• Journal of Internet Computing and Services
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• v.10 no.3
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• pp.1-8
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• 2009

The primary tasks of a workflow management system specify workflow models with respect to resource, control-flow, data-flow, functional, and operational perspectives, and to enact their workcases (workflow instances). In terms of enacting workflow models, the essential criterion grading the quality of the system is "how much is the system able to guarantee the correctness of workflow models' enactment?". Particularly, the workflow determinacy problem, which may be caused by the interference of the control-flow and the data-flow specifications, is the most challenging issue in guaranteeing the correctness of the system. We are able to solve the problem by either of the following two approaches-analysis of workflow model and verification of workflow enactment. In the paper, we propose a technique that guarantee the system's correctness through verifying workflow enactment. In other words, the technique is able to detect the conflicts of control-flow and data-flow enactments existing on a workflow model, which causes the system to be non-determinant in enacting workflow models. Finally, by applying the technique to the e-Chautauque workflow management system developed by the authors' research group, we prove that the technique is a feasible solution for the workflow determinacy problem.

• Korean Journal of Environment and Ecology
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• v.31 no.3
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• pp.318-328
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• 2017

In order to provide basic data for the ecological management of forest vegetation in Southern Naeyeon Mountains, A total of 149 sample plots were selected and vegetation survey was carried out by the phytosociological method of the ZM school to classify vegetation types and to grasp ecological characteristics. The forest vegetation was divided into 10 types in terms of species composition, and had a unit hierarchy of 2 community groups, 4 communities, 6 sub-communities and 6 variants. A total of 19 types of physiognomic vegetation were identified based on uppermost dominant species, of which 18 were natural vegetation and 1 was artificial vegetation. As a result of the analysis of the importance values of constituent species, Quercus mongolica, a potentially natural vegetation element, was found to be relatively more important in most stands than other species, and excluding the artificial interference, most of the areas except for some sites would be changed to Q. mongolica forest. In order to understand the spatial distribution of forest vegetation, 1/5,000 large-scale physiognomic vegetation map was created by the uppermost dominant species. As a result, natural vegetation accounted for 98.2%, the number of vegetation patches was 733 and the average area per patch 3.93ha.

• Korean Journal of Construction Engineering and Management
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• v.16 no.5
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• pp.97-104
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• 2015

Apartment Housing 25 in the field of construction since 2000 collected by types of labor: reinforced concrete, plaster, internal, equipment, electrics communication, the other work. And the performance of labor input was collected in the amount of construction work performed on a monthly basis. After changing the construction period in the standardization work that is 100% of the construction period, the amount was converted into labor ratio by type. Analysis of the input flow rate and the amount of labor conclusions were as follows: (1) The size of the labor rate is reinforced concrete work (38.25%), plastering work (5.10%), internal work (5.67%), equipment work (9.10%), electrics communication (8.76%), the other works (33.12%) and the size of labor rate is the largest work in reinforced concrete work. (2) The peak of labor input ratio was from 52.5% month to 62.5% month. This was when the labor rate of 3.6%. (3) The period month of the largest labor ratio% is 35% month by reinforced concrete construction, and this time it was 2.12% per month labor rate, and reinforced concrete construction is finishing from 65% month to 80% month. This showed the greatest congestion of mutual interference between each works is being continue. The results of this study are the greatest congestion in apartment housing construction has informed the high period(%months), which is essential to a successful project.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.256-261
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• 2008

The curtain-wall work has been more frequently applied in the construction industry since demand of high-rise buildings has been increased. The curtain-wall work is usually performed with the frame work simultaneously for reducing construction period, but it might be delayed because of several problems caused by interference of process. However, there is not an appropriate tool which can be used by a work manager for adjusting quantity of the construction equipments or the workers when the curtain-wall work was delayed. To resolve this problem a construction simulation anticipating and analyzing potential problems before starting the work can be applied in the curtain wall work. This research suggests a general model for the curtain-wall work by using construction simulation and produces a combination of construction equipments and workers which can estimate optimum work productivity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.669-672
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• 2015

Recent Internet of Things (IoT, Internet of Things) that can be applied to various fields as the development of technology has been developed a lot of service and has been developed with the service also for crop management. To manage the essential elements of soil moisture in the crop growth but existing a direct person measuring the fluid point to carry the measuring instrument, if you take advantage of the WPAN (Wireless Personal Area Network) in this paper to manage sensor data, a fixed 3 points (30, 60, 90 cm) and can be managed can be scientifically analyzed the state of growth of the crop. Open field environment is utilized as it is less disturbance of the interference and the frequency of the radio frequency signal of the structure provides a relatively comfortable environment. Therefore, WPAN building and data transmission scheme of the minimum cost is to be developed. In addition, the operation to enter low power mode, the algorithm is necessary because a lot of restrictions on the power supply applied to the sensor nodes and the gateway is constructed in the open field. In the experiment, verifying the effectiveness by using a network configuration of each of the sensor nodes and the gateway, and provides a method for time synchronization of the operation and a low power mode. The study protocol for the RF communication with the LoRa and to enhance communication efficiency is needed in the future.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.55 no.2
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• pp.171-182
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• 2022

The habitat degradation caused by large-scale reclamation leads to devastating impacts, such as fine sediment and mud shrimp Upogebia major settlement on Manila clam Ruditapes philippinarum aquaculture in the eastern Cheonsu Bay tidal flats, Republic of Korea. Despite these impacts, there is a lack of studies on the influence of fine sediments on tidal flats that constitute key mud shrimp habitats. This study provides information on the seawater-sediment environment and the influence of dissolved inorganic nitrogen (DIN) fluctuations depending on mud shrimp burrow hole density. Additionally, it discusses countermeasures for Manila clam habitat management. The results show that mean DIN effluxes in areas with a high-density of burrow holes were up to 4 times (0.12 mmol m^-2 d^-1) higher than those in sites of low-density (0.03 mmol m^-2 d^-1) within the Saho and Songhak-ri tidal flats. To manage interference within the competition zone of Songhak-ri tidal flat, it is important to utilize the settlements of spawning season in all three dimensions. Consequently, additional studies in other tidal flats are essential and research in zones where mud shrimps and juvenile clams coexist will help to determine the priorities in the efficient management of clam aquaculture.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.40 no.2
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• pp.44-58
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• 2022

Bunhwangsa Temple, Baekryulsa Temple and Sambulsa Temple are not famous cultural heritage area, but they are visited by many tourists and are located in Gyeongju National Park and Gyeongju Historic Areas, so environmental and cultural preservations are required. The purpose of this study is to manage the unique environment and landscape of cultural assets by analysing the invasive alien plant of traditional temple of Gyeongju. The whole flora were summarized as 188 taxa including 73 families, 136 genera, 154 species, 3 subspecies, 11 varieties, 4 forms, 5 hybrids and 12 cultivars., and the landscape plants were 163 taxa and 38 taxa of the invasive alien plants. The 13 taxa of invasive alien plants were planted in three temples. The ecosystem disturbance species were 3 taxa including Rumex acetosella, Lactuca seriola and Symphyotrichum pilosum. Invasive alien plants have artificial causes such as landscape planting, but there are also those that are introduced naturally from outside. The parking lot of the temple is expected to be a major propagation path for invasive alien plants due to the large amount of interference and disturbance. Based on the results of this study, the management plans are suggested as follows. First, it is necessary to use native species suitable for the natural environment and traditional landscape of Korea for landscape planting of traditional temples, and development of planting guidelines centered on cultural properties is required. Second, it is necessary to refrain from planting invasive alien plants because traditional temples are located in an important environment and historically. Third, for the preservation of the temple environment, it is necessary to promptly remove the ecosystem disturbance species. Fourth, in order to express the landscape characteristics of traditional temples, a unique planting plan should be established in consideration of the location environment and historicity.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.79-104
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• 2020

Recently, as deep learning has attracted attention, the use of deep learning is being considered as a method for solving problems in various fields. In particular, deep learning is known to have excellent performance when applied to applying unstructured data such as text, sound and images, and many studies have proven its effectiveness. Owing to the remarkable development of text and image deep learning technology, interests in image captioning technology and its application is rapidly increasing. Image captioning is a technique that automatically generates relevant captions for a given image by handling both image comprehension and text generation simultaneously. In spite of the high entry barrier of image captioning that analysts should be able to process both image and text data, image captioning has established itself as one of the key fields in the A.I. research owing to its various applicability. In addition, many researches have been conducted to improve the performance of image captioning in various aspects. Recent researches attempt to create advanced captions that can not only describe an image accurately, but also convey the information contained in the image more sophisticatedly. Despite many recent efforts to improve the performance of image captioning, it is difficult to find any researches to interpret images from the perspective of domain experts in each field not from the perspective of the general public. Even for the same image, the part of interests may differ according to the professional field of the person who has encountered the image. Moreover, the way of interpreting and expressing the image also differs according to the level of expertise. The public tends to recognize the image from a holistic and general perspective, that is, from the perspective of identifying the image's constituent objects and their relationships. On the contrary, the domain experts tend to recognize the image by focusing on some specific elements necessary to interpret the given image based on their expertise. It implies that meaningful parts of an image are mutually different depending on viewers' perspective even for the same image. So, image captioning needs to implement this phenomenon. Therefore, in this study, we propose a method to generate captions specialized in each domain for the image by utilizing the expertise of experts in the corresponding domain. Specifically, after performing pre-training on a large amount of general data, the expertise in the field is transplanted through transfer-learning with a small amount of expertise data. However, simple adaption of transfer learning using expertise data may invoke another type of problems. Simultaneous learning with captions of various characteristics may invoke so-called 'inter-observation interference' problem, which make it difficult to perform pure learning of each characteristic point of view. For learning with vast amount of data, most of this interference is self-purified and has little impact on learning results. On the contrary, in the case of fine-tuning where learning is performed on a small amount of data, the impact of such interference on learning can be relatively large. To solve this problem, therefore, we propose a novel 'Character-Independent Transfer-learning' that performs transfer learning independently for each character. In order to confirm the feasibility of the proposed methodology, we performed experiments utilizing the results of pre-training on MSCOCO dataset which is comprised of 120,000 images and about 600,000 general captions. Additionally, according to the advice of an art therapist, about 300 pairs of 'image / expertise captions' were created, and the data was used for the experiments of expertise transplantation. As a result of the experiment, it was confirmed that the caption generated according to the proposed methodology generates captions from the perspective of implanted expertise whereas the caption generated through learning on general data contains a number of contents irrelevant to expertise interpretation. In this paper, we propose a novel approach of specialized image interpretation. To achieve this goal, we present a method to use transfer learning and generate captions specialized in the specific domain. In the future, by applying the proposed methodology to expertise transplant in various fields, we expected that many researches will be actively conducted to solve the problem of lack of expertise data and to improve performance of image captioning.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.19-41
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• 2019

According to the rapidly increasing demand for text data analysis, research and investment in text mining are being actively conducted not only in academia but also in various industries. Text mining is generally conducted in two steps. In the first step, the text of the collected document is tokenized and structured to convert the original document into a computer-readable form. In the second step, tasks such as document classification, clustering, and topic modeling are conducted according to the purpose of analysis. Until recently, text mining-related studies have been focused on the application of the second steps, such as document classification, clustering, and topic modeling. However, with the discovery that the text structuring process substantially influences the quality of the analysis results, various embedding methods have actively been studied to improve the quality of analysis results by preserving the meaning of words and documents in the process of representing text data as vectors. Unlike structured data, which can be directly applied to a variety of operations and traditional analysis techniques, Unstructured text should be preceded by a structuring task that transforms the original document into a form that the computer can understand before analysis. It is called "Embedding" that arbitrary objects are mapped to a specific dimension space while maintaining algebraic properties for structuring the text data. Recently, attempts have been made to embed not only words but also sentences, paragraphs, and entire documents in various aspects. Particularly, with the demand for analysis of document embedding increases rapidly, many algorithms have been developed to support it. Among them, doc2Vec which extends word2Vec and embeds each document into one vector is most widely used. However, the traditional document embedding method represented by doc2Vec generates a vector for each document using the whole corpus included in the document. This causes a limit that the document vector is affected by not only core words but also miscellaneous words. Additionally, the traditional document embedding schemes usually map each document into a single corresponding vector. Therefore, it is difficult to represent a complex document with multiple subjects into a single vector accurately using the traditional approach. In this paper, we propose a new multi-vector document embedding method to overcome these limitations of the traditional document embedding methods. This study targets documents that explicitly separate body content and keywords. In the case of a document without keywords, this method can be applied after extract keywords through various analysis methods. However, since this is not the core subject of the proposed method, we introduce the process of applying the proposed method to documents that predefine keywords in the text. The proposed method consists of (1) Parsing, (2) Word Embedding, (3) Keyword Vector Extraction, (4) Keyword Clustering, and (5) Multiple-Vector Generation. The specific process is as follows. all text in a document is tokenized and each token is represented as a vector having N-dimensional real value through word embedding. After that, to overcome the limitations of the traditional document embedding method that is affected by not only the core word but also the miscellaneous words, vectors corresponding to the keywords of each document are extracted and make up sets of keyword vector for each document. Next, clustering is conducted on a set of keywords for each document to identify multiple subjects included in the document. Finally, a Multi-vector is generated from vectors of keywords constituting each cluster. The experiments for 3.147 academic papers revealed that the single vector-based traditional approach cannot properly map complex documents because of interference among subjects in each vector. With the proposed multi-vector based method, we ascertained that complex documents can be vectorized more accurately by eliminating the interference among subjects.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.13 no.3
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• pp.46-62
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• 2010

This study was conducted to understand the water and soil properties to propose the promotion of vegetation environment at farm pond depression. We selected 8 palustrine wetlands from agricultural area after consideration of human interference, surround land use, and size of area. Water quality analysis showed that the average SS, T-N, T-P were over the limit of agricultural water quality standard level at some sites. The cause for deterioration of water quality is supposed by the long-term stagnation of water in palustrine wetland. The recommended measures to improve water quality are as follows; improving water circulation by connecting with nearby natural water, preventing oxygen depletion by dredging deposit, lowering down T-N and T-P by removing autumn plants, preventing inflow of phosphorus in fertilizer ingredients which is the main cause for high T-P. The soil contamination of the surveyed area was about the same level of average heavy metal contents in soils from 2,010 paddy fields in Korea, which was much lower than soil contamination standards. As for soil texture, sand content was 40~90% and clay content was less than 20%. The content of silt and clay in soil from community of floating-leaved:submerged hydrophytes and community of emergent hydrophytes was higher that of soil from community of hygrophytes, and the content of sand in soil from community of hygrophytes was 10% higher than underwater soil. In terms of bulk density, the average was 0.24~0.96g/$cm^3$, which was quite low, because of high content of peat and organic matter in soil of the surveyed area. As for the average content of organic matter, community of floating-leaved:submerged hydrophytes was 18.25g/kg, community of emergent hydrophytes was 16.88g/kg, and community of hydrophytes was 25.63g/kg. The range of content of T-N in soil of community of floating-leaved；submerged hydrophytes was 0.022~0.307%, and that of community of emergent hydrophytes was 0.029~0.681% and that of community of hydrophytes was 0.088~0.325%. Apart from three sites in the surveyed area, most parts were over the standards or below the standard. After this study, we will conduct and discuss the relationship between vegetation characteristics and environments, which will be used of the best practical management and restoration of wetland.