• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.81-86
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• 2022

Digital technologies in the regional sector of public administration are the basis for its reform and a potential example for the whole country on how to use the benefits of the "digital" world. The synergistic potential of social, mobile, "cloud" technologies, as well as data analysis technologies and the "Internet of Things" can collectively lead to transformational changes in public administration and in general, that is, make the use of digital technologies for the economic development of the region in the system of digitalization of public administration effective, reactive and valuable. Thus, the purpose of the study is to identify modern prospects and realities of the development of digital technologies for the economic development of the region in the system of digitalization of public administration. As a result of the study, the main mechanisms and systems of digital technologies for the economic development of the region in the system of digitalization of public administration were analyzed.

• SUVANNABHUMI
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• v.13 no.2
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• pp.167-186
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• 2021

The Grand Stupa is mentioned in historical text as 'Rajakudakan', which means a royal building with a multitiered superstructure. This Grand Stupa is the principal construction of Wat Chedi Luang, and marks the center of the Chiang Mai City Plan. This study argues that the Grand Stupa was built in 1391 during Phaya Saen Mueang Ma's reign, possibly inspired by the construction of Ku Phaya in Bagan. Thereafter, in 1545, the Grand Stupa's superstructure collapsed after the great earthquake, resulted in the irreparable damage since then. Therefore, a survey using a 3D laser scanner is conducted to collect the most precise data on the current condition of the Grand Stupa, yielding an assumption of its reconstruction. Other simultaneous stupas or those that show a close architectural relationship (e.g. stupas in Wat Chiang Man and Wat Lok Moli and the stupa of King Tilokaraj in Wat Chet Yot in Chiang Mai) are also employed as research frameworks for the reconstruction. As a result, the architectural research on the Grands Stupa, compared with simultaneous stupas, yields a fruitful argument that the pre-collapse superstructure form of the Grand Stupa marks the most architectural similarity to the stupa of Wat Chiang Man.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.20-25
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• 2022

This paper represents an adaptive Region of Interest (ROI) decision for real-time performance in an autonomous driving perception module. Since the whole automated driving system consists of numerous modules and subdivisions of module occur, it is necessary to consider the characteristics, complexity, and limitations of each module. Furthermore, Light Detection And Ranging (Lidar) sensors require a considerable amount of time. In view of these limitations, division of submodule is inevitable to represent high real-time performance for stable system. This paper proposes ROI to reduce the number of data respect to computation time. ROI is set by a road's design speed and the corresponding ROI is applied differently to each vehicle considering its speed. The simulation model is constructed by ROS, and overall data analysis is conducted by Matlab. The algorithm is validated using real-time driving data in urban environment, and the result shows that ROI provides low computational costs.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.163-171
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• 2023

The intelligent transportation system has made a huge leap in the level of human services, which has had a positive impact on the quality of life of users. On the other hand, these services are becoming a new source of risk due to the use of data collected from vehicles, on which intelligent systems rely to create automatic contextual adaptation. Most of the popular privacy protection methods, such as Dummy and obfuscation, cannot be used with many services because of their impact on the accuracy of the service provided itself, they depend on changing the number of vehicles or their physical locations. This research presents a new approach based on the shuffling Nicknames of vehicles. It fully maintains the quality of the service and prevents tracking users permanently, penetrating their privacy, revealing their whereabouts, or discovering additional details about the nature of their behavior and movements. Our approach is based on creating a central Nicknames Pool in the cloud as well as distributed subpools in fog nodes to avoid intelligent delays and overloading of the central architecture. Finally, we will prove by simulation and discussion by examples the superiority of the proposed approach and its ability to adapt to new services and provide an effective level of protection. In the comparison, we will rely on the wellknown privacy criteria: Entropy, Ubiquity, and Performance.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.528-529
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• 2023

Due to vast points and irregular structure, labeling full points in large-scale point clouds is highly tedious and time-consuming. To resolve this issue, we propose a novel point-based transformer network in weakly-supervised semantic segmentation, which only needs 0.1% point annotations. Our network introduces general local features, representing global factors from different neighborhoods based on their order positions. Then, we share query point weights to local features through point attention to reinforce impacts, which are essential in determining sparse point labels. Geometric encoding is introduced to balance query point impact and remind point position during training. As a result, one point in specific local areas can obtain global features from corresponding ones in other neighborhoods and reinforce from its query points. Experimental results on benchmark large-scale point clouds demonstrate our proposed network's state-of-the-art performance.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.89-108
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• 2023

This study provides a comprehensive analysis of recent studies conducted on the topic of nowcasting in order to enhance the accuracy and promptness of official statistical data. Furthermore, we propose an alternative approach involving the utilization of real-time data and its corresponding collection methods to effectively operate a real-time nowcasting model capable of accurately capturing the current economic condition. We explore high-frequency real-time data that can predict economic indicators in both the public and private sectors and propose a pipeline for data collection processing and modeling that is based on cloud platforms. Furthermore we validate the essential elements required for the implementation of real-time nowcasting, as well as their data management protocols to ensure the reliability and consistency needed for accurate forecasting of official statistical indicators.

• Journal of Distribution Science
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• v.22 no.2
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• pp.21-30
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• 2024

Purpose: This study explores the development of zakat distribution studies and the integration of existing studies. This study is expected to complement a systematic literature review in the field of zakat distribution to inspire further research directions. Research design, data, and methodology: This research method uses a systematic literature review assisted by the Nvivo application and the PRISMA system, which selects from 427 articles to 53 articles to be analyzed based on publication and classification of the theme of its findings. This study describes publications, authors, themes, cited articles, and research themes. Results: This study shows the dominance of Malaysian writers and significant developments in 2020. In addition, the study shows the most popular articles based on the most citations and word cloud analysis. The primary topics of zakat distribution publications are management strategy, development, the zakat institution, and the recipient. Conclusions: The study advises that Future research could focus on zakat distribution's asnaf characteristics. Next, a study on administration expenses and scalability concerns in zakat collection and distribution planning can avoid wasting cash. This topic hinders zakat institutions' distribution services.

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.243-255
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• 2024

This study compares Static Terrestrial Laser Scanning (STLS)with the conventional Total Station (TS) method for the geometric assessment of cylindrical storage tanks. With the crucial need for maintaining tank integrity in the oil and gas industry, STLS and TS methods are evaluated for their efficacy in assessing tank deformations. Using STLS and TS, the roundness and verticality of two cylindrical tanks were examined. A deformation analysis based on American Petroleum Institute (API) standards was then provided. Key objectives included comparing the two methods according to API standards, evaluating the workflow for STLS point cloud processing, and presenting the pros and cons of the STLS method for tank geometric assessment. The study found that STLS, with its detailed and high-resolution data acquisition, offers a substantial advantage in having a comprehensive structural assessment over TS. However, STLS requires more processing time and prior knowledge about the data to tune certain parameters and achieve accurate assessment. The project outcomes intend to enhance industry professionals' understanding of applying STLS and TS to tank assessments, helping them choose the best method for their specific requirements.

• Journal of Platform Technology
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• v.12 no.1
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• pp.77-84
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• 2024

With the recent increase in the use of artificial intelligence, AI TRiSM data management within organizations has become important, and thus securing data reliability has emerged as an essential requirement for data-based decision-making. Digital content is transmitted through the unreliable Internet to the cloud where the digital content storage is located, then used in various applications. When detecting anomaly of data, it is difficult to provide a function to check content modification due to its damage in digital content systems. In this paper, we design a technique to guarantee the reliability of video data by expanding the function of data annotation. The designed annotation technique constitutes a prototype based on gRPC to handle a request and a response in a webUI that generates classification label and Merkle tree of given video data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.10
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• pp.920-927
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• 2013

Chroma key technique which composes images by separating an object from its background in specific color has restrictions on color and space. Especially, unlike general chroma key technique, image composition for stereo 3D display requires natural image composition method in 3D space. The thesis attempted to compose images in 3D space using depth keying method which uses high resolution depth information. High resolution depth map was obtained through camera calibration between the DSLR and Kinect sensor. 3D mesh model was created by the high resolution depth information and mapped with RGB color value. Object was converted into point cloud type in 3D space after separating it from its background according to depth information. The image in which 3D virtual background and object are composed obtained and played stereo 3D images using a virtual camera.