be conducted and the deliberations that go into the testing. HCI testing can be conducted in closed-door laboratory or in a field setting. While there is an increased interest in field testing of an HCI artifact, there is always an enduring concern over how to administer a field testing given that the testers will have less control over the course of testing. In this paper, we cover HCI testing deliberation as well as the operational issues of field testing, and conclude the paper with …

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The Impact Of Security Cues On User Perceived Security In E-Commerce, Samuel N. Smith, Fiona Fui-Hoon Nah, Maggie X. Cheng Jul 2016

The Impact Of Security Cues On User Perceived Security In E-Commerce, Samuel N. Smith, Fiona Fui-Hoon Nah, Maggie X. Cheng

Research Collection School Of Computing and Information Systems

Users are expected to assess the level of security of e-commerce websites before conducting online transactions. In this research, we examine user assessment of security of e-commerce web pages based on cues presented on the web pages. A pilot study was conducted in which each subject assessed six e-commerce web pages with varying cues (i.e., HTTP vs. HTTPS, fraudulent vs. authentic URL, padlocks beside fields), and the findings are reported.

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Patient Engagement In The Medical Facility Waiting Room Using Gamified Healthcare Information Delivery, Raheel Hassan, Nathan W. Twyman, Fiona F. Nah, Keng Siau Jul 2016

Patient Engagement In The Medical Facility Waiting Room Using Gamified Healthcare Information Delivery, Raheel Hassan, Nathan W. Twyman, Fiona F. Nah, Keng Siau

Research Collection School Of Computing and Information Systems

This study explores the proposition that medical facility waiting rooms are an opportune setting to engage with and educate patients while they are waiting for care. In collaboration with emergency department (ED) personnel, we developed ER Hero, a tablet-based application for waiting rooms that introduces patients to ED professionals and operations through mini-games and story-like interaction. We evaluated this prototype with human participants to determine how well it performed when compared to paper-based information disclosure presenting the same information. Participants using the application exhibited increased ED knowledge, decreased nervousness, and increased interest. The gamified application outperformed a paper-based approach on …

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The Effects Of Multiple Query Evidences On Social Image Retrieval, Zhiyong Cheng, Jialie Shen, Haiyan Miao Jul 2016

The Effects Of Multiple Query Evidences On Social Image Retrieval, Zhiyong Cheng, Jialie Shen, Haiyan Miao

Research Collection School Of Computing and Information Systems

System performance assessment and comparison are fundamental for large-scale image search engine development. This article documents a set of comprehensive empirical studies to explore the effects of multiple query evidences on large-scale social image search. The search performance based on the social tags, different kinds of visual features and their combinations are systematically studied and analyzed. To quantify the visual query complexity, a novel quantitative metric is proposed and applied to assess the influences of different visual queries based on their complexity levels. Besides, we also study the effects of automatic text query expansion with social tags using a pseudo …

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An Interference-Free Programming Model For Network Objects, Mischael Schill, Christopher M. Poskitt, Bertrand Meyer Jun 2016

An Interference-Free Programming Model For Network Objects, Mischael Schill, Christopher M. Poskitt, Bertrand Meyer

Research Collection School Of Computing and Information Systems

Network objects are a simple and natural abstraction for distributed object-oriented programming. Languages that support network objects, however, often leave synchronization to the user, along with its associated pitfalls, such as data races and the possibility of failure. In this paper, we present D-Scoop, a distributed programming model that allows for interference-free and transaction-like reasoning on (potentially multiple) network objects, with synchronization handled automatically, and network failures managed by a compensation mechanism. We achieve this by leveraging the runtime semantics of a multi-threaded object-oriented concurrency model, directly generalizing it with a message-based protocol for efficiently coordinating remote objects. We present …

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