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This paper describes the local harmonic decomposition: it is an efficient algorithm which can be used to extract angle information from a wavefield. It is then shown that this algorithm can be used in the context of geophysical processing to produce reflection angle gathers during a shot-record migration. Shot-record wave-equation migration is a very accurate method for imaging geophysical data in...
In the field of cycling competition, cyclists commonly utilize binding pedals to maximize their competitive performance. The feature of binding pedals is to hold the sole of cycling shoe on the upper body of pedal, which enables a cyclist to not only push down the pedals but also pull up the pedals in one revolution of pedaling motion. Pedaling motion is implemented by the combination of muscle activities...
Metalearning approach to the model selection problem - exploiting the idea that algorithms perform similarly on similar datasets - requires a suitable metric on the dataset space. One common approach compares the datasets based on fixed number of features describing the datasets as a whole. The information based on individual attributes is usually aggregated, taken for the most relevant attributes...
Advances in social computing and networking software and technologies enable users to intersect social behaviour with computing systems for creating social conventions and contexts. In recent years, social networking sites have become popular to facilitate collaboration and knowledge sharing between users. A rich set of information is embedded in these social media data. In this paper, we propose...
Classification of data points in a data stream is a fundamentally different set of challenges than data mining on static data. While streaming data is often placed into the context of "Big Data" (or more specifically "Fast Data") wherein one-pass algorithms are used, true data streams offer additional hurdles due to their dynamic, evolving, and non-stationary nature. During the...
In this paper, we introduce the concept of "value" to the abduction procedure. In fact, "values" are dealt with outside of the abduction procedure. For usual abduction, we always consider values included in the knowledge (hard coded). However, for a certain procedure, such values are unnecessary and sometimes harmful. Outside of the main abduction procedure, the inference system...
The widespread adoption of ubiquitous devices does not only facilitate the connection of billions of people, but has also fuelled a culture of sharing rich, high resolution locations through check-ins. Despite the profusion of GPS and WiFi driven location prediction techniques, the sparse and random nature of check-in data generation have ushered diverse problems, which have prompted the prediction...
This paper highlights the importance of measuring systemic risk of commercial banks. Conditional Value-at-Risk (CoVaR) is used to measure the degree of "risk externalities" that a specific bank contributes to the whole banking system. Our analysis not only presents current levels of systemic risk of individual banks but also the changes with time passes. There is some evidence that larger...
Due to the ubiquity of GPS enabled devices and the advances in sensing technologies, trajectory data has become abundant. Regions of interest are important since they describe specific hot-spots within the data that often correlate with domain specific phenomena. Traditional region of interest mining utilises grid based rasters to model space. This suffers from two main problems: hard to determine...
A compressive sensing (CS) based approach is developed in conjunction with an adaptive basis reweighting procedure for stochastic process power spectrum estimation. In particular, the problem of sampling gaps in stochastic process records, occurring for reasons such as sensor failures, data corruption, and bandwidth limitations, is addressed. Specifically, due to the fact that many stochastic process...
Web usage mining is to find the usage pattern of web pages from weblog records in order to get an improved understanding of user's way of accessing web pages. This information is especially valuable to the web master's to optimize the page navigation plan according to the page of interests for the visitor and it also helps in quantifying the visitor preferences. In this paper, an attempt is being...
Response model is one of the most frequently used predictive model. So I make a comprehensive introduction about basic concepts, key functions and main contents of response model and evaluated the model. Through design for utility function and attribute weights to get market value function. In this progress, positive cases and negative cases must be considered. Calculating market value can help enterprises...
With the advances of wireless technologies, moving objects or users equipped with sensors are located and tracked by wireless sensor networks. Recommendations for the direction and route in exhibition by analyzing and mining the user's movement behavior can be conducted. In this paper, we study how to mine the data of historical trajectories and develop an approach which can guide the users. When...
Data was mined for the purpose of extracting data from an online source to compute and classify hydraulic geometry as well as providing additional data (channel stability, material, and evenness) for pattern discovery. Hydraulic geometry, the relationships between a stream's geometry (width and depth) and flow (velocity and discharge), is applicable to flood prediction, water resources management,...
Spectral Embedding is one of the most effective dimension reduction algorithms in data mining. However, its computation complexity has to be mitigated in order to apply it for real-world large scale data analysis. Many researches have been focusing on developing approximate spectral embeddings which are more efficient, but meanwhile far less effective. This paper proposes Diverse Power Iteration Embeddings...
Recently, information hiding technique in image data has attracted attention as a countermeasure against illegal distribution, tampering and copyright infringement. In conventional information hiding, the image after the embedding (stego-image) is degraded. In application where image degradation is not tolerated, information hiding with reversible degradation is desired. Reversibility in this case...
We discuss connections between the interrelationship mining, proposed by the authors, and rough sets on two universes. The interrelationship mining enable us to extract characteristics based on comparison between values of different attributes. Rough sets on two universes is an theoretical extension of the original rough sets by considering connection between two universes. In this paper, we point...
As personalization technologies are widely used, preference extraction is becoming important. In this work, we propose a preference extraction method on the basis of applications that are installed on a user's smart device. In this method, keywords are extracted from descriptions of the installed applications on an application market. Then, each keyword is scored by three scoring criteria: degree...
With the development of Internet technology and outbreak of information revolution, "big data" has become a new keyword and is impacting on the marketing system of enterprises. The application of big data is propitious to data competitiveness construction, consumer demand insight and data innovative thinking, Cloud computing and data mining technology provide powerful supports for data mining...
The purpose of this paper is to provide a solution of extracting appropriate keywords to identify meaningful learning-contents on the Web. There are some issues in identifying documents that have learning content. Firstly, the documents need to be identified according to the learning area of a student's school year. Secondly, the documents need to be identified according to the learning area that...
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