• Title/Summary/Keyword: Warning algorithm

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Sinkhole Tracking by Deep Learning and Data Association (딥 러닝과 데이터 결합에 의한 싱크홀 트래킹)

  • Ro, Soonghwan;Hoai, Nam Vu;Choi, Bokgil;Dung, Nguyen Manh
    • The Journal of Korean Institute of Information Technology
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    • v.17 no.6
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    • pp.17-25
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    • 2019
  • Accurate tracking of the sinkholes that are appearing frequently now is an important method of protecting human and property damage. Although many sinkhole detection systems have been proposed, it is still far from completely solved especially in-depth area. Furthermore, detection of sinkhole algorithms experienced the problem of unstable result that makes the system difficult to fire a warning in real-time. In this paper, we proposed a method of sinkhole tracking by deep learning and data association, that takes advantage of the recent development of CNN transfer learning. Our system consists of three main parts which are binary segmentation, sinkhole classification, and sinkhole tracking. The experiment results show that the sinkhole can be tracked in real-time on the dataset. These achievements have proven that the proposed system is able to apply to the practical application.

Malicious Code Injection Vulnerability Analysis in the Deflate Algorithm (Deflate 압축 알고리즘에서 악성코드 주입 취약점 분석)

  • Kim, Jung-hoon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.32 no.5
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    • pp.869-879
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    • 2022
  • Through this study, we discovered that among three types of compressed data blocks generated through the Deflate algorithm, No-Payload Non-Compressed Block type (NPNCB) which has no literal data can be randomly generated and inserted between normal compressed blocks. In the header of the non-compressed block, there is a data area that exists only for byte alignment, and we called this area as DBA (Disposed Bit Area), where an attacker can hide various malicious codes and data. Finally we found the vulnerability that hides malicious codes or arbitrary data through inserting NPNCBs with infected DBA between normal compressed blocks according to a pre-designed attack scenario. Experiments show that even though contaminated NPNCB blocks were inserted between normal compressed blocks, commercial programs decoded normally contaminated zip file without any warning, and malicious code could be executed by the malicious decoder.

Design and Implementation of Location Information System and User Mapping System using DSDV Routing Algorithm in Ad-hoc Network Environment (Ad-hoc 네트워크 환경에서 DSDV 라우팅 알고리즘을 이용한 위치 정보 시스템 및 사용자 맵핑 시스템의 설계 및 구현)

  • Kwak, Jong Wook
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.3
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    • pp.1-9
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    • 2014
  • In this paper, we design and implement location information system and user mapping system using DSDV(Destination Sequenced Distance Vector) routing algorithm in ad-hoc network environment to efficient manage a number of mobile devices. The software part in proposed system construct ad-hoc network using DSDV routing algorithm and it activate alarm system, such as vibration, when one of devices disappears in the network. The hardware system, called u_LIN (User Location Information Node) construct ad-hoc network and it helps to find a disappeared device by using warning system. When we evaluate the performance of our prototype system, we have checked a correct operation, within the range of 250m in case of 1:1 communication and within the range of 100m in case of 1:N communication. The implemented system in this paper is highly expected to flexibly use in juvenile protection system, stray-child protection system, tourist guide system and so on.

A Method of Detecting the Aggressive Driving of Elderly Driver (노인 운전자의 공격적인 운전 상태 검출 기법)

  • Koh, Dong-Woo;Kang, Hang-Bong
    • KIPS Transactions on Software and Data Engineering
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    • v.6 no.11
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    • pp.537-542
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    • 2017
  • Aggressive driving is a major cause of car accidents. Previous studies have mainly analyzed young driver's aggressive driving tendency, yet they were only done through pure clustering or classification technique of machine learning. However, since elderly people have different driving habits due to their fragile physical conditions, it is necessary to develop a new method such as enhancing the characteristics of driving data to properly analyze aggressive driving of elderly drivers. In this study, acceleration data collected from a smartphone of a driving vehicle is analyzed by a newly proposed ECA(Enhanced Clustering method for Acceleration data) technique, coupled with a conventional clustering technique (K-means Clustering, Expectation-maximization algorithm). ECA selects high-intensity data among the data of the cluster group detected through K-means and EM in all of the subjects' data and models the characteristic data through the scaled value. Using this method, the aggressive driving data of all youth and elderly experiment participants were collected, unlike the pure clustering method. We further found that the K-means clustering has higher detection efficiency than EM method. Also, the results of K-means clustering demonstrate that a young driver has a driving strength 1.29 times higher than that of an elderly driver. In conclusion, the proposed method of our research is able to detect aggressive driving maneuvers from data of the elderly having low operating intensity. The proposed method is able to construct a customized safe driving system for the elderly driver. In the future, it will be possible to detect abnormal driving conditions and to use the collected data for early warning to drivers.

Novel Collision Warning System using Neural Networks (신경회로망을 이용한 새로운 충돌 경고 시스템)

  • Kim, Beomseong;Choi, Baehoon;An, Jhonghyun;Hwang, Jaeho;Kim, Euntai
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.4
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    • pp.392-397
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    • 2014
  • Recently, there are many researches on active safety system of intelligent vehicle. To reduce the probability of collision caused by driver's inattention and mistakes, the active safety system gives warning or controls the vehicle toward avoiding collision. For the purpose, it is necessary to recognize and analyze circumstances around. In this paper, we will treat the problem about collision risk assessment. In general, it is difficult to calculate the collision risk before it happens. To consider the uncertainty of the situation, Monte Carlo simulation can be employed. However it takes long computation time and is not suitable for practice. In this paper, we apply neural networks to solve this problem. It efficiently computes the unseen data by training the results of Monte Carlo simulation. Furthermore, we propose the features affects the performance of the assessment. The proposed algorithm is verified by applications in various crash scenarios.

Improvement of Model based on Inherent Optical Properties for Remote Sensing of Cyanobacterial Bloom (고유분광특성을 이용한 남조류 원격 추정 모델 개선)

  • Ha, Rim;Nam, Gibeom;Park, Sanghyun;Kang, Taegu;Shin, Hyunjoo;Kim, Kyunghyun;Rhew, Doughee;Lee, Hyuk
    • Korean Journal of Remote Sensing
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    • v.33 no.2
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    • pp.111-123
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    • 2017
  • The phycocyanin pigment (PC) is a marker for cyanobacterial presence in eutrophic inland water. Accurate estimation of low PC concentration in turbid inland water is challenging due to the optical complexity and criticalforissuing an early warning of potentialrisks of cyanobacterial bloom to the public. To monitor cyanobacterial bloom in eutrophic inland waters, an approach is proposed to partition non-water absorption coefficient from measured reflectance and to retrieve absorption coefficient of PC with the aim of improving the accuracy in remotely estimated PC, in particular for low concentrations. The proposed inversion model retrieves absorption spectra of PC ($a_{pc}({\lambda})$) with $R^2{\geq}0.8$ for $a_{pc}(620)$. The algorithm achieved more accurate Chl-a and PC estimation with $0.71{\leq}R^2{\leq}0.85$, relative root mean square error (rRMSE) ${\leq}39.4%$ and mean relative error(RE) ${\leq}78.0%$ than the widely used semi-empirical algorithm for the same dataset. In particular, low PC ($PC{\leq}50mg/m^3$) and low PC: Chl-a ratio values of for all datasets used in this study were well predicted by the proposed algorithm.

A Simulation of 3-D Navigation System of the Helicopter based on TRN Using Matlab

  • Kim, Eui-Hong;Lee, Hong-Ro
    • Spatial Information Research
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    • v.15 no.4
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    • pp.363-370
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    • 2007
  • This study has been carried for the development of the basic algorithm of helicopter navigation system based on TRN (Terrain Referenced Navigation) with information input from the GPS. The helicopter determines flight path due to Origination-Destination analysis on the Cartesian coordinate system of 3-D DTM. This system shows 3-D mesh map and the O-D flight path profile for the pilot's acknowledgement of the terrain, at first. The system builds TCF (terrain clearance floor) far the buffer zone upon the surface of ground relief to avid the ground collision. If the helicopter enters to the buffer zone during navigation, the real-time warning message which commands to raise the body pops up using Matlab menu. While departing or landing, control of the height of the body is possible. At present, the information (x, y, z coordinates) from the GPS is assumed to be input into the system every 92.8 m of horizontal distance while navigating along flight path. DTM of 3" interval has been adopted from that which was provided by ChumSungDae Co., Ltd..

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Design and Development of Network for Housing Estate Security System

  • Nachin, Awacharin;Mitatha, Somsak;Dejhan, Kobchai;Kirdpipat, Patchanon;Miyanaga, Yoshikazu
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1480-1484
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    • 2003
  • This paper presents the design and development of network for housing estate security system. The system can cover up to 961 houses which can be up to 1,200 meters long transfer rate of 9,600 bps. This system uses checking and warning the abnormal situation. More over this system has ability to control switch on/off the electrical equipment in the house via AC line control system. The system consists of 4 parts. The first part is a security system of each house using MCS-51 microcontroller as a central processing unit scan 32 sensors and control 8 appliances and send alarm. The MCS-51 microcontroller received control signal via telephone used DTMF circuit. The second part is distributed two levels master/slave network implementing after RS-485 serial communication standard. The protocol its base on the OSI (Open Systems Interconnection) 7 layers protocol model design focus on speed, reliability and security of data that is transferred. The network security using encrypt by DES algorithm, message sequence, time stamp checking and authentication system when user to access and when connect new device to this system. Flow control in system is Poll/Select and Stop-and-Wait method. The third part is central server that using microcomputer which its main function are storing event data into database and can check history event. The final part is internet system which users can access their own homes via the Internet. This web service is based on a combination of SOAP, HTTP and TCP/IP protocols. Messages are exchanged using XML format [6]. In order to save the number of IP address, the system uses 1 IP address for the whole village in which all homes and appliance in this village are addressed using internal identification numbers. This proposed system gives the data transfer accuracy over 99.8% and maximum polling time is 1,120 ms.

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TCP NJ+: Packet Loss Differentiated Transmission Mechanism Robust to High BER Environments (TCP NJ+ : 높은 BER에 강인한 패킷 손실 원인별 처리기반 전송방식)

  • Kim, Jung-Rae;Lee, You-Ho;Choo, Hyun-Seung
    • Journal of Internet Computing and Services
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    • v.8 no.5
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    • pp.125-132
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    • 2007
  • Transmission mechanisms that include an available bandwidth estimation algorithm and a packet loss differentiation scheme, in general, exhibit higher TCP performance in wireless networks. TCP New Jersey, known as the best existing scheme in terms of goodput, improves wireless TCP performance using the available bandwidth estimation at the sender and the congestion warning at intermediate routers. Although TCP New Jersey achieves 17% and 85% improvements in goodput over TCP Westwood and TCP Reno, respectively, we further improve TCP New Jersey by exploring improved available bandwidth estimation, retransmission timeout, and recovery mechanisms. Hence, we propose TCP New Jersey PLUS (shortly TCP NJ+), showing that under 1% packet loss rate, it outperforms 3% by TCP New Jersey and 5% by TCP Wes1wood. In 5% packet loss rate, a characteristic of high bit-error-rate wireless network, it outperforms other TCP variants by 19% to 104% in terms of goodput even when the network is in bi-directional congestion.

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Social security aimed disaster response policy based on Big Data application (사회안전을 위한 빅데이터 활용의 재난대응 정책)

  • Choung, Young-chul;Choy, Ik-su;Bae, Yong-guen
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.4
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    • pp.683-690
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    • 2016
  • In modern society, disasters frequently occur, and the effect is getting more massive. Also, unpredictable future increases anxiety about social security. Accordingly, in order to prevent national-scale emergency from happening, it is highly required governments' role as ICT power nation and transition to disaster management system using big data applied service. Thus, e-gov necessarily acquires disaster response system in order to predict and manage disasters. Disasters are linked with some attributes of modern society in diversity, complexity and unpredictability, so various approach and remedies of them will appease the nation's anxiety upon them. For this reason, this manuscript suggests epidemics preactive warning algorithm model as a mean of reduce national anxiety on disaster using big data for social security. Also, by recognizing the importance of e-gov and analyzing problems in weak disaster management system, it suggests political implication for disaster response.