A survey about the information needs of elderly people could find out the information required to address the needs of the aged in a community. Analyzing data collected from 600 elderly people through field investigat...
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A survey about the information needs of elderly people could find out the information required to address the needs of the aged in a community. Analyzing data collected from 600 elderly people through field investigation with a questionnaire in a rural community in central China, the results show that the preferred information format of the majority of aged people is audio and/or visual information product, especially audio product. Most of the aged people stated that they were in need of healthy and medical non-educational audio information products. The survey maybe lead to improved and expanded information services for respondents who are short of such services, including Public broadcasting services, extending the audiovisual collection, loaning audiovisuals, religious faith audiovisuals and others providing needed information to them. In summary, this paper assembles views on what the elderly people currently need to be helped by both practitioners and researchers in the elderly people services domain.
Over years, virtual backbone has attracted lots of attentions as a promising approach to deal with the broadcasting storm problem in wireless networks. One popular way to construct a quality virtual backbone is to sol...
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Over years, virtual backbone has attracted lots of attentions as a promising approach to deal with the broadcasting storm problem in wireless networks. One popular way to construct a quality virtual backbone is to solve the minimum connected dominating set problem. However, a virtual backbone computed in this way is not resilient against topology change since the induced graph by the connected dominating set is one-vertex-connected. As a result, the minimum k-connected m-dominating set problem is introduced to construct a fault-tolerant virtual backbone. Currently, the best known approximation algorithm for the problem in unit disk graph assumes k ≤ 3 and m ≥ 1 and its performance ratio is 280 when k = m = 3. In this paper, we use a classical result from graph theory, Tutte decomposition, to design a new approximation algorithm for the problem in unit disk graph for k ≤ 3 and m ≥ 3. In particular, the algorithm features with much simpler structure and much smaller performance ratio, e.g. nearly 66 when k = m = 3. We also conduct simulation to evaluate the performance of our algorithm.
Misdiagnosis of epilepsy, even by experienced clinicians, can cause exposure of patients to medical procedures and treatments with potential complications. Moreover, diagnostic delays (for 7 to 10 years on average) im...
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ISBN:
(纸本)9781467379847
Misdiagnosis of epilepsy, even by experienced clinicians, can cause exposure of patients to medical procedures and treatments with potential complications. Moreover, diagnostic delays (for 7 to 10 years on average) impose economic burden at individual and population levels. In this paper, a seizure classification framework of epileptic and non-epileptic events from multi-channel EEG data is proposed. In contrast to relevant studies found in the literature, in this study, the non-epileptic class consists of two types of paroxysmal episodes of loss of consciousness, namely the psychogenic non-epileptic seizure (PNES) and the vasovagal syncope (VVS). EEG signals are represented in the spectral-spatial-temporal domain. A tensor-based approach is employed to extract signature features to feed the classification models. TUCKER decomposition is applied to learn the essence of original, high-dimensional domain of feature space and extract a multilinear discriminative subspace. The classification models were evaluated on EEG epochs from 11 subjects in an inter-subject cross-validation setting and achieved an accuracy of 96%.
As an important resource for machine translation and cross-language information retrieval, collecting large-scale parallel corpus has been paid wide attention. With the development of the Internet, researchers begin t...
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Combining short instruction sequences originated only from existing code pieces, Return Oriented Programming (ROP) attacks can bypass the code-integrity effort model. To defeat this kind of attacks, current approaches...
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This paper calculates the carbon emissions from energy consumption of 30 provinces in China through 2000-2010, and research correlation of factors such as regional economic gap and regional characteristics of carbon e...
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Image segmentation problem is a fundamental task and process in computer vision and image processing applications. It is well known that the performance of image segmentation is mainly influenced by two factors: the s...
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Image segmentation problem is a fundamental task and process in computer vision and image processing applications. It is well known that the performance of image segmentation is mainly influenced by two factors: the segmentation approaches and the feature presentation. As for image segmentation methods, clustering algorithm is one of the most popular approaches. However, most current clustering-based segmentation methods exist some problems, such as the number of regions of image have to be given prior, the different initial cluster centers will produce different segmentation results and so on. In this paper, we present a novel image segmentation approach based on DP clustering algorithm. Compared with the current methods, our method has several improved advantages as follows: 1) This algorithm could directly give the cluster number of the image based on the decision graph; 2) The cluster centers could be identified correctly; 3) We could simply achieve the hierarchical segmentation according to the applications requirement. A lot of experiments demonstrate the validity of this novel segmentation algorithm.
作者:
Hu, HeDu, XiaoyongSchool of Information
Renmin University of China Key Laboratory of Data Engineering and Knowledge Engineering MoE No. 59 Zhongguancun St. Beijing100872 China
Online tagging is crucial for the acquisition and organization of web knowledge. We present TYG (Tag-as-You-Go) in this paper, a web browser extension for online tagging of personal knowledge on standard web pages. We...
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It is insufficient to search temporal text by only focusing on either time attribute or keywords today as we pay close attention to the evolution of event with time. Both temporal and textual constraints need to be co...
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ISBN:
(纸本)9781450325981
It is insufficient to search temporal text by only focusing on either time attribute or keywords today as we pay close attention to the evolution of event with time. Both temporal and textual constraints need to be considered in one single query, called Top-k Interval Keyword Query (TIKQ). In this paper, we presents a cloud-based system named INK that supports efficient execution of TIKQs with appropriate effectiveness on Hadoop and HBase. In INK, an Adaptive Index Selector (AIS) is devised to choose the better execution plan for various TIKQs adaptively based on the proposed cost model, and leverage two novel hybrid index modules (TriI and IS-Tree) to combine keyword and interval filtration seamlessly.
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