• Journal of the Korean Society of Safety
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• v.38 no.2
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• pp.30-35
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• 2023

Acetone is a widely used Volatile Organic Compound (VOC) in industries and laboratories. However, acetone affects human health adversely and causes fires and explosions. Early acetone detection and improved personnel training in safety and emergency management are necessary to prevent acetone-related accidents. The multi-VOC acetone detectors used currently have a sensitivity and selectivity limit. In this study, we discovered that Pt-loaded iron oxide (a metal oxide semiconductor) conversely, has high detection and selectivity for very low-levels of acetone gas. The loaded Pt catalyzes the reaction between the sensing materials' surface and the oxygen molecules in the air; this optimizes acetone detection and can decrease acetone-related illnesses, fires and explosions.

• ETRI Journal
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• v.45 no.4
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• pp.713-723
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• 2023

Game bots are illegal programs that facilitate account growth and goods acquisition through continuous and automatic play. Early detection is required to minimize the damage caused by evolving game bots. In this study, we propose a game bot detection method based on action time intervals (ATIs). We observe the actions of the bots in a game and identify the most frequently occurring actions. We extract the frequency, ATI average, and ATI standard deviation for each identified action, which is to used as machine learning features. Furthermore, we measure the performance using actual logs of the Aion game to verify the validity of the proposed method. The accuracy and precision of the proposed method are 97% and 100%, respectively. Results show that the game bots can be detected early because the proposed method performs well using only data from a single day, which shows similar performance with those proposed in a previous study using the same dataset. The detection performance of the model is maintained even after 2 months of training without any revision process.

• Journal of Power System Engineering
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• v.20 no.2
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• pp.66-72
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• 2016

As a method to improve the equipment reliability, early warning researches that can be detected fault symptom of an equipment at an early stage are being performed out among developed countries. In this paper, when abnormal signal is input to actual normal signal of a pump, early detection studies on pump's fault symptom were carried out with auto-associative kernel regression as an advanced pattern recognition algorithm. From analysis, correlations among power of motor driving pump, discharge flow of pump, power output of pump, and discharge pressure of pump are exited. When the abnormal signal is input to one of those normal signals, the other expected values are changed due to the influence of the abnormal signal. Therefore, the fault symptom of pump through the early-warning index is able to detect at an early stage.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2783-2790
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• 2010

In this paper, we first review LDPC codes in general and a belief propagation algorithm that works in logarithm domain. LDPC codes, which is chosen 802.11n for wireless local access network(WLAN) standard, require a large number of computation due to large size of coded block and iteration. Therefore, we presented three kinds of low computational algorithms for LDPC codes. First, sequential decoding with partial group is proposed. It has the same H/W complexity, and fewer number of iterations are required with the same performance in comparison with conventional decoder algorithm. Secondly, we have apply early stop algorithm. This method reduces number of unnecessary iterations. Third, early detection method for reducing the computational complexity is proposed. Using a confidence criterion, some bit nodes and check node edges are detected early on during decoding. Through the simulation, we knew that the iteration number are reduced by half using subset algorithm and early stop algorithm is reduced more than one iteration and computational complexity of early detected method is about 30% offs in case of check node update, 94% offs in case of check node update compared to conventional scheme. The LDPC decoder have been implemented in Xilinx System Generator and targeted to a Xilinx Virtx5-xc5vlx155t FPGA. When three algorithms are used, amount of device is about 45% off and the decoding speed is about two times faster than convectional scheme.

• Journal of KIISE:Information Networking
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• v.28 no.4
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• pp.517-526
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• 2001

In order to reduce the increasing packet loss rates caused by an exponential increase in network traffic, the IETF(Internet Engineering Task Force) is considering the deployment of active queue management techniques such as RED(Random Early Detection). While active queue management in routers and gateways can potentially reduce total packet loss rates in the Internet, this paper has demonstrated the inherent weakness of current techniques and shows that they are ineffective in preventing high loss rates. The inherent problem with these queue management algorithms is that they all use queue lengths as the indicator of the severity of congestion. In this paper, in order to solve this problem, a new active queue management algorithm called MRED(Modified Random Early Detection) is proposed. MRED computes the packet drop probability based on our heuristic method rather than the simple method used in RED. Using simulation, MRED is shown to perform better than existing queue management schemes. To analyze the performance, we also measure throughput of traffics under the FIFO control, and compared the performance with that of this MRED system.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.4
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• pp.2247-2254
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• 2016

Background: The incidence of breast cancer is rising in Oman, and the disease is diagnosed at late stages, when treatment success is limited. Omani women might benefit from better awareness, so that breast cancer can be detected early and treated. This study was conducted to assess Omani women's levels of breast cancer awareness and early detection practice, and explore factors which might influence these levels. Materials and Methods: A mixed methods study was conducted in 2014, including a quantitative survey of 1,372 and a qualitative assessment of 19 Omani women, aged ${\geq}20years$ from five Omani governorates using convenient sampling. Demographic information and scores for awareness levels were used in a multivariate regression model to investigate factors associated with awareness. Thematic analysis and interpretive description were used to analyse the qualitative data. Results: The overall means for early detection and general awareness scores were 0.58 (SD 0.24) and 0.46 (SD 0.21), respectively. General awareness was significantly associated with age, education, income and familiarity with cancer patients (p<0.05), while early detection was significantly associated with age, marital status and education. A majority of women (59.5%) agreed with a belief in 'evil eye' or envy as a risk factor for breast cancer. Women discussed various factors which may empower or inhibit awareness, including the cultural-religion-fatalistic system, personal-familial-environmental system, and healthcare-political-social system. Conclusions: The overall low scores for awareness and early detection, and the survey of local beliefs highlight a severe necessity for a contextually-tailored breast cancer awareness intervention programme in Oman.

• Journal of Korea Multimedia Society
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• v.21 no.1
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• pp.34-44
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• 2018

An early detection of intravenous (IV) infiltration is essential to minimize the injuries during infusion therapy, which is one of the most important tasks for nurses in nursing settings. We report that bioelectrical impedance analysis is useful in the early detection of infiltration at puncture sites. When infiltration was intentionally induced in the vein of a pig's posterior ear, impedance parameters (R, $X_C$, $C_m$) showed significant differences before and after infiltration. In particular, the relative resistance ($R/R_{BI}$) decreased significantly at infiltration and then slowly decreased. This indicates that the vein in pig's ear is thin and the amount of surrounding subcutaneous tissue, and hence the infiltrated solution accumulates slowly after infiltration. However, when infiltration was induced in the vein of human's forearm, the relative resistance at 20 kHz decreased gradually over time. In the $R-X_C$ graph, the positions in the case of infiltration induced in the pig' ear shifted rapidly before and after infiltration, whereas the positions in the case of infiltration induced in the human's forearm moved gradually during infiltration. Our findings suggest that the impedance parameters (R, $R/R_{BI}$, $X_C$, R vs. $X_C$, and $C_m$) are effective indicators to detect the infiltration early in a non-invasive and quantitative manners.

• Toxicological Research
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• v.32 no.1
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• pp.47-56
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• 2016

The identification of biomarkers for the early detection of acute kidney injury (AKI) is clinically important. Acute kidney injury (AKI) in critically ill patients is closely associated with increased morbidity and mortality. Conventional biomarkers, such as serum creatinine (SCr) and blood urea nitrogen (BUN), are frequently used to diagnose AKI. However, these biomarkers increase only after significant structural damage has occurred. Recent efforts have focused on identification and validation of new noninvasive biomarkers for the early detection of AKI, prior to extensive structural damage. Furthermore, AKI biomarkers can provide valuable insight into the molecular mechanisms of this complex and heterogeneous disease. Our previous study suggested that pyruvate kinase M2 (PKM2), which is excreted in the urine, is a sensitive biomarker for nephrotoxicity. To appropriately and optimally utilize PKM2 as a biomarker for AKI requires its complete characterization. This review highlights the major studies that have addressed the diagnostic and prognostic predictive power of biomarkers for AKI and assesses the potential usage of PKM2 as an early biomarker for AKI. We summarize the current state of knowledge regarding the role of biomarkers and the molecular and cellular mechanisms of AKI. This review will elucidate the biological basis of specific biomarkers that will contribute to improving the early detection and diagnosis of AKI.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.3
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• pp.571-578
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• 2018

The deteriorated pipline often causes the unexpected leakage and crack. Negligence and late maintenance leads the enormous damage for gas and water resource. This paper proposes early fault detection and diagnosis algorithm for pipeline using acoustic emission (AE) signals. Early fault detection method for pipeline compares the frequency amplitude of the spectrum to that of the spectrum in normal condition. Larger amplitude of the spectrum indicates abnormal condition. Early fault diagnosis algorithm uses support vector machines (SVM), which is trained for normal and abnormal conditions to diagnose the measured AE signal from the target pipeline. In the experiment, a pipeline testbed is constructed similarly to real industrial pipeline. Normal, 5mm cracked, 10mm holed pipelines are installed and tested in this study. The proposed fault detection and diagnosis technique is validated as an efficient approach to detect early faulty condition of pipeline.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2167-2172
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• 2013

Lung cancer remains a major cause of morbidity and mortality worldwide, accounting for more deaths than any other cause. All the clinical practice guidelines recommended against routine screening for lung cancer have cited lack of robust evidence, at least until a few years back. However, the potential to screen lung cancers has received renewed interest due to superior performance of low dose CT (LD-CT) in detecting early stage cancers. The incremental costs and risks involved due to the invasive procedures in the screened population due to a high false positivity rate questions the use of LD-CT scan as a reliable community based screening tool. There is therefore an urgent need to find a less invasive and a more reliable biomarker that is crucial to increase the probability of early lung cancer detection. This can truly make a difference in lung cancer survival and at the same time be more cost and resource utilization effective. Sampling blood serum being minimally invasive, low risk and providing an easy to obtain biofluid, needs to be explored for potential biomarkers. This review discusses the use of circulatory miRNAs that have been able to discriminate lung cancer patients from disease free controls. Several studies conducted recently suggest that circulating miRNAs may have promising future applications for screening and early detection of lung cancer.