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Band selection is a very important hyperspectral image preprocessing before using data. A novel bands selection method for hyperspectral data based on convolutional neural network (CNN) is proposed in this paper. In this way, we use a custom one-dimensional CNN to train the hyperspectral data to obtain a well-trained model. After testing band combinations, we use the model to obtain the test precision...
In this demo paper, we present a new data service composition sequence generation approach to solve the ad-hoc data query problem in EDMIS. Our approach allows end users to input some keywords, and then the data services related are found and the Top-K data services composition sequences are generated as output.
Though there are some existing data service mashup tools, it is still challenging for novice end users to develop data service mashup to solve data query problem in the situational and ad-hoc business scenario. This paper focuses on the problem of recommending data service mashup plans under the condition that 1) the mashup plan cannot be determined in advance and 2) user simple request description...
With the development of the Internet, e-commerce industry rises rapidly. Online shopping becomes more and more convenient and fast. However it is very difficult for consumers to find satisfied commodity because of abundant and mixed commodity. Especially when people purchase the items which they are not familiar with or consume in a strange place. The study of the recommended system is to figure out...
Automobile insurance fraud is gradually spreading in the global scope, and mining automobile insurance fraud is more and more concerned by the society. Concerning that the number of samples in the actual automobile insurance claims data is not balance and the amount of data is large, the real data of a automobile insurance company were selected to establish the random forest fraud mining model based...
For ARMAX models, a Latest-Estimation Based Hierarchical Recursive Extended Least Squares algorithm is presented in this paper. The basic idea is to make full use of the latest estimation, and combine this with the hierarchical idea. In the proposed algorithm, the estimates of the white noise information vector is updated by using the latest estimation. The convergence performance of the proposed...
Environmental control and life support system(ECLSS) of the manned spacecraft is an important system to guarantee the safety and life support of the astronauts and the environment inside the space station. For the physicochemical regeneration type of ECLSS(PRLSS), because of its complicated physicochemical process, to analyze and evaluate the mass balance and operation performance through simulation...
In this paper, we propose a novel approach to cluster incomplete images leveraging sparse subspace structure and total variation regularization. Sparse subspace clustering obtains a sparse representation coefficient matrix for input data points by solving an l1 minimization problem, and then uses the coefficient matrix to construct a sparse similarity graph over which spectral clustering is performed...
A logical data petri net (LDPN), a logical data workflow net (LDWN) and a collaborative logical data workflow net (CLDWN) are represented. They are improved formal models extended with data variables, guards and the output condition expressions based on our previous models. Data variables are used to represent data. Guards are used to indicate the additional constraint related to data except for a...
It is true that Internet has not only expanded our horizons, but also triggered an unprecedented revolution of operating electronization against the traditional method after we entered the 21st century — also called the age of Internet. In the business area, many enterprises have already achieved the goal of electronic management, saved human resources as well as material consuming, and largely increased...
Adversarial learning is the study of machine learning techniques deployed in non-benign environments. Example applications include classifications for detecting spam email, network intrusion detection and credit card scoring. In fact as the gamut of application domains of machine learning grows, the possibility and opportunity for adversarial behavior will only increase. Till now, the standard assumption...
In the opportunistic networks, nodes carry and store the data and forward it until they encounter each other. How to choose an appropriate opportunity to forward data is pivotal for nodes' routing in this type of networks. Since nodes currently will keep a regular movement state in the scene of this paper discussed, forecasting a node's moving track in the near future would be very helpful. Through...
The paper investigates the Relative Advancement Degree of Difficulty (RAD2) problem to evaluate the feasibility and effectivity of the technology. Firstly, the study reviews concept of Technology Readiness Level (TRL), Earned Value Management (EVM). Then, an improved method was developed by integrating the impact on cost, schedule and technical performance to calculate the RAD2. With the result of...
In this paper, we develop an online real-time system using Kinect and inertial measurement unit (IMU) to recognize and measure stairs for stair climbing tasks of erect mobile robots. This system combines the ideas of statistical characteristics of 3D point cloud data and adjustable geometric models for stair recognition tasks. Through this system, we not only verify the advantages of statistics methods...
In this paper, we describe a method for mining both frequent episodes and rare episodes in multiple data streams. The main issues include episodes mining and data streams relationship processing. Therefore, a mining algorithm together with two dedicated handling mechanisms is presented. We propose the concept of alternative support for discovering frequent and rare episodes, and define the semantic...
In mechanical product design, designers usually reuse a large number of standard parts and commonly used typical structures accumulated in long-term industry design practice. In this paper, a flexible part library system is proposed to promote the flexibility of PLS. The system uses a flexible part information presentation and User dynamic interface to realize the parameter diversity, and can adapt...
This paper deals with the enantioseparation of racemic propranolol containing S, S-di-n-dodecylltartrate as a chiral carrier using hollow fiber membrane contactor (HFMC). A mathematical mass transfer model of enantioseparation process for chiral compounds was deduced, factors such as the observed partition coefficient between the feed phase and the hollow fibers, the stripping phase and the hollow...
a trust evaluation model for mobile e-commerce trading platform was proposed, which is based on improved Grey-prediction-model. The model utilizes the theory of Gray prediction, constructs the GM (1,1) model according to the changes of previous trust values of entities interaction and predict the next trust value. Experiments show that the model is a better solution to mobile e-commerce on trust status...
After the research and analyze of demand and capacity management in supply chain, the paper proposed an analysis model of MRP and supplier's capacity based on the demand data model and capacity data model to cover the limitations in current management of demand and capacity. Through the practical application of the model in enterprise, the results showed that the bottleneck of capacity can be found...
In order to meet the requirements of the system running environments simulation for virtual machines' performance optimization and anomaly detection, an extensible tool named Characteristic Scenarios Simulator for Virtual Machine was developed base on the summarization and analysis of characteristic scenarios of virtual machines' running. The simulator takes an Analyser-Manager-Worker core architecture...
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