• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4664-4681
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• 2020

Modulation recognition (MR) plays a key role in cognitive radar, cognitive radio, and some other civilian and military fields. While existing methods can identify the signal modulation type by extracting the signal characteristics, the quality of feature extraction has a serious impact on the recognition results. In this paper, an end-to-end MR method based on long short-term memory (LSTM) and the gated recurrent unit (GRU) is put forward, which can directly predict the modulation type from a sampled signal. Additionally, the sliding window method is applied to fast-changing mixed-modulation signals for which the signal modulation type changes over time. The recognition accuracy on training datasets in different SNR ranges and the proportion of each modulation method in misclassified samples are analyzed, and it is found to be reasonable to select the evenly-distributed and full range of SNR data as the training data. With the improvement of the SNR, the recognition accuracy increases rapidly. When the length of the training dataset increases, the neural network recognition effect is better. The loss function value of the neural network decreases with the increase of the training dataset length, and then tends to be stable. Moreover, when the fast-changing period is less than 20ms, the error rate is as high as 50%. As the fast-changing period is increased to 30ms, the error rates of the GRU and LSTM neural networks are less than 5%.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.30 no.1
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• pp.44-49
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• 2022

This study performed precision instrument landing procedures for pilots with a commercial pilot license using VR HMD flight simulators, and assuming that the center of the pilot's gaze is in the front, 3-D.O.F. head tracking data and 2-D eye tracking of VR HMD worn by pilots gaze tracking was performed through. After that, AOI (Area of Interesting) was set for the instrument panel and external field of view of the cockpit to analyze how the pilot's gaze was distributed before and after the decision altitude. At the same time, the landing results were analyzed using the Localizer and G/S data as the pilot's precision instrument landing flight data. As a result, the pilot was quantitatively evaluated by reflecting the gaze tracking and the resulting landing result using a VR HMD simulator.

• Journal of the Korean Society of Physical Medicine
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• v.18 no.1
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• pp.59-66
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• 2023

PURPOSE: This study examined the foot pressure distribution using the sprinter and skater patterns of coordinative locomotor training. METHODS: Thirty healthy adults, comprising 11 men and 19 women, participated in the study. All the participants performed patterns in sprinter pattern conditions 1-3 and skater pattern conditions 1-3, and were measured using a pedoscan to determine the applied foot pressure distribution. RESULTS: The participants significantly differed in the big toe during the sprinter pattern. As a result of the post hoc test, opposite and opposite sprinters showed a significant difference from the same sprinters (same sprinter; 21.33 ± 5.92, opposite sprinter; 23.54 ± 5.41, and reopposite sprinter; 24.14 ± 6.46). There was a significant difference in the lateral side during the skater pattern. As a result of the post hoc test, reopposite and same skaters showed a significant difference from opposite skaters (same skater; 49.88 ± 5.75, opposite skater; 48.78 ± 5.64, and reopposite skater; 51.15 ± 5.37). CONCLUSION: The foot pressure was distributed toward the hallux and fifth toe according to the sprinter and skater patterns of coordinative locomotor training.

• The Journal of Bigdata
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• v.4 no.2
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• pp.73-83
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• 2019

Since the emergence of the fourth industrial revolution, data analysis is being conducted in various fields. Distributed data processing has already become essential for the fast processing of large amounts of data. However, in the defense sector, simulation used cannot fully utilize the unstructured data which are prevailing at real environments. In this study, we propose a distributed data processing platform that can be applied to battalion level simulation models to provide visualized data for command decisions during training. 500,000 data points of strategic game were analyzed. Considering the winning factors in the data, variance processing was conducted to analyze the data for the top 10% teams. With the increase in the number of nodes, the model becomes scalable.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.950-953
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• 2007

The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.300-305
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• 2023

Audience reactions in response to remote virtual performances must be compressed before being transmitted to the server. The server, which aggregates these data for group insights, requires a distribution code for the transfer. Recently, distributed learning algorithms such as federated learning have gained attention as alternatives that satisfy both the information security and efficiency requirements. In distributed learning, no individual user has access to complete information, and the objective is to achieve a learning effect similar to that achieved with the entire information. It is therefore important to distribute interdependent information among users and subsequently aggregate this information following training. In this paper, we present a new extension technique for minimal code that allows a new minimal code with a different length and Hamming weight to be generated through the product of any vector and a given minimal code. Thus, the proposed technique can generate minimal codes with previously unknown parameters. We also present a scenario wherein these combined methods can be applied.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.11
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• pp.393-402
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• 2016

A Military L-V-C system consists of distributed complex systems integrating Live systems working on physical wall-clock time, Virtual systems ruled by virtually pseudo realtime events on a computer, and Constructive systems only depending on the causal relationship between the continuous events. Recently many needs for L-V-C training systems are increasing in order to achieve the maximum training effects with low costs. While theoretical/logical researches or only partially interworking technologies have been proposed, there are few perfect interworking architectures for totally interoperating L-V-C systems in world-wide. In this paper, we design and develop a novel interworking architecture based on data centric middleware for the consistent global time with the same states on the entire L-V-C data and events by means of integrating the heterogeneous distributed middleware standards of each L-V-C system. In addition, simulated L-V-C systems based on real systems will be used for the efficiency and performance of the developed interworking architecture.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.7
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• pp.791-797
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• 2014

In order to create an environment for Apache Hadoop for parallel distributed processing system of Bigdata, by connecting a plurality of computers, or to configure the node, using the configuration of the virtual nodes on a single computer it is necessary to build a cloud fading environment. However, be constructed in practice for education in these systems, there are many constraints in terms of cost and complex system configuration. Therefore, it is possible to be used as training for educational institutions and beginners in the field of Bigdata processing, development of learning systems and inexpensive practical is urgent. Based on the Raspberry Pi board, training and analysis of Big data processing, such as Hadoop and NoSQL is now the design and implementation of a learning system of parallel distributed processing of possible Bigdata in this study. It is expected that Bigdata parallel distributed processing system that has been implemented, and be a useful system for beginners who want to start a Bigdata and education.

• Journal of the Korean Association of Geographic Information Studies
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• v.1 no.1
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• pp.70-85
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• 1998

This study intends to identify the effects of user attitude, user education & training on the information systems implementation performance. In order to obtain data, survey questionnaires were distributed to the users of 'D' company, the major findings can be summarized as follows. First, it's suggested from the analyses that user attitude and user education & training independently have statistically significant effects on information systems implementation performance. Second, it's revealed that even though the interaction effects by both user attitude and user education & training have positive effects on the level of usage, but have no statistically significant effects on satisfaction level. Based on these results, it's recommended to convert user attitude favorably toward user environment and to increase the level of user education & training, in order to promote information systems implementation performance. Especially, differentiated user education & training are highly recommended.

• Asia pacific journal of information systems
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• v.9 no.4
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• pp.143-161
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• 1999

The objective of this research is to develop education and training systems for IS department and user department personnel, which is essential to effective implementation IT(information technology) strategies in most of organizations. In order to achieve this research objective, first this study theoretically derives six categories of education and training based on comprehensive review of the previous research, and explicates concrete items for each category. And then, with respect to each of these items, we empirically investigate the degree of necessity measured by the gap between the required level of knowledge and skills which staff members should have for effective implementation of IT strategies and the present level of them which they really have. Field survey is employed for the data collection: 270 questionnaires are distributed to the companies in private and public sectors, and 196 questionnaires are collected in useful condition and are analyzed. The findings of this research shows that six dimensions of education and training are empirically derived by factor analysis as following: (1) general knowledge for organizational overview, (2) management knowledge and skills, (3) knowledge and skills of the specific information system which IS department and user department personnel are directly involved in developing and operating, (4) knowledge and skills for strategic use of IT, (5) general knowledge and skills for IT and (6) advanced expert knowledge and skills for specific IT. And the degree of necessity turns out to be statistically significantly different among six dimensions of education and training needed by IS department and user department personnel respectively. Also for each dimension, the degree of necessity is shown to be statistically significantly different between IS department and user department personnel The results of this study can provide the theoretical basis for constructing the IT education and training system for effective implementation of IT strategies, Also they can be used as a practical guideline in developing and promoting specific IT education and training programs in real organizations.