• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.715-723
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• 2015

Earthwork in a large construction project such as a land development generally costs 20-30% of the total cost. The earthmoving process, comprising of four repetitive tasks: loading, hauling, unloading, returning, is quite simple and it does not need delicate or advanced techniques. Therefore, earthmoving earthwork planning can heavily affect the cost and time., and Even a slight deviation from the plan can increase or decrease the cost and time. This study presents a planning model that minimizes average haul distance in a large complex construction project. Based on earthwork planning, practitioners' heuristics, a districting algorithm and Simulated Annealing algorithm were employed to build the model. Districting algorithm plays a role that divides in dividing an earthmoving area into several sections. Simulated annealing provides a function that decides whether a new generated solution is confident. Finally, the proposed model was applied to a real earthmoving project of a large land development. It was found that the model showed approximately 14% improvement in average hauling distance compared to the actual design plan.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.58-65
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• 2021

Meta-heuristic algorithms have been developed to efficiently solve difficult problems and obtain a global optimal solution. A common feature mimics phenomenon occurring in nature and reliably improves the solution through repetition. And at the same time, the probability is used to deviate from the regional optimal solution and approach the global optimal solution. This study compares the algorithm created based on the above common points with existed SA and HS to show advantages in time and accuracy of results. Existing algorithms have problems of low accuracy, high memory, long runtime, and ignorance. In a two-variable polynomial, the existing algorithms show that the memory increases and the accuracy decrease. In order to improve the accuracy, the new algorithm increases the number of initial inputs and increases the efficiency of the search by introducing a direction using vectors. And, in order to solve the optimization problem, the results of the last experiment were learned to show the learning effect in the next experiment. The new algorithm found a solution in a short time under the experimental conditions of long iteration counts using a two-variable polynomial and showed high accuracy. And, it shows that the learning effect is effective in repeated experiments.

• Journal of Space Technology and Applications
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• v.3 no.3
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• pp.229-238
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• 2023

One of the important ways to improve the performance of magnetometers in satellite exploration is to reduce magnetic noise from satellites. One of the methods to decrease magnetic noise is by extending the satellite boom. However, this approach is often not preferred due to its high cost and operational considerations. Therefore, in many cases, removing interference from the satellite platform in the measured dataset is widely utilized after data acquisition. In this study, we would like to introduce an algorithm for removing magnetic noise observed from magnetometers installed on two solar panels and one main body without a boom.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.146-170
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• 2017

Joint channel assignment and routing is a well-known problem in multi-radio wireless mesh networks for which optimal configurations is required to optimize the overall throughput and fairness. However, other objectives need to be considered in order to provide a high quality service to network users when it deployed with high traffic dynamic. In this paper, we propose a re-configuration optimization model that optimizes the network throughput in addition to reducing the disruption to the mesh clients' traffic due to the re-configuration process. In this multi-objective optimization model, four objective functions are proposed to be minimized namely maximum link-channel utilization, network average contention, channel re-assignment cost, and re-routing cost. The latter two objectives focus on reducing the re-configuration overhead. This is to reduce the amount of disrupted traffic due to the channel switching and path re-routing resulted from applying the new configuration. In order to adapt to traffic dynamics in the network which might be caused by many factors i.e. users' mobility, a centralized heuristic re-configuration algorithm called State-Aware Joint Routing and Channel Assignment (SA-JRCA) is proposed in this research based on our re-configuration model. The proposed algorithm re-assigns channels to radios and re-configures flows' routes with aim of achieving a tradeoff between maximizing the network throughput and minimizing the re-configuration overhead. The ns-2 simulator is used as simulation tool and various metrics are evaluated. These metrics include channel-link utilization, channel re-assignment cost, re-routing cost, throughput, and delay. Simulation results show the good performance of SA-JRCA in term of packet delivery ratio, aggregated throughput and re-configuration overhead. It also shows higher stability to the traffic variation in comparison with other compared algorithms which suffer from performance degradation when high traffic dynamics is applied.

• Korean Journal of Construction Engineering and Management
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• v.22 no.3
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• pp.40-51
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• 2021

MLS (Mobile Laser Scanning) which is a scanning method done by moving the LiDAR (Light Detection and Ranging) is widely employed to capture indoor PCD (Point Cloud Data) for floor plan generation in the AEC (Architecture, Engineering, and Construction) industry. The movement and rotation of LiDAR in the scanning phase cause deformation (i.e. skew) of PCD and impose a significant impact on quality of output. Thus, a de-skewing method is required to increase the accuracy of geometric representation. De-skewing methods which use position and pose information of LiDAR collected by IMU (Inertial Measurement Unit) have been mainly developed to refine the PCD. However, the existing methods have limitations on de-skewing PCD without IMU. In this study, a novel algorithm for de-skewing 2D PCD captured from MLS without IMU is presented. The algorithm de-skews PCD using scan matching between points captured from adjacent scan positions. Based on the comparison of the deskewed floor plan with the benchmark derived from TLS (Terrestrial Laser Scanning), the performance of proposed algorithm is verified by reducing the average mismatched area 49.82%. The result of this study shows that the accurate floor plan is generated by the de-skewing algorithm without IMU.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.10
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• pp.10-16
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• 2008

Generally, the satellite circling round in a low orbit goes through Van Allen belt connecting with the magnetic fold, in which electronic components are easily damaged and shortened by charged particles moving in a cycle between the South Pole and the North Pole. In particular, Single Event Upset(SEU) by radiation could cause electronic device on satellite to malfunction. Based on the idea mentioned above, this study considersabout SEU effect on the On-board Computer(OBC) of STSAT-1 in the space environment radiation, and shows algorithm to cope with SEUs. In this experiment, it also is shown that the repetitive memory read/write operation called memory wash is needed to prevent the accumulation of SEUs and the choice for the period of memory wash is examined. In conclusion, it is expected that this research not only contributes to understand low capacity of On-board Computer(OBC) on Low Earth Orbit satellite(LEOS) and SaTReC Technology satellite(STSAT) series, but also makes good use of each module development of Korea Multi-Purpose Satellite(COMPSAT) series.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.4
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• pp.35-41
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• 2002

To solve the large scale optimization problem approximately, various approaches have been introduced. They are mainly based on recent research advancement of simulations for evolutions, flocking, annealing, and interactions among organisms on artificial environments. The typical ones are simulated annealing(SA), artificial neural network(ANN), genetic algorithms(GA), tabu search(TS), etc. Recently the particle swarm optimization(PSO) has been introduced. The PSO simulates the process of birds flocking or fish schooling for food, as with the information of each agent Is share by other agents. The PSO technique has been applied to various optimization problems of which variables are continuous. However, there are seldom trials for visualization of searching process. This paper proposes a new visualization tool for searching process particle swarm optimization(PSO) algorithm. The proposed tool is effective for understanding the searching process of PSO method and educational for students.

• The KIPS Transactions:PartC
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• v.9C no.2
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• pp.189-196
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• 2002

IPSec is a protocol which provides data encryption, message authentication and data integrity on public and open network transmission. In IPSec, ESP protocol is used when it needs to Provide data encryption, authentication and integrity in real transmission Packets. ESP protocol uses DES-CBC encryption mode when sender encrypts packets and receiver decrypts data through this mode IV is used at that tome. This vague has many risks of attack during transmission by attacker because it is transferred clean and opened. If IV value is modified, then decryption of ESP data is impossible and higher level information is changed. In this paper we propose a new algorithm that it encrpty IV values using DES-ECB mode for preventing IV attack and checks integrity of whole ESP data using message authentication function. Therefore, we will protect attacks of IV and data, and guarantee more safe transmission on the public network.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.748-753
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• 2005

Among processes to manufacture parts from footwear materials like upper leathers, one of the most essential processes is the cutting one optimally arranging lots of parts on raw footwear materials and cutting. A new nesting strategy was proposed for the 2-dimensional part layout by using a two-stage approach, where which can be effectively used for water jet cutting. In the initial layout stage, a SOAL(Self-Organization Assisted Layout) based on the combination of FCM(Fuzzy C-Means) and SOM was adopted. In the layout improvement stage, SA(Simulated Annealing) based approach was adopted for a finer layout. The proposed approach saves much CPU time through a two-stage approach scheme, while other annealing-based algorithm so far reported fur a nesting problem are computationally expensive. The proposed nesting approach uses the stochastic process, and has a much higher possibility to obtain a global solution than the deterministic searching technique. We developed the automatic nesting software of NST(ver.1.1) software for footwear industry by implementing of these proposed algorithms. The NST software was applied by the optimized automatic arrangement algorithm to cut without the loss of leathers. if possible, after detecting damage areas. Also, NST software can consider about several features in not only natural loathers but artificial ones. Lastly, the NST software can reduce a required time to implement generation of NC code. cutting time, and waste of raw materials because the NST software automatically performs parts arrangement, cutting paths generation and finally NC code generation, which are needed much effect and time to generate them manually.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.6
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• pp.809-817
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• 2020

In the design and development process of Small-Sat power distribution and transmission module, the stability of dynamic resources was evaluated by a deep learning algorithm. The requirements for the stability evaluation consisted of the power distribution function of the power distribution module and demand module to the SAR radar in Small-Sat. To verify the performance of the switching power components constituting the power module PDM, the reliability was verified using a dynamic neural network. The adoption material of deep learning for reliability verification is the power distribution function of the payload to the power supplied from the small satellite main body. Modeling targets for verifying the performance of this function are output voltage (slew rate control), voltage error, and load power characteristics. First, to this end, the Coefficient Structure area was defined by modeling, and PCB modules were fabricated to compare stability and reliability. Second, Levenberg-Marquare based Two-Way NARX neural network Sigmoid Transfer was used as a deep learning algorithm.