• Title/Summary/Keyword: Safety algorithm

Search Result 1,835, Processing Time 0.031 seconds

A Study on the Detecting of Noncontact Biosignal using UWB Radar (UWB 레이더를 이용한 비접촉 생체신호 검출에 관한 연구)

  • Lee, Yonggyu;Cho, Joonggil;Kim, Taesung
    • Journal of the Korea Safety Management & Science
    • /
    • v.21 no.4
    • /
    • pp.1-6
    • /
    • 2019
  • This study relates to acquiring biological signal without attaching directly to the user using UWB(Ultra Wide Band) radar. The collected information is the respiratory rate, heart rate, and the degree of movement during sleep, and this information is used to measure the sleep state. A breathing measurement algorithm and a sleep state detection algorithm were developed to graph the measured data. Information about the sleep state will be used as a personalized diagnosis by connecting with the medical institution and contribute to the prevention of sleep related diseases. In addition, biological signal will be linked to various sensors in the era of the 4th industrial revolution, leading to smart healthcare, which will make human life more enriching.

An Population Management Genetic algorithm on coordinated scheduling problem between suppliers and manufacture (부품 공급업자와 조립업자간의 공동 일정계획을 위한 모집단 관리 유전 해법)

  • Yang, Byoung-Hak;Badiru, Adedeji B.
    • Journal of the Korea Safety Management & Science
    • /
    • v.11 no.3
    • /
    • pp.131-138
    • /
    • 2009
  • This paper considers a coordinated scheduling problem between multi-suppliers and an manufacture. When the supplier has insufficient inventory to meet the manufacture's order, the supplier may use the expedited production and the expedited transportation. In this case, we consider a scheduling problem to minimize the total cost of suppliers and manufacture. We suggest an population management genetic algorithm with local search and crossover (GALPC). By the computational experiments comparing with general genetic algorithm, the objective value of GALPC is reduced by 8% and the calculation time of GALPC is reduced by 70%.

A Study on the Relation between Multivariate Process Control Techniques and Trend Algorithm (다변량 공정관리 기술과 추세알고리즘의 연계에 관한 조사연구)

  • Jung, Hae-Woon
    • Journal of the Korea Safety Management & Science
    • /
    • v.13 no.4
    • /
    • pp.225-235
    • /
    • 2011
  • Autoregressed Controller, which have trend algorithm, seeks to minimize variability by transferring the output variable to the related process input variable, while multivariate process control techniques seek to reduce variability by detecting and eliminating assignable causes of variation. In the case of process control, a very reasonable objective is to try to minimize the variance of the output deviations from the target or set point. We also investigate algorithm with relevant Shewhart chart, Theoretical control charts, precontrol and process capability. To help the people who want to make the theoretical system, we compare the main techniques in "a study on the relation between multivariate process control techniques and trend algorithms".

An Efficient Algorithm for Balancing and Sequencing of Mixed Model Assembly Lines (혼합모델 조립라인의 작업할당과 투입순서 결정을 위한 효율적인 기법)

  • Kim Dong Mook;Kim Yong Ju;Lee keon Shang;Lee Nam Seok
    • Journal of the Korea Safety Management & Science
    • /
    • v.7 no.3
    • /
    • pp.85-96
    • /
    • 2005
  • This paper is concerned with the integrated problem of line balancing and model sequencing in mixed model assembly lines(MMALBS), which is important to efficient utilization of the lines. In the problem, we deal with the objective of minimizing the overall line length To apply the GAs to MMALBS problems, we suggest a GA representation which suitable for its problems, an efficient decoding technique for the objective, and genetic operators which produce feasible offsprings. Extensive experiments are carried out to analyze the performance of the proposed algorithm. The computational results show that our algorithm is promising in solution quality.

A Study on the Optimal Routing Planning Algorithm for Rescue of Multiple Victims in Disaster Area (재난 지역 다수 조난자 구조를 위한 최적 경로 계획 알고리즘 연구)

  • Kim, Ki-Tae;Cho, Sung-Jin;Jeon, Geon-Wook
    • Journal of the Korea Safety Management & Science
    • /
    • v.12 no.2
    • /
    • pp.17-23
    • /
    • 2010
  • The large-scale disasters occur to unexpected accidents such as natural disasters(earthquake, typhoon, tsunami, etc.), and human-caused accidents(fire, collapse, terror etc.). Rescue teams perform rescue activities to save many lives in large-scale disaster area. The main purpose of this study is to compose a optimal routing planning for rescue of multiple victims in disaster area. A realistic routing planning with rescue limit time which considers rehabilitation and reconstruction will be suggested in this study. A mathematical programming model and a hybrid genetic algorithm will be suggested to minimize the total spending time. By comparing the result, the suggested algorithm gives a better solution than existing algorithms.

Sequencing Problem to Keep a Constant Rate of Part Usage In Mixed Model Assembly Lines : A Genetic Algorithm Approach (혼합모델 조립라인에서 부품사용의 일정률 유지를 위한 생산순서 결정 : 유전알고리즘 적용)

  • Hyun, Chul-Ju
    • Journal of the Korea Safety Management & Science
    • /
    • v.9 no.4
    • /
    • pp.129-136
    • /
    • 2007
  • This paper considers the sequencing of products in mixed model assembly lines under Just-In-Time (JIT) systems. Under JIT systems, the most important goal for the sequencing problem is to keep a constant rate of usage every part used by the systems. The sequencing problem is solved using Genetic Algorithm Genetic Algorithm is a heuristic method which can provide a near optimal solution in real time. The performance of proposed technique is compared with existing heuristic methods in terms of solution quality. Various examples are presented and experimental results are reported to demonstrate the efficiency of the technique.

Personalized Prediction Algorithm of Physical Activity Energy Expenditure through Comparison of Physical Activity (신체활동 비교를 통한 개인 맞춤형 신체활동 에너지 소비량 예측 알고리즘)

  • Kim, Do-Yoon;Jeon, So-Hye;Pai, Yoon-Hyung;Kim, Nam-Hyun
    • Journal of the Korea Safety Management & Science
    • /
    • v.14 no.1
    • /
    • pp.87-93
    • /
    • 2012
  • The purpose of this study suggests a personalized algorithm of physical activity energy expenditure prediction through comparison and analysis of individual physical activity. The research for a 3-axial accelerometer sensor has increased the role of physical activity in promoting health and preventing chronic disease has long been established. Estimating algorithm of physical activity energy expenditure was implemented by using a tri-axial accelerometer motion detector of the SVM(Signal Vector Magnitude) of 3-axis(x, y, z). A total of 10 participants(5 males and 5 females aged between 20 and 30 years). The activities protocol consisted of three types on treadmill; participants performed three treadmill activity at three speeds(3, 5, 8 km/h). These activities were repeated four weeks.

A Selection of Path Planning Algorithm to Maximize Survivability for Unmanned Aerial Vehicle (무인 항공기 생존성 극대화를 위한 이동 경로 계획 알고리즘 선정)

  • Kim, Ki-Tae;Jeon, Geon-Wook
    • Journal of the Korea Safety Management & Science
    • /
    • v.13 no.2
    • /
    • pp.103-113
    • /
    • 2011
  • This research is to select a path planning algorithm to maximize survivability for Unmanned Aerial Vehicle(UAV). An UAV is a powered pilotless aircraft, which is controlled remotely or autonomously. UAVs are currently employed in many military missions(surveillance, reconnaissance, communication relay, targeting, strike etc.) and a number of civilian applications(communication service, broadcast service, traffic control support, monitoring, measurement etc.). In this research, a mathematical programming model is suggested by using MRPP(Most Reliable Path Problem) and verified by using ILOG CPLEX. A path planning algorithm for UAV is selected by comparing of SPP(Shortest Path Problem) algorithms which transfer MRPP into SPP.

Optimization of Steel Box Girder Bridges using Approximate Reanalysis Technique (재해석 기법을 이용한 강상자형교의 최적설계)

  • Min, Dae-Hong;Yoon, Woo-Hyun;Chung, Jee-Seung;Yang, Sung-Don
    • Journal of the Korean Society of Safety
    • /
    • v.26 no.4
    • /
    • pp.80-86
    • /
    • 2011
  • Structural optimization algorithm of steel box girder bridges using improved higher-order approximate reanalysis technique is proposed in this paper. The proposed approximation method is a generalization of the convex approximation method. The order of the approximate reanalysis for each function is analytically adjusted in the optimization process. This self-adjusted capability makes the approximate structural analysis values conservative enough to maintain the optimum design point of the approximate problem. The efficiency of proposed optimazation algorithm, compared with conventional algorithm, is successfully demonstrated in the steel box girder bridges. The efficiency and robustness of proposed algorithm is also demonstrated in practical steel box girder bridges.

Multi-Vehicle Tracking Adaptive Cruise Control (다차량 추종 적응순항제어)

  • Moon Il ki;Yi Kyongsu
    • Transactions of the Korean Society of Mechanical Engineers A
    • /
    • v.29 no.1 s.232
    • /
    • pp.139-144
    • /
    • 2005
  • A vehicle cruise control algorithm using an Interacting Multiple Model (IMM)-based Multi-Target Tracking (MTT) method has been presented in this paper. The vehicle cruise control algorithm consists of three parts; track estimator using IMM-Probabilistic Data Association Filter (PDAF), a primary target vehicle determination algorithm and a single-target adaptive cruise control algorithm. Three motion models; uniform motion, lane-change motion and acceleration motion. have been adopted to distinguish large lateral motions from longitudinal motions. The models have been validated using simulated and experimental data. The improvement in the state estimation performance when using three models is verified in target tracking simulations. The performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. These simulations show system response that is more realistic and reflective of actual human driving behavior.