Earticle

이 연구는 지자체, 지역고용센터, 그리고 지역 노동시장 연구자들을 대상으로 한 설문조사결과를 바탕 으로 우리나라 지역노동통계의 문제점을 진단하고, 개편방안을 제시하고 있다. 우리나라 지역노동통계(승인통계)는 총 13종으로 이중 대부분은 중앙부처에서 생산되고 유통되는 조사 통계와 행정통계인 것으로 확인되었다. 통계체계 측면에서도 중앙부처가 조사의 기획 및 설계와 관련된 주요한 의사결정을 담당하는 반면, 지역센터들은 집행기능만을 수행하는 수직적 구조를 갖고 있는 것으 로 파악되었다. 지자체, 고용센터, 그리고 지역 연구자들을 대상으로 한 수요조사에서는 각 영역별 - 통계의 활용, 지자체의 자체통계 생산, 통계자료의 분석, 각 주체간의 협력 - 로 이러한 통계 체계상의 문제점이 더욱 구체적으로 확인되었다. 이상의 분석결과를 바탕으로 지역노동통계 체계의 개선 방향은 각 주체간의 협력과 개방성에 기초한 수평적 구조로 이루어져야 함을 제안하고 있다. 이러한 방향에 기초하여 중앙정부의 조사통계 체계 개편, 행정자료 관리체계 개편, 지역주체가 주도하는 종단 조사 체계 구축, 일자리 사업과 통계정보의 연계 등 을 세부적인 개편과제로 제시하고 있다.

This study aims to identify some of the issues and shortcomings of Korea's local labor statistical systems and proposes some possible improvements. We base our analysis on the results of a survey administered to regional governments, regional employment centers, and researchers in the field of local labor markets. Of the 13 nationally recognized statistics on local labor markets currently in existence, most are produced (both research and adminstrative) and distributed by central government agencies. From the perspective of statistical systems, we find that there is usually a vertical structure between central and regional agencies, with the former determining the core agenda and design of statistical studies while the latter performs executive functions. The survey conducted for this study was administered to regional governments, regional employment centers, and researchers in the field of local labor markets, covering issues such as the use of statistics, self-produced statistics by regional governments, the analysis of statistical data, and inter-agency cooperation. Analysing the results of the survey, we find clearer evidence of the problem of vertical organization in the production and distribution of statistics. Based on these findings, we propose that inter-agency cooperation should be organized in a more open and horizontal manner. We also propose various concrete measures to implement the transformation - reorganization of the statistical systems of the central government, restructuring of the maintenance of administrative datasets, setting up longitudinal research systems by local bodies, inter-linkage of public job creation programs and statistical resources.

Oriental medicine statistics are essential in research planning, research evaluation, and policy decision based on objective data. However, integrated administration of such statistics is not presently possible in the oriental medicine field, which has been slow in incorporating information communication technology. In an effort to address this problem, the Korea Institute of Oriental Medicine (KIOM) developed an oriental medicine statistical system in 2009, and the system has been offered in the traditional medicine information portal of OASIS. However, according to a 2010 survey targeting OASIS users, those surveys reported that needs for a system where various statistical data can be extracted via an interactive approach to multidimensional data. As a result of an analysis of the functions of the existing system, it was found that it is necessary to array and arithmetically analyze Stats Value, Drill Up & Drill Down, and Pivot. To this end, the existing DB schema should be redesigned. Based on our analysis result, we redesigned the database into a structure that is applicable to the reverse pivot algorithm. We used J2EE/JSP and a Flex framework to design and develop an oriental medicine statistical system that can provide multidimensional statistical data. Considering that the improved oriental medicine statistical system is planned to be offered by OASIS of KIOM, utilization and value of oriental medicine statistical data are expected to be enhanced.

This paper presents a dynamic development of an ontology-based statistical information system supporting the collection, storage, processing, analysis, and the presentation of statistical knowledge at the national scale. To accomplish this, we propose a data mining technique to dynamically collect data relating to citizens from publicly available data sources; the collected data will then be structured, classified, categorized, and integrated into an ontology. Moreover, an intelligent platform is proposed in order to generate quantitative and qualitative statistical information based on the knowledge stored in the ontology. The main aims of our proposed system are to digitize administrative tasks and to provide reliable statistical information to governmental, economic, and social actors. The authorities will use the ontology-based statistical information system for strategic decision-making as it easily collects, produces, analyzes, and provides both quantitative and qualitative knowledge that will help to improve the administration and management of national political, social, and economic life.

A piezoelectric sensor-based health monitoring technique using a two-step support vector machine (SVM) classifier is developed for railroad track damage identification. A built-in active sensing system composed of two PZT patches was investigated in conjunction with both impedance and guided wave propagation methods to detect two kinds of damage in a railroad track (hole-damage 0.5cm in diameter at the web section and transverse cut damage 7.5cm in length and 0.5cm in depth at the head section). Two damage-sensitive features were separately extracted from each method: a) feature I: root mean square deviations (RMSD) of impedance signatures, and b) feature II: sum of square of wavelet coefficients for maximum energy mode of guided waves. By defining damage indices from these two damage-sensitive features, a two-dimensional damage feature (2-D DF) space was made. In order to enhance the damage identification capability of the current active sensing system, a two-step SVM classifier was applied to the 2-D DF space. As a result, optimal separable hyper-planes (OSH) were successfully established by the two-step SVM classifier: Damage detection was accomplished by the first step-SVM, and damage classification was carried out by the second step-SVM. Finally, the applicability of the proposed two-step SVM classifier has been verified by thirty test patterns prepared in advance from the intact state and two damage states.

음성 언어 이해는 자연어 음성으로부터 컴퓨터가 처리할 수 있는 형태의 의미를 저장하는 의미 구조를 추출하는 문제를 다룬다. 대부분의 음성 언어 이해 시스템들은 화행 분석과 개체명 분석을 구분하여 처리하고 있다. 기존 연구에서는 이러한 두 가지 문제를 독립적이거나 순차적인 방식으로 처리하고 있다. 하지만 순차적 시스템에서는 화행과 개체명이 한 방향으로만 영향을 주게 되는 단점이 존재한다. 본 논문에서는 화행과 개체명을 동시에 처리하기 위해 Triangular-chain CRF라는 새로운 결합 음성 언어 이해 모델을 제안한다. 음성 대화 데이터를 이용한 실험을 통해 제안하는 결합 모델이 독립 및 순차적 방법과 비교하여 성능이 향상됨을 제시한다.

Spoken language understanding (SLU) addresses the problem of mapping natural language speech into semantic frame for structure encoding of its meaning. Most of the SLU systems separate out the dialog act (DA) identification from the named entity (NE) recognition to generate the semantic frames. In previous works, these two subtasks are treated by independent or cascaded approaches. In the cascaded systems, however, DA and NE influence only to one side, rather than to both sides. In this paper, we develop a new joint SLU model with a triangular-chain conditional random field (CRF) to encode inter-dependence between DA and NE. On four real dialog data, we show that our joint approach outperforms both independent and cascaded approaches.

We fabricated superconducting quantum interference devices (SQUIDs) based on Nb Josephson junctions, and characterized the key parameters of the SQUIDs. The SQUIDs are double relaxation oscillation SQUIDs (DROSs) having larger flux-to-voltage transfer coefficient than the standard DC-SQUIDs. SQUID sensors were fabricated by using Nb junction technology consisted of a DC magnetron sputtering and a conventional photolithography process. In multichannel SQUID systems for whole-head magnetoencephalography measurement with a helmet-type SQUID array, we need about 336 SQUID sensors for each system. In this paper, we fabricated a few hundred SQUID sensors, measured the critical current, flux modulation voltage and decided if each tested SQUID can be used for the multichannel systems. As the criterion for the acceptance of the sensors, we chose the critical current and amplitude of the modulation voltage to be 8 ㎂ and 80 ㎶, respectively. The average critical current of the SQUIDs was 10.58 ㎂. The typical flux noise of the SQUIDs with input coil shorted was 2 μΦ0/√Hz at white region.

상수관망정비사업의 우선순위에 대한 의사결정시 누수에 영향을 미치는 인자를 조사⋅분석하여 수량, 수압, 수질 요소는 물론 시설개량비용, 에너지비용, 유지관리비용 등의 경제성요소를 고려한 과학적이고 체계적인 접근방법이 필요하다. 본 연구에서는 인천시 배수관망을 중심으로 상수도관망에서 누수에 영향을 미치는 인자를 조사하고, 가장 상관성이 높은 인자를 산정하기 위하여 통계분석을수행하였다. 이를 위해 소블록 별 관로노후도, 배수관연장, 관경, 급수전수, 급수량, 누수발생 횟수, 용도지역, 관망구성 형태 등을 조사⋅분석하였으며 급수에너지 개념을 도입하고, 상수관망 해석결과를 활용하여 에너지 비를 산출하였다. 상수관망 해석을 위한 물리적, 운영적인자를 선정하여 무수율을 종속변수로 하고, 상수관망 내 관로노후도, 급수에너지비, 급수전당 공급량을 독립변수로 하는 무수율 다중회귀식을 도출하였다. 향후 지역적인 상수관망의 특성과 수요패턴을 고려하여 무수율공식을 산출한다면 정확도를 향상하는 데 기여할 수 있을 것으로 판단되었다.

In deciding priorities for waterworks maintenance, a scientific and systematic approach would be needed to examine and analyze the main parameters affecting the leakage, along with water demand quantity, water pressure, energy costs, and so forth. In this study, a statistical analysis was performed to estimate the physical parameters in waterworks maintenance with the highest correlation with the leakage. For this purpose, water distribution analysis was performed to assess the demand energy ratio. The formula of non-revenue water estimation consists of independent variables related with physical parameters for waterworks. Deterioration rate of pipes, demand energy ratio and water supply quantity at each demand point were used in a multiple regression equation for water distribution network analysis. If regional characteristics of distribution network and demand patterns are considered in developed formula, the estimated accuracy for calculating the non-revenue water rate will be improved.

The evolution of semiconductor manufacturing technology has accelerated the reduction of device dimensions and the increase of integrated circuit density. In order to improve yield within a short turn around time and maintain it at high level, a system that can rapidly determine problematic processing steps is needed. The statistical process control detects abnormal process variation of key parameters. Expert systems in SPC can serve as a valuable tool to automate the analysis and interpretation of control charts. A set of IF-THEN rules was used to formalize knowledge base of special causes. This research proposes a strategy to apply expert system to SPC in semiconductor manufacturing. In analysis, the expert system accomplishes the instability detection of process parameter, In diagnosis, an engineer is supported by process analyzer program. An example has been used to demonstrate the expert system and the process analyzer.

표정은 감정을 직관적으로 전달할 수 있는 수단으로 메타버스 (metaverse)에서 사용자의 감정 변화를 실시간 감지에 사용할 수 있다. 하지만 표정이 실시간으로 변화할 경우, 다양한 감정이 섞여 정확한 감정을 파악하는 데 제한된다. 또한, 동일한 감정이 중복되어 수집된다면 불필요한 데이터가 메타버스로 전송되면 컴퓨팅 자원이 과도하게 소모될 수 있다. 따라서 본 논문에서는 메타버스에서 통계적 필터링 (statistical filtering)을 사용한 AIoT 감정 매핑 시스템을 제안한다. 통계적 필터링을 사용하여 원하는 감정만을 필터링하고 필터링된 감정은 국제 표준 oneM2M 기반 IoT 서버와 메타버스 연동 모듈을 사용하여 감정을 메타버스 블록에 매핑시킨다. 9초의 행복에 관한 영상으로 실험한 결과, 필터링을 거치지 않은 실험은 슬픔 64개, 행복 55개, 화남 11개, 두려움 1개의 결과를 얻었고, 필터링을 거친 결과는 화남 11개와 행복 55개가 나왔다. 앞 실험의 결과로 감정을 모아서 처리하고 불필요한 감정을 서버로 전달하지 않아 컴퓨팅 자원을 줄일 수 있는 것을 확인하였다.

Expression intuitively can convey emotion and detect users' emotional changes in real time within the metaverse. However, rapid changes in expressions can complicate accurate emotion identification due to mixed feelings. Redundant collection of the same emotion may lead to unnecessary data transmission, consuming excessive computing resources. This paper proposes an AIoT emotional mapping system using statistical filtering in the metaverse. By filtering out undesired emotions, the filtered emotions are mapped to metaverse blocks via an IoT server based on the oneM2M standard. An experiment with a 9-second happiness video showed that filtering reduced the data to 11 instances of anger and 55 instances of happiness, effectively optimizing resource usage.

This paper is concerned with the design of two residual control charts for real-time monitoring of the continuous flow processes. Two different control charts are designed under the situation that observations are correlated each other. Kalman-Filter based model estimation is employed when the process model is known. A black-box approach, based on Back-Propagation Neural Network, is also applied for the design of control chart when there is no prior information of process model. Performance of the designed control charts and traditional control charts is evaluated. Average run length(ARL) is adopted as a criterion for comparison. Experimental results show that the designed control chart using the Neural Network's modeling has shorter ARL than that of the other control charts when process mean is shifted. This means that the designed control chart detects the out-of-control state of the process faster than the others. The designed control chart using the Kalman-Filter based model estimation also has better performance than traditional control chart when process is out-of-control state.

이 연구는 우리나라 해양경찰 통계시스템에 대한 문제점을 살펴보고 바람직한 발전 방향을 모색함에 있어서, 주요 외국의 사례와 비교분석을 통하여 개선할 시사점을 얻는데 목적을 두고 있다. 연구의 완성도를 높이기 위하여 우리나라 해양경찰 통계시스템과 관련된 선행연구를 조사한 후, 비교 대상인 외국의 해양경찰 통계시스템을 조사하였다. 그동안 우리나라 해양경찰의 통계시스템은 수기방식으로 집계ㆍ생산되고 있었다. 그래서 정책부서 간에 중요 데이터의 공유가 원활하지 못하여 해상안전 확보에 필요한 각종 정책을 결정하는데도 어려움이 많았다. 아울러 정책평가를 위한 객관적인 지표로 활용하는데도 한계를 가질 수밖에 없었다. 한편 외국의 경우, 미국 해양경비대는 항만국통계ㆍ해상안전ㆍ해상보안으로 구분하여 통계 수치를 작성하고 있으며, 업무를 처리하는 담당 직원 수 등 구체적인 자료를 재가공할 수 있게 함으로써 정책 수립에 활용하고 있다. 일본 해상보안청은 해상안전관련 통계뿐만 아니라 오염 및 해류 관련 내용까지 수치화하여 해상에서 일어나는 모든 상황을 객관적으로 파악할 수 있는 시스템을 운영하고 있다. 이를 바탕으로 우리나라 해양경찰 통계시스템을 선진화하기 위한 통계항목 등을 개편하고 측정시스템을 보완하는 방향을 제시하였다.

The purpose of this study is to investigate the problems of maritime police statistical system in Korea and to find implications for improvement through comparative analysis of major foreign cases. In order to improve the completeness of the study, we surveyed previous researches related to the Korean Maritime Police Statistical System, and then examined the comparative foreign maritime police statistical system. In the meantime, the statistical system of marine police in Korea has been aggregated and produced by manual method. Therefore, sharing of important data among policy departments was not smooth, and it was difficult to decide various policies necessary for securing maritime safety. In addition, there was a limit to the utilization as an objective indicator for policy evaluation. On the other hand, in the case of foreign countries, the US Maritime Security Service compiles statistical figures by port statistics, maritime safety, and maritime security, and is used for policy formulation by enabling the reprocessing of specific data such as the number of staff members handling the work. The Japan Maritime Safety Agency operates a system that can quantify not only maritime safety statistics but also pollution and ocean currents, so that all situations occurring at sea can be grasped objectively. Based on this, we revised the statistical items to improve the maritime police statistical system in Korea and suggested a direction to complement the measurement system.

Recently, growth of internet causes rapid changes in many areas of statistics such as statistical computation and education. Especially, bootstrap is the most interesting statistical methods applying computer resampling simulation. In this study, we try to present how to use a method of bootstrap on the internet. We also develop to user a statistical system which is programed with java applet for user to handle easily.

교량의 설계에 있어서 정확한 하중의 산정은 교량의 안전성 확보에 가장 핵심적인 사항이며 향후 유지 관리 측면에서도 매우 중요하다. 일반적으로 교량에서 차량에 의한 하중효과는 주로 활하중(충격하중 포함) 및 피로하중으로 나타나는데 이들 하중의 정형화를 위해서는 실제 교량 상을 주행하는 중 차량의 중량 및 통행특성을 정확히 파악하는 것이 중요하다. 이를 위해서 주행 중인 차량을 정지시키지 않고 중량을 계측할 수 있는 시스템(Bridge Weigh-In-Motion, BWIM)의 개발이 선행되어야 한다. 본 연구에서는 다양한 기능을 갖는 BWIM시스템을 개발하고 이를 고속도로 교량에 적용하여 차량정보를 수집한 후 교량 설계를 위한 활하중 및 피로하중의 정형화를 수행하였다. 본 연구의 목적은 주행 중인 차량의 중량을 산정하는 BWIM시스템을 개발하여 시험 교량에 설치 한 후 교량거동의 계측을 통하여 최종적으로 고속도로 교통량 특성을 반영하는 활하중의 정형화 및 합리적인 피로하중산정 방안을 도출하는데 있다.

In design of bridges, estimation of actions and loadings is very important for the safety and maintenance of bridges. In general, effect of traffic loading on the bridge can be modeled as live load (including impact load) and fatigue load. For estimation of traffic loading, it is important to get reliable and comprehensive truck statistical data such as the traffic and weight information. To get statistical data, Bridge Weigh-In-Motion (BWIM), which measures the truck weights without stopping the traffic, is need to be developed. In this study, BWIM system with various functions is developed first. Then this system is used to get comprehensive truck data. Traffic loadings including fatigue and live loading are formulated from the truck data acquired from the bridges. Objectives of this study are to develop the BWIM system, to apply the system in test bridge in Highway, and to formulate the live and fatigue loading for bridge design.

유속계수는 상수도 설계, 운영, 유지관리 등의 과정에서 항상 현장 실정이 고려된 값이 사용되어야 한다. 본 연구는 광역상수도 정밀안전진단 과정에서의 174개 실측자료를 바탕으로 유속계수와 주요 인자 간의 관계를 통계적 기법을 활용하여 분석하였다. 이들 관계를 분석하기 위해서 교차분석, 일원배치 분산분석, 상관분석 등을 수행하였으며, 그 결과 유속계수와 사용년수 및 관경이 높은 상관관계를 나타내고 여러 범주형 자료 형태 영향인자 중에 내부도장재가 상대적으로 유속계수에 많은 영향을 주는 것으로 검토되었다. 반면 다중회귀분석의 결과에서는 사용년수, 관경 및 수종이 중요한 영향인자인 것으로 검토되었다. 군집분석 결과, 유속계수는 기본적으로 사용년수 약 20년, 관경 1500mm를 기준으로 분류되는 경향이 있었으며, 유속계수는 전반적으로 사용년수에 많은 영향은 받으나 대구경 관에서는 상대적으로 사용년수보다 관경에 많은 영향을 받는 것으로 검토되었다. 마지막으로 본 연구에서는 회귀분석과 군집분석을 사용하여 유속계수 산정식들을 제안하였으며, 이러한 추정식들은 추후 광역상수도의 유속계수 결정 및 사용 시에 판단기준이 될 수 있을 것으로 판단된다.

In case of the application of Hazen-Williams C for design, operation or maintenance of water supply system, field situations always should be reflected on the factors. In this study, the relationships between C factors and influencing factors are analyzed using statistical techniques with 174 measured C factor data collected in periodic inspection for safety diagnosis in multi-regional water supply systems. To analyze their relationships, cross analysis, one-way ANOVA, correlation analysis were conducted. Analysis results showed that C factors had high correlations with both of elapsed year and pipe diameter and were relatively highly affected by coating material among influencing factors with the categorical type. On the other hand, elapsed year, pipe diameter and water type were meaningful influencing factors according to the results of multiple regression analysis. The Cluster analysis revealed that C factors had a tendency of being fundamentally classified on the basis of the elapsed year of about 20 years and the pipe diameter of 1500mm. Although C factors were generally greatly affected by elapsed year, size of pipe diameter relatively had an large influence on values of them in case of large diameter pipes. Lastly, It can be suggested that C factor estimation formulas using multiple regression analysis and clustering analysis in this study, can be applied as decision standards of C factor in multi-regional water supply systems.

RFID(Radio Frequency Identification) 시스템은 응용 서비스의 비용과 에너지 효율성으로 인해 사물인터넷 기술의 핵심 구성 요소로 각광받고 있다. RFID 기술을 사물인터넷 응용 서비스 분야에서 사용하기 위해서는 RFID 시스템의 리더와 태그 사이의 단순한 인식뿐만 아니라 다양한 정보를 장기간 저장하고 관리할 수 있어야 한다. 그리고 정보를 태그에 읽고 쓰기 위하여 열악한 무선 채널에 강하고 신뢰성 있는 성능 향상 기술이 필요하다. 특히, UHF(Ultra High Frequency) RFID 시스템에서는 다수의 태그가 밀집 환경에서 수동적인 방법으로 통신하기 때문에 개별 태그의 인식률과 전송속도 향상이 필수적이다. 본 논문에서는 임펄스 잡음 환경에서 RFID 시스템의 성능을 분석하기 위하여 Middleton의 A급 임펄스 잡음 모델을 선정하였고 태그에서는 FM0 인코딩과 Miller 인코딩을 적용하여 RFID 시스템의 오율 성능을 분석하였다. Middleton의 A급 임펄스 잡음 채널에서 RFID 시스템의 성능을 분석한 결과, 가우스 잡음 대 임펄스 잡음의 전력비 값과 임펄스 잡음 지수 값이 클수록 가우시안 잡음 채널과 유사함을 알 수 있었다.

RFID(Radio Frequency Identification) systems are attracting attention as a key component of Internet of Things technology due to the cost and energy efficiency of application services. In order to use RFID technology in the IoT application service field, it is necessary to be able to store and manage various information for a long period of time as well as simple recognition between the reader and tag of the RFID system. And in order to read and write information to tags, a performance improvement technology that is strong and reliable in poor wireless channels is needed. In particular, in the UHF(Ultra High Frequency) RFID system, since multiple tags communicate passively in a crowded environment, it is essential to improve the recognition rate and transmission speed of individual tags. In this paper, Middleton's Class A impulsive noise model was selected to analyze the performance of the RFID system in an impulsive noise environment, and FM0 encoding and Miller encoding were applied to the tag to analyze the error rate performance of the RFID system. As a result of analyzing the performance of the RFID system in Middleton's Class A impulsive noise channel, it was found that the larger the Gaussian noise to impulsive noise power ratio and the impulsive noise index, the more similar the characteristics to the Gaussian noise channel.

해상조난사고로 인한 인명과 재산 피해를 최소화하고 사고의 발생을 방지할 수 있는 예방요인을 도출하며, 나아가 구조당국의 대응역량 개선요소를 발굴하는데 있 어 통계는 그 무엇보다 신뢰도 높은 대안의 방향성을 제시하는 길잡이 역할을 할 수 있다. 또한 조난사고 및 수색구조 통계는 사고의 예방과 대비·대응에 투입되는 국가 예산의 비용 대비 효과를 측정하는데 있어서도 매우 중요한 지표가 될 수 있고, 국 민이 해양안전 수준을 판단하는 감시창구의 기능 또한 수행하고 있다. 본 연구는 한국 해양경찰이 관리·운용하고 있는 해상조난사고 통계시스템을 수색 구조 통계관리의 우수 모델로 인정받고 있는 미국 코스트가드의 통계시스템과 비교 분석하여 사고의 발생 중심에서 수색구조 대응 중심으로 통계의 프레임을 전환하기 위한 유용한 시사점을 도출하였고, 그에 따라 통계시스템 입력항목의 세분화를 비롯 한 비현실적인 현행 구조율 산출식의 조정 방안, 통계의 신뢰도 확보를 위한 사고 데이터 입력 기준 설정 등 단기적으로 개선할 수 있는 방안을 제시함과 동시에 중· 장기적인 관점에서 빅데이터를 기반으로 한 첨단 수색구조 통계 플랫폼의 신규 개발 방안을 제안하였다.

Statistics can guide the direction of reliable alternatives in minimizing casualties caused by marine accidents, deriving preventive factors to prevent accidents in advance, and further discovering elements to improve the response capabilities of rescue authorities. In addition, statistics on marine accidents and Search and Rescue operations can be a vital indicator in measuring the cost-effectiveness of the national budget spent on preventing, preparing, and responding to accidents and serve as a monitoring window for the public to assess their level of marine safety. This study compared analyzed the marine accident statistics system operated by the Korea Coast Guard with the US Coast Guard’s statistics system, which is recognized as an outstanding model for search and rescue statistics management, to derive valuable implications for reforming the framework of Korean search and rescue statistics from ‘occurrence-oriented’ to ‘response -oriented.’ As a result, measures that can be improved in the short term, such as fractionating sub-categories of the statistical system’s input data, adjusting unrealistic formulas for lifesaving rates on SAR cases, and setting the input criteria as usable accident data to secure statistical reliability, were suggested. Furthermore, from a mid-to-long-term perspective, designing a state-of-art search and rescue statistics management platform based on big data was proposed.

의료 사물인터넷(IoMT)환경의 확산과 함께 네트워크 패킷 조작 및 생체 데이터 위·변조를 통한 사이버 위협이 증가하고 있다. 기존 IoMT 침입탐지 연구는 주로 네트워크 feature에 의존하였으며, 설명 가능한 AI 기법인 SHAP을 적용한 연구도 결과의 통계적 타당성 검증 없이 특징(feature) 중요도를 해석하는 방법론적 한계가 존재하였다. 본 연구는 WUSTL-EHMS-2020 데이터셋을 기반으로 XGBoost, Random Forest, KNN 모델을 적용한 멀티클래스 침입탐지 체계를 구축하고, Ablation Study, 통계적 분포 검증, SHAP·LIME XAI 분석으로 구성된 3중 검증 체계를 제안하였다. 실험 결과, XGBoost가 F1-score 0.9548로 최고 성능을 달성하였다. Ablation Study를 통해 생체 feature 통합 시 Spoofing 탐지 F1이 0.7962에서 0.8848로 향상됨을 확인하였으며, 이는 선행연구에서 보고된 AUC 25% 향상의 실질적 기여자가 Spoofing 클래스에서의 생체 feature 시너지임을 멀티클래스 분석으로 정량화한 것이다. 또한 SHAP 분석에서 Spoofing 탐지에 체온이 상위 기여 feature로 나타났으나, t-검정 및 LIME 분석과 의 불일치는 이것이 실제 판별력이 아닌 교란변수 효과임을 시사하였다. 본 연구에서 제안하는 3중 검증체계는 XAI 결과의 신뢰성을 보장하는 방법론적 안전망으로서 IoMT 환경에서 설명 가능하고 검증 가능한 AI 기반 침입탐지 모니터링 체계 구축을 위한 실용적 기반이 될 수 있다.

As the Internet of Medical Things environment continues to expand, cyber threats involving network packet manipulation and biomedical data falsification are increasingly emerging. Existing IoMT intrusion detection studies have primarily relied on network features, and even studies applying explainable AI techniques such as SHAP have faced methodological limitations in interpreting feature importance without statistical validation of the results. This study constructs a multiclass intrusion detection system applying XGBoost, Random Forest, and KNN models based on the WUSTL-EHMS-2020 dataset, and proposes a three-tier validation framework comprising Ablation Study, statistical distribution verification, and dual SHAP·LIME XAI analysis. Experimental results demonstrate that XGBoost achieves the highest performance with an F1- score of 0.9548. Ablation Study confirms that integrating biomedical features improves Spoofing detection F1 from 0.7962 to 0.8848, quantifying that the actual contributor to the 25% AUC improvement reported in prior research is biomedical feature synergy in the Spoofing class through multiclass analysis. Furthermore, although SHAP analysis identifies body temperature as a top contributing feature for Spoofing detection, inconsistencies with t-test results and LIME analysis suggest this reflects a confounding variable effect rather than actual discriminative power. The proposed three-tier validation framework serves as a methodological safeguard ensuring XAI reliability, and provides a practical foundation for building explainable and verifiable AIbased intrusion detection monitoring systems in IoMT environments.

This paper proposes a new wireless statistical division multiplexing (SDM) communication system, which is based on the two-input and two-output wireless communication experimental platform constructed and presented in our previous work. This novel system aims to transmit source signals simultaneously in the same frequency band over wireless channel and recovers the source signals at the receiver by utilizing the statistical characteristics of source signals and broadcasting characteristics of wireless channel. Therefore, the spectrum efficiency of SDM system is high compared to those of time division multiplexing (TDM), frequency division multiplexing (FDM), and code division multiplexing (CDM) systems, in which TDM, FDM and CDM signals are limited in time interval, frequency band and code. Taking advantage of the statistical properties of transmitted source signals, the SDM system can easily recover or retrieve them through the blind source separation (BSS) techniques at the receiver. This paper first introduces the system model of SDM briefly, but the main purpose is to analyze the performance of it including the relationship between the separation quality and the characteristics of source signals, the power of transmitters and separation algorithms. The performance validity and corresponding analysis are confirmed and performed through realistic experiments.

As of 2016, the cremation rates in the capital area are 91.2% in Incheon Metropolitan City, 87.5% in Seoul Special City, and 87.1% in Gyeonggi-do Province, of which Incheon has the highest rate, and cremation of general corpses through the online cremation reservation service of the funeral information system is continuously increasing every year. And as of 2017, the ratio of the cremation for those outside the jurisdiction (residents of other regions) among the users of public cremation establishment in Incheon, is about 32%. As the supply capacity is expected to reach the limit within several years due to the increase in demand for such a cremation facility, I would like to suggest a policy as follows. The expansion of cremation supply capacity by increasing the number of operations in the cremation furnace; The attractions of operating funds through contracts for joint use of the cremation facility with other local governments and investment funds for the expansion of cremation facilities; The plan for controlling the demand in cremation such as an increase in cremation charge for those outside the jurisdiction(residents of other regions), should be considered.