• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.171-178
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• 2014

This paper presents dynamic modelling of a virtual object in augmented reality environments when external forces are applied to the object in real-time fashion. In order to simulate a natural behavior of the object we employ the theory of Newtonian physics to construct motion equation of the object according to the varying external forces applied to the AR object. In dynamic modelling process, the physical interaction is taken placed between the augmented object and the physical object such as a haptic input device and the external forces are transferred to the object. The intrinsic properties of the augmented object are either rigid or elastically deformable (non-rigid) model. In case of the rigid object, the dynamic motion of the object is simulated when the augmented object is collided with by the haptic stick by considering linear momentum or angular momentum. In the case of the non-rigid object, the physics-based simulation approach is adopted since the elastically deformable models respond in a natural way to the external or internal forces and constraints. Depending on the characteristics of force caused by a user through a haptic interface and model's intrinsic properties, the virtual elastic object in AR is deformed naturally. In the simulation, we exploit standard mass-spring damper differential equation so called Newton's second law of motion to model deformable objects. From the experiments, we can successfully visualize the behavior of a virtual objects in AR based on the theorem of physics when the haptic device interact with the rigid or non-rigid virtual object.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.4
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• pp.80-89
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• 2000

In this paper, we propose a new CPLD technology mapping algorithm for sequential circuit under time constraints. The algorithm detects feedbacks of sequential circuit, separate each feedback variables into immediate input variable, and represent combinational part into DAG. Also, among the nodes of the DAG, the nodes that the number of outdegree is more than or equal to 2 is not separated, but replicated from the DAG, and reconstructed to fanout-free-tree. To use this construction method is for reason that area is less consumed than the TEMPLA algorithm to implement circuits, and process time is improved rather than TMCPLD within given time constraint. Using time constraint and delay of device the number of partitionable multi-level is defined, the number of OR terms that the initial costs of each nodes is set to and total costs that the$^1$costs is set to after merging nodes is calculated, and the nodes that the number of OR terms of CLBs that construct CPLD is excessed is partitioned and is reconstructed as subgraphs. The nodes in the partitioned subgraphs is merged through collapsing, and the collapsed equations is performed by bin packing so that it fit to the number of OR terms in the CLBs of a given device. In the results of experiments to MCNC circuits for logic synthesis benchmark, we can shows that proposed technology mapping algorithm reduces the number of CLBs by 15.58% rather than the TEMPLA, and reduces process time rather than the TMCPLD.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.2
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• pp.253-262
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• 2010

This study aimed to evaluate the nutritional situation of pigs kept in three ecological zones of central Vietnam: Upland, Lowland and Coastal Area. An interview-based questionnaire was made and surveys were conducted in 27 villages and data were collected from 1,200 participating households. The current study showed that amounts of feed and crude protein content in the diets for fattening pigs and sows are deficient for all three regions. Amounts of feed as DM (kg/d) fed to growing pigs of 20-50 kg BW was deficient by 0.54 kg (29%) in Lowland, 0.53 kg (28.6%) in the Coastal area and 0.42 kg (22.4%) in Upland. The deficiency in CP in the diets of growing pigs in this period (20-50 kg) was largest at 20.7 g/d (62.1%) in Lowland, following by 22.1 g/d (66.4%) in Coastal and 23.2 g/d (69.7%) in Upland. Amount of feed as DM (kg/d) fed to growing pigs of 50-90 kg BW had a deficiency of 1.26 (48.9%), 1.25 (51.2%) and 1.14 (51.5%) kg/d in Lowland, Coastal and Upland, respectively. The deficiencies in crude protein in the growing diet during this period in Lowland, Coastal and Upland regions were 27 g/d (68.3%), 29 g/d (71.9%) and 30 g/d (74.6%), respectively. The deficiency in DM intake (kg/d) of pregnant sows in the Lowland area was 0.3 kg (15%), 0.33 kg (16%) in the Coastal area and 0.47 kg (23.5%) in the Upland area. Crude protein content in the diet of pregnant sows raised in Lowland was 8 g/d (32.0%) deficient, in the Coastal region the deficiency was 11 g/d (42.7%) and in Upland this deficiency was 15 g/d (61.2%). The deficiency in DM intake (kg/d) of lactating sows raised in Lowland was 1.47 kg (31.1%), in the Coastal area this was 1.69 kg (39.2%) and in Upland it was most deficient at 2.46 kg (57.1%). The lack of crude protein content in the diets of sows raised in Lowland was 45 g/d (63.4%), in the Coastal region it was 46 g/d (65%), and in Upland it was 55 g/d (78.9%). The low input of feed in these areas is especially due to low quality and to the insufficient intake of nutrients by the pig. As a result, production and income of farmers are low.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.271-278
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• 2014

In spite of that stop line and crosswalk should be aware of the most basic objects in transportation system, its features extracted are very limited. In addition to image-based recognition technology, laser and RF, GPS/INS recognition technology, it is difficult to recognize. For this reason, the limited research in this area has been done. In this paper, the algorithm to recognize the stop line and crosswalk is designed and implemented using image-based recognition technology with the images input through a vision sensor. This algorithm consists of three functions.; One is to select the area, in advance, needed for feature extraction in order to speed up the data processing, 'Region of Interest', another is to process the images only that white color is detected more than a certain proportion in order to remove the unnecessary operation, 'Color Pattern Inspection', the other is 'Feature Extraction and Recognition', which is to extract the edge features and compare this to the previously-modeled one to identify the stop line and crosswalk. For this, especially by using case based feature comparison algorithm, it can identify either both stop line and crosswalk exist or just one exists. Also the proposed algorithm is to develop existing researches by comparing and analysing effect of in-vehicle camera installation and changes in recognition rate of distance estimation and various constraints such as backlight and shadow.

• The Transactions of the Korea Information Processing Society
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• v.7 no.1
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• pp.224-234
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• 2000

In this paper, we propose a new CPLD technology mapping algorithm for sequential circuit under time constraints. The algorithm detects feedbacks of sequential circuit, separate each feedback variables into immediate input variable, and represent combinational part into DAG. Also, among the nodes of the DAG, the nodes that the number of outdegree is more than or equal to 2 is not separated, but replicated from the DAG, and reconstructed to fanout-free-tree. To use this construction method is for reason that area is less consumed than the TEMPLA algorithm to implement circuits, and process time is improved rather than TMCPLD within given time constraint. Using time constraint and delay of device the number of partitionable multi-level is defined, the number of OR terms that the initial costs of each nodes is set to and total costs that the costs is set to after merging nodes is calculated, and the nodes that the number of OR terms of CLBs that construct CPLD is excessed is partitioned and is reconstructed as subgraphs. The nodes in the partitioned subgraphs is merged through collapsing, and the collapsed equations is performed by bin packing so that if fit to the number of OR terms in the CLBs of a given device. In the results of experiments to MCNC circuits for logic synthesis benchmark, we can shows that proposed technology mapping algorithm reduces the number of CLBs bu 15.58% rather than the TEMPLA, and reduces process time rather than the TMCPLD.

• Journal of Korea Trade
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• v.26 no.2
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• pp.45-64
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• 2022

Purpose - This paper examines South Korea's potential status as a carbon leakage country, and the level of risk posed by the Korean emissions trading scheme (ETS) for Korean industries. The economic effects of border carbon adjustments (BCAs) to protect energy-intensive Korean industries in the process of achieving the carbon reduction target by 2030 through the Korean ETS are also analyzed. Design/methodology - First, using the Korean Input-Output (IO) table, this paper calculates the balance of emissions embodied in trade (BEET) and the pollution terms of trade (PTT) to determine Korean industries' carbon leakage status. Analyses of the risk level posed by carbon reduction policy implementation in international trade are conducted for some sectors by applying the EU criteria. Second, using a computable general equilibrium (CGE) model, three BCA scenarios, exemption regulations (EXE), reimbursement (REB), and tariff reduction (TAR) to protect the energy-intensive industries under the Korean ETS are addressed. Compared to the baseline scenario of achieving carbon reduction targets by 2030, the effects of BCAs on welfare, carbon leakage, outputs, and trading are analyzed. Findings - As Korea's industrial structure has been transitioning from a carbon importing to a carbon leaking country. The results indicate that some industrial sectors could face the risk of losing international competitiveness due to the Korean ETS. South Korea's industries are basically exposed to risk of carbon leakage because most industries have a trade intensity higher than 30%. This could be interpreted as disproving vulnerability to carbon leakage. Although the petroleum and coal sector is not in carbon leakage, according to BEET and PTT, the Korean ETS exposes this sector to a high risk of carbon leakage. Non-metallic minerals and iron and steel sectors are also exposed to a high risk of carbon leakage due to the increased burden of carbon reduction costs embodied in the Korean ETS, despite relatively low levels of trade intensity. BCAs are demonstrated to have an influential role in protecting energy-intensive industries while achieving the carbon reduction target by 2030. The EXE scenario has the greatest impact on mitigation of welfare losses and carbon leakage, and the TAF scenario causes a disturbance in the international trade market because of the pricing adjustment system. In reality, the EXE scenario, which implies completely exempting energy-intensive industries, could be difficult to implement due to various practical constraints, such as equity and reduction targets and other industries; therefore, the REB scenario presents the most realistic approach and appears to have an effect that could compensate for the burden of economic activities and emissions regulations in these industries. Originality/value - This paper confirms the vulnerability of the Korean industrial the risk of carbon leakage, demonstrating that some industrial sectors could be exposed to losing international competitiveness by implementing carbon reduction policies such as the Korean ETS. The contribution of this paper is the identification of proposed approaches to protect Korean industries in the process of achieving the 2030 reduction target by analyzing the effects of BCA scenarios using a CGE model.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.457-468
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• 2020

Problems arising during pile design works for plant construction, civil and architecture work are mostly come from uncertainty of geotechnical characteristics. In particular, obtaining the N-value measured through the Standard Penetration Test (SPT) is the most important data. However, it is difficult to obtain N-value by drilling investigation throughout the all target area. There are many constraints such as licensing, time, cost, equipment access and residential complaints etc. it is impossible to obtain geotechnical characteristics through drilling investigation within a short bidding period in overseas. The geotechnical characteristics at non-drilling investigation points are usually determined by the engineer's empirical judgment, which can leads to errors in pile design and quantity calculation causing construction delay and cost increase. It would be possible to overcome this problem if N-value could be predicted at the non-drilling investigation points using limited minimum drilling investigation data. This study was conducted to predicted the N-value using an Artificial Neural Network (ANN) which one of the Artificial intelligence (AI) method. An Artificial Neural Network treats a limited amount of geotechnical characteristics as a biological logic process, providing more reliable results for input variables. The purpose of this study is to predict N-value at the non-drilling investigation points through patterns which is studied by multi-layer perceptron and error back-propagation algorithms using the minimum geotechnical data. It has been reviewed the reliability of the values that predicted by AI method compared to the measured values, and we were able to confirm the high reliability as a result. To solving geotechnical uncertainty, we will perform sensitivity analysis of input variables to increase learning effect in next steps and it may need some technical update of program. We hope that our study will be helpful to design works in the future.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.149-161
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• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.152-161
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• 2023

In general, large-capacity hydrogen storage vessels, typically in the form of vertical cylindrical vessels, are constructed using steel materials. These vessels are anchored to foundation slabs that are specially designed to suit the environmental conditions. This anchoring method involves pre-installed anchors on top of the concrete foundation slab. However, it's important to note that such a design can result in concentrated stresses at the anchoring points when external forces, such as seismic events, are at play. This may lead to potential structural damage due to anchor and concrete damage. For this reason, in this study, it selected an vertical hydrogen storage vessel based on site observations and created a 3D finite element model. Artificial seismic motions made following the procedures specified in ICC-ES AC 156, as well as domestic recorded earthquakes with a magnitude greater than 5.0, were applied to analyze the structural behavior and performance of the target structures. Conducting experiments on a structure built to actual scale would be ideal, but due to practical constraints, it proved challenging to execute. Therefore, it opted for an analytical approach to assess the safety of the target structure. Regarding the structural response characteristics, the acceleration induced by seismic motion was observed to amplify by approximately ten times compared to the input seismic motions. Additionally, there was a tendency for a decrease in amplification as the response acceleration was transmitted to the point where the centre of gravity is located. For the vulnerable components, specifically the sub-system (support columns and anchorages), the stress levels were found to satisfy the allowable stress criteria. However, the concrete's tensile strength exhibited only about a 5% margin of safety compared to the allowable stress. This indicates the need for mitigation strategies in addressing these concerns. Based on the research findings presented in this paper, it is anticipated that predictable load information for the design of storage vessels required for future shaking table tests will be provided.