45778067
Children's Use of New Technology for Picture-Taking
Photographs are often associated with children: People have children, they take pictures of them. We don't very often think about children as picture-takers, but our recent work has moved us in that direction. As part of an interest in children's use of new technology, we have studied children's picture-taking with new camera, computer, and Web technology. In this article, we discuss why and how children take pictures. We also discuss the issue of photofakery.
31784785
Tiger: Educational Research in the Age of the Internet
20360552
Internet attitudes and Internet use: some surprising findings from the HomeNetToo project
HomeNetToo is a longitudinal field study to examine the antecedents and consequences of home Internet use in low-income families. Among the antecedents considered are attitudes about the Internet and their ability to predict Internet use. Participants in the project were 117 adults who completed attitude measures at pre-trial, 3 months, 9 months and post-trial (16 months) and had their Internet use automatically recorded. Ethnographic accounts of their experiences with the Internet were also obtained. Findings indicate that attitudes about privacy and reliability of information on the Internet predict Internet use, but not as expected. Participants who believed less in privacy and reliability of information used the Internet more, even after the contributions of demographic characteristics (race and age), pre-trial experience using the Internet, and actual Internet use during the preceding time period were considered. Attitudes about the potential harm to children and health from Internet use predicted less use. Implications for efforts to reduce the digital divide, the importance of gathering both quantitative and qualitative data, and directions for future research are discussed.
27884919
Writing photo captions for the Web
Photographs are rarely self-sufficient. They need captions. A caption tells us something about the person or thing photographed, also something about the photographer. In this article, we discuss how to write photo captions for the Web. We provide examples from adultso and childrenos work.
14081236
Potential Advantages of Semantic Web for Internet Commerce
Past decade saw much hype in the area of information technology. The emerging of semantic Web makes us ask if it is another hype. This paper focuses on its potential application in Internet commerc ...
10152279
An on-chip IP address lookup algorithm
This paper proposes a new data compression algorithm to store the routing table in a tree structure using very little memory. This data structure is tailored to a hardware design reference model presented in this paper. By exploiting the low memory access latency and high bandwidth of on-chip memory, high-speed packet forwarding can be achieved using this data structure. With the addition of pipeline in the hardware, IP address lookup can only be limited by the memory access speed. The algorithm is also flexible for different implementation. Experimental analysis shows that, given the memory width of 144 bits, our algorithm needs only 400kb memory for storing a 20k entries IPv4 routing table and five memory accesses for a search. For a 1M entries IPv4 routing table, 9Mb memory and seven memory accesses are needed. With memory width of 1,068 bits, we estimate that we need 100Mb memory and six memory accesses for a routing table with 1M IPv6 prefixes.
37471711
Coarsening Classification Rules on Basis of Granular Computing
The task of classification, as a well-studied field of machine learning and data mining, has two main purposes: describing the classification rules in the training dataset and predicting the unseen new instances in the testing dataset. Normally, one expects a high accuracy for precisely descriptive use. However, a higher accuracy is intended to generate longer rules, which are not easy to understand, and may overfit the training instances. This motivates us to propose the approach of coarsening the classification rules, namely, reasonably sacrifice the accuracy of description in a controlled level in order to improve the comprehensibility and predictability. The framework of granular computing provides us a formal and systematic methodology for doing this. In this paper, a modified PRISM classification algorithm is presented based on the framework of granular computing.
38902380
Construction Algorithm of Principal Curves in the Sense of Limit
Principal curves have been defined as self-consistent, smooth, one-dimensional curves which pass through the middle of a multidimensional data set. They are nonlinear generalization of the first Principal Component. In this paper, we take a new approach by defining principal curves as continuous curves based on the local tangent space in the sense of limit. It is proved that this new principal curves not only satisfy the self-consistent property, but also are the unique existence for any given open covering. Based on the new definition, a new practical algorithm for constructing principal curves is given. And the convergence properties of this algorithm are analyzed. The new construction algorithm of principal curves is illustrated on some simulated data sets.
15790608
Clustering High-Dimensional Data with Low-Order Neighbors
Density-based and grid-based clustering are two main clustering approaches. The former is famous for its capability of discovering clusters of various shapes and eliminating noises, while the latter is well known for its high speed. Combination of the two approaches seems to provide better clustering results. To the best of our knowledge, however, all existing algorithms that combine density-based clustering and grid-based clustering take cells as atomic units, in the sense that either all objects in a cell belong to a cluster or no object in the cell belong to any cluster. This requires the cells to be small enough to ensure the fine resolution of results. In high-dimensional spaces, however, the number of cells can be very large when cells are small, which would make the clustering process extremely costly. On the other hand, the number of neighbors of a cell grows exponentially with the dimensionality of datasets, which makes the complexity increase further. In this paper, we present a new approach that takes objects (or points) as the atomic units, so that the restriction of cell size can be relaxed without degrading the resolution of clustering results. In addition, a concept of ith-order neighbors is introduced to avoid considering the exponential number of neighboring cells. By considering only low-order neighbors, our algorithm is very efficient while losing only a little bit of accuracy. Experiments on synthetic and public data show that our algorithm can cluster high-dimensional data effectively and efficiently.