• Journal of the Semiconductor & Display Technology
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• v.23 no.3
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• pp.148-151
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• 2024

Electric scooters are used by many people as a means of transportation because they are easy to operate and get around quickly. Although electric scooters can move at high speeds, they lack safety measures such as seat belts and blocked car body, which can lead to serious injury in the event of an accident. If there are two people on board, the braking speed will be slower and the weight of the vehicle will increase its braking distance during sudden stops, leading to even more serious damage. Therefore, this paper proposes the illuminance sensors based multiuser boarding detection scheme for electric scooter, which is expected to decrease the risk of accidents and to lessen the likelihood of injury. From the performance evaluation results, it has been shown that the proposed scheme has higher detection ratio than existing schemes and has the detection accuracy of about 83% by means of the machine learning based foot position estimation for the sensed data.

• The Plant Pathology Journal
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• v.20 no.4
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• pp.308-312
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• 2004

A method based on RNA-transcript conformation polymorphism (TCP) was tested for detection of two PVY isolates in a mixed infection. Differences in electrophoretic mobility of RNA transcripts copied from PCR products of each virus isolate enabled the distinction between the two virus isolates in a mixed infection. The identities of the RNA transcripts and hence of the infecting virus isolates were determined by annealing to reference oligonucleotides containing unique strain-specific sequences visualized by retardation of transcript mobility in gel. The ratio at which both virus isolates could be detected was as low as 1:10. The suitability of this procedure for the study of mixed virus infections is discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8B
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• pp.689-698
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• 2008

The performance of a TCP protocol on MANETs has been studied in a numerous researches. One of the significant reasons of TCP performance degradation on MANETs is inability to distinguish between packet losses due to congestion from those caused by nodes mobility and as consequence broken routes. This paper presents the Cluster-Label-based Routing (CLR) protocol that is an attempt to compensate source of TCP problems on MANETs - multi-hop mobile environment. By utilizing Cluster-Label-based mechanism for Backbone, the CLR is able to concentrate on detection and compensation of movement of a destination node. The proposed protocol provides better goodput and delay performance than standardized protocols especially in cases of large network size and/or high mobility rate.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.16 no.2
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• pp.113-119
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• 2003

We report the electrical properties of copper(II)-phthalocyanine(Cu-Pc) as a hole injaction layer in organic light-emitting diode (OLED). OLEDs were constructed by the following material structure : indium tin oxaide (ITO)/ CuPc/ triphenyl-diamine (TPD)/ tris-(8-hydroxyquinoline)aluminum (Alq3)/4-(Dicyanomethlene)-2-methyl-6-(4-dimethylaminostyryl)-4H-pyran (DCM)/ Al. we observed that the change of recombination zone by using a DCM detection thin layer (6 ${\AA}$) in a Alq$_3$ emitting layer. layer. Recombination zone was moved toward the cathode as the hole mobility increased due to the heat-treatment temperature of cupc layer increased.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.341-347
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• 2022

This paper presents a comparison result of two simultaneous localization and mapping (SLAM) algorithms for navigation that have been proposed in literature. The performances of Extended Kalman Filter (EKF) SLAM under Gaussian condition, FastSLAM algorithms using Rao-Blackwellised method for particle filtering are compared in terms of accuracy of state estimations for localization of a robot and mapping of its environment. The algorithms were run using the same type of robot on indoor environment. The results show that the Particle filter based FastSLAM has the better performance in terms of accuracy of localization and mapping. The experimental results are discussed and compared.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.6
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• pp.1097-1106
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• 2011

Tactical Information Communication Network(TICN), a concept-type integrated Military Communication system that enables precise command control and decision making, is designed to advance into high speed, large capacity, long distance wireless relay transmission. To support mobility in battlefield environments, the application of Ad-hoc networking technology to its wireless communication has been examined. Ad-hoc network works properly only if the participating nodes cooperate in routing and packet forwarding. However, if selfish nodes not forwarding packets of other nodes and malicious nodes making the false accusation are in the network, it is faced to many threats. Therefore, detection and management of these misbehaving nodes is necessary to make confident in Ad-hoc networks. To solve this problem, we propose an efficient intrusion detection technique to detect and manage those two types of attacks. The simulation-based performance analysis shows that our approach is highly effective and can reliably detect a multitude of misbehaving node.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.541-556
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• 2020

Wireless networks have become integral to society as they provide mobility and scalability advantages. However, their disadvantage is that they cannot control the media, which makes them vulnerable to various types of attacks. One example of such attacks is the evil twin access point (AP) attack, in which an authorized AP is impersonated by mimicking its service set identifier (SSID) and media access control (MAC) address. Evil twin APs are a major source of deception in wireless networks, facilitating message forgery and eavesdropping. Hence, it is necessary to detect them rapidly. To this end, numerous methods using clock skew have been proposed for evil twin AP detection. However, clock skew is difficult to calculate precisely because wireless networks are vulnerable to noise. This paper proposes an evil twin AP detection method that uses a multiple-feature-based machine learning classification algorithm. The features used in the proposed method are clock skew, channel, received signal strength, and duration. The results of experiments conducted indicate that the proposed method has an evil twin AP detection accuracy of 100% using the random forest algorithm.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.88-95
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• 2022

Detecting anomalies in human movement is an important task in industrial applications, such as monitoring industrial disasters or accidents and recognizing unauthorized factory intruders. In this paper, we propose an abnormal worker movement detection system based on data stream processing and hierarchical clustering. In the proposed system, Apache Spark is used for streaming the location data of people. A hierarchical clustering-based anomalous trajectory detection algorithm is designed for detecting anomalies in human movement. The algorithm is integrated into Apache Spark for detecting anomalies from location data. Specifically, the location information is streamed to Apache Spark using the message queuing telemetry transport protocol. Then, Apache Spark processes and stores location data in a data frame. When there is a request from a client, the processed data in the data frame is taken and put into the proposed algorithm for detecting anomalies. A real mobility trace of people is used to evaluate the proposed system. The obtained results show that the system has high performance and can be used for a wide range of industrial applications.

• Journal of Sensor Science and Technology
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• v.33 no.1
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• pp.18-23
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• 2024

Humanoid robots, designed to interact in human environments, require stable mobility to ensure safety. When a humanoid robot falls, it causes damage, breakdown, and potential harm to the robot. Therefore, fall detection is critical to preventing the robot from falling. Prevention of falling of a humanoid robot requires an operator controlling a crane. For efficient and safe walking control experiments, a system that can replace a crane operator is needed. To replace such a crane operator, it is essential to detect the falling conditions of humanoid robots. In this study, we propose falling detection methods using Convolution Neural Network (CNN) model. The image data of a humanoid robot are collected from various angles and environments. A large amount of data is collected by dividing video data into frames per second, and data augmentation techniques are used. The effectiveness of the proposed CNN model is verified by the experiments with the humanoid robot MAX-E1.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.329-336
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• 2008

Nowadays with advancement in technology and aging society, the number of disabled citizens is increasing. The disabled citizens always need a caretaker for daily life routines especially for mobility. In future, the need is considered to increase more. To reduce the burden from the disabled, various devices for healthcare are introduced using computer technology. The power wheelchair is an important and convenient mobility device. The demand of power wheelchair is increasing for assistance in mobility. In this paper we proposed a robotic wheelchair for mobility aid to reduce the burden from the disabled. The main issue in an autonomous wheelchair is the automatic detection and avoidance of obstacles and going to the pre-designated place. The proposed algorithm detects the obstacles and avoids them to drive the wheelchair to the desired place safely. By this way, the disabled will not always have to worry about paying deep attention to the surroundings and his path.