• International conference on construction engineering and project management
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• 2015.10a
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• pp.680-681
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• 2015

This study develops an algorithm that automatically performs reverse engineering on three-dimensional (3D) sweeping shapes using a user's pre-defined feature templates and 3D point cloud data (PCD) of sweeping shapes. Existing methods extract 3D sweeping shapes by extracting points on a PCD cross section together with the center point in order to perform curve fitting and connect the center points. However, a drawback of existing methods is the difficulty of creating a 3D sweeping shape in which the user's preferred feature center points and parameters are applied. This study extracts shape features from cross-sectional points extracted automatically from the PCD and compared with pre-defined feature templates for similarities, thereby acquiring the most similar template cross-section. Fitting the most similar template cross-section to sweeping shape modeling makes the reverse engineering process automatic.

• ETRI Journal
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• v.46 no.3
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• pp.473-484
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• 2024

We introduce a machine learning-based web application to help travel agents plan a package tour schedule. K-nearest neighbor (KNN) classification predicts the optimal tourists' dwelling time based on a variety of information to automatically generate a convenient tour schedule. A database collected in collaboration with an established travel agency is fed into the KNN algorithm implemented in the Python language, and the predicted dwelling times are sent to the web application via a RESTful application programming interface provided by the Flask framework. The web application displays a page in which the agents can configure the initial data and predict the optimal dwelling time and automatically update the tour schedule. After conducting a performance evaluation by simulating a scenario on a computer running the Windows operating system, the average response time was 1.762 s, and the prediction consistency was 100% over 100 iterations.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.185-199
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• 2024

In this paper, an improved automated spectral clustering (IASC) algorithm is proposed to address the limitations of the traditional spectral clustering (TSC) algorithm, particularly its inability to automatically determine the number of clusters. Firstly, a cluster number evaluation factor based on the optimal clustering principle is proposed. By iterating through different k values, the value corresponding to the largest evaluation factor was selected as the first-rank number of clusters. Secondly, the IASC algorithm adopts a density-sensitive distance to measure the similarity between the sample points. This rendered a high similarity to the data distributed in the same high-density area. Thirdly, to improve clustering accuracy, the IASC algorithm uses the cosine angle classification method instead of K-means to classify the eigenvectors. Six algorithms-K-means, fuzzy C-means, TSC, EIGENGAP, DBSCAN, and density peak-were compared with the proposed algorithm on six datasets. The results show that the IASC algorithm not only automatically determines the number of clusters but also obtains better clustering accuracy on both synthetic and UCI datasets.

• Journal of Information Technology Applications and Management
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• v.29 no.5
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• pp.27-37
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• 2022

This study intends to link agricultural machine history data with related organizations or collect them through IoT sensors, receive input from agricultural machine users and managers, and analyze them through AI algorithms. Through this, the goal is to track and manage the history data throughout all stages of production, purchase, operation, and disposal of agricultural machinery. First, LSTM (Long Short-Term Memory) is used to estimate oil consumption and recommend maintenance from historical data of agricultural machines such as tractors and combines, and C-LSTM (Convolution Long Short-Term Memory) is used to diagnose and determine failures. Memory) to build a deep learning algorithm. Second, in order to collect historical data of agricultural machinery, IoT sensors including GPS module, gyro sensor, acceleration sensor, and temperature and humidity sensor are attached to agricultural machinery to automatically collect data. Third, event-type data such as agricultural machine production, purchase, and disposal are automatically collected from related organizations to design an interface that can integrate the entire life cycle history data and collect data through this.

• 한국전기화학회:학술대회논문집
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• 2000.04a
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• pp.61-61
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• 2000

• Journal of Korea Game Society
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• v.16 no.5
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• pp.99-110
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• 2016

This paper proposes the adaptive way that intended screen applies the same proportion of the game screen to mobile devices having various resolution. Generally speaking, clipping is the way to show only part of screen with designated proportion and is widely used in game industry. It costs additionally because developers make game screens fit various resolutions. However, the proposed method of this study saves developing time and cost if automatically calculated output is possible according to designated screen proportion and devices' aspect ratio. This suggested algorithm makes it possible to display game screen in same proportion automatically to various resolution and the mini-map is automatically fixed regardless of the mobile devices' resolution.

• Journal of Digital Contents Society
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• v.16 no.4
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• pp.615-622
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• 2015

Recently virtual advertising is located in an important area of interest in the TV market by convenience of application and reduction of cost. The methods of inserting a virtual advertising in broadcasting are Up-link that method insert the image through the production equipment of the broadcasting station and dispatch equipment and technical personnel in the shooting and Down-streaming that method insert a virtual image automatically in relay video using image processing technology. In recent years, the image processing technology is an important research area in the virtual advertising area for automatically insertion of advertising images. In this paper, we propose the method to extract less-informative region in sports video using image processing. The proposed method extracts less-Informative region through rectangle detection of Hough transform and analysis of color histogram distribution.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.10
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• pp.1175-1182
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• 2015

This paper has been an era of full-fledged objects Internet of Things(IoT), which involved the subject of this communication in the communication paradigm of the human heart. Things Arduino-based appliances ON, the system was implemented using the smartphone alarm in the Internet environment. All appliances even if plug connected to an external power source only standby power is present. This system is used for communication with the Arduino things. Connect the appliances power automatically rings the smartphone alarm minimize appliances standby power to things all by ON automatically connected to the Arduino, and the work of giving consumer electronics devices to help weather that automatically operates by Objects is an Internet system.

• Journal of the Korea Convergence Society
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• v.11 no.6
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• pp.29-36
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• 2020

As the Ministry of Education adds an item to evaluate whether a university strictly manages class time compliance and student attendance, the number of cases in which universities use electronic attendance systems is increasing. If you use the electronic attendance system, you can manage attendance and record management in real time. In this paper, I would like to suggest a solution to the prevention of cheating, which is a problem with the existing electronic attendance system. In this paper, automatic attendance is possible by automatic or correction. If the electronic attendance is performed manually, the BLE beacon service of the professor's smartphone is activated, and then the student's electronic attendance application is automatically executed using the push message service. When the student clicks the attendance check button and the beacon is found, attendance is processed. In the case of automatic processing, the beacon is automatically searched and attendance is handled even if the student is not involved. The proposed system automatically handles attendance even when the student does not recognize it, and has the advantage of preventing illegal attendance because it can reconfirm attendance at unspecified intervals.

• Journal of KIISE:Software and Applications
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• v.36 no.9
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• pp.697-705
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• 2009

A GUI automated test can be divided into two areas. The first one is a regression test automation and the second one is an automated test. The former includes generating test cases manually and executing them automatically but the latter includes both generating test cases and executing them automatically. Costs of a software test are increasing more and more. Many companies are searching for a test automation method but most used things are limited to regression test automation. So, when testing at first, there should be test cases which are drawn up by a human. This paper explains to make test cases based on a source code and execute them automatically. In this paper, the study proceeds with a digital television set-top box application and explains to test without any effort of human. Of course, this study is far from a realization to industries. But this paper has a contribution at reducing more human efforts than the previous regression test automation and showing that later, fully automated test can be possible.