본 연구에서는 탄소나노튜브(CNT) 패치 센서를 기반으로 하여 구조물의 이상 거동을 감지하고 대 응할 수 있도록 하는 첨단 스마트 모니터링 시스템을 제안한다. 복합소재로 제작되는 CNT 센서는 유 연한 특성을 갖게 되어 다양한 형태의 구조물 표면에 적용할 수 있으며, 이를 통해 충격이나 피로 등 에 의해 발생되는 균열과 같은 비정상적인 거동을 감지할 수 있다. CNT 센서를 통해 수집한 데이터 는 IoT 시스템을 통해 실시간으로 분석되어 구조물의 거동 상태를 확인하고 건전성을 모니터링 할 수 있게 한다. 이 시스템의 성능 검증 및 사용성 검토를 위해 미국 소재 교량에서 실증 테스트를 하였으 며, 테스트 결과 CNT 센서를 이용한 구조물 거동 감지 시스템을 통해 구조물의 이상 거동을 효과적 으로 감지하고 모니터링하여 구조물에서 발생 될 수 있는 잠재적 문제를 사전에 예방할 수 있음을 확 인하였다. 이와 같은 기술은 추후 다양한 분야에서 적극적으로 활용될 수 있을 것으로 기대된다.

Recently, extreme terrorist attacks have frequently occurred around the world and are threatening the international community. It is no longer a safe zone for terrorism in our country. Therefore, domestic nuclear facilities as the highest level of national security facilities have established a physical protection system to protect facilities and lives against terrorist attacks. In addition, security search and access control are conducted for controlled items and unauthorized person. However, with the development of science and technology, disguised weapons or homemade explosives used in terrorism are becoming very sophisticated. Therefore, nuclear facilities need to strengthen security search of weapons or homemade explosives. Since these disguised weapons or homemade explosives are difficult to find only through security search, it is also necessary to actively identify unspecified people who possess disguised weapons or do abnormal behavior. For this reason, the “Abnormal Behavior Detection Method”, which is very effective in preemptive response to potential terrorist risks, has been introduced and operated in aviation security field. Korea Institute of Nuclear Nonproliferation and Control (KINAC) has established a “Practice Environment for Identifying Disguised Weapons” in 2020 for trainees to recognize the dangers of controlled items and to use for physical protection education. This Practice environment has not only the basic explanation of the controlled items of nuclear facilities, but also various actual disguised weapons were displayed. It also introduces actual terrorist incidents using homemade explosives such as attempted bombing of a cargo plane bound for Chicago and the Boston Marathon bombing. And then a model of the disguised explosives actually used is displayed and used for education. In addition, in 2022, the “Abnormal behavior detection method” education module was developed and used for physical protection education. In this module, the outline and introduction of the “Abnormal Behavior Detection Method” and “Behavior Detection Officer (BDOs)” are explained. In this way, the access control and security search system of nuclear facilities require the overall monitoring system, not only for dangerous goods but also for identification of persons possess and carrying them. This study describes the development of the Curriculum for “Disguised Weapon Identification” and “Abnormal Behavior Detection Method” to enhance the effectiveness of physical protection education.

Purpose: This study aimed to develop a web-based video program related to abnormal mental disorder behaviors in standardized patients and verify its effectiveness for nursing students. Methods: This study consisted of pre-test and post-test for a non-equivalent control group design. The participants were 46 nursing students(experimental group: 23, control group: 23). The experimental group was trained in a video program that applied standardized patients, while the control group received traditional training. Data collected from March to June, 2020, were analyzed using IBM SPSS Statistics for Windows, version 25.0, chi-square test, Fisher's exact test, Mann-Whitney U test, and independent t-test. Results: The difference between the experimental and control groups was statistically significant in terms of learning satisfaction (Z=2.08, p=.038), learning self-efficacy(t=2.80, p=.009), motivation for transfer(t=3.45, p=.001), and clinical reasoning competence(t=2.28, p=.028). Conclusion: This study showed that a video program on abnormal mental disorder behaviors in standardized patients is an effective tool for mental health nursing education.

NKN [(Na,K)NbO3] is a candidate lead-free piezoelectric material to replace PZT [Pb(Zr,Ti)O3]. A single crystal has excellent piezoelectric-properties and its properties are dependent of the crystal orientation direction. However, it is hard to fabricate a single crystal with stoichiometrically stable composition due to volatilization of sodium during the growth process. To solve this problem, a solid solution composition is designed (Na,K)NbO3-Ba(Cu,Nb)O3 and solid state grain growth is studied for a sizable single crystal. Ceramic powders of (Na,K)NbO3-M(Cu,Nb)O3 (M = Ca, Sr, Ba) are synthesized and grain growth behavior is investigated for different temperatures and times. Average normal grain sizes of individual specimens, which are heat-treated at 1,125 oC for 10 h, are 6.9, 2.8, and 1.6 m for M = Ca, Sr, and Ba, respectively. Depending on M, the distortion of NKN structure can be altered. XRD results show that (NKN-CaCuN: shrunken orthorhombic; NKN-SrCuN: orthorhombic; NKN-BaCuN: cubic). For the sample heat-treated at 1,125 oC for 10 h, the maximum grain sizes of individual specimens are measured as 40, 5, and 4,000 m for M = Ca, Sr, and Ba, respectively. This abnormal grain size is related to the partial melting temperature (NKN-CaCuN: 960 oC; NKN-SrCuN: 971 oC; NKN-BaCuN: 945 oC).

Pb(Zr,Ti)O3 (PZT) is used for the various piezoelectric devices owing to its high piezoelectric properties. However, lead (Pb), which is contained in PZT, causes various environment contaminations. (K,Na)NbO3 (NKN) is the most well-known candidate for a lead-free composition to replace PZT. A single crystal has excellent piezoelectric-properties and its properties can be changed by changing the orientation direction. It is hard to fabricate a NKN single crystal due to the sodium and potassium. Thus, (Na,K)NbO3-Ba(Cu,Nb)O3 (NKN-BCuN) is chosen to fabricate the single crystal with relative ease. NKNBCuN pellets consist of two parts, yellow single crystals and gray poly-crystals that contain copper. The area that has a large amount of copper particles may melt at low temperature but not the other areas. The liquid phase may be responsible for the abnormal grain growth in NKN-BCuN ceramics. The dielectric constant and tan δ are measured to be 684 and 0.036 at 1 kHz in NKN-BCuN, respectively. The coercive field and remnant polarization are 14 kV/cm and 20 μC/cm2.

The spontaneous mutant circling mouse (cir/cir) shows a circling behavior and hearing loss. We produced transgenic mice overexpressing transmembrane inner ear (tmie) gene, the causative gene, for the phenotypic rescue of the circling mouse. Through the continuous breeding with circling mice, the cir/cir homozygous mice carrying the transgene (cir/cir‐gtg) were produced. The rescued cir/cir‐gtg mice were able to swim in the water with proper orientation and did not show any circling behavior like wild type mice. Western blot and immunohistochemical analysis exhibited that the transgenic tmie was expressed in the inner ear. Inner and outer hair cells were recovered in the cochlea and spiral ganglion neurons were also recovered in the rescued mice. Auditory brainstem response (ABR) test demonstrated that the cir/cir‐gtg mice are able to respond to sound. This study demonstrates that tmie transgene can recover the hearing impairment and abnormal behavior in the circling mouse.

BaTiO3세라믹에서 미세구조를 조절하기 위하여 Ba/Ti비 변화에 따른 소결거동 및 비정상 입자성장에 대하여 연구하였다. 본 연구에서 사용한 BaTiO3분말은 BaCO3와 TiO2를 이용하여 일반적인 고상반응법으로 제조하였다. Ba/Ti비가 감소할수록(과잉 TiO2가 증가할수록)소결 시작온도가 낮아졌으며 치밀화가 증진되었다. 이것은 과잉 TiO2양이 증가할수록 하소된 분말의 크기가 감소되었기 때문으로 판단되며, 공융액상 형성으로 인한 액상소결에 의한 것이 아님을 알 수 있었다. 또한 과잉 TiO2양이 증가할수록 입자성장이 강력하게 억제되었으며, 이는 Ti-rich 이차상이 입자성장을 억제시킴을 의미한다. 따라서 이러한 이차상의 불균일한 분포로 인하여 비정상 입자성장이 일어나는 것으로 판단되었다.

This study investigates the behavior of foreign investors in the Stock Exchange of Thailand (SET) in the time of coronavirus disease 2019 (COVID-19) as to whether trading is abnormal, what strategy is followed, whether herd behavior is present, and whether the actions destabilize the market. Foreign investors’ trading behavior is measured by net buying volume divided by market capitalization, whereas the stock market behavior is measured by logged return on the SET index portfolio. The data are daily from Tuesday, August 28, 2018, to Monday, May 18, 2020. The study extends the conditional-regression model in an event-study framework and extracts the unobserved abnormal trading behavior using the Kalman filtering technique. It then applies vector autoregressions and impulse responses to test for the investors’ chosen strategy, herd behavior, and market destabilization. The results show that foreign investors’ abnormal trading volume is negative and significant. An analysis of the abnormal trading volume with stock returns reveals that foreign investors are not positive-feedback investors, but rather, they self-herd. Although foreign investors’ abnormal trading does not destabilize the market, it induces stock-return volatility of a similar size to normal trade. The methodology is new; the findings are useful for researchers, local authorities, and investors.

This paper introduces unfamiliarity index (UFI) that calculated from the FFT results of the short term timeline acceleration responses. If this algorithm, which can detect an abnormal behavior from the maximum constant signal, is used to the terminal sensors of an structure, more accurate safety control criteria will be prepared efficiently.

The collapse of a large infrastructure cause serious losses. Therefore, there has been an increasing demand in using Structural Health Monitoring techniques for the building structures so that their maintenance cost and time can be reduced. In this study, a experimental evaluation of abnormal behavior using data from a seismograph that already installed for potential of low-cost safety assessment.

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.

All living organisms use memory and oblivion algorithms considering the estimated lifetime and the changes in the ambient environment. Because of the expected lifetime of a bridge is similar to the human’s one, if a bridge uses the same algorithm of human memory, the abnormal responses of the structure can be easily detected. This paper introduces unfamiliarity index (UFI) that calculated from the FFT results of the short term timeline acceleration responses. If this algorithm, which can detect an abnormal behavior from the maximum constant signal, is used to the terminal sensors of an structure, more accurate safety control criteria will be prepared efficiently.