• Journal of radiological science and technology
• /
• v.24 no.1
• /
• pp.33-41
• /
• 2001

This study is to get preliminary data for an effectiveness evaluation of abdominal examination and improvement of it. Abnormal cases of abdominal ultrasonography are classified by sex, frequency, diagnosis and age. 4,924 examinees were included at a university hospital of health promotion center from January to December in 1999. The results are as follows. 1. According to the distribution of sex, there are more male patients(55.0%) than females patients(48.0%). For men, 40's showed the highest percentage among examinees. For women, 50's were the highest. 2. The reason that they visited the health promotion center was that 'they wanted to check their health status'. This answers were reported the highest(59.3%). 3. Patients that had abnormal cases of abdominal ultrasonography were 48.3%. Liver, kidney, gallbladder showed the highest percentage of abnormal cases in order of organs. Additionally, abnormal cases were discovered in liver cases. 4. According to the frequency of abnormal cases among examinees, the slight fatty liver were the highest regardless of sex. Men had the slight fatty liver, kidney simple cyst, liver calcification and liver simple cyst in order of abnormal cases. Women showed the slight fatty liver kidney simple cyst, kidney calcification, liver simple cyst, and blood vessel tumor in order of abnormal cases. 5. For the abnormal cases of liver by sex and age, the 50's reported the highest number of abnormal cases in men(299 patients). In addition, 60's had the highest of disease rata 47.8%. For women, 50's reported the highest number of abnormal cases(361 patients). Over 70's patients had the highest of disease rata 52.6%. For kidney, men and women showed the highest number of abnormal cases -62 vs 44 respectively. Over 70's patients had the highest percentage of disease rata-23.2% vs 14.0% respectively. For gallbladder, the number of abnormal cases were the most in men's 60's (31 patients) and in women's in the same age group (32patients). Disease showed the highest percentage in men's 60's(7.6%) and in women's 70's (14.0%). 6. According to malignant tumor, 17patients were liver cancer, 2patients stomach ca and 1pt kidney cancer. 7. The relationship between the malignant tumor and the examination motive was that 'they wanted to check their health status(41.0%)' and 'regular checkup (24.0%)'.

• Proceedings of the Korean Information Science Society Conference
• /
• 2003.10c
• /
• pp.229-231
• /
• 2003

기존에 제시된 ad hoc 라우팅 프로토콜에는 안정성에 대한 부분이 고려되어 있지 않다. 본 논문에서는 기존의 DSR ad hoc 라우팅 프로토콜에 안정성을 접목한 SDSR 라우팅 프로토콜을 제시한다. SDSR은 DSR에 안정성 제공을 위해 abnormal node detector와 neighbor table이라는 것을 추가한다. abnormal node detector는 네트워크 내에 abnormal 노드를 탐지해 네트워크에서 고립시켜 네트워크에 안정성을 제공하고 neighbor table에 있는 priority를 값에 따라 이웃 노드에서 들어온 패킷을 처리함으로써 효율적인 처리 능력을 제공한다. 본 논문에서는 abnormal node detector와 neighbor table을 통해 어떤 방식으로 네트워크에 안정성을 제공하는지 살펴보도록 하겠다.

• Journal of the Korean Data and Information Science Society
• /
• v.18 no.3
• /
• pp.619-628
• /
• 2007

This study is devoted to suggesting the norm of detection abnormal users who are inferior to the other users in the recommender system compared with estimation accuracy. To select the abnormal users, we propose the pre-filtering method by using the preference ratings to the item rated by users. In this study, the experimental result shows the possibility of detecting the abnormal users before the process of preference estimation through the prediction algorithm. And It will be possible to improve the performance of the recommender system by using this detecting norm.

• Journal of information and communication convergence engineering
• /
• v.9 no.4
• /
• pp.466-470
• /
• 2011

This paper proposes the new method based on fuzzy logic which recognizes between normal and abnormal. The object image was the Thyroid Gland cell image that was diagnosed as normal and abnormal(two types of abnormal : follicular neoplastic cell, and papillary neoplastic cell), respectively. The nuclei were successfully diagnosed as normal and abnormal. The multiple feature parameters (pre-obtained 16 feature parameters of image data) were used to extract the features of each nucleus. As a consequence of using fuzzy logic algorithm, proposed in this paper, average recognition rate of 98.25% was obtained.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.26 no.5
• /
• pp.314-326
• /
• 2014

On 31 March 2007, the abnormal wave occurred along the western coast of Korea. In order to investigate the generation mechanism of abnormal waves and to understand the amplification process of the abnormal waves, the observed data were analyzed and one-dimensional numerical model experiments were performed by using both the linear shallow water equation and the linear Boussinesq equation models. Various types of pressure jump for the abnormal waves previously proposed by other researchers were reviewed. As a result, it was not possible to reproduce the abnormal waves from the previously proposed pressure jumps. In this study, we proposed a new form of pressure jump, and numerical simulations were performed in order to check the validity of the proposed pressure jump. The numerical results showed that the calculated period of abnormal waves and the maximum water elevations agreed reasonably well with those of the observations.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.19 no.2
• /
• pp.92-98
• /
• 2015

Recently, buildings tend to be large size, complex shape and functional. As the size of buildings is becoming massive, the need for structural health monitoring (SHM) technique is increasing. Various SHM techniques have been studied for buildings which have different dynamic characteristics and influenced by various external loads. "Abnormal behavior point" is a moment when the structure starts vibrating abnormally and this can be detected by comparing between before and after abnormal behavior point. In other words, anomalous behavior is a sign of damage on structures and estimating the abnormal behavior point can be directly related to the safety of structure. Abnormal behavior causes damage on structures and this leads to enormous economic damage as well as damage for humans. This study proposes an estimating technique to find abnormal behavior point using Hilber-Huang Transform which is a time-frequency signal analysis technique and the proposed algorithm has been examined through laboratory tests with a bridge model using a shaking table.

• Journal of Sensor Science and Technology
• /
• v.29 no.4
• /
• pp.249-254
• /
• 2020

It is difficult to control children who exhibit negative behavior in dental clinics. Various methods are used for preventing pediatric dental patients from being afraid and for eliminating the factors that cause psychological anxiety. However, when it is difficult to apply this routine behavioral control technique, sedation therapy is used to provide quality treatment. When the sleep anesthesia treatment is performed at the dentist's clinic, it is challenging to identify emergencies using the current breath detection method. When a dentist treats a patient that is under the influence of an anesthetic, the patient is unconscious and cannot immediately respond, even if the airway is blocked, which can cause unstable breathing or even death in severe cases. During emergencies, respiratory instability is not easily detected with first aid using conventional methods owing to time lag or noise from medical devices. Therefore, abnormal breathing needs to be evaluated in real-time using an intuitive method. In this paper, we propose a method for identifying abnormal breathing in real-time using an intuitive method. Respiration signals were measured using a 3M Littman electronic stethoscope when the patient's posture was supine. The characteristics of the signals were analyzed by applying the signal processing theory to distinguish abnormal breathing from normal breathing. By applying a short-time Fourier transform to the respiratory signals, the frequency range for each patient was found to be different, and the frequency of abnormal breathing was distributed across a broader range than that of normal breathing. From the wavelet transform, time-frequency information could be identified simultaneously, and the change in the amplitude with the time could also be determined. When the difference between the amplitude of normal breathing and abnormal breathing in the time domain was very large, abnormal breathing could be identified.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.32 no.4
• /
• pp.647-660
• /
• 2022

Recent works demonstrate that the semi-supervised anomaly detection method functions quite well in the environment with normal data and some anomalous data. However, abnormal data shortages can occur in an environment where it is difficult to reserve anomalous data, such as an unknown attack in the cyber security fields. In this paper, we propose ADA-PH(Abnormal Data Augmentation Method using Perturbation based on Hypersphere), a novel anomalous data augmentation method that is applicable in an environment where abnormal data is insufficient to secure the performance of the semi-supervised anomaly detection method. ADA-PH generates abnormal data by perturbing samples located relatively far from the center of the hypersphere. With the network intrusion detection datasets where abnormal data is rare, ADA-PH shows 23.63% higher AUC performance than anomaly detection without data augmentation and even performs better than the other augmentation methods. Also, we further conduct quantitative and qualitative analysis on whether generated abnormal data is anomalous.

• Journal of Digital Convergence
• /
• v.20 no.1
• /
• pp.399-414
• /
• 2022

The purpose of this study was to test the structural model for the effect on abnormal eating behavior targeting 493 nurses. Results, The direct effects of variables affecting abnormal eating behavior were in the order of eating abstinence and socially imposed perfectionism, and these variables explained 85% of abnormal eating behavior. Explicit narcissism had a significant effect on abnormal eating behavior through socially imposed perfectionism and eating restraint, and sociocultural attitude toward appearance through eating restraint. In the multi-group moderating effect, the path coefficients between job stress and abnormal eating behavior, socially imposed perfectionism and abnormal eating behavior were different between groups. Therefore, it is necessary to find a way to lower the socially-imposed perfectionism and nursing intervention that can escape excessive eating abstinence.

• Journal of the East Asian Society of Dietary Life
• /
• v.16 no.6
• /
• pp.702-706
• /
• 2006

The aim of this study was to identify the onuses of abnormal precipitation in buckwheat extracts and to suggest the preventive solutions. Abnormal precipitation was formed by the coagulations of small round droplets, and increased when poor quality or old buckwheat used. It was found that, unlike poor quality buckwheat, extracts made from fresh buckwheat showed almost no saccharifying enzyme activity and a lower number of microorganisms. The addition of branched starch to the extracts restricted the occurrence of abnormal precipitation and microorganisms and imparted stability to the extracts.