• Title/Summary/Keyword: Intersection control

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An Intelligent CCTV-Based Emergency Detection System for Rooftop Access Control Problems (옥상 출입 통제 문제 해결을 위한 지능형 CCTV 기반 비상 상황 감지 시스템 제안)

  • Yeeun Kang;Soyoung Ham;Seungchae Joa;Hani Lee;Seongmin Kim;Hakkyong Kim
    • Convergence Security Journal
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    • v.24 no.1
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    • pp.59-68
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    • 2024
  • With advancements in artificial intelligence technology, intelligent CCTV systems are being deployed across various environments, such as river bridges and construction sites. However, a conflict arises regarding the opening and closing of rooftop access points due to concerns over potential accidents and crime incidents and their role as emergency evacuation spaces. While the relevant law typically mandates the constant opening of designated rooftop access points, closures are often tacitly permitted in practice for security reasons, with a lack of appropriate legal measures. In this context, this study proposes a detection system utilizing intelligent CCTV to respond to emergencies that may occur on rooftops. We develop a system based on the YOLOv5 object detection model to detect assault and suicide attempts by jumping, introducing a new metric to assess them. Experimental results demonstrate that the proposed system rapidly detects assault and suicide attempts with high accuracy. Additionally, through a legal analysis of rooftop access point management, deficiencies in the legal framework regarding rooftop access and CCTV installation are identified, and improvement measures are proposed. With technological and legal improvements, we believe that crime and accident incidents in rooftop environments will decrease.

Development of Neural Network Based Cycle Length Design Model Minimizing Delay for Traffic Responsive Control (실시간 신호제어를 위한 신경망 적용 지체최소화 주기길이 설계모형 개발)

  • Lee, Jung-Youn;Kim, Jin-Tae;Chang, Myung-Soon
    • Journal of Korean Society of Transportation
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    • v.22 no.3 s.74
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    • pp.145-157
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    • 2004
  • The cycle length design model of the Korean traffic responsive signal control systems is devised to vary a cycle length as a response to changes in traffic demand in real time by utilizing parameters specified by a system operator and such field information as degrees of saturation of through phases. Since no explicit guideline is provided to a system operator, the system tends to include ambiguity in terms of the system optimization. In addition, the cycle lengths produced by the existing model have yet been verified if they are comparable to the ones minimizing delay. This paper presents the studies conducted (1) to find shortcomings embedded in the existing model by comparing the cycle lengths produced by the model against the ones minimizing delay and (2) to propose a new direction to design a cycle length minimizing delay and excluding such operator oriented parameters. It was found from the study that the cycle lengths from the existing model fail to minimize delay and promote intersection operational conditions to be unsatisfied when traffic volume is low, due to the feature of the changed target operational volume-to-capacity ratio embedded in the model. The 64 different neural network based cycle length design models were developed based on simulation data surrogating field data. The CORSIM optimal cycle lengths minimizing delay were found through the COST software developed for the study. COST searches for the CORSIM optimal cycle length minimizing delay with a heuristic searching method, a hybrid genetic algorithm. Among 64 models, the best one producing cycle lengths close enough to the optimal was selected through statistical tests. It was found from the verification test that the best model designs a cycle length as similar pattern to the ones minimizing delay. The cycle lengths from the proposed model are comparable to the ones from TRANSYT-7F.

Hardware Approach to Fuzzy Inference―ASIC and RISC―

  • Watanabe, Hiroyuki
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.975-976
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    • 1993
  • This talk presents the overview of the author's research and development activities on fuzzy inference hardware. We involved it with two distinct approaches. The first approach is to use application specific integrated circuits (ASIC) technology. The fuzzy inference method is directly implemented in silicon. The second approach, which is in its preliminary stage, is to use more conventional microprocessor architecture. Here, we use a quantitative technique used by designer of reduced instruction set computer (RISC) to modify an architecture of a microprocessor. In the ASIC approach, we implemented the most widely used fuzzy inference mechanism directly on silicon. The mechanism is beaded on a max-min compositional rule of inference, and Mandami's method of fuzzy implication. The two VLSI fuzzy inference chips are designed, fabricated, and fully tested. Both used a full-custom CMOS technology. The second and more claborate chip was designed at the University of North Carolina(U C) in cooperation with MCNC. Both VLSI chips had muliple datapaths for rule digital fuzzy inference chips had multiple datapaths for rule evaluation, and they executed multiple fuzzy if-then rules in parallel. The AT & T chip is the first digital fuzzy inference chip in the world. It ran with a 20 MHz clock cycle and achieved an approximately 80.000 Fuzzy Logical inferences Per Second (FLIPS). It stored and executed 16 fuzzy if-then rules. Since it was designed as a proof of concept prototype chip, it had minimal amount of peripheral logic for system integration. UNC/MCNC chip consists of 688,131 transistors of which 476,160 are used for RAM memory. It ran with a 10 MHz clock cycle. The chip has a 3-staged pipeline and initiates a computation of new inference every 64 cycle. This chip achieved an approximately 160,000 FLIPS. The new architecture have the following important improvements from the AT & T chip: Programmable rule set memory (RAM). On-chip fuzzification operation by a table lookup method. On-chip defuzzification operation by a centroid method. Reconfigurable architecture for processing two rule formats. RAM/datapath redundancy for higher yield It can store and execute 51 if-then rule of the following format: IF A and B and C and D Then Do E, and Then Do F. With this format, the chip takes four inputs and produces two outputs. By software reconfiguration, it can store and execute 102 if-then rules of the following simpler format using the same datapath: IF A and B Then Do E. With this format the chip takes two inputs and produces one outputs. We have built two VME-bus board systems based on this chip for Oak Ridge National Laboratory (ORNL). The board is now installed in a robot at ORNL. Researchers uses this board for experiment in autonomous robot navigation. The Fuzzy Logic system board places the Fuzzy chip into a VMEbus environment. High level C language functions hide the operational details of the board from the applications programme . The programmer treats rule memories and fuzzification function memories as local structures passed as parameters to the C functions. ASIC fuzzy inference hardware is extremely fast, but they are limited in generality. Many aspects of the design are limited or fixed. We have proposed to designing a are limited or fixed. We have proposed to designing a fuzzy information processor as an application specific processor using a quantitative approach. The quantitative approach was developed by RISC designers. In effect, we are interested in evaluating the effectiveness of a specialized RISC processor for fuzzy information processing. As the first step, we measured the possible speed-up of a fuzzy inference program based on if-then rules by an introduction of specialized instructions, i.e., min and max instructions. The minimum and maximum operations are heavily used in fuzzy logic applications as fuzzy intersection and union. We performed measurements using a MIPS R3000 as a base micropro essor. The initial result is encouraging. We can achieve as high as a 2.5 increase in inference speed if the R3000 had min and max instructions. Also, they are useful for speeding up other fuzzy operations such as bounded product and bounded sum. The embedded processor's main task is to control some device or process. It usually runs a single or a embedded processer to create an embedded processor for fuzzy control is very effective. Table I shows the measured speed of the inference by a MIPS R3000 microprocessor, a fictitious MIPS R3000 microprocessor with min and max instructions, and a UNC/MCNC ASIC fuzzy inference chip. The software that used on microprocessors is a simulator of the ASIC chip. The first row is the computation time in seconds of 6000 inferences using 51 rules where each fuzzy set is represented by an array of 64 elements. The second row is the time required to perform a single inference. The last row is the fuzzy logical inferences per second (FLIPS) measured for ach device. There is a large gap in run time between the ASIC and software approaches even if we resort to a specialized fuzzy microprocessor. As for design time and cost, these two approaches represent two extremes. An ASIC approach is extremely expensive. It is, therefore, an important research topic to design a specialized computing architecture for fuzzy applications that falls between these two extremes both in run time and design time/cost. TABLEI INFERENCE TIME BY 51 RULES {{{{Time }}{{MIPS R3000 }}{{ASIC }}{{Regular }}{{With min/mix }}{{6000 inference 1 inference FLIPS }}{{125s 20.8ms 48 }}{{49s 8.2ms 122 }}{{0.0038s 6.4㎲ 156,250 }} }}

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Change of Pulmonary Artery Hemodynamics and Pulmonary Vascular Resistance in Experimental Pulmonary Embolism (실험적 급성 폐색전증에서 폐동맥혈역학 및 폐혈관저항의 변화)

  • Chung, Hee-Soon;Lee, Jae-Ho;Kim, Cheol-Ho
    • Tuberculosis and Respiratory Diseases
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    • v.42 no.6
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    • pp.913-922
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    • 1995
  • Background: When we define the pressure of pulmonary vasculature in which a recruitment of blood flow occurs as $P_I$ and the proportion of change in pulmonary artery to that in cardiac output as IR and then we compare PI and IR with pulmonary vascular resistance, we would find some problems in pulmonary vascular resistance. In other words, it is the theory that, IR should be increased mainly in pulmonary embolism in which decreases the cross sectional area of pulmonary vasculature. But there are many contradictory reports resulted from various researches and the fact is known widely that any difference exists between PVR and PI, IR. For this reason, the purpose of this study is to observe how PI and IR change at the time of the outbreak and during treatment of the pulmonary embolism, and to find out the meaning of these new indicators and the difference from the pulmonary vascular resistance used generally when we subdivide the pulmonary vascular resistance into PI and IR. Method: After making AV fistula in experimental dog, we controlled cardiac output at the intervals of 15 minute in case of three kinds(all AV fistula are obstructed, only one of fistula is open and all of fistula is open), and after evoking massive pulmonary embolism with radioactive autologous blood clots, we measured the mean pulmonary artery pressure, and calculated PI and IR. We observed the pattern of change in PI and IR, without giving the control group any specific treatment and with injecting intravenously rtPA in the Group 1 and Group 2 at the dose of 1mg per kg, for 15 minutes fot the former and 3 hours for the latter. Result: 1) Pulmonary vascular resistance showed a change similar to that of pulmonary artery pressure and in all three group, PVR increased significantly, but group 1 and group 2 showed tendency that PVR keeps on decreasing after treatment, and the rate of decrease in group 1 is more rapid than group 2 significantly. 2) Both intersection(PI) and degree(IR) are proved statistically significant, in view of the straight line relationship between cardiac output and pulmonary artery pressure, calculated by minimal regression method. 3) PI changed similarly to pulmonary vascular resistance, while in the IR which is theoretically more similar to PVR, there was no significant difference or change after rtPA infusion. Conclusion: In the pulmonary embolism, Both change in IR which means real resistance of pulmonary vasculature and PI which was developed due to secondary vasoconstriction by pulmonary embolism are reflected same time.

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