• Journal of applied mathematics & informatics
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• v.8 no.2
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• pp.305-326
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• 2001

We introduce a class of multilevel recursive incomplete LU preconditioning techniques (RILUM) for solving general sparse matrices. This techniques is based on a recursive two by two block incomplete LU factorization on the coefficient martix. The coarse level system is constructed as an (approximate) Schur complement. A dynamic preconditioner is obtained by solving the Schur complement matrix approximately. The novelty of the proposed techniques is to solve the Schur complement matrix by a preconditioned Krylov subspace method. Such a reduction process is repeated to yield a multilevel recursive preconditioner.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.11a
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• pp.31-37
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• 2006

The objective of this research is to select the most effective technique from task related techniques(motion & time study, job redesign, physical environment improvement) for improving work efficiency in shipbuilding enterprise. This study consists of several principal steps. The first step is to design critical criteria in evaluating work efficiency in shipbuilding enterprises. The second step is to develop sub-criteria of the critical criteria. The third step is to develop a four level AHP(Analytic Hierarchy Process)structure using the critical criteria, sub-criteria and techniques from task related techniques. The fourth step is to develop the pairwise comparison matrix by each level of AHP structure, which was based on survey data collected at the H heavy industry. And the last step is to select the most effective technique from task related techniques using AHP analysis. The result of AHP analysis has shown clear difference in priority among task related techniques in terms of work efficiency of the shipbuilding enterprise: The reduction of normal time has more importance than the reduction of allowance time, motion & time study techniques are most important for the reduction of normal time, physical environment improvement is most important for the reduction of allowance time as well.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.2
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• pp.67-74
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• 2007

The objective of this research is to select the most effective technique among task related techniques(motion & time study, job redesign, physical environment improvement) for improving work efficiency in shipbuilding enterprise. This study consists of several principal steps. The first step is to design critical criteria in evaluating work efficiency in ship-building enterprises. The second step is to develop sub-criteria of the critical criteria. The third step is to develop a four level AHP(Analytic Hierarchy Process) structure using the critical criteria, sub-criteria and techniques among task related techniques. The fourth step is to develop the pairwise comparison matrix at each level of AHP structure, which was based on survey data collected at the H heavy industry. And the last step is to select the most effective technique among task related techniques using AHP analysis. The result of AHP analysis has shown clear difference in priority among task related techniques in terms of work efficiency of the shipbuilding enterprise: The reduction of normal time is more important than the reduction of allowance time in improving of the work efficiency. Motion & time study is the most important technique for the reduction of normal time, and physical environment improvement is the most important technique for the reduction of allowance time as well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.6
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• pp.647-666
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• 2009

Multiple-input multiple-output (MIMO) multiplexing is an attractive technology that increases the channel capacity without requiring additional spectral resources. The design of low complexity and high performance detection algorithms capable of accurately demultiplexing the transmitted signals is challenging. In this technical survey, we introduce the state-of-the-art MIMO detection techniques. These techniques are divided into three categories, viz. linear detection (LD), decision-feedback detection (DFD), and tree-search detection (TSD). Also, we introduce the lattice basis reduction techniques that obtain a more orthogonal channel matrix over which the detection is done. Detailed discussions on the advantages and drawbacks of each detection algorithm are also introduced. Furthermore, several recent author contributions related to MIMO detection are revisited throughout this survey.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.662-668
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• 2015

This paper presents an improved predictive control of an induction machine fed by a matrix converter using N-switching vectors as the control action during a complete sampling period of the controller. The conventional model predictive control scheme based matrix converter uses a single switching vector over the same period which introduces high torque ripple. The proposed switching scheme for a matrix converter based model predictive control of an induction machine drive selects the appropriate switching vectors for control of electromagnetic torque with small variations of the stator flux. The proposed method can reduce the ripple of the electrical variables by selecting the switching state as well as the method used in the space vector modulation techniques. Simulation results are presented to verify the effectiveness of the improved predictive control strategy for induction machine fed by a matrix converter.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.61-68
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• 2012

Recommender Systems have gained much popularity among researchers and is applied in a number of applications. The exponential growth of users and products poses some key challenges for recommender systems. Recommender Systems mostly suffer from scalability and accuracy. The accuracy of Recommender system is somehow inversely proportional to its scalability. In this paper we proposed a Context Aware Hybrid Recommender System using matrix reduction for Hybrid model and clustering technique for predication of item features. In our approach we used user item-feature rating, User Demographic information and context information i.e. specific time and day to improve scalability and accuracy. Our Algorithm produce better results because we reduce the dimension of items features matrix by using different reduction techniques and use user demographic information, construct context aware hybrid user model, cluster the similar user offline, find the nearest neighbors, predict the item features and recommend the Top N- items.

• Steel and Composite Structures
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• v.52 no.4
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• pp.487-499
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• 2024

The primary objective of this study is to analyze the free vibration behavior of a sandwich cylindrical shell with a defective core and wavy carbon nanotube (CNT)-enhanced face sheets, utilizing the three-dimensional theory of elasticity. The intricate equations of motion for the structure are solved semi-analytically using the generalized differential quadrature method. The shell structure consists of a damaged isotropic core and two external face sheets. The distributions of CNTs are either functionally graded (FG) or uniform across the thickness, with their mechanical properties determined through an extended rule of mixture. In this research, the conventional theory regarding the mechanical effectiveness of a matrix embedding finite-length fibers has been enhanced by introducing tube-to-tube random contact. This enhancement explicitly addresses the progressive reduction in the tubes' effective aspect ratio as the filler content increases. The study investigates the influence of a damaged matrix, CNT distribution, volume fraction, aspect ratio, and waviness on the free vibration characteristics of the sandwich cylindrical shell with wavy CNT-reinforced face sheets. Unlike two-dimensional theories such as classical and the first shear deformation plate theories, this inquiry is grounded in the three-dimensional theory of elasticity, which comprehensively accounts for transverse normal deformations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.241-251
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• 1998

The purpose of this study is to evaluate the relative importance of seven JIT operational techniques in Domestic industries. These techniques are used to improve manufacturing effectiveness and efficiency such as : Setup time reduction, Kanban, Multi-functional worker, U type layout, Andon(line stop), Atonomation, and Smoothing production. The new analytic hierarchy process(AHP) model is used in order to evaluate the relative importance of the seven JIT operational techniques which are used to increase the manufacturing effectiveness and efficiency. To aggregate the multi-divisions priorities, in this paper, we suggest a way which decision maker can exclude outlier matrix from group by using the concept of the compatibility in AHP.

• Journal of the Korean Institute of Telematics and Electronics
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• v.11 no.2
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• pp.1-4
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• 1974

Matrix inversion is very inefficient for computing direct solutions of the large sparse systems of linear equations that arise in many network problems. This paper describes some computer programming techniques for taking advantage of the sparsity of the admittance matrix. with this method, direct solutions are computed from sparse matrix. It is Possible to gain a significant reduction in computing time, memory and round-off emir[r. Retails of the method, numerical examples and programming are given.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.230-240
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• 2022

Sharing of online videos via internet is an emerging and important concept in different types of applications like surveillance and video mobile search in different web related applications. So there is need to manage personalized web video retrieval system necessary to explore relevant videos and it helps to peoples who are searching for efficient video relates to specific big data content. To evaluate this process, attributes/features with reduction of dimensionality are computed from videos to explore discriminative aspects of scene in video based on shape, histogram, and texture, annotation of object, co-ordination, color and contour data. Dimensionality reduction is mainly depends on extraction of feature and selection of feature in multi labeled data retrieval from multimedia related data. Many of the researchers are implemented different techniques/approaches to reduce dimensionality based on visual features of video data. But all the techniques have disadvantages and advantages in reduction of dimensionality with advanced features in video retrieval. In this research, we present a Novel Intent based Dimension Reduction Semi-Supervised Learning Approach (NIDRSLA) that examine the reduction of dimensionality with explore exact and fast video retrieval based on different visual features. For dimensionality reduction, NIDRSLA learns the matrix of projection by increasing the dependence between enlarged data and projected space features. Proposed approach also addressed the aforementioned issue (i.e. Segmentation of video with frame selection using low level features and high level features) with efficient object annotation for video representation. Experiments performed on synthetic data set, it demonstrate the efficiency of proposed approach with traditional state-of-the-art video retrieval methodologies.