• Journal of the Korea Safety Management & Science
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• v.14 no.4
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• pp.229-238
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• 2012

Within last 10 years, internet has become a daily activity, and humankind had to face the Data Deluge, a dramatic increase of digital data (Economist 2012). Due to exponential increase in amount of digital data, large scale data has become a big issue and hence the term 'big data' appeared. There is no official agreement in quantitative and detailed definition of the 'big data', but the meaning is expanding to its value and efficacy. Big data not only has the standardized personal information (internal) like customer information, but also has complex data of external, atypical, social, and real time data. Big data's technology has the concept that covers wide range technology, including 'data achievement, save/manage, analysis, and application'. To define the connected technology of 'big data', there are Big Table, Cassandra, Hadoop, MapReduce, Hbase, and NoSQL, and for the sub-techniques, Text Mining, Opinion Mining, Social Network Analysis, Cluster Analysis are gaining attention. The three features that 'bid data' needs to have is about creating large amounts of individual elements (high-resolution) to variety of high-frequency data. Big data has three defining features of volume, variety, and velocity, which is called the '3V'. There is increase in complexity as the 4th feature, and as all 4features are satisfied, it becomes more suitable to a 'big data'. In this study, we have looked at various reasons why companies need to impose 'big data', ways of application, and advanced cases of domestic and foreign applications. To correspond effectively to 'big data' revolution, paradigm shift in areas of data production, distribution, and consumption is needed, and insight of unfolding and preparing future business by considering the unpredictable market of technology, industry environment, and flow of social demand is desperately needed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3412-3432
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• 2019

Recent advances in radio frequency (RF) power transfer provide a promising technology to power sensor nodes. Adoption of mobile chargers to replenish the nodes' energy has recently attracted a lot of attention and the mobility assisted energy replenishment provides predictable and sustained power service. In this paper, we study the joint optimization of mobile charging and data gathering in sensor networks. A wireless multi-functional vehicle (WMV) is employed and periodically moves along specified trajectories, charge the sensors and gather the sensed data via one-hop communication. The objective of this paper is to maximize the uplink throughput by optimally allocating the time for the downlink wireless energy transfer by the WMV and the uplink transmissions of different sensors. We consider two scenarios where the WMV moves in a straight line and around a circle. By time discretization, the optimization problem is formulated as a 0-1 programming problem. We obtain the upper and lower bounds of the problem by converting the original 0-1 programming problem into a linear programming problem and then obtain the optimal solution by using branch and bound algorithm. We further prove that the network throughput is independent of the WMV's velocity under certain conditions. Performance of our proposed algorithm is evaluated through extensive simulations. The results validate the correctness of our proposed theorems and demonstrate that our algorithm outperforms two baseline algorithms in achieved throughput under different settings.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.2
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• pp.152-159
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• 2019

In general, a Doppler radar can measure only the velocity of a moving target. To measure the distance of a moving target, it is necessary to use a frequency-modulated continuous wave or pulse radar. However, the latter are very complex in terms of both hardware as well as signal processing. Moreover, the requirement of wide bandwidth necessitates the use of millimeter-wave frequency bands of 24 GHz and 77 GHz. Recently, a new kind of Doppler radar using multitone frequency has been studied to sense the distance of moving targets in addition to their speed. In this study, we show that distance sensing of moving targets is possible by adjusting only the frequency of a 2.4 GHz Doppler radar with low cost phase lock loop. In particular, we show that distance can be sensed using only alternating current information without direct current offset information. The proposed technology satisfies the Korean local standard for low power radio equipment for moving target identification in the 2.4 GHz frequency band, and enables multiple long-range sensing and radio-frequency identification applications.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.19-22
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• 2019

상완동맥은 어깨에서부터 팔꿈치까지 내려오는 상완골의 내측부에 존재하며 혈압을 측정할 때 사용되는 혈관이다. 이 혈관은 골절로 인해 찢어지거나, 또는 혈액순환에 문제가 생겨 혈관이 막히는 경우가 발생한다. 이러한 경우 혈관의 상태를 확인하기 위하여 색조 도플러 초음파 검사를 사용하지만, 사용자에 따라 영상을 통한 판단 기준이 다르다는 문제점이 발생한다. 따라서 본 논문에서는 FCM과 Fuzzy Decision Tree를 이용한 영상 처리를 통해 일관성 있는 판단기준을 세우기 위한 혈류의 속도를 제안한다. 색조 도플러 초음파 영상에서의 상완 동맥을 추출하여 기울기를 이용한 FCM 알고리즘을 통해 소속도를 추출한 뒤 퍼지 룰에 적용하여 의사 결정 트리로 등급을 분류하고 결과적으로 혈류 속도를 추출한다. 색조 도플러 초음파 영상에서 환자의 개인 정보를 보호하기 위해 개인 정보 영역을 제거하여 ROI 영역을 추출하고 ROI 영역을 이진화를 통하여 상완동맥이 있는 영역을 추출한다. 이진화 된 ROI 영역에서 혈관 영상의 혈류 방향으로의 무게중심을 설정하고 각각의 픽셀과 무게중심 선과의 거리를 이용하여 소속도를 추출한 후 FCM을 사용하여 최적의 기울기를 선정한다. FCM을 통해 추출한 최종 소속도를 이용하여 퍼지 룰에 적용한 뒤 계산된 T-norm과 소속도의 분산을 이용하여 의사 결정 트리를 형성 트리의 단말 노드들은 각 픽셀을 분류한다. 분류되어진 데이터들의 노드별 소속도 평균을 구한 뒤 디퍼지화를 통해 COG(Center of Gravity)를 계산한다. 마지막으로 그 값을 이용하여 혈류 속도에 영향을 미치는 정도를 계산한 뒤 최종 혈류의 속도를 제안한다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.5
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• pp.529-536
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• 2019

In this paper, the signals of the sensor for extracting characteristic parameters of the rotor are collected and the performance of the extraction technique is analyzed. To this end, a vibration test league was developed for conducting model tests to analyze the signal characteristics under normal operation. As a result, it is judged that no change in the measured the raw data amplitude will occur in the acceleration sensor with the unbalanced mass measured from the acceleration sensor. Performing FFT showed a significant increase in amplitude of the rotational frequency of 20 Hz as the unbalanced mass increased. The analysis results according to the change in the unequal mass of the speed sensor also showed a significant increase in the 1X Harmonics component, such as the acceleration sensor. There was no change in the amplitude of the acceleration sensor data when the misalignment occurred, and for the Envelope data, the amplitude of 2X (40 Hz) was increased depending on the degree of misalignment. The velocity sensor at change of misalignment also showed similar results to the acceleration sensor, and the peak was reduced at 600 Hz as the load increased in the frequency spectrum.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.35-42
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• 2021

In this paper, we propose a deep learning-based person re-identification method using a three-dimensional RGB-Depth Xtion2 camera considering joint coordinates and dynamic features(velocity, acceleration). The main idea of the proposed identification methodology is to easily extract gait data such as joint coordinates, dynamic features with an RGB-D camera and automatically identify gait patterns through a self-designed one-dimensional convolutional neural network classifier(1D-ConvNet). The accuracy was measured based on the F1 Score, and the influence was measured by comparing the accuracy with the classifier model (JC) that did not consider dynamic characteristics. As a result, our proposed classifier model in the case of considering the dynamic characteristics(JCSpeed) showed about 8% higher F1-Score than JC.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1417-1423
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• 2020

This paper proposes a waypoint guidance algorithm for the Autonomous Underwater Vehicle(AUV). The proposed simplified guidance algorithm is presented, which is combined LOS guidance and cross-track guidance for path following. Cross-track error is calculated using the position of the AUV and reference path. LOS guidance and cross-track guidance are appropriately changed according to cross-track error. And the stability of the system has been improved using variable cross-track control gain by cross-track error. Also, in this paper, navigation hardware in-the loop simulation(HILS) is implemented to verify navigation algorithm of AUV that performs combined navigation using inertial navigation device and doppler velocity log(DVL). Finally, we design integrated system HILS (including navigation HILS) for performance verification of guidance algorithm of the autonomous underwater vehicle. By comparing the sea test result with HILS result, the proposed guidance algorithm and HILS configuration were confirmed be correct.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1319-1324
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• 2020

A smart tag complements various problems caused by the expansion of the use of existing magnet cards. This emerged as a result of the need for alternative means to perform safer and more diverse functions. RFID tags are becoming increasingly ubiquitous sensor networks and Internet of Things technologies as they give everything an ID, enabling automatic recognition of objects and forming a communication network between them. In this paper, a contactless RFID smart tag reader composed of RFID tags and readers using AVR processor was developed. The system has a low frequency band of 13.56MHz and is designed by PWM method of communication velocity 26.48kbps. The developed RFID smart tag board showed a faster response rate than the typical RFID system as a result of the simulation, and the actual experiment also showed an improvement in response rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1817-1825
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• 2021

Omnidirectional mobile robots can be mobile in any direction without changing the robot's direction, making them easy to apply in many applications and providing excellent maneuverability. Omnidirectional mobile robots have non-linear dynamic components such as friction, making them difficult to model accurately. In this paper, we linearize the mobile robot system using the mobile robot's inverse dynamics and integral sliding mode control method to remove these nonlinear components. And the position and velocity gains are optimized using a genetic algorithm to realize the optimal performance of the proposed system control method. As a result of the performance evaluation, the genetic algorithm's control method showed superior performance than the control method with an arbitrary gain. And the proposed inverse dynamic and integral sliding mode control method can be applied to other control methods. It can be beneficial for designing a linear control system.

• Journal of Korean Physical Therapy Science
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• v.29 no.2
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• pp.1-13
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• 2022

Background: This research was conducted to understand balance training in trunk control, balance, and walking in stroke patients. Design: Randomized controlled trial. Methods: The subjects included 40 stroke patients, of whom 20 undertook balance training using visual information and the other 20 undertook balance training using balance boards. Using visual feedback, the balance training group used a training program within the static balanced evaluation tool, while the balance training group trained using a balance board. All subjects underwent 20 mins of neurodevelopmental treatment, and both target groups underwent 10 mins each of balance training by using either visual feedback or a balance board. The treatment period lasted a total of 4 weeks, twice a day. Trunk control before and after training was evaluated with the Trunk Impairment Scale. Balance capability was assessed by the Berg Balance Scale, Functional Reach Test, Timed Up and Go test, and Static balance measurement tool. Walking capacity was measured using gait measuring equipment, and cadence and velocity were measured. Results: Both groups showed a significant improvement in their interstitial control, balance, and gait ability after the experiments compared to before the experiments (p<0.05). The difference between the two groups was not significant. The visual feedback balance training group showed a more substantial improvement than the balance board training group. Conclusion: In this study, we found that the balance training combined with visual feedback contributes to improving trunk control, balance, and gait in patients with hemiplegia due to stroke. In addition to this, I believe that balanced training combined with visual feedback can be used as a training method when considering patients who lack interstitial control, balance, and gait ability.