• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.6
• /
• pp.1530-1544
• /
• 2023

Data monitoring is an important foundation of modern science. In most cases, the monitoring data is time-series data, which has high application value. The deep learning algorithm has a strong nonlinear fitting capability, which enables the recognition of time series by capturing anomalous information in time series. At present, the research of time series recognition based on deep learning is especially important for data monitoring. Deep learning algorithms require a large amount of data for training. However, abnormal sample is a small sample in time series, which means the number of abnormal time series can seriously affect the accuracy of recognition algorithm because of class imbalance. In order to increase the number of abnormal sample, a data augmentation method called GANBATS (GAN-based Bi-LSTM and Attention for Time Series) is proposed. In GANBATS, Bi-LSTM is introduced to extract the timing features and then transfer features to the generator network of GANBATS.GANBATS also modifies the discriminator network by adding an attention mechanism to achieve global attention for time series. At the end of discriminator, GANBATS is adding averagepooling layer, which merges temporal features to boost the operational efficiency. In this paper, four time series datasets and five data augmentation algorithms are used for comparison experiments. The generated data are measured by PRD(Percent Root Mean Square Difference) and DTW(Dynamic Time Warping). The experimental results show that GANBATS reduces up to 26.22 in PRD metric and 9.45 in DTW metric. In addition, this paper uses different algorithms to reconstruct the datasets and compare them by classification accuracy. The classification accuracy is improved by 6.44%-12.96% on four time series datasets.

• Journal of Korean Society for Atmospheric Environment
• /
• v.23 no.6
• /
• pp.689-698
• /
• 2007

Particular attention is paid to the validity of PM-10 measurement using beta attenuation method. In this study, the inter-comparison studies were undertaken for PM-10 sampler with different measuring methods. The three beta attenuation monitoring instruments (BAM1020, FH C-14, and DIGS-150) and filter based gravitational method using High Volume Air Sampler were collocated and mass concentrations were compared from August to November, 2006. The results of the investigation show that beta attenuation monitoring instruments are comparable with gravitational method within 10% of measurement error. For specific conditions under high humidity and high concentrations, the inter-comparison results also showed a relatively good agreement and this can be explained as the effect of inlet heating of beta attenuation instrument. Subsequently, this study shows that beta attenuation monitoring instruments can be equivalently used with reasonable validity when compared gravimetric method.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.58 no.2
• /
• pp.175-184
• /
• 2022

This study analyzed the allocation of the skipper's attention during fishing operation in the wheelhouse of a Korean coastal composite fishing vessel by using video observation. To summarize the results, the ratio of lookout, radar and GPS monitoring, which is essential for prevention of collision at sea, was significantly lower than that of other fishing operation due to the attention concentration on the work place during hauling line. In order to reduce exposure to risk of collisions due to concentration of attention to certain tasks such as line hauling, it is necessary to develop an alert system that can notify the approach of other ships or obstruction throughout the ship using information from radar or the automatic identification system. In addition, the order of attention allocation to devices and facilities obtained in this study is expected to be used as basic data for device or facility layout based on the principle of usage frequency in designing wheelhouse for coastal composite fishing vessels in the future.

• Journal of the Korean Institute of Navigation
• /
• v.19 no.2
• /
• pp.115-120
• /
• 1995

Recently, the ship automation technology(SAT) has received great attention for the efficient management of the ship with minimum human efforts. Among the SAT, a distance measuring system, the key element is the signal processing unit for the interpretion of the received signal from the remote sensing of the oil tank. In this paper, the tank monitoring system using FM-CW is described for the oil tank level guage measurement with an emphsis of signal processing unit.

• 대한예방의학회:학술대회논문집
• /
• 1994.02b
• /
• pp.332-335
• /
• 1994

Compared to other variables being considered in therapeutics, patient compliance has long been given minor attention although it affects every aspect of medical care; Limited methodology of compliance measurement, in particular, has hampered major progress in research, and pre-conceptions have been reiterated. However, there is a recent surge in interest derived from new data revealed by reliable methods, i.g. continuous medication (compliance) monitoring. The visualization of dynamics in drug regimen compliance over time offers unique opportunities, both to scientific drug evaluation and therapeutics in medical practice. New perspectives related to the descriptive and explanatory side of the problem are outlined by giving examples from various therapeutic fields.

• Smart Structures and Systems
• /
• v.10 no.3
• /
• pp.209-228
• /
• 2012

Structural health monitoring with wireless sensor networks has received much attention in recent years due to the ease of sensor installation and low deployment and maintenance costs. However, sensor network technology needs to solve numerous challenges in order to substitute conventional systems: large amounts of data, remote configuration of measurement parameters, on-site calibration of sensors and robust networking functionality for long-term deployments. We present a structural health monitoring network that addresses these challenges and is used in several deployments for monitoring of bridges and buildings. Our system supports a diverse set of sensors, a library of highly optimized processing algorithms and a lightweight solution to support a wide range of network runtime configurations. This allows flexible partitioning of the application between the sensor network and the backend software. We present an analysis of this partitioning and evaluate the performance of our system in three experimental network deployments on civil structures.

• Journal of Korean Institute of Industrial Engineers
• /
• v.36 no.3
• /
• pp.154-163
• /
• 2010

Process monitoring of output variables affecting final performance have been mainly executed in semiconductor manufacturing process. However, even earlier detection of causes of output variation cannot completely prevent yield loss because a number of wafers after detecting them must be re-processed or cast away. Semiconductor manufacturers have put more attention toward monitoring process inputs to prevent yield loss by early detecting change-point of the process. In the paper, we propose the method to efficiently monitor functional input variables in multi-phase semiconductor manufacturing process. Measured input variables in the multi-phase process tend to be of functional structured form. After data pre-processing for these functional input data, change-point analysis is practiced to the pre-processed data set. If process variation occurs, key variables affecting process variation are selected using contribution plot for monitoring efficiency. To evaluate the propriety of proposed monitoring method, we used real data set in semiconductor manufacturing process. The experiment shows that the proposed method has better performance than previous output monitoring method in terms of fault detection and process monitoring.

• Transactions on Electrical and Electronic Materials
• /
• v.7 no.5
• /
• pp.247-251
• /
• 2006

The traction DC feeder cable is one of the key devices for the safety operation of subway system, but for low voltage DC feeder cable (<3000 V) for subway, little attention has been paid by investigators on its online monitoring technology. With an introduction of cable laying and operation environment for the cable, this paper investigated the on-line monitoring technology of 1500 V DC feeder cable of subway. Firstly, in the text, the fault model of 1500 V DC cable was proposed based on the analysis of the fault type of the DC feeder cable, and then put forward synthetically on-line monitoring discharge signal and DC leakage current signal to assess DC feeder cable insulating state. The results of laboratory experiment prove that the proposed methods are feasible and can be implemented on-line monitor on DC feeder cable of subway.

• Research in Mathematical Education
• /
• v.23 no.4
• /
• pp.219-233
• /
• 2020

Teachers' intervention in small groups is a research area that needs more research attention. Ehrenfeld and Horn (2020) identified teachers' group work monitoring routines that consist of four recurrent talk moves: 1) Initiation, 2) Entry, 3) Focus, and 4) Exit. To better understand prospective teachers' (PTs) intervention in small groups in mathematics classrooms, I investigated how PTs' intervention actions and purposes are related to the monitoring routines, particularly, in terms of Focus moves. I analyzed 26 PTs' responses to four written scenarios, each of which depicts interactions among students in a small group. I identified 1) types of PTs' math talk, 2) types of PTs' non-math talk, 3) types of intervention purposes, and 4) patterns of intervention actions and purposes by scenario. This study contributes to understanding PTs' intervention actions and purposes in mathematics instruction.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1998.10a
• /
• pp.413-414
• /
• 1998

This paper presents a real-time Spatial Decision Support System(SDSS) for security camera image monitoring. Other SDSSs are not real-time systems, i.e., they show the images that are already transformed into data format such as virtual reality. In our system, the image is broadcasted in real-time since the purpose of the security camera needs to do it in real-time. With these real-time images, other systems do not add up anything more; the screen just shows the images from the camera. However in our system, we created a motion detection system so that the supervisor(Judge) of a sec.urity monitoring system does not have to pay attention to it constantly. In other words, we created a judge advising system for the supervisor of the security monitoring system. Most of small objects do not need the supervisor's attention since they could be birds, cats, dogs, etc. if they show up in the screen image. In this new system the system only report the unusual change to the supervisor by calculating the motion and size of objects in the screen. Thus the supervisor can be liberated from the 24-hour concentration duty; instead he/she can be only alerted when the real security threat such as a big moving object like an human intruder appears. Thus this system can be called a real-time Spatial DSS. The utility of this system is proved mathematically by using the concept of entropy. In other words, big objects like human intruders increase the entropy of the screen images significantly therefore the supervisor must be alerted. Thus by proving its utility of the system theoretically, we can claim that our new real-time SDSS is superior to others which do not use our technique.hnique.