• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권2호
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• pp.504-519
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• 2023

Heart disease is becoming the top reason of death all around the world. Diagnosing cardiac illness is a difficult endeavor that necessitates both expertise and extensive knowledge. Machine learning (ML) is becoming gradually more important in the medical field. Most of the works have concentrated on the prediction of cardiac disease, however the precision of the results is minimal, and data integrity is uncertain. To solve these difficulties, this research creates an Integrated Accurate-Secure Heart Disease Prediction (IAS) Model based on Deep Convolutional Neural Networks. Heart-related medical data is collected and pre-processed. Secondly, feature extraction is processed with two factors, from signals and acquired data, which are further trained for classification. The Deep Convolutional Neural Networks (DCNN) is used to categorize received sensor data as normal or abnormal. Furthermore, the results are safeguarded by implementing an integrity validation mechanism based on the hash algorithm. The system's performance is evaluated by comparing the proposed to existing models. The results explain that the proposed model-based cardiac disease diagnosis model surpasses previous techniques. The proposed method demonstrates that it attains accuracy of 98.5 % for the maximum amount of records, which is higher than available classifiers.

• 한국안전학회지
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• 제18권1호
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• pp.8-13
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• 2003

This study proposes integrity evaluation method of weld zone in rails using high precision distance amplitude characteristics curve(DACC) and ultrasonic signals. For these purposes, the ultrasonic signals for defects(porosity and crack) of weld zone in rails are acquired in the type of time series data and echo strength. 6 lines in the DACC indicated damage evaluation standard of weld zone in rails. The aquired ultrasonic signals agree fairly well with the mesured results of reference block and sensitivity block(defect location, beam propagation distance, echo strength, etc). The proposed high precision DACC in this study can be used for integrity evaluation of weld zone in rails.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2008년도 춘계학술대회
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• pp.185-196
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• 2008

The objective of this study is to evaluate the mechanical behaviors and structural integrity of the weldment of high strength steel by using an acoustic emission (AE) techniques. Simple tension and AE tests were conducted against the 3 kind of welding test specimens. In order to analysis the effectiveness of weldability, joinability and structural integrity, we used K-means clustering method as a unsupervised learning pattern recognition algorithm for obtained multivariate AE main data sets, such as AE counts, energy, amplitude, hits, risetime, duration, counts to peak and rms signals. Through the experimental results, the effectiveness of the proposed method is discussed.

• 수산해양교육연구
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• 제17권2호
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• pp.270-280
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• 2005

Many researchers have proposed the various methods to detect illegal intrusion in order to improve internet environment. Among these researches, IDS(Intrusion Detection System) is classified the most common model to protect network security. In this paper, we propose new log format instead of Apache log format for SSL integrity verification. We translate file-DB log format into R-DB log format. Using these methods we can manage Web server's integrity, and log data is transmitted verification system to be able to perform both primary function of IDS and Web server's integrity management at the same time. The proposed system in this paper is also able to use for wire and wireless environment based on PDA.

• 대한안전경영과학회지
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• 제10권4호
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• pp.127-134
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• 2008

The objective of this study is to evaluate the mechanical behaviors and structural integrity of the weldment of high strength steel by using an acoustic emission (AE) techniques. Monotonic simple tension and AE tests were conducted against the 3 kinds of welded specimen. In order to analysis the effectiveness of weldability, joinability and structural integrity, we used K-means clustering method as a unsupervised learning pattern recognition algorithm for obtained multi-variate AE main data sets, such as AE counts, energy, amplitude, hits, risetime, duration, counts to peak and rms signals. Through the experimental results, the effectiveness of the proposed method is discussed.

• 한국철도학회논문집
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• 제5권2호
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• pp.55-60
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• 2002

This study proposes the post-processor simulator construction of ultrasonic signal for integrity evaluation of railway truck. For these purposes, the ultrasonic signals for defects(crack) of weld zone in frames are acquired in the type of time series data and echo strength. The detection of the natural defects in railway truck is performed using the characteristics of echodynamic pattern in ultrasonic signal. The constructed post-processor simulator agree fairly well with the measured results of test block(defect location, beam propagation distance, echo strength, etc). Proposed post-processor simulator construction of ultrasonic in this study can be used for the integrity evaluation of railway truck.

• 한국철도학회논문집
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• 제6권2호
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• pp.81-86
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• 2003

This study proposes the neural network simulator for the integrity evaluation of weld zone in railway rails. For these purposes, the ultrasonic signals for defects(crack) of weld zone in frames are acquired in the type of time series data and echo strength. The detection of the natural defects in railway truck is performed using the characteristics of echodynamic pattern in ultrasonic signal. And then their applications evaluated feature extraction based on the time-frequency-attractor domain(peak to peak, rise time, rise slope, fall time, fall slope, pulse duration, power spectrum, and bandwidth) and attractor characteristics (fractal dimension and attractor quadrant) etc. The constructed neural network simulator agrees fairly well with the measured results of test block(defect location, beam propagation distance, echo strength, etc). The Proposed neural network simulator in this study can be used for the integrity evaluation of weld zone in railway rails.

• 정보보호학회논문지
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• 제18권5호
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• pp.181-188
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• 2008

E-Science Grid is designed to cope with computation-intensive tasks and to manage a huge volume of science data efficiently. However, certain tasks may involve more than one grid can offer in computation capability or incur a long wait time on other tasks. Resource sharing among Grids can solve this problem with proper processing-integrity check via audit. Due to their computing-intensive nature, the processing time of e-Science tasks tends to be long. This potential long wait before an audit failure encourages earlier audit mechanism during execution in order both to prevent resource waste and to detect any problem fast. In this paper, we propose a Light-weight, Adaptive and Reliable Audit, LARA, of processing Integrity for e-Science applications. With the LARA scheme. researchers can verify their processing earlier and fast.

• 한국노년학
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• 제29권1호
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• pp.231-242
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• 2009

본 연구는 노인을 대상으로 사회적 지지, 학대, 자아통합감 간의 관계를 파악하고 사회적지지, 학대가 자아통합감에 미치는 영향을 확인하기 위하여 시도되었다. 대상자는 만 65세 이상의 재가 노인 306명 이었으며 자료 수집 기간은 2008년 3월부터 6월까지였다. 연구결과 노인의 사회적 지지가 높을수록 자아 통합감이 높은 것으로, 사회적 지지가 낮을수록 학대가 심하고, 학대가 심한수록 자아통합감이 낮은 것으로 조사되었다. 또한 노인 삶의 질을 증진시키는 주요 개념인 자아통합감에 사회적 지지와 학대가 영향을 미치는 것으로 나타났다. 사회적 지지와 학대는 노인의 건강과 안녕을 위한 주요 요소이며, 노인의 발달단계 과업의 성공적인 수행을 위한 주요 요인이므로 사회적 지지를 강화하고 학대를 예방하여 자아통합감을 성취할 수 있는 통합 프로그램이 필요하다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.2198-2222
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• 2019

The cloud storage service becomes a rising trend based on the cloud computing, which promotes the remote data integrity auditing a hot topic. Some research can audit the integrity and correctness of user data and solve the problem of user privacy leakage. However, these schemes cannot use fewer data blocks to achieve better auditing results. In this paper, we figure out that the random sampling used in most auditing schemes is not well apply to the problem of cloud service provider (CSP) deleting the data that users rarely use, and we adopt the probability proportionate to size sampling (PPS) to handle such situation. A new scheme named improving audit efficiency of remote data for cloud storage is designed. The proposed scheme supports the public auditing with fewer data blocks and constrains the server's malicious behavior to extend the auditing cycle. Compared with the relevant schemes, the experimental results show that the proposed scheme is more effective.