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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Hai-Yang Jia Juan Chen He-Long Yu Da-You Liu College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun Jilin China College of Information technology Jilin agricultural University Changchun Jilin China

Soil fertility grading is an important issue in the agriculture domain, AI based approach has been applied recently. But in most circumstance data obtaining is a expensive and time consuming procedure, sometimes even impossible. This paper presents a Bayesian Network based transfer learning algorithm. The existing training results can be transferred between the nearby land squares. The proposed algorithm considers both the similarity between the learning task and the geographical position of the land squares. Empirical experiment were implemented to prove the efficiency of the algorithm.

关键词： Bayesian methods Machine learning Learning Soil Random variables Machine learning algorithms Training data

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Exploring Time Varying Shortest Path of Urban OD Pairs Based on Floating Car data

Exploring Time Varying Shortest Path of Urban OD Pairs Based...

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The 18th International Conference on Geoinformatics(第18届国际地理信息科学与技术大会 Geoinformatics 2010)

作者： Wei TU Zhixiang FANG Qingquan Li State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanChina Engineering Research Centre for Spatio-Temporal Data Smart Acquisition and Application Ministry of Education of China Wuhan UniversityWuhanChina

ISBN: (纸本)9781424473014

Traffic state (for instance, link travel time, velocity, volume) in the links of the urban road network should be taken into account while calculating the shortest path in real application situations. However, the traffic state of the urban road network varies in different places and at different time. Constructing a time varying road network is critical to explore the time varying shortest path. The travel time of a road link can be described by some probability distribution functions, or estimated through using real time traffic information and shortterm traffic forecast. Therefore, the time varying road network can be built based on the varying travel time captured by various approaches. This paper proposes an effective approach to investigate the time varying shortest path based on floating car data. First, all space-time paths of floating cars are reconstructed after map-matching process of floating car data. Then, to capture the velocity and the distribution of vehicles that reflects traffic density, all space-time paths are sliced at every minute to build up the traffic snapshot of the road network. A congestion index is introduced to quantify the traffic state of each snapshot at any location, which is calculated based on velocity and traffic density. By virtue of these time-series traffic state snapshots, the timevarying transport network was established and shortest path of OD pair at different departure time was calculated by A* shortest path algorithm. A case study with one day floating car data in Wuhan, China was implemented, and the experimental prototype provides the capability of exploring the time-varying shortest paths by time of a day in the time varying transport network.

关键词： time varying shortest path:transport network floating car data:GIS

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Taxi-Viewer: Around the Corner Taxis Are!

Taxi-Viewer: Around the Corner Taxis Are!

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Ke Hu Zhangguang He Yang Yue Transportation Research Center Engineering Research Center for Spatio-Temporal Data Smart Acquisition and Application Ministry of Education of China State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University of Technology Wuhan China

Taxi is an indispensable component of urban transportation system, which aims to provide a convenient and efficient means of transport. However, unlike bus service that has fixed station and schedule, to most taxi-seekers, the formula for catching a taxi at the nearest place with the shortest waiting time is experience plus luck, especially in peak hour or adverse weather conditions. In this demo paper, we present Taxi-Viewer, a service-oriented online system to help users pinpoint the hot spots where usually have more chances to catch a taxi, and keep users informed of the real-time location and trajectory of taxis in a given neighborhood. With the functions provided in the demo, taxi-seekers can reduce waiting time, and taxi operator can also benefit from the system to improve service quality and increase profit as well.

关键词： Real time systems Vehicles Servers Roads Conferences Trajectory

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A hybrid algorithm of minimum spanning tree and nearest neighbor for classifying human cancers

A hybrid algorithm of minimum spanning tree and nearest neig...

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International Conference on Advanced Computer Theory and engineering, ICACTE

作者： Chunbao Zhou Liming Wan Yanchun Liang College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun China Research Institute on General Development and Evaluation of Equipment EAAF of PLA Beijing China

ISBN: (纸本)9781424465392

Classification and prediction of different cancers based on gene expression profiles are important for cancer diagnosis, cancer treatment and medication discovery. The k nearest neighbor algorithm (k-NN) is one easy and efficient machine learning method for cancer classification and the parameter k is crucial. In this paper, we integrate minimum spanning tree (MST) and k nearest neighbor algorithm (k-NN) for cancer classification. The MST is designed for the selection of parameter k and the nearest neighbors for k-NN. Firstly we build a minimum spanning tree (MST) based on Euclidean distance between each two samples for gene expression data only including one unknown class sample. Secondly for unknown class sample in the gene expression data, we find the connected samples and then apply majority vote principle. Thirdly if there are tied votes then we expend the connected samples with the nearest neighbors for unknown class sample until all the samples are expended or the class for unknown sample is obtained. This hybrid algorithm is referred to as MSTNN. The hybrid algorithm MSTNN is compared with k-NN and other 3 existing classification algorithms on CNS dataset, Colon dataset and Lung dataset, 3 binary class gene expression datasets and 3 multi-class gene expression datasets: Leukemia1, Leukemia2, and Leukemia3 involving human cancers. The MSTNN algorithm improves 5.65% better than k-NN on average LOOCV accuracy and 13.80% better than k-NN on testing datasets classification average accuracy, and achieves the best performance in all the 5 algorithms. The results demonstrate that the proposed MSTNN algorithm is feasible to classify human cancers.

关键词： Classification algorithms Artificial neural networks Niobium Lungs Colon Support vector machines Cancer

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A Fine-Grained data Reconstruction Algorithm for Solid-State Disks

A Fine-Grained Data Reconstruction Algorithm for Solid-State...

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International Conference on Networking, Architecture, and Storage (NAS)

作者： Peng Wang Diqing Hu Changsheng Xie Jianzong Wang Xiao Qin Wuhan National Laboratory of Optoelectronics Key Laboratory of Data Storage System Ministry of Education School of Computer Science and Technology Huazhong University of Science and Technology Wuhan Hubei China Department of Computer Science and Software Engineering Samuel Ginn College of Engineering Aubum University USA

Solid-state disks (SSDs) with high I/O performance are increasingly becoming popular. To extend the life time of flash memory, one can apply wear-leveling strategies to manage data blocks. However, wear-leveling strategies certainly inevitably degrade write performance. In addition to low write performance, wear-leveling strategies make one block unwritable when one bit of this block is invalid. Although data reconstruction techniques have been widely employed in disk arrays, the reconstruction techniques has not been studied in the context of solid-state disks. In this paper, we present a new fine-grained data-reconstruction algorithm for solid-state disks. The algorithm aims to provide a simple yet efficient wear-leveling strategy that improves both I/O performance and reliability of solid-state disks. Simulation experiments show that all data blocks have very similar in terms of erasure times. The number of extra erasures incurred by our algorithm is very marginal.

关键词： Reconstruction algorithms Reliability Mathematical model Flash memory Equations Arrays Parity check codes

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Studies and implementation of the trusted process mechanism in a secure operating system

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Qinghua Daxue Xuebao/Journal of Tsinghua University 2010年第SUPPL. 1期50卷 1547-1553页

作者： Zhang, Chongbin Li, Fengjuan Liang, Bin China Information Technology Security Evaluation Center Beijing 100085 China Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education School of Information Renming University of China Beijing 100872 China

The trusted process mechanism is an important part of the operating system security mechanism, but there is no uniform definition of the trusted process and there are some limitations in understanding its fundamental properties. In this paper, the trustworthiness of a trusted process is discussed in terms of privilege, data-operated integrity, functional and logic correctness, self-integrity, availability and trusted interactions. A trusted process definition is then given which summarizes the fundamental properties of a trusted process as a theoretical foundation for researching and enforcing the trusted process mechanism. A prototype of a trusted process mechanism is implemented in a secure operating system based on Linux, with the trustworthiness of the trusted process assured in many ways to improve and extende the original trust mechanisms in Linux.

关键词： Linux

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SAM: A Semantic-Aware Multi-tiered Source De-duplication Framework for Cloud Backup

SAM: A Semantic-Aware Multi-tiered Source De-duplication Fra...

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International Conference on Parallel Processing (ICPP)

作者： Yujuan Tan Hong Jiang Dan Feng Lei Tian Zhichao Yan Guohui Zhou School of Computer Science & Technology Huazhong University of Science and Technology China Key Laboratory of Data Storage Systems Ministry of Education of China China Department of Computer Science & Engineering University of Nebraska Lincoln USA

Existing de-duplication solutions in cloud backup environment either obtain high compression ratios at the cost of heavy de-duplication overheads in terms of increased latency and reduced throughput, or maintain small de-duplication overheads at the cost of low compression ratios causing high data transmission costs, which results in a large backup window. In this paper, we present SAM, a Semantic-Aware Multitiered source de-duplication framework that first combines the global file-level de-duplication and local chunk-level deduplication, and further exploits file semantics in each stage in the framework, to obtain an optimal tradeoff between the deduplication efficiency and de-duplication overhead and finally achieve a shorter backup window than existing approaches. Our experimental results with real world datasets show that SAM not only has a higher de-duplication efficiency/overhead ratio than existing solutions, but also shortens the backup window by an average of 38.7%.

关键词： Servers Semantics Redundancy Clouds data communication Image coding Indexes

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Semantic Retrieval System Based on Corn Ontology

Semantic Retrieval System Based on Corn Ontology

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Japan-China Joint Workshop on Frontier of Computer Science and Technology (FCST)

作者： Hong Qi Liangliang Zhang Ying Gao Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University China College of Computer Science and Technology Jilin University China Alcatel Lucent Shanghai Bell Company Limited China Jilin University Changchun Jilin CN

Most of the current information retrieval systems are mainly based on full text matching of keywords or topic-based classification, often return a large number of irrelevant information, and are unable to meet the user's request. Ontology-based semantic retrieval is a hot issue in current research. In this paper, the corn plant ontology is constructed using Formal Concept Analysis based approach in which the concept lattice is built from terminology-file relationship table and further reduced. Based on the corn plant ontology, we propose a semantic annotation method in which the feature words are selected by an improved method for weight calculation and the RDF triples are generated by syntactic parser. Finally a semantic retrieval system for corn plant is developed. In comparative experiment one hundred documents are selected as the dataset, and the result shows that the semantic retrieval system introduced in this paper is superior to keyword-based retrieval method in precision ratio and recall ratio.

关键词： Semantics Ontologies Information retrieval Lattices Feature extraction Resource description framework Optical wavelength conversion

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Operating system mechanisms for TPM-based lifetime measurement of process integrity

Operating system mechanisms for TPM-based lifetime measureme...

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2009 IEEE 6th International Conference on Mobile Adhoc and Sensor Systems, MASS '09

作者： Xiao, Li Wenchang, Shi Zhaohui, Liang Bin, Liang Zhiyong, Shan Key Laboratory of Data Engineering and Knowledge Engineering (Renmin University) Ministry of Education

ISBN: (纸本)9781424451135

Implementing runtime integrity measurement in an acceptable way is a big challenge. We tackle this challenge by developing a framework called Patos. This paper discusses the design and implementation concepts of our operating system mechanisms for runtime process integrity measurement, which is an important part of the Patos framework and is named Patos-RIP. Patos-RIP is developed into the mainstream Linux operating system and utilizes TPM as hardware support for tamper-resistance. From the beginning a process is created to the moment the process dies, Patos-RIP conducts integrity measurement at appropriate points of time when the process runs, so as to ensure that the integrity of a process is not compromised during its whole lifetime. This way, Patos-RIP can improve trustworthiness of processes by effectively detecting runtime tampering attacks on processes' integrity. ©2009 IEEE.

关键词： Computer operating systems

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Workflow-Based Spatial Modeling Environment and Its Application in Food Provisioning Services of Grassland Ecosystem

Workflow-Based Spatial Modeling Environment and Its Applicat...

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The 18th International Conference on Geoinformatics(第18届国际地理信息科学与技术大会 Geoinformatics 2010)

作者： Yimin Lu Tianxiang Yue Qinmin Wang Chenliang Wang State Key Lab.of Resources & Environmental Information System Institute of Geographic Sciences and N Key Laboratory of Data Mining & Information Sharing of Ministry of Education Spatial Information Res The College of Information Science and Engineering Shandong University of Science and Technology Qin

ISBN: (纸本)9781424473014

Nowadays, the key strategic issues about resource and environment, such as global warming, water resources shortage, food security etc. are more complex and multidisciplinary than ever before. In scientific research, the developmental tendency of modelling and integrating technique is all but irreversible. Focusing on the topic of model integration, we develop a Workflow-based Spatial Modeling Environment (WF-SME) which enables scientists and modeling users easy to design and create of complex systems models through a drag-drop operation or editing mathematical formula in model constructor. WF-SME, a visual integrated modeling environment is mainly used for the rapid realization of model dynamic integration, in which we can implement the composition and connection of the existing models, and generate new model through graphical operation. The papers firstly introduce the framework of model integration designed for WF-SME as well as its supporting theory, and then explain in detail how the modules of WF-SME have been realized. WF-SME is a platform for spatial modelling, which was designed in four parts, Spatial Workflow Designer, Model builder, Spatial Calculation engine and Visualization of Modelling Output. The spatial workflow designer built-in WFSME shipping with toolsets was adopted to create spatial workflow, reuse and aggregate models. Consisting of equation editor and data banding tool, the model builder enable modeller updates formulas on-demand. This editor parsed by MathML is powerful and flexible enough for the requirements of expressions of mathematical calculations. The spatial calculating engine developed based on component, through the map algebra language, executes mathematical calculations. The multi-form visualization module was developed to provide visual expression for a series of intermediate data and its result of the domain models. Finally, we illustrate how the typical practical application sample has been modeled in our modeling environment

关键词： Spatial workflow:Modeling environment:Model builder:MathML:Grassland ecosystem:Food provisioning model

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