• Proceedings of the Korea Database Society Conference
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• 2008.05a
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• pp.455-465
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• 2008

Recently the discussion on broadcasting and telecommunications convergence has been actively advanced, the convergence service which pulls down the guard of broadcasting and telecommunications industries is already embodied from the market. We need to clearly define a broadcasting and telecommunications convergence in order to develop promising convergence technologies based on future demands for broadcasting and telecommunications convergence. In this study, we consider both broadcasting and telecommunications as 'services-centered industries' and suggest new R&D project selection criteria. This could be used to present a new direction in R&D project management.

• Korean Journal of Remote Sensing
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• v.23 no.5
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• pp.473-481
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• 2007

Joint Forest Management(JFM) is a concept of developing partnerships between fringe forest user groups and the Forest Department(FD) on the basis of mutual trust and jointly defined roles and responsibilities with regard to forest protection and development. In India, JFM was started during 1992 and it was implemented in many states. However success rate of JFM activity was not promising. Though there are many factors attributed to the failures, one of the main factors is the JFM site. This paper deals with the significant ground works to be done before planning for JFM using recent technologies such as remote sensing(RS) and Geographic Information System(GIS). Also it deals with the advantages of weighted overlay analysis in selecting suitable sites for JFM taking into consideration the various criteria. As a result of weighted overlay analysis, there were four types of suitability classes viz., less, moderate, highly and un-suitable. The moderately suitable class occupied maximum area(13209.64 ha) than less and highly suitable classes. If JFM is implemented on the suitability area, then the failure could be avoided in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3821-3841
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• 2019

Cloud radio access networks (C-RANs) have been regarded in recent times as a promising concept in future 5G technologies where all DSP processors are moved into a central base band unit (BBU) pool in the cloud, and distributed remote radio heads (RRHs) compress and forward received radio signals from mobile users to the BBUs through radio links. In such dynamic environment, automatic decision-making approaches, such as artificial intelligence based deep reinforcement learning (DRL), become imperative in designing new solutions. In this paper, we propose a generic framework of autonomous cell activation and customized physical resource allocation schemes for energy consumption and QoS optimization in wireless networks. We formulate the problem as fractional power control with bandwidth adaptation and full power control and bandwidth allocation models and set up a Q-learning model to satisfy the QoS requirements of users and to achieve low energy consumption with the minimum number of active RRHs under varying traffic demand and network densities. Extensive simulations are conducted to show the effectiveness of our proposed solution compared to existing schemes.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.578-578
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• 2016

In the past decade, many countries developed varies promising theories, methodologies and technologies for water resources management, such as Smart Water in Korea, eWater in Australia, Intelligent Water in Untied States, and Internet of Water in China. It is no exaggeration to say that Smart Water Management(SWM) will have a major role to play in addressing the global water challenges in the background of climate change, population growth and rapid urbanization. As a result, we can see major shifts taking place in the structure of the water industry, with a need for new approaches, skills, and water management policies. All these point towards a brighter future for the smart water sector and a new water paradigm, with applications and potential throughout the water cycle. However, each countries have their technology and industry standard system which may swift similar innovation and technology into different channels. In that sense, developing a common performance index and standard docking adapter for assessing Smart Water Management Initiatives(SWMI) is crucial for drawing a linkage of SWMI and SWMs to a way to implement advanced technology across Asia and Pacific. The performance index and standard docking adapter will facilitate quantitative and qualitative effects of utilized SWM techniques.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.271-281
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• 2022

Manual seed classification challenges can be overcome using a reliable and autonomous seed purity identification and classification technique. It is a highly practical and commercially important requirement of the agricultural industry. Researchers can create a new data mining method with improved accuracy using current machine learning and artificial intelligence approaches. Seed classification can help with quality making, seed quality controller, and impurity identification. Seeds have traditionally been classified based on characteristics such as colour, shape, and texture. Generally, this is done by experts by visually examining each model, which is a very time-consuming and tedious task. This approach is simple to automate, making seed sorting far more efficient than manually inspecting them. Computer vision technologies based on machine learning (ML), symmetry, and, more specifically, convolutional neural networks (CNNs) have been widely used in related fields, resulting in greater labour efficiency in many cases. To sort a sample of 3000 seeds, KNN, SVM, CNN and CNN-SVM hybrid classification algorithms were used. A model that uses advanced deep learning techniques to categorise some well-known seeds is included in the proposed hybrid system. In most cases, the CNN-SVM model outperformed the comparable SVM and CNN models, demonstrating the effectiveness of utilising CNN-SVM to evaluate data. The findings of this research revealed that CNN-SVM could be used to analyse data with promising results. Future study should look into more seed kinds to expand the use of CNN-SVMs in data processing.

• Earthquakes and Structures
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• v.22 no.5
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• pp.487-502
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• 2022

China is prone to earthquake disasters, and the higher seismic performance is required by many existing civil buildings. And seismic evaluation and retrofit are effective measures to mitigate seismic hazards. With the development of performance-based seismic design and diverse retrofit technology for buildings, advanced evaluation methods and retrofit strategies are in need. In this paper, we introduced the evolution of seismic performance objectives in China combined with performance-based seismic design. Accordingly, multi-phase evaluation methods and comprehensive seismic capacity assessment are introduced. For buildings with seismic deficiency or higher performance requirements, the retrofit technologies are categorized into three types: component strengthening, system optimization, and passive control. Both engineering property and social property for the retrofit methods are discussed. The traditional seismic retrofit methods usually are costly and disturbing, and for example in Beijing, seismic strengthening costs approx. 1000 RMB/m² (for 160 USD/m²), for hospital building even more expensive as 5000 RMB/m²(for 790 USD/m²). So cost-efficient and little disturbance methods are promising techniques. In the end, some opinions about the retrofit strategy and schemes category are shared and wish to discuss the situation and future of seismic retrofit in China.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.399-408
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• 2020

The construction industry is suffering from aging workers, frequent accidents, as well as low productivity. With the rapid development of information technologies in recent years, automatic construction, especially automatic cranes, is regarded as a promising solution for the above problems and attracting more and more attention. However, in practice, limited by the complexity and dynamics of construction environment, manual inspection which is time-consuming and error-prone is still the only way to recognize the search object for the operation of crane. To solve this problem, an image-processing-based automated object recognition approach is proposed in this paper, which is a fusion of Convolutional-Neutral-Network (CNN)-based and traditional object detections. The search object is firstly extracted from the background by the trained Faster R-CNN. And then through a series of image processing including Canny, Hough and Endpoints clustering analysis, the vertices of the search object can be determined to locate it in 3D space uniquely. Finally, the features (e.g., centroid coordinate, size, and color) of the search object are extracted for further recognition. The approach presented in this paper was implemented in OpenCV, and the prototype was written in Microsoft Visual C++. This proposed approach shows great potential for the automatic operation of crane. Further researches and more extensive field experiments will follow in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.89-104
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• 2024

Cloud-based e-learning (CBEL) represents a promising technological frontier. Existing literature has presented a diverse array of findings regarding the determinants that influence the adoption of CBEL. The primary objective of this study is to conduct an exhaustive examination of the available literature, aiming to determine the key predictors of CBEL utilization by employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. A comprehensive review of 35 articles was undertaken, shedding light on the status of CBEL as an evolving field. Notably, there has been a discernible downturn in related research output during the COVID-19 pandemic, underscoring the temporal dynamics of this subject. It is noteworthy that a significant portion of this research has emanated from the Asian continent. Furthermore, the dominance of the technology acceptance model (TAM) in research frameworks is affirmed by our findings. Through a rigorous thematic analysis, our study identified five overarching themes, each encompassing a diverse range of sub-themes. These themes encompass 1) technological factors, 2) individual factors, 3) organizational factors, 4) environmental factors, and 5) security factors. This categorization provides a structured framework for understanding the multifaceted nature of CBEL adoption determinants. Our study serves as a compass, guiding future research endeavours in this domain. It underscores the imperative for further investigations utilizing diverse theoretical frameworks, contextual settings, research methodologies, and variables. This call for diversity and expansion in research efforts reflects the dynamic nature of CBEL and the evolving landscape of e-learning technologies.

• Journal of Sensor Science and Technology
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• v.33 no.2
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• pp.93-97
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• 2024

With the development of promising future mobility and urban air mobility (UAM) technologies, the demand for LIDAR sensors has increased. The SWIR photodetector is a sensor that detects lasers for the 3D mapping of lidar sensor and is the most important technology of LIDAR sensor. An SWIR photodetector based on QDs in an eye-safe wavelength band of over 1400 nm has been reported. QDs-based SWIR photodetectors can be synthesized and processed through a solution process and have the advantages of low cost and simple processing. However, the organic ligands of QDs have insulating properties that limit their ability to improve the sensitivity and stability of photodetectors. Therefore, the technology to replace organic ligands with inorganic ligands must be developed. In this study, the organic ligand of the synthesized PbS QDs was replaced with a MAPI inorganic ligand, and an SWIR photodetector was fabricated. The analysis of the characteristics of the manufactured photodetector confirmed that the photodetector based on MAPI-capped PbS QDs exhibited up to 26.5% higher responsivity than that based on organic ligand PbS QDs.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.3113-3113
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• 2001

Some two years ago our company undertook a project on manufacturing network rationalization to maximize competitiveness through continuous improvement in manufacturing efficiency. One key outcome was the recognition of the benefits that could be derived from timely application of new technology or novel use of existing technologies and even more importantly the need to develop company wide strategies to maximize the impact of such applications. As a direct result an exercise was undertaken to identify the ten most promising technologies from a list of literally hundreds seen as having the capability of making a rapid impact on the manufacturing initiative. One of the outcomes of this exercise was the identification of Near Infrared Spectroscopy as a pivotal technology for improving process understanding, performance, and control to deliver consistent product quality cost effectively with broad applicability across our product range. While NIR had been in use in targeted areas on some of our sites for some years our new challenge was to develop a strategy to extend NIRs application, initially over 17 manufacturing sites, while concurrently expanding the NIR skill base company wide to ensure that the return on initial investment could be further maximized as shared applications across the remaining sites as required. This presentation will provide an overview of how life cycle based user requirement specifications were developed covering: ㆍSpectrophotometers ㆍSample interfaces ㆍSoftware ㆍEquipment and Software qualification ㆍCalibration transfer ㆍ Ease of developing effective user interfaces and control for applications transferred to a production area ㆍUser training ㆍWorld wide support The presentation will also describe the process adopted for vendor selection to ensure maximum utilization of the existing company wide NIR skill base and its future development to expedite applications of the technology in development, quality control and production areas.