• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• Journal of the Korean Society of Costume
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• v.1
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• pp.119-129
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• 1977

It is significant for developing the future for us to know our present age. In order to preserve our Korean costume as a fola clothes retaining our distinguished independent characterisitics and to help design the tomorrow of our Korean costume playing a role as a racial to develop the world clothing culture, a survey was conducted to investigate modern people's conscious-ness and wearing practumes of Korean costume by questionaire and interviewing methods. The results of the survey were analyzed as follows: (1) At present, Korean costumes were purchased as customtailored(64.0%) and as ready-made(17.8%) and most of them were not made at individual homes. The laundry and ironing of them were carried out at laundry shops(68.8%). Considering our present economic, social and cultural aspects, sowing, laundryand ironing will not be carried out at homes again in the future and ready made costumes seen to be produced in a large scale in the future. Garment makers and laundry shop operators should be trained how to make our Korean costumes retain our traditional beauty in the course of their production and laundry and the makers of ready-made costumes must make research how to efficiently produce ideal ready-made costumes by adopting the synchro system in their wrk odisivion. (2) The age group wearing Korean costumes most frequently was the aged people over 60 (their wearing rate; 45%-50%) and the group wearing them most frequently next io the aged people over 60, was housewives(their wearing rate; 15%-20%). Excludign aged people and housewives, other respondentsdid not wear Korean costumes very frequently. Men's wearing rate was lower their wearing rate was the younger their ages were and the less their monthly incomes were. Korean costumes were used for holiday and festival(60%), wedding and funeral ceremonies (52%), visiting and working(22%), casual wear(12.8%) and home wear(9.2%). The use of Korean costumes as casual and home wears, was lower than the use for holday, festival, visiting and working, Under our present circumstances in which our Korean people use both Western style clothes and Korean costumer, our Korean costume has lostits position as a basic and necessary requiement in Korean people's daily life and become a ceremonical and fancy costume. It is natural that the times and life change everything in our daily life. Our costume has to be made as good ceremonial and fancy clothes satisfying modern sensibility according to its new role. In order for us to get close with our clothes, a keen study must be carried out to cleat the color, material, style, function and harmony of the Korean costume matching the of the times. (3) The 47.8% of the respondents answered that they were proud of our Korean costume as our folk clothes, 47.6% replied that thought them just common and 1.1% responded that they were ashamed of it. Most of them were affirmative in feeling pride with our Korean costume. (4) Considering the functional aspect of Korean costumes, their strong points were symetric beauty, rhythmical beauty, unity feeling, harmonical beauty and detailed decorations. Their common shortcomings were lack of individuality and inadequateness for active life. The shortcomings of woman costumes were suppressing breast, making resperation difficult and in adequnteness in summer time. The main reason not to wear our Korean costumes, was due to the fact that they are incomvenient for active life. As a measure to eliminate such shortcomings, 1) the suspension system of skirt to remove the suppression of breast should be generally adopted. 2) they should be simplified in their structure to make them convenient for active life and adepuate in wearing them in hot weather in an extent to which the traditional beauty of the costume may not be lostand 3) a new technique must be explored for showing individuality by wearing method and new arrangment of colors and decorations. (5) The reasons desiring to wear Korean costumes were classifide as follows: A. Korean costumes are our traditional clothes(43.4%). B. Korean costumes are noble and beautiful(26.8%). C. They are accustomed to wear Korean costumes by habit(19.5%). D. Korean costumes are necessary for attending ceremoneis(9.5%). E. Miscellaneous reasons(0.8%). Classifying these reasons into age groups, the high age group over 40 wore them because they were easy to wear by habit and the low age group of 10-30 never thought that they were east to wear by habit. Considering that even those who were accustomed to wear Korean costumes showed a low wearing rate and that the young generation were accustomed to wear Western style clothes rather than Korean costumes, the wearing rate of Korean costumes will be reduced in the future if such trend continues. It is urgent for us to make our best efforts in order to enhance the interest of young generation in Korean costumes and not to make them lose the strong points of Korean costume in the future. (6) Conicering the plan of the respondents on what kind of clothes they were going to wear in the future, among the age group over 50, those who wanted to wear only Korean costumes were 24.8%(men) and 35.1%(women), those who wanted to wear 49.7%(men) and 47.4(women), those who wanted to wear chiefly Western style clothes were 20.7% (men) and 14.4%(women) and those who wanted to wear only Western style clothes, were 2.4% (men) and 2.1%(women). This shows that the general tendency to wear only or chiefly Korean costumes is more prevalent than that to wear only Western style. Among the age group under 50, the tendency to wear Western style clothes was conspicuous and most of the respondent answered that they would wear chiefly Western style clothes and Korean costumes occasionally. Only 5.4% of the respondent answered that they would wear only Western style clothes and this shows that meny respondents still wonted to wear Korean costumes. Those who wanted their descendants to wear what they desire, were 50.1%(men) and 68.8% (women) and those who wanted their descendants to wear Koran costumes occasionally, were 85.8%(men) and 86.3%(women). This shows that most of respondents wanted their descendants to wear Korean costumes. In order to realize, it is necessory for us to make ourdescendants recognize the preciousness of our traditional culture and modify our Korean costumes according to their taste so that they may like wearing them.

• Korean Chemical Engineering Research
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• v.52 no.5
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• pp.657-666
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• 2014

Coal gasification technology is considered as next generation clean coal technology even though it uses coal as fuel which releases huge amount of greenhouse gas because it has many advantages for carbon capture. Coal or pet-coke slurry gasification is very attractive technology at present and in the future because of its low construction cost and flexibility of slurry feeding system in spite of lower efficiency compared to dry feeding technology. In this study, we carried out gasification experiment using bituminous coal slurry sample by integrating coal slurry feeding facility and slurry burner into existing dry feeding compact gasifier. Especially, our experiment was conducted under fairly lower operation temperature than that of existing entrained-bed gasifier, resulting in partial slagging operation mode in which only part of ash was converted to slag and the rest of ash was released as fly ash. Carbon conversion rate was calculated from data analysis of collected slag and ash, and then cold gas efficiency, which is the most important indicator of gasifier performance, was estimated by carbon mass balance method. Fairly high performance considering pilot-scale experiment, 98.5% of carbon conversion and 60.4% of cold gas efficiency, was achieved. In addition, soundness of experimental result was verified from the comparison with chemical equilibrium composition and energy balance calculations.

• 한국균학회소식:학술대회논문집
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• 2015.05a
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• pp.53-53
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• 2015

Agrobacterium tumefaciens-mediated transformation(ATMT) of Flammulina velutipes was used to produce a diverse number of transformants to discover the functions of gene that is vital for its variation color, spore pattern and cellulolytic activity. Futhermore, the transformant pool will be used as a good genetic resource for studying gene functions. Agrobacterium-mediated transformation was conducted in order to generate intentional mutants of F. velutipes strain KACC42777. Then Agrobacterium tumefaciens AGL-1 harboring pBGgHg was transformed into F. velutipes. This method is use to determine the functional gene of F. velutipes. Inverse PCR was used to insert T-DNA into the tagged chromosomal DNA segments and conducting sequence analysis of the F. velutipes. But this experiment had trouble in diverse morphological mutants because of dikaryotic nature of mushroom. It needed to make monokaryotic fruiting varients which introduced genes of compatible mating types. In this study, next generation sequencing data was generated from 28 strains of Flammulina velutipes with different phenotypes using Illumina Hiseq platform. Filtered short reads were initially aligned to the reference genome (KACC42780) to construct a SNP matrix. And then we built a phylogenetic tree based on the validated SNPs. The inferred tree represented that white- and brown- fruitbody forming strains were generally separated although three brown strains, 4103, 4028, and 4195, were grouped with white ones. This topological relationship was consistently reappeared even when we used randomly selected SNPs. Group I containing 4062, 4148, and 4195 strains and group II containing 4188, 4190, and 4194 strains formed early-divergent lineages with robust nodal supports, suggesting that they are independent groups from the members in main clades. To elucidate the distinction between white-fruitbody forming strains isolated from Korea and Japan, phylogenetic analysis was performed using their SNP data with group I members as outgroup. However, no significant genetic variation was noticed in this study. A total of 28 strains of Flammulina velutipes were analyzed to identify the genomic regions responsible for producing white-fruiting body. NGS data was yielded by using Illumina Hiseq platform. Short reads were filtered by quality score and read length were mapped on the reference genome (KACC42780). Between the white- and brown fruitbody forming strains. There is a high possibility that SNPs can be detected among the white strains as homozygous because white phenotype is recessive in F. velutipes. Thus, we constructed SNP matrix within 8 white strains. SNPs discovered between mono3 and mono19, the parental monokaryotic strains of 4210 strain (white), were excluded from the candidate. If the genotypes of SNPs detected between white and brown strains were identical with those in mono3 and mono19 strains, they were included in candidate as a priority. As a result, if more than 5 candidates SNPs were localized in single gene, we regarded as they are possibly related to the white color. In F. velutipes genome, chr01, chr04, chr07,chr11 regions were identified to be associated with white fruitbody forming. White and Brown Fruitbody strains can be used as an identification marker for F. veluipes. We can develop some molecular markers to identify colored strains and discriminate national white varieties against Japanese ones.

• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.292-292
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• 2016

Transition metal dichalcogenides (TMDs) with a two-dimensional layered structure have been considered highly promising materials for next-generation flexible, wearable, stretchable and transparent devices due to their unique physical, electrical and optical properties. Recent studies on TMD devices have focused on developing a suitable doping technique because precise control of the threshold voltage ($V_{TH}$) and the number of tightly-bound trions are required to achieve high performance electronic and optoelectronic devices, respectively. In particular, it is critical to develop an ultra-low level doping technique for the proper design and optimization of TMD-based devices because high level doping (about $10^{12}cm^{-2}$) causes TMD to act as a near-metallic layer. However, it is difficult to apply an ion implantation technique to TMD materials due to crystal damage that occurs during the implantation process. Although safe doping techniques have recently been developed, most of the previous TMD doping techniques presented very high doping levels of ${\sim}10^{12}cm^{-2}$. Recently, low-level n- and p-doping of TMD materials was achieved using cesium carbonate ($Cs_2CO_3$), octadecyltrichlorosilane (OTS), and M-DNA, but further studies are needed to reduce the doping level down to an intrinsic level. Here, we propose a novel DNA-based doping method on $MoS_2$ and $WSe_2$ films, which enables ultra-low n- and p-doping control and allows for proper adjustments in device performance. This is achieved by selecting and/or combining different types of divalent metal and trivalent lanthanide (Ln) ions on DNA nanostructures. The available n-doping range (${\Delta}n$) on the $MoS_2$ by Ln-DNA (DNA functionalized by trivalent Ln ions) is between $6{\times}10^9cm^{-2}$ and $2.6{\times}10^{10}cm^{-2}$, which is even lower than that provided by pristine DNA (${\sim}6.4{\times}10^{10}cm^{-2}$). The p-doping change (${\Delta}p$) on $WSe_2$ by Ln-DNA is adjusted between $-1.0{\times}10^{10}cm^{-2}$ and $-2.4{\times}10^{10}cm^{-2}$. In the case of Co-DNA (DNA functionalized by both divalent metal and trivalent Ln ions) doping where $Eu^{3+}$ or $Gd^{3+}$ ions were incorporated, a light p-doping phenomenon is observed on $MoS_2$ and $WSe_2$ (respectively, negative ${\Delta}n$ below $-9{\times}10^9cm^{-2}$ and positive ${\Delta}p$ above $1.4{\times}10^{10}cm^{-2}$) because the added $Cu^{2+}$ ions probably reduce the strength of negative charges in Ln-DNA. However, a light n-doping phenomenon (positive ${\Delta}n$ above $10^{10}cm^{-2}$ and negative ${\Delta}p$ below $-1.1{\times}10^{10}cm^{-2}$) occurs in the TMD devices doped by Co-DNA with $Tb^{3+}$ or $Er^{3+}$ ions. A significant (factor of ~5) increase in field-effect mobility is also observed on the $MoS_2$ and $WSe_2$ devices, which are, respectively, doped by $Tb^{3+}$-based Co-DNA (n-doping) and $Gd^{3+}$-based Co-DNA (p-doping), due to the reduction of effective electron and hole barrier heights after the doping. In terms of optoelectronic device performance (photoresponsivity and detectivity), the $Tb^{3+}$ or $Er^{3+}$-Co-DNA (n-doping) and the $Eu^{3+}$ or $Gd^{3+}$-Co-DNA (p-doping) improve the $MoS_2$ and $WSe_2$ photodetectors, respectively.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.65 no.3
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• pp.161-171
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• 2020

Direct seeding is one of the rice seedling establishment methods that is increasingly being practiced by farmers to save labor and reduce costs. However, this method often causes poor germination under flooding conditions after sowing. In this study, we developed japonica elite lines with quantitative trait loci (QTL) associated with anaerobic germination (AG) tolerance to overcome poor germination and seedling establishment in wet direct seeding. The QTL introgression lines were developed from a cross between weedy photoblastic rice as the AG donor and the Nampyeong variety via phenotypic and genotypic selection. Compared to Nampyeong, the survival rates of the selected lines were improved by approximately 50% and 240% under field and greenhouse conditions, respectively. To improve selection efficiency by marker assisted selection, the QTL markers associated with AG tolerance were converted to cleaved amplified polymorphic sequence markers designed based on next-generation sequence analysis. These lines retained similar agronomic traits and yield potential to the parent, Nampyeong. Among these lines, we selected the most promising line, which exhibited high survival rate and good agricultural traits under flooding conditions and named the line as Jeonju643. This line will contribute to breeding programs aiming to develop rice cultivars adapted to wet direct seeding. This study demonstrates the successful application of marker-assisted selection to targeted introgression of anaerobic genes into a premium quality japonica rice variety.

• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.35-42
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• 2016

Recently many researches have been focused on the use of the markerless augmented reality system using face, foot, and hand of user's body to alleviate many disadvantages of the marker based augmented reality system. In addition, most existing augmented reality systems have been utilized rigid objects since they just desire to insert and to basic interaction with virtual object in the augmented reality system. In this paper, unlike restricted marker based augmented reality system with rigid objects that is based in display, we designed and implemented the markerless augmented reality system using deformable objects to apply various fields for interactive situations with a user. Generally, deformable objects can be implemented with mass-spring modeling and the finite element modeling. Mass-spring model can provide a real time simulation and finite element model can achieve more accurate simulation result in physical and mathematical view. In this paper, the proposed markerless augmented reality system utilize the mass-spring model using tetraheadron structure to provide real-time simulation result. To provide plausible simulated interaction result with deformable objects, the proposed method detects and tracks users hand with Kinect SDK and calculates the external force which is applied to the object on hand based on the position change of hand. Based on these force, 4th order Runge-Kutta Integration is applied to compute the next position of the deformable object. In addition, to prevent the generation of excessive external force by hand movement that can provide the natural behavior of deformable object, we set up the threshold value and applied this value when the hand movement is over this threshold. Each experimental test has been repeated 5 times and we analyzed the experimental result based on the computational cost of simulation. We believe that the proposed markerless augmented reality system with deformable objects can overcome the weakness of traditional marker based augmented reality system with rigid object that are not suitable to apply to other various fields including healthcare and education area.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.139-152
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• 2011

Recommender systems have become an important research field since the emergence of the first paper on collaborative filtering in the mid-1990s. In general, recommender systems are defined as the supporting systems which help users to find information, products, or services (such as books, movies, music, digital products, web sites, and TV programs) by aggregating and analyzing suggestions from other users, which mean reviews from various authorities, and user attributes. However, as academic researches on recommender systems have increased significantly over the last ten years, more researches are required to be applicable in the real world situation. Because research field on recommender systems is still wide and less mature than other research fields. Accordingly, the existing articles on recommender systems need to be reviewed toward the next generation of recommender systems. However, it would be not easy to confine the recommender system researches to specific disciplines, considering the nature of the recommender system researches. So, we reviewed all articles on recommender systems from 37 journals which were published from 2001 to 2010. The 37 journals are selected from top 125 journals of the MIS Journal Rankings. Also, the literature search was based on the descriptors "Recommender system", "Recommendation system", "Personalization system", "Collaborative filtering" and "Contents filtering". The full text of each article was reviewed to eliminate the article that was not actually related to recommender systems. Many of articles were excluded because the articles such as Conference papers, master's and doctoral dissertations, textbook, unpublished working papers, non-English publication papers and news were unfit for our research. We classified articles by year of publication, journals, recommendation fields, and data mining techniques. The recommendation fields and data mining techniques of 187 articles are reviewed and classified into eight recommendation fields (book, document, image, movie, music, shopping, TV program, and others) and eight data mining techniques (association rule, clustering, decision tree, k-nearest neighbor, link analysis, neural network, regression, and other heuristic methods). The results represented in this paper have several significant implications. First, based on previous publication rates, the interest in the recommender system related research will grow significantly in the future. Second, 49 articles are related to movie recommendation whereas image and TV program recommendation are identified in only 6 articles. This result has been caused by the easy use of MovieLens data set. So, it is necessary to prepare data set of other fields. Third, recently social network analysis has been used in the various applications. However studies on recommender systems using social network analysis are deficient. Henceforth, we expect that new recommendation approaches using social network analysis will be developed in the recommender systems. So, it will be an interesting and further research area to evaluate the recommendation system researches using social method analysis. This result provides trend of recommender system researches by examining the published literature, and provides practitioners and researchers with insight and future direction on recommender systems. We hope that this research helps anyone who is interested in recommender systems research to gain insight for future research.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.121-139
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• 2014

Predicting corporate failure has been an important topic in accounting and finance. The costs associated with bankruptcy are high, so the accuracy of bankruptcy prediction is greatly important for financial institutions. Lots of researchers have dealt with the topic associated with bankruptcy prediction in the past three decades. The current research attempts to use ensemble models for improving the performance of bankruptcy prediction. Ensemble classification is to combine individually trained classifiers in order to gain more accurate prediction than individual models. Ensemble techniques are shown to be very useful for improving the generalization ability of the classifier. Bagging is the most commonly used methods for constructing ensemble classifiers. In bagging, the different training data subsets are randomly drawn with replacement from the original training dataset. Base classifiers are trained on the different bootstrap samples. Instance selection is to select critical instances while deleting and removing irrelevant and harmful instances from the original set. Instance selection and bagging are quite well known in data mining. However, few studies have dealt with the integration of instance selection and bagging. This study proposes an improved bagging ensemble based on instance selection using genetic algorithms (GA) for improving the performance of SVM. GA is an efficient optimization procedure based on the theory of natural selection and evolution. GA uses the idea of survival of the fittest by progressively accepting better solutions to the problems. GA searches by maintaining a population of solutions from which better solutions are created rather than making incremental changes to a single solution to the problem. The initial solution population is generated randomly and evolves into the next generation by genetic operators such as selection, crossover and mutation. The solutions coded by strings are evaluated by the fitness function. The proposed model consists of two phases: GA based Instance Selection and Instance based Bagging. In the first phase, GA is used to select optimal instance subset that is used as input data of bagging model. In this study, the chromosome is encoded as a form of binary string for the instance subset. In this phase, the population size was set to 100 while maximum number of generations was set to 150. We set the crossover rate and mutation rate to 0.7 and 0.1 respectively. We used the prediction accuracy of model as the fitness function of GA. SVM model is trained on training data set using the selected instance subset. The prediction accuracy of SVM model over test data set is used as fitness value in order to avoid overfitting. In the second phase, we used the optimal instance subset selected in the first phase as input data of bagging model. We used SVM model as base classifier for bagging ensemble. The majority voting scheme was used as a combining method in this study. This study applies the proposed model to the bankruptcy prediction problem using a real data set from Korean companies. The research data used in this study contains 1832 externally non-audited firms which filed for bankruptcy (916 cases) and non-bankruptcy (916 cases). Financial ratios categorized as stability, profitability, growth, activity and cash flow were investigated through literature review and basic statistical methods and we selected 8 financial ratios as the final input variables. We separated the whole data into three subsets as training, test and validation data set. In this study, we compared the proposed model with several comparative models including the simple individual SVM model, the simple bagging model and the instance selection based SVM model. The McNemar tests were used to examine whether the proposed model significantly outperforms the other models. The experimental results show that the proposed model outperforms the other models.

• Korean journal of applied entomology
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• v.42 no.1
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• pp.43-51
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• 2003

This study was carried out to develop the forecasting model of Pseudococcus comtocki Kuwana for timing spray. Field phonology and temperature-dependent development of p. comstocki were studied, and its stage transition models were developed. p comstocki occurred three generations a year in Suwon. The 1 st adults occurred during mid to late June, and the 2nd adults were abundant during mid to late August. The 3rd adults were observed after late October. The development times of each instar of p. comstocki decreased with increasing temperature up to 25$^{\circ}C$, and thereafter the development times increased. The estimated low-threshold temperatures were 14.5, 8.4, 10.2, 11.8, and 10.1$^{\circ}C$ for eggs, 1st+2nd nymphs, 3rd nymphs, preoviposition, and 1st nymphs to preoviposition, respectively. The degree-days (thermal constants) for completion of each instar development were 105 DD for egg,315 DD for 1st+2nd nymph, 143 DD for 3rd nymph, 143 DD for preoviposition, and 599 DD for 1 st nymph to preoviposition. The stage transition models of p. comstocki, which simulate the proportion of individuals shifted from a stage to the next stage, were constructed using the modified Sharpe and DeMichele model and the Weibull function. In field validation, degree-day models using mean-minus-base, sine wave, and rectangle method showed 2-3d, 1-7d, and 0-6 d deviation with actual data in predicting the peak oviposition time of the 1st and 2nd generation adults, respectively. The rate summation model, in which daily development rates estimated by biophysical model of Sharpe and DeMichele were accumulated, showed 1-2 d deviation with actual data at the same phonology predictions.