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Node clustering has wide-ranging applications in decentralized P2P networks such as P2P file sharing systems, mobile ad-hoc networks, P2P sensor networks, and so forth. This paper proposes an approach to construct clusters in unstructured P2P networks based on small-world theory. In contrast to centralized graph clustering algorithms, our scheme is completely decentralized and it only uses the knowledge...
Collaborative filtering (CF) recommender systems help people discover what they really need in a large set of alternatives by analyzing the preferences of other related users. Recent research has shown that the accuracy of recommendations can be improved significantly by using matrix factorization (MF) models. In particular, a mixed MF model was used by BellKor's Pragmatic Chaos to win the Netflix...
In this paper we describe some new ideas to improve recommendations to groups of people. Our approach maximizes the global satisfaction for the group taking into account people personality and the social relationships among people in the group. We present some results with two cases of study based on the movie recommendation domain with heterogeneous groups. The first case study uses synthetically...
Accurate land use/cover (LUC) classification data derived from remotely sensed data are very important for land use planning and environment sustainable development. Traditionally, statistical classifiers are often used to generate these data, but these classifiers rely on assumptions that may limit their utilities for many datasets. Conversely, artificial neural network (ANN) and decision tree (DT)...
Land use change was the most significant aspect in the research field of globe changing. Affected by both of natural and artificial factors, the land use and land resources quality varied continually. Zhongshan City where the zone had a typical feature of land use change and significant ecological effects was selected as a case. Applying the satellite images of Landsat-TM and the integrating techniques...
A tool for discovery of gait anomalies of elderly from motion sensor data is proposed. The gait of the user is captured with the motion capture system, which consists of tags attached to the body and sensors situated in the apartment. Position of the tags is acquired by the sensors and the resulting time series of position coordinates are analyzed with dynamic time warping and machine learning algorithms...
Supplier performance evaluation is a key issue of supply chain and is complicated since a variety of attributes must be considered. In this article, an integrated DEA-NN model is proposed. By taking advantages from both data envelopment analysis (DEA) and neural networks (NN), an application of the integrated DEA-NN method is given. The results indicate that the method is effective and applicable.
In this paper, we further develop the idea of subject specific mental tasks selection process as a necessary prerequisite in any EEG-based brain computer interface (BCI) application. While, in two previous researches we proved - using the EEG-extracted auto-regressive (AR) parameters and twelve different mental tasks -, the major gains one can obtain in tasks classification performance only by selecting...
This paper presents an Augmented Reality (AR) system for physical text documents that enable users to click a document. In the system, we track the relative pose between a camera and a document to overlay some virtual contents on the document continuously. In addition, we compute the trajectory of a fingertip based on skin color detection for clicking interaction. By merging a document tracking and...
This paper proposes a method that solves the problem of geometric calibration of microphone arrays. We consider a distributed system, in which each array is controlled by separate acquisition devices that do not share a common synchronization clock. Given a set of probing sources, e.g. loudspeakers, each array computes an estimate of the source locations using a conventional TDOA-based algorithm....
Efficient data mining and indexing is important for multimedia analysis and retrieval. In the field of large-scale video analysis, effective genre categorization plays an important role and serves one of the fundamental steps for data mining. Existing works utilize domain-knowledge dependent feature extraction, which is limited from genre diversification as well as data volume scalability. In this...
Motion estimation as well as the corresponding motion compensation is a core part of modern video coding standards, which highly improves the compression efficiency. On the other hand, motion information takes considerable portion of compressed bit stream, especially in low bit rate situation. In this paper, an efficient motion vector prediction algorithm is proposed to minimize the bits used for...
In a monaural polyphonic context, music transcription and specifically, multiple-F0 estimation systems have achieved promising results in the last decade. However, most of these systems present intermittent misses of pitch within a note or inaccurate definitions about onsets and offsets due to frame-by-frame analysis. In this paper, we propose a multiple-F0 estimation system which extracts a set of...
Indoor wireless localization has emerged as a key wireless network technology and has been used for a variety of applications. In this paper, we examine the possibility to use one RF-based fingerprint system for indoor wireless localization, and show that there is room for improvement in its location sensing approach. We propose an indoor wireless localization solution by improving a fingerprinting...
We propose a simple yet effective non-line-of-sight (NLOS) mitigation method that is incorporated into our earlier-developed iterative parallel projection method (IPPM) for collaborative position location. The proposed method handles NLOS range estimates based on the available a priori knowledge about NLOS condition and is demonstrated to significantly improve the localization accuracy in NLOS-dense...
This works illustrates the LAURA system, which performs localization, tracking and monitoring of patients hosted at nursing institutes by exploiting a wireless sensor network based on the IEEE 801.15.4 (Zigbee) standard. We focus on the indoor personal localization module, which leverages a method based on received signal strength measurements, together with a particle filter to perform tracking of...
Cooperative positioning is an emerging topic in wireless sensor networks and navigation. It can improve the positioning accuracy and coverage in GPS-challenged conditions such as inside tunnels, in urban canyons, and indoors. Different algorithms have been proposed relying on iteratively exchanging and updating positional information. For the purpose of computational complexity, network traffic, and...
RSS-based localization is considered a low-complexity algorithm with respect to other range techniques such as TOA or AOA. The accuracy of RSS methods depends on the suitability of the propagation models used for the actual propagation conditions. In indoor environments, in particular, it is very difficult to obtain a good propagation model. For that reason, we present a cooperative location algorithm...
Location estimation and tracking for the mobile stations have attracted a significant amount of attention in recent years. Moreover, different types of signal sources are considered available to provide the measurement inputs for location estimation and tracking. In this paper, a hybrid unified Kalman tracking (HUKT) technique is proposed to provide an integrated algorithm for precise location tracking...
Wireless location refers to obtaining the position information of a mobile subscriber in a cellular environment. Such positioning information is usually provided in terms of geographic coordinates of the mobile subscriber with respect to a geographic reference point. Wireless location finding has emerged as an essential feature of cellular systems and has many potential applications in areas such...
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