• The Journal of Information Systems
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• v.31 no.3
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• pp.177-195
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• 2022

Purpose This paper aims to prepare a full operational readiness by establishing an optimal flight plan considering the weather conditions in order to effectively perform the mission and operation of military aircraft. This paper suggests a flight prediction model and rules by analyzing the correlation between flight implementation and cancellation according to weather conditions by using big data collected from historical flight information of military aircraft supplied by Korean manufacturers and meteorological information from the Korea Meteorological Administration. In addition, by deriving flight rules according to weather information, it was possible to discover an efficient flight schedule establishment method in consideration of weather information. Design/methodology/approach This study is an analytic study using data mining techniques based on flight historical data of 44,558 flights of military aircraft accumulated by the Republic of Korea Air Force for a total of 36 months from January 2013 to December 2015 and meteorological information provided by the Korea Meteorological Administration. Four steps were taken to develop optimal flight prediction models and to derive rules for flight implementation and cancellation. First, a total of 10 independent variables and one dependent variable were used to develop the optimal model for flight implementation according to weather condition. Second, optimal flight prediction models were derived using algorithms such as logistics regression, Adaboost, KNN, Random forest and LightGBM, which are data mining techniques. Third, we collected the opinions of military aircraft pilots who have more than 25 years experience and evaluated importance level about independent variables using Python heatmap to develop flight implementation and cancellation rules according to weather conditions. Finally, the decision tree model was constructed, and the flight rules were derived to see how the weather conditions at each airport affect the implementation and cancellation of the flight. Findings Based on historical flight information of military aircraft and weather information of flight zone. We developed flight prediction model using data mining techniques. As a result of optimal flight prediction model development for each airbase, it was confirmed that the LightGBM algorithm had the best prediction rate in terms of recall rate. Each flight rules were checked according to the weather condition, and it was confirmed that precipitation, humidity, and the total cloud had a significant effect on flight cancellation. Whereas, the effect of visibility was found to be relatively insignificant. When a flight schedule was established, the rules will provide some insight to decide flight training more systematically and effectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.85-92
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• 2018

Reductions of the electricity charge are achieved by demand management of the load. The demand management method of the load using ESS involves peak shifting, which shifts from a high demand time to low demand time. By shifting the load, the peak load can be lowered and the energy charge can be saved. Electricity charges consist of the energy charge and the basic charge per contracted capacity. The energy charge and peak load are minimized by Linear Programming (LP) and Quadratic Programming (QP), respectively. On the other hand, each optimization method has its advantages and disadvantages. First, the LP cannot separate the efficiency of the ESS. To solve these problems, the charge and discharge efficiency of the ESS was separated by Mixed Integer Linear Programming (MILP). Nevertheless, both methods have the disadvantages that they must assume the reduction ratio of peak load. Therefore, QP was used to solve this problem. The next step was to optimize the formula combination of QP and LP to minimize the electricity charge. On the other hand, these two methods have disadvantages in that the charge and discharge efficiency of the ESS cannot be separated. This paper proposes an optimization method according to the situation by analyzing quantitatively the advantages and disadvantages of each optimization method.

• The KIPS Transactions:PartA
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• v.16A no.6
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• pp.463-472
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• 2009

Real-time operating systems must have satisfying various conditions such as effective scheduling policies, minimized interrupt delay, resolved priority inversion problems, and its applications to be completed within desired deadline. The real-time operating systems, therefore, should be designed and developed to be optimal for these requirements. MicroC/OS-II, a kind of Real-time operating systems, uses the basic priority inheritance with a mutex to solve priority inversion problems. For the implementation of mutex, the kernel in an operating system should provide supports for numerous tasks with same priority. However, MicroC/OS-II does not provide this support for the numerous tasks of same priority. To solve this problem, MicroC/OS-II cannot but using priority reservation, which leads to the waste of unnecessary resources. In this study, we have dealt with new design a protocol, so called TPSP(Temporary Priority Swap Protocol), by an effective solution for above-mentioned problem, eventually enabling embedded systems with constrained resources environments to run applications.

• The Journal of Society for e-Business Studies
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• v.24 no.4
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• pp.119-133
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• 2019

Recently, the importance prediction of photovoltaic power (PV) is considered as an essential function for scheduling adjustments, deciding on storage size, and overall planning for stable operation of PV facility systems. In particular, since most of PV power is generated in peak time, PV power prediction in a peak time is required for the PV system operators that enable to maximize revenue and sustainable electricity quantity. Moreover, Prediction of the PV power output in peak time without meteorological information such as solar radiation, cloudiness, the temperature is considered a challenging problem because it has limitations that the PV power was predicted by using predicted uncertain meteorological information in a wide range of areas in previous studies. Therefore, this paper proposes the LSTM (Long-Short Term Memory) based the PV power prediction model only using the meteorological, seasonal, and the before the obtained PV power before peak time. In this paper, the experiment results based on the proposed model using the real-world data shows the superior performance, which showed a positive impact on improving the PV power in a peak time forecast performance targeted in this study.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.86-94
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• 2012

In this paper we propose a hardware architecture of high-speed CGH (computer generated hologram) generation processor, which particularly reduces the number of memory access times to avoid the bottle-neck in the memory access operation. For this, we use three main schemes. The first is pixel-by-pixel calculation rather than light source-by-source calculation. The second is parallel calculation scheme extracted by modifying the previous recursive calculation scheme. The last one is a fully pipelined calculation scheme and exactly structured timing scheduling by adjusting the hardware. The proposed hardware is structured to calculate a row of a CGH in parallel and each hologram pixel in a row is calculated independently. It consists of input interface, initial parameter calculator, hologram pixel calculators, line buffer, and memory controller. The implemented hardware to calculate a row of a $1,920{\times}1,080$ CGH in parallel uses 168,960 LUTs, 153,944 registers, and 19,212 DSP blocks in an Altera FPGA environment. It can stably operate at 198MHz. Because of the three schemes, the time to access the external memory is reduced to about 1/20,000 of the previous ones at the same calculation speed.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.7
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• pp.370-379
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• 2006

Computational grid provides the environment which integrates v 따 ious computing resources. Grid environment is more complex and various than traditional computing environment, and consists of various resources where various software packages are installed in different platforms. For more efficient usage of computational grid, therefore, some kind of integration is required to manage grid resources more effectively. In this paper, a global scheduler is suggested, which integrates grid resources at meta level with applying various scheduling policies. The global scheduler consists of a mechanical part and three policies. The mechanical part mainly search user queues and resource queues to select appropriate job and computing resource. An algorithm for the mechanical part is defined and optimized. Three policies are user selecting policy, resource selecting policy, and executing policy. These can be defined newly and replaced with new one freely while operation of computational grid is temporarily holding. User selecting policy, for example, can be defined to select a certain user with higher priority than other users, resource selecting policy is for selecting the computing resource which is matched well with user's requirements, and executing policy is to overcome communication overheads on grid middleware. Finally, various algorithms for user selecting policy are defined only in terms of user fairness, and their performances are compared.

• Journal of Broadcast Engineering
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• v.15 no.2
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• pp.205-216
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• 2010

In this paper, a method of MPEG-2 Transport Stream (TS) multiplexing for Ultra HDTV (UHDTV) and its design and implementation as a SW tool is described. In practice, UHD video may be divided into several HD videos and each video is encoded in parallel. Therefore, it is necessary to synchronize and multiplex multiple bitstreams encoding each HD video for transmitting and storing UHD video. In this paper, it is assumed that 4 HD videos partitioning a UHD spatially are encoded as H.264/AVC and two 5.0 channel audios are encoded by AC-3. Therefore, 4 H.264/AVC elementary streams (ESs) and 2 AC-3 ESs is mainly considered in the TS multiplexing of UHD. For the carriage of H.264/AVC and AC-3 over MPEG-2 TS, PES packetization and TS multiplexing are designed and implemented based on the extended specification of the MPEG-2 Systems and ATSC (Digital audio compressed standard), respectively. The implemented UHD TS multiplexing tool emulates real time HW operation in the time unit corresponding to the duration of one TS packet transmission in a given TS rate. In particular, in order to satisfy the timing model, the buffers defined in the TS System Target Decoder (T-STD) are monitored and their statuses are considered in the scheduling of TS multiplexing. For UHD multiplexing, two kinds of multiplexing structures, which are UHD re-multiplexing and UHD program multiplexing, are implemented and their strength and weakness are investigated. The developed UHD TS multiplexing tool is tested and verified in terms of the syntax and semantics conformance and functionalities by using a commercial analyzer and real-time presentation tools.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.12
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• pp.5622-5632
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• 2011

This paper presents the simulation design and analysis of Integrated Logistics System(ILS) which is operated by using the AGV(Automated Guided Vehicle). To maximize the operation performances of ILS with AGV, many parameters should be considered such as the number, velocity, and dispatching rule of AGV, part types, scheduling, and buffer sizes. We established the design of experiment in a way of Orthogonal Array in order to consider (1)maximizing the throughput; (2)maximizing the vehicle utilization; (3)minimizing the congestion; and (4)maximizing the Automated Storage and Retrieval System(AS/RS) utilization among various critical factors. Furthermore, we performed the optimization by using the simulation-based analysis and Evolution Strategy(ES). As a result, Orthogonal Array which is conducted far fewer than ES significantly saved not only the time but the same outcome when compared after validation test on the result from the two methods. Therefore, this approach ensures the confidence and provides better process for quick analysis by specifying exact experiment outcome even though it provides small number of experiment.

• The KIPS Transactions:PartC
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• v.8C no.6
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• pp.793-805
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• 2001

In the recent priority system, high-priority packet will be served first and low-priority packet will be served when there isn\`t any high-priority packet in the system. By the way, even high-priority packet can be blocked by HOL (Head of Line) contention in the input queueing System. Therefore, the whole switching performance can be improved by serving low-priority packet even though high-priority packet is blocked. In this paper, we study the performance of preemptive priority in an input queueing switch for high speed switch system. The analysis of this switching system is taken into account of the influence of priority scheduling and the window scheme for head-of-line contention. We derive queue length distribution, delay and maximum throughput for the switching system based on these control schemes. Because of the service dependencies between inputs, an exact analysis of this switching system is intractable. Consequently, we provide an approximate analysis based on some independence assumption and the flow conservation rule. We use an equivalent queueing system to estimate the service capability seen by each input. In case of the preemptive priority policy without considering a window scheme, we extend the approximation technique used by Chen and Guerin [1] to obtain more accurate results. Moreover, we also propose newly a window scheme that is appropriate for the preemptive priority switching system in view of implementation and operation. It can improve the total system throughput and delay performance of low priority packets. We also analyze this window scheme using an equivalent queueing system and compare the performance results with that without the window scheme. Numerical results are compared with simulations.

• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.113-122
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• 2009

Since the traditional pattern mining methods only probe unspecified moving patterns that seem to satisfy users' requests among diverse patterns within the limited scopes of time and space, they are not applicable to problems involving the mining of optimal moving patterns, which contain complex time and space constraints, such as 1) searching the optimal path between two specific points, and 2) scheduling a path within the specified time. Therefore, in this paper, we illustrate some problems on mining the optimal moving patterns with complex time and space constraints from a vast set of historical data of numerous moving objects, and suggest a new moving pattern mining method that can be used to search patterns of an optimal moving path as a location-based service. The proposed method, which determines the optimal path(most frequently used path) using pattern frequency retrieved from historical data of moving objects between two specific points, can efficiently carry out pattern mining tasks using by space generalization at the minimum level on the moving object's location attribute in consideration of topological relationship between the object's location and spatial scope. Testing the efficiency of this algorithm was done by comparing the operation processing time with Dijkstra algorithm and $A^*$ algorithm which are generally used for searching the optimal path. As a result, although there were some differences according to heuristic weight on $A^*$ algorithm, it showed that the proposed method is more efficient than the other methods mentioned.