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Articles 5941 - 5970 of 9024

Full-Text Articles in Computer Sciences

Should We Use The Sample? Analyzing Datasets Sampled From Twitter's Stream Api, Yazhe Wang, Jamie Callan, Baihua Zheng Jun 2015

Should We Use The Sample? Analyzing Datasets Sampled From Twitter's Stream Api, Yazhe Wang, Jamie Callan, Baihua Zheng

Research Collection School Of Computing and Information Systems

Researchers have begun studying content obtained from microblogging services such as Twitter to address a variety of technological, social, and commercial research questions. The large number of Twitter users and even larger volume of tweets often make it impractical to collect and maintain a complete record of activity; therefore, most research and some commercial software applications rely on samples, often relatively small samples, of Twitter data. For the most part, sample sizes have been based on availability and practical considerations. Relatively little attention has been paid to how well these samples represent the underlying stream of Twitter data. To fill …

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Continuous Non-Malleable Key Derivation And Its Application To Related-Key Security, Baodong Qin, Shenli Liu, Tsz Hon Yuen, Robert H. Deng, Kefei Chen Jun 2015

Continuous Non-Malleable Key Derivation And Its Application To Related-Key Security, Baodong Qin, Shenli Liu, Tsz Hon Yuen, Robert H. Deng, Kefei Chen

Research Collection School Of Computing and Information Systems

Related-Key Attacks (RKAs) allow an adversary to observe the outcomes of a cryptographic primitive under not only its original secret key e.g., s, but also a sequence of modified keys ϕ(s), where ϕ is specified by the adversary from a class Φ of so-called Related-Key Derivation (RKD) functions. This paper extends the notion of non-malleable Key Derivation Functions (nm-KDFs), introduced by Faust et al. (EUROCRYPT’14), to continuous nm-KDFs. Continuous nm-KDFs have the ability to protect against any a-priori unbounded number of RKA queries, instead of just a single time tampering attack as in the definition of …

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History-Based Controller Design And Optimization For Partially Observable Mdps, Akshat Kumar, Shlomo Zilberstein Jun 2015

History-Based Controller Design And Optimization For Partially Observable Mdps, Akshat Kumar, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

Partially observable MDPs provide an elegant framework forsequential decision making. Finite-state controllers (FSCs) are often used to represent policies for infinite-horizon problems as they offer a compact representation, simple-to-execute plans, and adjustable tradeoff between computational complexityand policy size. We develop novel connections between optimizing FSCs for POMDPs and the dual linear programfor MDPs. Building on that, we present a dual mixed integer linear program (MIP) for optimizing FSCs. To assign well-defined meaning to FSC nodes as well as aid in policy search, we show how to associate history-based features with each FSC node. Using this representation, we address another challenging …

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Replica Placement For Availability In The Worst Case, Peng Li, Debin Gao, Mike Reiter Jun 2015

Replica Placement For Availability In The Worst Case, Peng Li, Debin Gao, Mike Reiter

Research Collection School Of Computing and Information Systems

We explore the problem of placing object replicas on nodes in a distributed system to maximize the number of objects that remain available when node failures occur. In our model, failing (the nodes hosting) a given threshold of replicas is sufficient to disable each object, and the adversary selects which nodes to fail to minimize the number of objects that remain available. We specifically explore placement strategies based on combinatorial structures called t-packings; provide a lower bound for the object availability they offer; show that these placements offer availability that is c-competitive with optimal; propose an efficient algorithm for computing …

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Reliable Patch Trackers: Robust Visual Tracking By Exploiting Reliable Patches, Yang Li, Jianke Zhu, Steven C. H. Hoi Jun 2015

Reliable Patch Trackers: Robust Visual Tracking By Exploiting Reliable Patches, Yang Li, Jianke Zhu, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Most modern trackers typically employ a bounding box given in the first frame to track visual objects, where their tracking results are often sensitive to the initialization. In this paper, we propose a new tracking method, Reliable Patch Trackers (RPT), which attempts to identify and exploit the reliable patches that can be tracked effectively through the whole tracking process. Specifically, we present a tracking reliability metric to measure how reliably a patch can be tracked, where a probability model is proposed to estimate the distribution of reliable patches under a sequential Monte Carlo framework. As the reliable patches distributed over …

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The Role Of Intermediary In Sustainable Lending: An Economic Analysis Of Crowdfunding Platform, Ling Ge, Zhiling Guo Jun 2015

The Role Of Intermediary In Sustainable Lending: An Economic Analysis Of Crowdfunding Platform, Ling Ge, Zhiling Guo

Research Collection School Of Computing and Information Systems

Is the interest-free crowdfunding platform a promising alternative to the non-zero interest platform? This study investigates the lenders and borrowers’ incentives and choices between an indirect, non-zero interest rate platform intermediated by a field partner and a direct-lending, interest-free platform. We model the field partner as a profit maximizer that filters qualified borrowers to enable the lenders’ capital to be better utilized on the crowdfunding platform. We show that, under certain conditions, both the borrowers and lenders are better off from the existence of the field partner. The existence of field partner is necessary to effectively segment the market and …

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Assessing The Opportunities And Challenges With Big Data In The Mobile Payments Ecosystem, Jun Liu, Robert John Kauffman, Dan Ma Jun 2015

Assessing The Opportunities And Challenges With Big Data In The Mobile Payments Ecosystem, Jun Liu, Robert John Kauffman, Dan Ma

Research Collection School Of Computing and Information Systems

Information and communication technology (ICT) is an important driver of mobile payments in the financial services industry. Mobile payments (m-payments) technologies enable new channels for consumer payments for goods and services purchases, and other forms of economic exchange. The m-payments ecosystem involves multiple distinct stakeholders, and a high level of consumer data-sharing. In this paper, we will assess the current m-payments ecosystem, and discuss the challenges and opportunities with big data captured from mpayments transactions. We will also propose new directions to encourage research that will shed the light on how stakeholders can facilitate the successful adoption and realize the …

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Probabilistic Inference Techniques For Scalable Multiagent Decision Making, Akshat Kumar, Shlomo Zilberstein, Marc Toussaint Jun 2015

Probabilistic Inference Techniques For Scalable Multiagent Decision Making, Akshat Kumar, Shlomo Zilberstein, Marc Toussaint

Research Collection School Of Computing and Information Systems

Decentralized POMDPs provide an expressive framework for multiagent sequential decision making. However, the complexity of these models---NEXP-Complete even for two agents---has limited their scalability. We present a promising new class of approximation algorithms by developing novel connections between multiagent planning and machine learning. We show how the multiagent planning problem can be reformulated as inference in a mixture of dynamic Bayesian networks (DBNs). This planning-as-inference approach paves the way for the application of efficient inference techniques in DBNs to multiagent decision making. To further improve scalability, we identify certain conditions that are sufficient to extend the approach to multiagent systems …

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Aarpa: Combining Mobile And Power-Line Sensing For Fine-Grained Appliance Usage And Energy Monitoring, Nirmalya Roy, Nilavra Pathak, Archan Misra Jun 2015

Aarpa: Combining Mobile And Power-Line Sensing For Fine-Grained Appliance Usage And Energy Monitoring, Nirmalya Roy, Nilavra Pathak, Archan Misra

Research Collection School Of Computing and Information Systems

To promote energy-efficient operations in residential and office buildings, non-intrusive load monitoring (NILM) techniques have been proposed to infer the fine-grained power consumption and usage patterns of appliances from power-line measurement data. Fine-grained monitoring of everyday appliances (such as toasters and coffee makers) can not only promote energy-efficient building operations, but also provide unique insights into the context and activities of individuals. Current building-level NILM techniques are unable to identify the consumption characteristics of relatively low-load appliances, whereas smart-plug based solutions incur significant deployment and maintenance costs. In this paper, we investigate an intermediate architecture, where smart circuit breakers provide …

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Dynamic Redeployment To Counter Congestion Or Starvation In Vehicle Sharing Systems, Supriyo Ghosh, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet Jun 2015

Dynamic Redeployment To Counter Congestion Or Starvation In Vehicle Sharing Systems, Supriyo Ghosh, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet

Research Collection School Of Computing and Information Systems

Extensive usage of private vehicles has led to increased traffic congestion, carbon emissions, and usage of non-renewable resources. These concerns have led to the wide adoption of vehicle sharing (ex: bike sharing, car sharing) systems in many cities of the world. In vehicle-sharing systems, base stations (ex: docking stations for bikes) are strategically placed throughout a city and each of the base stations contain a pre-determined number of vehicles at the beginning of each day. Due to the stochastic and individualistic movement of customers,there is typically either congestion (more than required)or starvation (fewer than required) of vehicles at certain base …

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Author Topic Model-Based Collaborative Filtering For Personalized Poi Recommendations, Shuhui Jiang, Xueming Qian, Jialie Shen, Yun Fu, Tao Mei Jun 2015

Author Topic Model-Based Collaborative Filtering For Personalized Poi Recommendations, Shuhui Jiang, Xueming Qian, Jialie Shen, Yun Fu, Tao Mei

Research Collection School Of Computing and Information Systems

From social media has emerged continuous needs for automatic travel recommendations. Collaborative filtering (CF) is the most well-known approach. However, existing approaches generally suffer from various weaknesses. For example, sparsity can significantly degrade the performance of traditional CF. If a user only visits very few locations, accurate similar user identification becomes very challenging due to lack of sufficient information for effective inference. Moreover, existing recommendation approaches often ignore rich user information like textual descriptions of photos which can reflect users' travel preferences. The topic model (TM) method is an effective way to solve the "sparsity problem," but is still far …

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Keeping Pace With Criminals: Designing Patrol Allocation Against Adaptive Opportunistic Criminals, Chao Zhang, Arunesh Sinha, Milind Tambe May 2015

Keeping Pace With Criminals: Designing Patrol Allocation Against Adaptive Opportunistic Criminals, Chao Zhang, Arunesh Sinha, Milind Tambe

Research Collection School Of Computing and Information Systems

Police patrols are used ubiquitously to deter crimes in urban areas. A distinctive feature of urban crimes is that criminals react opportunistically to patrol officers' assignments. Compared to strategic attackers (such as terrorists) with a well-laid out plan, opportunistic criminals are less strategic in planning attacks and more flexible in executing them. In this paper, our goal is to recommend optimal police patrolling strategy against such opportunistic criminals. We first build a game-theoretic model that captures the interaction between officers and opportunistic criminals. However, while different models of adversary behavior have been proposed, their exact form remains uncertain. Rather than …

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Heuristic Collective Learning For Efficient And Robust Emergence Of Social Norms, Jianye Hao, Jun Sun, Dongping Huang, Yi Cai, Chao Yu May 2015

Heuristic Collective Learning For Efficient And Robust Emergence Of Social Norms, Jianye Hao, Jun Sun, Dongping Huang, Yi Cai, Chao Yu

Research Collection School Of Computing and Information Systems

In multiagent systems, social norms is a useful technique in regulating agents’ behaviors to achieve coordination or cooperation among agents. One important research question is to investigate how a desirable social norm can be evolved in a bottom-up manner through local interactions. In this paper, 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. Experimental results show that both learning strategies can support the emergence of desirable social norms more efficiently in a much broader range of multiagent interaction scenarios than previous work, …

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Relative Localization Of Rfid Tags Using Spatial-Temporal Phase Profiling, Longfei Shangguan, Zheng Yang, Alex X. Liu, Zimu Zhou, Yunhao Liu May 2015

Relative Localization Of Rfid Tags Using Spatial-Temporal Phase Profiling, Longfei Shangguan, Zheng Yang, Alex X. Liu, Zimu Zhou, Yunhao Liu

Research Collection School Of Computing and Information Systems

Many object localization applications need the relative locations of a set of objects as oppose to their absolute locations. Although many schemes for object localization using Radio Frequency Identification (RFID) tags have been proposed, they mostly focus on absolute object localization and are not suitable for relative object localization because of large error margins and the special hardware that they require. In this paper, we propose an approach called Spatial-Temporal Phase Profiling (STPP) to RFID based relative object localization. The basic idea of STPP is that by moving a reader over a set of tags during which the reader continuously …

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Non-Invasive Detection Of Moving And Stationary Human With Wifi, Chenshu Wu, Zheng Yang, Zimu Zhou, Xuefeng Liu, Yunhao Liu, Jiannong Cao May 2015

Non-Invasive Detection Of Moving And Stationary Human With Wifi, Chenshu Wu, Zheng Yang, Zimu Zhou, Xuefeng Liu, Yunhao Liu, Jiannong Cao

Research Collection School Of Computing and Information Systems

Non-invasive human sensing based on radio signals has attracted a great deal of research interest and fostered a broad range of innovative applications of localization, gesture recognition, smart health-care, etc., for which a primary primitive is to detect human presence. Previous works have studied the detection of moving humans via signal variations caused by human movements. For stationary people, however, existing approaches often employ a prerequisite scenario-tailored calibration of channel profile in human-free environments. Based on in-depth understanding of human motion induced signal attenuation reflected by PHY layer channel state information (CSI), we propose DeMan, a unified scheme for non-invasive …

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Efficient Reverse Top-K Boolean Spatial Keyword Queries On Road Networks, Yunjun Gao, Xu Qin, Baihua Zheng, Gang Chen May 2015

Efficient Reverse Top-K Boolean Spatial Keyword Queries On Road Networks, Yunjun Gao, Xu Qin, Baihua Zheng, Gang Chen

Research Collection School Of Computing and Information Systems

Reverse k nearest neighbor (RkNN) queries have a broad application base such as decision support, profile-based marketing, and resource allocation. Previous work on RkNN search does not take textual information into consideration or limits to the Euclidean space. In the real world, however, most spatial objects are associated with textual information and lie on road networks. In this paper, we introduce a new type of queries, namely, reverse top-k Boolean spatial keyword (RkBSK) retrieval, which assumes objects are on the road network and considers both spatial and textual information. Given a data set P on a road network and a …

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Report On The Fg 2015 Video Person Recognition Evaluation, J.R. Beveridge, H. Zhang, B.A. Draper, P.J. Flynn, Z. Feng, P. Huber, J. Kittler, Zhiwu Huang, Li S., Li Y., M. Kan, R. Wang, S. Shan, X. Chen, Li H., G. Hua, V. Struc, J. Krizaj, C. Ding, D. Tao May 2015

Report On The Fg 2015 Video Person Recognition Evaluation, J.R. Beveridge, H. Zhang, B.A. Draper, P.J. Flynn, Z. Feng, P. Huber, J. Kittler, Zhiwu Huang, Li S., Li Y., M. Kan, R. Wang, S. Shan, X. Chen, Li H., G. Hua, V. Struc, J. Krizaj, C. Ding, D. Tao

Research Collection School Of Computing and Information Systems

This report presents results from the Video Person Recognition Evaluation held in conjunction with the 11th IEEE International Conference on Automatic Face and Gesture Recognition. Two experiments required algorithms to recognize people in videos from the Point-and-Shoot Face Recognition Challenge Problem (PaSC). The first consisted of videos from a tripod mounted high quality video camera. The second contained videos acquired from 5 different handheld video cameras. There were 1401 videos in each experiment of 265 subjects. The subjects, the scenes, and the actions carried out by the people are the same in both experiments. Five groups from around the world …

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Beyond Traits: Social Context Based Personality Model, Jaroslaw Kochanowicz, Ah-Hwee Tan, Daniel Thalmann May 2015

Beyond Traits: Social Context Based Personality Model, Jaroslaw Kochanowicz, Ah-Hwee Tan, Daniel Thalmann

Research Collection School Of Computing and Information Systems

The relation between individual’s personality and environmental context is a key issue in psychology, recently also in character simulations. This paper contributes to both domains by proposing a socio-cognitive, contextual personality model - a new voice in a century old problem of personality, but also an approach to simulating groups of more humanlike agents. After analyzing the influence of popularity of ‘trait personality models’ on psychology and computer simulation, we propose Social Context based Personality model - a continuation and specification of the Cognitive-Affective Personality System theory. The discussion, model and implementation are provided, followed by an example application in …

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Tasknav: Task-Based Navigation Of Software Documentation, Christoph Treude, Mathieu Sicard, Marc Klocke, Martin P. Robillard May 2015

Tasknav: Task-Based Navigation Of Software Documentation, Christoph Treude, Mathieu Sicard, Marc Klocke, Martin P. Robillard

Research Collection School Of Computing and Information Systems

To help developers navigate documentation, we introduce Task Nav, a tool that automatically discovers and indexes task descriptions in software documentation. With Task Nav, we conceptualize tasks as specific programming actions that have been described in the documentation. Task Nav presents these extracted task descriptions along with concepts, code elements, and section headers in an auto-complete search interface. Our preliminary evaluation indicates that search results identified through extracted task descriptions are more helpful to developers than those found through other means, and that they help bridge the gap between documentation structure and the information needs of software developers. Video: https://www.youtube.com/watch?v=opnGYmMGnqY.

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Ambient Rendezvous: Energy Efficient Neighbor Discovery Via Acoustic Sensing, Keyu Wang, Zheng Yang, Zimu Zhou, Yunhao Liu, Lionel M. Ni May 2015

Ambient Rendezvous: Energy Efficient Neighbor Discovery Via Acoustic Sensing, Keyu Wang, Zheng Yang, Zimu Zhou, Yunhao Liu, Lionel M. Ni

Research Collection School Of Computing and Information Systems

The continual proliferation of mobile devices has stimulated the development of opportunistic encounter-based networking and has spurred a myriad of proximity-based mobile applications. A primary cornerstone of such applications is to discover neighboring devices effectively and efficiently. Despite extensive protocol optimization, current neighbor discovery modalities mainly rely on radio interfaces, whose energy and wake up delay required to initiate, configure and operate these protocols hamper practical applicability. Unlike conventional schemes that actively emit radio tones, we exploit ubiquitous audio events to discover neighbors passively. The rationale is that spatially adjacent neighbors tend to share similar ambient acoustic environments. We propose …

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Mining Patterns Of Unsatisfiable Constraints To Detect Infeasible Paths, Sun Ding, Hee Beng Kuan Tan, Lwin Khin Shar May 2015

Mining Patterns Of Unsatisfiable Constraints To Detect Infeasible Paths, Sun Ding, Hee Beng Kuan Tan, Lwin Khin Shar

Research Collection School Of Computing and Information Systems

Detection of infeasible paths is required in many areas including test coverage analysis, test case generation, security vulnerability analysis, etc. Existing approaches typically use static analysis coupled with symbolic evaluation, heuristics, or path-pattern analysis. This paper is related to these approaches but with a different objective. It is to analyze code of real systems to build patterns of unsatisfiable constraints in infeasible paths. The resulting patterns can be used to detect infeasible paths without the use of constraint solver and evaluation of function calls involved, thus improving scalability. The patterns can be built gradually. Evaluation of the proposed approach shows …

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Self-Organizing Neural Networks Integrating Domain Knowledge And Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Jacek M. Zurada May 2015

Self-Organizing Neural Networks Integrating Domain Knowledge And Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Jacek M. Zurada

Research Collection School Of Computing and Information Systems

The use of domain knowledge in learning systems is expected to improve learning efficiency and reduce model complexity. However, due to the incompatibility with knowledge structure of the learning systems and real-time exploratory nature of reinforcement learning (RL), domain knowledge cannot be inserted directly. In this paper, we show how self-organizing neural networks designed for online and incremental adaptation can integrate domain knowledge and RL. Specifically, symbol-based domain knowledge is translated into numeric patterns before inserting into the self-organizing neural networks. To ensure effective use of domain knowledge, we present an analysis of how the inserted knowledge is used by …

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A Nested Recursive Logit Model For Route Choice Analysis, Tien Mai, Mogens Fosgerau, Emma Frejinger May 2015

A Nested Recursive Logit Model For Route Choice Analysis, Tien Mai, Mogens Fosgerau, Emma Frejinger

Research Collection School Of Computing and Information Systems

We propose a route choice model that relaxes the independence from irrelevant alternatives property of the logit model by allowing scale parameters to be link specific. Similar to the recursive logit (RL) model proposed by Fosgerau et al. (2013), the choice of path is modeled as a sequence of link choices and the model does not require any sampling of choice sets. Furthermore, the model can be consistently estimated and efficiently used for prediction.A key challenge lies in the computation of the value functions, i.e. the expected maximum utility from any position in the network to a destination. The value …

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Breaking The News: First Impressions Matter On Online News, Julio Reis, Fabr´Icio Benevenuto, Pedro Olmo, Raquel Prates, Haewoon Kwak, Jisun An May 2015

Breaking The News: First Impressions Matter On Online News, Julio Reis, Fabr´Icio Benevenuto, Pedro Olmo, Raquel Prates, Haewoon Kwak, Jisun An

Research Collection School Of Computing and Information Systems

A growing number of people are changing the way they consume news, replacing the traditional physical newspapers and magazines by their virtual online versions or/and weblogs. The interactivity and immediacy present in online news are changing the way news are being produced and exposed by media corporations. News websites have to create effective strategies to catch people’s attention and attract their clicks. In this paper we investigate possible strategies used by online news corporations in the design of their news headlines. We analyze the content of 69,907 headlines produced by four major global media corporations during a minimum of eight …

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Map: A Computational Model For Adaptive Persuasion, Yilin Kang, Ah-Hwee Tan May 2015

Map: A Computational Model For Adaptive Persuasion, Yilin Kang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

While a variety of persuasion agents have been created and applied in different domains such as marketing, military training and health industry, there is a lack of a model which provides a unified framework for different persuasion strategies. Specifically, persuasion is not adaptable to the individuals’ personal states in different situations. Grounded in the Elaboration Likelihood Model (ELM), this paper presents a computational model called Model for Adaptive Persuasion (MAP) for virtual agents. MAP is a semi-connected network model which enables an agent to adapt its persuasion strategies through feedback. We have implemented and evaluated a MAP-based virtual nurse agent …

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Discovering The Rise And Fall Of Software Engineering Ideas From Scholarly Publication Data, Subhajit Datta, Santonu Sarkar, Sajeev A. S. M., Nishant Kumar May 2015

Discovering The Rise And Fall Of Software Engineering Ideas From Scholarly Publication Data, Subhajit Datta, Santonu Sarkar, Sajeev A. S. M., Nishant Kumar

Research Collection School Of Computing and Information Systems

For researchers and practitioners of a relatively young discipline like software engineering, an enduring concern is to identify the acorns that will grow into oaks -- ideas remaining most current in the long run. Additionally, it is interesting to know how the ideas have risen in importance, and fallen, perhaps to rise again. We analyzed a corpus of 19,000+ papers written by 21,000+ authors across 16 software engineering publication venues from 1975 to 2010, to empirically determine the half-life of software engineering research topics. We adapted existing measures of half-life as well as defined a specific measure based on publication …

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Solving Multi-Vehicle Profitable Tour Problem Via Knowledge Adoption In Evolutionary Bi-Level Programming, Stephanus Daniel Handoko, Abhishek Gupta, Chen Kim Heng, Hoong Chuin Lau, Yew Soon Ong, Puay Siew Tan May 2015

Solving Multi-Vehicle Profitable Tour Problem Via Knowledge Adoption In Evolutionary Bi-Level Programming, Stephanus Daniel Handoko, Abhishek Gupta, Chen Kim Heng, Hoong Chuin Lau, Yew Soon Ong, Puay Siew Tan

Research Collection School Of Computing and Information Systems

Profitable tour problem (PTP) belongs to the class of vehicle routing problem (VRP) with profits seeking to maximize the difference between the total collected profit and the total cost incurred. Traditionally, PTP involves single vehicle. In this paper, we consider PTP with multiple vehicles. Unlike the classical VRP that seeks to serve all customers, PTP involves the strategic-level customer selection so as to maximize the total collected profit and the operational-level route optimization to minimize the total cost incurred. Therefore, PTP is essentially the knapsack problem at the strategic level with VRP at the operational level. That means the evolutionary …

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Measuring Centralities For Transportation Networks Beyond Structures, Yew-Yih Cheng, Lee Ka Wei, Roy, Ee-Peng Lim, Feida Zhu May 2015

Measuring Centralities For Transportation Networks Beyond Structures, Yew-Yih Cheng, Lee Ka Wei, Roy, Ee-Peng Lim, Feida Zhu

Research Collection School Of Computing and Information Systems

In an urban city, its transportation network supports efficient flow of people between different parts of the city. Failures in the network can cause major disruptions to commuter and business activities which can result in both significant economic and time losses. In this paper, we investigate the use of centrality measures to determine critical nodes in a transportation network so as to improve the design of the network as well as to devise plans for coping with the network failures. Most centrality measures in social network analysis research unfortunately consider only topological structure of the network and are oblivious of …

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Flutcha: Using Fluency To Distinguish Humans From Computers, Kotaro Hara, Mohammad Taghi Hajiaghayi, Benjamin B. Benderson May 2015

Flutcha: Using Fluency To Distinguish Humans From Computers, Kotaro Hara, Mohammad Taghi Hajiaghayi, Benjamin B. Benderson

Research Collection School Of Computing and Information Systems

Improvements in image understanding technologies aremaking it possible for computers to pass traditionalCAPTCHA tests with high probability. This suggests theneed for new kinds of tasks that are easy to accomplishfor humans but remain difficult for computers. In thispaper, we introduce Fluency CAPTCHA (FluTCHA), anovel method to distinguish humans from computersusing the fact that humans are better than machines atimproving the fluency of sentences. We propose a wayto let users work on FluTCHA tests and simultaneouslycomplete useful linguistic tasks. Evaluation studiesdemonstrate the feasibility of using FluTCHA todistinguish humans from computers.

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Electronic Contract Signing Without Using Trusted Third Party, Zhiguo Wan, Robert H. Deng, David Kuo Chuen Lee May 2015

Electronic Contract Signing Without Using Trusted Third Party, Zhiguo Wan, Robert H. Deng, David Kuo Chuen Lee

Research Collection School Of Computing and Information Systems

Electronic contract signing allows two potentially dis-trustful parties to digitally sign an electronic document “simultaneously” across a network. Existing solutions for electronic contract signing either require the involvement of a trusted third party (TTP), or are complex and expensive in communication and computation. In this paper we propose an electronic contract signing protocol between two parties with the following advantages over existing solutions: 1) it is practical and scalable due to its simplicity and high efficiency; 2) it does not require any trusted third party as the mediator; and 3) it guarantees fairness between the two signing parties. We achieve …

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