• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.26 no.4
• /
• pp.374-380
• /
• 2015

With explosion of wireless traffic it is required to further investigate the technologies on acquiring available spectrum resources and on sharing frequency with existing users. In 3GPP, it is started to study on feasibility and functional requirement of LTE standard in order to extend cellular services offered on only licensed band to 5 GHz unlicensed band. Operating scenario on LTE in unlicensed band is focused on carrier aggregation with licensed band, and the coexistence with Wi-Fi services in 5 GHz band is concerned as a major requirement. For a single global solution framework for licensed assisted access to unlicensed spectrum, listen-before-talk(LBT) mechanism of European regulation for fair access to channel under the coexistence environments is currently examined in 3GPP. In this paper, we evaluate two types of LBT, frame based equipment and load based equipment, with considering LTE carrier aggregation feature and performances of file transferred time and throughput.

• Journal of Digital Convergence
• /
• v.17 no.9
• /
• pp.147-152
• /
• 2019

Infrastructure is rapidly growing as Internet business grows with the latest IT technologies such as IoT, BigData, and AI. However, in most companies, a limited number of people need to manage a lot of hardware and software. Therefore, Polestar Enterprise Management System(PEMS) is applied to monitor the system operation status, IT service and key KPI monitoring. Real-time monitor screening prevents system malfunctions and quick response. With PEMS, you can see configuration information related to IT hardware and software at a glance, and monitor performance throughout the entire end-to-end period to see when problems occur in real time.

• Convergence Security Journal
• /
• v.23 no.1
• /
• pp.89-95
• /
• 2023

In order to help reduce the medical expenses of patients with auto insurance accidents, this study predicted the treatment period, which is the most important factor in the medical expenses of patients in their 40s and 50s, and analyzed the factors affecting the treatment period. To this end, a mechine learning model using five algorithms such as Decision Tree was created, and its performance was compared and analyzed between models. There were three algorithms that showed good performance including Decison Tree, Gradient Boost, and XGBoost. In addition, as a result of analyzing the factors affecting the prediction of the treatment period, the type of hospital, the treatment area, age, and gender were found. Through these studies, easy research methods such as the use of AutoML were presented, and we hope that the results of this study will help policies to reduce medical expenses for automobile insurance accidents.

• Korean Journal of Remote Sensing
• /
• v.38 no.3
• /
• pp.251-263
• /
• 2022

This paper presents an idea of ScanSAR image formation. For image formation of ScanSAR that utilizes the burst mode for raw signal acquisition, most conventional single burst methods essentially require a step of azimuth stitching which contributes to radiometric and phase distortions to some extent. Time-domain cross correlation could replace SPECAN which is most popularly used for ScanSAR processing. The core idea of the proposed method is that it is possible to relieve the necessity of azimuth stitching by an extension of Doppler bandwidth of the reference function to the burst cycle period. Performance of the proposed method was evaluated by applying it to the raw signals acquired by a spaceborne SAR system, and results satisfied all image quality requirements including 3 dB width, peak-to-sidelobe ratio (PSLR), compression ratio,speckle noise, etc. Image quality of ScanSAR is inferior to that of Stripmap in all aspects. However, it is also possible to improve the quality of ScanSAR image competitive to that of Stripmap if focused on a certain parameter while reduced qualities of other parameters. Thus, it is necessary for a ScanSAR processor to offer a great degree of flexibility complying with different requirements for different applications and techniques.

• The Journal of the Acoustical Society of Korea
• /
• v.33 no.5
• /
• pp.316-325
• /
• 2014

The basic unit of school is a classroom and the aural environment of the classrooms is essential factor for education purposes. Therefore, many efforts have been undertaken for enhancing the acoustical performance of the classrooms in many countries. As a result, acoustic criteria including reverberation time and background noise level have been established in US and UK for school classrooms depending on the usage and size of the rooms. However, in Korea, there has been little researches concerning the room acoustical investigations of the classrooms. The present study investigates the current situation of the aural environment of the 15 classrooms in Korea including elementary, middle and high schools. The acoustic criteria measured include RT, $D_{50}$, STI, SNR and background noise level. As the results, it was found that the background noise levels of the schools adjacent to roads exceed the US and UK standard of 35 dB(A). Also, most schools have so low SNR that they may be interfered by noise, which may affect speech transmission. It was also revealed that some schools have longer RT than the US standard of 0.6 s, but they all have high speech intelligibility.

• Journal of the Korea Society for Simulation
• /
• v.29 no.3
• /
• pp.57-72
• /
• 2020

To respond to the threat of Long range artillery of North Korea, it is necessary to establish the Korean counter long range artillery intercept system(CLRAIS). The purpose of this study is to study the operational concept of the CLRAIS against the threat of long range artillery of North Korea, and to develop the operational effectiveness process of the CLRAIS. First, we set up the operating concept of the CLRAIS and established the concept of an effectiveness in a many-to-many engagement situation and a process to derive it. Based on this, a tool was developed to analyze the actual effectiveness. In order to find out the factors influencing the effectiveness in many-to-many engagement situations, simulation experiments were performed by combining various variables such as detection assets, engagement control, and launchpad performance. As a result, it was found that in addition to the missile performance, the performance of the detection assets and the engagement control center had a significant impact on the intercept rate and the defense success rate. These findings can be used to understand important indicators in terms of effectiveness in many-to-many engagement situations in the future development of weapon system, and to determine the development direction and target value of each element necessary for the level of defense success rate to be achieved.

• Journal of KIISE
• /
• v.44 no.7
• /
• pp.674-679
• /
• 2017

In big-data environments wherein large amounts of text documents are produced daily, titles are very important clues that enable a prompt catching of the key ideas in documents; however, titles are absent for numerous document types such as blog articles and social-media messages. In this paper, a title-generation model for which sequence-to-sequence RNNs with attention and copying mechanisms are employed is proposed. For the proposed model, input sentences are encoded based on bi-directional GRU (gated recurrent unit) networks, and the title words are generated through a decoding of the encoded sentences with keywords that are automatically selected from the input sentences. Regarding the experiments with 93631 training-data documents and 500 test-data documents, the attention-mechanism performances are more effective (ROUGE-1: 0.1935, ROUGE-2: 0.0364, ROUGE-L: 0.1555) than those of the copying mechanism; in addition, the qualitative-evaluation radiative performance of the former is higher.

• Journal of Digital Convergence
• /
• v.13 no.9
• /
• pp.269-276
• /
• 2015

Recently, with the activation of the industry related to the big data, the global security companies have expanded their scopes from structured to unstructured data for the intelligent security threat monitoring and prevention, and they show the trend to utilize the technique of user's tendency analysis for security prevention. This is because the information scope that can be deducted from the existing structured data(Quantify existing available data) analysis is limited. This study is to utilize the analysis of security tendency(Items classified purpose distinction, positive, negative judgment, key analysis of keyword relevance) applying the machine learning algorithm($Na{\ddot{i}}ve$ Bayes, Decision Tree, K-nearest neighbor, Apriori) in the big data environment. Upon the capability analysis, it was confirmed that the security items and specific indexes for the decision of security tendency could be extracted from structured and unstructured data.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.12
• /
• pp.67-77
• /
• 2023

This study represents an innovative research conducted in the smart farm environment, developing a deep learning-based disease and pest detection model and applying it to the Intelligent Internet of Things (IoT) platform to explore new possibilities in the implementation of digital agricultural environments. The core of the research was the integration of the latest ImageNet models such as Pseudo-Labeling, RegNet, EfficientNet, and preprocessing methods to detect various diseases and pests in complex agricultural environments with high accuracy. To this end, ensemble learning techniques were applied to maximize the accuracy and stability of the model, and the model was evaluated using various performance indicators such as mean Average Precision (mAP), precision, recall, accuracy, and box loss. Additionally, the SHAP framework was utilized to gain a deeper understanding of the model's prediction criteria, making the decision-making process more transparent. This analysis provided significant insights into how the model considers various variables to detect diseases and pests.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.23 no.4
• /
• pp.475-483
• /
• 2012

This paper presents new type of the hybrid supply modulator for the next reconfigurable transmitters. The efficiency of the hybrid supply modulator is one of the most important performance. For enhancement the efficiency, multi-switching structure in the hybrid supply modulator is employed. Additionally, input envelope signal sensing stage is employed for implementation multi-mode operation. To compare the performance of the proposed hybrid supply modulator, the conventional hybrid supply modulator is also designed. The measured efficiency of the proposed hybrid supply modulator is 85 %/84 %/79 % for EDGE/WCDMA/LTE signals which have 384 kHz/3.84 MHz/5 MHz bandwidth, respectively. The efficiency of the proposed hybrid supply modulator is higher than the conventional hybrid supply modulator. Therefore, this structure shows good candidate for the reconfigurable transmitters.