• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.750-757
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• 2012

This paper focuses on human adaptive HVAC system that can regulate the thermal comfort of the resident in intelligent buildings. The thermal comfort is represented in this paper by PMV (Predicted Mean Vote) as defined by ISO 7730. This PMV value indicates how hot or cold a resident feels by considering temperature, humidity, resident's metabolic rate, relative air velocity, and clothing insulation. In order to develop such a system, a location detection system based on ZigBee module was used along with temperature sensors, other environment sensors. The human adaptive HVAC system was evaluated experimentally on a test bed emulating a room.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.2
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• pp.11-22
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• 2015

The almost of Web page has been gathered the personal information(Korean resident registration number, name, cell-phone number, home telephone number, E-mail address, home address, etc.) using the membership and log-in. The all most user of Web page are concerned for gathering of the personal information. I-pin is the alternative means of resident registration number and has been used during the last ten-year period in the internet. The accident of I-pin mass illegal issue was happened by hacker at February, 2015. In this paper, we analysis the problems of I-pin system about I-pin mass illegal issue accident and propose a improvement method of it. First, I-pin issue must be processed by the off-line of face certification in spite of user's inconvenience. Second, I-pin use must be made up through second certification of password or OTP. The third, the notification of I-pin use must be sent to the user by the text messaging service of cell-phone or the E-mail. The forth, I-pin must be used an alternative means of Korean resident registration number in Internet. The methods can reduce the problems of I-pin system.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.6
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• pp.37-44
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• 2007

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.9
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• pp.905-911
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• 2006

Smart homes are expected to offer various intelligent services by recognizing the residents' life pattern, health, and feeling. One of the key issues for realizing the smart home is how to detect the locations of residents. Currently, the research effort is focused on two approaches: terminal-based and non-terminal-based method. The terminal-based method employs a type of device that should be carried by the resident while the non-terminal-based method has no such device. This paper presents a novel non-terminal-based approach using an array of pyroelectric infrared sensors (PIRs) that can detect residents. The feasibility of the system is evaluated experimentally on a test bed.

• Journal of Veterinary Clinics
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• v.32 no.3
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• pp.282-284
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• 2015

This report describes asymptomatic Haemoproteus infection in wild Eurasian eagle owls (Bubo bubo) diagnosed by blood smear and DNA analysis. This is the first description of natural Haemoproteus infection in wild Eurasian eagle owl in South Korea and suggests that the wild resident bird population can be a source for Haemoproteus infection of domestic poultry.

• Journal of KIISE:Databases
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• v.37 no.4
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• pp.197-202
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• 2010

Recent studies on change detection for RDF data are focused on not only the structural difference but also the semantic-aware difference by computing the closure of RDF models. However, since these techniques which take into account the semantics of RDF model require both RDF models to be memory resident, or they use a forward-chaining strategy which computes the entire closure in advance, it is not efficient to apply them directly to detect changes in large RDF data. In this paper, we propose a scalable change detection technique for RDF data, which uses a backward-chaining inference based on relational database. Proposed method uses a new approach for RDF reasoning that computes only the relevant part of the closure for change detection in a relational database. We show that our method clearly outperforms the previous works through experiment using the real RDF from the bioinformatics domain.

• Bulletin of the Korean Chemical Society
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• v.18 no.1
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• pp.32-37
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• 1997

We have built a laser ionization mass spectrometer (LIMS) for chemical composition analysis of solid samples, which employs an Nd:YAG laser and a time-of-flight mass analyzer. In this spectrometer, the maximum mass we identified clearly is higher than 2000 amu. A mass resolution of 230 has been achieved at m/z 208 (Pb element) in the linear TOFMS and can be even improved up to 1550 by employing a reflectron. The detection limit is determined to be on the order of ppm for Fe and In. The depth resolution is found to be about 20Å/spectrum with a laser power of 0.5 J/cm2. We also report a preliminary application of the LIMS to identifying impurities resident in several solid samples.

• Korean Journal of Veterinary Service
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• v.35 no.2
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• pp.111-117
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• 2012

This study investigated the occurrence of honeybee diseases in Incheon area, at the point of great widespread of sacbrood disease in the country. Sixteen resident beekeeping apiaries; 3 native honeybee and 13 European honeybee apiaries were selected for this research. Over 20 adult bees were evenly collected from the most colonies of each apiary three times (March, June, November) within a year. In this work, 13 honeybee diseases including 7 viral diseases, 2 bacterial diseases, 2 fungal diseases, and 2 parasitic diseases were detected by preliminary inspections and PCR. As a result, viral infections were confirmed at 34 among 48 apiaries (70.8%) over the entire examination period. Parasitic diseases showed the highest detection rate of 45.8%, which are detected in 44 among 96 cases. In the seasonal prevalence, 30 cases (15.6%) of 7 pathogens were detected from 14 apiaries in March, 50 cases (24.0%) of 9 pathogens and 56 cases (26.9%) of 9 pathogens were detected from all apiaries in June and November, respectively. Nosema was shown to be the most prevalent pathogen from March to November, followed by sacbrood virus (SBV) and stonebrood. The spread of SBV infection in Incheon would be under-estimated by the increasing of detection rate over the time. Especially, Chinese sacbrood virus was detected from 4 European honybee apiaries, but clinical symptoms were not found. No chalkbrood, acute bee paralysis virus, and chronic bee paralysis virus were detected in this study. The effective therapy and preventive measures should be prepared for beekeeping industry.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.12
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• pp.5309-5314
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• 2016

Background: Breast cancer is the most common type of cancer amongst women throughout the world. Currently, there are various follow-up strategies implemented in Iran, which are usually dependent on clinic policies and agreement among the resident oncologists. Purpose: A cost-effectiveness analysis was performed to assess the cost-effectiveness of intensive follow-up versus standard models for early breast cancer patients in Iran. Materials and methods: This cross sectional study was performed with 382 patients each in the intensive and standard groups. Costs were identified and measured from a payer perspective, including direct medical outlay. To assess the effectiveness of the two follow-up models we used a decision tree along with indicators of detection of recurrence and metastasis, calculating expected costs and effectiveness for both cases; in addition, incremental cost-effectiveness ratios were determined. Results: The results of decision tree showed expected case detection rates of 0.137 and 0.018 and expected costs of US$24,494.62 and US$6,859.27, respectively, for the intensive and standard follow-up models. Tornado diagrams revealed the highest sensitivity to cost increases using the intensive follow-up model with an ICER=US$148,196.2. Conclusion: Overall, the results showed that the intensive follow-up method is not cost-effective when compared to the standard model.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.486-494
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• 2014

Intelligent homes consist of ubiquitous sensors, home networks, and a context-aware computing system. These homes are expected to offer many services such as intelligent air-conditioning, lighting control, health monitoring, and home security. In order to realize these services, many researchers have worked on various research topics including smart sensors with low power consumption, home network protocols, resident and location detection, context-awareness, and scenario and service control. This paper presents the real-time metabolic rate estimation method that is based on measured heart rate for human adaptive appliance (air-conditioner, lighting etc.). This estimation results can provide valuable information to control smart appliances so that they can adjust themselves according to the status of residents. The heart rate based method has been experimentally compared with the location-based method on a test bed.