• Journal of IKEEE
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• v.2 no.1 s.2
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• pp.1-14
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• 1998

In this paper, Antenna, LNA, Mixer, VCO, and Modulation/Demodulation in Baseband processor which are the RF main components in Wireless LAN system for ultra high-speed communications network are studied. Antenna bandwidth and selective fading due to multipath can be major obstacles in high speed digital communications. To solve this problem, wide band MSA which has loop-structure magnetic antenna characteristics is designed. Distributed mixer using dual-gate GaAs MESFET can achieve over 10dB LO/RF isolation without hybrid, and minimize circuit size. As linear mixing signal is produced, distortions can be decreased at baseband signals. Conversion gain is achieved by mixing and amplification simultaneously. Mixer is designed to have wide band characteristics using distributed amplifier. In VCO design, Oscillator design method by large signal analysis is used to produce stable signal. Modulation/Demodulation system in baseband processor, DS/SS technique which is robust against noise and interference is used to eliminate the effect of multipath propagation. DQPSK modulation technique with M-sequences for wideband PN spreading signals is adopted because of BER characteristic and high speed digital signal transmission.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.4
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• pp.189-198
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• 2015

Most IoT-related approaches have tried to establish the relation by connecting the network between things. The proposed research will present how the pervasive interaction of eco-system formed by touching the objects between humans and things can be recognized on purpose. By collecting and sharing the detected patterns among all kinds of things, we can construct the environment which enables individualized interactions of different objects. To perform the aforementioned, we are going to utilize technical procedures such as event-driven signal processing, pattern matching for signal recognition, and hardware in the loop simulation. We will also aim to implement the prototype of sensor processor based on Arduino MCU, which can be integrated with system using Arduino-Matlab/Simulink hybrid-interoperation environment. In the experiment, we use piezo transducer to detect the vibration or vibrates the surface using acoustic wave, which has specific frequency spectrum and individualized signal shape in terms of time axis. The signal distortion in time and frequency domain is recorded into memory tracer within sensor processor to extract the meaningful pattern by comparing the stored with lookup table(LUT). In this paper, we will contribute the initial prototypes for the acoustic touch processor by using off-the-shelf MCU and the integrated framework based on Matlab/Simulink model to provide the individualization of the touch-sensing for the user on purpose.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.1
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• pp.167-176
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• 2010

Managing the growing number of data generated through various processes requires the aid of Database Management System (DBMS) to efficiently handle the huge amount of data. These data can be inserted into database m real time or in batch, that come from multiple sources, including those that are coming from inside and outside of a network. The insertion of large amount of data is commonly done through specific bulk loading or insertion function supplied by each individual DBMS. In this paper, we analyze and evaluate on handling data bulk loading for heterogeneous systems that is organised as multi-tiered architecture and compare the result of DBMS bulk loader against program insertion from a software development perspective. We propose a hybrid solution using staging database that can be easily deployed for enhancing bulk loading performance compared to insertion by application.

• Korean System Dynamics Review
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• v.14 no.3
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• pp.25-49
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• 2013

As global competition for green car, that is environmentally friendly car, is getting tougher, the governments and the related industries are putting their core efforts in its diffusion. However, the green car sales are disappointing so far. To overcome the gridlock, it is necessary to develop concrete analytical framework to understand the diffusion process. Based on causal loop analysis from the previous work, we have identified main variables and relationships of them in the diffusion process and developed a stock-flow diagram and mathematical formula for the main components. The model would be applied for further quantitative simulation on the diffusion process of green car and other innovative goods as well. Also, we have suggested constructive insights for the policy makers and for the related industries. First, it is important to increase consumers' willingness to consider through marketing and word of mouth to accelerate the diffusion process. Second, in the perspective of the industry, the market share of green car should be increased at the earliest possible stage and this could be done by enhancing each components of green car attractiveness(e.g. price, driving range, social infra). Third, companies should develop a balanced investment between consumer and technology sector through a flexible financial policy. Fourth, the government continuously has the role of investing in the related R&D and social infra building. We expect the green car diffusion model and related formula from the research can provide meaningful tools to analyze the diffusion process of other new and innovative goods based on its deep researched literature review.

• Journal of the Korean Geographical Society
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• v.45 no.5
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• pp.647-668
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• 2010

As well as "Sangyeongpyo," "Gogyeong-Jeongripyo," table of national road transportation system is important to comprehend identity of national geography in Joseon era even if it had not been researched yet. The aim of this study is to divide type of these tables and find its genealogy through mainly analyzing the road network and land names. As the result of this research, "Yeojigo," topographical researches of Korea, edited by Shin Gyeong-Jun as a palt of "Dongguk-Munheonbigo" official book in natural history of the Joseon Dynasty published in 1770, might be identified as the origin for all copy of "Gogyeong-Jeongripyo." Then "Gogyeong-Jeongripyo," can be divided into at least three major types; almost direct descent of "Yeoji go" as 'type1', minor modification as 'type2', and hybrid edition(type3) with second type that quoted many land names as route information from "Dorogo," another topography specialized for road transportation. Since "Dorogo" was also composed by Shin, after all, all genealogy of "Gogyeong-Jeongripyo" came from him.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.6
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• pp.628-636
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• 2014

This paper describes the design and analysis of five-element planar array antenna of an anti-jamming satellite navigation system. We propose a design of multi-layer patch antenna for Global Positioning System(GPS) $L_1/L_2$ dual bands. The proposed antenna has two ports feeding network with a hybrid chip coupler for a broad bandwidth with Right-Handed Circular Polarization(RHCP). The measurement results show the bore-sight gains of 1.10 dBic($L_1$) and 0.37 dBic($L_2$) for the center element. The bore-sight gains of an edge element are 0.99 dBic($L_1$) and -0.57 dBic($L_2$). At a fixed elevation angle of $30^{\circ}$, antennas show average gains of -2.08 dBic ($L_1$) and -5.33 dBic($L_2$) for the center element, and average gains of -0.40 dBic($L_1$) and -2.09 dBic($L_2$) for the edge elements. The results demonstrate that the proposed array antenna is suitable for anti-jamming applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2496-2512
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• 2021

The requirements for powerful computing capability, high capacity, low latency and low energy consumption of emerging services, pose severe challenges to the fifth-generation (5G) network. As a promising paradigm, mobile edge networks can provide services in proximity to users by deploying computing components and cache at the edge, which can effectively decrease service delay. However, the coexistence of heterogeneous services and the sharing of limited resources lead to the competition between various services for multiple resources. This paper considers two typical heterogeneous services: computing services and content delivery services, in order to properly configure resources, it is crucial to develop an effective offloading and caching strategies. Considering the high energy consumption of 5G base stations, this paper considers the hybrid energy supply model of traditional power grid and green energy. Therefore, it is necessary to design a reasonable association mechanism which can allocate more service load to base stations rich in green energy to improve the utilization of green energy. This paper formed the joint optimization problem of computing offloading, caching and resource allocation for heterogeneous services with the objective of minimizing the on-grid power consumption under the constraints of limited resources and QoS guarantee. Since the joint optimization problem is a mixed integer nonlinear programming problem that is impossible to solve, this paper uses deep reinforcement learning method to learn the optimal strategy through a lot of training. Extensive simulation experiments show that compared with other schemes, the proposed scheme can allocate resources to heterogeneous service according to the green energy distribution which can effectively reduce the traditional energy consumption.

• Journal of Periodontal and Implant Science
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• v.53 no.1
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• pp.38-53
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• 2023

Purpose: The current Classification of Periodontal and Peri-Implant Diseases and Conditions, published and disseminated in 2018, involves some difficulties and causes diagnostic conflicts due to its criteria, especially for inexperienced clinicians. The aim of this study was to design a decision system based on machine learning algorithms by using clinical measurements and radiographic images in order to determine and facilitate the staging and grading of periodontitis. Methods: In the first part of this study, machine learning models were created using the Python programming language based on clinical data from 144 individuals who presented to the Department of Periodontology, Faculty of Dentistry, Süleyman Demirel University. In the second part, panoramic radiographic images were processed and classification was carried out with deep learning algorithms. Results: Using clinical data, the accuracy of staging with the tree algorithm reached 97.2%, while the random forest and k-nearest neighbor algorithms reached 98.6% accuracy. The best staging accuracy for processing panoramic radiographic images was provided by a hybrid network model algorithm combining the proposed ResNet50 architecture and the support vector machine algorithm. For this, the images were preprocessed, and high success was obtained, with a classification accuracy of 88.2% for staging. However, in general, it was observed that the radiographic images provided a low level of success, in terms of accuracy, for modeling the grading of periodontitis. Conclusions: The machine learning-based decision system presented herein can facilitate periodontal diagnoses despite its current limitations. Further studies are planned to optimize the algorithm and improve the results.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.78-87
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• 2011

A variety of intelligent application using the sensor network system is being studied. In general, the sensor network consists of nodes which equipped with a variety of sensing module and is utilized to collect environment information. Recently, the demands of multimedia data are increasing due to the demands of more detailed environmental monitoring or high-quality data. In this paper, we overcome the limitations of low bandwidth in Zigbee-based sensor networks and propose a routing algorithm for real-time multimedia data transmission. In the previously proposed algorithm for multimedia data transmission occurs delay time of routing setup phase and has a low data transmission speed due to bandwidth limitations of Zigbee. In this paper, we propose the hybrid routing algorithm that consist of Zigbee and Bluetooth and solve the bandwidth problem of existing algorithm. We also propose the disjointed multipath setup algorithm based on competition that overcome delay time of routing setup phase in existing algorithm. To evaluate the superiority of the proposed algorithm, we compare it with the existing algorithm. Our experimental results show that the latency was reduced by approximately 78% and the communication speed is increased by approximately 6.9-fold.