• 제목/요약/키워드: human-machine communication

검색결과 221건 처리시간 0.026초

LTE-A 네트워크 환경에서 MTC를 위한 효율적인 접근관리 기법 (Efficient Access Management Scheme for Machine Type Communications in LTE-A Networks)

  • 문지훈;임유진
    • 예술인문사회 융합 멀티미디어 논문지
    • /
    • 제7권1호
    • /
    • pp.287-295
    • /
    • 2017
  • 최근 들어, 사물 인터넷 (Internet of Things)을 지원하기 위한 중요한 기술 중 하나로 고려되고 있는 MTC (Machine Type Communication)는 사람의 개입 없이 MTC 단말들에게 네트워크 연결을 제공하는 기술이다. 그러나 짧은 시간 내에 많은 MTC 단말들이 접속을 시도하는 경우, 제한된 통신 자원으로 인하여 자원 경쟁이 심화되고, 이로 인하여 단말의 접속 실패가 야기될 수 있다. 이러한 문제를 해결하기 위해서는 단말들의 통신 자원 접근을 분산시킬 필요가 있다. 본 논문에서는 LTE-A 환경에서 MTC 단말들의 효율적인 접근관리 기법을 제안한다. 먼저 특정 시간구간 동안 접속을 시도하는 단말 개수를 측정하고, 이를 기반으로 다음 시간구간 동안 접속을 시도할 단말 개수를 예측한다. 이러한 예측 개수를 기반으로 제안 기법은 통신자원 접근을 시도하는 단말 개수를 제어한다. 제안된 기법의 성능 증명을 위하여, 성공확률, 실패확률, 충동확률, 그리고 접속지연시간 측면에서 성능을 분석하였다.

얼굴 특징점 추적을 통한 사용자 감성 인식 (Emotion Recognition based on Tracking Facial Keypoints)

  • 이용환;김흥준
    • 반도체디스플레이기술학회지
    • /
    • 제18권1호
    • /
    • pp.97-101
    • /
    • 2019
  • Understanding and classification of the human's emotion play an important tasks in interacting with human and machine communication systems. This paper proposes a novel emotion recognition method by extracting facial keypoints, which is able to understand and classify the human emotion, using active Appearance Model and the proposed classification model of the facial features. The existing appearance model scheme takes an expression of variations, which is calculated by the proposed classification model according to the change of human facial expression. The proposed method classifies four basic emotions (normal, happy, sad and angry). To evaluate the performance of the proposed method, we assess the ratio of success with common datasets, and we achieve the best 93% accuracy, average 82.2% in facial emotion recognition. The results show that the proposed method effectively performed well over the emotion recognition, compared to the existing schemes.

변전자동화 클라이언트의 IEC 61850 기본 적합성 시험방안에 관한 연구 (A Study on the Basic Conformance test of IEC 61850 based Client)

  • 이남호;장병태;김병헌;심응보
    • 한국조명전기설비학회:학술대회논문집
    • /
    • 한국조명전기설비학회 2009년도 춘계학술대회 논문집
    • /
    • pp.259-262
    • /
    • 2009
  • IEC 61850 based substation automation system mainly consists of human machine interface and a various of IEDs in charge of protective and control functions of the substation. Both of them should require the performance verification of IEC 61850 communication services because their communication relation is the same as client and server throughout the digital network. This paper shows a research result on the testing method of basic communication interface of the IEC 61850 based client, which was implemented by the analysis of real communication between HMI and IED of IEC 61850 based substation automation system and refereed to IED IEC 61850 conformance test procedures.

  • PDF

Several models for tunnel boring machine performance prediction based on machine learning

  • Mahmoodzadeh, Arsalan;Nejati, Hamid Reza;Ibrahim, Hawkar Hashim;Ali, Hunar Farid Hama;Mohammed, Adil Hussein;Rashidi, Shima;Majeed, Mohammed Kamal
    • Geomechanics and Engineering
    • /
    • 제30권1호
    • /
    • pp.75-91
    • /
    • 2022
  • This paper aims to show how to use several Machine Learning (ML) methods to estimate the TBM penetration rate systematically (TBM-PR). To this end, 1125 datasets including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), punch slope index (PSI), distance between the planes of weakness (DPW), orientation of discontinuities (alpha angle-α), rock fracture class (RFC), and actual/measured TBM-PRs were established. To evaluate the ML methods' ability to perform, the 5-fold cross-validation was taken into consideration. Eventually, comparing the ML outcomes and the TBM monitoring data indicated that the ML methods have a very good potential ability in the prediction of TBM-PR. However, the long short-term memory model with a correlation coefficient of 0.9932 and a route mean square error of 2.68E-6 outperformed the remaining six ML algorithms. The backward selection method showed that PSI and RFC were more and less significant parameters on the TBM-PR compared to the others.

Study on Gesture and Voice-based Interaction in Perspective of a Presentation Support Tool

  • Ha, Sang-Ho;Park, So-Young;Hong, Hye-Soo;Kim, Nam-Hun
    • 대한인간공학회지
    • /
    • 제31권4호
    • /
    • pp.593-599
    • /
    • 2012
  • Objective: This study aims to implement a non-contact gesture-based interface for presentation purposes and to analyze the effect of the proposed interface as information transfer assisted device. Background: Recently, research on control device using gesture recognition or speech recognition is being conducted with rapid technological growth in UI/UX area and appearance of smart service products which requires a new human-machine interface. However, few quantitative researches on practical effects of the new interface type have been done relatively, while activities on system implementation are very popular. Method: The system presented in this study is implemented with KINECT$^{(R)}$ sensor offered by Microsoft Corporation. To investigate whether the proposed system is effective as a presentation support tool or not, we conduct experiments by giving several lectures to 40 participants in both a traditional lecture room(keyboard-based presentation control) and a non-contact gesture-based lecture room(KINECT-based presentation control), evaluating their interests and immersion based on contents of the lecture and lecturing methods, and analyzing their understanding about contents of the lecture. Result: We check that whether the gesture-based presentation system can play effective role as presentation supporting tools or not depending on the level of difficulty of contents using ANOVA. Conclusion: We check that a non-contact gesture-based interface is a meaningful tool as a sportive device when delivering easy and simple information. However, the effect can vary with the contents and the level of difficulty of information provided. Application: The results presented in this paper might help to design a new human-machine(computer) interface for communication support tools.

A Face Robot Actuated With Artificial Muscle Based on Dielectric Elastomer

  • Kwak Jong Won;Chi Ho June;Jung Kwang Mok;Koo Ja Choon;Jeon Jae Wook;Lee Youngkwan;Nam Jae-do;Ryew Youngsun;Choi Hyouk Ryeol
    • Journal of Mechanical Science and Technology
    • /
    • 제19권2호
    • /
    • pp.578-588
    • /
    • 2005
  • Face robots capable of expressing their emotional status, can be adopted as an efficient tool for friendly communication between the human and the machine. In this paper, we present a face robot actuated with artificial muscle based on dielectric elastomer. By exploiting the properties of dielectric elastomer, it is possible to actuate the covering skin, eyes as well as provide human-like expressivity without employing complicated mechanisms. The robot is driven by seven actuator modules such eye, eyebrow, eyelid, brow, cheek, jaw and neck module corresponding to movements of facial muscles. Although they are only part of the whole set of facial motions, our approach is sufficient to generate six fundamental facial expressions such as surprise, fear, angry, disgust, sadness, and happiness. In the robot, each module communicates with the others via CAN communication protocol and according to the desired emotional expressions, the facial motions are generated by combining the motions of each actuator module. A prototype of the robot has been developed and several experiments have been conducted to validate its feasibility.

추가 데이터 및 도메인 적응을 위한 기계독해 질의 생성 (Question Generation of Machine Reading Comprehension for Data Augmentation and Domain Adaptation)

  • 이현구;장영진;김진태;왕지현;신동훈;김학수
    • 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
    • /
    • 한국정보과학회언어공학연구회 2019년도 제31회 한글 및 한국어 정보처리 학술대회
    • /
    • pp.415-418
    • /
    • 2019
  • 기계독해 모델에 새로운 도메인을 적용하기 위해서는 도메인에 맞는 데이터가 필요하다. 그러나 추가 데이터 구축은 많은 비용이 발생한다. 사람이 직접 구축한 데이터 없이 적용하기 위해서는 자동 추가 데이터 확보, 도메인 적응의 문제를 해결해야한다. 추가 데이터 확보의 경우 번역, 질의 생성의 방법으로 연구가 진행되었다. 그러나 도메인 적응을 위해서는 새로운 정답 유형에 대한 질의가 필요하며 이를 위해서는 정답 후보 추출, 추출된 정답 후보로 질의를 생성해야한다. 본 논문에서는 이러한 문제를 해결하기 위해 듀얼 포인터 네트워크 기반 정답 후보 추출 모델로 정답 후보를 추출하고, 포인터 제너레이터 기반 질의 생성 모델로 새로운 데이터를 생성하는 방법을 제안한다. 실험 결과 추가 데이터 확보의 경우 KorQuAD, 경제, 금융 도메인의 데이터에서 모두 성능 향상을 보였으며, 도메인 적응 실험에서도 새로운 도메인의 문맥만을 이용해 데이터를 생성했을 때 기존 도메인과 다른 도메인에서 모두 기계독해 성능 향상을 보였다.

  • PDF

Online Digit Recognition using Start and End Point

  • Shim, Jae-chang;Ansari, Md Israfil
    • Journal of Multimedia Information System
    • /
    • 제4권1호
    • /
    • pp.39-42
    • /
    • 2017
  • Communication between human and machine is having been researched from last few decades and still it's a challenging task because human behavior is unpredictable. When it comes on handwritten digits almost each human has their own writing style. Handwritten digit recognition plays an important role, especially in the courtesy amounts on bank checks, postal code on mail address etc. In our study, we proposed an efficient feature extraction system for recognizing single digit number drawn by mouse or by a finger on a screen. Our proposed method combines basic image processing and reading the strokes of a line drawn. It is very simple and easy to implement in various platform as compare to the system which required high system configuration. This system has been designed, implemented, and tested successfully.

생체신호 분석을 통한 인간감성의 측정 (Measurement of Human Sensibility by Bio-Signal Analysis)

  • 박준영;박장현;박지형;박동수
    • 대한기계학회:학술대회논문집
    • /
    • 대한기계학회 2003년도 춘계학술대회
    • /
    • pp.935-939
    • /
    • 2003
  • The emotion recognition is one of the most significant interface technologies which make the high level of human-machine communication possible. The central nervous system stimulated by emotional stimuli affects the autonomous nervous system like a heart, blood vessel, endocrine organs, and so on. Therefore bio-signals like HRV, ECG and EEG can reflect one' emotional state. This study investigates the correlation between emotional states and bio-signals to realize the emotion recognition. This study also covers classification of human emotional states, selection of the effective bio-signal and signal processing. The experimental results presented in this paper show possibility of the emotion recognition.

  • PDF

Design and Implementation of a Body Fat Classification Model using Human Body Size Data

  • Taejun Lee;Hakseong Kim;Hoekyung Jung
    • Journal of information and communication convergence engineering
    • /
    • 제21권2호
    • /
    • pp.110-116
    • /
    • 2023
  • Recently, as various examples of machine learning have been applied in the healthcare field, deep learning technology has been applied to various tasks, such as electrocardiogram examination and body composition analysis using wearable devices such as smart watches. To utilize deep learning, securing data is the most important procedure, where human intervention, such as data classification, is required. In this study, we propose a model that uses a clustering algorithm, namely, the K-means clustering, to label body fat according to gender and age considering body size aspects, such as chest circumference and waist circumference, and classifies body fat into five groups from high risk to low risk using a convolutional neural network (CNN). As a result of model validation, accuracy, precision, and recall results of more than 95% were obtained. Thus, rational decision making can be made in the field of healthcare or obesity analysis using the proposed method.