• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.1
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• pp.1-12
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• 2023

It is very time-intensive to obtain data with labels on anomaly detection tasks for multivariate time series. Therefore, several studies have been conducted on unsupervised learning that does not require any labels. However, a well-done integrative survey has not been conducted on in-depth discussion of learning architecture and property for multivariate time series anomaly detection. This study aims to explore the characteristic of well-known architectures in anomaly detection of multivariate time series. Additionally, architecture was categorized by using top-down and bottom-up approaches. In order toconsider real-world anomaly detection situation, we trained models with dataset such as power grids or Cyber Physical Systems that contains realistic anomalies. From experimental results, we compared and analyzed the comprehensive performance of each architecture. Quantitative performance were measured using precision, recall, and F1 scores.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.45-52
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• 2014

The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.

• Korean Journal of Construction Engineering and Management
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• v.16 no.1
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• pp.52-63
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• 2015

Business facilities among domestic architectures have rapidly been constructed along with domestic economic development. It is an important facility taking the second largest proportion next to apartment buildings among current 31 building types of fire department classification of 2012 year for urban architectures. The expected service life of business facilities is 15 years, but 70% of those in urban areas have surpassed the 15 year service life as of the present 2014. Thus, the demand for urgent rehabilitation of such facilities is constantly increasing due to the aging and performance deterioration of the facilities'main finishing materials. Especially, the business facilities are being used for the lease of company office or private office, and such problems as aging and performance deterioration of the facilities could cause less competitive edge for leasing and real estate value depreciation for the O&M (Operation & Management) agent and the owner, respectively. Therefore, an effective planned rehabilitation as a preventive measure according to the standardized repair rate by the number of years after the construction is in need in order to prevent the aging and performance deterioration of the facilities(La et al. 2001). Nonetheless, domestic repair/rehabilitation standards based on the repair rate are mainly limited to apartment buildings and pubic institutions, resulting in impractical application of such standards to business facilities. It has been investigated and analyzed that annual repair rate data for each finishing material are required for examination of the applicability of the repair rate standard for the purpose of establishment of a repair plan. Hence, this study aimed at developing a repair rate computation model for finishing materials of the facilities and verifying the appropriateness of the annual repair rate for each finishing material through a case study after collecting and analyzing the repair history data of six business facilities. The results of this study are expected to contribute to the planning and implementation of more efficient repair/rehabilitation budget by preventing the waste of unpredicted repair cost and opportunity cost for the sake of the business facilities' owners and O&M agents.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.36D no.5
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• pp.11-20
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• 1999

The data transfer width between the mocroprocessor and the memory comes to a critical part that limits system performance since the data transfer width has been as it was while the performance of a microprocessor is getting higher due to its continuous development in speed. And it is important that the memory should be in small size for the reduction of embedded microprocessor's price which is integrated on a single chip with the memory and IO circuit. In this paper, a mocroprocessor tentatively named as Extendable Instruction Set Computer(EISC) is proposed as the high code density 32 bit mocroprocessor architecture. The 32 bit EISC has 16 general purpose registers and 16 bit fixed length instruction which has the short length offset and small immediate operand. By using and extend register and extend flag, the offset and immediate operand could be extended. The proposed 32 bit EISC is implemented with an FPGA and all of its functions have been tested and verified at 1.8432MHz. And the cross assembler, the cross C/C++ compiler and the instruction simulator of the 32 bit EISC shows 140-220% and 120-140% higher code density than RISC and CISC respectively, which is much higher than any other traditional architectures. As a consequence, the EISC is suitable for the next generation computer architecture since it requires less data transfer width compared to any other ones. And its lower memory requirement will embedded microprocessor more useful.

• Journal of KIISE
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• v.42 no.4
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• pp.434-441
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• 2015

Next generation memory technologies, which we denote as 'new memory', have both non-volatile and byte addressable properties. These characteristics are expected to bring changes to the conventional computer system structure. In this paper, we propose a fast boot technique for hybrid main memory architectures that have both new memory and DRAM. The key technique used for fast booting is write-tracking. Write-tracking is used to detect and manage modified data detection and involves setting the kernel region to read-only. This setting is used to trigger intentional faults upon modification requests. As the fault handler can detect the faulting address, write-tracking makes use of the address to manage the modified data. In particular, in our case, we make use of the MMU (Memory Management Unit) translation table. When a write occurs to the boot completed state, write-tracking preserves the original state of the modified address of the kernel region to a particular location, and execution continues. Upon booting, the fast booting process restores the preserved data to the original kernel region allowing rapid system boot-up. We develop the fast booting technique in an actual embedded board equipped with new memory. The boot time is reduced to less than half a second compared to around 15 seconds that is required for the original system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.9
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• pp.828-840
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• 2014

There is a new evolution in technological advancement taking place called the Internet of Things (IoT). The IoT enables physical world objects in our surroundings to be connected to the Internet. For this idea to come to life, two architectures are required: the Sensing Entity in the environment which collects data and connects to the cloud and the Cloud Service that hosts the data. In particular, the combination of wireless sensor network for sensing and cloud computing for managing sensor data is becoming a popular intervention for the IoT era. The pharmaceutical cold chain requires controlled environmental conditions for the sensitive products in order for them to maintain their potency and fit for consumption. The monitoring of distribution process is the only assurance that a process has been successfully validated. The distribution process is so critical that anomaly at any point will result in the process being no longer valid. Taking the cold chain monitoring to IoT and using its benefits and power will result in better management and product handling in the cold chain. In this paper, Arduino based wireless sensor network for storage and logistics (land and sea) is presented and integrated with Xively cloud service to offer a real-time and innovative solution for pharmaceutical cold chain monitoring.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.6
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• pp.55-64
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• 2017

High-capacity, high-definition image applications need to process considerable amounts of data at high speed. Accordingly, users of these applications demand a high-speed parallel execution system. To increase the speed of a parallel execution system, Park (2004) proposed a technique, called MAMS (Multi-Access Memory System), to access data in several execution units without the conflict of parallel processing memories. Since then, many studies on MAMS have been conducted, furthering the technique to MAMS-PP16 and MAMS-PP64, among others. As a memory architecture for parallel processing, MAMS must be constructed in one chip; therefore, a method to achieve the identical functionality as the existing MAMS while minimizing the architecture needs to be studied. This study proposes a method of miniaturizing the MAMS architecture in which the architectures of the ACR (Address Calculation and Routing) circuit and MMS (Memory Module Selection) circuit, which deliver data in memories to parallel execution units (PEs), do not use the MMS circuit, but are constructed as one shift and conditional statements whose number is the same as that of memory modules inside the ACR circuit. To verify the performance of the realized architecture, the study conducted the processing time of the proposed MAMS-PP64 through an image correlation test, the results of which demonstrated that the ratio of the image correlation from the proposed architecture was improved by 1.05 on average.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.7-18
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• 2021

Recently, various connected industrial parks (CIPs) architectures using new technologies such as cloud computing, CPS, big data, fifth-generation mobile communication 5G, IIoT, VR-AR, and ventilation transportation AI algorithms have been proposed in Korea. Korea's small and medium-sized enterprises do not have the upper hand in technological competitiveness than overseas advanced countries such as the United States, Europe and Japan. For this reason, Korea's small and medium-sized enterprises have to invest a lot of money in technology research and development. As a latecomer, Korean SMEs need to improve their profitability in order to find sustainable growth potential. Financially, it is most efficient for small and medium-sized Korean companies to cut costs to increase their profitability. This paper made profitability improvement by reducing costs for small and medium-sized enterprises located in CIPs in Korea a major task. VJP (Vehicle Action Program) was noted as a way to reduce costs for small and medium-sized enterprises located in CIPs in Korea. The method of achieving minimum logistics costs for small businesses through the Korean CIPs payment system was analyzed. The details of the new Korean CIPs payment system were largely divided into four types: "Business", "Data", "Technique", and "Finance". Cost Benefit Analysis (CBA) was used as a performance analysis method for CIPs payment systems.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.38 no.1
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• pp.77-84
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• 2020

This study is apply 3D spatial information per traditional landscape space by comparing spatial information data created using a small drone and 3D scanner used for 3D spatial information construction for efficient preservation and management of traditional landscaping space composed of areas such as scenic sites and traditional landscape architectures. The analysis results are as follows. First, aerial photogrammetry data is less accurate than 3D scanners, but it was confirmed to be more suitable for monitoring landscape changes by reading RGB images than 3D scanners by texture mapping using digital data in constructing orthographic image data. Second, the orthographic image data constructed by aerial photogrammetry in a traditional landscaping space consisting of a fixed area, such as Gwanghalluwon Garden, produced visually accurate and precise results. However, as a result of the data extraction, data for trees, which is one of the elements that make up the traditional landscaping, was not extracted, so it was determined that 3D scanning and aerial surveying had to be performed in parallel, especially in areas where trees were densely populated. Third, The surrounding trees in Soswaewon Garden caused many errors in 3D spatial information data including topographic data. It was analyzed that it is preferable to use 3D scanning technology for precise measurement rather than aerial photogrammetry because buildings, landscaping facilities and trees are dense in a relatively small space. When 3D spatial information construction data for a traditional landscaping space composed of area using a small drone and a 3D scanner free from temporal and spatial constraints and compared the data was compared, the aerial photogrammetry is effective for large site such as Hahoe Village, Gyeongju and construction of a 3D space using a 3D scanner is effective for traditional garden such as Soswaewon Garden.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.4
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• pp.383-392
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• 2000

Currently, multiprocessors are evaluated almost exclusively with scientific applications. Commercial applications are rarely explored because it is difficult to obtain the source codes of commercial DBMS. Even when the source code is available, such as for POSTGRES, understanding the source code enough to perform detailed meaningful performance evaluations is a daunting task for computer architects.To evaluate multiprocessors with commercial applications, we have developed our own DBMS, called EZDB. EZDB is a parallelized DBMS, loosely inspired from POSTGRES, and running on top of a software architecture simulator. It is capable of executing parallel programs written in SQL. Contrary to POSTGRES, EZDB is not intended as a prototype for a production-quality DBMS. Its purpose is to easily run and evaluate the performance of commercial applications on multiprocessor architectures. To illustrate the usefulness of EZDB, we showed the cache performance data collected for the TPC-B benchmark on a shared-memory multiprocessor. The simulation results showed that the data structures exhibited unique sharing characteristics and that their locality properties and working sets were very different from those in scientific applications.