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In our modern living era, pressure sensing is one of the most performed measurements to enhance the quality of life. The more advanced technology such as silicon based Micro-electro-mechanical Systems (MEMS) technology is usually explored due to its competitive cost and proven performance. We have explored and implemented the design of MEMS micro pressure sensor on silicon for biomedical applications...
In this paper, the necessary conditions for bilevel multiobjective programming problems are discussed. Assuming the upper-level objective functions in bilevel multiobjective programming problems are differentiable, we give and prove its first-order necessary conditions of the weak (strong) minimizer by applying the concept and properties of the contingent epiderivative for set-valued maps. The obtained...
Service discovery is the behavior of locating a Web service which has been unknown previously and meets certain functional criteria. It is an important aspect in the service oriented computing approach. Semantic discovery mechanisms provide a better result set than UDDI, but the mechanisms also have disadvantages. This paper proposes a user experience-oriented Web service discovery method combining...
The purpose of this study is to help a bank to build a cross-selling model to score the propensity of a credit card customer to take up a home loan. In order to guarantee the prediction accuracy and enhance the model comprehensibility, it is quite necessary to select out salient features and representative training samples efficiently. A new framework that coordinates feature selection and sample...
This paper models knowledge diffusion as a barter process among people which are connected in a mentor-protege network. Experimental results demonstrate the effects of knowledge diffusion among people under mentor-protege relationship. Moreover, two extended knowledge diffusion models are proposed to enhance effectiveness and efficiency of knowledge diffusion in team, and some suggestions on organizational...
In a data-mining approach, a model for estimation of aerosol optical depth (AOD) from satellite observations is learned using collocated satellite and ground-based observations. For accurate learning of such a spatio-temporal model, it is important to collect ground-based data from a large number of sites. The objective of this project is to determine appropriate locations for the next set of ground-based...
The success of transfer to improve learning on a target task is highly dependent on the selected source data. Instance-based transfer methods reuse data from the source tasks to augment the training data for the target task. If poorly chosen, this source data may inhibit learning, resulting in negative transfer. The current best performing algorithm for instance-based transfer, TrAdaBoost, performs...
The inverse frequent set mining problem is the problem of computing a database on which a given collection of itemsets must emerge to be frequent. Earlier studies focused on investigating computational and approximability properties of this problem. In this paper, we face it under the pragmatic perspective of defining heuristic solution approaches that are effective and scalable in real scenarios...
Concept lattice has many applications and isomorphic judgment of concept lattice is important in some fields. This paper presents a novel algorithm of complete lattice isomorphic judgment. The algorithm, first, introduces a layer computing method which divides the nodes into four types according to their indegree and outdegree. Then the equivalence classes are created. Second, taking equivalence classes...
In this paper, we present a method for solving a kind of arbitrary order linear initial value problems. Based on this method, an algorithm is proposed and fulfilled by numerical and symbolic computations with mechanization in Maple. Finally, some examples are given to illustrate the proposed method. From the results, they show that the proposed method is feasible and efficient.
Bayesian networks are known for providing an intuitive and compact representation of probabilistic information and allowing the creation of models over a large and complex domain. Bayesian learning and reasoning are nontrivial for a large Bayesian network. In parallel, it is a tough job for users (domain experts) to extract accurate information from a large Bayesian network due to dimensional difficulty...
This paper describes a local and distributed expectation maximization algorithm for learning parameters of Gaussian mixture models (GMM) in large peer-to-peer (P2P) environments. The algorithm can be used for a variety of well-known data mining tasks in distributed environments such as clustering, anomaly detection, target tracking, and density estimation to name a few, necessary for many emerging...
Segmentation, the task of splitting a long sequence of discrete symbols into chunks, can provide important information about the nature of the sequence that is understandable to humans. Algorithms for segmenting mostly belong to the supervised learning family, where a labeled corpus is available to the algorithm in the learning phase. We are interested, however, in the unsupervised scenario, where...
In this paper, we formulate a new research problem of learning from vaguely labeled one-class data streams, where the main objective is to allow users to label instance groups, instead of single instances, as positive samples for learning. The batch-labeling, however, raises serious issues because labeled groups may contain non-positive samples, and users may change their labeling interests at any...
The Toeplitz Corona Theorem characterizes the infimal ???? norm of a systems right inverses in terms of a Toeplitz operators smallest singular value. Recently, it has been shown that the finite section method can be used to approximate this infimal ???? norm. In this paper, we point out that these results can also be used to approximate the limit of the gamma iteration in discrete-time ???? full information...
Using K.P method with the help of perturbation theory, the arbitrary k wave vector directional hole effective masses in strained Si1-xGex/(101)Si were obtained. It is found that the more obvious anisotropy of the hole effective mass occurs in strained Si1-xGex on (101) Si substrate and that the [010] directional hole effective mass decreases obviously under strain, compared with the one in relaxed...
To support legacy migration to service-oriented architecture (SOA), this paper presents a method that derives candidates of SOA services from procedural programs. In SOA, every service is supposed to be a process (procedure) with (1) open interface, (2) self-containedness, (3) coarse granularity for business. We identify such services from the source code and its data flow diagram (DFD), by analyzing...
Photo-device efficiency and performance are limited by the surface carrier recombination because the minority carriers are lost in the recombination process which also generates heat and increases device temperature. Based on Shockley-Read-Hall steady-state theory of recombination-generation-trapping kinetics, in the paper, the recombination DC current voltage (R-DCIV) method is extended to explore...
In CIS'2006 Li et al proposed a proxy ring signature, which allows proxy signer to sign messages on behalf of the original signer while providing anonymity. At the same conference, Weng et al proposed an ID-based key-insulated signature scheme. In this paper, we point out that the former scheme is not correctly specified. The required hash function H2 should be a map from an elliptic curve to itself...
In order to build open-loop large scale RFID applications, it is necessary to establish public RFID service infrastructure, the key issue is to build efficient and robust RFID code resolution network. But there exist some problems, such as load balancing, single node failure, etc. On the basis of recent research, according to features of governmental administration and enterprise applications, a hierarchical...
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