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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Journal of Korean Institute of Intelligent Systems
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Korean Institute of Intelligent Systems
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Volume & Issues
Volume 26, Issue 3 - Jun 2016
Volume 26, Issue 2 - Apr 2016
Volume 26, Issue 1 - Feb 2016
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A Study on Task Planning and Design of Modular Quadruped Robot with Docking Capability
Sun, Eun-Hey ; Kim, Yong-Tae ;
Journal of Korean Institute of Intelligent Systems, volume 26, issue 3, 2016, Pages 169~175
DOI : 10.5391/JKIIS.2016.26.3.169
There are many researches to develop robots that improve its mobility and task planning to adapt in various uneven environments. In this paper, we propose the design method and task planning of quadruped robot which can have top-bottom docking structure. The proposed quadruped robot is designed to adjust leg length using linear actuators and perform top-bottom docking and undocking using octagonal cone shaped docking module. Also, to stable walking and information gathering in the various environments, a geomagnetic sensor, PSD sensor, LRF sensor and camera. We propose an obstacle avoidance method and the topbottom docking algorithm of the two quadruped robots using linear actuator. The robot can overcome obstacles using adjusting leg length and activate the top-bottom docking function. The top-bottom docking robots of two quadruped robot can walk 4 legged walking and 6 legged walking, and use 4 arms or 2 arms the upper. We verified that the docking robots can carry objects using 4 leg of the upper robot.
Autonomous Mobile Robot Control using the Wearable Devices Based on EMG Signal for detecting fire
Kim, Jin-Woo ; Lee, Woo-Young ; Yu, Je-Hun ; Sim, Kwee-Bo ;
Journal of Korean Institute of Intelligent Systems, volume 26, issue 3, 2016, Pages 176~181
DOI : 10.5391/JKIIS.2016.26.3.176
In this paper, the autonomous mobile robot control system for detecting fire was proposed using the wearable device based on EMG(Electromyogram) signal. Myo armband is used for detecting the user's EMG signal. The gesture was classified after sending the data of EMG signal to a computer using Bluetooth communication. Then the robot named 'uBrain' was implemented to move by received data from Bluetooth communication in our experiment. 'Move front', 'Turn right', 'Turn left', and 'Stop' are controllable commands for the robot. And if the robot cannot receive the Bluetooth signal from a user or if a user wants to change manual mode to autonomous mode, the robot was implemented to be in the autonomous mode. The robot flashes the LED when IR sensor detects the fire during moving.
A Method for Correcting Air-Pressure Data Collected by Mini-AWS
Ha, Ji-Hun ; Kim, Yong-Hyuk ; Im, Hyo-Hyuc ; Choi, Deokwhan ; Lee, Yong Hee ;
Journal of Korean Institute of Intelligent Systems, volume 26, issue 3, 2016, Pages 182~189
DOI : 10.5391/JKIIS.2016.26.3.182
For high accuracy of forecast using numerical weather prediction models, we need to get weather observation data that are large and high dense. Korea Meteorological Administration (KMA) mantains Automatic Weather Stations (AWSs) to get weather observation data, but their installation and maintenance costs are high. Mini-AWS is a very compact automatic weather station that can measure and record temperature, humidity, and pressure. In contrast to AWS, costs of Mini-AWS's installation and maintenance are low. It also has a little space restraints for installing. So it is easier than AWS to install mini-AWS on places where we want to get weather observation data. But we cannot use the data observed from Mini-AWSs directly, because it can be affected by surrounding. In this paper, we suggest a correcting method for using pressure data observed from Mini-AWS as weather observation data. We carried out preconditioning process on pressure data from Mini-AWS. Then they were corrected by using machine learning methods with the aim of adjusting to pressure data of the AWS closest to them. Our experimental results showed that corrected pressure data are in regulation and our correcting method using SVR showed very good performance.
A R&D strategies for development using structured association map
Song, Wonho ; Lee, Junseok ; Park, Sangsung ;
Journal of Korean Institute of Intelligent Systems, volume 26, issue 3, 2016, Pages 190~195
DOI : 10.5391/JKIIS.2016.26.3.190
A technology is continuously developed in a rapidly changing global market. A company requires an appropriate R&D strategy for adapting to this environment. That is, the technologies owned by the company needs to be thoroughly analyzed to improve its competitiveness. Alternatively, technology classification using IPC codes is carried out recently in an objective and quantitative way. International Patent Classification, IPC is an internationally specified classification system, so it is helpful to conduct an objective and quantitative patent analysis of technology. In this study, all of the patents owned by company C are investigated and a matrix representing IPC codes of each patent is created. Then, a structured association map of the patents is made through association rules mining based on Confidence. The association map can be used to inspect the current situation of a company about patents. It also allows highly associated technologies to be clustered. Using the association map, this study analyzes the technologies of company C and how it changes with time. The strategy for future technologies is established based on the result.
Analysis on Rehabilitation of Elbow Joint Using Elastic String
Kim, Byoung-Ho ;
Journal of Korean Institute of Intelligent Systems, volume 26, issue 3, 2016, Pages 196~201
DOI : 10.5391/JKIIS.2016.26.3.196
This paper analyses the characteristics of a stiffness-based rehabilitation mechanism for improving the function of the elbow joint of a human. We consider an elastic string as a tool for the elbow joint rehabilitation, where the string has been modeled as a linear spring with a stiffness. For effective rehabilitation training by using such a mechanism, we need to analyse the available torque characteristics of the elbow joint according to the stiffness of the string. Through various simulations, the torque pattern and its range of the elbow joint by assigning the stiffness of the string have been identified for a pre-defined trajectory of motion of the elbow joint. Finally, we show that the specified stiffness-based rehabilitation scheme can be used for effective rehabilitation of the elbow joint.
Determination of Optimal Checkpoint Intervals for Real-Time Tasks Using Distributed Fault Detection
Kwak, Seong Woo ; Yang, Jung-Min ;
Journal of Korean Institute of Intelligent Systems, volume 26, issue 3, 2016, Pages 202~207
DOI : 10.5391/JKIIS.2016.26.3.202
Checkpoint placement is an effective fault tolerance technique against transient faults in which the task is re-executed from the latest checkpoint when a fault is detected. In this paper, we propose a new checkpoint placement strategy separating data saving and fault detection processes that are performed together in conventional checkpoints. Several fault detection processes are performed in one checkpoint interval in order to decrease the latency between the occurrence and detection of faults. We address the placement method of fault detection processes to maximize the probability of successful execution of a task within the given deadline. We develop the Markov chain model for a real-time task having the proposed checkpoints, and derive the optimal fault detection and checkpoint interval.
Simulation of Sensor Measurements for Location Estimation of an Underwater Vehicle
Han, Jun Hee ; Ko, Nak Yong ; Choi, Hyun Taek ; Lee, Chong Moo ;
Journal of Korean Institute of Intelligent Systems, volume 26, issue 3, 2016, Pages 208~217
DOI : 10.5391/JKIIS.2016.26.3.208
This paper describes a simulation method to generate sensor measurements for location estimation of an underwater robot. Field trial of a navigation method of an underwater robot takes much time and expenses and it is difficult to change the environment of the field trial as desired to test the method in various situations. Therefore, test and verification of a navigation method through simulation is inevitable for underwater environment. This paper proposes a method to generate sensor measurements of range, depth, velocity, and attitude taking the uncertainties of measurements into account through simulation. The uncertainties are Gaussian noise, outlier, and correlation between the measurement noise. Also, the method implements uncertainty in sampling time of measurements. The method is tested and verified by comparing the uncertainty parameters calculated statistically from the generated measurements with the designed uncertainty parameters. The practical feasibility of the measurement data is shown by applying the measurement data for location estimation of an underwater robot.
A Study on Propriety of Pilot Aptitude Test Using Phased Analysis of Pilot Training
Kim, HeeYoung ; Kim, SuHwan ; Moon, HoSeok ;
Journal of Korean Institute of Intelligent Systems, volume 26, issue 3, 2016, Pages 218~225
DOI : 10.5391/JKIIS.2016.26.3.218
It is important to select the personnel with ideal pilot aptitude considering dramatically advancing aircraft performance and complexity of military operations as a consequence to the highly developed science and technology. The opportunity cost lost from dropouts and human error being the first cause of aviation accidents are the realistic reasons for the significance of personnel selection based on their aptitude. This study analyses the ROKAF pilot aptitude test that was improved in 2004, using various classification models. This study discusses the significance of the selected variables along with the direction of ROKAF pilot aptitude test for its development in the future. The accuracy of the classification models was improved by taking into account differing personnel characteristics of individuals on the test.
A Study on the Improving Method of Academic Effect based on Arduino sensors
Bae, Youngchul ; Hong, YouSik ;
Journal of Korean Institute of Intelligent Systems, volume 26, issue 3, 2016, Pages 226~232
DOI : 10.5391/JKIIS.2016.26.3.226
The research for the improvement in math and science scores is active by the brain exercises, stress reliefs, and emotion sensitized illuminations. This principle is based on the following facts that the most effective brain turns are supported with the circumstances not only when the brain wave should keep stability and comfort in science criticism, but also when minimized stress and comfortable illumination should be adjusted in solving math problem. In this paper, in order to effectively learn mathematics and science, the most optimized simulating tests in learning conditions are conducted by using a stress relief. However, depending on the users' tastes, the effectiveness on favorite music or colors therapy have no convergency but many differentiations. Therefore, in this paper, in order to solve this problem, the proposed optimal illumination and music therapy treatment using fuzzy inference method.
Data Fusion Algorithm based on Inference for Anomaly Detection in the Next-Generation Intrusion Detection
Kim, Dong-Wook ; Han, Myung-Mook ;
Journal of Korean Institute of Intelligent Systems, volume 26, issue 3, 2016, Pages 233~238
DOI : 10.5391/JKIIS.2016.26.3.233
In this paper, we propose the algorithms of processing the uncertainty data using data fusion for the next generation intrusion detection. In the next generation intrusion detection, a lot of data are collected by many of network sensors to discover knowledge from generating information in cyber space. It is necessary the data fusion process to extract knowledge from collected sensors data. In this paper, we have proposed method to represent the uncertainty data, by classifying where is a confidence interval in interval of uncertainty data through feature analysis of different data using inference method with Dempster-Shafer Evidence Theory. In this paper, we have implemented a detection experiment that is classified by the confidence interval using IRIS plant Data Set for anomaly detection of uncertainty data. As a result, we found that it is possible to classify data by confidence interval.
A Study on the Implementation of Intelligent Navigational Risk Assessment System for High-risk Vessel using IoT Sensor Gateway
Kim, Do-Yeon ; Kim, Kil-Yong ; Park, Gyei-Kark ; Jeong, Jung-Sik ;
Journal of Korean Institute of Intelligent Systems, volume 26, issue 3, 2016, Pages 239~245
DOI : 10.5391/JKIIS.2016.26.3.239
In the midst of continuing international recession, the rate of maritime traffic and marine leisure markets are consistently growing. The Republic of Korea controls the marine traffic volume through vessel traffic centers and various other management facilities. Nevertheless, the continuous growth and complexity of marine traffic is resulting in repeated occurrences of marine accidents. Recovery is very difficult in cases of human injuries or deaths caused by marine accidents due to its nature, and the scale of marine accidents is also becoming greater with advanced ship building technologies. Passenger ships, oil tankers, and other such vessels used for specific purposes requires a more detailed navigational status surveillance and analysis, and numerous research has been conducted with an objective for monitoring such special purpose vessels. However, the data elements transmitted from the ocean to the shore station are limited to AIS and ARPA. We are implementing IoT ship sensor collection and a syncing system capable of transmitting various ship sensing data to the shore station, and also proposing a Safe Navigation Status Analysis System utilizing the collected data.
Fault Detection Method for Steam Boiler Tube Using Mahalanobis Distance
Yu, Jungwon ; Jang, Jaeyel ; Yoo, Jaeyeong ; Kim, Sungshin ;
Journal of Korean Institute of Intelligent Systems, volume 26, issue 3, 2016, Pages 246~252
DOI : 10.5391/JKIIS.2016.26.3.246
Since thermal power plant (TPP) equipment is operated under very high pressure and temperature, failures of the equipment give rise to severe losses of life and property. To prevent the losses, fault detection method is, therefore, absolutely necessary to identify abnormal operating conditions of the equipment in advance. In this paper, we present Mahalanobis distance (MD) based fault detection method for steam boiler tube in TPP. In the MD-based method, it is supposed that abnormal data samples are far away from normal samples. Using multivariate samples collected from normal target system, mean vector and covariance matrix are calculated and threshold value of MD is decided. In a test phase, after calculating the MDs between the mean vector and test samples, alarm signals occur if the MDs exceed the predefined threshold. To demonstrate the performance, a failure case due to boiler tube leakage in 200MW TPP is employed. The experimental results show that the presented method can perform early detection of boiler tube leakage successfully.