Information Processing Society of Japan (IPSJ) has announced the Computing Curriculum Standard J07 which is compatible with the Computing Curricula 2005 (CC2005) Series proposed in the United States. Both J07 and CC2005 are composed of five major domains, CS, CE, SE, IS and IT, each of which is developed by a different community so that the relationship among these domains is not clear. In this paper, we analyze each body of knowledge (BOK) of the domains and map them into the ICT common body of knowledge (ICTBOK) which we have proposed in our previous paper. We also analyze Japan Information Technology Engineers Examination (JITEE) whose syllabus is published for each of 12 examination categories provided by the Japanese government. We estimate the degree of importance and the requirement level in terms of the 155 ICTBOK areas for each J07 domain and JITEE examination category by utilizing the mapping. Moreover we estimate the similarity and the difference among them. As a result, the relationship among J07 domains and JITEE examination categories is clarified.
With an aim to realizing highly accurate position estimation, we propose in this paper a method for efficiently and accurately detecting the 3D positions and poses of traditional fiducial markers with black frames in high-resolution images taken by ordinary web cameras. Our tracking method can be efficiently executed utilizing GPGPU computation, and in order to realize this, we devised a connected-component labeling method suitable for GPGPU execution. In order to improve accuracy, we devised a method for detecting 2D positions of the corners of markers in subpixel accuracy. We implemented our method in Java and OpenCL, and we confirmed that the proposed method provides better detection and measurement accuracy, and recognizing from high-resolution images is beneficial for improving accuracy. We also confirmed that our method is more than two times as fast as the existing method with CPU computation.
Recently user-generated content (UGC) has become major content of the Web and one of the most important factors of UGC is who has generated it. Even if the same information is disseminated, its credibility is different according to its author. Typically, authors are characterized by reputation systems. Although cloud computing enables both information dissemination and reputation aggregation with scalability, it is better to minimize the use of clouds due to cost problems. In this paper, we propose to apply the circular board method based on Chord to user centric media to disseminate information and aggregate reputation efficiently in a P2P manner. Its ring topology makes it possible to effectively collect the reputation from users at the same time when each piece of UGC passes through user terminals. The results of simulations reveal the feasibility of P2P information dissemination and reputation aggregation and provide insights about trade-offs between network resource consumed and time required for information dissemination and reputation aggregation.
Yosenabe is one of Nikoli's pencil puzzles, which is played on a rectangular grid of cells. Some of the cells are colored gray, and two gray cells are considered connected if they are adjacent vertically or horizontally. A set of connected gray cells is called a gray area. Some of the gray areas are labeled by numbers, and some of the non-gray cells contain circles with numbers. The object of the puzzle is to draw arrows, vertically or horizontally, from all circles to gray areas so that (i) the arrows do not bend, and do not cross other circles or lines of other arrows, (ii) the number in a gray area is equal to the total of the numbers of the circles which enter the gray area, and (iii) gray areas with no numbers may have any sum total, but at least one circle must enter each gray area. It is shown that deciding whether a Yosenabe puzzle has a solution is NP-complete.
Since Hamming distances can be calculated by bitwise computations, they can be calculated with a lighter computational load than L2 distances. Similarity searches can therefore be performed faster in Hamming distance space. On the other hand, the arrangement of hyperplanes induces a transformation from the feature vectors into feature bit strings, which are elements of the Hamming distance space. This transformation is a type of locality-sensitive hashing that has been attracting attention as a way of performing approximate similarity searches at high speed. Supervised learning of hyperplane arrangements enables us to devise a method that transforms the higher-dimensional feature vectors into feature bit strings that reflect the information about the labels applied to feature vectors. In this paper, we propose a supervised learning method for hyperplane arrangements in feature space that uses a Markov chain Monte Carlo (MCMC) method. We consider the probability density functions used during learning and evaluate their performance. We also consider the sampling method for data pairs needed in learning and evaluate its performance. The performance evaluations indicate that the accuracy of this learning method, when using a suitable probability density function and sampling method, is greater than those of existing learning methods.
We propose a novel video summarization approach that takes the mass quantity of nursery school surveillance videos as input and produces short daily video digests for children. The proposed approach makes full use of a distance metric, which is learned using a novel learning algorithm called the adaptive large margin nearest neighbor (ALMNN), and can properly measure the similarity between video clips. The learned distance metric is combined with supervised classification and unsupervised clustering to categorize daily raw surveillance videos into individual event categories. The final digest is constructed by selecting representative video clips that belong to individual event categories. Digests generated using our approach cover and reflect the various activities of children in nursery schools. They are of interest to parents, and they also enable easy access to mass quantities of daily surveillance video data. We implemented the approach as a practical system in a real nursery school environment and assessed its performance.
In this paper, we present a novel method to extract keyposes from motion-capture data streams. It adaptively extracts keyposes in response to the motion characteristics of a given data stream. We adopt an approach to detect local minima in the temporal variation of motion speed. In the developed algorithm, the intensity of each local minimum is first evaluated by using a set of signals; it is obtained by applying a set of low-pass filters to a one-dimensional motion-speed data stream. The cut-off frequencies of the filters are distributed over a wide frequency range. By adding up the speed-descent values of each local minimum over all the signals, we exhaustively obtain the information on its intensity provided at all the time-scale levels covered by a given data stream. Then, the obtained intensity values are categorized by a clustering algorithm; the local minima categorized as those of little significance are deleted and the remaining ones are fixed as those giving keyposes. Experimental results showed that the present method provided results comparable to the best of those given by the methods previously proposed. This was achieved without readjusting the values of parameters used in the algorithm. Readjustment was indispensable for the other methods to obtain good results.
In this paper, we set out to define the out together feeling as the experience when two people at different locations feel as though they are together. In other words, it makes a pair of users, one outdoors and the other indoors, feel as if they are both outdoors together. To determine a set of interaction methods to enable indoor and outdoor users to interact and share the out together feeling, we carried out preliminary experiments to observe the basic elements of communication between people who are really together. We then carried out an experiment in which indoor and outdoor users communicated via a videophone and observed the interaction patterns of each user as they attempted to achieve a given goal. From the analysis of these data, we defined three basic elements that are required to achieve the out together feeling: (1) both users can freely peruse the outdoor user's surroundings, (2) know where each other is looking, (3) and can communicate non-verbally using gestures. Using these basic elements, we designed and implemented a system called WithYou. This consists of two subsystems: a wearable system for the outdoor user and an immersive space for the indoor user. The indoor user wears a head-mounted display (HMD) and watches video from a pan-and-tilt camera mounted on the outdoor user's chest. Thus, the indoor user can look around by simply turning their head. The orientation of the outdoor user's face is also displayed on the HMD screen to indicate where they are looking. We experimentally evaluated the system and, based on an analysis of the subjects' response to questionnaires and video recordings, we were able to assess the level to which the out together feeling was achieved.
In this paper, we will present the results and implications of analyses of the dialogue process and its consequences by conducting a case study of the workshop using the World Café as a collective dialogue method. The workshop addresses a new way of working in a Japanese company after the earthquake on March 11, 2011. We investigated both dialogue processes quantitatively and qualitatively, the level of recognition of the workshop theme, and participants' actions and their effects after the workshop. The results indicate that the more active the quantitative dialogue process is, the more positively the participants feel about the quality of the dialogue process and the more actions the participant takes. To understand the dialogue process in a workshop could be useful for practitioners and researchers to develop a facilitation method or supporting system that could promote better dialogues leading to better actions and effects.
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July 31, 2017 Due to the end of the Yahoo!JAPAN OpenID service, My J-STAGE will end the support of the following sign-in services with OpenID on August 26, 2017: -Sign-in with Yahoo!JAPAN ID -Sign-in with livedoor ID * After that, please sign-in with My J-STAGE ID.
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May 18, 2016 We have released “J-STAGE BETA site”.
May 01, 2015 Please note the "spoofing mail" that pretends to be J-STAGE.