• Journal of Information Processing Systems
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• v.8 no.2
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• pp.347-358
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• 2012

Recently, security researches have been processed on the method to cover a broader range of hacking attacks at the low level in the perspective of hardware. This system security applies not only to individuals' computer systems but also to cloud environments. "Cloud" concerns operations on the web. Therefore it is exposed to a lot of risks and the security of its spaces where data is stored is vulnerable. Accordingly, in order to reduce threat factors to security, the TCG proposed a highly reliable platform based on a semiconductor-chip, the TPM. However, there have been no technologies up to date that enables a real-time visual monitoring of the security status of a PC that is operated based on the TPM. And the TPB has provided the function in a visual method to monitor system status and resources only for the system behavior of a single host. Therefore, this paper will propose a m-TMS (Mobile Trusted Monitoring System) that monitors the trusted state of a computing environment in which a TPM chip-based TPB is mounted and the current status of its system resources in a mobile device environment resulting from the development of network service technology. The m-TMS is provided to users so that system resources of CPU, RAM, and process, which are the monitoring objects in a computer system, may be monitored. Moreover, converting and detouring single entities like a PC or target addresses, which are attack pattern methods that pose a threat to the computer system security, are combined. The branch instruction trace function is monitored using a BiT Profiling tool through which processes attacked or those suspected of being attacked may be traced, thereby enabling users to actively respond.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2443-2450
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• 2014

In the motion recognition system using depth image, the depth image is converted to the real world formed 3D point cloud data for efficient algorithm apply. And then, output depth image is converted by the projective world after algorithm apply. However, when coordinate conversion, rounding error and data loss by applied algorithm are occurred. In this paper, when convert 3D point cloud data to depth image, we proposed efficient conversion method and its hardware implementation without rounding error and data loss according image size change. The proposed system make progress using the OpenCV and the window program, and we test a system using the Kinect in real time. In addition, designed using Verilog-HDL and verified through the Zynq-7000 FPGA Board of Xilinx.

• Asia pacific journal of information systems
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• v.34 no.1
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• pp.150-190
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• 2024

This article proposes a framework to elucidate the structural dynamics of the generative AI ecosystem. It also outlines the practical application of this proposed framework through illustrative policies, with a specific emphasis on the development of the Korean generative AI ecosystem and its implications of platform strategies at AI platform-squared. We propose a comprehensive classification scheme within generative AI ecosystems, including app builders, technology partners, app stores, foundational AI models operating as operating systems, cloud services, and chip manufacturers. The market competitiveness for both app builders and technology partners will be highly contingent on their ability to effectively navigate the customer decision journey (CDJ) while offering localized services that fill the gaps left by foundational models. The strategically important platform of platforms in the generative AI ecosystem (i.e., AI platform-squared) is constituted by app stores, foundational AIs as operating systems, and cloud services. A few companies, primarily in the U.S. and China, are projected to dominate this AI platform squared, and consequently, they are likely to become the primary targets of non-market strategies by diverse governments and communities. Korea still has chances in AI platform-squared, but the window of opportunities is narrowing. A cautious approach is necessary when considering potential regulations for domestic large AI models and platforms. Hastily importing foreign regulatory frameworks and non-market strategies, such as those from Europe, could overlook the essential hierarchical structure that our framework underscores. Our study suggests a clear strategic pathway for Korea to emerge as a generative AI powerhouse. As one of the few countries boasting significant companies within the foundational AI models (which need to collaborate with each other) and chip manufacturing sectors, it is vital for Korea to leverage its unique position and strategically penetrate the platform-squared segment-app stores, operating systems, and cloud services. Given the potential network effects and winner-takes-all dynamics in AI platform-squared, this endeavor is of immediate urgency. To facilitate this transition, it is recommended that the government implement promotional policies that strategically nurture these AI platform-squared, rather than restrict them through regulations and stakeholder pressures.

• Advances in robotics research
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• v.1 no.2
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• pp.127-140
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• 2014

This work presents an IR-based system for parking assistance and obstacle detection in the automotive field that employs the Microsoft Kinect camera for fast 3D point cloud reconstruction. In contrast to previous research that attempts to explicitly identify obstacles, the proposed system aims to detect "reachable regions" of the environment, i.e., those regions where the vehicle can drive to from its current position. A user-friendly 2D traversability grid of cells is generated and used as a visual aid for parking assistance. Given a raw 3D point cloud, first each point is mapped into individual cells, then, the elevation information is used within a graph-based algorithm to label a given cell as traversable or non-traversable. Following this rationale, positive and negative obstacles, as well as unknown regions can be implicitly detected. Additionally, no flat-world assumption is required. Experimental results, obtained from the system in typical parking scenarios, are presented showing its effectiveness for scene interpretation and detection of several types of obstacle.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.1
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• pp.87.1-87.1
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• 2010

Main-belt comets (hereafter MBCs) are one of the hottest topics in the solar system astronomy. They are objects orbiting in the main asteroid belt which show cometary activity. Unlike most comets, which spend most of their orbit beyond 5AU from the Sun, MBCs follow near-circular orbits within the asteroid belt that are indistinguishable from the orbits of major population of the asteroids. P/2010 A2, the fifth MBC, was discovered by on January 6, 2010 by Lincoln Near-Earth Asteroid Research. It passed its perihelion at 2.01AU on December 3, 2009, about a month before it was discovered. With an aphelion of only 2.6 AU, P/2010 A2 spends all of its time inside of the frostline ~2.7 AU. We made observations of P/2010 A2 with Nishi-Harima Astronomical Observatory 2-m telescope only a week after the discovery. From the observed images, we found that the dust cloud was composed of large particles (>1mm) impulsively ejected between March and June, 2009. No coma was detected by our observations, suggesting that this object was no longer active. Consequently, we conjecture that these dust particles could be released by the impact collision among asteroids.

• Genomics & Informatics
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• v.16 no.4
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• pp.24.1-24.4
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• 2018

Taxonomic identification is fundamental to all microbiology studies. Particularly in metagenomics, which identifies the composition of microorganisms using thousands of sequences, its importance is even greater. Identification is inevitably affected by the choice of database. This study was conducted to evaluate the accuracy of three widely used 16S databases-Greengenes, Silva, and EzBioCloud-and to suggest basic guidelines for selecting reference databases. Using public mock community data, each database was used to assign taxonomy and to test its accuracy. We show that EzBioCloud performs well compared with other existing databases.

• Journal of KIISE
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• v.41 no.9
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• pp.674-685
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• 2014

The Knowledge service system needs to infer a new knowledge from indicated knowledge to provide its effective service. Most of the Knowledge service system is expressed in terms of ontology. The volume of knowledge information in a real world is getting massive, so effective technique for massive data of ontology is drawing attention. This paper is to provide the method to infer massive data-ontology to the extent of RDFS, based on cloud computing environment, and evaluate its capability. RDFS inference suggested in this paper is focused on both the method applying MapReduce based on RDFS meta table, and the method of single use of cloud computing memory without using MapReduce under distributed file computing environment. Therefore, this paper explains basically the inference system structure of each technique, the meta table set-up according to RDFS inference rule, and the algorithm of inference strategy. In order to evaluate suggested method in this paper, we perform experiment with LUBM set which is formal data to evaluate ontology inference and search speed. In case LUBM6000, the RDFS inference technique based on meta table had required 13.75 minutes(inferring 1,042 triples per second) to conduct total inference, whereas the method applying the cloud computing memory had needed 7.24 minutes(inferring 1,979 triples per second) showing its speed twice faster.

• Journal of Korean Society of Archives and Records Management
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• v.19 no.3
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• pp.271-292
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• 2019

Recently, the central administrative agency changed its business management system to cloud-based On-nara 2.0. To transfer and manage the records of the cloud business management system, the National Archives Service has developed and distributed a cloud-based records management system. It serves as an opportunity to maximize the benefits of cloud computing and redesign the records management to be more effective and efficient. The process and method of electronic record management can be transformed through digital technologies. First, we can change the transfer method for electronic records. When the business and the records management systems share the same cloud storage, it is possible to transfer the content files between the two systems without moving the contents files physically, thus copying only the metadata and reducing the cost and the risk of integrity damage. Second, the strategy for allocating storage space for contents can be conceived. Assuming that the cloud storage is shared by the business and the record management systems, it is advantageous to distinguish the storage location based on the retention period of the content files. Third, systems that access content files, such as records creation, records management, and information disclosure systems, can share the cloud storage and minimize the duplication of content files.

• The Transactions of the Korea Information Processing Society
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• v.13 no.7
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• pp.291-298
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• 2024

Despite its wide application, cloud computing raises privacy leakage concerns because users should send their private data to the cloud. Homomorphic encryption (HE) can resolve the concerns by allowing cloud servers to compute on encrypted data without decryption. However, due to the huge computation overhead of HE, simply executing an entire cloud program with HE causes significant computation. Manually partitioning the program and applying HE only to the partitioned program for the cloud can reduce the computation overhead. However, the manual code partitioning and HE-transformation are time-consuming and error-prone. This work proposes a new homomorphic encryption enabled annotation-guided code partitioning compiler, called Heapa, for privacy preserving cloud computing. Heapa allows programmers to annotate a program about the code region for cloud computing. Then, Heapa analyzes the annotated program, makes a partition plan with a variable list that requires communication and encryption, and generates a homomorphic encryptionenabled partitioned programs. Moreover, Heapa provides not only two region-level partitioning annotations, but also two instruction-level annotations, thus enabling a fine-grained partitioning and achieving better performance. For six machine learning and deep learning applications, Heapa achieves a 3.61 times geomean performance speedup compared to the non-partitioned cloud computing scheme.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.237-248
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• 2018

The vertical distribution of hydrometeor before precipitation near the cloud base has been analyzed using a scanning lidar, rawinsonde data, and Cloud-Resolving Storm Simulator (CReSS). This study mostly focuses on 13 Desember 2016 only. The typical synoptic pattern of lake-effect snowstorm induced easterly in the Yeongdong region. Clouds generated due to high temperature difference between 850 hPa and sea surface (SST) penentrated in the Yeongdong region along with northerly and northeasterly, which eventually resulted precipitation. The cloud base height before the precipitation changed from 750 m to 1,280 m, which was in agreement with that from ceilometer at Sokcho. However, ceilometer tended to detect the cloud base 50 m ~ 100 m below strong signal of lidar backscattering coefficient. As a result, the depolarization ratio increased vertically while the backscattering coefficient decreased about 1,010 m~1,200 m above the ground. Lidar signal might be interpreted to be attenuated with the penetration depth of the cloud layer with of nonspherical hydrometeor (snow, ice cloud). An increase in backscattering signal and a decrease in depolarization ratio occured in the layer of 800 to 1,010 m, probably being associated with an increase in non-spherical particles. There seemed to be a shallow liquid layer with a low depolarization ratio (<0.1) in the layer of 850~900 m. As the altitude increases in the 680 m~850 m, the backscattering coefficient and depolarization ratio increase at the same time. In this range of height, the maximum value (0.6) is displayed. Such a result can be inferred that the nonspherical hydrometeor are distributed by a low density. At this time, the depolarization ratio and the backscattering coefficient did not increase under observed melting layer of 680 m. The lidar has a disadvantage that it is difficult for its beam to penetrate deep into clouds due to attenuation problem. However it is promising to distinguish hydrometeor morphology by utilizing the depolarization ratio and the backscattering coefficient, since its vertical high resolution (2.5 m) enable us to analyze detailed cloud microphysics. It would contribute to understanding cloud microphysics of cold clouds and snowfall when remote sensings including lidar, radar, and in-situ measurements could be timely utilized altogether.