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Research Collection School Of Computing and Information Systems

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Articles 5671 - 5700 of 6891

Full-Text Articles in Physical Sciences and Mathematics

User Interfaces For Visual Analysis And Monitoring In Business Intelligence, Lars Grammel, Margaret-Anne Storey, Christoph Treude Nov 2009

User Interfaces For Visual Analysis And Monitoring In Business Intelligence, Lars Grammel, Margaret-Anne Storey, Christoph Treude

Research Collection School Of Computing and Information Systems

Business intelligence is concerned with understanding and leveraging the vast amounts of information stored in the databases of modern enterprises. Visualization techniques have been used to make sense of this data for a long time, first in the form of simple charts, and nowadays in the form of interactive visualizations. By leveraging the strengths of the human perceptual system and incorporating user interaction, they support the flexible analysis of data as well as data monitoring by users. The recent progress in the fields of information and data visualization as well as new hardware developments and trends in business intelligence have …

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Mining Hierarchical Scenario-Based Specifications, David Lo, Shahar Maoz Nov 2009

Mining Hierarchical Scenario-Based Specifications, David Lo, Shahar Maoz

Research Collection School Of Computing and Information Systems

Scalability over long traces, as well as comprehensibility and expressivity of results, are major challenges for dynamic analysis approaches to specification mining. In this work we present a novel use of object hierarchies over traces of inter-object method calls, as an abstraction/refinement mechanism that enables user-guided, top-down or bottom-up mining of layered scenario-based specifications, broken down by hierarchies embedded in the system under investigation. We do this using data mining methods that provide statistically significant sound and complete results modulo user-defined thresholds, in the context of Damm and Harel’s live sequence charts (LSC); a visual, modal, scenario-based, inter-object language. Thus, …

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What Makes Categories Difficult To Classify?, Aixin Sun, Ee Peng Lim, Ying Liu Nov 2009

What Makes Categories Difficult To Classify?, Aixin Sun, Ee Peng Lim, Ying Liu

Research Collection School Of Computing and Information Systems

In this paper, we try to predict which category will be less accurately classified compared with other categories in a classification task that involves multiple categories. The categories with poor predicted performance will be identified before any classifiers are trained and additional steps can be taken to address the predicted poor accuracies of these categories. Inspired by the work on query performance prediction in ad-hoc retrieval, we propose to predict classification performance using two measures, namely, category size and category coherence. Our experiments on 20-Newsgroup and Reuters-21578 datasets show that the Spearman rank correlation coefficient between the predicted rank of …

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Trust Relationship Prediction Using Online Product Review Data, Nan Ma, Ee Peng Lim, Viet-An Nguyen, Aixin Sun Nov 2009

Trust Relationship Prediction Using Online Product Review Data, Nan Ma, Ee Peng Lim, Viet-An Nguyen, Aixin Sun

Research Collection School Of Computing and Information Systems

Trust between users is an important piece of knowledge that can be exploited in search and recommendation.Given that user-supplied trust relationships are usually very sparse, we study the prediction of trust relationships using user interaction features in an online user generated review application context. We show that trust relationship prediction can achieve better accuracy when one adopts personalized and cluster-based classification methods. The former trains one classifier for each user using user-specific training data. The cluster-based method first constructs user clusters before training one classifier for each user cluster. Our proposed methods have been evaluated in a series of experiments …

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A Service Choice Model For Optimizing Taxi Service Delivery, Shih-Fen Cheng, Xin Qu Oct 2009

A Service Choice Model For Optimizing Taxi Service Delivery, Shih-Fen Cheng, Xin Qu

Research Collection School Of Computing and Information Systems

Taxi service has undergone radical revamp in recent years. In particular, significant investments in communication system and GPS devices have improved quality of taxi services through better dispatches. In this paper, we propose to leverage on such infrastructure and build a service choice model that helps individual drivers in deciding whether to serve a specific taxi stand or not. We demonstrate the value of our model by applying it to a real-world scenario. We also highlight interesting new potential approaches that could significantly improve the quality of taxi services.

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Parallel Sets In The Real World: Three Case Studies, Robert Kosara, Caroline Ziemkiewicz, F. Joseph Iii Mako, Tin Seong Kam Oct 2009

Parallel Sets In The Real World: Three Case Studies, Robert Kosara, Caroline Ziemkiewicz, F. Joseph Iii Mako, Tin Seong Kam

Research Collection School Of Computing and Information Systems

Parallel Sets are a visualization technique for categorical data. We recently released an implementation to the public in an effort to make our research useful to real users. This paper presents three case studies of Parallel Sets in use with real data.

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Mining Globally Distributed Frequent Subgraphs In A Single Labeled Graph, Xing Jiang, Hui Xiong, Chen Wang, Ah-Hwee Tan Oct 2009

Mining Globally Distributed Frequent Subgraphs In A Single Labeled Graph, Xing Jiang, Hui Xiong, Chen Wang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Recent years have observed increasing efforts on graph mining and many algorithms have been developed for this purpose. However, most of the existing algorithms are designed for discovering frequent subgraphs in a set of labeled graphs only. Also, the few algorithms that find frequent subgraphs in a single labeled graph typically identify subgraphs appearing regionally in the input graph. In contrast, for real-world applications, it is commonly required that the identified frequent subgraphs in a single labeled graph should also be globally distributed. This paper thus fills this crucial void by proposing a new measure, termed G-Measure, to find globally …

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Domain Adaptive Semantic Diffusion For Large Scale Context-Based Video Annotation, Yu-Gang Jiang, Jun Wang, Shih-Fu Chang, Chong-Wah Ngo Oct 2009

Domain Adaptive Semantic Diffusion For Large Scale Context-Based Video Annotation, Yu-Gang Jiang, Jun Wang, Shih-Fu Chang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Learning to cope with domain change has been known as a challenging problem in many real-world applications. This paper proposes a novel and efficient approach, named domain adaptive semantic diffusion (DASD), to exploit semantic context while considering the domain-shift-of-context for large scale video concept annotation. Starting with a large set of concept detectors, the proposed DASD refines the initial annotation results using graph diffusion technique, which preserves the consistency and smoothness of the annotation over a semantic graph. Different from the existing graph learning methods which capture relations among data samples, the semantic graph treats concepts as nodes and the …

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Analyzing The Video Popularity Characteristics Of Large-Scale User Generated Content Systems, Meeyoung Cha, Haewoon Kwak, Pablo Rodriguez, Yong-Yeol Ahn, Sue Moon Oct 2009

Analyzing The Video Popularity Characteristics Of Large-Scale User Generated Content Systems, Meeyoung Cha, Haewoon Kwak, Pablo Rodriguez, Yong-Yeol Ahn, Sue Moon

Research Collection School Of Computing and Information Systems

User generated content (UGC), now with millions of video producers and consumers, is re-shaping the way people watch video and TV. In particular, UGC sites are creating new viewing patterns and social interactions, empowering users to be more creative, and generating new business opportunities. Compared to traditional video-on-demand (VoD) systems, UGC services allow users to request videos from a potentially unlimited selection in an asynchronous fashion. To better understand the impact of UGC services, we have analyzed the world's largest UGC VoD system, YouTube, and a popular similar system in Korea, Daum Videos. In this paper, we first empirically show …

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Unsupervised Face Alignment By Robust Nonrigid Mapping, Jianke Zhu, Luc Van Gool, Steven C. H. Hoi Oct 2009

Unsupervised Face Alignment By Robust Nonrigid Mapping, Jianke Zhu, Luc Van Gool, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

We propose a novel approach to unsupervised facial image alignment. Differently from previous approaches, that are confined to affine transformations on either the entire face or separate patches, we extract a nonrigid mapping between facial images. Based on a regularized face model, we frame unsupervised face alignment into the Lucas-Kanade image registration approach. We propose a robust optimization scheme to handle appearance variations. The method is fully automatic and can cope with pose variations and expressions, all in an unsupervised manner. Experiments on a large set of images showed that the approach is effective.

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Sharing Mobile Multimedia Annotations To Support Inquiry-Based Learning Using Mobitop, Khasfariyati Razikin, Dion Hoe-Lian Goh, Yin-Leng Theng, Quang Minh Nguyen, Thi Nhu Quynh Kim, Ee Peng Lim, Chew-Hung Chang, Kalyani Chatterjea, Aixin Sun Oct 2009

Sharing Mobile Multimedia Annotations To Support Inquiry-Based Learning Using Mobitop, Khasfariyati Razikin, Dion Hoe-Lian Goh, Yin-Leng Theng, Quang Minh Nguyen, Thi Nhu Quynh Kim, Ee Peng Lim, Chew-Hung Chang, Kalyani Chatterjea, Aixin Sun

Research Collection School Of Computing and Information Systems

Mobile devices used in educational settings are usually employed within a collaborative learning activity in which learning takes place in the form of social interactions between team members while performing a shared task. We introduce MobiTOP (Mobile Tagging of Objects and People), a geospatial digital library system which allows users to contribute and share multimedia annotations via mobile devices. A key feature of MobiTOP that is well suited for collaborative learning is that annotations are hierarchical, allowing annotations to be annotated by other users to an arbitrary depth. A group of student-teachers involved in an inquiry-based learning activity in geography …

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Semantics-Preserving Bag-Of-Words Models For Efficient Image Annotation, Lei Wu, Steven C. H. Hoi, Nenghai Yu Oct 2009

Semantics-Preserving Bag-Of-Words Models For Efficient Image Annotation, Lei Wu, Steven C. H. Hoi, Nenghai Yu

Research Collection School Of Computing and Information Systems

The Bag-of-Words (BoW) model is a promising image representation for annotation. One critical limitation of existing BoW models is the semantic loss during the codebook generation process, in which BoW simply clusters visual words in Euclidian space. However, distance between two visual words in Euclidean space does not necessarily reflect the semantic distance between the two concepts, due to the semantic gap between low-level features and high-level semantics. In this paper, we propose a novel scheme for learning a codebook such that semantically related features will be mapped to the same visual word. In particular, we consider the distance between …

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Continuous Monitoring Of Spatial Queries In Wireless Broadcast Environments, Kyriakos Mouratidis, Spiridon Bakiras, Dimitris Papadias Oct 2009

Continuous Monitoring Of Spatial Queries In Wireless Broadcast Environments, Kyriakos Mouratidis, Spiridon Bakiras, Dimitris Papadias

Research Collection School Of Computing and Information Systems

Wireless data broadcast is a promising technique for information dissemination that leverages the computational capabilities of the mobile devices in order to enhance the scalability of the system. Under this environment, the data are continuously broadcast by the server, interleaved with some indexing information for query processing. Clients may then tune in the broadcast channel and process their queries locally without contacting the server. Previous work on spatial query processing for wireless broadcast systems has only considered snapshot queries over static data. In this paper, we propose an air indexing framework that 1) outperforms the existing (i.e., snapshot) techniques in …

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Scalable Detection Of Partial Near-Duplicate Videos By Visual-Temporal Consistency, Hung-Khoon Tan, Chong-Wah Ngo, Richang Hong, Tat-Seng Chua Oct 2009

Scalable Detection Of Partial Near-Duplicate Videos By Visual-Temporal Consistency, Hung-Khoon Tan, Chong-Wah Ngo, Richang Hong, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Following the exponential growth of social media, there now exist huge repositories of videos online. Among the huge volumes of videos, there exist large numbers of near-duplicate videos. Most existing techniques either focus on the fast retrieval of full copies or near-duplicates, or consider localization in a heuristic manner. This paper considers the scalable detection and localization of partial near-duplicate videos by jointly considering visual similarity and temporal consistency. Temporal constraints are embedded into a network structure as directed edges. Through the structure, partial alignment is novelly converted into a network flow problem where highly efficient solutions exist. To precisely …

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First Acm Sigmm International Workshop On Social Media (Wsm'09), Suzanne Boll, Steven C. H. Hoi, Jiebo Luo, Rong Jin, Dong Xu, Irwin King Oct 2009

First Acm Sigmm International Workshop On Social Media (Wsm'09), Suzanne Boll, Steven C. H. Hoi, Jiebo Luo, Rong Jin, Dong Xu, Irwin King

Research Collection School Of Computing and Information Systems

The ACM SIGMM International Workshop on Social Media(WSM’09) is the first workshop held in conjunction withthe ACM International Multimedia Conference (MM’09) atBejing, P.R. China, 2009. This workshop provides a forumfor researchers and practitioners from all over the world toshare information on their latest investigations on social mediaanalysis, exploration, search, mining, and emerging newsocial media applications.

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A Study Of Content Authentication In Proxy-Enabled Multimedia Delivery Systems: Model, Techniques, And Applications, Robert H. Deng, Yanjiang Yang Oct 2009

A Study Of Content Authentication In Proxy-Enabled Multimedia Delivery Systems: Model, Techniques, And Applications, Robert H. Deng, Yanjiang Yang

Research Collection School Of Computing and Information Systems

Compared with the direct server-user approach, the server-proxy-user architecture for multimedia delivery promises significantly improved system scalability. The introduction of the intermediary transcoding proxies between content servers and end users in this architecture, however, brings unprecedented challenges to content security. In this article, we present a systematic study on the end-to-end content authentication problem in the server-proxy-user context, where intermediary proxies transcode multimedia content dynamically. We present a formal model for the authentication problem, propose a concrete construction for authenticating generic data modality and formally prove its security. We then apply the generic construction to authenticating specific multimedia formats, for …

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Analysis Of Tradeoffs Between Buffer And Qos Requirements In Wireless Networks, Raphael Rom, Hwee-Pink Tan Oct 2009

Analysis Of Tradeoffs Between Buffer And Qos Requirements In Wireless Networks, Raphael Rom, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

In this paper, we consider the scheduling problem where data packets from K input-flows need to be delivered to K corresponding wireless receivers over a heterogeneous wireless channel. Our objective is to design a wireless scheduler that achieves good throughput and fairness performance while minimizing the buffer requirement at each wireless receiver. This is a challenging problem due to the unique characteristics of the wireless channel. We propose a novel idea of exploiting both the long-term and short-term error behavior of the wireless channel in the scheduler design. In addition to typical first-order Quality of Service (QoS) metrics such as …

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A Surprise Triggered Adaptive And Reactive (Star) Framework For Online Adaptation In Non-Stationary Environments, Truong-Huy Dinh Nguyen, Tze-Yun Leong Oct 2009

A Surprise Triggered Adaptive And Reactive (Star) Framework For Online Adaptation In Non-Stationary Environments, Truong-Huy Dinh Nguyen, Tze-Yun Leong

Research Collection School Of Computing and Information Systems

We consider the task of developing an adaptive autonomous agent that can interact with non-stationary environments. Traditional learning approaches such as Reinforcement Learning assume stationary characteristics over the course of the problem, and are therefore unable to learn the dynamically changing settings correctly. We introduce a novel adaptive framework that can detect dynamic changes due to non-stationary elements. The Surprise Triggered Adaptive and Reactive (STAR) framework is inspired by human adaptability in dealing with daily life changes. An agent adopting the STAR framework consists primarily of two components, Adapter and Reactor. The Reactor chooses suitable actions based on predictions made …

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Distance Metric Learning From Uncertain Side Information With Application To Automated Photo Tagging, Lei Wu, Steven C. H. Hoi, Rong Jin, Jianke Zhu, Nenghai Yu Oct 2009

Distance Metric Learning From Uncertain Side Information With Application To Automated Photo Tagging, Lei Wu, Steven C. H. Hoi, Rong Jin, Jianke Zhu, Nenghai Yu

Research Collection School Of Computing and Information Systems

Automated photo tagging is essential to make massive unlabeled photos searchable by text search engines. Conventional image annotation approaches, though working reasonably well on small testbeds, are either computationally expensive or inaccurate when dealing with large-scale photo tagging. Recently, with the popularity of social networking websites, we observe a massive number of user-tagged images, referred to as "social images", that are available on the web. Unlike traditional web images, social images often contain tags and other user-generated content, which offer a new opportunity to resolve some long-standing challenges in multimedia. In this work, we aim to address the challenge of …

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Mining Quantified Temporal Rules: Formalism, Algorithms, And Evaluation, David Lo, Ganesan Ramalingam, Venkatesh-Prasad Ranganath, Kapil Vaswani Oct 2009

Mining Quantified Temporal Rules: Formalism, Algorithms, And Evaluation, David Lo, Ganesan Ramalingam, Venkatesh-Prasad Ranganath, Kapil Vaswani

Research Collection School Of Computing and Information Systems

Libraries usually impose constraints on how clients should use them. Often these constraints are not well-documented. In this paper, we address the problem of recovering such constraints automatically, a problem referred to as specification mining. Given some client programs that use a given library, we identify constraints on the library usage that are (almost) satisfied by the given set of clients.The class of rules we target for mining combines simple binary temporal operators with state predicates (involving equality constraints) and quantification. This is a simple yet expressive subclass of temporal properties that allows us to capture many common API usage …

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Secure Mobile Agents With Designated Hosts, Qi Zhang, Yi Mu, Minji Zhang, Robert H. Deng Oct 2009

Secure Mobile Agents With Designated Hosts, Qi Zhang, Yi Mu, Minji Zhang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Mobile agents often travel in a hostile environment where their security and privacy could be compromised by any party including remote hosts in which agents visit and get services. It was proposed in the literature that the host visited by an agent should jointly sign a service agreement with the agent's home, where a proxy-signing model was deployed and every host in the agent system can sign. We observe that this actually poses a serious problem in that a host that should be excluded from an underlying agent network could also send a signed service agreement. In order to solve …

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Streaming 3d Meshes Using Spectral Geometry Images, Ying He, Boon Seng Chew, Dayong Wang, Steven C. H. Hoi, Lap Pui Chau Oct 2009

Streaming 3d Meshes Using Spectral Geometry Images, Ying He, Boon Seng Chew, Dayong Wang, Steven C. H. Hoi, Lap Pui Chau

Research Collection School Of Computing and Information Systems

The transmission of 3D models in the form of Geometry Images (GI) is an emerging and appealing concept due to the reduction in complexity from R3 to image space and wide availability of mature image processing tools and standards. However, geometry images often suffer from the artifacts and error during compression and transmission. Thus, there is a need to address the artifact reduction, error resilience and protection of such data information during the transmission across an error prone network. In this paper, we introduce a new concept, called Spectral Geometry Images (SGI), which naturally combines the powerful spectral analysis with …

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Localizing Volumetric Motion For Action Recognition In Realistic Videos, Xiao Wu, Chong-Wah Ngo, Jintao Li, Yongdong Zhang Oct 2009

Localizing Volumetric Motion For Action Recognition In Realistic Videos, Xiao Wu, Chong-Wah Ngo, Jintao Li, Yongdong Zhang

Research Collection School Of Computing and Information Systems

This paper presents a novel motion localization approach for recognizing actions and events in real videos. Examples include StandUp and Kiss in Hollywood movies. The challenge can be attributed to the large visual and motion variations imposed by realistic action poses. Previous works mainly focus on learning from descriptors of cuboids around space time interest points (STIP) to characterize actions. The size, shape and space-time position of cuboids are fixed without considering the underlying motion dynamics. This often results in large set of fragmentized cuboids which fail to capture long-term dynamic properties of realistic actions. This paper proposes the detection …

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Towards Google Challenge: Combining Contextual And Social Information For Web Video Categorization, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo Oct 2009

Towards Google Challenge: Combining Contextual And Social Information For Web Video Categorization, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Web video categorization is a fundamental task for web video search. In this paper, we explore the Google challenge from a new perspective by combing contextual and social information under the scenario of social web. The semantic meaning of text (title and tags), video relevance from related videos, and user interest induced from user videos, are integrated to robustly determine the video category. Experiments on YouTube videos demonstrate the effectiveness of the proposed solution. The performance reaches 60% improvement compared to the traditional text based classifiers.

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Distribution-Based Concept Selection For Concept-Based Video Retrieval, Juan Cao, Hongfang Jing, Chong-Wah Ngo, Yongdong Zhang Oct 2009

Distribution-Based Concept Selection For Concept-Based Video Retrieval, Juan Cao, Hongfang Jing, Chong-Wah Ngo, Yongdong Zhang

Research Collection School Of Computing and Information Systems

Query-to-concept mapping plays one of the keys to concept-based video retrieval. Conventional approaches try to find concepts that are likely to co-occur in the relevant shots from the lexical or statistical aspects. However, the high probability of co-occurrence alone cannot ensure its effectiveness to distinguish the relevant shots from the irrelevant ones. In this paper, we propose distribution-based concept selection (DBCS) for query-to-concept mapping by analyzing concept score distributions of within and between relevant and irrelevant sets. In view of the imbalance between relevant and irrelevant examples, two variants of DBCS are proposed respectively by considering the two-sided and onesided …

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Semantic Context Transfer Across Heterogeneous Sources For Domain Adaptive Video Search, Yu-Gang Jiang, Chong-Wah Ngo, Shih-Fu Chang Oct 2009

Semantic Context Transfer Across Heterogeneous Sources For Domain Adaptive Video Search, Yu-Gang Jiang, Chong-Wah Ngo, Shih-Fu Chang

Research Collection School Of Computing and Information Systems

Automatic video search based on semantic concept detectors has recently received significant attention. Since the number of available detectors is much smaller than the size of human vocabulary, one major challenge is to select appropriate detectors to response user queries. In this paper, we propose a novel approach that leverages heterogeneous knowledge sources for domain adaptive video search. First, instead of utilizing WordNet as most existing works, we exploit the context information associated with Flickr images to estimate query-detector similarity. The resulting measurement, named Flickr context similarity (FCS), reflects the co-occurrence statistics of words in image context rather than textual …

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First Acm Sigmm International Workshop On Social Media (Wsm'09), Suzanne Boll, Steven C. H. Hoi, Jiebo Luo, Rong Jin, Dong Xu, Irwin King Oct 2009

First Acm Sigmm International Workshop On Social Media (Wsm'09), Suzanne Boll, Steven C. H. Hoi, Jiebo Luo, Rong Jin, Dong Xu, Irwin King

Research Collection School Of Computing and Information Systems

No abstract provided.

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Verifying Stateful Timed Csp Using Implicit Clocks And Zone Abstraction, Jun Sun, Yang Liu, Jin Song Dong, Xian Zhang Sep 2009

Verifying Stateful Timed Csp Using Implicit Clocks And Zone Abstraction, Jun Sun, Yang Liu, Jin Song Dong, Xian Zhang

Research Collection School Of Computing and Information Systems

In this work, we study model checking of compositional real-time systems. A system is modeled using mutable data variables as well as a compositional timed process. Instead of explicitly manipulating clock variables, a number of compositional timed behavioral patterns are used to capture quantitative timing requirements, e.g. delay, timeout, deadline, timed interrupt, etc. A fully automated abstraction technique is developed to build an abstract finite state machine from the model. The idea is to dynamically create/delete clocks, and maintain/solve a constraint on the clocks. The abstract machine weakly bi-simulates the model and, therefore, LTL model checking or trace-refinement checking are …

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A Latent Model For Visual Disambiguation Of Keyword-Based Image Search, Kong-Wah Wan, Ah-Hwee Tan, Joo-Hwee Lim, Liang-Tien Chia, Sujoy Roy Sep 2009

A Latent Model For Visual Disambiguation Of Keyword-Based Image Search, Kong-Wah Wan, Ah-Hwee Tan, Joo-Hwee Lim, Liang-Tien Chia, Sujoy Roy

Research Collection School Of Computing and Information Systems

The problem of polysemy in keyword-based image search arises mainly from the inherent ambiguity in user queries. We propose a latent model based approach that resolves user search ambiguity by allowing sense specific diversity in search results. Given a query keyword and the images retrieved by issuing the query to an image search engine, we first learn a latent visual sense model of these polysemous images. Next, we use Wikipedia to disambiguate the word sense of the original query, and issue these Wiki-senses as new queries to retrieve sense specific images. A sense-specific image classifier is then learnt by combining …

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Detecting Automotive Exhaust Gas Based On Fuzzy Inference System, Li. Shujin, Ming Bai, Quan Wang, Bo Chen, Xiaobing Zhao, Ting Yang, Zhaoxia Wang Sep 2009

Detecting Automotive Exhaust Gas Based On Fuzzy Inference System, Li. Shujin, Ming Bai, Quan Wang, Bo Chen, Xiaobing Zhao, Ting Yang, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

This paper proposes a method of detecting automotive exhaust gas based on fuzzy logic inference after analyzing the principle of the infrared automobile exhaust gas analyzer and the influence of the environmental temperature on analyzer. This paper analyses the measurement error caused by environmental temperature, and then makes a non-linear error correction of temperature for the infrared sensor using fuzzy inference. The results of simulation have clearly demonstrated that the proposed fuzzy compensation scheme is better than the non-fuzzy method.

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