• Journal of Communications and Networks
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• v.17 no.6
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• pp.568-581
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• 2015

Predicting locations of users with portable devices such as IP phones, smart-phones, iPads and iPods in public wireless local area networks (WLANs) plays a crucial role in location management and network resource allocation. Many techniques in machine learning and data mining, such as sequential pattern mining and clustering, have been widely used. However, these approaches have two deficiencies. First, because they are based on profiles of individual mobility behaviors, a sequential pattern technique may fail to predict new users or users with movement on novel paths. Second, using similar mobility behaviors in a cluster for predicting the movement of users may cause significant degradation in accuracy owing to indistinguishable regular movement and random movement. In this paper, we propose a novel fusion technique that utilizes mobility rules discovered from multiple similar users by combining clustering and sequential pattern mining. The proposed technique with two algorithms, named the clustering-based-sequential-pattern-mining (CSPM) and sequential-pattern-mining-based-clustering (SPMC), can deal with the lack of information in a personal profile and avoid some noise due to random movements by users. Experimental results show that our approach outperforms existing approaches in terms of efficiency and prediction accuracy.

• Journal of Korea Multimedia Society
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• v.8 no.7
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• pp.906-915
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• 2005

In this paper we propose content based image retrieval method using sequential clustering and projection information. Proposed method uses the mean of color in clustered color regions by sequential clustering and the projection information in each clustered color regions, which combines spatial information with color information in images efficiently. The experimental results showed that the proposed method retrieval efficiency improved 11.6 percent over conventional methods. In addition, the proposed method robustly tolerates large changes in appearance and shape caused by changes in viewing positions, camera zooms, etc.

• International Journal of Contents
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• v.16 no.1
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• pp.44-56
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• 2020

The purpose of this study was to examine how the presentation mode (sequential- vs. simultaneous-mode) of information influences its evaluation. Three experiments revealed the interaction effect between the presentation mode and the valence of the product information. When respondents read about the positive aspects of the product, the evaluation was higher in the simultaneous presentation mode than in the sequential presentation mode. For negative product information, respondents' evaluation was higher in the sequential presentation mode than in the simultaneous presentation mode. The simultaneous presentation mode intensified the impact of the information valence on evaluation. This study proposed that the sequential and the simultaneous presentation modes prime high and low construal levels, respectively. The mediation analysis provides support for such a prediction. Finally, the mediating effect of construal levels in evaluation was shown to disappear when respondents focused on the product information for a longer duration, while the mediation effect remained when the response time was short.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.43-49
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• 2018

In this paper, we propose a displacement measurement method based on deep learning using image data obtained from tensile tests of a material specimen. We focus on the fact that the sequential images during the tension are generated and the displacement of the specimen is represented in the image data. So, we designed sample generation model which makes sequential images of specimen. The behavior of generated images are similar to the real specimen images under tensile force. Using generated images, we trained and validated our model. In the deep neural network, sequential images are assigned to a multi-channel input to train the network. The multi-channel images are composed of sequential images obtained along the time domain. As a result, the neural network learns the temporal information as the images express the correlation with each other along the time domain. In order to verify the proposed method, we conducted experiments by comparing the deformation measuring performance of the neural network changing the displacement range of images.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.220-223
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• 2002

The digital logic systems(DLS) is classified into digital combinational logic systems(CDLS) and digital sequential logic systems(SDLS). This paper presents a method of constructing the digital sequential logic systems without feedback. Firstly we assign all elements in Finite Fields to P-valued digit codes using mathematical properties of Finine Fields. Also, we discuss the operarional properties of the building block T-gate that is used to realizing digital sequential logic systems over Finite Fields. Then we realize the digital sequential logic systems without feedback. This digital sequential logic systems without feedback is constructed ny following steps. Firstly, we assign the states in the state-transition diagram to state P-valued digit dodo, then we obtain the state function and predecessor table that is explaining the relationship between present state and previous states. Next, we obtained the next-state function and predecessor table. Finally, we realize the circuit using T-gate and decoder.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.880-883
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• 2005

This paper presents a method of constructing the sequential logic machines over finite fields(or galois fields). The proposed the sequential logic machines is constructed by as following. First of all, we obtain the linear characteristics between present state and next state based on mathematical properties of finite fields and sequential logic machines. Next, we realize the sequential logic machines over finite field GF(P) using above linear characteristics and characteristic polynomial that expressed using by matrix.

• Language and Information
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• v.9 no.1
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• pp.35-49
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• 2005

Lakoff(1986) claim that sequential fading alone suffices to sanction ATB violations cannot be supported in Korean verbal coordination of TP, since extraction from the conjunction of TP in Korean is impossible regardless of whether the conjuncts are interpreted sequentially or non-sequentially. However, ATB violations are allowed in the coordination of Non-TP, only when the conjuncts are interpreted sequentially. 1 will argue that Non-TP, in coordination are ambiguous between a conjunct and adjunct analysis. Furthermore, a claim made here is that the distinction between the sequential and non-sequential reading in Non-TP coordination is a distinction made by syntax, while the sequential vs. non-sequential reading in TP coordination is derived from semantics or pragmatics.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.10
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• pp.1354-1360
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• 2013

In transmission system, reclosing scheme is very useful method to improve continuity of power supply and reliability of system. Especially, high speed reclosing which is used generally in transmission systems has a benefit improving transient stability. However, the reclosing can jeopardize the stability under the condition having high difference of voltage phase angle between both ends. Thus, this paper proposes optimal sequential reclosing scheme to improve transient stability due to reclosing operation. The optimal sequential reclosing is that each phase is closed sequentially considering transient energy. In this paper, 345kV and 154kV transmission system is modeled using EMTP (ElectroMagnetic Transient Program) to verify the performance and effectiveness of optimal sequential reclosing on transient stability. Also, Integral Square Error(ISE) method is used to assess the transient stability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2680-2700
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• 2017

Finite field arithmetic over GF($2^m$) is used in a variety of applications such as cryptography, coding theory, computer algebra. It is mainly used in various cryptographic algorithms such as the Elliptic Curve Cryptography (ECC), Advanced Encryption Standard (AES), Twofish etc. The multiplication in a finite field is considered as highly complex and resource consuming operation in such applications. Many algorithms and architectures are proposed in the literature to obtain efficient multiplication operation in both hardware and software. In this paper, a modified serial multiplication algorithm with interleaved modular reduction is proposed, which allows for an efficient realization of a sequential polynomial basis multiplier. The proposed sequential multiplier supports multiplication of any two arbitrary finite field elements over GF($2^m$) for generic irreducible polynomials, therefore made versatile. Estimation of area and time complexities of the proposed sequential multiplier is performed and comparison with existing sequential multipliers is presented. The proposed sequential multiplier achieves 50% reduction in area-delay product over the best of existing sequential multipliers for m = 163, indicating an efficient design in terms of both area and delay. The Application Specific Integrated Circuit (ASIC) and the Field Programmable Gate Array (FPGA) implementation results indicate a significantly less power-delay and area-delay products of the proposed sequential multiplier over existing multipliers.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.457-462
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• 2006

Sequential Pattern Mining is the mining approach which addresses the problem of discovering the existent maximal frequent sequences in a given databases. In the daily and scientific life, sequential data are available and used everywhere based on their representative forms as text, weather data, satellite data streams, business transactions, telecommunications records, experimental runs, DNA sequences, histories of medical records, etc. Discovering sequential patterns can assist user or scientist on predicting coming activities, interpreting recurring phenomena or extracting similarities. For the sake of that purpose, the core of sequential pattern mining is finding the frequent sequence which is contained frequently in all data sequences. Beside the discovery of frequent itemsets, sequential pattern mining requires the arrangement of those itemsets in sequences and the discovery of which of those are frequent. So before mining sequences, the main task is checking if one sequence is a subsequence of another sequence in the database. In this paper, we implement the subsequence matching method as the preprocessing step for sequential pattern mining. Matched sequences in our implementation are the normalized sequences as the form of number chain. The result which is given by this method is the review of matching information between input mapped sequences.