• Journal of Korea Multimedia Society
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• v.6 no.4
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• pp.685-697
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• 2003

The Web based multimedia programmes/courses are becoming widely available in recent years. Most of these courses focus on Behaviorist way of learning, which does not promote deep learning in any way. For Adults this approach further incapacitated, as it does not satisfy Andragogical needs. The search for Constructivist way of learning through the web applied to Indian conditions led to need for developing a curriculum development approach that would promote construction of knowledge through web based collaboration. This paper attempts to reengineer existing curriculum development processes and lays out a framework of‘Problem Based Online Learning (PBOL)’curriculum design. In this context, entire curriculum development life cycle is evolved and explained. This is a part of doctoral work (Ph.D), which is in progress and being undertaken by K.James Mathai, and guided of Dr.D.S.Karaulia.

• Journal of Educational Research in Mathematics
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• v.16 no.2
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• pp.115-138
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• 2006

The purpose of this paper is to investigate students' constructing similarities in the understanding the problem phase and the devising a plan phase of problem solving. the relation between similarities that students construct and how students construct similarities is researched through case study. Based on the results from the research, authors reached a conclusion as following. All of two students constructed surface similarities in the beginning of the problem solving process and responded to the context of the problem information sensitively. Specially student who constructed the similarities and the difference in terms of a specific dimension by using diagram for herself could translate the equation which used to solve the base problem or the experienced problem into the equation of the target problem solution. However student who understood globally the target problem being based on the surface similarity could not translate the equation that she used to solve the base problem into the equation of target problem solution.

• Journal of the Korean Chemical Society
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• v.47 no.4
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• pp.391-400
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• 2003

This study was performed the analysis of seven kinds of the hight school chemistry II textbooks based on the 6th curriculum. Particularly, inquiry activity part was analyzed by the three dimension framework which consists of inquiry content dimension, inquiry process dimension and inquiry context dimension. In the analysis of the inquiry content dimension of inquiry activities, the total number of themes in seven kinds of textbook was 212. And the number of inquiry activities in seven kinds of textbook was diverse: A textbook had 28, B textbook 25, C textbook 31, D textbook 35, E textbook 31, F textbook 29 and G textbook 33. As for the avaerage number of inquiry activities of each chapter, chapter I "Material Science" is 3.00(9.91${\%}$), chapter II "Atomic Structure and Periodic Table" 4.57(15.1${\%}$), chapter III "Chemical Bonding and Compound" 6.86(22.6${\%}$), chapter IV "State of Matter and Solution" 7.00(23.1${\%}$), chapter V "Chemical Reaction" 8.86(29.2${\%}$). For the analysis of inquiry process dimension, it follows in the order of 'observation and measuring (66.7${\%}$)', 'Interpreting data and formulating generalizations (26.5${\%}$)', 'seeing a problem and seeking ways to solve it (4.1%)', and 'building, testing and revising the theoretical model (2.7${\%}$)'. As for the analysis of the inquiry context dimension, the scientific context occupied 90.5${\%}$, the individual context 4.3${\%}$, the social context 0.9${\%}$, and the technical context 4.3${\%}$. It shows that the proportion of STS(Science-Technology-Society) related contents in inquiry activities was only 9.5${\%}$.

• Journal of KIISE:Software and Applications
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• v.27 no.7
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• pp.769-783
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• 2000

In this paper, in order to disambiguate Korean noun word sense, we define a local context and explain how to extract it from a raw corpus. Following the intuition that two different nouns are likely to have similar meanings if they occur in the same local context, we use, as a clue, the word that occurs in the same local context where the target noun occurs. This method increases the usability of extracted knowledge and makes it possible to disambiguate the sense of infrequent words. And we can overcome the data sparseness problem by extending the verbs in a local context. The sense of a target noun is decided by the maximum similarity to the clues learned previously. The similarity between two words is computed by their concept distance in the sense hierarchy borrowed from WordNet. By reducing the multiplicity of clues gradually in the process of computing maximum similarity, we can speed up for next time calculation. When a target noun has more than two local contexts, we assign a weight according to the type of each local context to implement the differences according to the strength of semantic restriction of local contexts. As another knowledge source, we get a co-occurrence information from dictionary definitions and example sentences about the target noun. This is used to support local contexts and helps to select the most appropriate sense of the target noun. Through experiments using the proposed method, we discovered that the applicability of local contexts is very high and the co-occurrence information can supplement the local context for the precision. In spite of the high multiplicity of the target nouns used in our experiments, we can achieve higher performance (89.8%) than the supervised methods which use a sense-tagged corpus.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.2
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• pp.68-77
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• 2003

The Least-Laxity First(or LLF) scheduling algorithm assigns the highest priority to a task with the least laxity, and has been proved to be optimal for a uni-processor and sub-optimal for a multi-processor. However, this algorithm Is Impractical to implement because laxity tie results in the frequent context switches among tasks. In this paper, a Modified Least-Laxity First on Multiprocessor(or MLLF/MP) scheduling algorithm is proposed to solve this problem, i.e., laxity tie results in the excessive scheduling overheads. The MLLF/MP is based on the LLF, but allows the laxity inversion. MLLF/MP continues executing the current running task as far as other tasks do not miss their deadlines. Consequently, it avoids the frequent context switches. We prove that the MLLF/MP is also sub-optimal in multiprocessor systems. By simulation results, we show that the MLLF/MP has less scheduling overheads than LLF.

• The Journal of the Acoustical Society of Korea
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• v.21 no.3
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• pp.285-292
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• 2002

One of the problems that should be solved in Text-To-Speech (TTS) is discontinuities at unit-joining points. To cope with this problem, a smoothing method using a low-pass filter is employed in this paper, In the proposed soothing method, a filter coefficient that controls the amount of smoothing is determined according to contort information to be synthesized. This method efficiently reduces both discontinuities at unit-joining points and artifacts caused by undesired smoothing. The amount of smoothing is determined with discontinuities around unit-joins points in the current synthesized speech and discontinuities predicted from context. The discontinuity predictor is implemented by CART that has context feature variables. To evaluate the performance of the proposed method, a corpus-based concatenative TTS was used as a baseline system. More than 6075 of listeners realized that the quality of the synthesized speech through the proposed smoothing is superior to that of non-smoothing synthesized speech in both naturalness and intelligibility.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4B
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• pp.397-402
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• 2004

In this paper, we have designed and simulated a new file transmission method. This method restricts memory copy and context switching happened in traditional file transmission. This method shows an improved performance than traditional method in network environment. When the UNIX/LINUX system that uses the existing file transfer technique transmits a packet to the remote system, a memory copy between the user and kernel space occurs over twice at least. Memory copy between the user and kernel space increase a file transmission time and the number of context switching. As a result, the existing file transfer technique has a problem of deteriorating the performance of file transmission. We propose a new algorithm for solving these problems. It doesn't perform memory copy between the user and kernel space. Hence, the number of memory copy and context switching is limited to the minimum. We have modified the network related source code of LINUX kernel 2.6.0 to analyzing the performance of proposed algorithm and implement new network system calls.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1779-1785
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• 2018

In this paper, we propose an error correction method to improve the accuracy of human activity recognition using sensor event data obtained by smart devices such as wearable and smartphone. In the context awareness through the smart device, errors inevitably occur in sensing the necessary context information due to the characteristics of the device, which degrades the prediction performance. In order to solve this problem, we apply Kalman filter's error correction algorithm to compensate the signal values obtained from 3-axis acceleration sensor of smart device. As a result, it was possible to effectively eliminate the error generated in the process of the data which is detected and reported by the 3-axis acceleration sensor constituting the time series data through the Kalman filter. It is expected that this research will improve the performance of the real-time context-aware system to be developed in the future.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.117-124
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• 2014

Cluttered background is a major obstacle in developing salient object detection and tracking system for mobile device captured natural scene video frames. In this paper we propose a context aware feature vector selection model to provide an efficient noise filtering by machine learning based classifiers. Since the context awareness for feature selection is achieved by searching nearest neighborhoods, known as NP hard problem, we apply a fast approximation method with complexity analysis in details. Separability enhancement in feature vector space by adding the context aware feature subsets is studied rigorously using principal component analysis (PCA). Overall performance enhancement is quantified by the statistical measures in terms of the various machine learning models including MLP, SVM, Naïve Bayesian, CART. Summary of computational costs and performance enhancement is also presented.

• School Mathematics
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• v.9 no.1
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• pp.13-28
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• 2007

Division of fractions can be categorized as measurement division, partitive or sharing division, the inverse of multiplication, and the inverse of Cartesian product. Division algorithm for fractions has been interpreted with manipulative aids or models mainly in the contexts of measurement division and partitive division. On the contrary, there are few interpretations for the context of the inverse of a Cartesian product. In this paper the significance and the limits of existing interpretations of division of fractions in the context of the inverse of a Cartesian product were discussed. And some new easier interpretations of division algorithm in the context of a Cartesian product are developed. The problem to determine the length of a rectangle where the area and the width of it are known can be solved by various approaches: making the width of a rectangle be equal to one, making the width of a rectangle be equal to some natural number, making the area of a rectangle be equal to 1. These approaches may help students to understand the meaning of division of fractions and the meaning of the inverse of the divisor. These approaches make the inverse of a Cartesian product have many merits as an introductory context of division algorithm for fractions.