Open Access. Powered by Scholars. Published by Universities.®

Digital Commons Network™

Open Access. Powered by Scholars. Published by Universities.®

Singapore Management University

Discipline
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 8371 - 8400 of 10509

Full-Text Articles in Entire DC Network

Learning Feature Dependencies For Noise Correction In Biomedical Prediction, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang Apr 2011

Learning Feature Dependencies For Noise Correction In Biomedical Prediction, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

The presence of noise or errors in the stated feature values of biomedical data can lead to incorrect prediction. We introduce a Bayesian Network-based Noise Correction framework named BN-NC. After data preprocessing, a Bayesian Network (BN) is learned to capture the feature dependencies. Using the BN to predict each feature in turn, BN-NC estimates a feature's error rate as the deviation between its predicted and stated values in the training data, and allocates the appropriate uncertainty to its subsequent findings during prediction. BN-NC automatically generates a probabilistic rule to explain BN prediction on the class variable using the feature values …

Go to article

Mkboost: A Framework Of Multiple Kernel Boosting, Hao Xia, Steven C. H. Hoi Apr 2011

Mkboost: A Framework Of Multiple Kernel Boosting, Hao Xia, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Multiple kernel learning (MKL) has been shown as a promising machine learning technique for data mining tasks by integrating with multiple diverse kernel functions. Traditional MKL methods often formulate the problem as an optimization task of learning both optimal combination of kernels and classifiers, and attempt to resolve the challenging optimization task by various techniques. Unlike the existing MKL methods, in this paper, we investigate a boosting framework of exploring multiple kernel learning for classification tasks. In particular, we present a novel framework of Multiple Kernel Boosting (MKBoost), which applies boosting techniques for learning kernel-based classifiers with multiple kernels. Based …

Go to article

A Family Of Simple Non-Parametric Kernel Learning Algorithms From Pairwise Constraints, Jinfeng Zhuang, Ivor W. Tsang, Steven C. H. Hoi Apr 2011

A Family Of Simple Non-Parametric Kernel Learning Algorithms From Pairwise Constraints, Jinfeng Zhuang, Ivor W. Tsang, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Previous studies of Non-Parametric Kernel Learning (NPKL) usually formulate the learning task as a Semi-Definite Programming (SDP) problem that is often solved by some general purpose SDP solvers. However, for N data examples, the time complexity of NPKL using a standard interior-point SDP solver could be as high as O(N6.5), which prohibits NPKL methods applicable to real applications, even for data sets of moderate size. In this paper, we present a family of efficient NPKL algorithms, termed "SimpleNPKL", which can learn non-parametric kernels from a large set of pairwise constraints efficiently. In particular, we propose two efficient SimpleNPKL algorithms. One …

Go to article

Predicting Item Adoption Using Social Correlation, Freddy Chong-Tat Chua, Hady W. Lauw, Ee Peng Lim Apr 2011

Predicting Item Adoption Using Social Correlation, Freddy Chong-Tat Chua, Hady W. Lauw, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Users face a dazzling array of choices on the Web when it comes to choosing which product to buy, which video to watch, etc. The trend of social information processing means users increasingly rely not only on their own preferences, but also on friends when making various adoption decisions. In this paper, we investigate the effects of social correlation on users’ adoption of items. Given a user-user social graph and an item-user adoption graph, we seek to answer the following questions: 1) whether the items adopted by a user correlate to items adopted by her friends, and 2) how to …

Go to article

Heterogeneous Signcryption With Key Privacy, Qiong Huang, Duncan S. Wong, Guomin Yang Apr 2011

Heterogeneous Signcryption With Key Privacy, Qiong Huang, Duncan S. Wong, Guomin Yang

Research Collection School Of Computing and Information Systems

A signcryption scheme allows a sender to produce a ciphertext for a receiver so that both confidentiality and non-repudiation can be ensured. It is built to be more efficient and secure, for example, supporting insider security, when compared with the conventional sign-then-encrypt approach. In this paper, we propose a new notion called heterogeneous signcryption in which the sender has an identity-based secret key while the receiver is holding a certificate-based public key pair. Heterogeneous signcryption is suitable for practical scenarios where an identity-based user, who does not have a personal certificate or a public key, wants to communicate securely with …

Go to article

Weight-Based Boosting Model For Cross-Domain Relevance Ranking Adaptation, Peng Cai, Wei Gao, Kam-Fai Wong, Aoying Zhou Apr 2011

Weight-Based Boosting Model For Cross-Domain Relevance Ranking Adaptation, Peng Cai, Wei Gao, Kam-Fai Wong, Aoying Zhou

Research Collection School Of Computing and Information Systems

Adaptation techniques based on importance weighting were shown effective for RankSVM and RankNet, viz., each training instance is assigned a target weight denoting its importance to the target domain and incorporated into loss functions. In this work, we extend RankBoost using importance weighting framework for ranking adaptation. We find it non-trivial to incorporate the target weight into the boosting-based ranking algorithms because it plays a contradictory role against the innate weight of boosting, namely source weight that focuses on adjusting source-domain ranking accuracy. Our experiments show that among three variants, the additive weight-based RankBoost, which dynamically balances the two types …

Go to article

Corn: Correlation-Driven Nonparametric Learning Approach For Portfolio Selection, Bin Li, Steven C. H. Hoi, Vivekanand Gopalkrishnan Apr 2011

Corn: Correlation-Driven Nonparametric Learning Approach For Portfolio Selection, Bin Li, Steven C. H. Hoi, Vivekanand Gopalkrishnan

Research Collection School Of Computing and Information Systems

Machine learning techniques have been adopted to select portfolios from financial markets in some emerging intelligent business applications. In this article, we propose a novel learning-to-trade algorithm termed CO Relation-driven Nonparametric learning strategy (CORN) for actively trading stocks. CORN effectively exploits statistical relations between stock market windows via a nonparametric learning approach. We evaluate the empirical performance of our algorithm extensively on several large historical and latest real stock markets, and show that it can easily beat both the market index and the best stock in the market substantially (without or with small transaction costs), and also surpass a variety …

Go to article

Confidence Weighted Mean Reversion Strategy For On-Line Portfolio Selection, Bin Li, Steven C. H. Hoi, Peilin Zhao, Vivek Gopalkrishnan Apr 2011

Confidence Weighted Mean Reversion Strategy For On-Line Portfolio Selection, Bin Li, Steven C. H. Hoi, Peilin Zhao, Vivek Gopalkrishnan

Research Collection School Of Computing and Information Systems

On-line portfolio selection has been attracting increasing attention from the data mining and machine learning communities. All existing on-line portfolio selection strategies focus on the first order information of a portfolio vector, though the second order information may also be beneficial to a strategy. Moreover, empirical evidences show that the stock price relatives may follow the mean reversion property, which has not been fully exploited by existing strategies. This article proposes a novel on-line portfolio selection strategy named ``Confidence Weighted Mean Reversion'' (CWMR). Inspired by the mean reversion principle in finance and confidence weighted online learning technique in machine learning, …

Go to article

Two-Layer Multiple Kernel Learning, Jinfeng Zhuang, Ivor W. Tsang, Steven C. H. Hoi Apr 2011

Two-Layer Multiple Kernel Learning, Jinfeng Zhuang, Ivor W. Tsang, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Multiple Kernel Learning (MKL) aims to learn kernel machines for solving a real machine learning problem (e.g. classification) by exploring the combinations of multiple kernels. The traditional MKL approach is in general “shallow” in the sense that the target kernel is simply a linear (or convex) combination of some base kernels. In this paper, we investigate a framework of Multi-Layer Multiple Kernel Learning (MLMKL) that aims to learn “deep” kernel machines by exploring the combinations of multiple kernels in a multi-layer structure, which goes beyond the conventional MKL approach. Through a multiple layer mapping, the proposed MLMKL framework offers higher …

Go to article

Asymptotic Theory For Zero Energy Functionals With Nonparametric Regression Applications, Qiying Wang, Peter C. B. Phillips Apr 2011

Asymptotic Theory For Zero Energy Functionals With Nonparametric Regression Applications, Qiying Wang, Peter C. B. Phillips

Research Collection School Of Economics

A local limit theorem is given for the sample mean of a zero energy function of a nonstationary time series involving twin numerical sequences that pass to infinity. The result is applicable in certain nonparametric kernel density estimation and regression problems where the relevant quantities are functions of both sample size and bandwidth. An interesting outcome of the theory in nonparametric regression is that the linear term is eliminated from the asymptotic bias. In consequence and in contrast to the stationary case, the Nadaraya-Watson estimator has the same limit distribution (to the second order including bias) as the local linear …

Go to article

Efficient Topological Olap On Information Networks, Qiang Qu, Feida Zhu, Xifeng Yan, Jiawei Han, Philip Yu, Hongyan Li Apr 2011

Efficient Topological Olap On Information Networks, Qiang Qu, Feida Zhu, Xifeng Yan, Jiawei Han, Philip Yu, Hongyan Li

Research Collection School Of Computing and Information Systems

We propose a framework for efficient OLAP on information networks with a focus on the most interesting kind, the topological OLAP (called “T-OLAP”), which incurs topological changes in the underlying networks. T-OLAP operations generate new networks from the original ones by rolling up a subset of nodes chosen by certain constraint criteria. The key challenge is to efficiently compute measures for the newly generated networks and handle user queries with varied constraints. Two effective computational techniques, T-Distributiveness and T-Monotonicity are proposed to achieve efficient query processing and cube materialization. We also provide a T-OLAP query processing framework into which these …

Go to article

Comparing Twitter And Traditional Media Using Topic Models, Wayne Xin Zhao, Jing Jiang, Jianshu Weng, Jing He, Ee Peng Lim, Hongfei Yan, Xiaoming Li Apr 2011

Comparing Twitter And Traditional Media Using Topic Models, Wayne Xin Zhao, Jing Jiang, Jianshu Weng, Jing He, Ee Peng Lim, Hongfei Yan, Xiaoming Li

Research Collection School Of Computing and Information Systems

Twitter as a new form of social media can potentially contain much useful information, but content analysis on Twitter has not been well studied. In particular, it is not clear whether as an information source Twitter can be simply regarded as a faster news feed that covers mostly the same information as traditional news media. In This paper we empirically compare the content of Twitter with a traditional news medium, New York Times, using unsupervised topic modeling. We use a Twitter-LDA model to discover topics from a representative sample of the entire Twitter. We then use text mining techniques to …

Go to article

Fusing Heterogeneous Modalities For Video And Image Re-Ranking, Hung-Khoon Tan, Chong-Wah Ngo Apr 2011

Fusing Heterogeneous Modalities For Video And Image Re-Ranking, Hung-Khoon Tan, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Multimedia documents in popular image and video sharing websites such as Flickr and Youtube are heterogeneous documents with diverse ways of representations and rich user-supplied information. In this paper, we investigate how the agreement among heterogeneous modalities can be exploited to guide data fusion. The problem of fusion is cast as the simultaneous mining of agreement from different modalities and adaptation of fusion weights to construct a fused graph from these modalities. An iterative framework based on agreement-fusion optimization is thus proposed. We plug in two well-known algorithms: random walk and semi-supervised learning to this framework to illustrate the idea …

Go to article

Ir-Tree: An Efficient Index For Geographic Document Search, Zhisheng Li, Ken C. K. Lee, Baihua Zheng, Wang-Chien Lee, Dik Lun Lee, Xufa Wang Apr 2011

Ir-Tree: An Efficient Index For Geographic Document Search, Zhisheng Li, Ken C. K. Lee, Baihua Zheng, Wang-Chien Lee, Dik Lun Lee, Xufa Wang

Research Collection School Of Computing and Information Systems

Given a geographic query that is composed of query keywords and a location, a geographic search engine retrieves documents that are the most textually and spatially relevant to the query keywords and the location, respectively, and ranks the retrieved documents according to their joint textual and spatial relevances to the query. The lack of an efficient index that can simultaneously handle both the textual and spatial aspects of the documents makes existing geographic search engines inefficient in answering geographic queries. In this paper, we propose an efficient index, called IR-tree, that together with a top-k document search algorithm facilitates four …

Go to article

A High-Throughput Routing Metric For Reliable Multicast In Multi-Rate Wireless Mesh Networks, Xin Zhao, Jun Guo, Chun Tung Chou, Archan Misra, Sanjay Jha Apr 2011

A High-Throughput Routing Metric For Reliable Multicast In Multi-Rate Wireless Mesh Networks, Xin Zhao, Jun Guo, Chun Tung Chou, Archan Misra, Sanjay Jha

Research Collection School Of Computing and Information Systems

We propose a routing metric for enabling highthroughput reliable multicast in multi-rate wireless mesh networks. This new multicast routing metric, called expected multicast transmission time (EMTT), captures the combined effects of 1) MAC-layer retransmission-based reliability, 2) transmission rate diversity, 3) wireless broadcast advantage, and 4) link quality awareness. The EMTT of one-hop transmission of a multicast packet minimizes the amount of expected transmission time (including that required for retransmissions). This is achieved by allowing the sender to adapt its bit-rate for each ongoing transmission/retransmission, optimized exclusively for its nexthop receivers that have not yet received the multicast packet. We model …

Go to article

Utility-Oriented K-Anonymization On Social Networks, Yazhe Wang, Long Xie, Baihua Zheng, Ken C. K. Lee Apr 2011

Utility-Oriented K-Anonymization On Social Networks, Yazhe Wang, Long Xie, Baihua Zheng, Ken C. K. Lee

Research Collection School Of Computing and Information Systems

"Identity disclosure" problem on publishing social network data has gained intensive focus from academia. Existing k-anonymization algorithms on social network may result in nontrivial utility loss. The reason is that the number of the edges modified when anonymizing the social network is the only metric to evaluate utility loss, not considering the fact that different edge modifications have different impact on the network structure. To tackle this issue, we propose a novel utility-oriented social network anonymization scheme to achieve privacy protection with relatively low utility loss. First, a proper utility evaluation model is proposed. It focuses on the changes on …

Go to article

Peercast: Improving Link Layer Multicast Through Cooperative Relaying, Jie Xiong, Romit Roy Choudhury Apr 2011

Peercast: Improving Link Layer Multicast Through Cooperative Relaying, Jie Xiong, Romit Roy Choudhury

Research Collection School Of Computing and Information Systems

Wireless multicast applications, such as MobiTV, web telecast, and multimedia classrooms, are gaining rapid popularity. The broadcast nature of the wireless channel is amenable to such multicasts because a single packet transmission can be received by all clients. Unfortunately, the rate of this transmission is bottlenecked by data rate of the weakest client, degrading system performance. Attempts to increase the data rate results in lower reliability and higher unfairness. This paper presents PeerCast, a wireless multicast protocol that engages clients in cooperative relaying. The main idea is simple. Instead of multicasting at the bottleneck rate, the access point transmits at …

Go to article

Abstracting Events For Data Mining, David Lo, Ganesan Ramalingam, Venkatesh-Prasad Ranganath, Kapil Vaswani Apr 2011

Abstracting Events For Data Mining, David Lo, Ganesan Ramalingam, Venkatesh-Prasad Ranganath, Kapil Vaswani

Research Collection School Of Computing and Information Systems

An event is described herein as being representable by a quantified abstraction of the event. The event includes at least one predicate, and the at least one predicate has at least one constant symbol corresponding thereto. An instance of the constant symbol corresponding to the event is identified, and the instance of the constant symbol is replaced by a free variable to obtain an abstracted predicate. Thus, a quantified abstraction of the event is composed as a pair: the abstracted predicate and a mapping between the free variable and an instance of the constant symbol that corresponds to the predicate. …

Go to article

Accounting Information Systems Research Over The Past Decade: Past And Future Trends, Colin Ferguson, Poh Sun Seow Mar 2011

Accounting Information Systems Research Over The Past Decade: Past And Future Trends, Colin Ferguson, Poh Sun Seow

Research Collection School Of Accountancy

This article reviews the extant accounting information systems (AIS) literature by conducting an analysis of AIS articles published in 18 leading accounting, management information systems, and computer science journals from 1999 to 2009 with a view to identifying whether or not the focus of AIS research has changed, and if so how it has changed, since the Poston and Grabski’s (2000) review of AIS research from 1982 to 1998. We also report our insights into where AIS research is likely to be heading in the future. We analyse each of the 395 articles identified as reporting AIS research to identify …

Go to article

A Virtualization-Based Approach For Zone Migration In Distributed Virtual Environments, Nguyen Binh Duong Ta, Thang Nguyen, Tran Nguyen, Do Nguyen, Xueyan Tang, Wentong Cai, Suiping Zhou Mar 2011

A Virtualization-Based Approach For Zone Migration In Distributed Virtual Environments, Nguyen Binh Duong Ta, Thang Nguyen, Tran Nguyen, Do Nguyen, Xueyan Tang, Wentong Cai, Suiping Zhou

Research Collection School Of Computing and Information Systems

This paper deals with the zone migration problem in large-scale distributed virtual environments (DVEs), e.g., massively multi-player online games, distributed military simulations, etc. To support real-time interactions among thousands of concurrent, geographically separated clients, a distributed server architecture is generally needed. In such architecture, the large virtual world can be partitioned into multiple smaller zones, enabling load distributions or zone-to-server mappings to improve interactivity. For example, a zone might be mapped (assigned) to a server location near most of its clients to reduce network latency. In this paper, we consider the problem of live zone migration over wide area networks …

Go to article

Strongly Secure Certificateless Key Exchange Without Pairing, Guomin Yang, Chik How Tan Mar 2011

Strongly Secure Certificateless Key Exchange Without Pairing, Guomin Yang, Chik How Tan

Research Collection School Of Computing and Information Systems

In certificateless cryptography, a user secret key is derived from two partial secrets: one is the identity-based secret key (corresponding to the user identity) generated by a Key Generation Center (KGC), and the other is the user selfgenerated secret key (corresponding to a user self-generated and uncertified public key). Two types of adversaries are considered for certificateless cryptography: a Type-I adversary who can replace the user self-generated public key (in transmission or in a public directory), and a Type-II adversary who is an honest-but-curious KGC. In this paper, we present a formal study on certificateless key exchange (CLKE). We show …

Go to article

Multi-Objective Zone Mapping In Large-Scale Distributed Virtual Environments, Nguyen Binh Duong Ta, Suiping Zhou, Wentong Cai, Xueyan Tang, Rassul Avani Mar 2011

Multi-Objective Zone Mapping In Large-Scale Distributed Virtual Environments, Nguyen Binh Duong Ta, Suiping Zhou, Wentong Cai, Xueyan Tang, Rassul Avani

Research Collection School Of Computing and Information Systems

In large-scale distributed virtual environments (DVEs), the NP-hard zone mapping problem concerns how to assign distinct zones of the virtual world to a number of distributed servers to improve overall interactivity. Previously, this problem has been formulated as a single-objective optimization problem, in which the objective is to minimize the total number of clients that are without QoS. This approach may cause considerable network traffic and processing overhead, as a large number of zones may need to be migrated across servers. In this paper, we introduce a multi-objective approach to the zone mapping problem, in which both the total number …

Go to article

Longitudinal Assessment Of Changes In Job Performance And Work Attitudes: Conceptual And Methodological Issues, David Chan Mar 2011

Longitudinal Assessment Of Changes In Job Performance And Work Attitudes: Conceptual And Methodological Issues, David Chan

Research Collection School of Social Sciences

No abstract provided.

Go to article

How Information Management Capability Influences Firm Performance, Sunil Mithas, Narayan Ramasubbu, V. Sambamurthy Mar 2011

How Information Management Capability Influences Firm Performance, Sunil Mithas, Narayan Ramasubbu, V. Sambamurthy

Research Collection School Of Computing and Information Systems

How do information technology capabilities contribute to firm performance? This study develops a conceptual model linking IT-enabled information management capability with three important organizational capabilities (customer management capability, process management capability, and performance management capability). We argue that these three capabilities mediate the relationship between information management capability and firm performance. To test our conceptual model, we use a rare archival data set that contains actual scores from multidimensional and high-quality assessments of firms and intraorganizational units of a conglomerate business group that had adopted a model of performance excellence for organizational transformation based on the Baldrige criteria. This research …

Go to article

Chameleon All-But-One Tdfs And Their Application To Chosen-Ciphertext Security, Junzuo Lai, Robert H. Deng, Shengli Liu Mar 2011

Chameleon All-But-One Tdfs And Their Application To Chosen-Ciphertext Security, Junzuo Lai, Robert H. Deng, Shengli Liu

Research Collection School Of Computing and Information Systems

In STOC’08, Peikert and Waters introduced a new powerful primitive called lossy trapdoor functions (LTDFs) and a richer abstraction called all-but-one trapdoor functions (ABO-TDFs). They also presented a black-box construction of CCA-secure PKE from an LTDF and an ABO-TDF. An important component of their construction is the use of a strongly unforgeable one-time signature scheme for CCA-security.In this paper, we introduce the notion of chameleon ABO-TDFs, which is a special kind of ABO-TDFs. We give a generic as well as a concrete construction of chameleon ABO-TDFs. Based on an LTDF and a chameleon ABO-TDF, we presented a black-box construction, free …

Go to article

Modeling Link Formation Behaviors In Dynamic Social Networks, Viet-An Nguyen, Cane Wing-Ki Leung, Ee Peng Lim Mar 2011

Modeling Link Formation Behaviors In Dynamic Social Networks, Viet-An Nguyen, Cane Wing-Ki Leung, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Online social networks are dynamic in nature. While links between users are seemingly formed and removed randomly, there exists some interested link formation behaviors demonstrated by users performing link creation and removal activities. Uncovering these behaviors not only allows us to gain deep insights of the users, but also pave the way to decipher how social links are formed. In this paper, we propose a general framework to define user link formation behaviors using well studied local link structures (i.e., triads and dyads) in a dynamic social network where links are formed at different timestamps. Depending on the role a …

Go to article

Authenticated Key Exchange Under Bad Randomness, Guomin Yang, Shanshan Duan, Duncan S. Wong, Chik How Tan, Huaxiong Wang Mar 2011

Authenticated Key Exchange Under Bad Randomness, Guomin Yang, Shanshan Duan, Duncan S. Wong, Chik How Tan, Huaxiong Wang

Research Collection School Of Computing and Information Systems

We initiate the formal study on authenticated key exchange (AKE) under bad randomness. This could happen when (1) an adversary compromises the randomness source and hence directly controls the randomness of each AKE session; and (2) the randomness repeats in different AKE sessions due to reset attacks. We construct two formal security models, Reset-1 and Reset-2, to capture these two bad randomness situations respectively, and investigate the security of some widely used AKE protocols in these models by showing that they become insecure when the adversary is able to manipulate the randomness. On the positive side, we propose simple but …

Go to article

Certificateless Public Key Encryption: A New Generic Construction And Two Pairing-Free Schemes, Guomin Yang, Chik How Tan Mar 2011

Certificateless Public Key Encryption: A New Generic Construction And Two Pairing-Free Schemes, Guomin Yang, Chik How Tan

Research Collection School Of Computing and Information Systems

The certificateless encryption (CLE) scheme proposed by Baek, Safavi-Naini and Susilo is computation-friendly since it does not require any pairing operation. Unfortunately, an error was later discovered in their security proof and so far the provable security of the scheme remains unknown. Recently, Fiore, Gennaro and Smart showed a generic way (referred to as the FGS transformation) to transform identity-based key agreement protocols to certificateless key encapsulation mechanisms (CL-KEMs). As a typical example, they showed that the pairing-free CL-KEM underlying Baek et al.’s CLE can be “generated” by applying their transformation to the Fiore–Gennaro (FG) identity-based key agreement (IB-KA) protocol.In …

Go to article

Secure Mobile Subscription Of Sensor-Encrypted Data, Cheng-Kang Chu, Wen-Tao Zhu, Sherman S. M. Chow, Jianying Zhou, Robert H. Deng Mar 2011

Secure Mobile Subscription Of Sensor-Encrypted Data, Cheng-Kang Chu, Wen-Tao Zhu, Sherman S. M. Chow, Jianying Zhou, Robert H. Deng

Research Collection School Of Computing and Information Systems

In an end-to-end encryption model for a wireless sensor network (WSN), the network control center preloads encryption and decryption keys to the sensor nodes and the subscribers respectively, such that a subscriber can use a mobile device in the deployment field to decrypt the sensed data encrypted by the more resource-constrained sensor nodes. This paper proposes SMS-SED, a provably secure yet practically efficient key assignment system featuring a discrete time-based access control, to better support a business model where the sensors deployer rents the WSN to customers who desires a higher flexibility beyond subscribing to strictly consecutive periods. In SMS-SED, …

Go to article

An Energy Efficient Quality Adaptive Multi-Modal Sensor Framework For Context Recognition, Nirmalya Roy, Archan Misra, Christine Julien, Sajal K. Das, Jit Biswas Mar 2011

An Energy Efficient Quality Adaptive Multi-Modal Sensor Framework For Context Recognition, Nirmalya Roy, Archan Misra, Christine Julien, Sajal K. Das, Jit Biswas

Research Collection School Of Computing and Information Systems

Proliferation of mobile applications in unpredictable and changing environments requires applications to sense and act on changing operational contexts. In such environments, understanding the context of an entity is essential for adaptability of the application behavior to changing situations. In our view, context is a high-level representation of a user or entity’s state and can capture activities, relationships, capabilities, etc. Inherently, however, these high-level context measures are difficult to sense directly and instead must be inferred through the combination of many data sources. In pervasive computing environments where this context is of significant importance, a multitude of sensors is already …

Go to article

First Prev Next Last