• Journal of information and communication convergence engineering
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• v.18 no.2
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• pp.100-105
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• 2020

With the advent of the 5G era, the rapid growth in demand for mobile content services has increased the need for additional backhaul investment. To meet this demand, employing a content delivery network (CDN) and optical access solution near the last mile has become essential for the configuration of 5G networks. In this paper, a cache-enabled architecture using the passive optical network (PON) is presented to serve video on demand (VoD) for users. For efficient use of mobile backhaul, I propose a request deduplication scheme (RDS) that can provide all the requested services missed in cache with minimum bandwidth by eliminating duplicate requests for movies within tolerable range of the quality of service (QoS). The performance of the proposed architecture is compared with and without RDS in terms of the number of requests arriving at the origin server (OS), hit ratio, and improvement ratio according to user requests and cache sizes.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.173-178
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• 2020

A common problem with neural network learning is that it is too suitable for the specificity of learning. In this paper, various methods were compared to avoid overfitting: regularization, drop-out, different numbers of data and different types of neural networks. Comparative studies of the above-mentioned methods have been provided to evaluate the test accuracy. I found that the more data using method is better than the regularization and dropout methods. Moreover, we know that deep convolutional neural networks outperform multi-layer neural networks and simple convolution neural networks.

• Annual Conference of KIPS
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• 2019.10a
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• pp.164-167
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• 2019

차량 네트워크의 핵심 기술인 V2X 발전에 따라, V2I에서 중요한 역할을 하는 RSU에 대한 연구 또한 진행되고 있다. 그러나 기존 RSU 는 저성능 및 유지보수 고비용의 문제점이 존재하여 차량이 RSU 기능을 수행하는 mRSU가 제안되었다. 이에 mRSU를 배치하는 연구는 진행되고 있으나 mRSU 역할을 하는 차량을 선정하기 전, 해당 차량의 안전성을 판단하는 방안이 존재하지 않아 보안에 취약하다는 한계가 있다. 이를 해결하기 위해 본 논문에서는 차량을 mRSU 로 선정하기 전 교통 관제 센터에서 해당 차량의 안전성을 판단하고, mRSU 적합도를 수치화하여 이 데이터를 블록체인으로 저장 및 관리하는 방안에 대해 제안한다. 이를 통해 신뢰 적인 기관의 검증된 데이터의 무결성을 보장하여 보안 취약성을 보완할 수 있다는 장점이 존재한다.

• Journal of Industrial Convergence
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• v.2 no.1
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• pp.47-72
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• 2004

The study has tried to address particular situations relating to HRM. In my paper I give suggestions based on the present state of Korean Corporations. They are from 2 view points. These view points include the level of vertical fitness as a basic task of strategic human resource management and the level of empowerment to the line managers. This study could be defined by examining the following question: What are the contingent factors and organizational policies that enable us to foresee levels of strategic integration and empowerment? We seem to require the wisdom of human resource management for establishing the foundation of presenting a standard.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.61-72
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• 2020

Recently, researches that are using deep learning technology in various fields are being conducted. The fields include geographic map processing. In this paper, I propose a method to infer where the map area included in the image is. The proposed method generates and learns images including a map, detects map areas from input images, extracts character strings belonging to those map areas, and converts the extracted character strings into coordinates through geocoding to infer the coordinates of the input image. Faster R-CNN was used for learning and map detection. In the experiment, the difference between the center coordinate of the map on the test image and the center coordinate of the detected map is calculated. The median value of the results of the experiment is 0.00158 for longitude and 0.00090 for latitude. In terms of distance, the difference is 141m in the east-west direction and 100m in the north-south direction.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.173-181
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• 2023

Data collection is an essential element in the construction and operation of a smart factory. The quality of data collection is greatly influenced by network conditions, and existing wireless network systems for IoT inevitably lose data due to wireless signal strength. This data loss has contributed to increased system instability due to misinformation based on incorrect data. In this study, I designed a distributed MQTT IoT smart sensor and gateway structure that supports wireless multicasting for smooth sensor data collection. Through this, it was possible to derive significant results in the service latency and data loss rate of packets even in a wireless environment, unlike the MQTT QoS-based system. Therefore, through this study, it will be possible to implement a data collection management system optimized for the domestic smart factory manufacturing environment that can prevent data loss and delay due to abnormal data generation and minimize the input of management personnel.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.2
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• pp.89-97
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• 2019

Recently, there is an increasing demand for applications utilizing maps and locations such as autonomous vehicles and location-based services. Since these applications are developed based on spatial data, interest in spatial data processing is increasing and various studies are being conducted. In this paper, I propose a parallel mining algorithm using the CUDA library to efficiently analyze large spatial data. Spatial data includes both geometric (spatial) and non-spatial (aspatial) attributes. The proposed parallel spatial data mining algorithm analyzes both the geometric and non-spatial relationships between two layers. The experiment was performed on graphics cards containing CUDA cores based on TIGER/Line data, which is the actual spatial data for the US census. Experimental results show that the proposed parallel algorithm using CUDA greatly improves spatial data mining performance.

• Korean Journal of Mathematics
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• v.32 no.3
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• pp.533-544
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• 2024

Given a groupoid (X, *) and a real-valued function d : X → R, a new (derived) function Φ(X, *)(d) is defined as [Φ(X, *)(d)](x, y) := d(x * y) + d(y * x) and thus Φ(X, *) : R^X → R^X2 as well, where R is the set of real numbers. The mapping Φ(X, *) is an R-linear transformation also. Properties of groupoids (X, *), functions d : X → R, and linear transformations Φ(X, *) interact in interesting ways as explored in this paper. Because of the great number of such possible interactions the results obtained are of necessity limited. Nevertheless, interesting results are obtained. E.g., if (X, *, 0) is a groupoid such that x * y = 0 = y * x if and only if x = y, which includes the class of all d/BCK-algebras, then (X, *) is *-metrizable, i.e., Φ(X, *)(d) : X² → X is a metric on X for some d : X → R.

• Journal of the Korea Convergence Society
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• v.9 no.8
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• pp.143-148
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• 2018

This study focused on the difference between Oculus Store of Oculus and FXGEARs. NOON VR Stores service platform. First the literature study considered the current status and prospect of the VR market and conducted a case study on the VR service platform. In addition, this study conducts the platform strategies of Andrei Hakgu and Hirano AtsushI. After that Interviewers were interviewed to investigate the usability of the VR service platforms. The result of this study is expected to be used as a design guideline to form a VR service platform in the future, and as a user experience study.

• IE interfaces
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• v.19 no.2
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• pp.140-152
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• 2006

Today, many companies realize that the effort to develop new products / services faster that customers want and continue to purchase is crucial for their survival. As the service sector is rapidly growing, one of the challenges faced by the service industries is the lack of effective methodologies for new service development. This paper proposes a systematic framework for developing new service concepts, with an emphasis on generating innovative, convergence-type service concepts from the customer‘s perspective. The framework consists of three phases-identification of customer needs (Phase I), extraction of new service opportunities (Phase II), and generation of new service concepts (Phase III). The proposed framework is demonstrated through a case study in the telecommunications industry. In the case study, a survey was conducted on ten customers to identify the latent customer needs; 61 new service opportunities were extracted; and 129 new service concepts were generated.