• KIISE Transactions on Computing Practices
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• v.24 no.3
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• pp.129-137
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• 2018

NVMe(Non-Volatile Memory Express) SSD(Solid State Drive) is a high-performance storage that makes use of flash memory as a storage cell, PCIe as an interface and NVMe as a protocol on the interface. It supports multiple I/O queues which makes it feasible to process parallel-I/Os on multi-core environments and to provide higher bandwidth than SATA SSDs. Hence, NVMe SSD is considered as a next generation-storage for data-center and cloud computing system. However, in the virtualization system, the performance of NVMe SSD is not fully utilized due to the bottleneck of the software I/O stack. Especially, when it uses I/O stack of the hypervisor or the host operating system like Xen and KVM, I/O performance degrades seriously due to doubled-I/O stack between host and virtual machine. In this paper, we propose a new I/O engine, called Direct-AIO (Direct-Asynchronous I/O) engine, that can access NVMe SSD directly for I/O performance improvements on QEMU emulator. We develop our proposed I/O engine and analyze I/O performance differences between the existed I/O engine and Direct-AIO engine.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.350-354
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• 2009

To optimize the performance of software programs, it is important to know certain hardware parameters such as the CPU speed, the cache size, the number of TLB entries, and the parameters of the memory subsystem. There exist several ways to obtain the values of various hardware parameters. Firstly. the values can be taken from the hardware manual. Secondly, the parameters can be obtained by calling functions provided by the operating systems. Finally, hardware detection programs can find the desired values. Such programs are usually executed on PC or server systems and report the CPU speed, the cache size, the number of TLB entries, and so on. However, they do not sufficiently detect the parameters of one of the most important parts of the computer concerning performance, namely the memory bank layout in the memory subsystem. In this paper, we present an algorithm to detect the memory bank parameters. We run an implementation of our algorithm on various embedded systems and compare the detected values with the real hardware parameters. The results show that the presented algorithm detects the cache size, the number of TLB entries, and the memory bank layout with high accuracy.

• KIISE Transactions on Computing Practices
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• v.20 no.9
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• pp.519-524
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• 2014

The operating systems in the system architecture, which is integrated several applications and modular electronic devices in the same computing device, demand partitioning technology for safety. Thus, operation system requires partition scheduler for partition scheduling. When we design partition scheduler in embedded system, which has small memory and low performance, such as space system, we must consider not only performance but also memory. In this paper, we introduces a linux-based memory efficient partition scheduler using partition bitmap. This partition scheduler demands small memory space and produce low partition switching overhead. The prototype was executed on a LEON4 processor, which is the Next Generation Multicore Processor (NGMP) in the space sector. In evaluation, this prototype shows accuracy, additional memory space and low partition switching overhead.

• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.677-684
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• 2014

The purpose of this study, due to recent increase of digital outdoor media, is to analyze the consumer experience of interaction with digital media. Through this study it was found that experience factor consisting of cognitive, emotional, and interactional factors has a mediating effect on brand preference and brand reliability which in turn influence consumers' purchasing intention. On the other hand, it was verified that the consumer satisfaction of the experience does not directly influence purchasing intention, but only through the mediation of brand reliability. This research has implications on the academic field as well as in work-level practices, as a study based on an actual operating digital media, not a laboratory simulation that verifies the importance of digital media experience in forming brand equity through immediate influence on brand preference and brand reliability.

• Korean Journal of Veterinary Research
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• v.55 no.2
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• pp.97-103
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• 2015

In this study, the Korean veterinary medical devices management system was evaluated relative to systems in the USA, EU, and Japan. Veterinary medical devices are regulated in Korea based on the Medical Appliance Act of 1997. This was initially supervised by the Ministry of Agriculture, Food and Rural Affairs and Korea Animal Health Products Association, and subsequently by the Animal and Plant Quarantine Agency (QIA) in 2000. These devices were classified approximately 1,400 categories as instruments, supplies, artificial insemination apparatus, and other categories. Each of these devices was assigned to four regulatory grades by the QIA in 2007. The ranking system for veterinary medical devices was implemented in 2014 with 820 products from 162 companies registered by that year. However, in vitro diagnostic devices (IVDDs) for animals were managed as medical devices and biological medicine. In vitro diagnostic reagents for treating infection diseases are not subjected to either a classification or grading system. Veterinary medical devices are currently exempt from good manufacturing practices (GMP) and device tracking requirements. Due to gradual growth of the domestic veterinary medical devices market since 2008, regulation of these devices should be improved with re-examination of IVDDs and GMP certification for the effective operating system.

• Nutrition Research and Practice
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• v.6 no.4
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• pp.366-374
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• 2012

In order to create a worker-friendly environment for institutional foodservice, facilities operating with a dry kitchen system have been recommended. This study was designed to compare the work safety and work environment of foodservice between wet and dry kitchen systems. Data were obtained using questionnaires with a target group of 303 staff at 57 foodservice operations. Dry kitchen facilities were constructed after 2006, which had a higher construction cost and more finishing floors with anti-slip tiles, and in which employees more wore non-slip footwear than wet kitchen (76.7%). The kitchen temperature and muscular pain were the most frequently reported employees' discomfort factors in the two systems, and, in the wet kitchen, "noise of kitchen" was also frequently reported as a discomfort. Dietitian and employees rated the less slippery and slip related incidents in dry kitchens than those of wet kitchen. Fryer area, ware-washing area, and plate waste table were the slippery areas and the causes were different between the functional areas. The risk for current leakage was rated significantly higher in wet kitchens by dietitians. In addition, the ware-washing area was found to be where employees felt the highest risk of electrical shock. Muscular pain (72.2%), arthritis (39.1%), hard-of-hearing (46.6%) and psychological stress (47.0%) were experienced by employees more than once a month, particularly in the wet kitchen. In conclusion, the dry kitchen system was found to be more efficient for food and work safety because of its superior design and well managed practices.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.5
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• pp.521-529
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• 2003

In this paper we present an improved method by using demographic information for overcoming the similarity miss-calculation from the sparsity problem in collaborative filtering recommendation systems. The similarity between a pair of users is only determined by the ratings given to co-rated items, so items that have not been rated by both users are ignored. To solve this problem, we add virtual neighbor's rating using demographic information of neighbors for improving prediction accuracy. It is one kind of extentions of traditional collaborative filtering methods using the peason correlation coefficient. We used the Grouplens movie rating data in experiment and we have compared the proposed method with the collaborative filtering methods by the mean absolute error and receive operating characteristic values. The results show that the proposed method is more efficient than the collaborative filtering methods using the pearson correlation coefficient about 9% in MAE and 13% in sensitivity of ROC.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.2
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• pp.173-186
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• 2000

Real-time embedded systems should accommodate many kinds of hardware platforms and resource management policies that vary depending on their operating environments and purposes. It is not an easy job to adapt a multitasking kernel to new system services and hardware platforms, as the kernel must strictly satisfy constraints on its size and performance. This paper describes the design and implementation of an object-oriented multitasking framework that can be reused for implementing microprocessor-based real-time embedded multitasking kernels, In this kernel framework, those parts that can vary depending on hardware platforms and system resource management policies are separated into the hot spots and encapsulated by abstract classes. Our framework thus can be effectively used to implement microprocessor-based real-time embedded kernels that demand high portability and adaptability.

• KIISE Transactions on Computing Practices
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• v.22 no.9
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• pp.473-478
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• 2016

Server virtualization provides abstraction of physical resources to users and thus accomplishes high resource utilization and flexibility. However, the characteristics of server virtualization, such as the limited number of physical resources shared by virtual machines, can cause problems, mainly performance interference. The performance interference is caused by the fact that the CPU scheduler running on the host operating system schedules virtual machines without considering the characteristics of the virtual machine's internal process. To address performance interference, a number of research activities to improve performance interference have been conducted, but do not deal with the fundamental analysis of performance interference. In this paper, in order to analyze the cause of performance interference, we carry out profiling in a variety of scenarios in a virtualized environment based on KVM. As a result, we analyze the phenomenon of the performance interference in terms of CPU scheduling and propose an efficient scheduling solution.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.6
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• pp.637-647
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• 2010

Recent embedded systems are being more complicated due to their hierarchical software architecture including operating systems. The performance of such complicated software architecture could not be well analyzed through separate analysis of each software layer; the combined effect and the interactions among the whole software layers should be considered. In this paper, we show the design and implementation of a performance analysis framework that enables hierarchical analysis of performance of Linux-based embedded systems considering interactions among the software layers. By using the proposed framework, we can obtain useful run-time information about a hierarchical software structure which usually consists of user-defined function layer, library function layer, system call layer, and kernel events layer. Experimental results reveal that the proposed framework could accurately identify the performance bottlenecks with the corresponding software layers during executions of target applications through the accompanying sub-steps of the analysis: the actual execution paths, the execution time of each observed event in each software layer, and the control flows across the software layers.