• Journal of Korea Technology Innovation Society
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• v.16 no.4
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• pp.954-977
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• 2013

This paper investigates the factors to affect the consumer selection of machine-to-machine (M2M) technology in the purchase and utilization of home appliances. M2M technology, based on mobile internet, allows for automatic operation and remote control of home appliances and equipment. The introduction of M2M technology could lead to the saving of domestic housework and of active social participation for women. With a view to focusing on the liberating potential of M2M technology, this paper analyzes the correlation between four independent variables (gender, income, employment status of married woman, and possession of mobile internet devices) and two dependent variables (intention for purchase and utilization of M2M household appliances). The possession of mobile internet devices such as smart phone and tablet PC turns out to be the most significant factor to affect both the purchase and utilization of M2M household appliances. The employment status (employed or not-employed) affects only the intention for purchase. Neither the income level nor gender has significant correlation with the intention for purchase or utilization. The results differ from the conventional wisdom that the consumer selection of household technology is substantially affected by gender, income and employment of housewife.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.49-56
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• 2023

Computer architecture serves as a link between application requirements and underlying technology capabilities such as technical, mathematical, medical, and business applications' computational and storage demands are constantly increasing. Machine learning these days grown and used in many fields and it performed better than traditional computing in applications that need to be implemented by using mathematical algorithms. A mathematical algorithm requires more extensive and quicker calculations, higher computer architecture specification, and takes longer execution time. Therefore, there is a need to improve the use of computer hardware such as CPU, memory, etc. optimization has a main role to reduce the execution time and improve the utilization of computer recourses. And for the importance of execution time in implementing machine learning supervised module linear regression, in this paper we focus on optimizing machine learning algorithms, for this purpose we write a (Diabetes prediction program) and applying on it a Practical Swarm Optimization (PSO) to reduce the execution time and improve the utilization of computer resources. Finally, a massive improvement in execution time were observed.

• Tunnel and Underground Space
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• v.13 no.3
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• pp.196-206
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• 2003

In order to investigate the workability of Raise Boring Machine(RBM) such as utilization, penetration rate and advance rate, a vertical shaft of 98 m in length and 3.05 m in diameter was constructed in the layer of conglomerate by using the RBM in this study. In addition, field data from tow different construction sites including water-pump power plant tunnel, roadway tunnel and mining tunnel by RBM were collected and analyzed. The results show that the average weekly bored length is 19.3 m and its average utilization is between 54.3 % and 75.1 % very higher than that of the TBM(Tunnel Boring Machine). It also turns out that the bit force increases linearly with respect to the increase of the RPM(revolution per minute) of RBM. However, the net penetration rate decreases with the increase of bit force, RPM of RBM and depth of shaft. The findings of this study can be used to provide the useful information for the design of shaft and the selection of RBM.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.323-327
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• 2017

Soft magnetic composite (SMC) material has recently received a significant attention in the area of high-speed machines because of its unique properties such as good design flexibility and low eddy current loss. However, SMC's electromagnetic property is poor compared to silicon steel in terms of saturation, relative permeability, and hysteresis loss. This paper presents a technique for utilization of SMC in two strategic designs of a switched reluctance machine (SRM) depending on a loss pattern. To investigate the effect of SMC's merits and demerits, the stator material is changed from laminated steel to SMC.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1302-1320
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• 2015

In cloud, everything can be provided as a service wherein a large number of users submit their jobs and wait for their services. hus, scheduling plays major role for providing the resources efficiently to the submitted jobs. The brainwave of the proposed ork is to improve user satisfaction, to balance the load efficiently and to bolster the resource utilization. Hence, this paper roposes an Adaptive Multilevel Scheduling System (AMSS) which will process the jobs in a multileveled fashion. The first level ontains Preprocessing Jobs with Multi-Criteria (PJMC) which will preprocess the jobs to elevate the user satisfaction and to itigate the jobs violation. In the second level, a Deadline Based Dynamic Priority Scheduler (DBDPS) is proposed which will ynamically prioritize the jobs for evading starvation. At the third level, Contest Mapping Jobs with Virtual Machine (CMJVM) is roposed that will map the job to suitable Virtual Machine (VM). In the last level, VM Scheduler is introduced in the two-tier VM rchitecture that will efficiently schedule the jobs and increase the resource utilization. These contributions will mitigate job iolations, avoid starvation, increase throughput and maximize resource utilization. Experimental results show that the performance f AMSS is better than other algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.3
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• pp.562-565
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• 2017

In this letter, we consider a 7-step transmission procedure of a large number of machine nodes when they simultaneously request random access to transmit uplink data. We model the radio resource utilization of LTE systems, and analyze the overloaded resources. From the simulation results, we show that the resource of PDCCH becomes significantly overloaded as the number of machine nodes increases in a cell. To alleviate the overload of PDCCH, we allocate radio resource of PDSCH to PDCCH. The result shows that the resource utilization of PDCCH is improved.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.109-114
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• 1997

As CNC machine tool is one of core elements of manufacturing system, it is much important that it remains without troubleshoots. As a virtual machine is a recent alternative using IT for optimal utilization of CNC machine tool, it is a computer model that represents a CNC machine tool. But a virtual machine is still conceptual. So, in this paper, it is proposed that a virtual machine be a realistic model in the fault diagnosis module. For this purpose, the fault diagnosis system of machine tool using CORBA and fault diagnosis expert system has been implemented. Using this system, we have expections to diagnose exactly and prompty without the restriction of time or location, to reduce MTTR(Mean Time To Repair) and finally to increase the availability of manufacturing system.

• Tunnel and Underground Space
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• v.29 no.5
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• pp.356-366
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• 2019

Various TBM performance prediction models have been developed and most of them were considered penetration rate only. Despite the fact that some models have suggested equations and charts for estimating the utilization factor, but there are a few studies to estimate the TBM utilization factor. Utilization factor is affected by the type of TBM machine, operation, maintenance of machine, geological conditions, contractor experience and other factors. In this study, more than 100 case studies are analyzed to determine the relationship between the utilization factor and RMR, geological conditions, TBM types, tunnel length, and TBM diameter. Simple and multiple linear regression analysis are performed to develop predictive models for the utilization factor. The predictive model with explanatory variables of geological conditions, TBM types, tunnel length, and TBM diameter does not give a good correlation. The predictive models with explanatory variable of RMR give higher values of the coefficient of determination.

• Journal of Veterinary Clinics
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• v.28 no.4
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• pp.408-414
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• 2011

This study was carried out to analyze the utilization of ultrasound machines in animal hospitals and focused on surveying the present condition of diagnostic ultrasound on veterinary medicine in South Korea. Total 279 veterinary hospitals were surveyed with e-mail questionnaires or telephone survey. E-mail questionnaires consist of 17 items of questions including existence of ultrasound machine, types of ultrasound machine, ultrasound examination costs, frequency, purposes, other diagnostic imaging equipments, and referring system of ultrasound. Telephone surveys asked about the existence of the ultrasound machine and types of the ultrasound machine to 279 animal hospitals. Two hundred and seventy-one out of 279 animal hospitals holds ultrasound machine. Seventy-two percents clinics purchased used ultrasonographic machines and mean years after the date of manufacture is 7.5 years and the proportion of superannuated machines are relatively high. Also many clinicians prefer single organ scanning rather than general scan technique and more than 60% of clinics perform ultrasonographic examination less than 5 times a week. Clinics located in Seoul area tend to have more expensive and brand-new ultrasonographic machines and the distribution of radiology specialist are higher in this area. Problems associated with the present condition were oversupply of machines, unequal distribution of the medical equipment in different localities, ineffective use of the medical equipment, and high percentage of old poor-quality medical equipments. There should be a viable alternative proposal to control amount and quality of the ultrasound machines. Also, the improved management system for the ultrasound machine is required.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.1
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• pp.53-59
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• 2011

End milling is available for machining the various shape of products and has been widely applied in many manufacturing industries. The quality of products depends on a machine tool performance and machining conditions. Recognition characteristics of the cutting condition is becoming a critical requirement for improving the utilization and flexibility of present-day CNC machine tools. The measurement of tool wear would be performed by coordinate-measuring machine(CMM). However, the usage of CMM requires much time and cost. In order to overcome the difficulties, on-line measurement(OLM) system was applied for a tool wear measurement. This study shows a reliable technique for the reduction of machining error components by developing a system using a CCD camera and machine vision to be able to precisely measure the size of tool wear in flat end milling for CNC machining. The CCD camera and machine vision attached to a CNC machine can determine tool wear quickly and easily.