• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.4
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• pp.424-434
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• 2012

This paper presents a path planning algorithm of the unmanned aerial vehicle for the neutralization of the enemy firepower. The long range firepower of the ememy is usually located at the rear side of the mountain which is difficult to bomb. The path planner not only consider the differential constraints of the Unmanned Aerial Vehicle (UAV) but also consider the final approaching angle constraint. This problem is easily solved by incorporating the analytical upper bounded continuous curvature path smoothing algorithm into the Rapidly Exploring Random Tree (RRT) planner. The proposed algorithm can build a feasible path satisfying the kinematic constraints of the UAV on the fly. In addition, the curvatures of the path are continuous over the whole path. Simulation results show that the proposed algorithm can generate a feasible path of the UAV for the bombing mission regardless of the posture of the tunnel.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1089-1098
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• 2020

In this study, we propose a method to detect red tide Cochlodinium Polykrikoide using by machine learning and geostationary marine satellite images. To learn the machine learning model, GOCI Level 2 data were used, and the red tide location data of the National Fisheries Research and Development Institute was used. The machine learning model used logistic regression model, decision tree model, and random forest model. As a result of the performance evaluation, compared to the traditional GOCI image-based red tide detection algorithm without machine learning (Son et al., 2012) (75%), it was confirmed that the accuracy was improved by about 13~22%p (88~98%). In addition, as a result of comparing and analyzing the detection performance between machine learning models, the random forest model (98%) showed the highest detection accuracy.It is believed that this machine learning-based red tide detection algorithm can be used to detect red tide early in the future and track and monitor its movement and spread.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.7
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• pp.989-998
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• 1993

In a bursty user traffic mode, ALOHA random multiple access protocol achieves higher performance than any conventional fixed assignment technique. One of central problems in slotted ALOHA is synchronization. Because of the long propagation delay in satellite mobile communication, packet may be spilt over into adjacent slots and thus guard time may be included between packet intervals. In conventional ALOHA channels, simultaneous transmission by two or more users results in a collision : the unsuccessful packets have to be retransmitted according to some retransmission algorithm. However, in a radio environment, users are often at different distances from the receiver : therefore, their received signals have substantially different power levels. The packet arriving with the highest energy now has a good chance of being detected accurately. Similarly, in some spread-spectrum random access systems, the earliest arriving packet dominates later arriving packets and thus captures the channel. In this paper slotted ALOHA channel with non zero guard time and capture probability is studied. Using the Markovian model, the performance of slotted ALOHA with guard time and capture effects is derived and compared with that of the conventional ALOHA via numerical analysis.

• The Journal of the Korea Contents Association
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• v.17 no.12
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• pp.516-524
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• 2017

This study was to examine the effectiveness of Self-Determination Group Program for children with disabilities in Korea by using method of meta-analysis. For the purpose of the study, master's theses, doctoral dissertations, and journal articles published in Korea up to June, 2017 were systematically reviewed. As a result, a total of 17 studies were eligible for the inclusion criteria. The mean effect sizes and test for homogeneity of effect size(Q-statistic) were analyzed by using Comprehensive Meta-Analysis software 2.0. The main findings of the study were as follows. First, the average effect sizes for Self-Determination Group Program were ES=1.695 of Self-Determination, ES= 1.316 of Social Skills. Second, the moderate variables of the effect size for Self-Determination Group Program was 'age' of 'a type of disability', 'sessions', 'the number of sessions within a week', 'time of one session' and 'a major of the director'. Based on the study results, the research and practice implications were discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.3045-3052
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• 2010

The international standard signature algorithm DSA has been guaranteed its security based on discrete logarithm problem. Recently, the DSA was known to be vulnerable to some fault analysis attacks in which the secret key stored inside of the device can be extracted by occurring some faults when the device performs signature algorithm. After analyzing an existing fault attack presented by Bao et al., this paper proposed a new fault analysis attack by disturbing the random number. Furthermore, we presented a countermeasure to compute DSA signature that has its immunity in the two types of fault attacks. The security and efficiency of the proposed countermeasure were verified by computer simulations.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.4
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• pp.10-16
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• 2007

This paper analyzes the output signal-to-interference-plus-noise ratio (SINR) for a multiple-input-multiple-output (MIMO) multicarrier code division multiple access (MC-CDMA) system with minium mean square error receivers. A previous work of a single antenna MC-CDMA system cannot directly applied to a MIMO MC-CDMA system because some assumptions for single antenna do not match the case of multiple antenna. Therefore this paper expands the concept of freeness to MIMO system by using the Marcenko Pastur law. The analysis shows that the output SINR asymptotically converges to a deterministic value and finds the value on the assumption of freeness. From the analysis, it is easy to calculate bit error rate and the calculation is verified by simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5A
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• pp.479-486
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• 2008

In this paper, an efficient training symbol design with m-sequence is proposed for the MIMO-OFDM based next generation wireless transmission system which supports gigabits per second data rate. In the traditional blute force method, the preamble design is based on the case by case comparison with the system requirements. This paper discusses a training symbol design methodology for the MIMO-OFDM system based on the m-sequence which has been widely used in the spread spectrum communication areas due to its good correlation characteristics. Also the step-by-step design and performance verification method within the limited search space is discussed. The proposed method targets the design of the training symbol which satisfies system requirements for the packet based MIMO-OFDM wireless communication system including automatic gain control(AGC), timing synchronization, frequency and sampling offset estimation, and MIMO channel estimation.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1363-1372
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• 2021

Red tide, defined as the major reproduction of harmful birds, has the characteristics of being generated and diffused in a wide area. This has limitations in detection only with the existing investigation method. Therefore, in this study, red tide was detected using a remote sensing technique. In addition, it was intended to increase the accuracy of detection by using optical characteristics, not just the concentration of chlorophyll. Red tide mainly occurs on the southern coast where sea signals are complex, and the main red tide control species on the southern coast is Cochlodinium polykirkoides. Therefore, it was intended to secure objectivity by reflecting features that could not be found depending on the researcher's observation and experience, not limited to visual judgment using machine learning techniques. In this study, support background machines and random forest were used among machine learning models, and as a result of calculating accuracy as performance evaluation indicators of the two models, the accuracy was 85.7% and 80.2%, respectively.

• Knowledge Management Research
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• v.21 no.3
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• pp.177-195
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• 2020

The social consciousness on fake reviews has triggered researchers to suggest ways to cope with them by analyzing contents of fake reviews or finding ways to discover them by means of structural characteristics of them. This research tried to collect data from blog posts in Naver and detect habitual patterns users use unconsciously by variables extracted from blogs and blog posts by a machine learning model and wanted to use the technique in predicting fake reviews. Data analysis showed that there was a very high relationship between the number of all the posts registered in the blog of the writer of the related writing and the date when it was registered. And, it was found that, as model to detect advertising reviews, Random Forest is the most suitable. If a review is predicted to be an advertising one by the model suggested in this research, it is very likely that it is fake review, and that it violates the guidelines on investigation into markings and advertising regarding recommendation and guarantee in the Law of Marking and Advertising. The fact that, instead of using analysis of morphemes in contents of writings, this research adopts behavior analysis of the writer, and, based on such an approach, collects characteristic data of blogs and blog posts not by manual works, but by automated system, and discerns whether a certain writing is advertising or not is expected to have positive effects on improving efficiency and effectiveness in detecting fake reviews.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.3
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• pp.8-14
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• 2012

Improving the speed of image processing is in great demand according to spread of high quality visual media or massive image applications such as 3D TV or movies, AR(Augmented reality). SIMD computer attached to a host computer can accelerate various image processing and massive data operations. MAMS is a multi-access memory system which is, along with multiple processing elements(PEs), adequate for establishing a high performance pipelined SIMD machine. MAMS supports simultaneous access to pq data elements within a horizontal, a vertical, or a block subarray with a constant interval in an arbitrary position in an $M{\times}N$ array of data elements, where the number of memory modules(MMs), m, is a prime number greater than pq. MAMS-PP4 is the first realization of the MAMS architecture, which consists of four PEs in a single chip and five MMs. This paper presents implementation of image processing algorithms and performance analysis for MAMS-PP16 which consists of 16 PEs with 17 MMs in an extension or the prior work, MAMS-PP4. The newly designed MAMS-PP16 has a 64 bit instruction format and application specific instruction set. The author develops a simulator of the MAMS-PP16 system, which implemented algorithms can be executed on. Performance analysis has done with this simulator executing implemented algorithms of processing images. The result of performance analysis verifies consistent response of MAMS-PP16 through the pyramid operation in image processing algorithms comparing with a Pentium-based serial processor. Executing the pyramid operation in MAMS-PP16 results in consistent response of processing time while randomly response time in a serial processor.