• Speech Sciences
• /
• v.8 no.4
• /
• pp.119-129
• /
• 2001

Language is one aspect of cognition, along with attention and concentration, learning and memory, visuospatial abilities, and executive function. The purpose of this study was to determine the effect of language intervention by cognitive approach on language expressive performance in a patient with conduction aphasia. This study used several tasks such as Attention and concentration task, visual memory tasks, memory tasks, categorization, divergent thinking, self-monitoring and evaluate thinking. The effects of treatment were evaluated by periodic probing of both trained and untrained familiar words in three tasks; picture naming, answering to questions and telling stories. The results showed improvements both in trained and untrained words. Therefore, we concluded that expressive language performance of this aphasic patient is amenable to this intervention, and that cognitive therapy approach can be useful.

• Journal of Information Processing Systems
• /
• v.17 no.6
• /
• pp.1071-1082
• /
• 2021

Since the smart factory has been recently recognized as an industrial core requirement, various mechanisms to ensure efficient and stable operation have attracted much attention. This attention is based on the fact that in a smart factory environment where operating processes, such as facility control, data collection, and decision making are automated, the disruption of processes due to problems such as facility anomalies causes considerable losses. Although many studies have considered methods to prevent such losses, few have investigated how to effectively apply the solutions. This study proposes a Kubernetes based system applied in a smart factory providing effective operation and facility management. To develop the system, we employed a useful and popular open source project, and adopted deep learning based anomaly detection model for multi-sensor anomaly detection. This can be easily modified without interruption by changing the container image for inference. Through experiments, we have verified that the proposed method can provide system stability through nondisruptive maintenance, monitoring and non-disruptive updates for anomaly detection models.

• Journal of Korea Multimedia Society
• /
• v.25 no.2
• /
• pp.421-431
• /
• 2022

The purpose of this research is to determine the point of fixation of the driver during the process of driving. Based on the results of this research, the driving instructor can make a judgement on what the trainee stare on the most. Traffic accidents have become a serious concern in modern society. Especially, the traffic accidents among unskilled and elderly drivers are at issue. A driver should put attention on the vehicles around, traffic signs, passersby, passengers, road situation and its dashboard. An eye-tracking-based application was developed to analyze the driver's gaze behavior. It is a prototype for real-time eye tracking for monitoring the point of interest of drivers in driving practice. In this study, the driver's attention was measured by capturing the movement of the eyes in real road driving conditions using these tools. As a result, dwelling duration time, entry time and the average of fixation of the eye gaze are leading parameters that could help us prove the idea of this study.

• International journal of advanced smart convergence
• /
• v.13 no.1
• /
• pp.48-56
• /
• 2024

The application of artificial intelligence (AI) is becoming increasingly important to coping with air pollution. AI is effective in coping with it in various ways including air pollution forecasting, monitoring, and control, which is attracting a lot of attention. This attention has created high need for analyzing studies on AI and air pollution. To contribute for satisfying it, this study performed bibliometric analyses on the studies on AI and air pollution from 2012 to 2022 using the Web of Science database. This study analyzed them in various aspects such as the trend in the number of articles, the trend in the number of citations, the top 10 countries of origin, the top 10 research organizations, the top 10 research funding agencies, the top 10 journals, the top 10 articles in terms of total citations, and the distribution by languages. This study not only reports the bibliometric analysis results but also reveals the eight distinct features in the research steam in studies on AI and air pollution, identified from the bibliometric analysis results. They are expected to make a useful contribution for understanding the research stream in AI and air pollution.

• Smart Structures and Systems
• /
• v.25 no.3
• /
• pp.285-299
• /
• 2020

Long term structural health monitoring has gained wide attention among civil engineers in recent years due to the scale and severity of infrastructure deterioration. Establishing effective damage indicators and proposing enhanced monitoring methods are of great interests to the engineering practices. In the case of bridge health monitoring, long term structural vibration measurement has been acknowledged to be quite useful and utilized in the planning of maintenance works. Previous researches are majorly concentrated on linear time series models for the measurement, whereas nonlinear dependences among the measurement are not carefully considered. In this paper, a new bridge health monitoring method is proposed based on the use of long term vibration measurement. A combination of the fundamental ARMA model and copula theory is investigated for the first time in detecting bridge structural damages. The concept is applied to a real engineering practice in Japan. The efficiency and accuracy of the copula based damage indicator is analyzed and compared in different window sizes. The performance of the copula based indicator is discussed based on the damage detection rate between the intact structural condition and the damaged structural condition.

• International Journal of Internet, Broadcasting and Communication
• /
• v.12 no.4
• /
• pp.109-121
• /
• 2020

As a decrease in labor became a serious issue in the manufacturing industry, smart factory technology, which combines IT and the manufacturing business, began to attract attention as a solution. In this study, we have designed and implemented a real-time remote management system for smart factories, which is connected to an IoT sensor and gateway, for plastic manufacturing plants. By implementing the REST API in which an IoT sensor and smart gateway can communicate, the system enabled the data measured from the IoT sensor and equipment status data to the real-time monitoring system through the gateway. Also, a web-based management dashboard enabled remote monitoring and control of the equipment and raw material processing status. A comparative analysis experiment was conducted on the suggested system for the difference in processing speed based on equipment and measurement data number change. The experiment confirmed that saving equipment measurement data using cache mechanisim offered faster processing speed. Through the result our works can provide the basic framework to factory which need implement remote management system.

• Structural Monitoring and Maintenance
• /
• v.3 no.4
• /
• pp.395-406
• /
• 2016

Modal parameter identification has received much attention recently for their usefulness in earthquake engineering, damage detection and structural health monitoring. The identification method based on Matrix Pencil technique is adopted in this paper to identify structural modal parameters, such as natural frequencies, damping ratios and modal shapes using impulse vibration responses. This method can also be applied to dynamic responses induced by stationary and white-noise inputs since the auto- and cross-correlation function of the two outputs has the same form as the impulse response dynamic functions. Matrix Pencil method is very robust to noise contained in the measurement data. It has a lower variance of estimates of the parameters of interest than the Polynomial Method, and is also computationally more efficient. The numerical simulation results show that this technique can identify modal parameters accurately even if the noise level is high.

• Proceedings of the Korean Society of Plant Pathology Conference
• /
• 2003.10a
• /
• pp.80.2-81
• /
• 2003

Since hot peppers (Capsicum annuum L.) are getting reputation as an important source of vitamins, medicine and many other areas, consumption and cultivation is being increased in the world. In spite of this usefulness, so little attention has been given to the hot pepper plants. To date, less than 500 nucleotide sequences including redundancy has been identified in NCBI database. Therefore we started to EST sequencing project for initial characterization of the genome, because of the large genome size of hot pepper (2.7 3.3 ${\times}$ 109 bp), To date, a set of 10,000 non-redundant genes were identified by EST sequencing for microarray-based gene expression studies. At present, cDNA microarrays containing 4,685 unigene clones are used for hybridization labeled targets derived from pathogen infected and uninoculated leaf tissues. Monitoring of gene expression profiles of hot pepper interactions with soybean pustule pathogen (Xag；Xanthomonas axonopodis pv. glycine) will be presented.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.20 no.3
• /
• pp.209-213
• /
• 2015

With the increasing popularity of renewable generation systems and the advancement of power electronics, DC distribution systems have recently received considerable research attention. DC distribution has numerous advantages, including reliability, power quality, and efficiency. Owing to these advantages, DC distribution has been applied to data centers and power quality-sensitive electronic load conditions. Because grounding electrodes in DC are much more susceptible to corrosion than in AC, the IT system defined in IEC Standard 60364 may be a good candidate for an earthing method for DC distribution systems. In addition, IEC Standard 61557 specifies the requirements for insulation monitoring devices (IMD) for protection of the IT system, which continuously monitors the insulation resistances between the power lines and the earth. This paper discusses the development and evaluation of IMD to promote the reliability of distribution systems and increase safety of humans and facilities.

• Proceedings of the KSR Conference
• /
• 2007.11a
• /
• pp.1913-1919
• /
• 2007

Substantive provisions of the concept of an estimation and safety of complex technical systems are envisaged. New problems are assume orientation to use of the formalized methods of an estimation of residual resources of reliability of objects, and also development of other methodological base in creation of complex technical systems that is connected with detailed elaboration of attention to a safety at all stages of creation of systems: from designing until operation. In this connection existing large objects should be provided by the developed systems of engineering monitoring and diagnostics.