• Magazine of the Korean Society of Agricultural Engineers
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• v.15 no.2
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• pp.2949-2967
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• 1973

The purpose of this study is to find out and determine the minimum consumptive use of water for Korean cabbage and turmp, so that the minimum water requirement can be secured always for a stable cultivation of these vegetables regardless of weather conditions. The experiment was conducted in two periods; first one from May to July and second one from August to October, each experiment with two varieties of cabbage and two varieties of radish with 2 replicants and 15 treatments. The results found from the above are briefly as follows: 1. Since the mean soil moisture equivalent 64 days after the treatment was 28.5% and the soil moisture content at the time was 2.67% which is far less than that of the wilting point, the crop seemed to be extremely caused by a drought. 2. The rate of 51 days after the seeding, soil moisture content of plot No.2 where irrigation has been continuous was the highest or 21.3%, whereas the plot No.14 without irrigations was 11.2% and the lowest. Therefore, the soil moisture content for the minimum qrowth seemed to be 20%. 3. The consumptive coefficient of Blaney and Criddle on cabbage in two periods were K=1.14 and 0.97 respectively, and on radish in two periods were K=1.06 and 0.86 respectively, thus, cabbage was higher than radish. The consumptive coefficient in the first experiment (May-July) was 0.17 to 0.20 higher than the 2nd experiment(August-October). 4. Nomally, cabbage and radish germinate within one week, however, the germination ot these crops which were treated with a suspended water supply from the beginning took two full weeks. 5. When it elapsed 30 days after seeding, the conditions in plot 1,2 and 3 were fairly good however, the crops in the plops other than these showed a withering and the leaves were withered and changed into high green due to an extrem drought. Though it was about same at the beginning, the drought damage on cabbage was worse than that on radish period, and the reasos for this appears in the latter that the roots are grown too deep. 6. The cabbage showed a high affinity between treated plots and varieties. Consequently, it can be said that cabbage is very suseptive to drought damage, and the yield showed a difference of 35% to 56% depending on the selection oe varieties. 7. The radish also showed a high affinity between the treated plots, however, almost us affinity existed between varieties. Therfore, the yield of radish largely depends on the extent of drought, and the selection of variety does not affect at all. 8. The normal consumptive use on cabbage is $0.62{\ell}/sec$, while that on radish is $0.64{\ell}/sec$, and the minimum optimum water requirement that was obtained in this study is $4,000cc/day/m^3$ or $0.462{\ell}/sec/ha$.

• Applied Biological Chemistry
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• v.10
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• pp.1-13
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• 1968

Phytin is a salt(mainly calcium and magnesium) of phytic acid and its purity and molecular formula can be determined by assaying the contents of phosporus, calcium and magnesium in phytin. In order to devise a new method for the quantitative analysis of the three elements in phytin, the chelatometric method was developed as follows: 1) As the pretreatment for phytin analysis, it was ashfied st $550{\sim}600^{\circ}C$ in the presence of concentrated nitric acid. This dry process is more accurate than the wet process. 2) Phosphorus, calcium and megnesium were analyzed by the conventional and the new method described here, for the phytin sample decomposed by the dry process. The ashfied phytin solution in hydrochloric acid was partitioned into cation and anion fractions by means of a ration exchange resin. A portion of the ration fraction was adjusted to pH 7.0, followed by readjustment to pH 10 and titrated with standard EDTA solution using the BT [Eriochrome black T] indicator to obtain the combined value of calcium and magnesium. Another portion of the ration fraction was made to pH 7.0, and a small volume of standard EDTA solution was added to it. pH was adjusted to $12{\sim}13$ with 8 N KOH and it was titrate by a standard EDTA solution in the presence of N-N[2-Hydroxy-1-(2-hydroxy-4-sulfo-1-naphytate)-3-naphthoic acid] diluted powder indicator in order to obtain the calcium content. Magnesium content was calculated from the difference between the two values. From the anion fraction the magnesium ammonium phosphate precipitate was obtained. The precipitate was dissolved in hydrochloric acid, and a standard EDTA solution was added to it. The solution was adjusted to pH 7.0 and then readjusted to pH 10.0 by a buffer solution and titrated with a standard magnesium sulfate solution in the presence of BT indicator to obtain the phosphorus content. The analytical data for phosphorus, calcium and magnesium were 98.9%, 97.1% and 99.1% respectively, in reference to the theoretical values for the formula $C_6H_6O_{24}P_6Mg_4CaNa_2{\cdot}5H_2O$. Statical analysis indicated a good coincidence of the theoretical and experimental values. On the other hand, the observed values for the three elements by the conventional method were 92.4%, 86.8% and 93.8%, respectively, revealing a remarkable difference from the theoretical. 3) When sodium phytate was admixed with starch and subjected to the analysis of phosphorus, calcium and magnesium by the chelatometric method, their recovery was almost 100% 4) In order to confirm the accuracy of this method, phytic acid was reacted with calcium chloride and magnesium chloride in the molar ratio of phytic: calcium chloride: magnesium chloride=1 : 5 : 20 to obtain sodium phytate containing one calcium atom and four magnesium atoms per molecule of sodium phytate. The analytical data for phosporus, calcium and magnesium were coincident with those as determine d by the aforementioned method. The new method employing the dry process, ion exchange resin and chelatometric assay of phosphorus, calcium and magnesium is considered accurate and rapid for the determination of phytin.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.79-94
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• 2013

Recently, the high value added business is steadily growing in the culture and art area. To generated high value from a performance, the satisfaction of audience is necessary. The flow in a critical factor for satisfaction, and it should be induced from audience and measures. To evaluate interest and emotion of audience on contents, producers or investors need a kind of index for the measurement of the flow. But it is neither easy to define the flow quantitatively, nor to collect audience's reaction immediately. The previous studies of the group flow were evaluated by the sum of the average value of each person's reaction. The flow or "good feeling" from each audience was extracted from his face, especially, the change of his (or her) expression and body movement. But it was not easy to handle the large amount of real-time data from each sensor signals. And also it was difficult to set experimental devices, in terms of economic and environmental problems. Because, all participants should have their own personal sensor to check their physical signal. Also each camera should be located in front of their head to catch their looks. Therefore we need more simple system to analyze group flow. This study provides the method for measurement of audiences flow with group synchronization at same time and place. To measure the synchronization, we made real-time processing system using the Differential Image and Group Emotion Analysis (GEA) system. Differential Image was obtained from camera and by the previous frame was subtracted from present frame. So the movement variation on audience's reaction was obtained. And then we developed a program, GEX(Group Emotion Analysis), for flow judgment model. After the measurement of the audience's reaction, the synchronization is divided as Dynamic State Synchronization and Static State Synchronization. The Dynamic State Synchronization accompanies audience's active reaction, while the Static State Synchronization means to movement of audience. The Dynamic State Synchronization can be caused by the audience's surprise action such as scary, creepy or reversal scene. And the Static State Synchronization was triggered by impressed or sad scene. Therefore we showed them several short movies containing various scenes mentioned previously. And these kind of scenes made them sad, clap, and creepy, etc. To check the movement of audience, we defined the critical point, ${\alpha}$and ${\beta}$. Dynamic State Synchronization was meaningful when the movement value was over critical point ${\beta}$, while Static State Synchronization was effective under critical point ${\alpha}$. ${\beta}$ is made by audience' clapping movement of 10 teams in stead of using average number of movement. After checking the reactive movement of audience, the percentage(%) ratio was calculated from the division of "people having reaction" by "total people". Total 37 teams were made in "2012 Seoul DMC Culture Open" and they involved the experiments. First, they followed induction to clap by staff. Second, basic scene for neutralize emotion of audience. Third, flow scene was displayed to audience. Forth, the reversal scene was introduced. And then 24 teams of them were provided with amuse and creepy scenes. And the other 10 teams were exposed with the sad scene. There were clapping and laughing action of audience on the amuse scene with shaking their head or hid with closing eyes. And also the sad or touching scene made them silent. If the results were over about 80%, the group could be judged as the synchronization and the flow were achieved. As a result, the audience showed similar reactions about similar stimulation at same time and place. Once we get an additional normalization and experiment, we can obtain find the flow factor through the synchronization on a much bigger group and this should be useful for planning contents.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.1-22
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• 2021

Aspect Based Sentiment Analysis (ABSA), which analyzes sentiment based on aspects that appear in the text, is drawing attention because it can be used in various business industries. ABSA is a study that analyzes sentiment by aspects for multiple aspects that a text has. It is being studied in various forms depending on the purpose, such as analyzing all targets or just aspects and sentiments. Here, the aspect refers to the property of a target, and the target refers to the text that causes the sentiment. For example, for restaurant reviews, you could set the aspect into food taste, food price, quality of service, mood of the restaurant, etc. Also, if there is a review that says, "The pasta was delicious, but the salad was not," the words "steak" and "salad," which are directly mentioned in the sentence, become the "target." So far, in ABSA, most studies have analyzed sentiment only based on aspects or targets. However, even with the same aspects or targets, sentiment analysis may be inaccurate. Instances would be when aspects or sentiment are divided or when sentiment exists without a target. For example, sentences like, "Pizza and the salad were good, but the steak was disappointing." Although the aspect of this sentence is limited to "food," conflicting sentiments coexist. In addition, in the case of sentences such as "Shrimp was delicious, but the price was extravagant," although the target here is "shrimp," there are opposite sentiments coexisting that are dependent on the aspect. Finally, in sentences like "The food arrived too late and is cold now." there is no target (NULL), but it transmits a negative sentiment toward the aspect "service." Like this, failure to consider both aspects and targets - when sentiment or aspect is divided or when sentiment exists without a target - creates a dual dependency problem. To address this problem, this research analyzes sentiment by considering both aspects and targets (Target-Aspect-Sentiment Detection, hereby TASD). This study detected the limitations of existing research in the field of TASD: local contexts are not fully captured, and the number of epochs and batch size dramatically lowers the F1-score. The current model excels in spotting overall context and relations between each word. However, it struggles with phrases in the local context and is relatively slow when learning. Therefore, this study tries to improve the model's performance. To achieve the objective of this research, we additionally used auxiliary loss in aspect-sentiment classification by constructing CNN(Convolutional Neural Network) layers parallel to existing models. If existing models have analyzed aspect-sentiment through BERT encoding, Pooler, and Linear layers, this research added CNN layer-adaptive average pooling to existing models, and learning was progressed by adding additional loss values for aspect-sentiment to existing loss. In other words, when learning, the auxiliary loss, computed through CNN layers, allowed the local context to be captured more fitted. After learning, the model is designed to do aspect-sentiment analysis through the existing method. To evaluate the performance of this model, two datasets, SemEval-2015 task 12 and SemEval-2016 task 5, were used and the f1-score increased compared to the existing models. When the batch was 8 and epoch was 5, the difference was largest between the F1-score of existing models and this study with 29 and 45, respectively. Even when batch and epoch were adjusted, the F1-scores were higher than the existing models. It can be said that even when the batch and epoch numbers were small, they can be learned effectively compared to the existing models. Therefore, it can be useful in situations where resources are limited. Through this study, aspect-based sentiments can be more accurately analyzed. Through various uses in business, such as development or establishing marketing strategies, both consumers and sellers will be able to make efficient decisions. In addition, it is believed that the model can be fully learned and utilized by small businesses, those that do not have much data, given that they use a pre-training model and recorded a relatively high F1-score even with limited resources.

• Journal of Korean Society of Forest Science
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• v.30 no.1
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• pp.19-29
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• 1976

The fiberboard and paper mills in this country are much affected by the price hikes and shortage of phenolic resins, since phenolic acid as a raw material depends on imported good. It is prerequisite to fiberboard industry to help replace with other sized and stabilize the prices and supply of them, improving the quality of boards. Thus, the present study was carried out to examine the effect of strength increasing sized such as urea formaldehyde resin (anion and cation type) and urea melamine copolymer resin, on the quality of the wet forming hardboard, and comparing them with two types of proprietary modified melamine resins, and ordinary size, phenol resin. The Asplund pulp was prepared from wood wastes mixed with 20 percent of lauan and 80 percent of pines as a fibrous material. After sizing agents were added at a pH of 4.5 for 10 minutes with alum in the beater, the stock was made in the form of wet sheet, prepared, and then performed by hot pressing cycle: $180^{\circ}C$, $50-6-5kg/cm^2$, 1-2-7 minutes. The properties of hardboard were examined after air conditioning. The results obtained are summarized as follows: 1. There is a significant difference in specific gravity among hardboards that were treated with strength increasing resins, but no difference is effected by the increase in the resin content. In the case of modified melamine resin, its specific gravity is highest. The middle group comprises cation type of urea resin, anion type of urea resin, and acid colloid of urea-melamine copolymer resin. The lowest is phenolic resin. 2. The difference of the moisture content of hardboard both by the resins and by the amount of each resin applied is significant. The moisture content of hardboard becomes lower along with the increase of each resin content, but there is no difference between 2 and 3 percent. 3. For water absorption, there is a significant difference both in the adhesives used and in the amount of paraffin wax emulsion. The water resistance becomes higher inn proportion to the content of the paraffin wax emulsion. To satisfy KS F standards of the water resistance, a proprietary modified melamine resin (p-6100) and modified cation type of urea resin (p-1500) do not require any paraffin wax emulsion, but in the case of anion type of urea resin, cation type of urea resin, and urea-melamine copolymer resin, 1 percent of paraffin wax emulsion is needed, and 2 percent of paraffin wax emulsion in the case of phenolic resin. 4. The difference of flexural strength of hardboard both by the resins and by the amount of each resin is significant. Modified melamine resin shows the highest degree of flexural strength. Among the middle group are urea-melamine copolymer resin, p-1500, anion type of urea resin, and cation type of urea resin. Phenolic resin is the lowest. The cause may be attributable to factors combined with the pressing temperature, sizing effect, and thermal efficiency of press platens heated electrically. 5. Considering the economic advantages and properties of hardboard, it is proposed that urea-melamine copolymer resin and cation type of urea resin be used for the development of the fiberboard industry. It is desirable to further develop the modified urea-melamine copolymer resin and cation type of urea resin through continuous study.

• The Journal of Natural Sciences
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• v.7
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• pp.133-162
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• 1995

Paderborn's companies, Wameling and Cassau, produce the liturgical vestments, which have much traditional artistic merit. And Kevelaerer Fahnen + Paramenten GmbH, located in Kevelater which is a place of pilgrimage of the Virgin Mary, was known to Europe, Africa, America and the Scandinavia Peninsula as the "Hidden Company" of liturgical vesments maker up to now. Paderborn and Kevelaer were the place of the center of the religious world and the Catholic ceremony during a good few centries. The Catholic liturgical vestiments of these 3 companies use versatile design, color, shape and techniques. These have not only the symbolism of religion, but also can meet our's expectations of utilization of modern textile art, art clothing and wide-all division of design. These give the understanding of symbolic meanings and harmony according to liturgical vestments to the believers. And these have an influence on mental thinking and induction of religious belief to the non-believers as the recognition and concerns about the religious art. The liturgical vestments are clothes which churchmen put on at the all ceremonial function of a mass, a sacrament, performance and a parade according to rules of church. These show the represen-tation of "Holy God" in silence and distinguish between common people and churchmen. And these represent a status and dignity of churchmen and induce majesty and respect to churchmen. Common clothes of the beginning of the Greece and Rome was developed to Christian clothes with the tendency of religion. There were no special uniforms distinguished from commen people until the Christianity was recognized officially by the Roman Emperor Constantinus at A.D.313. The color of liturgical vestments was originally white and changed to special colors according to liturgical day and each time by the Pope Innocentius at 12th century. The color and symbolic meaning of the liturgical vestments of present day was originated by the Pope St. Pius(1566-1572). Wool and Linen was used as decorations and materials in the beginnings and the special materials like silk was used after 4th century and beautiful materials made of gold thread was used at 12th century. It is expected that there is no critical changes to the liturgical vestments of future. But the development of liturgical vestments will continues slowly by the command of conservative church and will change to simple and convenient formes according to the culture, the trend of the times and the fashion of clothes. The companies of liturgical vestments develop versatile design, embroidery technique and realization of creative design for distinction of the liturgical vestments of each company and artistic progress. The cooperation of companies, artists and church will make the bright future of these 3 companies. We expect that our country will be a famous producing center of the liturgical vestments through the research and development of companies, participation of artists in religeous arts and concerts of church.

• Journal of agricultural medicine and community health
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• v.26 no.1
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• pp.81-103
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• 2001

This study was conducted to identify the health behavior of middle-aged rural women and the factors that have an effect on them. For the purpose of the study, examinations were made from March 01, 2000 to March 31, 2000 with 468 women aged 40 to 64 out of 2,263 people whom four Primary Health Posts located in Yechon County, Kyongsangbuk-do Province, are in charge of. The results are summarized as follows. 17.5% of the subjects responded that the extent of their own interest in health were high. For the subjects having a chronic disease, a nuclear family, or an open family atmosphere, the extent appeared to be relatively higher, 15.4% responded that the extent of family's interest in their health was high. It was significantly high if the extent of education was high or if the family atmosphere was open. The subjects' average score of self-efficacy was 49.9 out of 68. The score significantly varied depending on religion, education, living together with a spouse or not, and the extent of the subjects' interest in health. The family pattern, family atmosphere, family's interest in the subjects' health were the variables that significantly influenced the self-efficacy. The average score of family function was 5.51 out of 10. The score significantly varies depending on age, education, occupation, financial status, the extent of the subjects' own interest in health, family atmosphere and family's interest in the subjects' health. In the practice of health behavior, the nonsmoking rate was 89.5%, the nondrinking rate 63.0%, the rate of exercising practice 6.6%, the rate of normal sleeping 75.6%, the rate of eating breakfast 91.7%, the rate of not eating between meals 18.2%, and the standard BMI 69.2%. In the frequency of health behavior, the subjects with the Breslow Index of 0-3, 4-5 and 6-7 accounted for 4.5%, 53.2%, and 42.3%, respectively. The average score of health behavior was 5.20 out of 7, in which significant variables were living together with a spouse or not, financial status, absence or presence of a chronic disease, and family atmosphere. In the multiple regression analysis with health behavior as a dependent variable, it was shown that living together with a spouse or not, financial status, and family atmosphere were the significantly substantial variables. The subjects were found to do health behavior well if they had not a spouse, a good financial status, or an open family atmosphere. They were also found to do health behavior well if the extent of self-efficacy was high or if the extent of family function was low, but these were not the significant variables. It is needed to develop a standard measuring tool fit for our environment and perform more studies in the future because the measuring tool used in this study was a tool developed in a foreign county. In promoting community health projects, it is required not to provide all community people with a uniform health program but to identify the health behavior of individuals and other variables such as living together with a spouse or not, financial status and family atmosphere before arranging for a proper health program.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.39-55
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• 2019

Recently banks and large financial institutions have introduced lots of Robo-Advisor products. Robo-Advisor is a Robot to produce the optimal asset allocation portfolio for investors by using the financial engineering algorithms without any human intervention. Since the first introduction in Wall Street in 2008, the market size has grown to 60 billion dollars and is expected to expand to 2,000 billion dollars by 2020. Since Robo-Advisor algorithms suggest asset allocation output to investors, mathematical or statistical asset allocation strategies are applied. Mean variance optimization model developed by Markowitz is the typical asset allocation model. The model is a simple but quite intuitive portfolio strategy. For example, assets are allocated in order to minimize the risk on the portfolio while maximizing the expected return on the portfolio using optimization techniques. Despite its theoretical background, both academics and practitioners find that the standard mean variance optimization portfolio is very sensitive to the expected returns calculated by past price data. Corner solutions are often found to be allocated only to a few assets. The Black-Litterman Optimization model overcomes these problems by choosing a neutral Capital Asset Pricing Model equilibrium point. Implied equilibrium returns of each asset are derived from equilibrium market portfolio through reverse optimization. The Black-Litterman model uses a Bayesian approach to combine the subjective views on the price forecast of one or more assets with implied equilibrium returns, resulting a new estimates of risk and expected returns. These new estimates can produce optimal portfolio by the well-known Markowitz mean-variance optimization algorithm. If the investor does not have any views on his asset classes, the Black-Litterman optimization model produce the same portfolio as the market portfolio. What if the subjective views are incorrect? A survey on reports of stocks performance recommended by securities analysts show very poor results. Therefore the incorrect views combined with implied equilibrium returns may produce very poor portfolio output to the Black-Litterman model users. This paper suggests an objective investor views model based on Support Vector Machines(SVM), which have showed good performance results in stock price forecasting. SVM is a discriminative classifier defined by a separating hyper plane. The linear, radial basis and polynomial kernel functions are used to learn the hyper planes. Input variables for the SVM are returns, standard deviations, Stochastics %K and price parity degree for each asset class. SVM output returns expected stock price movements and their probabilities, which are used as input variables in the intelligent views model. The stock price movements are categorized by three phases; down, neutral and up. The expected stock returns make P matrix and their probability results are used in Q matrix. Implied equilibrium returns vector is combined with the intelligent views matrix, resulting the Black-Litterman optimal portfolio. For comparisons, Markowitz mean-variance optimization model and risk parity model are used. The value weighted market portfolio and equal weighted market portfolio are used as benchmark indexes. We collect the 8 KOSPI 200 sector indexes from January 2008 to December 2018 including 132 monthly index values. Training period is from 2008 to 2015 and testing period is from 2016 to 2018. Our suggested intelligent view model combined with implied equilibrium returns produced the optimal Black-Litterman portfolio. The out of sample period portfolio showed better performance compared with the well-known Markowitz mean-variance optimization portfolio, risk parity portfolio and market portfolio. The total return from 3 year-period Black-Litterman portfolio records 6.4%, which is the highest value. The maximum draw down is -20.8%, which is also the lowest value. Sharpe Ratio shows the highest value, 0.17. It measures the return to risk ratio. Overall, our suggested view model shows the possibility of replacing subjective analysts's views with objective view model for practitioners to apply the Robo-Advisor asset allocation algorithms in the real trading fields.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.149-169
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• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."