• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권1호
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• pp.241-269
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• 2012

Wireless networks composed of multimedia-enabled resource-constrained sensor nodes have enriched a large set of monitoring sensing applications. In such communication scenario, however, new challenges in data transmission and energy-efficiency have arisen due to the stringent requirements of those sensor networks. Generally, congested nodes may deplete the energy of the active congested paths toward the sink and incur in undesired communication delay and packet dropping, while bit errors during transmission may negatively impact the end-to-end quality of the received data. Many approaches have been proposed to face congestion and provide reliable communications in wireless sensor networks, usually employing some transport protocol that address one or both of these issues. Nevertheless, due to the unique characteristics of multimedia-based wireless sensor networks, notably minimum bandwidth demand, bounded delay and reduced energy consumption requirement, communication protocols from traditional scalar wireless sensor networks are not suitable for multimedia sensor networks. In the last decade, such requirements have fostered research in adapting existing protocols or proposing new protocols from scratch. We survey the state of the art of transport protocols for wireless multimedia sensor networks, addressing the recent developments and proposed strategies for congestion control and loss recovery. Future research directions are also discussed, outlining the remaining challenges and promising investigation areas.

• 한국통신학회논문지
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• 제32권1B호
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• pp.53-60
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• 2007

본 연구에서는 Diffserv 기반의 네트워크, 특히 그 중에서도 트리구조를 가지는 네트워크에서의 지연시간에 대해서 연구하였다. 이러한 네트워크에서의 지연시간 최대치를 구하는 수식을 구하였고, 특히 기존에 알려진 바와는 달리 트리구조의 네트워크에서는 네트워크 utilization과는 상관없이 최대치가 항상 존재함을 보였다. 지연시간 최대치의 특성은 다음과 같이 표현된다. 네트워크 utilization이 큰 경우 네트워크내의 최대 hop count의 제곱에 비례하며, 네트워크 utilization이 작은 경우는 최대 hop count에 비례한다. 이러한 결과를 바탕으로 실제 Metro Ethernet Network과 같은 대규모 네트워크의 경우에서 DiffServ를 이용하여 실시간 트래픽 전송이 가능하다는 것을 보였다.

• Journal of Welding and Joining
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• 제11권2호
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• pp.27-41
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• 1993

The estimation of nugget sizes was attempted by utilizing the artificial neural networks method. Artificial neural networks is a highly simplified model of the biological nervous system. Artificial neural networks is composed of a large number of elemental processors connected like biological neurons. Although the elemental processors have only simple computation functions, because they are connected massively, they can describe any complex functional relationship between an input-output pair in an autonomous manner. The electrode head movement signal, which is a good indicator of corresponding nugget size was determined by measuring the each test specimen. The sampled electrode movement data and the corresponding nugget sizes were fed into the artificial neural networks as input-output pairs to train the networks. In the training phase for the networks, the artificial neural networks constructs a fuctional relationship between the input-output pairs autonomusly by adjusting the set of weights. In the production(estimation) phase when new inputs are sampled and presented, the artificial neural networks produces appropriate outputs(the estimates of the nugget size) based upon the transfer characteristics learned during the training mode. Experimental verification of the proposed estimation method using artificial neural networks was done by actual destructive testing of welds. The predicted result by the artifficial neural networks were found to be in a good agreement with the actual nugget size. The results are quite promising in that the real-time estimation of the invisible nugget size can be achieved by analyzing the process variable without any conventional destructive testing of welds.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권9호
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• pp.3907-3923
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• 2020

An enhanced irregular repetition slotted ALOHA (IRSA) protocol is proposed by using polarization characteristic of satellite link and MIMO detection in low earth orbit (LEO) satellite networks, which is dubbed polarized MIMO IRSA (PM-IRSA). In the proposed scheme, one or two packets in one slot can be decoded by employing polarized MIMO detection, and more than two collided packets in multiple slots which can construct the virtual MIMO model can be decoded by the MIMO detection algorithm. The performance of the proposed scheme is analyzed with the density evolution (DE) approach and the degree distribution is optimized to maximize the system throughput by using a differential evolution. Numerical results certify our analysis and show that the normalized throughput of the proposed PM-IRSA can achieve 1.89 bits/symbol.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권5호
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• pp.1108-1130
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• 2013

Wireless Body Area Networks (WBANs) are becoming increasingly important to solve the issue of health care. IEEE 802.15.6 is a wireless communication standard for WBANs, aiming to provide a real-time and continuous monitoring. In this paper, we present our development of a modified Markov Chain model and a backoff model, in which most features such as user priorities, contention windows, modulation and coding schemes (MCSs), and frozen states are taken into account. Then we calculate the normalized throughput and average access delay of IEEE 802.15.6 networks under saturation and ideal channel conditions. We make an evaluation of network performances by comparing with IEEE 802.15.4 and the results validate that IEEE 802.15.6 networks can provide high quality of service (QoS) for nodes with high priorities.

• Journal of Advanced Marine Engineering and Technology
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• 제33권1호
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• pp.120-130
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• 2009

In recent years, many mobile wireless communication devices and applications have been deployed on the planet. The mobile multi-hop wireless network models appeared to provide means to access to networks where few infrastructure exists. However, the mobile multi-hop wireless networks have weaker points in attacks and intrusions than the wired and one-hop wireless networks. In this paper, the secure routing issues in most mobile multi-hop wireless network models are surveyed in depth. The state-of-the-art technologies and research activities are explained. Finally, the issues and technologies for the secure routing specific to a maritime network model are sufficiently discussed as conclusions.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.562-567
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• 1998

This paper examined the relations among the multidimensional linear interpolation(MDI) and fuzzy reasoning , and neural networks, and showed that an showed that an MDI is a special form of Tsukamoto's fuzzy reasoning and regularization networks in the perspective of fuzzy reasoning and neural networks, respectively. For this purposes, we proposed a special Tsukamoto's membership (STM) systemand triangular basis function (TBF) networks, Also we verified the condition when our proposed TBF becomes a well-known radial basis function (RBF).

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.1207-1210
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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 and test performances consist of the only 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.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.1215-1218
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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 mixed data The mixed data involves the historic data and the generated data using PARMA (1,1). And, the testing data consist of the only 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.