• Tuberculosis and Respiratory Diseases
• /
• v.86 no.1
• /
• pp.23-32
• /
• 2023

Everyone is aware that air and environmental pollutants are harmful to health. Among them, indoor air quality directly affects physical health, such as respiratory rather than outdoor air. However, studies that have examined the correlation between environmental and health information have been conducted with public data targeting large cohorts, and studies with real-time data analysis are insufficient. Therefore, this research explores the research with an indoor air quality monitoring (AQM) system based on developing environmental detection sensors and the internet of things to collect, monitor, and analyze environmental and health data from various data sources in real-time. It explores the usage of wearable devices for health monitoring systems. In addition, the availability of big data and artificial intelligence analysis and prediction has increased, investigating algorithmic studies for accurate prediction of hazardous environments and health impacts. Regarding health effects, techniques to prevent respiratory and related diseases were reviewed.

• Asia pacific journal of information systems
• /
• v.24 no.4
• /
• pp.611-635
• /
• 2014

Information systems (IS) have become ubiquitous and changed every aspect of how people live their lives. While some IS have been successfully adopted and widely used, others have failed to be adopted and crowded out in spite of remarkable progress in technologies. Both the technology acceptance model (TAM) and the IS Success Model (ISSM), among many others, have contributed to explain the reasons of success as well as failure in IS adoption and usage. While the TAM suggests that intention to use and perceived usefulness lead to actual IS usage, the ISSM indicates that information quality, system quality, and service quality affect IS usage and user satisfaction. Upon literature review, however, we found a significant void in theoretical development and its applications that employ either of the two models, and we raise research questions. First of all, in spite of the causal relationship between intention to use and actual usage, in most previous studies, only intention to use was employed as a dependent variable without overt explaining its relationship with actual usage. Moreover, even in a few studies that employed actual IS usage as a dependent variable, the degree of actual usage was measured based on users' perceptual responses to survey questionnaires. However, the measurement of actual usage based on survey responses might not be 'actual' usage in a strict sense that responders' perception may be distorted due to their selective perceptions or stereotypes. By the same token, the degree of system quality that IS users perceive might not be 'real' quality as well. This study seeks to fill this void by measuring the variables of actual usage and system quality using 'fact' data such as system logs and specifications of users' information and communications technology (ICT) devices. More specifically, we propose an integrated research model that bring together the TAM and the ISSM. The integrated model is composed of both the variables that are to be measured using fact as well as survey data. By employing the integrated model, we expect to reveal the difference between real and perceived degree of system quality, and to investigate the relationship between the perception-based measure of intention to use and the fact-based measure of actual usage. Furthermore, we also aim to add empirical findings on the general research question: what factors influence actual IS usage and how? In order to address the research question and to examine the research model, we selected a mobile campus application (MCA). We collected both fact data and survey data. For fact data, we retrieved them from the system logs such information as menu usage counts, user's device performance, display size, and operating system revision version number. At the same time, we conducted a survey among university students who use an MCA, and collected 180 valid responses. A partial least square (PLS) method was employed to validate our research model. Among nine hypotheses developed, we found five were supported while four were not. In detail, the relationships between (1) perceived system quality and perceived usefulness, (2) perceived system quality and perceived intention to use, (3) perceived usefulness and perceived intention to use, (4) quality of device platform and actual IS usage, and (5) perceived intention to use and actual IS usage were found to be significant. In comparison, the relationships between (1) quality of device platform and perceived system quality, (2) quality of device platform and perceived usefulness, (3) quality of device platform and perceived intention to use, and (4) perceived system quality and actual IS usage were not significant. The results of the study reveal notable differences from those of previous studies. First, although perceived intention to use shows a positive effect on actual IS usage, its explanatory power is very weak ($R^2$=0.064). Second, fact-based system quality (quality of user's device platform) shows a direct impact on actual IS usage without the mediating role of intention to use. Lastly, the relationships between perceived system quality (perception-based system quality) and other constructs show completely different results from those between quality of device platform (fact-based system quality) and other constructs. In the post-hoc analysis, IS users' past behavior was additionally included in the research model to further investigate the cause of such a low explanatory power of actual IS usage. The results show that past IS usage has a strong positive effect on current IS usage while intention to use does not have, implying that IS usage has already become a habitual behavior. This study provides the following several implications. First, we verify that fact-based data (i.e., system logs of real usage records) are more likely to reflect IS users' actual usage than perception-based data. In addition, by identifying the direct impact of quality of device platform on actual IS usage (without any mediating roles of attitude or intention), this study triggers further research on other potential factors that may directly influence actual IS usage. Furthermore, the results of the study provide practical strategic implications that organizations equipped with high-quality systems may directly expect high level of system usage.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1995.10a
• /
• pp.1039-1042
• /
• 1995

In real time application such as motion control, it is hard to find the application of non-causal filtering due to its need for future position data, even though it shows wide usage in off-line digital signal processing. Recently, some of motion control areas such as learning and repetitive control use non-causal filtering technique in their application. these kinds of zero-lag non-causal filter application are very usful not only to reduce the machine vibration, but also to increase control accuracy with comparatively less work. In this paper, genuine method to implement zero-lag non-causal filter in a CNC is introduced. Also the variation of this implementation for the learning operation is suggested to give the NC better control performance for a specific job. By adopting the new NC architecture call Soft-NC, all these implementions are made possible here, and especially large memory requirement which hinders their usage for many years is no longer barrier in their real world application.

• Earthquakes and Structures
• /
• v.6 no.4
• /
• pp.375-392
• /
• 2014

Time history analyses have been preferred commonly in earthquake engineering area to determine earthquake performances of structures in recent years. Advances in computer technology and structural analysis have led to common usage of time history analyses. Eurocode 8 allows the use of real earthquake records as an input for linear and nonlinear time history analyses of structures. However, real earthquake records with the desired characteristics sometimes may not be found, for example depending on soil classes, in this case artificial and synthetic earthquake records can be used for seismic analyses rather than real records. Selected earthquake records should be scaled to a code design spectrum to reduce record to record variability in structural responses of considered structures. So, scaling of earthquake records is one of the most important procedures of time history analyses. In this paper, four real earthquake records are scaled to Eurocode 8 design spectrums by using SESCAP (Selection and Scaling Program) based on time domain scaling method and developed by using MATLAB, GUI software, and then scaled and real earthquake records are used for linear time history analyses of a six-storied building. This building is modeled as spatial by SAP2000 software. The objectives of this study are to put basic procedures and criteria of selecting and scaling earthquake records in a nutshell, and to compare the effects of scaled earthquake records on structural response with the effects of real earthquake records on structural response in terms of record to record variability of structural response. Seismic analysis results of building show that record to record variability of structural response caused by scaled earthquake records are fewer than ones caused by real earthquake records.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.6
• /
• pp.1346-1352
• /
• 2009

Warranty cost of automobile parts varies depending on the parts failure rate in a warranty region of individual markets. Parts failure rate is significantly affected by usage-rate given that other stressors of individual markets are similar. Accordingly, warranty cost can be predicted by failure modeling which reflects usage-rate and using a stochastic process. In this paper, one-dimensional approach is used by applying accelerated failure time model on the assumption that the usage-rate is linear. Such model can explain changes in parts failure rate depending on the changes in usage-rate since it can be expressed as a function of usage-rate. Therefore, acquisition of usage-rate in a new market will automatically lead to estimate of failure rate even without warranty data and warranty cost of parts can be predicted through a renewal process in replacement cases. A case study using warranty data of two real markets is presented in the application part of this paper.

• Environmental and Resource Economics Review
• /
• v.25 no.2
• /
• pp.141-178
• /
• 2016

This paper, using AMR (Automatic Meter Reading) electricity data accurately measured in real time, analyses the characteristics and patterns of temperature effect on the industrial electricity usage. For this goal, the paper constructs and estimates a model which captures the properties of AMR time series including long-term trends, mid-term temperature effects, and short-term special day effects. Based on the estimated temperature response function and the temperature effect, we categorize the whole industry into two groups: one group with sharp temperature effect and the other with weak temperature effect. Furthermore, the industry group with sharp temperature effect is classified into a summer peak industry group and a winter peak industry group, based on the estimates of the temperature response function. These empirical results carry practical policy implications on the real time electricity demand management.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.10C
• /
• pp.983-991
• /
• 2009

While H.264/AVC is in wide use for multimedia applications such as DMB and IPTV service, we have limited usage cases for embedded real-time applications due to its high computational demand. The paper provides judicious guide line for optimization method selection, by presenting the detailed experiments data through the development process of a real time H.264 software encoder on embedded DSP. The experimental analysis includes an intensive profiling analysis, fast algorithm application, optimal memory assignment, and intrinsic-based instruction selection. We have realized a real-time software that encodes CIF resolution videos 15 fps on TMS320DM64x processors.

• Convergence Security Journal
• /
• v.5 no.2
• /
• pp.1-8
• /
• 2005

Network event analysis gives useful information on the network status that helps protect attacks. It involves finding sets of frequently used packet information such as IP addresses and requires real-time processing by its nature. Apriori algorithm used for data mining can be applied to find frequent item sets, but is not suitable for analyzing network events on real-time due to the high usage of CPU and memory and thus low processing speed. This paper develops a network event audit module by applying association rules to network events using a new algorithm instead of Apriori algorithm. Test results show that the application of the new algorithm gives drastically low usage of both CPU and memory for network event analysis compared with existing Apriori algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2013.10a
• /
• pp.77-80
• /
• 2013

SURF algorithm is an algorithm to extract feature points and to generate descriptors from input images. It is robust to change of environment such as scale, rotation, illumination and view points. Because of these features, it is used for many image processing applications such as object recognition, constructing panorama pictures and 3D image restoration. But there is disadvantage for real time operation because many recognition algorithms such as SURF algorithm requires a lot of calculations. In this paper, we propose a design of feature extractor and descriptor generator based on SURF for high memory efficiency. The proposed design reduced a memory access and memory usage to operate in real time.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.12 no.3
• /
• pp.121-130
• /
• 2017

NAND flash memory has advantages of non-volatility, little power consumption and fast access time. However, it suffers from inability that does not provide to update-in-place and the erase cycle is limited. Moreover, the unit of read/write operation is a page and the unit of erase operation is a block. Therefore, erase operation is slower than other operations. The AGC, the proposed garbage collection policy focuses on not only garbage collection time reduction for real-time guarantee but also wear-leveling for a flash memory lifetime. In order to achieve above goals, we define three garbage collection operating modes: Fast Mode, Smart Mode, and Wear-leveling Mode. The proposed policy decides the garbage collection mode depending on system CPU usage rate. Fast Mode selects the dirtiest block as victim block to minimize the erase operation time. However, Smart Mode selects the victim block by reflecting the invalid page number and block erase count to minimizing the erase operation time and deviation of block erase count. Wear-leveling Mode operates similar to Smart Mode and it makes groups and relocates the pages which has the similar update time. We implemented the proposed policy and measured the performance compare with the existing policies. Simulation results show that the proposed policy performs better than Cost-benefit policy with the 55% reduction in the operation time. Also, it performs better than Greedy policy with the 87% reduction in the deviation of erase count. Most of all, the proposed policy works adaptively according to the CPU usage rate, and guarantees the real-time performance of the system.