• 한국도로학회논문집
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• 제15권5호
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• pp.91-99
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• 2013

PURPOSES : This study aims at proposing the methodology for benefit evaluations in pavement maintenance methods and timings using KoPMS(Korean Pavement Management System) software which was developed for efficient pavement management. METHODS : This study classified pavement sections into 4 clusters considering AADT(Annual Average Daily Traffic) and ESAL(Equivalent Single-Axle Load) using cluster analysis and used the deterioration models in each cluster. Increased user costs due to pavement deterioration as time goes by and agent costs for maintenance were estimated. Based on deterioration model and KoPMS software, Methodology for benefit evaluation was proposed in pavement maintenance methods and with/without implementation using real pavement section data. RESULTS : This study verified that considering agent costs only would be constrained to decide pavement maintenance methods and timings, and ascertained that decision making with agent and user costs would be effective. In addition, this study revealed that pavement maintenance methods and timings can be affected by AADT and ESAL and frequent pavement maintenances can be more efficient for benefits in pavement sections with more AADT and ESAL. Also this study found that user costs would be more affected to decision making than agent costs. Moreover, Delay of conducting pavement maintenance caused increased vehicle operating costs and environmental costs because of poor conditions of pavements. CONCLUSIONS : This study proposed LCCA and benefit estimation methodology of pavement with considering agent and user costs. The results of this study can be used for baseline data of efficient pavement asset management.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2008년 영문 학술대회
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• pp.330-339
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• 2008

Ground-based interceptors(GBI) comprise a major element of the strategic defense against hostile targets like Intercontinental Ballistic Missiles(ICBM) and reentry vehicles(RV) dispersed from them. An optimum design of the subsystems is required to increase the performance and reliability of these GBI. Propulsion subsystem design and optimization is the motivation for this effort. This paper describes an effort in which an entire GBI missile system, including a multi-stage solid rocket booster, is considered simultaneously in a Genetic Algorithm(GA) performance optimization process. Single goal, constrained optimization is performed. For specified payload and miss distance, time of flight, the most important component in the optimization process is the booster, for its takeoff weight, time of flight, or a combination of the two. The GBI is assumed to be a multistage missile that uses target location data provided by two ground based RF radar sensors and two low earth orbit(LEO) IR sensors. 3Dimensional model is developed for a multistage target with a boost phase acceleration profile that depends on total mass, propellant mass and the specific impulse in the gravity field. The monostatic radar cross section (RCS) data of a three stage ICBM is used. For preliminary design, GBI is assumed to have a fixed initial position from the target launch point and zero launch delay. GBI carries the Kill Vehicle(KV) to an optimal position in space to allow it to complete the intercept. The objective is to design and optimize the propulsion system for the GBI that will fulfill mission requirements and objectives. The KV weight and volume requirements are specified in the problem definition before the optimization is computed. We have considered only continuous design variables, while considering discrete variables as input. Though the number of stages should also be one of the design variables, however, in this paper it is fixed as three. The elite solution from GA is passed on to(Sequential Quadratic Programming) SQP as near optimal guess. The SQP then performs local convergence to identify the minimum mass of the GBI. The performance of the three staged GBI is validated using a ballistic missile intercept scenario modeled in Matlab/SIMULINK.

• 한국컴퓨터정보학회논문지
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• 제7권3호
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• pp.80-91
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• 2002

ATM 네트워크의 목적은 다양한 네트워크의 접속을 지원하는 것이다. ATM 망에서 ABR 서비스는 CBR, VBR에 할당된 전송률을 제외한 나머지를 이용해서 데이터를 전송한다. 오디오 또는 비디오 데이터와 같이 실시간 전송이 필요한 서비스들은 전송지연이 제한되는 CBR이나 VBR 트래픽을 이용하여 제공할 수 있지만, 이런 경우에는 전체 전송률을 효과적으로 사용하지 못하는 단점이 있다. 따라서 본 논문에서는 ABR 스위치의 스위치 알고리즘인 ERICA(Explicit Rate Indicate Avoidance) 스위치 방식과 EPRCA(Enhanced Proportional Rate Control Algorithm) 스위치 방식의 성능을 평가하기 위하여 시뮬레이션을 수행하였다. 시뮬레이션의 평가 기준으로 과도상태와 정상상태에서 각 송신원에서의 전송률(ACR:Allowed Cell Rate)의 변화, 큐 길이, 링크 대역폭 이용률과 전송률의 공평성 여부를 사용하였다. 실험결과 EPRCA 스위치 방식은 ERICA 방식보다 뛰어난 반응 특성을 나타내는 결과를 얻을 수 있었으며, 안정성과 페어웨어 특성은 ERICA 스위치 방식이 EPRCA 스위치 방식보다 우수한 결과를 얻을 수 있었다.

• 대한의용생체공학회:의공학회지
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• 제42권6호
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• pp.268-276
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• 2021

Functional near-infrared spectroscopy-based brain-computer interface (fNIRS-based BCI) has been receiving much attention. However, we are practically constrained to obtain a lot of fNIRS data by inherent hemodynamic delay. For this reason, when employing machine learning techniques, a problem due to the high-dimensional feature vector may be encountered, such as deteriorated classification accuracy. In this study, we employ an elastic net-based feature selection which is one of the embedded methods and demonstrate the utility of which by analyzing the results. Using the fNIRS dataset obtained from 18 participants for classifying brain activation induced by mental arithmetic and idle state, we calculated classification accuracies after performing feature selection while changing the parameter α (weight of lasso vs. ridge regularization). Grand averages of classification accuracy are 80.0 ± 9.4%, 79.3 ± 9.6%, 79.0 ± 9.2%, 79.7 ± 10.1%, 77.6 ± 10.3%, 79.2 ± 8.9%, and 80.0 ± 7.8% for the various values of α = 0.001, 0.005, 0.01, 0.05, 0.1, 0.2, and 0.5, respectively, and are not statistically different from the grand average of classification accuracy estimated with all features (80.1 ± 9.5%). As a result, no difference in classification accuracy is revealed for all considered parameter α values. Especially for α = 0.5, we are able to achieve the statistically same level of classification accuracy with even 16.4% features of the total features. Since elastic net-based feature selection can be easily applied to other cases without complicated initialization and parameter fine-tuning, we can be looking forward to seeing that the elastic-based feature selection can be actively applied to fNIRS data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권6호
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• pp.1706-1727
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• 2023

Under Water Sensor Networks (UWSN) has gained attraction among various communities for its potential applications like acoustic monitoring, 3D mapping, tsunami detection, oil spill monitoring, and target tracking. Unlike terrestrial sensor networks, it performs an acoustic mode of communication to carry out collaborative tasks. Typically, surface sink nodes are deployed for aggregating acoustic phenomena collected from the underwater sensors through the multi-hop path. In this context, UWSN is constrained by factors such as lower bandwidth, high propagation delay, and limited battery power. Also, the vulnerabilities to compromise the aquatic environment are in growing numbers. The paper proposes an Energy-Efficient standalone Intrusion Detection System (EEIDS) to entail the acoustic environment against malicious attacks and improve the network lifetime. In EEIDS, attributes such as node ID, residual energy, and depth value are verified for forwarding the data packets in a secured path and stabilizing the nodes' energy levels. Initially, for each node, three agents are modeled to perform the assigned responsibilities. For instance, ID agent verifies the node's authentication of the node, EN agent checks for the residual energy of the node, and D agent substantiates the depth value of each node. Next, the classification of normal and malevolent nodes is performed by determining the score for each node. Furthermore, the proposed system utilizes the sheep-flock heredity algorithm to validate the input attributes using the optimized probability values stored in the training dataset. This assists in finding out the best-fit motes in the UWSN. Significantly, the proposed system detects and isolates the malicious nodes with tampered credentials and nodes with lower residual energy in minimal time. The parameters such as the time taken for malicious node detection, network lifetime, energy consumption, and delivery ratio are investigated using simulation tools. Comparison results show that the proposed EEIDS outperforms the existing acoustic security systems.

• 한국통신학회논문지
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• 제38B권11호
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• pp.911-923
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• 2013

무선 센서 네트워크에서 다중경로 라우팅 방안은 종단 간 데이터 전달의 신뢰성을 향상시키기 위한 연구주제 중 하나이다. 최근에는 다중경로의 강건함과 효율성을 위해서 경로의 분리와 관리를 위한 연구가 다수 진행 되었다. 그러나 이전의 연구들은 무선 통신 환경을 고려하지 않은 다중경로의 분리 방법을 이용하고 있다. 게다가, 그들은 불규칙 네트워크 환경에서 노드나 통신 실패로 인해 발생하는 경로 실패를 관리하는 방법이 없거나 추가경로를 생성하는 간단한 방법을 통해 다중경로를 유지한다. 이를 보완하기 위해서, 네트워크 오류지역을 우회 전송하고 경로를 재구성하는 다중경로 유지 방안이 제안되었지만, 중앙 집중적이고 정적인 경로 관리 방법을 이용하기 때문에, 경로 재구성 과정에서 데이터 전달의 중단이나 링크의 단절, 그리고 많은 경로 재구성 비용 등이 요구되는 문제가 있다. 이런 제약과 문제들은 데이터 전달의 신뢰성 저하와 긴급 데이터의 보고 실패로 이뤄질 수 있다. 따라서 본 논문에서는 불규칙적이고 제한적인 무선 센서 네트워크 환경을 고려하여 유연한 분리형 다중경로를 구축하는 방법과 효율적으로 다중경로를 유지할 수 있도록 경로의 우선순위 규칙을 적용한 지역 결정 기반의 다중경로 관리 방법을 제안한다. 그리고 제안 방법의 성능을 평가하기 위해서 시뮬레이션을 수행한다.

• 한국정보과학회논문지:시스템및이론
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• 제37권5호
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• pp.292-303
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• 2010

온칩(on-chip) 캐쉬는 외부 메모리로의 접근을 감소시키며 빈번하게 접근되기 때문에 내장형 시스템의 성능과 에너지 소비 측면에서 중요한 역할을 한다. 본 논문에서는 내장형 시스템에 맞추어 설계된 2-레벨 데이터 캐쉬 메모리 구조를 제안하고자 한다. 레벨1(L1) 캐쉬의 구성으로 작은 크기, 직접시장(direct-mapped) 그리고 바로쓰기(write-through)를 채용한다. 대조적으로 레벨2(L2) 캐쉬는 보통의 캐쉬 크기와 집합연관(set-associativity) 그리고 나중쓰기(write-back) 정책을 채용한다. 결과적으로 L1 캐쉬는 빠른 접근 시간을 가지며 (한 사이클 이내) L2 캐쉬는 전체 캐쉬의 미스율(global miss rate)을 낮추는데 효과적이다. 작은 크기의 L1 데이터 캐쉬로 인한 증가된 캐쉬 미스율(miss rate)을 줄이기 위해 ECP(Early Cache hit Predictor)기법을 제안하였다. 제안된 ECP기법은 L1 캐쉬 히트 예측을 통해서 요청된 데이터가 L1 캐쉬에 있는지 예측할 수 있으며 추가적으로, ALU를 필요로 하지 않고 빠르게 유효주소(effective address)계산을 할 수 있다. 또한, 두 캐쉬 계층간 바로쓰기(write-through) 정책에서 오는 빈번한 L2 캐쉬 접근으로 인한 에너지 소비를 줄이기 위해 지정웨이 쓰기(one-way write) 기법을 제안하였다. 제안된 지정웨이 쓰기 기법을 이용하면 바로쓰기 정책으로 인한 L1 캐쉬에서 L2 캐쉬로의 쓰기 접근시 태그(tag) 비교 과정을 거치지 않고 하나의 지정된 웨이를 바로 접근할 수 있다. 사이클 단위 정확도의 시뮬레이터와 내장형 벤치마크를 이용한 실험 결과 본 논문에서 제안한 2-레벨 데이터 캐쉬 메모리 구조는 평균적으로 3.6%의 성능향상과 50%의 데이터 캐쉬 에너지 소비를 감소 시켰다.

• 정보처리학회논문지A
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• 제16A권6호
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• pp.463-472
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• 2009

실시간 운영체제는 효율적인 스케줄링, 최소화된 인터럽트 지연, 우선순위 역전현상 해결 등의 다양한 조건을 만족시킴과 동시에, 응용프로 그램이 정해진 기한 내에 수행되는 것을 보장하여야 한다. 따라서 실시간 운영체제는 상기 조건을 만족시킬 수 있도록 설계/개발되어야 한다. 대중적인 실시간 커널의 한 종류인 MicroC/OS-II에서는 우선순위 역전 현상에 대한 해결 기법으로 뮤텍스(Mutex)를 사용한 기본적인 우선순 위 상속(Basic Priority Inheritance) 프로토콜을 사용한다. 뮤텍스를 구현하려면 우선순위가 같은 여러 태스크를 사용할 수 있도록 커널이 지원 해야 하나 MicroC/OS-II 운영체제는 우선순위가 같은 여러 태스크의 동시 사용을 지원하지 않는다. 이를 해결하기 위해 추가적인 우선순위 예 약을 사용할 수밖에 없게 되고, 결과적으로 제한된 우선순위 자원을 낭비하게 된다. 본 논문에서는 MicroC/OS-II의 불필요한 우선순위 자원을 낭비하는 문제점을 해결할 수 있는 일시적 우선순위 교환 프로토콜(Temporary Priority Swapping Protocol; TPSP)을 설계 및 구현하여, 한정 된 자원 환경을 가진 임베디드 장비에 효율적으로 운용되도록 하는데 목적을 둔다.

• 국제초고층학회논문집
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• 제12권3호
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• pp.225-234
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• 2023

Even at this point in the era of digital transformation, we are still facing many problems in the safety sector that cannot prevent the occurrence or spread of human casualties. When you are in an unexpected emergency, it is often difficult to respond only with human physical ability. Human casualties continue to occur at construction sites, manufacturing plants, and multi-use facilities used by many people in everyday life. If you encounter a situation where normal judgment is impossible in the event of an emergency at a life site where there are still many safety blind spots, it is difficult to cope with the existing manual guidance method. New variable guidance technology, which combines artificial intelligence and digital twin, can make it possible to prevent casualties by processing large amounts of data needed to derive appropriate countermeasures in real time beyond identifying what safety accidents occurred in unexpected crisis situations. When a simple control method that divides and monitors several CCTVs is digitally converted and combined with artificial intelligence and 3D digital twin control technology, intelligence augmentation (IA) effect can be achieved that strengthens the safety decision-making ability required in real time. With the enforcement of the Serious Disaster Enterprise Punishment Act, the importance of distributing a smart location guidance system that urgently solves the decision-making delay that occurs in safety accidents at various industrial sites and strengthens the real-time decision-making ability of field workers and managers is highlighted. The smart location guidance system that combines artificial intelligence and digital twin consists of AIoT HW equipment, wireless communication NW equipment, and intelligent SW platform. The intelligent SW platform consists of Builder that supports digital twin modeling, Watch that meets real-time control based on synchronization between real objects and digital twin models, and Simulator that supports the development and verification of various safety management scenarios using intelligent agents. The smart location guidance system provides on-site monitoring using IoT equipment, CCTV-linked intelligent image analysis, intelligent operating procedures that support workflow modeling to immediately reflect the needs of the site, situational location guidance, and digital twin virtual fencing access control technology. This paper examines the limitations of traditional fixed passive guidance methods, analyzes global technology development trends to overcome them, identifies the digital transformation properties required to switch to intelligent variable smart location guidance methods, explains the characteristics and components of AI-based public facility smart fire safety integrated system (ISFS).