• Journal of Power Electronics
• /
• v.5 no.3
• /
• pp.198-205
• /
• 2005

The mechanical system of a drive can often be modeled as a two- or three-mass-system. The load is coupled to the driving motor by a shaft able to perform torsion oscillations. For the automatic tuning of the control, it is necessary to know the mathematical description of the system and the corresponding parameters. As the manpower and setup-time necessary during the commissioning of electrical drives are major cost factors, the development of self-operating identification strategies is a task worth pursuing. This paper presents an identification method which can be utilized for the assisted commissioning of electrical drives. The shaft assembly can be approximated as a two-mass non-rigid mechanical system with four parameters that have to be identified. The mathematical background for an identification procedure is developed and some important implementation issues are addressed. In order to avoid the excitation of the system with its natural resonance frequency, the frequency response can be obtained by exciting the system with a Pseudo Random Binary Signal (PRBS) and using the cross correlation function (CCF) and the auto correlation function (ACF). The reference torque is used as stimulation and the response is the mechanical speed. To determine the parameters, especially in advanced control schemes, a numerical algorithm with excellent convergence characteristics has also been used that can be implemented together with the proposed measurement procedure in order to assist the drive commissioning or to achieve an automatic setting of the control parameters. Simulations and experiments validate the efficiency and reliability of the identification procedure.

• Science of Emotion and Sensibility
• /
• v.21 no.3
• /
• pp.83-102
• /
• 2018

The process model of emotion regulation suggests that cognitive reappraisal and expressive suppression engage at different time points in the regulation process. Although multiple brain regions and networks have been identified for each strategy, no articles have explored changes in network characteristics or network connectivity over time. The present study examined (a) the whole-brain network and six other resting-state networks, (b) their modularity and global efficiency, which is an index of the efficiency of information exchange across the network, (c) the degree and betweenness centrality for 160 brain regions to identify the hub nodes with the most control over the entire network, and (d) the intra-network and inter-network functional connectivity (FC). Such investigations were performed using a traditional large-scale FC analysis and a relatively recent sliding window correlation analysis. The results showed that the right inferior orbitofrontal cortex was the hub region of the whole-brain network for both strategies. The present findings of temporally altering functional activity of the networks revealed that the default mode network (DMN) activated at the early stage of reappraisal, followed by the task-positive networks (cingulo-opercular network and fronto-parietal network), emotion-processing networks (the cerebellar network and DMN), and sensorimotor network (SMN) that activated at the early stage of suppression, followed by the greater recruitment of task-positive networks and their functional connection with the emotional response-related networks (SMN and occipital network). This is the first study that provides neuroimaging evidence supporting the process model of emotion regulation by revealing the temporally varying network efficiency and intra- and inter-network functional connections of reappraisal and suppression.

• Journal of Korea Multimedia Society
• /
• v.19 no.12
• /
• pp.2014-2023
• /
• 2016

Web presence is one of the key issues for extensive deployment of Internet-of-Things (IoT). An obstacle to overcome for Web presence is relatively low computing power of IoT devices. In this paper, we present implementation of an IoT platform based on Constrained Application Protocol (CoAP) which is a web transfer protocol proposed by Internet Engineering Task Force (IETF) for the low performance IoT devices such as Wireless Sensor Network (WSN) nodes and micro-controllers. To qualify the performance of CoAP-based IoT system for such an application as smart grid, we designed a test platform consisting of Raspberry Pi2, Kmote WSN node and a desktop PC. Using open source softwares, CoAP was implemented on top of the platform. Leveraging the GET command defined at CoAP specification, performance of the system was measured in terms of round-trip time (RTT) from web application to the Kmote sensor node. To investigate abnormal cases among the test results, hop-by-hop delays were measured to analyze resulting data. The average response time of CoAP-based communication except the abnormal data was reduced by 23% smaller than the previous research result.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.7
• /
• pp.2977-2997
• /
• 2018

In big data era, fresh data grows rapidly every day. More than 30,000 gigabytes of data are created every second and the rate is accelerating. Many organizations rely heavily on real time streaming, while big data stream computing helps them spot opportunities and risks from real time big data. Storm, one of the most common online stream computing platforms, has been used for big data stream computing, with response time ranging from milliseconds to sub-seconds. The performance of Storm plays a crucial role in different application scenarios, however, few studies were conducted to evaluate the performance of Storm. In this paper, we investigate the performance of Storm under different application scenarios. Our experimental results show that throughput and latency of Storm are greatly affected by the number of instances of each vertex in task topology, and the number of available resources in data center. The fault-tolerant mechanism of Storm works well in most big data stream computing environments. As a result, it is suggested that a dynamic topology, an elastic scheduling framework, and a memory based fault-tolerant mechanism are necessary for providing high throughput and low latency services on Storm platform.

• Convergence Security Journal
• /
• v.17 no.2
• /
• pp.69-80
• /
• 2017

Due to the advanced IT environment, the role of Security Monitoring & Control becomes more important as the cyber-crime is becoming intelligent, diversified, and advanced. In contrast to the way it relied solely on security devices such as Firewall and IDS in the past, Security Monitoring & Control tasks responding to cyber attacks through real-time monitoring have become wide spread and their role is also important. In response to current cyber threats, since security equipment alone can not be guaranteed a stable defense, the task of Security Monitoring & Control became essential to operate and monitor security equipment and to respond in real time. In this study, we will discuss how to configure network security system effectively and how to improve the real-time Security Monitor & Control.

• Korean Journal of School Psychology
• /
• v.16 no.2
• /
• pp.207-230
• /
• 2019

This study examined the effect of Attention Feedback Awareness and Control Training(A-FACT) on attention bias and generalized anxiety symptoms in college students. A total of 31 college students with at least 10 points on the Generalized Anxiety Disorder 7-item (GAD-7) scale or at least 56 points on the Korean version of the Penn State Worry Questionnaire (K-PSWQ) with attention bias were randomly assigned to one of three groups: A-FACT( n = 11), Attention Bias Modification (ABM)(n = 10) and Active Placebo Control (APC)(n = 10). Participants in A-FACT group received real-time feedback on attention bias based on their Baseline Neutral Response time(BNR) during A-FACT using a dot probe task. Participants in the ABM group received standard ABM, and those in the APC performed a dot probe task that they were informed was a program to reduce attention bias, but feedback was not provided. A total of eight sessions was conducted twice a week over a 4-week period. After every two sessions, GAD-7, K-PSWQ and K-STAI were rated. The effect of attention bias modification training was rated by changes in the Attention Bias Score(ABS), and in GAD-7, K-PSWQ and K-STAI scores. The results of repeated measure ANOVA indicated that the A-FACT group showed a significant decrease in ABS as well as in GAD-7, K-PSWQ and K-STAI scores compared to the other groups. Current results suggest that self-regulatory control of attention, that is, recognition of bias through feedback in A-FACT, may be effective in alleviating attention bias and generalized anxiety symptoms by recognizing bias through feedback on bias in attention bias modification training.

• Proceedings of the IEEK Conference
• /
• 2002.07a
• /
• pp.98-101
• /
• 2002

This paper reports a parallel architecture in a HMM based speech recognition system for a low-power LSI design. The proposed architecture calculates output probability of continuous HMM (CHMM) by using concurrent and pipeline processing. They enable to reduce memory access and have high computing efficiency. The novel point is the efficient use of register arrays that reduce memory access considerably compared with any conventional method. The implemented system can achieve a real time response with lower clock in a middle size vocabulary recognition task (100-1000 words) by using this technique.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2008.04a
• /
• pp.45-46
• /
• 2008

The conventional biased vertical alignment (BVA) mode has several advantages such as rubbing- and protrusion-free, wide-viewing angle and stable LC dynamics against external pressure. However manufacturing process of BVA mode is difficult task because the pixel and bias electrode signal are different in each frame. To solve this problem, we investigated the pattern free vertical alignment (PFVA) by using the UV-curable reactive mesogen (RM), in which the LC molecules were made to be pre-tilted. Eventually transmittance and response time in PFVA mode were found to be improved as compared to BVA mode.

• Proceedings of the KSPS conference
• /
• 2006.05a
• /
• pp.71-74
• /
• 2006

The purpose of this study is to observe how Korean listeners detect a target phoneme with 'Focus' represented by prosodic prominence and question-induced semantic emphasis. According to the automated phoneme detection task using E-Prime, Korean listeners detected phoneme targets more rapidly when the target-bearing words were in prominence position and in question-induced position. However, when phoneme targets were in prominence position, response time was much faster than in question-induced position. The results suggest that the prosodic prominence which is explicit method of focus representation be more effective than question-inducing, implicit method of it, in phoneme detecting.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.5
• /
• pp.1998-2014
• /
• 2016

In recent years, cloud computing services based on smart phones and other mobile terminals have been a rapid development. Cloud computing has the advantages of mass storage capacity and high-speed computing power, and it can meet the needs of different types of users, and under the background, mobile cloud computing (MCC) is now booming. In this paper, we have put forward a new classification-based virtual machine placement (CBVMP) algorithm for MCC, and it aims at improving the efficiency of virtual machine (VM) allocation and the disequilibrium utilization of underlying physical resources in large cloud data center. By simulation experiments based on CloudSim cloud platform, the experimental results show that the new algorithm can improve the efficiency of the VM placement and the utilization rate of underlying physical resources.