Earticle

This study was executed as correlation study to investigate the correla-tion between the dimensions of diaphragm movement, and respiratory functions and pressures in accordance with the Gross Motor Function Classification System (GMFCS) levels on children with cerebral palsy as the participants. Forty-three children in the age range of 5–13 years di-agnosed with cerebral palsy as the research participants were divided into three groups (levels I, II, and III) through systematic stratified ran-dom sampling in accordance with their GMFCS levels. Pearson correla-tion analysis was executed to examine the correlation between dimen-sions of diaphragm movement, and respiratory functions and pressures in accordance with the GMFCS levels of the participants. There was no significant correlation between the dimensions of diaphragm move-ment, and respiratory functions and pressures in all of the three groups in accordance with the GMFCS levels of the participants. Therefore, it is deemed that although measurement of the dimensions of diaphragm movement of children with cerebral palsy by using diagnostic ultrason-ic M-mode imaging device can be considered as auxiliary tool in pre-dicting the breathing capabilities, it cannot be used as independent measurement equipment.

표준 기록관리시스템(이하 RMS)이 2007년 중앙행정기관의 도입을 시작으로 현재 지방자치단체, 그 밖의 공공기관에도 도입되어 사용되고 있다. RMS는 전자기록환경에서 기록을 관리하기 위한 필수도구이나, 실제 RMS의 기능들이 표준이나 실무를 잘 반영하고 있는지, 얼마만큼 업무에 활용되고 있는지는 잘 알려져 있지 않다. 본 연구는 이러한 문제의식에서 출발하여, 기록관리시스템에 구현된 기능 중 ‘기준관리’에 대한 평가와 그 의미를 분석하고자 하였다. ‘기준관리’는 RMS상 기록관리기준표·기준정보관리·분류체계지정·재분류로 구성되어 있는데, 이것은 기록관리기준표 관리와 관련된, 다시 말해 기록의 분류와 처분일정의 영역이다. 분류와 처분일정은 기록에 대한 지적 통제의 중심이자 기록관리의 핵심영역이므로, 이것이 시스템에서 그 역할을 제대로 하고 있는지 분석하는 것은 중요한 일이다. 본 연구에서는 RMS의 기준관리에 대하여 기능 평가와 이용 평가를 함께 실시하였다. 기능 평가는 국내외 표준에서 제시하는 기능요건을 RMS가 얼마나 구현하고 있는지를 비교분석한 것이다. 그리고 이용 평가는 그러한 기능들을 얼마만큼 실제로 사용하고 있는지, 문제점은 무엇인지 진단한 것이다. 중앙행정기관과 광역 및 기초 지자체를 대상으로 실시한 이러한 평가를 통해 얻은 시사점들을 제도적, 기능·이용적, 행정적 측면으로 구분하여 정리하였다. RMS 기준관리 기능이, 더 나아가 RMS 시스템 전체가 기록관리 실무에서 원활하게 사용되기 위해 중요한 것은 사용자를 비롯한 이해당사자들의 소통임이 연구과정에서 드러났다. 사용자들은 RMS를 이용하면서 발생하는 요구사항을 지속적으로 제기하여야 하며, 중앙기록물관리기관은 그들의 요구사항을 분석·파악하고 이를 시스템에 반영하여, 시스템을 고도화 시키고 개선하는데 많은 노력을 하여야 한다.

Since central governments began to establish and use the Standard Records Management System(RMS) in 2007, more and more local governments and other public organizations have constructed RMS. RMS is the essential tool for records management in electronic environments, but it is not known how well the functions of RMS reflect standards and practice related records management or how many records managers use RMS in performing their works. This paper deals with analyzing the evaluation of ‘classification & disposal schedule management’ function in RMS. ‘Classification & disposal schedule management’ function has 4 subfunctions of review of classification & preservation period, management of the schedule items, assignment of classification scheme and reclassification. Classification and disposal schedule is at the heart of intellectual control of records and core area of records management. So it is important to analyze whether this function plays well a role in RMS or not. This research carried out evaluation of function and use about classification & disposal schedule management in RMS. Functional evaluation is to compare and analyze how well RMS meets the functional requirements which home and foreign standards give. Use evaluation is to investigate how records managers use RMS in accomplishing their task of managing classification & disposal schedule and to look into what is the problem with the use. This paper could get the implications through the survey of records managers who are working at central governments, regional local governments and basic local governments. And these implications are considered in institutional, functional, use and administrative aspect. It is important to communicate with stakeholders so that ‘classification & disposal schedule management’ function, further, all functions of the RMS in practice of records management could be used smoothly. Users of RMS have to raise demands or call for technical solutions of the problems which come up in use, while RMS developers and administrators must make more of an effort to satisfy their demands, reflect them on the RMS and enhance the system.

본 연구는 한국 표준직업분류에 따른 근로자의 구강기능문제를 파악하고 근로자들이 집단구강건강관리사업의 혜택을 받을 수 있도록 산업안전보건법의 개정을 촉구하기 위한 근거자료로 제공하고자 시행하였다. 국민건강영양조사 제7기 원시자료(1차,2차)를 이용하여 만 19세 이상 한국 표준직업분류에 따른 근로자를 대상으로 씹기문제와 말하기문 제를 조사한 결과 한국 표준직업분류에 따른 근로자의 유형과 씹기문제, 말하기문제의 연관성이 확인되었다(p<0.05). 이에 근로자의 구강건강을 향상시키기 위해서는 집단구강건강관리사업이 실행되어야 하며 집단구강건강관리사업의 주 최가 될 전문성을 갖춘 전문보건의료관리자를 채용할 수 있도록 산업안전보건법이 개정되어야 할 것이다.

This study was conducted to identify the oral function problems of workers according to Korean Standard Classification of Occupations (KSCO) and to provide evidentiary material to promote them to revise the Occupational Safety and Health Act so that workers can benefit from the collective oral healthcare project. For the research materials, it was used the 7th raw data (1st and 2nd) of National Health and Nutrition Examination Survey. It was examined the problems of chewing and speaking for the workers over 19 years old by KSCO. The connection between the types of workers and the problems of chewing and speaking has been confirmed (p<0.05). In order to improve the workers’ oral healthcare, the collective oral healthcare project should be implemented. Therefore, the Occupational Safety and Health Act should be revised to hire professional health care manager with expertise, who will be host of the collective oral healthcare project.

연구목적: 본 연구의 목적은 한국 발달장애학생의 직업능력을 평가함에 있어 Grooved Pegboard Test(GPT)의 타당도를 검증하고 직업수준 분류에 대한 영향력 분석을 통해 한국 직업능력평가 현장에서 GPT의 실질적인 활용 적절성을 검토하는 것이다. 연구방법: GPT의 타당도 검증 및 직업수준 분류에 대한 영향력 분석을 위하여 연구를 두 부분으로 나누어 진행하였다. 연구 1에서는 발달장애학생 82명을 대상으로 KEAD 손기능 작업표본검사와의 상관분석, ROC 곡선분석 비교를 통해 공인타당도를 산출하였다. 연구 2에서는 GPT가 발달장애학생의 직업수준을 반영하는지 알아보기 위해 발달장애학생 66명을 대상으로 체질량지수(BMI), 악력계, VMI, GPT, 고용서비스 다양성 검사의 하위척도(신체능력, 인지능력, 고용준비태도) 검사 결과를 활용하여 상관분석 및 다중회귀분석을 실시하였다. 연구결과: 연구 1에서 GPT는 KEAD 손기능작업표본검사와의 상관은 우세손, 비우세손 모두 적절한 상관관계에 있고, AUC 통계량을 살펴본 결과 ROC 곡선이 적합함을 보여 공인타당도를 충족하였다. 연구 2에서 발달장애학생의 직업수준과 유의미한 상관관계를 보이는 검사는 인지능력, 비우세손 GPT, 우세손 GPT, 고용준비태도, 신체능력, VMI 순으로 나타났다. 다중회귀분석 결과에서 직업수준에 영향을 미치는 주요 변인은 인지능력, 신체능력, 우세손 GPT이었고, 이들 변인은 발달장애학생의 직업수행 수준 분산의 54%를 설명하였다. 결론 또는 시사점: 본 연구는 발달장애학생의 직업능력평가 및 진로설계컨설팅에 있어 GPT가 타당성과 실용적 유용성을 갖추고 있음을 검증하였다. 추가적으로 본 연구의 시사점과 후속연구를 위한 제언을 제시하였다.

Purpose: This study aimed to verify the validity of the Grooved Pegboard Test(GPT) in evaluating the vocational abilities of students with developmental disabilities and to examine its practical applicability in Korean vocational evaluation settings. Method: To verify the validity of GPT, the study was conducted in two parts. In Study 1, the concurrent validity was calculated through correlation analysis and ROC curve analysis with the KEAD hand function work sample test for 82 students with disabilities. In Study 2, to determine the GPT’s ability to reflect vocational performance levels of students with disabilities, correlation and multiple regression analyses were conducted on 66 students with developmental disabilities using the result of BMI, grip dynamometer, VMI, GPT, and subscales of the Employment Service Diversity Assessment (physical ability, cognitive ability, and employment readiness attitudes). Results: In Study 1, the GPT showed appropriate correlations with the KEAD Hand Function Work Sample Test for both dominant and non?dominant hands, and Examination of the AUC statistics revealed that the ROC curve was appropriate, meeting the criteria for public validity. In Study 2, the tests that showed significant correlations with the occupational performance of students with developmental disabilities were cognitive ability, non-dominant hand GPT, dominant hand GPT, employment readiness attitude, physical ability, and VMI, in that order. In addition, the results of multiple regression analysis indicated that the major variables influencing occupational performance were cognitive ability, physical ability, and dominant hand GPT, and theses variables collectively explained 54% of variance in the vocational performance levels of students with developmental disabilities. Conclusion: This study verified the validity and practical utility of the GPT for vocational evaluation and career planning consulting for students with developmental disabilities. Additionally, the implications of these findings and suggestions for future research were presented.

Stroke patients often experience reduced respiratory muscle function, which leads to decreased cardiopulmonary capacity and negatively affects gait and trunk stability. This single- subject study aimed to examine the effects of respiratory muscle strengthening exercises using proprioceptive neuromuscular facilitation (PNF) on respiratory function, trunk stability, gait speed, and endurance in a patient with right-sided hemiplegia. Based on the international classification of functioning, disability and health (ICF), a PNF-based respiratory muscle strengthening program was implemented three times per week for four weeks, with each session lasting 50 minutes. Respiratory function was assessed using forced vital capacity (FVC), maximum inspiratory pressure (MIP), and maximum expiratory pressure (MEP). Gait function was evaluated using the 10 meter walking test (10MWT) and 6-minute walking test (6MWT), and trunk function was measured using the trunk impairment scale (TIS) and a pressure biofeedback device. After the intervention, respiratory function, gait performance, and trunk stability improved, suggesting that PNF-based respiratory muscle strengthening may enhance recovery in individuals with stroke.

Objective: To evaluate the clinical usefulness of ICF (International Classification of Functioning, Disability and Health) through correlation among existing functional evaluation tools and examined environmental factors affecting its function. Method: One hundred eight persons with disabilities living in Seoul were randomly selected according to disability severity categories. Functional Independence Measure (FIM), modified Barthel index (MBI) and ICF were examined and subjects were interviewed by trained rehabilitation doctors and occupational therapists. We compared correlation between these three functional measurements. We coded environmental factors affecting function. That was used in second level of 74 ICF items. Results: The average of FIM, modified Barthel index, capacity and performance scores of ICF was 112.76, 92.97, 5.74 and 3.19. There was a statistical correlation among FIM, Barthel index, and ICF. The facilitator chapters among ICF's environmental factors were support and relationships (51.9%), attitudes (45.8%) in order. Most facilitated second level domains among the 68 items were immediate family (66.77%) and health professionals (52.8%). The most barrier chapters in ICF were product and a technology (19.5%), environment changes (15.5%) in order. Most barrier second level domains were design, construction and technology of buildings for public use (37%) and assets (37.0%). Conclusion: ICF correlates with the existing functional evaluation tool and can facilitate management of activity and participation by linking the result with the environmental factors, which may exacerbate or minimize them.

본 연구는 가스 안전 작업 관리 모바일 앱의 개발을 위하여 다음과 같은 사항을 연구하였다. 기 연구된 초기 연구에 의해 모바일 앱의 시나리오 설계 및 1, 2차 이미지 도출이 완료된 후 후속 연구로 이루어 진 본 연구에 서는 1) 가스 작업의 유형별 분류를 형태별 분류와 위험도 별 분류로 나누어 제안 2) 투핸드 작업의 많은 산업현장 에서 모바일 앱과 작업자의 효과적인 연동을 위한 인터랙션 방안의 연구 및 제안이 이루어졌다. 특히 가스 작업 뿐 아니라 각 산업현장 영역에서 이를 관리하는 메인 시스템과 상호작용하는 모바일 앱의 개발은 국내 최초의 시도 라 할 수 있으며, 다양한 인터랙션 방안을 통해 작업자가 자유롭고 안전하게 작업할 수 있도록 도왔다.

In this paper, we investigated the following items for the development of gas safety work mobile app. In this study, which is a follow-up study after the completion of the scenario design and the first, second image extraction of the mobile app based on the initial research that has been studied, 1) Suggested classification of gas works by type classification and risk classification 2) The research and proposal of interaction method for effective interworking of mobile app and worker in many industrial fields of two-hand work have been made. In particular, the development of a mobile app that interacts with the main system that manages not only the gas work but also the field of each industrial field is the first attempt in Korea and has helped the worker to work freely and safely through various interaction methods.

현실 세계에서는 기존에 알려지지 않은 새로운 유형의 변종 공격이 끊임없이 등장하고 있지만, 인공신경망과 지도학 습을 통해 개발된 공격 트래픽 분류모델은 학습을 실시하지 않은 새로운 유형의 공격을 제대로 탐지하지 못한다. 기존 연구들 대부분은 이러한 문제점을 간과하고 인공신경망의 구조 개선에만 집중한 결과, 다수의 새로운 공격을 정상 트래 픽으로 분류하는 현상이 빈번하게 발생하여 공격 트래픽 분류성능이 심각하게 저하되었다. 한편, 다중분류 문제에서 각 클래스에 대한 분류가 정답일 확률을 결과값으로 출력하는 소프트맥스(softmax) 함수도 학습하지 않은 새로운 유형의 공격 트래픽에 대해서는 소프트맥스 점수를 제대로 산출하지 못하여 분류성능의 신뢰도 또는 정확도를 제고하는데 한계 를 노출하고 있다 . 이에 본 논문에서는 소프트맥스 함수의 이러한 특성을 활용하여 모델이 일정 수준 이하의 확률로 판단한 트래픽을 공격으로 분류함으로써 새로운 유형의 공격에 대한 탐지성능을 향상시키는 방안을 제안하고, 실험을 통해 효율성을 입증한다.

In the real world, new types of attacks or variants are constantly emerging, but attack traffic classification models developed through artificial neural networks and supervised learning do not properly detect new types of attacks that have not been trained. Most of the previous studies overlooked this problem and focused only on improving the structure of their artificial neural networks. As a result, a number of new attacks were frequently classified as normal traffic, and attack traffic classification performance was severly degraded. On the other hand, the softmax function, which outputs the probability that each class is correctly classified in the multi-class classification as a result, also has a significant impact on the classification performance because it fails to calculate the softmax score properly for a new type of attack traffic that has not been trained. In this paper, based on this characteristic of softmax function, we propose an efficient method to improve the classification performance against new types of attacks by classifying traffic with a probability below a certain level as attacks, and demonstrate the efficiency of our approach through experiments.

This study aims to categorize ‘topic coherence function’ of Korean discourse markers and analyze ‘starting a topic function’. First, the study analyzes the functions of discourse markers from the perspective of ‘discourse coherence’ and analyzes their functions to classify them into seven types of coherence layers. The topic coherence function was further divided into ‘macroscopic coherence of topic’ including starting a topic, changing a topic, and returning to a topic and ‘microscopic coherence of topic’ including ‘filling the gap,’ ‘modifying the articulation,’ and ‘listing.’ Then discourse markers provided according to the functions and the usage of each function have been analyzed. A list of discourse markers by function is provided. The significance of the present study comes from systematically classifying the topic coherence functions of discourse markers that have been sporadically suggested and providing a list of discourse markers for Starting a topic function from the perspective of teaching Korean as a foreign language. The results of the present study can be utilized as fundamental data in selecting discourse markers as a lesson and in composing a syllabus.

본 연구는 시민단체 기록의 분류방안을 마련해 보는 데에 연구의 목적을 두고, 환경운동연합을 사례로 환경연합기록의 분류체계 및 처리일정표 개발 과정을 제시해 보았다. 환경연합 기록의 분류원칙으로 기능분류에 주제분류를 결합한 형태의 분류원칙을 적용하였으며, 기능분류체계 개발을 위해 기록관리 업무분석 표준인 AS 5090와 DIRKS 방법론을 활용하였다. 연구 방법으로는 문헌연구, 자료조사, 인터뷰, 업무분석, 설문조사 등을 활용하였다.

This study aims to identify the developing process of classification shemes for NGO records. And it chooses the KFEM(Korea Federation for Environmental Movenment) for case study, which is a representative NGO of Korea. This study proposes the classification principles in the form that the function classification and subject classification are combined. The development model of function classification schemes on the KFEM records is based on the Australian Standard Work Process Analysis for Recordkeeping(AS 5090) and the DIRKS (Designing and Implementing Recordkeeping Systems) methodology. Literature review, interviews, work process analysis, and questionnaire surveys have been employed as research methodology.

The face recognition task involves extraction of unique features from the human face. Manifold learning methods are proposed to project the original data into a lower dimensional feature space by preserving the local neighborhood structure. PCA and LDA are used for the feature extraction and the resultant feature vectors are fused with the different fusion techniques and the proposed method yields good recognition rate with PCA Fusion of PCA and LDA features and those are classified with neural network. In general the size of the face database is too high and it needs more memory and needs more time for training so that to improve time and space complexities there is a need for dimensionality reduction. The extracted features are classified with Neural Network to improve the recognition rate.

At present, information retrieval systems are simply expressed with a combination of keyword search according to the direct keyword matching method to get the information that users need. Because of this, documents retrieval systems serve too many documents due to term ambiguity. This makes the user need extra time and effort to get closer the document. To overcome these problems, this paper proposes the information retrieval system based on the content that connects documents according to the degree of semantic link that expresses a fuzzy value by fuzzy function. This paper also proposes an algorithm that produces a hierarchical structure using the degree of concept and content among documents. As a result, we are able to select and to provide user-interested documents.

In this paper we propose a model of classification based on the principle of the fuzzy proximity of the terms within the documents. Given the heterogeneous nature of the Arabic documents in our possession, we have studied for this purpose the research model based on the semantic proximity of terms and inspired from the classic Boolean model. Our approach is based on the assumption that more the occurrences of terms in query are close with good connectivity in the extracted semantic graph from the set of document , more this document is relevant to this query. We propose a measure that provides a contextual and semantic search. We used not only a semantic graph to highlight the semantic connections between terms, but also an auxiliary dictionary to increase the connectivity of the graph and therefore the discrimination of documents relevant to the query.

본 연구는, 문헌조사를 바탕으로 대한민국의 업무참조모델(BRM)인 ‘정부기능분류체계’의 도입에서 개발․적용에 이르기까지의 행정연혁을 통하여, 정부기능분류체계의 본래 개발목적과 의도를 밝혀내고, 현재 정부기능분류체계에서 관찰되는 문제점과의 관계를 밝힘으로써 현행에서 드러나는 정부기능분류체계의 문제에 대한 원인을 찾아보고자 하였다. 정부기능분류체계의 현황조사 는 정책영역 ‘문화재’ 영역(대기능 9개, 중기능 59개, 소기능 297개와 단위과제 1,287개)을 대상으로 중앙정부와 지방정부의 기능분류체계를 조사하였다. 그 결과, 중앙정부와 지방정부의 기능 간에 분절된 현상과 그밖에 문제점들을 발견하였고, 이를 대표하는 ‘문화재 지정’ 등의 4가지 사례를 통해 개선모형을 제안하였다. 또한, ‘정부기능분류체계’의 재정비를 위하여, 업무재현성을 갖춘 업무기능의 설계, 업무기능의 일관성유지를 위한 관리와 운영에 있어서의 제도마련, 이용자의 사용촉진을 위한 교육, 지속적인 유지관리와 개선이 필요함을 제안하였다.

This study investigated the administrative history, from the introduction of the “Standard of Government Function Classification” (BRM) to its development and application. Through the results of the survey, the causes of the problems observed in the current government’s functional classification system were revealed. The current survey examined the functional classification scheme of the central government and local governments on the “cultural heritage” policy area (9 major functions, 59 middle functions, 297 small functions, and 1,287 unit tasks). It confirmed the problem of the separation of functions between central and local governments as well as other problems. Among the problems, this study proposed an improvement model through four representative cases such as the “designation of cultural heritage.” In order to reorganize the “Standard of Government Function Classification,” it is necessary to design a business function with the reproduction of tasks, establish a system for management and operation in order to maintain the consistency of the business function, educate users, and suggest continuous improvement.

주행 중인 차량의 타이어와 노면 사이에서 발생하는 랜덤성 초음파신호의 주기성을 검출하여 타이어의 손상을 분별하는 방법에 대하여 연구하였다. 잡음으로부터 타이어손상에 의한 유효한 펄스를 검출하기 위해 적응 임계치를 설정하는 방법을 제안하였고, 이를 위한 전처리로서 신호의 랜덤성을 감소시키는 저역통과필터를 사용하였다. 자동차의 속도에 따라 검출된 펄스의 시간간격을 밀도함수화하고 피크점의 시간을 측정하여 타이어 손상물질을 검출하는 방법을 제안하였다. 손상물질이 한 개이고, 주행속도가 50km/h, 80km/h, 100km/h 일 때, 시간밀도함수의 제 1 피크시간 측정결과는 각각 169.8ms, 97.9ms, 81.8ms로 주행속도에 따라 계산한 타이어 회전주기의 오차범위내로 측정되었으며, 한 개 이상의 손상물질의 경우에는 각 피크시간의 합이 타이어 회전주기의 오차범위내로 측정되는 결과를 얻을 수 있었다.

The tire damage classification method is researched on the periodicity detection of ramdomness ultrasonic signals to occur at the driving vehicle tire. Setting method of adaptive threshold is proposed in order to valid pulse detection by tire damage in ultrasonic noise on the road and used low pass filter for decrease signal ramdomness as preprocessing. Time interval of detected pulse is setted the density function depend on the vehicle's speed and the method of tire damage detection is proposed that measuring the first peak's time of time density function.The result of time density function in case of one damage material, the first peak's time is measured within the error limit of tire's rotation period, 169.8ms and 97.9ms and 81.8ms , about the speed of 50km/h and 80km/h and 100km/h. In case of more than one damage material, the sum of each peak's time is measured within the error limit of tire's rotation period about the speed.

데이터 불균형은 분류 문제에서 흔히 마주치는 문제로, 데이터셋 내의 클래스간 샘플 수의 현저한 차이에서 기인 한다. 이러한 데이터 불균형은 일반적으로 분류 모델에서 과적합, 과소적합, 성능 지표의 오해 등의 문제를 야기한다. 이를 해결하기 위한 방법으로는 Resampling, Augmentation, 규제 기법, 손실 함수 조정 등이 있다. 본 논문에서는 손실 함수 조정에 대해 다루며 특히, 불균형 문제를 가진 Multi-Class 블랙박스 동영상 데이터에서 여러 구성의 손실 함수(Cross Entropy, Balanced Cross Entropy, 두 가지 Focal Loss 설정: α = 1 및 α = Balanced, Asymmetric Loss)의 성능을 I3D, R3D_18 모델을 활용하여 비교하였다.

Data imbalance is a common issue encountered in classification problems, stemming from a significant disparity in the number of samples between classes within the dataset. Such data imbalance typically leads to problems in classification models, including overfitting, underfitting, and misinterpretation of performance metrics. Methods to address this issue include resampling, augmentation, regularization techniques, and adjustment of loss functions. In this paper, we focus on loss function adjustment, particularly comparing the performance of various configurations of loss functions (Cross Entropy, Balanced Cross Entropy, two settings of Focal Loss: α = 1 and α = Balanced, Asymmetric Loss) on Multi-Class black-box video data with imbalance issues. The comparison is conducted using the I3D, and R3D_18 models.

주행 중인 차량의 타이어에서 발생하는 초음파 신호의 포락선에서 손상 물질에 의한 특징 신호의 주기를 검출하여 타이어 손상을 분별하는 방법을 연구하였다. 손상된 타이어는 주행 시 회전에 의해 주기성을 갖는 신호를 발생하기 때문에 이를 펄스화하고 펄스 간의 시간 간격을 밀도함수로 나타내어 우성 주기를 검출하였다. 펄스화하기 위한 임계값은 포락선 신호를 이동평균필터 처리하여 결정하였다. 손상물질이 한 개이고, 주행속도가 약 50km/h, 80km/h일 때, 시간밀도함수의 결과는 제 1 피크시간이 156ms, 102ms로 주행속도에 따라 계산한 타이어의 회전주기와 일치하였고, 한 개 이상의 손상물질의 경우에는 각 피크시간의 합이 타이어의 회전주기와 동일한 결과를 얻을 수 있었다.

The tire damage classification method is researched by periodicity detection of ultrasonic envelope signals to occur at the driving vehicle tire. Because periodic signals is generated by rotations of the damaged tire, it should convert to pulse for using the density function. After time intervals of pulses are represented by the density function, the dominant periodicity is detected. The threshold to make a pulse is calculated by moving average of envelope signals. The result of time density function in case of one damage material, the first peak's time is equals to tire's rotation period, 162ms and 102ms, about the speed of 50km/h and 80km/h. In case of more than one damage material, the sum of each peak's time is equals to tire's rotation period about the speed.

We propose some methods to obtain optimal thresholds and classification functions by using various cutoff criterion based on the bivariate ROC curve that represents bivariate cumulative distribution functions. The false positive rate and false negative rate are calculated with these classification functions for bivariate normal distributions.