• Title/Summary/Keyword: Behavior detection

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Slope Behavior Analysis Using the Measurement of GFRP Underground Displacement (GFRP 록볼트 계측을 통한 사면 거동 분석)

  • Jin, Ji-Huan;Lim, Hyun-Taek;Bibek, Tamang;Chang, Suk-Hyun;Kim, Yong-Seong
    • Journal of the Korean Geosynthetics Society
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    • v.17 no.4
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    • pp.11-19
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    • 2018
  • Although many researches related to monitoring and automatic measuring devices for early warning system during slope failure have been carried out in Korea and aboard, most of the researches have installed measuring devices on the slope surface, and there are only few researches about warning systems that can detect and warn before slope failure and disaster occurs. In this study, slope failure simulation experiment was performed by attaching sensors to rock bolts, and initial slope behavior characteristics during slope failure were analyzed. Also, the experiment results were compared and reviewed with varied slope conditions, i.e. shotcrete slope and natural slope, and varied material conditions, i.e. GFRP and steel rock bolt. This study can be used as a basic data in development of warning and alarm system for early evacuation through early detection and warning before slope failure occurs in steep slopes and slope failure vulnerable areas.

Fraud Detection in E-Commerce

  • Alqethami, Sara;Almutanni, Badriah;AlGhamdi, Manal
    • International Journal of Computer Science & Network Security
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    • v.21 no.6
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    • pp.312-318
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    • 2021
  • Lack of knowledge and digital skills is a threat to the information security of the state and society, so the formation and development of organizational culture of information security is extremely important to manage this threat. The purpose of the article is to assess the state of information security of the state and society. The research methodology is based on a quantitative statistical analysis of the information security culture according to the EU-27 2019. The theoretical basis of the study is the theory of defense motivation (PMT), which involves predicting the individual negative consequences of certain events and the desire to minimize them, which determines the motive for protection. The results show the passive behavior of EU citizens in ensuring information security, which is confirmed by the low level of participation in trainings for the development of digital skills and mastery of basic or above basic overall digital skills 56% of the EU population with a deviation of 16%. High risks to information security in the context of damage to information assets, including software and databases, have been identified. Passive behavior of the population also involves the use of standard identification procedures when using the Internet (login, password, SMS). At the same time, 69% of EU citizens are aware of methods of tracking Internet activity and access control capabilities (denial of permission to use personal data, access to geographical location, profile or content on social networking sites or shared online storage, site security checks). Phishing and illegal acquisition of personal data are the biggest threats to EU citizens. It have been identified problems related to information security: restrictions on the purchase of products, Internet banking, provision of personal information, communication, etc. The practical value of this research is the possibility of applying the results in the development of programs of education, training and public awareness of security issues.

Analysis and Application of Power Consumption Patterns for Changing the Power Consumption Behaviors (전력소비행위 변화를 위한 전력소비패턴 분석 및 적용)

  • Jang, MinSeok;Nam, KwangWoo;Lee, YonSik
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.4
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    • pp.603-610
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    • 2021
  • In this paper, we extract the user's power consumption patterns, and model the optimal consumption patterns by applying the user's environment and emotion. Based on the comparative analysis of these two patterns, we present an efficient power consumption method through changes in the user's power consumption behavior. To extract significant consumption patterns, vector standardization and binary data transformation methods are used, and learning about the ensemble's ensemble with k-means clustering is applied, and applying the support factor according to the value of k. The optimal power consumption pattern model is generated by applying forced and emotion-based control based on the learning results for ensemble aggregates with relatively low average consumption. Through experiments, we validate that it can be applied to a variety of windows through the number or size adjustment of clusters to enable forced and emotion-based control according to the user's intentions by identifying the correlation between the number of clusters and the consistency ratios.

Game-bot Detection based on Analysis of Harvest Coordinate

  • Choi, Jae Woong;Kang, Ah Reum
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.5
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    • pp.157-163
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    • 2022
  • As the online game market grows, the use of game bots is causing the most serious problem for game services. We propose a harvest coordinate analysis model to detect harvesting bots among game bots of the Massively Multiplayer Online Role-Playing Games(MMORPGs) genre. The proposed model analyzes the player's harvesting behavior using the coordinate data. Game bots can obtain in-game goods and items more easily than normal players and are not affected by realistic restrictions such as sleep time and character manipulation fatigue. As a result, there is a difference in harvesting coordinates between normal players and game bots. We divided the coordinate zones and used these coordinate zone differences to distinguish between game bot players and normal players. We created a dataset with NCSoft's AION log and applied it to a random forest model to detect game bots, and as a result, we derived performance with a recall of 0.72 and a precision of 0.92.

Comparative analysis of existing reinforced concrete buildings damaged at different levels during past earthquakes using rapid assessment methods

  • Sezer Aynur;Hilal Meydanli Atalay
    • Structural Engineering and Mechanics
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    • v.85 no.6
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    • pp.793-808
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    • 2023
  • Türkiye is located in a region where destructive earthquakes are frequently experienced due to its geological characteristics and geographical location. Therefore, considering the possibility of a devastating earthquake at any time, determining the reinforced concrete (RC) building seismic safety, constructed before or after the current seismic buildings code, is one of the most important issues to be completed firstly. For this purpose, rapid assessment methods developed to quickly determine the seismic safety of buildings are available in the literature. Comparison of the principles of Principles of the Determination of Risky Structures-2019, Column and Wall Index Method, P25 Scoring Method and Improved Discriminant Analysis Method, which are among these methods, have been aimed within the scope of this study. Within the scope of this paper, a total of 43 buildings in the Yalova/Çınarcık region of Türkiye that the damage level was determined by street observation method immediately after the 1999 Kocaeli (Izmit) Earthquake; 15 buildings with heavy damage and 28 buildings with moderate damage were examined by rapid assessment methods. Although the risk detection difference was not separated as a clear line in any of the methods used, the results obtained from the rapid assessment methods are evaluated as being compatible with the detected after earthquake structural seismic behavior of the buildings. The PDRS-2019 and column and wall index method gave the most approximate results. In the results obtained from the analyzes; structural features such as number of floors, frame continuity, soft/weak story irregularity, effective shear strength area, existence of heavy overhangs in plan, type of structural system have been found to be significantly effective on the earthquake behavior of buildings.

Finite Element Analysis of Stress and Strain Distribution on Thin Disk Specimen for SCC Initiation Test in High Temperature and Pressure Environment (고온 고압 응력부식균열 개시 시험용 디스크 시편의 응력과 변형에 대한 유한요소 해석)

  • Tae-Young Kim;Sung-Woo Kim;Dong-Jin Kim;Sang-Tae Kim
    • Corrosion Science and Technology
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    • v.22 no.1
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    • pp.44-54
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    • 2023
  • The rupture disk corrosion test (RDCT) method was recently developed to evaluate stress corrosion cracking (SCC) and was found to have great potential for the real-time detection of SCC initiation in a high temperature and pressure environment, simulating the primary water coolant of pressurized water reactors. However, it is difficult to directly measure the stress applied to a disk specimen, which is an essential factor in SCC initiation. In this work, finite element analysis (FEA) was performed using ABAQUSTM to calculate the stress and deformation of a disk specimen. To determine the best mesh design for a thin disk specimen, hexahedron, hex-dominated, and tetrahedron models were used in FEA. All models revealed similar dome-shaped deformation behavior of the disk specimen. However, there was a considerable difference in stress distribution in the disk specimens. In the hex-dominated model, the applied stress was calculated to be the maximum at the dome center, whereas the stress was calculated to be the maximum at the dome edge in the hexahedron and tetrahedron models. From a comparison of the FEA results with deformation behavior and SCC location on the disk specimen after RDCT, the most proper FE model was found to be the tetrahedron model.

Smart Radar System for Life Pattern Recognition (생활패턴 인지가 가능한 스마트 레이더 시스템)

  • Sang-Joong Jung
    • Journal of the Institute of Convergence Signal Processing
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    • v.23 no.2
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    • pp.91-96
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    • 2022
  • At the current camera-based technology level, sensor-based basic life pattern recognition technology has to suffer inconvenience to obtain accurate data, and commercial band products are difficult to collect accurate data, and cannot take into account the motive, cause, and psychological effect of behavior. the current situation. In this paper, radar technology for life pattern recognition is a technology that measures the distance, speed, and angle with an object by transmitting a waveform designed to detect nearby people or objects in daily life and processing the reflected received signal. It was designed to supplement issues such as privacy protection in the existing image-based service by applying it. For the implementation of the proposed system, based on TI IWR1642 chip, RF chipset control for 60GHz band millimeter wave FMCW transmission/reception, module development for distance/speed/angle detection, and technology including signal processing software were implemented. It is expected that analysis of individual life patterns will be possible by calculating self-management and behavior sequences by extracting personalized life patterns through quantitative analysis of life patterns as meta-analysis of living information in security and safe guards application.

Preparation and Oil Absorption Properties of PAN Based 3D Shaped Carbon Nanofiber Sponge (폴리아크릴로니트릴 기반 3D 탄소나노섬유 스펀지의 제조 및 오일 흡착 특성)

  • Hye-Won Ju;Jin-Hyeok Kang;Jong-Ho Park;Jae-Kyoung Ko;Yun-Su Kuk;Changwoo Nam;Byoung-Suhk Kim
    • Composites Research
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    • v.36 no.3
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    • pp.217-223
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    • 2023
  • In this work, the preparation and its oil adsorption behavior of polyacrylonitrile-based carbon nanofiber sponge were investigated. The prepared carbon sponges showed excellent selective oil adsorption in the mixture of water and oil, and the adsorption capacity of reused carbon nanofiber sponge was also investigated. Further, carbon nanofiber sponge adsorbent with internally structured channel showed fast oil adsorption behavior due to a capillary phenomenon. After use, sponge adsorbent was heat-treated at 800℃ under N2 and studied the possibility of a sensor for electrochemical detection of 4-aminophenol.

Object Detection Based on Deep Learning Model for Two Stage Tracking with Pest Behavior Patterns in Soybean (Glycine max (L.) Merr.)

  • Yu-Hyeon Park;Junyong Song;Sang-Gyu Kim ;Tae-Hwan Jun
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2022.10a
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    • pp.89-89
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    • 2022
  • Soybean (Glycine max (L.) Merr.) is a representative food resource. To preserve the integrity of soybean, it is necessary to protect soybean yield and seed quality from threats of various pests and diseases. Riptortus pedestris is a well-known insect pest that causes the greatest loss of soybean yield in South Korea. This pest not only directly reduces yields but also causes disorders and diseases in plant growth. Unfortunately, no resistant soybean resources have been reported. Therefore, it is necessary to identify the distribution and movement of Riptortus pedestris at an early stage to reduce the damage caused by insect pests. Conventionally, the human eye has performed the diagnosis of agronomic traits related to pest outbreaks. However, due to human vision's subjectivity and impermanence, it is time-consuming, requires the assistance of specialists, and is labor-intensive. Therefore, the responses and behavior patterns of Riptortus pedestris to the scent of mixture R were visualized with a 3D model through the perspective of artificial intelligence. The movement patterns of Riptortus pedestris was analyzed by using time-series image data. In addition, classification was performed through visual analysis based on a deep learning model. In the object tracking, implemented using the YOLO series model, the path of the movement of pests shows a negative reaction to a mixture Rina video scene. As a result of 3D modeling using the x, y, and z-axis of the tracked objects, 80% of the subjects showed behavioral patterns consistent with the treatment of mixture R. In addition, these studies are being conducted in the soybean field and it will be possible to preserve the yield of soybeans through the application of a pest control platform to the early stage of soybeans.

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Metabolic syndrome awareness in the general Korean population: results from a nationwide survey

  • Hyun-Jin Kim;Mi-Seung Shin;Kyung-Hee Kim;Mi-Hyang Jung;Dong-Hyuk Cho;Ju-Hee Lee;Kwang Kon Koh
    • The Korean journal of internal medicine
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    • v.39 no.2
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    • pp.272-282
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    • 2024
  • Background/Aims: Metabolic syndrome (MetS) raises the risk of cardiovascular disease and type 2 diabetes. An awareness of MetS is vital for early detection and proactive management, which can mitigate the risks associated with MetS. Therefore, our study aimed to investigate the level of awareness of MetS among the Korean population. Methods: We conducted a nationwide survey between January and February 2023 among a representative sample of the Korean population using an online survey. Information regarding the awareness of MetS and its risk, the importance of lifestyle modification, and health behavior were collected. The question about the awareness of MetS was "How much do you think you know about MetS?" and there were five answers: 1) I know very well, 2) I know well, 3) I know a little, 4) I do not know, and 5) I have no idea. The high-awareness group was defined as those who answered that they knew very well or well. Results: Among 1,000 participants (mean age, 45.7 ± 13.2 yr), 29% were unaware of MetS, and only 20.8% had high awareness. The high-awareness group was significantly more knowledgeable about lifestyle modifications and demonstrated better health behaviors. After adjustment for possible confounding factors, younger age, low household income, and absence of comorbidity were independently associated with a lack of awareness regarding MetS. Conclusions: The high-awareness group showed greater knowledge of the importance of lifestyle modifications and better health behaviors regarding MetS. The findings highlight the need for improved public education and awareness programs regarding MetS.