• Title/Summary/Keyword: Systems Engineering Capability Model

Search Result 270, Processing Time 0.028 seconds

The Operational Comparison of SPOT GCP Acquisition and Accuracy Evaluation

  • Kim, Kam-Lae;Kim, Uk-Nam;Chun, Ho-Woun;Lee, Ho-Nam
    • Korean Journal of Geomatics
    • /
    • v.1 no.1
    • /
    • pp.1-5
    • /
    • 2001
  • This paper presents an investigation into the operational comparison of SPOT triangulation to build GCP library by analytical plotter and DPW (digital photogrammetric workstation). GCP database derived from current SPOT images can be used to other image sensors of satellite, if any reasons, such as lack of topographic maps or GCPs. But, general formulation of a photogrammetric process for GCP measurement has to take care of the scene interpretation problem. There are two classical methods depending on whether an analytical plotter or DPW is being used. Regardless of the method used, the measurement of GCPs is the weakest point in the automation of photogrammetric orientation procedures. To make an operational comparison, five models of SPOT panchromatic images (level 1A) and negative films (level 1AP) were used. Ten images and film products were used for the five GRS areas. Photogrammetric measurements were carried out in a manual mode on P2 analytical plotter and LH Systems DPW770. We presented an approach for exterior orientation of SPOT images, which was based on the use of approximately eighty national geodetic control points as GCPs which located on the summit of the mountain. Using sixteen well-spaced geodetic control points per model, all segments consistently showed RMS error just below the pixel at the check points in analytical instrument. In the case of DPW, half of the ground controls could not found or distinguished exactly when we displayed the image on the computer monitor. Experiment results showed that the RMS errors with DPW test was fluctuated case by case. And the magnitudes of the errors were reached more than three pixels due to the lack of image interpretation capability. It showed that the geodetic control points is not suitable as the ground control points in DPW for modeling the SPOT image.

  • PDF

Analyzing Machine Learning Techniques for Fault Prediction Using Web Applications

  • Malhotra, Ruchika;Sharma, Anjali
    • Journal of Information Processing Systems
    • /
    • v.14 no.3
    • /
    • pp.751-770
    • /
    • 2018
  • Web applications are indispensable in the software industry and continuously evolve either meeting a newer criteria and/or including new functionalities. However, despite assuring quality via testing, what hinders a straightforward development is the presence of defects. Several factors contribute to defects and are often minimized at high expense in terms of man-hours. Thus, detection of fault proneness in early phases of software development is important. Therefore, a fault prediction model for identifying fault-prone classes in a web application is highly desired. In this work, we compare 14 machine learning techniques to analyse the relationship between object oriented metrics and fault prediction in web applications. The study is carried out using various releases of Apache Click and Apache Rave datasets. En-route to the predictive analysis, the input basis set for each release is first optimized using filter based correlation feature selection (CFS) method. It is found that the LCOM3, WMC, NPM and DAM metrics are the most significant predictors. The statistical analysis of these metrics also finds good conformity with the CFS evaluation and affirms the role of these metrics in the defect prediction of web applications. The overall predictive ability of different fault prediction models is first ranked using Friedman technique and then statistically compared using Nemenyi post-hoc analysis. The results not only upholds the predictive capability of machine learning models for faulty classes using web applications, but also finds that ensemble algorithms are most appropriate for defect prediction in Apache datasets. Further, we also derive a consensus between the metrics selected by the CFS technique and the statistical analysis of the datasets.

A Study on the Scale Optimization of the Korean-type Aircraft Carrier based on Efficiency Considering National Competency (국가 역량을 고려한 효율성 기반 한국형 항공모함 규모 최적화 연구)

  • Jung, Byungki;Kim, Kitae;Park, Sungje
    • Journal of Korean Society of Industrial and Systems Engineering
    • /
    • v.45 no.3
    • /
    • pp.49-56
    • /
    • 2022
  • ROK Navy intends to secure the Korean-type aircraft carrier in order to effectively prepare for various future security threats. In general, the Korean national competency is considered to be at the level of having an aircraft carrier, but it is unclear what scale aircraft carrier would be appropriate. In this study, the efficiency was evaluated through the relative comparison between national competency(national power, economic power) and the scale of aircraft carriers, and the optimal scale of the Korean-type aircraft carrier that could be acquired was presented. A DEA(Data Envelopment Analysis) model was applied to aircraft carriers(19 aircraft carriers in 11 countries) currently in operation and scheduled to be possessed in the world. As input variables, CINC(Composite Index of National Capability) and GDP(Gross Domestic Product), which are the most widely used as indicators of national and economic power, and as output variables, the full-load displacement, length, and width of aircraft carriers were selected. ARIMA(short-term within 5 years) and simple regression(long-term over 5 years) were used to estimate the future national competency of each country at the time of aircraft carriers acquisition. The relative efficiency score of the Korean-type aircraft carrier currently being evaluated is 1.062, and it was evaluated as small-scale aircraft carrier compared to the national competency. Based on Korean national competency, the optimal scale of the Korean-type aircraft carrier calculated by aggregating benchmark groups, is 58,308.1 tons of full-load displacement, 279.4m in length, and 68.3m in width.

Automatic Calibration of Storage-Function Rainfall-Runoff Model Using an Optimization Technique (최적화(最適化) 기법(技法)에 의한 저유함수(貯留函數) 유출(流出) 모형(模型)의 자동보정(自動補正))

  • Shim, Soon Bo;Kim, Sun Koo;Ko, Seok Ku
    • KSCE Journal of Civil and Environmental Engineering Research
    • /
    • v.12 no.3
    • /
    • pp.127-137
    • /
    • 1992
  • For the real-time control of a multi-purpose reservoir in case of a storm, it is absolutely necessary to forecast accurate flood inflows through a good rainfall-runoff model by calibrating the parameters with the on-line rainfall and water level data transmitted by the telemetering systems. To calibrate the parameters of a runoff model. the trial and error method of manual calibration has been adopted from the subjective view point of a model user. The object of this study is to develop a automatic calibration method using an optimization technique. The pattern-search algorithm was applied as an optimization technique because of the stability of the solution under various conditions. The object function was selected as the sum of the squares of differences between observed and fitted ordinates of the hydrograph. Two historical flood events were applied to verify the developed technique for the automatic calibration of the parameters of the storage-function rainfall-runoff model which has been used for the flood control of the Soyanggang multi-purpose reservoir by the Korea Water Resources Corporation. The developed method was verified to be much more suitable than the manual method in flood forecasting and real-time reservoir controlling because it saves calibration time and efforts in addition to the better flood forecasting capability.

  • PDF

Preference-based Supply Chain Partner Selection Using Fuzzy Ontology (퍼지 온톨로지를 이용한 선호도 기반 공급사슬 파트너 선정)

  • Lee, Hae-Kyung;Ko, Chang-Seong;Kim, Tai-Oun
    • Journal of Intelligence and Information Systems
    • /
    • v.17 no.1
    • /
    • pp.37-52
    • /
    • 2011
  • Supply chain management is a strategic thinking which enhances the value of supply chain and adapts more promptly for the changing environment. For the seamless partnership and value creation in supply chains, information and knowledge sharing and proper partner selection criteria must be applied. Thus, the partner selection criteria are critical to maintain product quality and reliability. Each part of a product is supplied by an appropriate supply partner. The criteria for selecting partners are technological capability, quality, price, consistency, etc. In reality, the criteria for partner selection may change according to the characteristics of the components. When the part is a core component, quality factor is the top priority compared to the price. For a standardized component, lower price has a higher priority. Sometimes, unexpected case occurs such as emergency order in which the preference may shift on the top. Thus, SCM partner selection criteria must be determined dynamically according to the characteristics of part and its context. The purpose of this research is to develop an OWL model for the supply chain partnership depending on its context and characteristics of the parts. The uncertainty of variable is tackled through fuzzy logic. The parts with preference of numerical value and context are represented using OWL. Part preference is converted into fuzzy membership function using fuzzy logic. For the ontology reasoning, SWRL (Semantic Web Rule Language) is applied. For the implementation of proposed model, starter motor of an automobile is adopted. After the fuzzy ontology is constructed, the process of selecting preference-based supply partner for each part is presented.

CONSEQUENCE OF BACKWARD EULER AND CRANK-NICOLSOM TECHNIQUES IN THE FINITE ELEMENT MODEL FOR THE NUMERICAL SOLUTION OF VARIABLY SATURATED FLOW PROBLEMS

  • ISLAM, M.S.
    • Journal of the Korean Society for Industrial and Applied Mathematics
    • /
    • v.19 no.2
    • /
    • pp.197-215
    • /
    • 2015
  • Modeling water flow in variably saturated, porous media is important in many branches of science and engineering. Highly nonlinear relationships between water content and hydraulic conductivity and soil-water pressure result in very steep wetting fronts causing numerical problems. These include poor efficiency when modeling water infiltration into very dry porous media, and numerical oscillation near a steep wetting front. A one-dimensional finite element formulation is developed for the numerical simulation of variably saturated flow systems. First order backward Euler implicit and second order Crank-Nicolson time discretization schemes are adopted as a solution strategy in this formulation based on Picard and Newton iterative techniques. Five examples are used to investigate the numerical performance of two approaches and the different factors are highlighted that can affect their convergence and efficiency. The first test case deals with sharp moisture front that infiltrates into the soil column. It shows the capability of providing a mass-conservative behavior. Saturated conditions are not developed in the second test case. Involving of dry initial condition and steep wetting front are the main numerical complexity of the third test example. Fourth test case is a rapid infiltration of water from the surface, followed by a period of redistribution of the water due to the dynamic boundary condition. The last one-dimensional test case involves flow into a layered soil with variable initial conditions. The numerical results indicate that the Crank-Nicolson scheme is inefficient compared to fully implicit backward Euler scheme for the layered soil problem but offers same accuracy for the other homogeneous soil cases.

Reverse Simulation Software Architecture for Required Performance Analysis of Defense System (국방 시스템의 요구 성능 분석을 위한 역 방향 시뮬레이션 소프트웨어 아키텍처)

  • Hong, Jeong Hee;Seo, Kyung-Min;Kim, Tag Gon
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.40 no.4
    • /
    • pp.750-759
    • /
    • 2015
  • This paper focuses on reverse simulation methods to find and analyze the required performance of a defense system under a given combat effectiveness. Our approach is motivated that forward simulation, that traditionally employs the effectiveness analysis of performance alternatives, is not suitable for resolving the above issue because it causes a high computational cost due to repeating simulations of all possible alternatives. To this end, the paper proposes a reverse simulation software architecture, which consists of several functional sub-modules that facilitate two types of reverse simulations according to possibility of inverse model design. The proposed architecture also enable to apply various search algorithms to find required operational capability efficiently. With this architecture, we performed two case studies about underwater and anti-air warfare scenarios. The case studies show that the proposed reverse simulation incurs a smaller computational cost, while finding the same level of performance alternatives compared with traditional forward simulation. Finally we expect that this study provides a guide those who desire to make decisions about new defense systems development.

Corroded and loosened bolt detection of steel bolted joints based on improved you only look once network and line segment detector

  • Youhao Ni;Jianxiao Mao;Hao Wang;Yuguang Fu;Zhuo Xi
    • Smart Structures and Systems
    • /
    • v.32 no.1
    • /
    • pp.23-35
    • /
    • 2023
  • Steel bolted joint is an important part of steel structure, and its damage directly affects the bearing capacity and durability of steel structure. Currently, the existing research mainly focuses on the identification of corroded bolts and corroded bolts respectively, and there are few studies on multiple states. A detection framework of corroded and loosened bolts is proposed in this study, and the innovations can be summarized as follows: (i) Vision Transformer (ViT) is introduced to replace the third and fourth C3 module of you-only-look-once version 5s (YOLOv5s) algorithm, which increases the attention weights of feature channels and the feature extraction capability. (ii) Three states of the steel bolts are considered, including corroded bolt, bolt missing and clean bolt. (iii) Line segment detector (LSD) is introduced for bolt rotation angle calculation, which realizes bolt looseness detection. The improved YOLOv5s model was validated on the dataset, and the mean average precision (mAP) was increased from 0.902 to 0.952. In terms of a lab-scale joint, the performance of the LSD algorithm and the Hough transform was compared from different perspective angles. The error value of bolt loosening angle of the LSD algorithm is controlled within 1.09%, less than 8.91% of the Hough transform. Furthermore, the proposed framework was applied to fullscale joints of a steel bridge in China. Synthetic images of loosened bolts were successfully identified and the multiple states were well detected. Therefore, the proposed framework can be alternative of monitoring steel bolted joints for management department.

Proximal Policy Optimization Reinforcement Learning based Optimal Path Planning Study of Surion Agent against Enemy Air Defense Threats (근접 정책 최적화 기반의 적 대공 방어 위협하 수리온 에이전트의 최적 기동경로 도출 연구)

  • Jae-Hwan Kim;Jong-Hwan Kim
    • Journal of the Korea Society for Simulation
    • /
    • v.33 no.2
    • /
    • pp.37-44
    • /
    • 2024
  • The Korean Helicopter Development Program has successfully introduced the Surion helicopter, a versatile multi-domain operational aircraft that replaces the aging UH-1 and 500MD helicopters. Specifically designed for maneuverability, the Surion plays a crucial role in low-altitude tactical maneuvers for personnel transportation and specific missions, emphasizing the helicopter's survivability. Despite the significance of its low-altitude tactical maneuver capability, there is a notable gap in research focusing on multi-mission tactical maneuvers that consider the risk factors associated with deploying the Surion in the presence of enemy air defenses. This study addresses this gap by exploring a method to enhance the Surion's low-altitude maneuvering paths, incorporating information about enemy air defenses. Leveraging the Proximal Policy Optimization (PPO) algorithm, a reinforcement learning-based approach, the research aims to optimize the helicopter's path planning. Visualized experiments were conducted using a Surion model implemented in the Unity environment and ML-Agents library. The proposed method resulted in a rapid and stable policy convergence for generating optimal maneuvering paths for the Surion. The experiments, based on two key criteria, "operation time" and "minimum damage," revealed distinct optimal paths. This divergence suggests the potential for effective tactical maneuvers in low-altitude situations, considering the risk factors associated with enemy air defenses. Importantly, the Surion's capability for remote control in all directions enhances its adaptability in complex operational environments.

Impacts of wave and tidal forcing on 3D nearshore processes on natural beaches. Part I: Flow and turbulence fields

  • Bakhtyar, R.;Dastgheib, A.;Roelvink, D.;Barry, D.A.
    • Ocean Systems Engineering
    • /
    • v.6 no.1
    • /
    • pp.23-60
    • /
    • 2016
  • The major objective of this study was to develop further understanding of 3D nearshore hydrodynamics under a variety of wave and tidal forcing conditions. The main tool used was a comprehensive 3D numerical model - combining the flow module of Delft3D with the WAVE solver of XBeach - of nearshore hydro- and morphodynamics that can simulate flow, sediment transport, and morphological evolution. Surf-swash zone hydrodynamics were modeled using the 3D Navier-Stokes equations, combined with various turbulence models (${\kappa}-{\varepsilon}$, ${\kappa}-L$, ATM and H-LES). Sediment transport and resulting foreshore profile changes were approximated using different sediment transport relations that consider both bed- and suspended-load transport of non-cohesive sediments. The numerical set-up was tested against field data, with good agreement found. Different numerical experiments under a range of bed characteristics and incident wave and tidal conditions were run to test the model's capability to reproduce 3D flow, wave propagation, sediment transport and morphodynamics in the nearshore at the field scale. The results were interpreted according to existing understanding of surf and swash zone processes. Our numerical experiments confirm that the angle between the crest line of the approaching wave and the shoreline defines the direction and strength of the longshore current, while the longshore current velocity varies across the nearshore zone. The model simulates the undertow, hydraulic cell and rip-current patterns generated by radiation stresses and longshore variability in wave heights. Numerical results show that a non-uniform seabed is crucial for generation of rip currents in the nearshore (when bed slope is uniform, rips are not generated). Increasing the wave height increases the peaks of eddy viscosity and TKE (turbulent kinetic energy), while increasing the tidal amplitude reduces these peaks. Wave and tide interaction has most striking effects on the foreshore profile with the formation of the intertidal bar. High values of eddy viscosity, TKE and wave set-up are spread offshore for coarser grain sizes. Beach profile steepness modifies the nearshore circulation pattern, significantly enhancing the vertical component of the flow. The local recirculation within the longshore current in the inshore region causes a transient offshore shift and strengthening of the longshore current. Overall, the analysis shows that, with reasonable hypotheses, it is possible to simulate the nearshore hydrodynamics subjected to oceanic forcing, consistent with existing understanding of this area. Part II of this work presents 3D nearshore morphodynamics induced by the tides and waves.