• Title/Summary/Keyword: Input devices

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ZigBee Authentication Protocol with Enhanced User Convenience and Safety (사용자 편의성 및 안전성이 강화된 ZigBee 인증 프로토콜)

  • Ho-jei Yu;Chan-hee Kim;Sung-sik Im;Soo-hyun Oh
    • Convergence Security Journal
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    • v.22 no.1
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    • pp.81-92
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    • 2022
  • The rapidly growing IoT market is expanding not only in general households but also in smart homes and smart cities. Among the major protocols used in IoT, ZigBee accounts for more than 90% of the smart home's door lock market and is mainly used in miniaturized sensor devices, so the safety of the protocol is very important. However, the device using Zig Bee is not satisfied with the omnidirectional safety because it uses a fixed key during the authentication process that connects to the network, and it has not been resolved in the recently developed ZigBee 3.0. This paper proposes a design method that provides omnidirectional safety to the ZigBee authentication protocol and can be quickly applied to existing protocols. The proposed improved ZigBee authentication protocol analyzed and applied the recently developed OWE protocol to apply ECDH, which has low computational volume and provides omnidirectional safety in IoT. Based on this, it provides the safety of the ZigBee authentication protocol, and it is expected that it will be able to provide user convenience as it does not require a separate certificate or password input.

The Status of Teachers of Students with Intellectual Disabilities in Practicing Strategies for the Modification of Aggressive Behaviour in Saudi Arabia

  • Alqurashi, Yasser O.;Bagadood, Nizar H.
    • International Journal of Computer Science & Network Security
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    • v.22 no.1
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    • pp.241-247
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    • 2022
  • This study examines teachers' implementation of strategies to modify the aggressive behavior of students with intellectual disabilities in Saudi Arabia, to determine the obstacles to their real-world execution. In addition, it presents potential approaches to overcome the obstacles to implementing strategies with this group of students. The research employed a qualitative design using semi-structured interviews as a data collection tool and applied a thematic analysis. The study population comprised 35 teachers of students with intellectual disabilities and the study sample numbered six teachers. The interviews were conducted via different methods: three by phone, two face-to face, and one using the Zoom platform. The results revealed inadequate understanding among teachers of intellectual disability and behaviour modification strategies, and this affected their capacity to develop plans that were compatible with the needs of students with intellectual disability. The findings also identified multiple obstacles that impede teachers' implementation of strategies to modify aggressive behaviour among students with intellectual disabilities; the most important being the lack of input from a psychological specialist when developing programs to modify aggressive behaviour. In general, it is apparent that programs for modifying aggressive behaviour are neither structured nor complementary, due to the scarcity of administrators with sufficient knowledge and familiarity with the characteristics and personalities of students with intellectual disabilities. This study presents several recommendations, the most important of which is that teachers of students with intellectual disability should develop themselves through training courses to enable them to deal with these students and create treatment plans that include strategies and clear steps to modify the aggressive behaviour of students with intellectual disabilities. To support teachers, it is also necessary to remove the obstacles facing education centres by providing financial support to create an environment in which they can access the required devices and equipment in their classes.

Distance Estimation Based on RSSI and RBF Neural Network for Location-Based Service (위치 서비스를 위한 RBF 신경회로망과 RSSI 기반의 거리추정)

  • Byeong-Ro Lee;Ju-Won Lee
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.16 no.5
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    • pp.265-271
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    • 2023
  • Recently, location information services are gradually expanding due to the development of information and communication technology. RSSI is widely used to extract indoor and outdoor locations. The indoor and outdoor location estimation methods using RSSI are less accurate due to the influence of radio wave paths, interference, and surrounding wireless devices. In order to improve this problem, a distance estimation method that takes into account the wireless propagation environment is necessary. Therefore, in this study, we propose a distance estimation algorithm that takes into account the radio wave environment. The proposed method estimates the distance by learning RSSI input and output considering the RBF neural network and the propagation environment. To evaluate the performance of the proposed method, the performance of estimating the location of the receiver within a range of up to 55[m] using a BLE beacon transmitter and receiver was compared with the average filter and Kalman filter. As a result, the distance estimation accuracy of the proposed method was 6.7 times higher than that of the average filter and Kalman filter. As shown in the results of this performance evaluation, if the method of this study is applied to location services, more accurate location estimation will be possible.

Blood glucose prediction using PPG and DNN in dogs - a pilot study (개의 PPG와 DNN를 이용한 혈당 예측 - 선행연구)

  • Cheol-Gu Park;Sang-Ki Choi
    • Journal of Digital Policy
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    • v.2 no.4
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    • pp.25-32
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    • 2023
  • This paper is a study to develop a deep neural network (DNN) blood glucose prediction model based on heart rate (HR) and heart rate variability (HRV) data measured by PPG-based sensors. MLP deep learning consists of an input layer, a hidden layer, and an output layer with 11 independent variables. The learning results of the blood glucose prediction model are MAE=0.3781, MSE=0.8518, and RMSE=0.9229, and the coefficient of determination (R2) is 0.9994. The study was able to verify the feasibility of glycemic control using non-blood vital signs using PPG-based digital devices. In conclusion, a standardized method of acquiring and interpreting PPG-based vital signs, a large data set for deep learning, and a study to demonstrate the accuracy of the method may provide convenience and an alternative method for blood glucose management in dogs.

Study on the Fly-back Topology of New Power Feed-back Method for Active Cell Balancing (엑티브 셀 밸런싱을 위한 새로운 전력 피드백 방식의 플라이백 토폴로지에 관한 연구)

  • Seong-Yong Kang;Myeong-Jin Song;Seong-Mi Park;Sung-Jun Park;Jae-Ha Ko
    • Journal of the Korean Society of Industry Convergence
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    • v.26 no.6_2
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    • pp.1083-1095
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    • 2023
  • Recently, the demand for low-voltage, high-capacity ESS is rapidly increasing due to the revitalization of the e-mobility industry, which is mainly powered by electricity. In addition, the demand for portable power banks is rapidly increasing due to the revitalization of leisure industries such as camping and fishing. The ESS with this structure consists of a small number of series cells and many parallel cells, resulting in a system with a large rated current. Therefore, the number of power devices for cell balancing configured in series is small, but a balancing device with a large current capacity is required. Construction of a constant temperature device in such a low-voltage, high-current ESS is difficult due to economic issues. The demand for an active balancing system that can solve the passive balancing heating problem is rapidly increasing. In this paper, propose a power feedback fly-back topology that can solve the balancing heating problem. The characteristic of the proposed topology is that a series-connected voltage sharing voltage is used as the input of the flyback converter, and the converter output is connected to one transformer. In this structure, the converter output for cell voltage balancing shares magnetic flux through one high-frequency transformer, so the cell voltage connected to the converter automatically converges to the same voltage.

A.C. servo motor current control parameter measurement strategy using the three phase inverter driver (3상 인버터 구동기를 이용하는 교류 서보전동기의 전류제어 파라미터 계측법)

  • Jung-Keyng Choi
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.16 no.6
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    • pp.434-440
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    • 2023
  • This paper propose the method that measure the main system parameters for current control of a.c. motor adopting the vector control technique. The automatical method that tuning PI control gains for current control of servo motors are used frequently through the information of main system parameters, wire resistance and inductance. In this study, the techniques to measure these two system parameters through the control of 3-phase inverter are presented. These control and measuring method are implemented by measuring output phase current obtained as a results of the step current control using simple proportional feedback input. Moreover, this method use freewheeling current of inverter at special switching mode for measuring inductance. This analytic strategy is could measure and calculate the system parameters without the complex measurement algorithm and new additional measuring circuits. That is could measure the total resistance and total inductance including wiring resistance and conduction resistance of switching devices using real driving circuits to control the motors.

Two-way Interactive Algorithms Based on Speech and Motion Recognition with Generative AI Technology (생성형 AI 기술을 적용한 음성 및 모션 인식 기반 양방향 대화형 알고리즘)

  • Dae-Sung Jang;Jong-Chan Kim
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.2
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    • pp.397-402
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    • 2024
  • Speech recognition and motion recognition technologies are applied and used in various smart devices, but they are composed of simple command recognition forms and are used as simple functions. Apart from simple functions for recognition data, professional command execution capabilities are required based on data learned in various fields. Research is being conducted on a system platform that provides optimal data to users using Generative AI, which is currently competing around the world, and can interact through voice recognition and motion recognition. The main technical processes designed for this study were designed using technologies such as voice and motion recognition functions, application of AI technology, and two-way communication. In this paper, two-way communication between a device and a user can be achieved by various input methods through voice recognition and motion recognition technology applied with AI technology.

Automatic Indexing Algorithm of Golf Video Using Audio Information (오디오 정보를 이용한 골프 동영상 자동 색인 알고리즘)

  • Kim, Hyoung-Gook
    • The Journal of the Acoustical Society of Korea
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    • v.28 no.5
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    • pp.441-446
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    • 2009
  • This paper proposes an automatic indexing algorithm of golf video using audio information. In the proposed algorithm, the input audio stream is demultiplexed into the stream of video and audio. By means of Adaboost-cascade classifier, the continuous audio stream is classified into announcer's speech segment recorded in studio, music segment accompanied with players' names on TV screen, reaction segment of audience according to the play, reporter's speech segment with field background, filed noise segment like wind or waves. And golf swing sound including drive shot, iron shot, and putting shot is detected by the method of impulse onset detection and modulation spectrum verification. The detected swing and applause are used effectively to index action or highlight unit. Compared with video based semantic analysis, main advantage of the proposed system is its small computation requirement so that it facilitates to apply the technology to embedded consumer electronic devices for fast browsing.

Deep learning-based anomaly detection in acceleration data of long-span cable-stayed bridges

  • Seungjun Lee;Jaebeom Lee;Minsun Kim;Sangmok Lee;Young-Joo Lee
    • Smart Structures and Systems
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    • v.33 no.2
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    • pp.93-103
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    • 2024
  • Despite the rapid development of sensors, structural health monitoring (SHM) still faces challenges in monitoring due to the degradation of devices and harsh environmental loads. These challenges can lead to measurement errors, missing data, or outliers, which can affect the accuracy and reliability of SHM systems. To address this problem, this study proposes a classification method that detects anomaly patterns in sensor data. The proposed classification method involves several steps. First, data scaling is conducted to adjust the scale of the raw data, which may have different magnitudes and ranges. This step ensures that the data is on the same scale, facilitating the comparison of data across different sensors. Next, informative features in the time and frequency domains are extracted and used as input for a deep neural network model. The model can effectively detect the most probable anomaly pattern, allowing for the timely identification of potential issues. To demonstrate the effectiveness of the proposed method, it was applied to actual data obtained from a long-span cable-stayed bridge in China. The results of the study have successfully verified the proposed method's applicability to practical SHM systems for civil infrastructures. The method has the potential to significantly enhance the safety and reliability of civil infrastructures by detecting potential issues and anomalies at an early stage.

Specifying the Characteristics of Tangible User Interface: centered on the Science Museum Installation (실물형 인터렉션 디자인 특성 분석: 과학관 체험 전시물을 대상으로)

  • Cho, Myung Eun;Oh, Myung Won;Kim, Mi Jeong
    • Science of Emotion and Sensibility
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    • v.15 no.4
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    • pp.553-564
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    • 2012
  • Tangible user interfaces have been developed in the area of Human-Computer Interaction for the last decades, however, the applied domains recently have been extended into the product design and interactive art. Tangible User Interfaces are the combination of digital information and physical objects or environments, thus they provide tangible and intuitive interaction as input and output devices, often combined with Augmented Reality. The research developed a design guideline for tangible user interfaces based on key properties of tangible user interfaces defined previously in five representative research: Tangible Interaction, Intuitiveness and Convenience, Expressive Representation, Context-aware and Spatial Interaction, and Social Interaction. Using the guideline emphasizing user interaction, this research evaluated installation in a science museum in terms of the applied characteristics of tangible user interfaces. The selected 15 installations which were evaluated are to educate visitors for science by emphasizing manipulation and experience of interfaces in those installations. According to the input devices, they are categorized into four Types. TUI properties in Type 3 installation, which uses body motions for interaction, shows the highest score, where items for context-aware and spatial interaction were highly rated. The context-aware and spatial interaction have been recently emphasized as extended properties of tangible user interfaces. The major type of installation in the science museum is equipped with buttons and joysticks for physical manipulation, thus multimodal interfaces utilizing visual, aural, tactile senses etc need to be developed to provide more innovative interaction. Further, more installation need to be reconfigurable for embodied interaction between users and the interactive space. The proposed design guideline can specify the characteristics of tangible user interfaces, thus this research can be a basis for the development and application of installation involving more TUI properties in future.

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