• Journal of the Korean Institute of Navigation
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• v.24 no.4
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• pp.227-234
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• 2000

In general, neural networks are widely used for the category classification of multispectral images. Since the input multispectral images into neural networks we, however, low contrast images, neural networks converge very slowly and are of bad performance. To overcome this problem, we propose a new image enhancement method which consists of smoothing process, finding the main valley and enhancement process. In addition the enhanced images by the proposed method are used as the input of neural networks for the category classification. When the new category classification method is applied to multispectral LANDSAT TM images, we verified that the neural networks converge very lastly and that the overall category classification performance is improved.

• Journal of Korea Multimedia Society
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• v.11 no.12
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• pp.1697-1705
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• 2008

Several studies made for wireless mesh networks aim to optimize the capacity for wireless networks. Aside from protocol improvements, researches were also done on the physical layer particularly on modulation techniques and antenna efficiency schemes. This paper is concerned with the capacity improvements derived from using spatial diversity with smart adaptive array antennas. The use of spatial diversity, which has been widely proposed for use in cellular networks in order to lessen frequency re-use, can be used in mesh networks both to minimize co-channel interference (CCI) and enable multiple transmissions. This paper aims to study the capacity region and bounds in using smart antennas for single-channel multi-radio systems in relation to the number of spatial diversity or sectors as defined by the beam angle $\beta$.

• ETRI Journal
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• v.43 no.3
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• pp.427-435
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• 2021

Data filtering is an essential task for improving the energy efficiency of radiofrequency identification (RFID) networks. Among various energy-efficient approaches, clustering-based data filtering is considered to be the most effective solution because data from cluster members can be filtered at cluster heads before being sent to base stations. However, this approach quickly depletes the energy of cluster heads. Furthermore, most previous studies have assumed that readers are fixed and interrogate mobile tags in a workspace. However, there are several applications in which readers are mobile and interrogate fixed tags in a specific area. This article proposes a model for dynamic clustering-based data filtering (DCDF) in mobile RFID networks, where mobile readers are re-clustered periodically and the cluster head role is rotated among the members of each cluster. Simulation results show that DCDF is effective in terms of balancing energy consumption among readers and prolonging the lifetime of the mobile RFID networks.

• Knowledge Management Research
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• v.19 no.4
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• pp.19-37
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• 2018

Knowledge transfer among employees integrates individual knowledge scattered within a firm, thus increases organizational effectiveness. In particular, the role of knowledge broker, which enables knowledge sharing across multiple teams or subunits, is critical for the success of knowledge management. This study classified the types of knowledge broker that facilitates knowledge flows among team, and examined the influences of various intra- and inter-team social networks. Survey responses from 128 employees of four R&D teams were gathered and analyzed using partial least square structural equation modeling. The results of analysis showed that all types of inter-team networks(i.e., emotional closeness network, frequency of interaction network, and perceived expertise network) had significant influences on related knowledge brokerage behaviors. In case of intra-team networks, only the emotional closeness network showed significant influence. These results proved the necessity of managing various types of intra- and inter-team networks to encourage knowledge brokerage behaviors within a firm.

• Electronics and Telecommunications Trends
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• v.38 no.2
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• pp.46-55
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• 2023

Extended reality (XR) provides an immersive virtual experience by using various media. The XR virtual environment enables interactions between the real and virtual worlds in virtual, augmented, and mixed reality scenarios. XR is being used in various areas such as industry, medical care, road transportation, gaming, education, and culture. XR and multimedia enhancement are important business scenarios for fifth-generation (5G) mobile networks. As users' demand for emerging media services gradually increases, enhancements in networks should be implemented for delivering multimedia services such as XR. We describe related standardization trends and requirements of the XR service in 5G mobile networks. We also discuss technological enhancements for 5G mobile networks as specified by the 3GPP SA2 working group.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.228-240
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• 2023

Growing complexity in ecosystem structure and functions, under impacts of climate and land-use changes, requires interdisciplinary understandings of processes and the whole-system, and accurate estimates of the changing functions. In the last three decades, observation networks for biodiversity, ecosystems, and ecosystem functions under climate change, have been developed by interested scientists, research institutions and universities. In this paper we will review (1) the development and on-going activities of those observation networks, (2) some outcomes from forest carbon cycle studies at our super-site "Takayama site" in Japan, and (3) a few ideas how we connect in-situ and satellite observations as well as fill observation gaps in the Asia-Oceania region. There have been many intensive research and networking efforts to promote investigations for ecosystem change and functions (e.g., Long-Term Ecological Research Network), measurements of greenhouse gas, heat, and water fluxes (flux network), and biodiversity from genetic to ecosystem level (Biodiversity Observation Network). Combining those in-situ field research data with modeling analysis and satellite remote sensing allows the research communities to up-scale spatially from local to global, and temporally from the past to future. These observation networks oftern use different methodologies and target different scientific disciplines. However growing needs for comprehensive observations to understand the response of biodiversity and ecosystem functions to climate and societal changes at local, national, regional, and global scales are providing opportunities and expectations to network these networks. Among the challenges to produce and share integrated knowledge on climate, ecosystem functions and biodiversity, filling scale-gaps in space and time among the phenomena is crucial. To showcase such efforts, interdisciplinary research at 'Takayama super-site' was reviewed by focusing on studies on forest carbon cycle and phenology. A key approach to respond to multidisciplinary questions is to integrate in-situ field research, ecosystem modeling, and satellite remote sensing by developing cross-scale methodologies at long-term observation field sites called "super-sites". The research approach at 'Takayama site' in Japan showcases this response to the needs of multidisciplinary questions and further development of terrestrial ecosystem research to address environmental change issues from local to national, regional and global scales.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.1
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• pp.279-290
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• 2020

Informal networks between individuals are widely seen as important in East Asian business systems. However, while the performance implications of guanxi in China have been extensively studied, much less is known on how informal networks may influence business outcomes in other East Asian countries. We examine informal networks in inter-organizational research collaborations in South Korea by studying the role of pre-existing social ties and relational orientation in new product development (NPD) collaborations and university-industry research (UIR) collaborations. We conduct an interview-based, in-depth case analysis of five NPD collaborations and five UIR collaborations. Pre-existing social ties and relational orientation are prevalent in both types of research collaborations. However, they have different consequences for collaboration outcomes. Pre-existing social ties strongly vary in their types and strength, and negatively affect collaboration outcomes unless they result in the selection of competent and motivated partners. Relational orientation manifests itself in a task-related and social exchange between collaboration partners, which contributes to outcomes such as knowledge acquisition and business performance. Korean collaboration managers should rely only on pre-existing social ties that are well-aligned with task-related requirements when initiating and conducting research collaborations. However, the creation of strong relationships between collaboration team members of partnering organizations should be encouraged.

• Journal of the Korea Institute of Building Construction
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• v.20 no.6
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• pp.577-584
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• 2020

Construction automation and robotics have been widely adopted in the construction industry as a promising solution to such issues like a shortage of skilled labor and the difficulties workers face in harsh working environments. The analysis of the knowledge structure and its evolution from the existing articles helps identify essential knowledge elements and possible future research directions. This study attempts to (1) construct keyword networks from the papers published in the International Symposium on Automation and Robotics in Construction (ISARC), (2) investigate how keywords and keyword communities are associated with each other, and (3) examine the changes in the crucial keywords over time. Through cluster analysis, 79 keywords were categorized into four groups (BIM, Building construction, Sensing, and GPS as representative keywords) with similar structural positions. Research trends show that research themes related to Infrastructure, Construction equipment, and 3D have consistently received a large amount of attention, regardless of geographical region. Research on as-built status model utilization through BIM and Laser scanning and improving Energy performance is taking place more frequently. In contrast, research studies related to problem-solving based on Neural networks are not as common as previously. This study provides useful insights into the construction automation field, at both the macro and micro levels.

• ETRI Journal
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• v.32 no.5
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• pp.819-822
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• 2010

Supporting QoS over multihop wireless mesh networks is difficult because end-to-end delay increases quickly with the increasing number of hops. This paper introduces a novel multichannel time-division multiple-access media access control (McTMAC) protocol that can help to efficiently reduce delay over multihop networks. Performance evaluation results demonstrate that McTMAC outperforms existing alternative protocols. The max-delay can be reduced by as much as 60% by using McTMAC.

• Journal of applied mathematics & informatics
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• v.28 no.1_2
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• pp.295-309
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• 2010

In this paper, we study delayed high-order Cohen-Grossberg neural networks with reaction-diffusion terms and Neumann boundary conditions. By using inequality techniques and constructing Lyapunov functional method, some sufficient conditions are given to ensure the existence and convergence of the periodic oscillatory solution. Finally, an example is given to verify the theoretical analysis.