• Journal of Ecology and Environment
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• v.47 no.4
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• pp.187-192
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• 2023

The United States (US) National Science Foundation's (NSF's) National Ecological Observatory Network (NEON) is a continental-scale observation facility, constructed and operated by Battelle, that collects long-term ecological data to better understand and forecast how US ecosystems are changing. All data and samples are collected using standardized methods at 81 field sites across the US and are freely and openly available through the NEON data portal, application programming interface (API), and the NEON Biorepository. NSF led a decade-long design process with the research community, including numerous workshops to inform the key features of NEON, culminating in a formal final design review with an expert panel in 2009. The NEON construction phase began in 2012 and was completed in May 2019, when the observatory began the full operations phase. Full operations are defined as all 81 NEON sites completely built and fully operational, with data being collected using instrumented and observational methods. The intent of the NSF is for NEON operations to continue over a 30-year period. Each challenge encountered, problem solved, and risk realized on NEON offers up lessons learned for constructing and operating distributed ecological data collection infrastructure and data networks. NEON's construction phase included offices, labs, towers, aquatic instrumentation, terrestrial sampling plots, permits, development and testing of the instrumentation and associated cyberinfrastructure, and the development of community-supported collection plans. Although colocation of some sites with existing research sites and use of mostly "off the shelf" instrumentation was part of the design, successful completion of the construction phase required the development of new technologies and software for collecting and processing the hundreds of samples and 5.6 billion data records a day produced across NEON. Continued operation of NEON involves reexamining the decisions made in the past and using the input of the scientific community to evolve, upgrade, and improve data collection and resiliency at the field sites. Successes to date include improvements in flexibility and resilience for aquatic infrastructure designs, improved engagement with the scientific community that uses NEON data, and enhanced methods to deal with obsolescence of the instrumentation and infrastructure across the observatory.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.11
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• pp.85-94
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• 2018

This study aims to investigate how easy pedestrians get around within/through the "Apartment Complexes (AC), " a common style of high-rise multi-family housing in Korea. Over the past six decades, the AC has been the most conventional way to provide standardized housing efficiently to address the problems of the shortage of housing and the substandard housing, due to the explosion of urban population with the rapid industrialization. The AC is a huge chunk of homeogenous multi-family housing, mostly condos with decent infrastructure, including parks, pedestrian passages, schools, ect. Both in the new town development and urban renewal programs have utilized the advantages of the AC. Since the design principals of AC tend to adopt the "protective design" to prevent cars and pedestrians coming outside from passing it, it has been criticised for dissecting the continuity of socioeconomic context in neighborhoods. The neo-traditional planning urbanists, including Jane Jacobs, emphasize that smaller blocks and grid road newtworks are the key in improving social, cultural, and economic vitality of the neighborhoods, because these design concepts allow more pedestrians and different types of people to be mixed in a neighborhood. In this study, we first adopted objective measures for pedestrian accessibility and pedestrian efficiency. These measures were used to calculate the lengths of shortest paths from residential buildings to the edges of AC. We tested the difference in shortest paths between the current pedestrian networks of AC and hypothetical grid networks on the AC, and the relative difference is considered as the pedestrian efficiency, using the network analysis function of Geographic Information Systems (GIS) and Python programming. We found from the randomly selected 30 ACs that the existing non-grid road networks in ACs are worse than the hypothesized grid networks, in terms of pedestrian efficiency. In average, pedestrians in AC with the conventional road networks have to walk than 25%, 26%, and 27% longer than the networks of $125{\times}45m$, $100{\times}45m$, and $75{\times}45m$, respectively. With the t-test analysis, we found the pedestrian efficiency of AC with the conventional network is lower than grid-networks. Many new urbanists stress, easiness of walking is one of the most import elements for community building and social bonds. With the findings from the objective measures of pedestrian accessibility and efficiency, the AC would have limitations to attract people outside into the AC itself, which would increase dis-connectivity with adjacent areas.

• Journal of the Korean association of regional geographers
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• v.14 no.6
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• pp.643-663
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• 2008

The rural area of S. Korea has been excluded from the process of industrialization and urbanization, and is to be faced with a serious crisis in the context of recent globalization/localization with a rapid economic and political change. And hence it is required to give a active attention to community-based welfare for rural areas. The status of welfare of Koryung-gun as such a rural area adjacent to Daegu city is still low, even though recently it has been improved dramatically, and the welfare policy seems not to reflect the rapidly changing conditions of reality, though it has been institutionalized systematically. What is more, the number of dwellers who demand basic welfare has been increased, as welfare services seem not to delivered to them. In order to improve this totally low level of social welfare, major tasks should be pursued to formulate as basic principles an integral approach for community-based welfare and ultimately a restoration of rural community; to construct a mobilization system of diverse resources within community, to develop connections between welfare demanders and providers, and networks of institutes and facilities for community welfare; and to find out and to extend financial sources for welfare policies.

• Journal of Information Technology Services
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• v.14 no.1
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• pp.159-173
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• 2015

This paper presents a study on the Internet of Things based low-power wireless sensor networks for remote monitoring of wildlife ecosystem due to climate change. Especially, it is targeting the wild vegetation communities ecological monitoring. First, we performed a pre-test and analysis for selecting the appropriate frequency for the sensor network to collect and deliver information reliably in harsh propagation environment of the forest area, and selected for sensors for monitoring wild vegetation communities on the basis of considerations for selecting the best sensor. In addition, we have presented the platform concept and hierarchical function structures for effectively monitoring, analyzing and predicting of ecosystem changes, to apply the Internet of Things in the ecological monitoring area. Based on this, this paper presents the system architecture and design of the Internet of Things based low-power wireless sensor networks for monitoring the ecosystem of the wild vegetation communities. Finally, we constructed and operated the test-bed applied to real wild trees, using the developed prototype based on the design.

• International Journal of Contents
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• v.9 no.4
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• pp.22-29
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• 2013

In this paper, we propose a integrated real-time monitoring system for recycling agriculture resourcing based on USN. We design and implement the monitoring system so that we can integrate the quality control of farmyard and liquid manures, barn environment monitoring, and positioning information control into a total management system performing recycling of excrement and manure. Selection of sensors and sensor-node construction and requirements, structure of wire/wireless communication networks, and design of monitoring program are also presented. As a result of operating our system, we can get over various drawbacks of conventional separated system and promote the proper circulation of excrement up to the farmyard. We confirm that these advanced effects arise from the effective management of the total system integrating quality control of farmyard/liquid manure, barn/farmhouse information, and vehicle moving monitoring information etc. Moreover, this monitoring system is able to exchange real-time information throughout communication networks so that we can construct a convenient information environment for agricultural community by converging IT technology with farm and stockbreeding industries. Finally we present some results of processing using our monitoring system. Sensing data and their graphs are processed in real-time, positioning information on the v-world map offers various moving paths of vehicles, and statistical analysis shows all the procedure from excrement occurrence to recycling and resourcing.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.3
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• pp.195-206
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• 2018

Paying close attention to those new to an organization, whether fresh or experienced, whose primary interest is in (re)socialization, the current study intends to (1) further the concept of mentoring from a bilateral relationship to a community and culture fostered by developmental networks, (2) propose an integrated conceptual framework for organizational socialization, and (3) suggest implications for practice and future research. This study reviews, analyzes, and integrates research assets and subsequently re-conceptualizes the aggregate information as valid propositions and a conceptual framework. The findings include (1) 11 propositions regarding the relationships among network characteristics (embeddedness, diversity), developmental functions (career support, psychosocial support, and role modeling), and socialization outcomes (learning and attitudinal outcomes); and (2) an integrated conceptual framework that depicts a comprehensive mechanism through which developmental networks conduce to organizational socialization of newcomers. Implications are that developmental networking must be an individual's fundamental competency and an essential part of organizational onboarding processes, and imperative for both members' career development and innovative organizational culture. By integrating research assets on the developmental phenomenon into conceptualizations, this study furthers the concept of mentoring to organizational culture and stimulates a substantive discourse for theory-building towards organizational socialization from the developmental network perspective.

• Journal of Communications and Networks
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• v.3 no.4
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• pp.342-350
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• 2001

The Internet routing instability, or the rapid fluctuation of network reachability information, is an important problem currently facing the Internet engineering community. High levels of network instability can lead to packet loss, increased network latency, and delayed routing convergence. At the extreme, high levels of routing instability can lead to the loss of internal connectivity in wide-area networks. In this paper, we investigate the variation of domain degree and domain count of the inter-domain network over time by using linear regression model in order to analyze the topology variation of inter-domain network. We Also propose an efficient policy management model to reduce the instability in the inter-domain routing system. The proposed model can be used to identify whether a routing policy is adequate to reduce convergence time that is required to return to a normal state when BGP routing instability happens. Experimental analysis shows that the proposed model can be used to set up routing policy in domains for the purpose of minimizing the effects and the propagation of BGP routing instability.

• The Journal of Bigdata
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• v.4 no.1
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• pp.99-118
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• 2019

This study used network analysis and clustering techniques to analyze studies on social media participation. As a result of the main path analysis, 37 major studies were extracted and divided into two networks: community-related networks and new media-related. Network analysis and clustering result in four clusters. This study has the academic significance of using academic data to grasp research trends at a macro level and using network analysis and machine learning as a methodology.

• International Journal of Contents
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• v.15 no.4
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• pp.59-64
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• 2019

In recent years, emotion recognition has been an interesting and challenging topic. Compared to facial expressions and speech modality, gesture-based emotion recognition has not received much attention with only a few efforts using traditional hand-crafted methods. These approaches require major computational costs and do not offer many opportunities for improvement as most of the science community is conducting their research based on the deep learning technique. In this paper, we propose an end-to-end deep learning approach for classifying emotions based on bodily gestures. In particular, the informative keyframes are first extracted from raw videos as input for the 3D-CNN deep network. The 3D-CNN exploits the short-term spatiotemporal information of gesture features from selected keyframes, and the convolutional LSTM networks learn the long-term feature from the features results of 3D-CNN. The experimental results on the FABO dataset exceed most of the traditional methods results and achieve state-of-the-art results for the deep learning-based technique for gesture-based emotion recognition.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.195-200
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• 2002

ART (Adaptive Resonance Theory [1]) neural network and its variations perform non-hierarchical clustering by unsupervised learning. We propose a scheme "arboART" for hierarchical clustering by using several ART1.5-SSS networks. It classifies multidimensional vectors as a cluster tree, and finds features of clusters. The Basic idea of arboART is to use the prototype formed in an ART network as an input to other ART network that has looser distance criteria (Ishihara, et al., [2,3]). By sending prototype vectors made by ART to one after another, many small categories are combined into larger and more generalized categories. We can draw a dendrogram using classification records of sample and categories. We have confirmed its ability using standard test data commonly used in pattern recognition community. The clustering result is better than traditional computing methods, on separation of outliers, smaller error (diameter) of clusters and causes no chaining. This methodology is applied to Kansei evaluation experiment data analysis.