• Communications of the Korean Mathematical Society
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• v.16 no.4
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• pp.659-666
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• 2001

The aim of this paper is to derive the analytical so-lution of the queue: H$_{r}$/M/c/k/N for machine interference with balking and reneging, and FIFO (first in, first out) service disci-pline.e.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.958-964
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• 2016

In this paper, we propose an i-vector based language recognition system to identify the spoken language of the speaker, which uses multiple discriminative deep neural network (DNN) models analogous to the multi-class support vector machine (SVM) classification system. The proposed model was trained and tested using the i-vectors included in the NIST 2015 i-vector Machine Learning Challenge database, and shown to outperform the conventional language recognition methods such as cosine distance, SVM and softmax NN classifier in open-set experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.2
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• pp.566-579
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• 2012

Ubiquitous computing called pervasive one is based on the thought of pervading ability of computation in daily life applications. In other words, it aims to include computation in devices such as electronic equipment and automobiles. This has led to disengagement of computers from desktop form. Accordingly, the notice in ubiquitous computing being taken of a world steeped in remote and wireless computer-based-services. Handheld and wearable programmed devices such as sense and control appliances are such devices. This advancement is rapidly moving domestic tasks and life from device-and-human communication to the device-and-device model. This model called Machine to Machine (M2M) has led to acceleration of developments in sciences such as nano-science, bio-science, and information science. As a result, M2M led to appearance of applications in various fields such as, environment monitoring, agricultural, health care, logistics, and business. Since it is envisaged that M2M communications will play a big role in the future in all wireless applications and will be emerged as a progressive linkage for next-generation communications, this paper aims to consider how much M2M architectures can realize ubiquitous computing in daily life applications. This is carried out after acquainting and initiating readers with M2M architectures and arguments for M2M. Some of the applications was not achievable before but are becoming viable owing to emergence of M2M communications.

• Journal of information and communication convergence engineering
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• v.17 no.1
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• pp.8-13
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• 2019

Smart Farming has been regarded as an important application in information and communications technology (ICT) fields. Selecting crops for cultivation at the pre-production stage is critical for agricultural producers' final profits because over-production and under-production may result in uncountable losses, and it is necessary to predict crop production to prevent these losses. The ITU-T Recommendation for Smart Farming (Y.4450/Y.2238) defines plan/production consultation service at the pre-production stage; this type of service must trace crop production in a predictive way. Several research papers present that machine learning technology can be applied to predict crop production after related data are learned, but these technologies have little to do with standardized ICT services. This paper clarifies the relationship between agricultural consultation services and predicting crop production. A prediction scheme is proposed, and the results confirm the usability and superiority of machine learning for predicting crop production.

• Journal of Korea Multimedia Society
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• v.25 no.6
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• pp.769-782
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• 2022

A study on agricultural automation became more important. In Korea, sweet persimmon farmers spend a lot of time and effort on classifying profitable persimmons. In this paper, we propose and implement an efficient grading algorithm for persimmons before shipment. We gathered more than 1,750 images of persimmons, and the images were graded and labeled for classifications purpose. Our main algorithm is based on EfficientDet object detection model but we implemented more exquisite method for better classification performance. In order to improve the precision of classification, we adopted a machine learning algorithm, which was proposed by PyCaret machine learning workflow generation library. Finally we acquired an improved classification model with the accuracy score of 81%.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.375-382
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• 2001

The agricultural machine estimated sales survey is a survey to estimate annual sales quantities of eight major agricultural machines such as tracter, combine, etc. The purpose of this study is to design a multipurpose sample for the agricultural machine estimated sales survey. Main achievements of this study are to present an efficient stratification criterion and to suggest a reasonable estimation method by using the concept of post-stratification.

• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.317-325
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• 2022

In this study, we propose a technological system designed to provide machine vision-based automatic inspection and autonomous operation services for an entire process related to product inspection in wire harness manufacturing. The smart factory paradigm is a valuable and necessary goal, small companies may encounter steep barriers to entry. Therefore, the best approach is to develop towards this approach gradually in stages starting with the relatively simple improvement to manufacturing processes, such as replacing manual quality assurance stages with machine vision-based inspection. In this study, we consider design issues of a system based on the proposed technology and describe an experimental implementation. In addition, we evaluated the implementation of the proposed technology. The test results show that the adoption of the proposed machine vision-based automatic inspection and operation service system for multi-wire harness production may be considered justified, and the effectiveness of the proposed technology was verified.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.20-26
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• 2013

We propose PHY Frame Structure for M2M direct communications in licensed frequency band. Especially, the proposed PHY Frame Structure coexists in the same licensed frequency band as currently operating cellular systems. Recently, Machine to Machine (M2M) service markets, including SmartGrid, Mobile Health, and Smart Car, are being rapidly expanded. Supporting M2M services in a specific case can waste Radio Resource in cellular systems. For example, when two M2M terminals communicating to each other are closely located, direct communication is radio resource efficient. In this paper, we set the requirement of maintaining the existing PHY frame structure in cellular systems to meet the backward compatibility. Based on this backward compatibility requirement, PHY frame structure for M2M direct communications is developed while satisfying coexistence with current operating cellular system. The proposed PHY frame structure meets backward compatibility. Accordingly, it is expected that the proposed M2M frame structure is useful for its frequency resource efficiency.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.5
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• pp.27-33
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• 2003

G-code, another name of ISO6983, has been a popular commanding language for operating machine tools. This G-code, however, limits the usage of today's fast evolving high-performance hardware. For intelligent machines, the communications between machine and CAD/CAM departments become important, but the loss of information during generating G-code makes the production department isolated. The new standard for operating machine tools, named STEP-NC is just about to be standardized as ISO14649. As this new standard stores CAD/CAM information as well as operation commands of CNC machines, and this characteristic makes this machine able to exchange information with other departments. In this research, the new CNC machine operated by STEP-NC was built and tested. Unlike other prototypes of STEP-NC milling machines, this system uses the STEP-NC file in XML file form as data input. This machine loads information from XML file and deals with XML file structure. It is possible for this machine to exchange information to other databases using XML. The STEP-NC milling machines in this research loads information from the XML file, makes tool paths for two5D features with information of STEP-NC, and machines automatically without making G-code. All software is programmed with Visual $C^{++}$, and the milling machine is built with table milling machine, step motors, and motion control board for PC that can be directly controlled by Visual $C^{++}$ commands. All software and hardware modules are independent from each other; it allows convenient substitution and expansion of the milling machine. Example 1 in ISO14649-11 having the full geometry and machining information and example 2 having only the geometry and tool information were used to test the automatic machining capability of this system.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.877-878
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• 2008

We suggest a feature reduction method to classify mouse function data sets, which integrate several biological data sets represented as high dimensional vectors. To increase classification accuracy and decrease computational overhead, it is important to reduce the dimension of features. To do this, we employed Hybrid Huberized Support Vector Machine with kernels used for a kernel logistic regression method. When compared to support vector machine, this a pproach shows the better accuracy with useful features for each mouse function.