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Articles 7921 - 7950 of 10509
Full-Text Articles in Entire DC Network
Dynamic Stochastic Orienteering Problems For Risk-Aware Applications, Hoong Chuin Lau, William Yeoh, Pradeep Varakantham, Duc Thien Nguyen
Dynamic Stochastic Orienteering Problems For Risk-Aware Applications, Hoong Chuin Lau, William Yeoh, Pradeep Varakantham, Duc Thien Nguyen
Research Collection School Of Computing and Information Systems
Orienteering problems (OPs) are a variant of the well-known prize-collecting traveling salesman problem, where the salesman needs to choose a subset of cities to visit within a given deadline. OPs and their extensions with stochastic travel times (SOPs) have been used to model vehicle routing problems and tourist trip design problems. However, they suffer from two limitations travel times between cities are assumed to be time independent and the route provided is independent of the risk preference (with respect to violating the deadline) of the user. To address these issues, we make the following contributions: We introduce (1) a dynamic …
Control-Theoretic Utility Maximization In Multihop Wireless Networks Under Mission Dynamics, Sharanya Eswaran, Archan Misra, Thomas La Porta
Control-Theoretic Utility Maximization In Multihop Wireless Networks Under Mission Dynamics, Sharanya Eswaran, Archan Misra, Thomas La Porta
Research Collection School Of Computing and Information Systems
Both bandwidth and energy become important resource constraints when multi-hop wireless networks are used to transport high data rate traffic for a moderately long duration. In such networks, it is important to control the traffic rates to not only conform to the link capacity bounds but also to ensure that the energy of battery-powered forwarding nodes is utilized judiciously to avoid premature exhaustion (i.e., the network lasts as long as the applications require data from the sources) without being unneccesarily conservative (i.e., ensuring that the applications derive the maximum utility possible). Unlike prior work that focuses on the instantaneous distributed …
Presynaptic Learning And Memory With A Persistent Firing Neuron And A Habituating Synapse: A Model Of Short Term Persistent Habituation, Kiruthika Ramanathan, Ning Ning, Dhiviya Dhanasekar, Guoqi Li, Luping Shi, Prahlad Vadakkepat
Presynaptic Learning And Memory With A Persistent Firing Neuron And A Habituating Synapse: A Model Of Short Term Persistent Habituation, Kiruthika Ramanathan, Ning Ning, Dhiviya Dhanasekar, Guoqi Li, Luping Shi, Prahlad Vadakkepat
Research Collection School Of Computing and Information Systems
Our paper explores the interaction of persistent firing axonal and presynaptic processes in the generation of short term memory for habituation. We first propose a model of a sensory neuron whose axon is able to switch between passive conduction and persistent firing states, thereby triggering short term retention to the stimulus. Then we propose a model of a habituating synapse and explore all nine of the behavioral characteristics of short term habituation in a two neuron circuit. We couple the persistent firing neuron to the habituation synapse and investigate the behavior of short term retention of habituating response. Simulations show …
Collective Churn Prediction In Social Network, Richard J. Oentaryo, Ee-Peng Lim, David Lo, Feida Zhu, Philips K. Prasetyo
Collective Churn Prediction In Social Network, Richard J. Oentaryo, Ee-Peng Lim, David Lo, Feida Zhu, Philips K. Prasetyo
Research Collection School Of Computing and Information Systems
In service-based industries, churn poses a significant threat to the integrity of the user communities and profitability of the service providers. As such, research on churn prediction methods has been actively pursued, involving either intrinsic, user profile factors or extrinsic, social factors. However, existing approaches often address each type of factors separately, thus lacking a comprehensive view of churn behaviors. In this paper, we propose a new churn prediction approach based on collective classification (CC), which accounts for both the intrinsic and extrinsic factors by utilizing the local features of, and dependencies among, individuals during prediction steps. We evaluate our …
Automatic Compositional Verification Of Timed Systems, Shang-Wei Lin, Yang Liu, Jun Sun, Jin Song Dong, Étienne André
Automatic Compositional Verification Of Timed Systems, Shang-Wei Lin, Yang Liu, Jun Sun, Jin Song Dong, Étienne André
Research Collection School Of Computing and Information Systems
Specification and verification of real-time systems are important research topics with crucial applications; however, the so-called state space explosion problem often prevents model checking to be used in practice for large systems. In this work, we present a self-contained toolkit to analyze real-time systems specified using event-recording automata (ERAs), which supports system modeling, animated simulation, and fully automatic compositional verification based on learning techniques. Experimental results show that our tool outperforms the state-of-the-art timed model checker.
A Non-Parametric Visual-Sense Model Of Images: Extending The Cluster Hypothesis Beyond Text, Kong-Wah Wan, Ah-Hwee Tan, Joo-Hwee Lim, Liang-Tien Chia
A Non-Parametric Visual-Sense Model Of Images: Extending The Cluster Hypothesis Beyond Text, Kong-Wah Wan, Ah-Hwee Tan, Joo-Hwee Lim, Liang-Tien Chia
Research Collection School Of Computing and Information Systems
The main challenge of a search engine is to find information that are relevant and appropriate. However, this can become difficult when queries are issued using ambiguous words. Rijsbergen first hypothesized a clustering approach for web pages wherein closely associated pages are treated as a semantic group with the same relevance to the query (Rijsbergen 1979). In this paper, we extend Rijsbergen’s cluster hypothesis to multimedia content such as images. Given a user query, the polysemy in the return image set is related to the many possible meanings of the query. We develop a method to cluster the polysemous images …
Boosting Multi-Kernel Locality-Sensitive Hashing For Scalable Image Retrieval, Hao Xia, Steven C. H. Hoi, Pengcheng Wu, Rong Jin
Boosting Multi-Kernel Locality-Sensitive Hashing For Scalable Image Retrieval, Hao Xia, Steven C. H. Hoi, Pengcheng Wu, Rong Jin
Research Collection School Of Computing and Information Systems
Similarity search is a key challenge for multimedia retrieval applications where data are usually represented in high-dimensional space. Among various algorithms proposed for similarity search in high-dimensional space, Locality-Sensitive Hashing (LSH) is the most popular one, which recently has been extended to Kernelized Locality-Sensitive Hashing (KLSH) by exploiting kernel similarity for better retrieval efficacy. Typically, KLSH works only with a single kernel, which is often limited in real-world multimedia applications, where data may originate from multiple resources or can be represented in several different forms. For example, in content-based multimedia retrieval, a variety of features can be extracted to represent …
Message From General Chair And Program Co-Chairs [Of Icec '12, 14th Annual International Conference On Electronic Commerce, Held In Singapore, 7-8 August 2012], Robert J. Kauffman, Martin Bichler, Hoong Chuin Lau, Christopher Yang, Yinping Yang
Message From General Chair And Program Co-Chairs [Of Icec '12, 14th Annual International Conference On Electronic Commerce, Held In Singapore, 7-8 August 2012], Robert J. Kauffman, Martin Bichler, Hoong Chuin Lau, Christopher Yang, Yinping Yang
Research Collection School Of Computing and Information Systems
Singapore, a major hub in the Asia Pacific region well known for its multi-racial and multicultural society, is proud to host the 14th International Conference on Electronic Commerce. Singapore Management University (SMU), the School of Information Systems (SIS) and the Living Analytics Research Center (LARC) are also delighted to be able to support the delivery of this event.
Sampling And Ontologically Pooling Web Images For Visual Concept Learning, Shiai Zhu, Chong-Wah Ngo, Yu-Gang Jiang
Sampling And Ontologically Pooling Web Images For Visual Concept Learning, Shiai Zhu, Chong-Wah Ngo, Yu-Gang Jiang
Research Collection School Of Computing and Information Systems
Sufficient training examples are essential for effective learning of semantic visual concepts. In practice, however, acquiring noise-free training examples has always been expensive. Recently the rapid popularization of social media websites, such as Flickr, has made it possible to collect training exemplars without human assistance. This paper proposes a novel and efficient approach to collect training samples from the noisily tagged Web images for visual concept learning, where we try to maximize two important criteria, relevancy and coverage, of the automatically generated training sets. For the former, a simple method named semantic field is introduced to handle the imprecise and …
Adapting Video Delivery Based On Motion Triggered Visual Attention, Hari Kalva, V. Adzic, Lai-Tee Cheok
Adapting Video Delivery Based On Motion Triggered Visual Attention, Hari Kalva, V. Adzic, Lai-Tee Cheok
Research Collection School Of Computing and Information Systems
Cues from human visual system (HVS) can be used for further optimization of compression in modern hybrid video coding platforms. We present work that explores and exploits motion related attentional limitations. Algorithms for exploiting motion triggered attention were developed and compared with MPEG AVC/H.264 encoder with various settings for different bitrate levels. For the sequences with high motion activity our algorithm provides up to 8% bitrate savings.
Optimal Estimation Under Nonstandard Conditions, Werner Ploberger, Peter C. B. Phillips
Optimal Estimation Under Nonstandard Conditions, Werner Ploberger, Peter C. B. Phillips
Research Collection School Of Economics
We analyze optimality properties of maximum likelihood (ML) and other estimators when the problem does not necessarily fall within the locally asymptotically normal (LAN) class, therefore covering cases that are excluded from conventional LAN theory such as unit root nonstationary time series. The classical Hajek-Le Cam optimality theory is adapted to cover this situation. We show that the expectation of certain monotone "bowl-shaped" functions of the squared estimation error are minimized by the ML estimator in locally asymptotically quadratic situations, which often occur in nonstationary time series analysis when the LAN property fails. Moreover, we demonstrate a direct connection between …
Online Feature Selection For Mining Big Data, Steven C. H. Hoi, Jialei Wang, Peilin Zhao, Rong Jin
Online Feature Selection For Mining Big Data, Steven C. H. Hoi, Jialei Wang, Peilin Zhao, Rong Jin
Research Collection School Of Computing and Information Systems
Most studies of online learning require accessing all the attributes/features of training instances. Such a classical setting is not always appropriate for real-world applications when data instances are of high dimensionality or the access to it is expensive to acquire the full set of attributes/features. To address this limitation, we investigate the problem of Online Feature Selection (OFS) in which the online learner is only allowed to maintain a classifier involved a small and fixed number of features. The key challenge of Online Feature Selection is how to make accurate prediction using a small and fixed number of active features. …
Measurement-Driven Performance Analysis Of Indoor Femtocellular Networks, Trung-Tuan Luong, Vigneshwaran Subbaraju, Archan Misra, Srinivasan Seshan
Measurement-Driven Performance Analysis Of Indoor Femtocellular Networks, Trung-Tuan Luong, Vigneshwaran Subbaraju, Archan Misra, Srinivasan Seshan
Research Collection School Of Computing and Information Systems
This paper describes initial empirical studies, performed on a 6-node 3G indoor femtocellular testbed, that investigate the impact of pedestrian mobility on network parameters, such as handoff behavior and data throughput. The studies establish that, owing to the small radii of cells, even modest changes in movement speed can have disproportionately large impact on handoff patterns and network throughput. By also revealing a strong temporal dependency effect, the studies motivate the need for algorithms to accurately predict RF signal strength distributions in dynamic indoor environments. We present such an RF prediction algorithm, based on crowd-sourced signal strength readings, and show …
Recent Advances In Nonstationary Time Series: A Festschrift In Honor Of Peter C. B. Phillips, Robert S. Mariano, Zhijie Xiao, Jun Yu
Recent Advances In Nonstationary Time Series: A Festschrift In Honor Of Peter C. B. Phillips, Robert S. Mariano, Zhijie Xiao, Jun Yu
Research Collection School Of Economics
On July 14–15, 2008, the School of Economics and the Sim Kee Boon Institute for Financial Economics at Singapore Management University (SMU) co-hosted a conference honoring the contribution of Peter Phillips to econometrics and statistics, in celebration of his 60th birthday. In total, 51 papers were presented by his colleagues and former students, who deeply appreciate and respect Peter as a true scholar and a good friend. These papers mainly cover two areas of Peter’s current research interests—nonstationary time series analysis, and panel, nonlinear and nonparametric models. On the basis of this conference, we have taken the opportunity to edit …
Mistaken Identity, Identity Theft And Problems Of Remote Authentication In E-Commerce, Eliza Mik
Mistaken Identity, Identity Theft And Problems Of Remote Authentication In E-Commerce, Eliza Mik
Research Collection Yong Pung How School Of Law
The problem of mistaken identity in e-commerce transactions brings together seemingly unrelated issues: privacy, network security, digital signatures – and classic contract law. The technological characteristics of the Internet have a tendency to turn traditional legal doctrines on their head, or, at least expose flaws in existing legal arguments. Combining an academic exercise with the practical implications of the insecurity of the Internet, this paper draws some unexpected conclusions regarding cases of mistaken identity. The latter must be analysed afresh with a number of factors in mind: the more widespread use of fictitious identities in on-line transactions, the higher incidence …
The Case For Cloud-Enabled Mobile Sensing Services, Sougata Sen, Archan Misra, Rajesh Krishna Balan, Lipyeow Lim
The Case For Cloud-Enabled Mobile Sensing Services, Sougata Sen, Archan Misra, Rajesh Krishna Balan, Lipyeow Lim
Research Collection School Of Computing and Information Systems
We make the case for cloud-enabled mobile sensing services that support an emerging application class, one which infers near-real time collective context using sensor data obtained continuously from a large set of consumer mobile devices. We present the high-level architecture and functional requirements for such a mobile sensing service, and argue that such a service can significantly improve the scalability and energy-efficiency of large-scale mobile sensing by coordinating the sensing & processing tasks across multiple devices. We then focus specifically on the problem of energy efficiency and provide early exemplars of how optimizing query execution jointly over multiple phones can …
Uncertain Congestion Games With Assorted Human Agent Populations, Asrar Ahmed, Pradeep Reddy Varakantham, Shih-Fen Cheng
Uncertain Congestion Games With Assorted Human Agent Populations, Asrar Ahmed, Pradeep Reddy Varakantham, Shih-Fen Cheng
Research Collection School Of Computing and Information Systems
Congestion games model a wide variety of real-world resource congestion problems, such as selfish network routing, traffic route guidance in congested areas, taxi fleet optimization and crowd movement in busy areas. However, existing research in congestion games assumes: (a) deterministic movement of agents between resources; and (b) perfect rationality (i.e. maximizing their own expected value) of all agents. Such assumptions are not reasonable in dynamic domains where decision support has to be provided to humans. For instance, in optimizing the performance of a taxi fleet serving a city, movement of taxis can be involuntary or nondeterministic (decided by the specific …
Bidder Behaviors In Repeated B2b Procurement Auctions, Jong Han Park, Jae Kyu Lee, Hoong Chuin Lau
Bidder Behaviors In Repeated B2b Procurement Auctions, Jong Han Park, Jae Kyu Lee, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
B2B auctions play a key role in a firm's procurement process. Even though it is known that repetition is a key characteristic of procurement auctions, traditional auctioneers typically have not put in place a suitable mechanism that supports repetitive auctions effectively. In this paper, we empirically investigate what has taken place in repeated procurement auctions based on real world data from a major outsourcing company of MRO (Maintenance, Repair and Operations) items in Korea. From this empirical study, we discovered the followings. First, we discovered that the repeated bidders contribute majority of all bids, and that the number of new …
A Secure And Efficient Discovery Service System In Epcglobal Network, Jie Shi, Yingjiu Li, Robert H. Deng
A Secure And Efficient Discovery Service System In Epcglobal Network, Jie Shi, Yingjiu Li, Robert H. Deng
Research Collection School Of Computing and Information Systems
In recent years, the Internet of Things (IOT) has drawn considerable attention from the industrial and research communities. Due to the vast amount of data generated through IOT devices and users, there is an urgent need for an effective search engine to help us make sense of this massive amount of data. With this motivation, we begin our initial works on developing a secure and efficient search engine (SecDS) based on EPC Discovery Services (EPCDS) for EPCglobal network, an integral part of IOT. SecDS is designed to provide a bridge between different partners of supply chains to share information while …
Modeling Concept Dynamics For Large Scale Music Search, Jialie Shen, Hwee Hwa Pang, Meng Wang, Shuicheng Yan
Modeling Concept Dynamics For Large Scale Music Search, Jialie Shen, Hwee Hwa Pang, Meng Wang, Shuicheng Yan
Research Collection School Of Computing and Information Systems
Continuing advances in data storage and communication technologies have led to an explosive growth in digital music collections. To cope with their increasing scale, we need effective Music Information Retrieval (MIR) capabilities like tagging, concept search and clustering. Integral to MIR is a framework for modelling music documents and generating discriminative signatures for them. In this paper, we introduce a multimodal, layered learning framework called DMCM. Distinguished from the existing approaches that encode music as an ensemble of order-less feature vectors, our framework extracts from each music document a variety of acoustic features, and translates them into low-level encodings over …
Adaptive Display Power Management For Oled Displays, Kiat Wee Tan, Rajesh Krishna Balan
Adaptive Display Power Management For Oled Displays, Kiat Wee Tan, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Mobile gaming has become increasingly popular in the past few years with the proliferation of smartphones that have the increased CPU, memory, and network (3.5G etc.) capabilities to support a vast range of interesting games. In addition, these phones also have high quality displays, such as Organic Light Emitting Diodes (OLED) displays, that allow the intricate details in games to be shown in vivid detail to end users. Unfortunately, these displays tend to consume a lot of energy which in turn limits the amount of time that a user can spend actually playing games on these devices. In this paper, …
Investment Timing For Mobile Payment Systems, Robert J. Kauffman, Jun Liu, Dan Ma
Investment Timing For Mobile Payment Systems, Robert J. Kauffman, Jun Liu, Dan Ma
Research Collection School Of Computing and Information Systems
The recent launch of Google Wallet has brought the issue of technology solutions in the mobile payment (m-payment) area to the forefront. In deciding whether and when to adopt m-payment technology, senior managers in banks are naturally concerned about uncertainties regarding future market conditions, technology standards, and consumer and merchant responses, especially their willingness to adopt. This study applies economic theory and modeling for decision-making under uncertainty to bank investments in mobile payment technology. We assess the projected benefits and costs of investment as a continuous-time stochastic process to determine optimal investment timing. We find that the value of waiting …
The Pricing Model Of Cloud Computing Services, Jianhui Huang, Dan Ma
The Pricing Model Of Cloud Computing Services, Jianhui Huang, Dan Ma
Research Collection School Of Computing and Information Systems
Cloud computing service providers offer computing resource as a utility and software as a service over network. Many believe that Cloud computing is making an industry-wise paradigm shift for IT use. Besides its technique issues, the business feature of Cloud computing attracts our interests. Specifically the practice of Amazon EC2 introduces an interesting pricing scheme. Amazon provides users with virtual computing instances as a combination of interruptible service (i.e., spot instance) and uninterruptible service (i.e., on-demand and reserved instance). Spot instance is charged at a per use price which is dynamically changing over time; users of spot instance face the …
Valuation Of Benchmark Provisions On It Services Contracts, Robert J. Kauffman, Ryan Sougstad
Valuation Of Benchmark Provisions On It Services Contracts, Robert J. Kauffman, Ryan Sougstad
Research Collection School Of Computing and Information Systems
Information technology (IT) services are often subject to downward price pressures due to improvements in technology and business processes in a competitive market. When clients enter into IT services contracts, they are faced with the future risk that their services will be overpriced relative to the broader IT services market. To mitigate this risk, clients often add benchmark provisions, whereby a neutral third party assesses the prevailing market price for services. It will support fair price adjustments if the market prices are lower than the current prices. We model the decision to benchmark in order to provide managerial information on …
Consumer Micro-Behavior And Tv Viewership Patterns: Data Analytics For The Two-Way Set-Top Box, Ray M. Chang, Robert J. Kauffman, Insoo Son
Consumer Micro-Behavior And Tv Viewership Patterns: Data Analytics For The Two-Way Set-Top Box, Ray M. Chang, Robert J. Kauffman, Insoo Son
Research Collection School Of Computing and Information Systems
Consumer behavior patterns related to home digital media use are changing due to technological innovations. We examine them in the presence of two-way cable television (CATV) settop boxes. They permit viewers to change channels, switch to the Internet, and order paid programming, among other functions. We focus on micro-level data that are generated from consumer CATV viewing behavior. We capture clickstreams of channel-changing behavior when consumer use a remote control handset to interact with the set-top box in their home. We explore a variety of data analytics results that characterize patterns of consumer channel-switching behavior, as a basis for suggesting …
Shortest Path Computation With No Information Leakage, Kyriakos Mouratidis, Man Lung Yiu
Shortest Path Computation With No Information Leakage, Kyriakos Mouratidis, Man Lung Yiu
Research Collection School Of Computing and Information Systems
Shortest path computation is one of the most common queries in location-based services (LBSs). Although particularly useful, such queries raise serious privacy concerns. Exposing to a (potentially untrusted) LBS the client’s position and her destination may reveal personal information, such as social habits, health condition, shopping preferences, lifestyle choices, etc. The only existing method for privacy-preserving shortest path computation follows the obfuscation paradigm; it prevents the LBS from inferring the source and destination of the query with a probability higher than a threshold. This implies, however, that the LBS still deduces some information (albeit not exact) about the client’s location …
Toward Large-Scale Agent Guidance In An Urban Taxi Service, Agussurja Lucas, Hoong Chuin Lau
Toward Large-Scale Agent Guidance In An Urban Taxi Service, Agussurja Lucas, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Empty taxi cruising represents a wastage of resources in the context of urban taxi services. In this work, we seek to minimize such wastage. An analysis of a large trace of taxi operations reveals that the services’ inefficiency is caused by drivers’ greedy cruising behavior. We model the existing system as a continuous time Markov chain. To address the problem, we propose that each taxi be equipped with an intelligent agent that will guide the driver when cruising for passengers. Then, drawing from AI literature on multiagent planning, we explore two possible ways to compute such guidance. The first formulation …
From Clickstreams To Searchstreams: Search Network Graph Evidence From A B2b E-Market, Mei Lin, M. F. Lin, Robert J. Kauffman
From Clickstreams To Searchstreams: Search Network Graph Evidence From A B2b E-Market, Mei Lin, M. F. Lin, Robert J. Kauffman
Research Collection School Of Computing and Information Systems
Consumers in e-commerce acquire information through search engines, yet to date there has been little empirical study on how users interact with the results produced by search engines. This is analogous to, but different from, the ever-expanding research on clickstreams, where users interact with static web pages. We propose a new network approach to analyzing search engine server log data. We call this searchstream data. We create graph representations based on the web pages that users traverse as they explore the search results that their use of search engines generates. We then analyze the graph-level properties of these search network …
Hedonic Valuation Of Online Game Participation, Robert J. Kauffman, Kwansoo Kim, Byungjoon Yoo
Hedonic Valuation Of Online Game Participation, Robert J. Kauffman, Kwansoo Kim, Byungjoon Yoo
Research Collection School Of Computing and Information Systems
We use hedonic valuation to establish a basis for valuing the time a user participates in an online gaming community. We distinguish between utilitarian and hedonic value. Our application involves elements of both utilitarian and hedonic value, however, the latter is much more important. We use an extensive data set involving a massive multi-player online role-playing game (MMORPG) from Korea. We specify and test econometric models that reflect the appropriate empirical structure for the setting, based on information about the players and the activities they engage in. The results permit us to estimate the hedonic value in monetary terms for …
Toward A Mobile Platform For Pervasive Games, Inseok Hwang, Youngki Lee, Taiwoo Park, Junehwa Song
Toward A Mobile Platform For Pervasive Games, Inseok Hwang, Youngki Lee, Taiwoo Park, Junehwa Song
Research Collection School Of Computing and Information Systems
Emerging pervasive games will be immersed into real-life situations and leverage new types of contextual interactions therein. For instance, a player’s punching gesture, running activity, and fast heart rate conditions can be used as the game inputs. Although the contextual interaction is the core building blocks of pervasive games, individual game developers hardly utilize a rich set of interactions within a game play. Most challenging, it is significantly difficult for developers to expect dynamic availability of input devices in real life, and adapt to the situation without system-level support. Also, it is challenging to coordinate its resource use with other …