• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.4
• /
• pp.22-29
• /
• 2021

This study evaluates the accuracy of corrective feedback from Grammarly, an online grammar checker, on essays written by cyber university learners in terms of detected errors, suggested replacement forms, and false alarms.The results indicate that Grammarly has a high overall error detection rate of over 65%, being particularly strong at catching errors related to articles and prepositions. In addition, on the detected errors, Grammarly mostly provide accurate replacement forms and very rarely make false alarms. These findings suggest that Grammarly has high potential as a useful educational tool to complement the drawbacks of teacher feedback and to help learnersimprove grammatical accuracy in their written work. However, it is still premature to conclude that Grammarly can completely replace teacher feedback because it has the possibility (approximately 35%) of failing to detect errors and the limitationsin detecting errors in certain categories. Since the feedback from Grammarly is not entirely reliable, caution should be taken for successful integration of Grammarly in English writing classes. Teachers should make judicious decisions on when and how to use Grammarly, based on a keen awareness of Grammarly's strengths and limitations.

• Journal of Korean Institute of Industrial Engineers
• /
• v.14 no.1
• /
• pp.1-15
• /
• 1988

DS1 transmission systems use framing bit errors, bipolar violations and code-detected errors to estimate the bit error rate when determining errored and severely errored seconds. Using the coefficient of variation under the memoryless binary symmetric channel assumption, a basic framework to evaluate these estimation schemes is proposed to provide a practical guideline in determining errored and severely errored seconds which are fundamental in monitoring the real-ime error performance of DS1 transmission systems carrying live traffic. To evaluate the performance of the cyclic redundancy check code (CRC), a computer simulation model is used. Several drawbacks of the superframe format in association with real time error performance monitoring are discussed. A few recommendations are suggested in measuring errored and severely errored seconds, and determining service limit alarms through the use of the superframe format. Furthermore, we propose a new robust scheme for determining service limit alarms which take into consideration the limitations of some estimation schemes for the time interval of one second.

• Atmosphere
• /
• v.22 no.2
• /
• pp.137-147
• /
• 2012

The technique of Brightness Temperature Difference (BTD) between 11 and $12{\mu}m$ separates yellow sand dust from clouds according to the difference in absorptive characteristics between the channels. However, this method causes consistent false alarms in many cases, especially over the desert. In order to reduce these false alarms, we should eliminate the background noise originated from surface. We adopted the Background BTD (BBTD), which stands for surface characteristics on clear sky condition without any dust or cloud. We took an average of brightness temperatures of 11 and $12{\mu}m$ channels during the previous 15 days from a target date and then calculated BTD of averaged ones to obtain decontaminated pixels from dust. After defining the BBTD, we subtracted this index from BTD for the Yellow Sand Index (YSI). In the previous study, this method was already verified using the geostationary satellite, MTSAT. In this study, we applied this to the polar orbiting satellite, MODIS, to detect yellow sand dust over Northeast Asia. Products of yellow sand dust from OMI and MTSAT were used to verify MODIS YSI. The coefficient of determination between MODIS YSI and MTSAT YSI was 0.61, and MODIS YSI and OMI AI was also 0.61. As a result of comparing two products, significantly enhanced signals of dust aerosols were detected by removing the false alarms over the desert. Furthermore, the discontinuity between land and ocean on BTD was removed. This was even effective on the case of fall. This study illustrates that the proposed algorithm can provide the reliable distribution of dust aerosols over the desert even at night.

• The KIPS Transactions:PartC
• /
• v.11C no.3
• /
• pp.301-308
• /
• 2004

Misuse IDS is known to have an acceptable accuracy but suffers from high rates of false alarms. We show a behavior based alarm reduction with a memory-based machine learning technique. Our extended form of IBL, (XIBL) examines SNORT alarm signals if that signal is worthy sending signals to security manager. An experiment shows that there exists an apparent difference between true alarms and false alarms with respect to XIBL behavior This gives clear evidence that although an attack in the network consists of a sequence of packets, decisions over Individual packet can be used in conjunction with misuse IDS for better performance.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38A no.7
• /
• pp.592-602
• /
• 2013

The purpose of this study is to optical cable closure and fiber line monitoring system. The current optical cable closure cases have not had any systems that help the central control station recognize opening as well as closing the cases in real-time when opening B2B and B2C lines. to solve this problem, it is considered to create systems that go off alarms, real-time fault location immediately, set alarms for open and close monitoring optical cable closure, and inspect regularly whether optical cables are deficient when monitoring the optical line in real-time and cutting them, in this paper, the monitoring system whose the central control station finds an optical signal block immediately and goes off the alarms when line workers separate components like a connector or a tray from the optical cable closure through OTDR. this study can contribute to stabilize the network quality through the quick and effective operation of the cables.

• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.4
• /
• pp.276-280
• /
• 2016

Due to the increasing interest in safety and consistent product quality over a past few decades, demand for effective quality monitoring and safe operation in the modern industry has propelled research into statistical based fault detection and diagnosis methods. This paper describes the application of Hotelling $T^2$ index based Principal Component Analysis (PCA) method for fault detection and diagnosis in industrial processes. Multivariate statistical process control techniques are now widely used for performance monitoring and fault detection. Conventional methods such as PCA are suitable only for steady state processes. These conventional projection methods causes false alarms or missing data for the systems with transient values of processes. These issues significantly compromise the reliability of the monitoring systems. In this paper, a reliable method is used to overcome false alarms occur due to varying process conditions and missing data problems in transient states. This monitoring method is implemented and validated experimentally along with matlab. Experimental results proved the credibility of this fault detection method for both the steady state and transient operations.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.2
• /
• pp.139-147
• /
• 2019

A false alarm, which is an incorrect report of an emergency, could trigger an unnecessary action. The predictive maintenance framework developed in our previous work has a feature whereby a machine alarm is triggered based on sensor data evaluation. The sensor data evaluator performs three essential evaluation steps. First, it evaluates each sensor data value based on its threshold (lower and upper bound) and labels the data value as "alarm" when the threshold is exceeded. Second, it calculates the duration of the occurrence of the alarm. Finally, in the third step, a domain expert is required to assess the results from the previous two steps and to determine, thereby, whether the alarm is true or false. There are drawbacks of the current evaluation method. It suffers from a high false-alarm ratio, and moreover, given the vast amount of sensor data to be assessed by the domain expert, the process of evaluation is prolonged and inefficient. In this paper, we propose a method for automatic false-alarm labeling that mimics how the domain expert determines false alarms. The domain expert determines false alarms by evaluating two critical factors, specifically the duration of alarm occurrence and identification of anomalies before or while the alarm occurs. In our proposed method, Hierarchical Temporal Memory (HTM) is utilized to detect anomalies. It is an unsupervised approach that is suitable to our main data characteristic, which is the lack of an example of the normal form of sensor data. The result shows that the technique is effective for automatic labeling of false alarms in sensor data.

• Convergence Security Journal
• /
• v.20 no.4
• /
• pp.217-225
• /
• 2020

In recent years, the "social distance" has drastically reduced overseas travelers. On the other hand, for personal safety and security, it is expected that interest and demand for CCTV, electric alarm and signaling devices, electric diagnostics and medical devices will increase significantly. The purpose of this paper is to find out the effect of airport transfer passengers and exports of CCTV, electrical diagnostics and medical devices, electrical alarms and signaling devices on exports to Korea, and the synchronism of each variable. To this end, this study used a total of 231 monthly data from January 2000 to April 2020 in the National Statistics Service. As a result of empirical analysis, CCTV and electrical diagnostics and medical devices showed relatively high synchronization with respect to exports to Korea. Electric alarms & signaling devices and transit passengers also showed a certain level of synchronization with exports, but were relatively weak.

• Neonatal Medicine
• /
• v.17 no.2
• /
• pp.245-249
• /
• 2010

Purpose: Numerous false alarms by pulse oximetry, which is widely used in neonatal intensive care unit, can delay response to true alarms. Masimo $SET^{(R)}$ was introduced lately, to overcome false alarms by motion. We compared the clinical performance of two devices (Nellcor $N-595^{(R)}$ and Masimo $SET^{(R)}$) for the evaluation of the false alarm frequency during usual motion artifacts and stable state. Methods: A total of 20 preterm infants weighing 1,000-2,500 g were enrolled in the study. The sensors of two devices were placed on the different feet on the same infants, and both devices were programmed to emit an alarm for episode of hypoxemia (SpO2$\leq$85%). The false alarms were defined as episodes of poor correlation with ECG heart rate, poor waveforms, and the absence of obvious signs of hypoxia. We compared the frequency of false alarms between the two devices. Results: The mean chronological age was 20.8 days and the mean body weight was 1,668 g on the study day. The frequency of total false alarm was significantly fewer for Masimo $SET^{(R)}$ pulse oximetry (48 in Nellcor $N-595^{(R)}$, 27 in Masimo $SET^{(R)}$) although the false alarm during usual motion artifacts was not significantly between two devices (32 in Nellcor $N-595^{(R)}$, 19 in Masimo $SET^{(R)}$). Conclusion: The Masimo $SET^{(R)}$ pulse oximetry has fewer false alarm rates and identified more true hypoxic events than Nellcor $N-595^{(R)}$ pulse oximetry. Therefore, it is useful for adequate oxygen therapy and helps to decrease unnecessary handling by clinicians and nurses.

• Journal of Internet Computing and Services
• /
• v.22 no.4
• /
• pp.83-98
• /
• 2021

The purpose of this study to find the factors influencing the fire alarms using IoT firefighting facility management system data of Seoul Fire & Disaster Headquarters, and to present academic implications for establishing an effective prevention system of fire situation. As the number of high and complex buildings increases and former bulidings are advanced, the fire detection facilities that can quickly respond to emergency situations are also increasing. However, if the accuracy of the fire situation is incorrectly detected and the accuracy is lowered, the inconvenience of the residents increases and the reliability decreases. Therefore, it is necessary to improve accuracy of the system through efficient inspection and the internal environment investigation of buildings. The purpose of this study is to find out that false detection may occur due to building characteristics such as usage or time, and to aim of emphasizing the need for efficient system inspection and controlling the internal environment. As a result, it is found that the size(total area) of the building had the greatest effect on the fire alarms, and the fire alarms increased as private buildings, R-type receivers, and a large number of failure or shutoff days. In addition, factors that influencing fire alarms were different depending on the main usage of the building. In terms of time, it was found to follow people's daily patterns during weekdays(9 am to 6 pm), and each peaked around 10 am and 2 pm. This study was claimed that it is necessary to investigate the building environment that caused the fire alarms, along with the system internal inspection. Also, it propose additional recording of building environment data in real-time for follow-up research and system enhancement.