• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.1211-1214
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• 2009

The goal of this research is to apply the neural networks models for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks models consist of generalized regression neural networks model (GRNNM) and multilayer perceptron neural networks model (MLP-NNM), respectively. The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks models, they are composed of training and test performances, respectively. The training data consist of the generated data using PARMA (1,1). And, the testing data consist of the historic data, respectively. From this research, we evaluate the impact of GRNNM and MLP-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE data from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• 한국경영과학회지
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• 제35권2호
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• pp.53-69
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• 2010

This paper proposes an ant-based routing algorithm, Ant System-Routing in wireless Senor Networks(AS-RSN), for wireless sensor networks. Using a transition rule in Ant System, sensors can spread data traffic over the whole network to achieve energy balance, and consequently, maximize the lifetime of sensor networks. The transition rule advances one of the original Ant System by re-defining link cost which is a metric devised to consider energy-sufficiency as well as energy-efficiency. This metric gives rise to the design of the AS-RSN algorithm devised to balance the data traffic of sensor networks in a decentralized manner and consequently prolong the lifetime of the networks. Therefore, AS-RSN is scalable in the number of sensors and also robust to the variations in the dynamics of event generation. We demonstrate the effectiveness of the proposed algorithm by comparing three existing routing algorithms: Direct Communication Approach, Minimum Transmission Energy, and Self-Organized Routing and find that energy balance should be considered to extend lifetime of sensor network and increase robustness of sensor network for diverse event generation patterns.

• 한국멀티미디어학회논문지
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• 제20권12호
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• pp.1940-1950
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• 2017

The security threat types in underwater communication networks environment are almost the same as the terrestrial, but the security of mechanisms the terrestrial RF-based networks environment can not be directly applied due to not only the limited resources of each node but also unsafe channel such as low propagation delay, high bit error rate etc. Nevertheless there has not been much research on the security of underwater acoustic communication networks. Therefore, in this paper analyzes the differences between the terrestrial communication networks and underwater acoustic communication networks, and identifies issues that are the starting points of underwater communication networks security research.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2010년도 학술발표회
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• pp.1645-1648
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• 2010

The goal of this research is to apply the neural networks model for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks model consists of recurrent neural networks model (RNNM). The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks model, it is composed of training and test performances, respectively. The training and test performances consist of the historic, the generated, and the mixed data, respectively. From this research, we evaluate the impact of RNNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2010년도 학술발표회
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• pp.1346-1349
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• 2010

The goal of this research is to apply the neural networks models for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks models consist of generalized regression neural networks model (GRNNM) and multilayer perceptron neural networks model (MLP-NNM), respectively. The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks models, they are composed of training and test performances, respectively. The training and test performances consist of the historic, the generated, and the mixed data, respectively. From this research, we evaluate the impact of GRNNM and MLP-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권1호
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• pp.147-161
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• 2012

In recent years, machine-to-machine (M2M) communications are under rapid development to meet the fast-increasing requirements of multi-type wireless services and applications. In order to satisfy M2M communications requirements, heterogeneous networks convergence appears in many areas, i.e., mobile cellular networks (MCNs) and wireless sensor networks (WSNs) are evolving from heterogeneous to converged. In this paper, we introduce the system architecture and application requirement for converged MCN and WSN, where mobile terminals in MCN are acting as both sensor nodes and gateways for WSN. And then, we discuss the joint optimization of converged networks for M2M communications. Finally, we discuss the technical challenges in the converged process of MCN and WSN.

• International Journal of Computer Science & Network Security
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• 제23권12호
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• pp.137-144
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• 2023

The relevance of the research topic lies in the necessity to use social networks as innovative tools of marketing communications. A wide audience and the ability to segment the market for a specific consumer determine the construction of a corporate strategy, which will be based on using the social networking approach. The spread of the global coronavirus pandemic has led to the rapid development of remote communication channels between the company and the customer. The issue of using marketing tools in social networks acquires the most urgent importance in the modern world of the introduction and implementation of the company's marketing strategies. The purpose of the academic paper is to study the use of social networks as features of implementing the marketing campaign. Social networks are the result of the development of digital technologies and the processes of creating an information society involved in the digital space. The objectives of the research are to analyse the opportunity of using social networks as a tool for marketing communications and their implementation at the level of its widespread use by enterprises and establishments. It is significant to create an advertising campaign by defining the target audience and outlining the key aspects, on which the company is focused. The research methodology consists in determining the theoretical and methodological approaches to the essence of introducing social networks and their practical importance in the implementation of marketing activities of companies. The obtained results can significantly improve the quality of functioning of modern enterprises and organizations that plan to master a new market segment or gain competitive advantages in the existing one. The academic paper examines the essence of social networks as a tool of marketing communications. The key principles of the development of digital social platforms were revealed. The quality of implementing the advertising campaign in the social network was studied, and further prospects for the development of using social networks as a component of the marketing strategy were outlined. Therefore, the academic paper analyses the problems of using social networks as a marketing tool.

• 한국정보통신학회논문지
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• 제18권12호
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• pp.2847-2856
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• 2014

해상 멀티대역 네트워크에서 가용한 해상 통신들을 통합 운용하여 다양한 멀티미디어 서비스를 단절없이 제공하기 위해 수직 핸드오버 기술은 필수적이다. IEEE 802.21에서 육상 무선 네트워크를 위한 수직핸드오버 기술을 권고하나, 해상의 VHF, HF, 위성 네트워크는 고려되지 않아 해상 멀티대역 네트워크에 적용하기 어렵다. 본 논문에서는 해상 멀티대역 네트워크에 적용할 수 있는 수직 핸드오버를 위한 논리 구조와 참조 통신모델을 제안하고, 관련 명령어를 재정의한 수직핸드오버 절차를 제안한다. 이는 해상 멀티대역 네트워크 구현 시, 수직핸드오버에 대한 참조 모델로 유용하게 적용될 수 있다. 더욱이 해상 멀티대역 네트워크를 위한 수직핸드오버 기술은 IEEE 802.21과 연계되어 육상과 해상 전체를 아우르는 이기종 무선 네크워크의 실현에 적용할 수 있다.

• 한국항해학회지
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• 제23권3호
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• pp.35-44
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• 1999

This research aims to seek active control of ball-beam position stability by resorting to neural networks whose layers are given bias weights. The controller consists of an LQR (linear quadratic regulator) controller and a neural networks controller in parallel. The latter is used to improve the responses of the established LQR control system, especially when controlling the system with nonlinear factors or modelling errors. For the learning of this control system, the feedback-error learning algorithm is utilized here. While the neural networks controller learns repetitive trajectories on line, feedback errors are back-propagated through neural networks. Convergence is made when the neural networks controller reversely learns and controls the plant. The goals of teaming are to expand the working range of the adaptive control system and to bridge errors owing to nonlinearity by adjusting parameters against the external disturbances and change of the nonlinear plant. The motion equation of the ball-beam system is derived from Newton's law. As the system is strongly nonlinear, lots of researchers have depended on classical systems to control it. Its applications of position control are seen in planes, ships, automobiles and so on. However, the research based on artificial control is quite recent. The current paper compares and analyzes simulation results by way of the LQR controller and the neural network controller in order to prove the efficiency of the neural networks control algorithm against any nonlinear system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권12호
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• pp.4856-4871
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• 2015

Backpressure based scheduling has been considered as a promising technique for improving the throughput of a wide range of communication networks. However, this scheduling technique has not been well studied for heterogeneous wireless networks. In this paper, we propose a virtual-queue based backpressure scheduling (VQB) algorithm for heterogeneous multi-hop wireless networks. The VQB algorithm introduces a simple virtual queue for each flow at a node for backpressure scheduling, whose length depends on the cache size of the node. When calculating flow weights and making scheduling decisions, the length of a virtual queue is used instead of the length of a real queue. We theoretically prove that VQB is throughput-optimal. Simulation results show that the VQB algorithm significantly outperforms a classical backpressure scheduling algorithm in heterogeneous multi-hop wireless networks in terms of the packet delivery ratio, packet delivery time, and average sum of the queue lengths of all nodes per timeslot.