• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.235-242
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• 2002

We propose an advanced transaction scheduling protocol for concurrency control of multilevel secure databases in wireless mobile network environment. Wireless communication is characterized by frequent spurious disconnections. So short-lived transaction must quickly access database without any delay by long-lived one. We adapted two-phase locking protocol, namely traditional syntax-oriented serializability notions, to multilevel secure databases in wireless mobile network environment. Altruistic locking, as an advanced protocol, has attempted to reduce delay effect associated with lock release moment by use of the idea of donation. An improved form of a1truism has also been deployed for extended a1truistic locking. This is in a way that scope of data to he early released is enlarged to include even data initially not intended to be donated. Our protocol is based on extended altruistic locking, but a new method, namely bi-directional donation locking for multilevel secure databases (MLBiDL), is additionally used in order to satisfy security requirements and concurrency. We showed the Simulation experiments that MLBiDL outperforms the other locking protocols in terms of the degree of throughput and average waiting time.

• Journal of Animal Environmental Science
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• v.8 no.3
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• pp.199-208
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• 2002

This paper introduces the method to make management network about milking cow farm tasks. The object of this research was to design of biological measuring system and managing network system in a livestock farm. This auto-management system provides informations about individual cows' temperature, conductivity of milk and weight for efficient management of feeding, and milking works by a micro-processor and RS -485 type serial COM. ports. And measured bio-data which are basic informations for remote raising management are saved to user PC by serial communication between the PLC and user PC. Milking cow farm is divided into three working place to each measurement work and feed. The first working place is milking station which has two thermometers, a conduct meter and a scale set. The second working place is feeding station, and the third place is cattle cage. These are combined by network system and the PLC which is used to drive network and sub-modules. Sub-modules have a micro-process to control the sensor and to interface with network. The PLC which drive network and control sequence has two serial communication port to be linked with user PC for sending the measured data and for receiving data. Above all, in this study tells the sequence operating method by the driving scenario of breeding milk cow for livestock auto-management using the PLC and network system.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.9
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• pp.219-226
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• 2018

One of the systematic ways to generate the number of all cases is a combination to construct a combination tree, and its time complexity is O($2^n$). A combination tree is used for various purposes such as the graph homogeneity problem, the initial model for calculating frequent item sets, and so on. However, algorithms that must search the number of all cases of a combination are difficult to use realistically due to high time complexity. Nevertheless, as the amount of data becomes large and various studies are being carried out to utilize the data, the number of cases of searching all cases is increasing. Recently, as the GPU environment becomes popular and can be easily accessed, various attempts have been made to reduce time by parallelizing algorithms having high time complexity in a serial environment. Because the method of generating the number of all cases in combination is sequential and the size of sub-task is biased, it is not suitable for parallel implementation. The efficiency of parallel algorithms can be maximized when all threads have tasks with similar size. In this paper, we propose a method to efficiently collaborate between CPU and GPU to parallelize the problem of finding the number of all cases. In order to evaluate the performance of the proposed algorithm, we analyze the time complexity in the theoretical aspect, and compare the experimental time of the proposed algorithm with other algorithms in CPU and GPU environment. Experimental results show that the proposed CPU and GPU collaboration algorithm maintains a balance between the execution time of the CPU and GPU compared to the previous algorithms, and the execution time is improved remarkable as the number of elements increases.

• Journal of the Korean Society of Radiology
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• v.12 no.6
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• pp.785-791
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• 2018

Recently, Disk array is widely used as a long term storage device in PACS, but reliability is not enough in relation to annual failure rate of disk. Between October 2016 and February 2017, we scanned the serial port of the hard disk while reading or storing medical images on a PACS reader. The data rate was calculated from the data stored in HDD 99ea that were used in the PCAS image storage device and in HDD 101ea that were used in the Personal Computer. When a CT image was read from a PACS reader, Reading was 87.8% and Writing was 12.2% in units of several tens of megabytes or less. When the CT image was stored in the PACS reader, Reading was 11.4% and Writing was 88.6% in units of several tens of megabytes or less. While reading the excel file on the personal computer, Reading was 75% and Writing was 25% in less than 3 MB, and In the process of storing the excel file on the personal computer, Reading was carried out by 38% and Writing was carreid out 62% in the units of 3 MB or less. The transfer rate of the hard disk used in the PACS image storage device was 10 GB/h, and the transfer rate per hour of the hard disk of the personal computer was 5 GB / h. Annual failure rate of hard disk of image storage system is 0.97 ~ 1.13%, Annual failure rate of Hard Disk of personal computer is 0.97 ~ 1.13%. the higher transfer rate is, the higher annual failure rate is. These results will be used as a basis for predicting the life expectancy of the hard disk and the annual failure rate.