• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.11
• /
• pp.28-36
• /
• 2020

As many types of magnetic sensors are widely applied in various industries, the analysis and processing of magnetic sensor data need to be accurate. On the other hand, owing to the complexity of the magnetic field line caused by a moving magnet, the magnetic data generated by magnetic sensors are unpredictably nonlinear. Many industry systems using magnetic sensors have struggled with the nonlinear nature of magnetic sensor data. To reduce the effect of the nonlinearity, they have the target objects fixed firmly. Therefore, to collect accurate and reliable data, considerable efforts have been made to resolve the issues with the expensive tools and systems required. Through this paper, to tackle the issues, the data analysis and methodologies, including intelligent algorithms, are presented for the wrist rehabilitation system using magnetic sensors while being implemented without using expensive tools or systems. On processing magnetic sensor data, this paper adopted an intelligent algorithm, fuzzy logic, and compared the performance of other algorithms for comparison.

• Proceedings of the KSPS conference
• /
• 2000.07a
• /
• pp.166-177
• /
• 2000

The purpose of this study was to create letters for of nonliterary Pulang tribe in Thailand those who immigrant from China. illiterate Pulang tribe hand down their tradition by primary oral culture therefore their tradition can't initiate and keep, moreover, it may disappear throughout history. So it is expected to crusade against unlettered people. The scheme of research adopted in this study was a minority race who habitate at the northern Machan, Chiangrai in Thailand. It is not only analysis of language but also the eradication of literacy and the research based on linguistic, ethnolinguistic, and primary oral culture. Five Pulang people who live in that area were chosen for creating letters. By using the I. P. A., after each word was listen to their pronunciation one by one it was described and repeated this process several times; the material words and humanbody were pointed in front of them while other words were described by gesture. For final description, number of people were in the lineup for listening the sound of words and phrases to sentences. In the first stage, it was an analysis segmental of Pulang: vocoid, contoid and diphthong were described with each sample syllables and words. The suprasegmental were studied with intonation and juncture of the words in the second stage. Two words were compared and different meanings within their intonation and juncture were shown. At the end of this part, each case of phonemic or morphophonemics representation described the juncture in the words. In the third stage, minimal pairs were analyzed with vowels and consonants and described in free variation based on words. In the last stage, syllable structure in open syllable and closed syllable was studied and then each syllable of its structure was analyzed with samples. There were thirty-two phonemes in apong Pulang as follows: seven vocoids; a, i, e, o, u, ${\ae}$, and $\wedge$, one diphthong; wu, 24 contoids; b, c, d, f, g, h, j, k, k, 1, m, n, ${\eta}, {\;}p^{h}$, p, p, r, s, s, sh, t, t, w, and y. Their pronunciations of p, s, d, $p^{h}$, j, and t are frequently used in speech and are unique in triphthong. Moreover, most of the words used initial and final consonant cluster.

• Korean Journal of Child Studies
• /
• v.34 no.3
• /
• pp.1-19
• /
• 2013

The purpose of this study was to investigate the relationship between parents' behavior during picture-book reading and home literacy environment and their effects on toddlers' vocabulary. The subjects of the study were 46 toddlers and their parents. The MCDI-K(Im, 2002), Lee and Kim(2004)'s categories of Verbal Behaviors, the categories of Nonverbal Behavioral Analysis(Kim, 2005), and the Home Literacy Environment Index(Han, 2006) were used. The analysis of the collected data was guided by the research questions and involved the use of descriptive statistics, t-test and an analysis of relevant correlations. The results of this study were as follows; First, the toddlers' receptive vocabulary score was 1.2 times higher than the toddler's expressive vocabulary score. Second, the father's book reading behaviors and mother's book reading behaviors were quite similar, the most frequent types of behavior being the use of 'feedback', 'explanation', 'questioning' and 'pointing'. On the other hand, there was a significant difference between the reading behavior of the mother and father as regards the categories of 'linguistic attention ventilation', 'suggesting', 'directing(instructing)', 'expanding feedback', 'pointing' and 'gesture'. Mothers performed more of these behaviors than the fathers. Third, toddler's vocabulary scores were positively correlated with the mother's 'linguistic attention ventilation'. However, the mother's use of 'restriction' was negatively correlated with the toddler's vocabulary level. Toddler's vocabulary scores were positively correlated with the father's 'description', 'reasoning/predicting', 'questioning about function or action', 'demanding feedback' and 'pointing'. The toddler's vocabulary scores were also positively correlated with the relative abundance of home environment materials and the amount of time spent on parent-child home literacy activity.

• The KIPS Transactions:PartB
• /
• v.16B no.5
• /
• pp.341-346
• /
• 2009

The motion data glove is a representative human-computer interaction tool that inputs human hand gestures to computers by measuring their motions. The motion data glove is essential equipment used for new computer technologiesincluding home automation, virtual reality, biometrics, motion capture. For its popular usage, this paper attempts to develop an inexpensive visual.type motion data glove that can be used without any special equipment. The proposed approach has the special feature; it can be developed as a low-cost one becauseof not using high-cost motion-sensing fibers that were used in the conventional approaches. That makes its easy production and popular use possible. This approach adopts a visual method that is obtained by improving conventional optic motion capture technology, instead of mechanical method using motion-sensing fibers. Compared to conventional visual methods, the proposed method has the following advantages and originalities Firstly, conventional visual methods use many cameras and equipments to reconstruct 3D pose with eliminating occlusions But the proposed method adopts a mono vision approachthat makes simple and low cost equipments possible. Secondly, conventional mono vision methods have difficulty in reconstructing 3D pose of occluded parts in images because they have weak points about occlusions. But the proposed approach can reconstruct occluded parts in images by using originally designed thin-bar-shaped optic indicators. Thirdly, many cases of conventional methods use nonlinear numerical computation image analysis algorithm, so they have inconvenience about their initialization and computation times. But the proposed method improves these inconveniences by using a closed-form image analysis algorithm that is obtained from original formulation. Fourthly, many cases of conventional closed-form algorithms use approximations in their formulations processes, so they have disadvantages of low accuracy and confined applications due to singularities. But the proposed method improves these disadvantages by original formulation techniques where a closed-form algorithm is derived by using exponential-form twist coordinates, instead of using approximations or local parameterizations such as Euler angels.

• Journal of rehabilitation welfare engineering & assistive technology
• /
• v.11 no.4
• /
• pp.371-376
• /
• 2017

In this paper, we propose an algorithm that can recognize the pattern regardless of the sensor position when performing EMG pattern recognition using circular EMG system equipment. Fourteen features were extracted by using the data obtained by measuring the eight channel EMG signals of six motions for 1 second. In addition, 112 features extracted from 8 channels were analyzed to perform principal component analysis, and only the data with high influence was cut out to 8 input signals. All experiments were performed using k-NN classifier and data was verified using 5-fold cross validation. When learning data in machine learning, the results vary greatly depending on what data is learned. EMG Accuracy of 99.3% was confirmed when using the learning data used in the previous studies. However, even if the position of the sensor was changed by only 22.5 degrees, it was clearly dropped to 67.28% accuracy. The accuracy of the proposed method is 98% and the accuracy of the proposed method is about 98% even if the sensor position is changed. Using these results, it is expected that the convenience of the users using the circular EMG system can be greatly increased.