• Journal of Multimedia Information System
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• v.8 no.4
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• pp.221-232
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• 2021

One bottleneck of Bengali to Hindi transfer based machine translation system is the translation of suffixes of noun. The appropriate translation of a nominal suffix often depends on the semantic role of the corresponding noun chunk in the sentence. With the availability of a high performance Bengali morphological analyzer and a basic Bengali parser it is possible to identify the role of each noun chunk. This information may be used for building rules for translating the ambiguous nominal suffixes. As there are some similarities between the uses of Bengali and Hindi nominal suffixes we find that the rules may be identified by linguistically analyzing corpus data. In this paper, we identify rules for the ambiguous four Bengali nominal suffixes from corpus data and evaluate their performances. This set of rules is able to resolve a majority of the nominal suffix ambiguities in Bengali to Hindi transfer based machine translation system. Using the rules, we are able to translate 98.17% Bengali nouns correctly which is much better than the baseline ILMT system's accuracy of 62.8%.

• ETRI Journal
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• v.45 no.1
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• pp.60-74
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• 2023

Integration of the machine learning (ML) technique in all-optical networks can enhance the effectiveness of resource utilization, quality of service assurances, and scalability in optical networks. All-optical multistage interconnection networks (MINs) are implicitly designed to withstand the increasing highvolume traffic demands at data centers. However, the contention resolution mechanism in MINs becomes a bottleneck in handling such data traffic. In this paper, a select list of ML algorithms replaces the traditional electronic signal processing methods used to resolve contention in MIN. The suitability of these algorithms in improving the performance of the entire network is assessed in terms of injection rate, average latency, and latency distribution. Our findings showed that the ML module is recommended for improving the performance of the network. The improved performance and traffic grooming capabilities of the module are also validated by using a hardware testbed.

• Journal of IKEEE
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• v.25 no.3
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• pp.493-500
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• 2021

In this paper, we propose the development of deep learning structure to improve quality of polygonal containers. The deep learning structure consists of a convolution layer, a bottleneck layer, a fully connect layer, and a softmax layer. The convolution layer is a layer that obtains a feature image by performing a convolution 3x3 operation on the input image or the feature image of the previous layer with several feature filters. The bottleneck layer selects only the optimal features among the features on the feature image extracted through the convolution layer, reduces the channel to a convolution 1x1 ReLU, and performs a convolution 3x3 ReLU. The global average pooling operation performed after going through the bottleneck layer reduces the size of the feature image by selecting only the optimal features among the features of the feature image extracted through the convolution layer. The fully connect layer outputs the output data through 6 fully connect layers. The softmax layer multiplies and multiplies the value between the value of the input layer node and the target node to be calculated, and converts it into a value between 0 and 1 through an activation function. After the learning is completed, the recognition process classifies non-circular glass bottles by performing image acquisition using a camera, measuring position detection, and non-circular glass bottle classification using deep learning as in the learning process. In order to evaluate the performance of the deep learning structure to improve quality of polygonal containers, as a result of an experiment at an authorized testing institute, it was calculated to be at the same level as the world's highest level with 99% good/defective discrimination accuracy. Inspection time averaged 1.7 seconds, which was calculated within the operating time standards of production processes using non-circular machine vision systems. Therefore, the effectiveness of the performance of the deep learning structure to improve quality of polygonal containers proposed in this paper was proven.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.573-574
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• 2016

Before the Machine Socialization System used to connected between server and router. However, the data flow increases due to the poor performance of the router increased traffic, as a result, the loss of data when the problem occurred Collaboration between devices increases that have been interrupted. This action moves the server connected to the router is required to solve these problems. In this paper, by utilizing the cloud server to reduce bottlenecks proposed a system that can reduce the loss of data during cooperation between devices. In addition, by dividing the management unit and the sensor using the virtualization technology, we designed a system that can efficiently make use of the resource.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.04a
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• pp.409-414
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• 1994

A FMS is a typical discrete event system exhibiting concurrency, asynchronicity and non-determinism. Torepresent a FMS with those chatcteristics, Colored and Timed Petri Nets is defined and the modeling procedure is provided in this paper. Toanalyze and evaluate the performance of a FMS, a simulation software is developed and applied to SNU FMS/CIM Center. This software enables to detect the bottleneck machine and decide the optimaldirection in case of the expansion of a FMS.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.4
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• pp.174-181
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• 1994

A FMS is a typical discrete event system exhibiting concurrency, asynchronicity and non-determinism. To represent a FMS with those characteristics, Colored and Timed Petri Nets is defined and the modeling procedure is provided in this paper. To analyze and evaluate the performance of a FMS, a simulation software is developed and applied to SNU FMS/CM Center. This software enables to detect the bottleneck machine and decide the optimal direction in case of the expansion of a FMS.

• Journal of Korean Society for Quality Management
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• v.36 no.2
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• pp.28-35
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• 2008

This study deals with an Excel-based scheduling system for a small and medium sized manufacturing factory without sufficient capability for managing full-scale information systems. The factory has the bottleneck with identical machines and unique batching characteristics. The scheduling problem is formulated as a variation of the parallel-machine scheduling system. It can be solved by a two-phase method: the first phase with an ant colony optimization (ACO) heuristic for order grouping and the second phase with a mixed integer programming (MIP) algorithm for scheduling groups on machines.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.38
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• pp.9-15
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• 1996

The purpose of this research is to develop a method for part-machine grouping subject to production and management constraints. In the proposed integer programming model, minimization of operating and material-handling costs are considered as an objective function. The model allows one to recognize the existing parts and machines into disaggregated cells. New constraints are introduced in the model to resolve unbalancing capacity and bottleneck problems. It is found that this approach could have a better flexibility on cell size design for mote alternatives than conventional methods. Experimental grouping and comparison studies with ROC algorithm are given for evaluation purposes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.4
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• pp.141-146
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• 2004

This research considers the problem of scheduling jobs on unrelated parallel machines with a common due date. The objective is to minimize the total absolute deviation of job completion times about the common due date. This problem is motivated by the fact that a certain phase of printed circuit board manufacturing and other production systems is bottleneck and the processing speeds of parallel machines in this phase are different for each job. A zero-one integer programming formulation is presented and two dominance properties are proved. By these dominance properties, it is shown that the problem is reduced to asymmetric assignment problem and is solvable in polynomial time.

• Journal of KIISE:Software and Applications
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• v.26 no.10
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• pp.1178-1178
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• 1999

A spatial join has the property that its execution time exponentially increases in proportion to the number of spatial objects. Recently, there have been many attempts for improving the performance of the spatial join by using parallel processing schemes, In the case of executing parallel spatial join using the parallel machine with shared disk architecture, the disk bottleneck of parallel processing of spatial join worsens in comparison with sequential spatial join. This paper presents the algorithms of task creation and assignment to reduce the disk bottleneck caused by accessing the shared disk at the same time, and to minimize message passing between processors, This paper proposes object caching which is a higher level of abstraction than page caching, and uses it to do creation and assignment of tasks according to temporal and spatial localities for minimizing disk access time. The object caching shows the performance improvement of 50%. The task creation and assignment using localities gives the gain of 30% and 20%. Overall performance evaluation of the proposed algorithms shows 7.2 times speed up than those of sequential execution of spatial joins.