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The prevalence of heart failure is 2-3% of the adult population and it is expected to grow. Half of all patients diagnosed with it die within four years. To minimize life-threatening situations and to minimize costs, it is interesting to predict mortality rates for a patient with heart failure. In this paper, a fuzzy decision tree based on classification ambiguity and a fuzzy decision tree based on...
The software development process patterns in open source software projects are not well known. Consequently, the longevity of new open source software projects is left up to subjective experiences of the development team. In this study, we are investigating a data mining approach for identifying relevant patterns in software development process. We demonstrate the capabilities of wavelet analysis...
CCTV is one of the tools that can be used to extract the needed traffic Information. Extracted information from image sequences of CCTV can give us real information about the number of passing vehicles and vehicles speed. In this paper we propose a new method in detecting the number of vehicles and vehicle speed measurement in low light conditions. Headlight detection is used in order to identify...
Considering the increasing need of the contents of 3D video, it is significant to do some research in 2D-to-3D conversion. The depth map is necessary for this processing. In this paper, we propose an effective method to estimate the depth information of the low depth field images of static scenes. Firstly, construct a high-order statistics (HOS) map, which represents the high-frequency components...
This paper presents a method for extracting regions of non-rigid moving objects from a video. The proposed method utilizes interactive image cutout and local affine transformation. In the proposed method, once a user draws seed-lines on the object and background regions of the first frame of a video, the seed-lines are automatically tracked to next frames based on local affine transformation, and...
The availability of inexpensive tracking devices, such as GPS-enabled devices, gives the opportunity to collect large amounts of trajectory data from vehicles. In this context, we are interested in the problem of generating the traffic information in time-dependent networks using this kind of data. This problem is not trivial since several works in literature use strong assumptions on the error distribution...
How can we find data for quality prediction? Early in the life cycle, projects may lack the data needed to build such predictors. Prior work assumed that relevant training data was found nearest to the local project. But is this the best approach? This paper introduces the Peters filter which is based on the following conjecture: When local data is scarce, more information exists in other projects...
The building of an object-level knowledge base is the foundation of a new methodology for many perception tasks in artificial intelligence, and is an area that has received increasing attention in recent years. In this paper, we propose, for the first time, to mine category shape patterns directly from a large urban environment, thus constructing a category structure base. Conventionally, category...
A cyber-physical system (CPS) is a system featuring a tight combination of, and coordination between, the system's computational and physical elements. System reliability is a critical requirement of cyber-physical systems. An unreliable CPS often leads to system malfunctions, service disruptions, financial losses and even human life. Improving CPS reliability requires an objective measurement, estimation...
Crowdsourcing is a new trend for pervasively discovering traffic information due to its low deployment and maintenance cost as compared with traditional infrastructure-based approaches, e.g., loop detectors and CCTV. Mining techniques and the penetration rate of participators in the discovery process are two major issues in such approaches. In this work, we first point out the shockwave phenomenon...
In this paper, we present an algorithm that is to estimate the position of a hand-held camera with respect to terrestrial LiDAR data. Our input is a set of 3D range scans with intensities and one or a set of 2D uncalibrated camera images of the scene. The algorithm that automatically registers range scans and 2D images is composed of following steps. In the first step, we project the terrestrial LiDAR...
We present our vision on the use of data mining for official statistics, illustrate this with some examples, sketch a general framework, and provide directions for future research.
Breeding value is the sum of additive effects of all the genes, which has important effect on breeding. Statistical methods are often used traditionally to estimate breeding value. This paper uses support vector regression machine to estimate breeding value, and two feature-selection methods are developed to preprocess the data. the proposed algorithm is compared with statistical methods in other...
Research based on indoor location systems has recently been developed due to growing interest in location-aware services to be implemented in light mobile devices. Most of this work is based on received signal strength (RSS) from access points. However, a major drawback from using RSS is its variability due to indoor multipath effect caused by reflection, diffraction and scattering of signal propagation...
In former work, the authors developed a modeling system for university learning processes, which aims at evaluating and refining university curricula to reach an optimum of learning success in terms of a best possible grade point average (GPA). This is performed by applying an Educational Data Mining (EDM) technology to former students curricula and their degree of success (GPA) and thus, uncovering...
Handling the large amount of information from aircraft trajectories that are produced daily from air traffic control radar systems requires models for representing trajectories in a compact, easy to calculate, representative and distinctive form. These models should permit to perform clustering and classification operations efficiently and effectively. The Fourier descriptors have these characteristics...
Crowd density estimation is important for intelligent video surveillance. Many methods based on texture features have been proposed to solve this problem. Most of the existing algorithms only estimate crowd density on the whole image while ignore crowd density in local region. In this paper, we propose a novel texture descriptor based on Local Binary Pattern (LBP) Co-occurrence Matrix (LBPCM) for...
Mining the frequently visited places of single mobile users, i.e., significant places, is crucial for supporting personalized location-based services. Most of existing works for significance place mining have a need to take advantage the GPS trajectories of users. However, it is difficult to encourage mobile users to contribute GPS trajectories because of the high power consumption of GPS. In this...
In the last decade, a large number of software repositories have been created for different purposes. In this paper we present a survey of the publicly available repositories and classify the most common ones as well as discussing the problems faced by researchers when applying machine learning or statistical techniques to them.
Parallelization of big-data analytics services over a federation of heterogeneous clouds has been considered to improve performance. However, contrary to common intuition, there is an inherent tradeoff between the level of parallelism and the performance for big-data analytics principally because of a significant delay for big-data to get transferred over the network. The data transfer delay can be...
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