• Title/Summary/Keyword: Optimal policy

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Classifying the severity of pedestrian accidents using ensemble machine learning algorithms: A case study of Daejeon City (앙상블 학습기법을 활용한 보행자 교통사고 심각도 분류: 대전시 사례를 중심으로)

  • Kang, Heungsik;Noh, Myounggyu
    • Journal of Digital Convergence
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    • v.20 no.5
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    • pp.39-46
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    • 2022
  • As the link between traffic accidents and social and economic losses has been confirmed, there is a growing interest in developing safety policies based on crash data and a need for countermeasures to reduce severe crash outcomes such as severe injuries and fatalities. In this study, we select Daejeon city where the relative proportion of fatal crashes is high, as a case study region and focus on the severity of pedestrian crashes. After a series of data manipulation process, we run machine learning algorithms for the optimal model selection and variable identification. Of nine algorithms applied, AdaBoost and Random Forest (ensemble based ones) outperform others in terms of performance metrics. Based on the results, we identify major influential factors (i.e., the age of pedestrian as 70s or 20s, pedestrian crossing) on pedestrian crashes in Daejeon, and suggest them as measures for reducing severe outcomes.

Predicting Accident Vulnerable Situation and Extracting Scenarios of Automated Vehicleusing Vision Transformer Method Based on Vision Data (Vision Transformer를 활용한 비전 데이터 기반 자율주행자동차 사고 취약상황 예측 및 시나리오 도출)

  • Lee, Woo seop;Kang, Min hee;Yoon, Young;Hwang, Kee yeon
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.5
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    • pp.233-252
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    • 2022
  • Recently, various studies have been conducted to improve automated vehicle (AV) safety for AVs commercialization. In particular, the scenario method is directly related to essential safety assessments. However, the existing scenario do not have objectivity and explanability due to lack of data and experts' interventions. Therefore, this paper presents the AVs safety assessment extended scenario using real traffic accident data and vision transformer (ViT), which is explainable artificial intelligence (XAI). The optimal ViT showed 94% accuracy, and the scenario was presented with Attention Map. This work provides a new framework for an AVs safety assessment method to alleviate the lack of existing scenarios.

Reinforcement Learning-based Dynamic Weapon Assignment to Multi-Caliber Long-Range Artillery Attacks (다종 장사정포 공격에 대한 강화학습 기반의 동적 무기할당)

  • Hyeonho Kim;Jung Hun Kim;Joohoe Kong;Ji Hoon Kyung
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.45 no.4
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    • pp.42-52
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    • 2022
  • North Korea continues to upgrade and display its long-range rocket launchers to emphasize its military strength. Recently Republic of Korea kicked off the development of anti-artillery interception system similar to Israel's "Iron Dome", designed to protect against North Korea's arsenal of long-range rockets. The system may not work smoothly without the function assigning interceptors to incoming various-caliber artillery rockets. We view the assignment task as a dynamic weapon target assignment (DWTA) problem. DWTA is a multistage decision process in which decision in a stage affects decision processes and its results in the subsequent stages. We represent the DWTA problem as a Markov decision process (MDP). Distance from Seoul to North Korea's multiple rocket launchers positioned near the border, limits the processing time of the model solver within only a few second. It is impossible to compute the exact optimal solution within the allowed time interval due to the curse of dimensionality inherently in MDP model of practical DWTA problem. We apply two reinforcement-based algorithms to get the approximate solution of the MDP model within the time limit. To check the quality of the approximate solution, we adopt Shoot-Shoot-Look(SSL) policy as a baseline. Simulation results showed that both algorithms provide better solution than the solution from the baseline strategy.

Energy Performance and Cost Assessment for Implementing GroundSource Heat Pump System in Military Building (군사시설 내 지열 히트펌프 시스템 적용에 따른 에너지 성능과 비용 절감 효과 평가)

  • Byonghu Sohn;Kyung Joo Cho;Dong Woo Cho
    • Journal of the Korean Society for Geothermal and Hydrothermal Energy
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    • v.18 no.4
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    • pp.45-57
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    • 2022
  • The Ministry of National Defense of the Republic of Korea is showing a lot of interest in net zero-energy buildings (NZEBs) to reduce energy consumption of military facilities and to promote green growth policy in military sector. The application of building passive technologies and renewable energies is essential to achieving NZEBs. This paper analyzed energy performance and energy cost on the conventional heating and cooling system (baseline scenario) and three different alternative scenarios (ALT 1, ALT 2 and ALT 3) applied in a hypothetical military building. A building modeling and simulation software (DesignBuilder V6.1) with EnergyPlus calculation engine was used to calculate the energy consumption for each scenario. Overall, when the GSHPs are applied to both space airconditioning and domestic hot water (DHW) production, Alt-2 and Alt-3, the amount of energy consumption for target building can be greatly reduced. In addition, when the building envelope performance is increased like Alt-3, the energy consumption can be further reduced. The annual energy cost analysis showed that the baseline was approximately 161 million KRW, while Alt-3 was approximately 33 million KRW. Therefore, it was analyzed that the initial construction cost increase could be recovered within about 6.7 years for ALT 3. The results of this study can help decision-makers to determine the optimal strategy for implementing GSHP systems in military buildings through energy performance and initial construction cost assessment.

Design of Low-Complexity FSM based on Viterbi for Optimum Bluetooth GFSK Signal Receiver (최적의 Bluetooth GFSK 신호 수신을 위한 Viterbi 기반 저복잡도 FSM 설계)

  • Kwon, Taek-Won;Lee, Kyu-Man
    • Journal of Digital Convergence
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    • v.20 no.1
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    • pp.185-190
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    • 2022
  • Bluetooth is a common wireless technology that is widely used as a connection medium between various consumer electronic devices. The Bluetooth receiver usually adopts a Viterbi algorithm to improve signal-to-noise ratio performance, but requires complex hardware and calculations for continuous search and estimation for the irrational modulation indexes at the transmission. This paper proposes a non-coherent maximum estimation based 8-State Viterbi FSM to solve these complexity problems. The proposed optimal Viterbi FSM can detect Gaussian frequency-shfit keying symbol without any prior information and estimation for the modulation indexes. The HV1/HV2 packets are used for the estimation of the proposed algorithm and the simulation results have shown performance improvements with about 2dB for 10-3 BER compared to other ideal approaches such as decision direct method.

Adaptive Burst Size-based Loss Differentiation for Transmitting Massive Medical Data in Optical Internet (광 인터넷에서 대용량 의학 데이터 전송을 위한 적응형 버스트 길이 기반 손실 차등화 기법)

  • Lee, Yonggyu
    • Journal of Digital Convergence
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    • v.20 no.3
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    • pp.389-397
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    • 2022
  • As increasing the growth of the Internet in medical area, a new technology to transmit effectively massive medical data is required. In optical internet, all OBS nodes have fiber delay lines, hardware components. These components are calculated under some optimal traffic conditions, and this means that if the conditions change, then the components should be altered. Therefore, in this article a new service differentiation algorithm using the previously installed components is proposed, which is used although the conditions vary. When traffic conditions change, the algorithm dynamically recalculates the threshold value used to decide the length of data bursts. By doing so, irrelevant to changes, the algorithm can maintain the service differentiation between classes without replacing any fiber delay lines. With the algorithm, loss sensitive medical data can be transferred well.

Reinforcement Learning for Minimizing Tardiness and Set-Up Change in Parallel Machine Scheduling Problems for Profile Shops in Shipyard (조선소 병렬 기계 공정에서의 납기 지연 및 셋업 변경 최소화를 위한 강화학습 기반의 생산라인 투입순서 결정)

  • So-Hyun Nam;Young-In Cho;Jong Hun Woo
    • Journal of the Society of Naval Architects of Korea
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    • v.60 no.3
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    • pp.202-211
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    • 2023
  • The profile shops in shipyards produce section steels required for block production of ships. Due to the limitations of shipyard's production capacity, a considerable amount of work is already outsourced. In addition, the need to improve the productivity of the profile shops is growing because the production volume is expected to increase due to the recent boom in the shipbuilding industry. In this study, a scheduling optimization was conducted for a parallel welding line of the profile process, with the aim of minimizing tardiness and the number of set-up changes as objective functions to achieve productivity improvements. In particular, this study applied a dynamic scheduling method to determine the job sequence considering variability of processing time. A Markov decision process model was proposed for the job sequence problem, considering the trade-off relationship between two objective functions. Deep reinforcement learning was also used to learn the optimal scheduling policy. The developed algorithm was evaluated by comparing its performance with priority rules (SSPT, ATCS, MDD, COVERT rule) in test scenarios constructed by the sampling data. As a result, the proposed scheduling algorithms outperformed than the priority rules in terms of set-up ratio, tardiness, and makespan.

Analysis on Time Dependent Traffic Volume Characteristics on Highways linked to Recreation Areas (관광지 종류별 일반국도 교통량의 시간별 특성 연구)

  • Kim, Yun Seob;Oh, Ju Sam;Kim, Hyun Seok
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.1D
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    • pp.23-30
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    • 2006
  • The variation in the traffic volume on any given roads is the reflection of its user's economic activities and life patterns. And traffic volume flows in every hour usually take different charateristics depending on the location and the function of the roads. This study produced the Monthly Adjustment Factor, Weekly Adjustment Factor and Design hourly Factor, each of which is the index indicating the traffic volume charaterirstics on the highways leading to the recreation areas in the mountainous and seaside tourist sites. Applying these results, it might be possible to calculate the optimal AADT (Annual Average Daily Traffic) and DHV (Design Hour Volume), also be a help to establish a traffic management policy. Finally, it hopes to promote new version of KHCM (Korea Highway Capacity Manual) which includes traffic volume characteristics on recreation areas.

A Study on The Network Design of Smart Village to Provide Wired and Wireless Convergence Services on IoT (IoT기반의 유무선 융복합 서비스 제공을 위한 스마트빌리지의 네트워크 구성방안에 관한 연구)

  • Kim, Yun-ha;Jeong, Jae-woong;Kim, Young-sung;Choi, Hyun-ju
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.296-299
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    • 2022
  • The rapid urban expansion and the increase in natural disasters due to the increase of population after industrialization and climate change are causing numerous urban management problems. The IP based hyper-connectivity caused by the initiation of the 4th industrial revolution enables a variety of technologies and services that produce vast amounts of data and solve urban management problems based on this. Especially, the quality of life is improved by providing the necessary information for life that are produced through a sensor network on wired and wireless communication. In this study, we intend to propose the method of optimal communcation network composition for innovative and futuristic city management technology through the case of K-water Smart Village Communication System

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Study on the Distribution Status of Construction Aggregates in Incheon Metropolitan City and Nearby Areas (인천광역시 및 인근 지역의 건설용 골재 유통현황 분석 연구)

  • Chul-Seoung Baek;Byoung-Woon You;Kun-Ki Kim;Yu-Jeong Jang;Jin-Young Lee
    • Economic and Environmental Geology
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    • v.57 no.2
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    • pp.219-231
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    • 2024
  • A survey of concrete plants in Incheon Metropolitan City and Gyeonggi Province was used to conduct an analysis of aggregate transport distance and production forms, as well as to evaluate the features and current status of aggregates distribution. As a result, areas such as Incheon, Siheung, Bucheon, Gimpo, and Siheung, where the distance to the demand points is less than 20 km, exhibited bidirectional distribution whereas Paju, Yongin, Yangju, and Pocheon, with distances ranging from 20 to 50 km is showed a unidirectional distribution pattern supplying aggregates exclusively to Incheon. Survey on manufacturing forms, more than 85% of the gravel dispersed in the Incheon area is made up of crushed aggregates derived from rocks discharged at construction sites indicating a considerable skew in supply chain. These findings are predicted to have a detrimental influence on aggregate supply in the long run, necessitating policy changes targeted at building an optimal aggregate distribution market.