• 한국벤처창업학회:학술대회논문집
• /
• 2023.04a
• /
• pp.59-62
• /
• 2023

100세 인생 시대의 도래는 사회적으로 많은 변화를 요구하고 있다. 기성세대들이 기존의 조직구조 속에서 일할 수 있는 최고 연령이 60대 초반인 것을 감안한다면 100세 인생 시대에는 퇴직한 후에 3~40년간 살아나갈 대안이 있어야 한다는 것이다. 이러한 환경 속에서 일반 직장인들에 비해 직장에서 많은 시간과 노력을 하고 있는 경찰관들이 퇴직 후에 경제활동을 지속하게 하는데 영향을 미치는 요인에 대한 연구를 하는 것이 중요하다고 생각한다. 따라서 본 연구는 정년을 마친 후 연금을 받게 되는 경찰관들이 다른 직종의 직장인들과 비교하여 경제활동에 대한 필요성을 느낄 것인가? 그렇다면 그 이유는 무엇인가? 퇴직 후에도 경제활동을 하려는 경찰관들에게 어떠한 요인들이 영향을 주는 것일까? 등에 대한 것을 기존 연구와 문헌들을 통하여 연구 모형과 가설을 정하고 설문 조사를 통해 실증적으로 분석하고자 한다. 본 연구는 재직 경찰관들이 퇴직 후에 경제활동을 지속하기 위한 의도에 영향을 미치는 요인에 관한 연구를 위해 개인역량, 경제활동 동기, 돈과 경제에 대한 인식, 경제적 만족도와 직장 안정성, 직장 공정성과 상하관계, 교육 및 교육 참여, 은퇴 준비, 직무만족과 직무의 미래비전을 독립 변수로 하고 경제활동 지속의도를 종속 변수로 설정하여 진행하였다.

• Proceedings of the Korean Society of Disaster Information Conference
• /
• 2022.10a
• /
• pp.325-326
• /
• 2022

통계청에 의하면 65세 이상 인구가 2024년 1,000만명을 도래할 것으로 예측하고 있으며, 노인인구 증가와 함께 노인치안 이슈들은 매년 증가하고 있다. 특히, 경찰청 자료에 따르면 최근 5년간 노인범죄피해는 매년 증가하고 있는 것으로 나타났다(경찰청, 2021). 치안서비스 대상에서 주요한 영역을 차지하게 될 노인을 대상으로 한 범죄예방정책을 마련하기 위하여 범죄피해노인의 특성에 관한 연구를 함에 있어 연도별 노인의 범죄피해영향요인의 차이가 있는지를 이 연구에서는 분석하고자 하였다. 따라서 이 연구에서는 한국형사·법무정책연구원의 2014년, 2016년, 2018년 전국범죄피해조사 2차 자료를 활용하였으며, 그 중 만65세 노인대상 자료만을 추출하여 2014년 1.921명, 2016년, 2,935명, 2018년 2,707명을 각각 최종분석에 활용하였다. Spss ver 21. 통계프로그램을 활용하여 로지스틱회귀분석을 실시하였으며, 연구결과 2014년에는 사회적 무질서 수준과 노인범죄피해와의 관계성이 높았다면, 2016년에는 물리적 무질서 수준과 노인범죄피해와의 관계성이 높았고, 2016년과 2018년에는 독거노인과 빈 집으로 가구가 노출되는 시간이 긴 정도가 노인범죄피해와의 관계성이 높은 것으로 볼 수 있었다. 이러한 연도별 노인 범죄피해 영향요인의 변화를 실증연구를 통해 검증함으로써 추후 노인범죄예방을 위한 정책마련의 자료로 활용하고자 한다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.9 no.4
• /
• pp.330-336
• /
• 2016

In this paper, we studied for modified bartlett method to estimate desired information signal. Constrained length of bartlett method is assigned as one, and estimate desired information signal to compensate for delay time. Modified bartlett method is an optimum direction-of-arrival (DoA) estimation algorithm to apply delay time compensation to update optimum weight. The optimum weight is used linear constrained minimum variance method(LCMV). Through simulation, we are comparative analysis proposed algorithm and general Bartlett and MUSIC method. In desired signal estimation, condition simulation is an array antenna element numbers 6 or 9 and desired information signals number 3. We show the superior performance of the proposed algorithm relative to the existing method in estimation of desired information signal.

• KDI Journal of Economic Policy
• /
• v.19 no.1
• /
• pp.3-50
• /
• 1997

경제자유화(經濟自由化)와 규제완화(規制緩和)라는 세계적인 흐름과 함께 우리나라도 1992년 이후 자본시장(資本市場)을 점진적으로 개방(開放)하고 있다. 본 연구에서는 우선 몇몇 핵심 거시경제변수(巨視經濟變數)들의 상관관계(相關關係)가 자본거래의 자유화와 더불어 어떻게 변화할 것인가에 대한 이론적(理論的)인 배경(背景)을 설명하고 있다. 여기에서는 무엇보다도 자본자유화(資本自由化)와 더불어 나타나게 되는 실질환율체상(實質換率切上)및 경상수지적자(經常收支赤字)의 의미를 합리적인 경제주체들이 자원(資源)을 보다 효율적(效率的)으로 배분(配分)하고자 하는 노력의 결과로 나타나는 현상으로 파악하고 있다. 즉 자본시장의 개방은 상대적으로 높은 국내의 자본생산성 및 실질이자율을 향한 해외자본의 유입(자본수지(資本收支)의 흑자(黑字))을 초래하며, 대외부문의 항등식을 고려하는 한 이는 경상수지(經常收支)의 적자(赤字)로 연결된다. 또한 본 연구에서는 신고전파적(新古典派的) 장기모형(長期模型)과 케인즈적(的) 단기모형(短期模型)에 기초한 거시경제 모형을 구성하고 자본자유화(資本自由化)의 속도(速度), 환율(換率)및 통화정책(通貨政策)의 변화에 따른 거시경제의 동태적(動態的) 시간경로(時間經路)를 계량화하고자 노력하였다. 예를 들어 경상수지적자(經常收支赤字)의 폭은 자본자유화의 추진속도 및 거시정책에 의존할 것이나, 예상하지 못한 큰 충격이 도래하지 않는 경우 향후 2~3년간 GDP 대비 3% 내외에 이를 것으로 추정되며, 그 이후에는 실질이자율의 하락과 함께 적자폭도 축소될 것으로 나타나고 있다. 그리고 실질환율(實質換率)의 시간경로는 자본유입과 함께 지속적으로 절상될 수는 없으며 개방초기의 절상에 이어 점차 절하되는 추세에 놓이게 될 것이다. 자본시장의 개방에 따른 경상수지의 적자는 국내의 (실물)자본축적을 보다 용이하게 함으로써 실질이자율(實質利子率)을 하락(下落)시킬 것으로 기대되나 그 효과는 연 0.2%포인트 이내에 머무를 것으로 추정되었다. 아울러 자본자유화의 초기단계에 발생할 환율절상은 수출의 가격경쟁력을 약화시켜 단기적(短期的)으로 경기침체(景氣沈滯)를 유발할 수 있으나 중장기적(中長期的)으로 성장잠재력(成長潛在力)을 확충시킨다.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.1
• /
• pp.1-16
• /
• 2020

With the advent of the fourth industrial revolution era, there has been a growing interest in deep learning using big data, and studies using deep learning have been actively conducted in various fields. In the transportation sector, there are many advantages to using deep learning in research as much as using deep traffic big data. In this study, a short -term travel speed prediction model using LSTM, a deep learning technique, was constructed to predict the travel speed. The LSTM model suitable for time series prediction was selected considering that the travel speed data, which is used for prediction, is time series data. In order to predict the travel speed more precisely, we constructed a model that reflects both temporal and spatial effects. The model is a short-term prediction model that predicts after one hour. For the analysis data, the 5minute travel speed collected from the Seoul Transportation Information Center was used, and the analysis section was selected as a part of Gangnam where traffic was congested.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.13 no.3
• /
• pp.288-300
• /
• 2002

In this paper, a novel method of equalization of RF transceivers is suggested for MIMO(Multiple Input Multiple Output) antenna actively studied for high speed data transmission in the recent IMT-2000 system. The core of suggestion is in equalizing the transfer characteristics of multiple transceivers using feedback and memory during the predefined calibration time. This makes it possible to weight the signals in the intermediate frequency, which is easier in the application of recently developed DoA(Direction of Arrival) algorithms. In addition, the time varying optimum cell formation according to traffic is feasible by antenna beam-forming based on the DoA information. The suggested method of equalizing multiple transceivers are successfully verified using envelope simulation. two outputs. This paper is concerned with the diagnosis of multiple crosstalk-faults in OSM. As the network size becomes larger in these days, the convent.
nal diagnosis methods based on tests and simulation be.
me inefficient, or even more impractical. We propose a simple and easily implementable alg？ithm for detection and isolation of the multiple crosstalk-faults in OSM. Specifically, we develop an algorithm for isolation of the source fault in switc.
ng elements whenever the multiple crosstalk-faults are.
etected in OSM. The proposed algorithm is illustrated by an example of 16$\times$16 OSM.

• Journal of Practical Engineering Education
• /
• v.16 no.2
• /
• pp.185-193
• /
• 2024

With the advent of smartphones, people can access various information through the internet anytime and anywhere. Even in the vehicle environment, users can use the internet. Users interact with web and applications every day and get information. However, as the amount of data to be processed by the program increases, users inevitably receive a message to wait. User waiting is an inconvenient experience, but minimizing user waiting is the best way because there is time required for data processing. However, if the service processing time exceeds the expected time, users experience more severe boredom and pain. Therefore, various methods and researches are being conducted to alleviate the boredom of user waiting. The most commonly used method to alleviate user waiting boredom is loading. In this study, we investigated the effect of skeleton loading, the latest loading technique, on user waiting experience, and how attractive it is as a design technique in terms of UI compared to other loading techniques.

• The Transactions of the Korea Information Processing Society
• /
• v.13 no.7
• /
• pp.311-318
• /
• 2024

As the amount of data increases due to the development of artificial intelligence and the Internet, data management is becoming increasingly important, and the efficient utilization of data retrieval and memory space is crucial. In this study, we investigate how to optimize search speed and memory efficiency by analyzing data structure based on metadata. As a research method, we compared and analyzed the performance of the array, association list, dictionary binary tree, and graph data structures using metadata of photographic images, focusing on temporal and space complexity. Through experimentation, it was confirmed that dictionary data structure performs best in collection speed and graph data structure performs best in search speed when dealing with large-scale image data. We expect the results of this paper to provide practical guidelines for selecting data structures to optimize search speed and memory efficiency for the images data.

• The Journal of Korean Philosophical History
• /
• no.56
• /
• pp.81-117
• /
• 2018

The purpose of this study is to clarify the overall features and its meaning of the Gaebyok(開闢) through the intercomparison of the Gaebyok idea that is the core idea of a newly risen modern religion in Korea. Limitation of most studies so far is that they have stayed in the fragmentary study on the Gaebyok idea of each new religion. In order to overcome this problem, first of all, the Gaebyok idea was studied from a philosophical point encompassing the cosmological view of time in the book of changes. And based on this methodological foundation, with organizing the existing result of study, the process of development and characteristics in the Gaebyok idea of a posteriori Donghak(東學), Right I Ching (正易), Won Buddhism(圓佛敎), and Kangjeungsan(姜甑山) was investigated respectively. And through comparing and analyzing each Gaebyok idea, the similarities and differences between each other were organized. The founders of new religions thought that a great change in the universal and natural luck was made before and after the point of their living. The concept of the frequency of revolution theory is the concept to explain the aspect of transition according to the frequency of revolution(運度) of the cosmological nature that returns to the beginning, and in the idea of the posterior Gaebyok, this content and concepts is contained as it was. This study showed that the concept of the frequency of revolution theory in an apriority and a posterior like those becomes appeared in some preaches of Suun, Ilbu, Sotaesan and Jeungsan. An apriority in the Gaebyok idea of new religion is the world of crisis that represents the limited condition of human being, and a posterity means the religious ideal world realized through the power of the absolute being or a dramatic universal change from that limited circumstances. So the Gaebyok ida is a kind of an universal eschatology and religious view that expects the coming of ideal world in the future. In addition, since the universal eschatology is a kind of a view of time, it inevitably has an issue how long time apriority and a posterity included in it have. And especially, it becomes to premise the content how the social condition and human condition change in an apriority and a posterity. Accordingly, in this study, based on the understanding of the view of time in the cosmological level, the content of answers that each newly risen religion discloses was listed and analyzed with comparison. It can be considered that Suun took charge of a mission to deliver the message through being possessed of a god in heaven who is able to be called a transcendental existence, Ilbu disclosed the coming of the world of a posterity beyond an apriority through the Book of Changes(易學), Jeungsan proclaimed himself as the absolute being who could make such a posterity and bring it, and Sotaesan proposed the Gaebyok of mind in order to meet with the world of a posterity and to live in that era.

• KIPS Transactions on Software and Data Engineering
• /
• v.5 no.12
• /
• pp.623-634
• /
• 2016

Most of existing frequent pattern mining methods address time efficiency and greatly rely on the primary memory. However, in the era of big data, the size of real-world databases to mined is exponentially increasing, and hence the primary memory is not sufficient enough to mine for frequent patterns from large real-world data sets. To solve this problem, there are some researches for frequent pattern mining method based on disk, but the processing time compared to the memory based methods took very time consuming. There are some researches to improve scalability of frequent pattern mining, but their processes are very time consuming compare to the memory based methods. In this paper, we present PPFP as a novel disk-based approach for mining frequent itemset from big data; and hence we reduced the main memory size bottleneck. PPFP algorithm is based on FP-growth method which is one of the most popular and efficient frequent pattern mining approaches. The mining with PPFP consists of two setps. (1) Constructing an IFP-tree: After construct FP-tree, we assign index number for each node in FP-tree with novel index numbering method, and then insert the indexed FP-tree (IFP-tree) into disk as IFP-table. (2) Mining frequent patterns with PPFP: Mine frequent patterns by expending patterns using stack based PUSH-POP method (PPFP method). Through this new approach, by using a very small amount of memory for recursive and time consuming operation in mining process, we improved the scalability and time efficiency of the frequent pattern mining. And the reported test results demonstrate them.