• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.67-80
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• 2023

Rice is an important food crop for most of the population in Nowadays, psychologists consider social media an important tool to examine mental disorders. Among these disorders, depression is one of the most common yet least cured disease Since abundant of writers having extensive followers express their feelings on social media and depression is significantly increasing, thus, exploring the literary text shared on social media may provide multidimensional features of depressive behaviors: (1) Background: Several studies observed that depressive data contains certain language styles and self-expressing pronouns, but current study provides the evidence that posts appearing with self-expressing pronouns and depressive language styles contain high emotional temperatures. Therefore, the main objective of this study is to examine the literary cyber writers' posts for discovering the symptomatic signs of depression. For this purpose, our research emphases on extracting the data from writers' public social media pages, blogs, and communities; (3) Results: To examine the emotional temperatures and sentences usage between depressive and not depressive groups, we employed the SentiStrength algorithm as a psycholinguistic method, TF-IDF and N-Gram for ranked phrases extraction, and Latent Dirichlet Allocation for topic modelling of the extracted phrases. The results unearth the strong connection between depression and negative emotional temperatures in writer's posts. Moreover, we used Naïve Bayes, Support Vector Machines, Random Forest, and Decision Tree algorithms to validate the classification of depressive and not depressive in terms of sentences, phrases and topics. The results reveal that comparing with others, Support Vectors Machines algorithm validates the classification while attaining highest 79% f-score; (4) Conclusions: Experimental results show that the proposed system outperformed for detection of depression trends in literary cyber writers using sentiment analysis.

• Atmosphere
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• v.19 no.2
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• pp.169-182
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• 2009

To improve the performance of climate and numerical models, concerns on the land-atmosphere schemes are steadily increased in recent years. For the realistic calculation of land-atmosphere interaction, a land surface information of high quality is strongly required. In this study, a new land cover map over the Korean peninsula was developed using MODIS (MODerate resolution Imaging Spectroradiometer) data. The seven phenological data set (maximum, minimum, amplitude, average, growing period, growing and shedding rate) derived from 15-day normalized difference vegetation index (NDVI) were used as a basic input data. The ISOData (Iterative Self-Organizing Data Analysis), a kind of unsupervised non-hierarchical clustering method, was applied to the seven phenological data set. After the clustering, assignment of land cover type to the each cluster was performed according to the phenological characteristics of each land cover defined by USGS (US. Geological Survey). Most of the Korean peninsula are occupied by deciduous broadleaf forest (46.5%), mixed forest (15.6%), and dryland crop (13%). Whereas, the dominant land cover types are very diverse in South-Korea: evergreen needleleaf forest (29.9%), mixed forest (26.6%), deciduous broadleaf forest (16.2%), irrigated crop (12.6%), and dryland crop (10.7%). The 38 in-situ observation data-base over South-Korea, Environment Geographic Information System and Google-earth are used in the validation of the new land cover map. In general, the new land cover map over the Korean peninsula seems to be better classified compared to the USGS land cover map, especially for the Savanna in the USGS land cover map.

• Korean Journal of Environmental Biology
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• v.23 no.1
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• pp.32-46
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• 2005

The distribution and standing crop of the phytoplankton were investigated at five freshwater lakes Suwon-si and Pyongtaek-si, Gyeonggi-do from Mar. to Nov., 2003. In this investigation, 199 taxa in total were found and classified as 5 phylums 5 classes 16 orders 26 families 72 genera 167 species 1 subspecies 28 varieties and 3 forms by Engler's classification system. The indicator species of clean water was Cladophora glomerata, which was appeared in Gwanggyo reservoir on September, 2003. Twenty taxa including Oscillatoria chlorina were identified as the indicators of water pollution, and three taxa of cyanophyte were toxic algae. In terms of Yang and Dickman's standard of chlorophyll-a content in eutrophication of water, four lakes including Seo lake were found to be in the hypereutrophic state, and Gwanggyo reservoir was in eutrophic state except in winter.

• The Korea Journal of Herbology
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• v.34 no.5
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• pp.1-12
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• 2019

Objectives : The consumption of licorice is large in Korea, but domestic production is insufficient due to the lack of adaptability. This study aimed to provide a morphological basis for adding interspecific hybrid licorice with improved adaptability to pharmacopoeia. Methods : This study was to establish identification criteria for the original plants, external and internal morphology of the authentic herbal medicines (Glycyrrhiza uralensis, G. glabra and G. inflata), market products and artificially interspecific hybrid forms of licorice. For this purpose, previous studies were investigated and visual and histological observations were carried out. We focused on the internal morphology by microscopic observation for securing objectivity. Finally, we proposed the identification keys for precise classification of each part. Results : 1) Original plant : Licorice species in the compendium were distinguished by the number of leaflets, presence of hair on the fruit, curvature and swelling of the fruit. 2) External morphology : Licorice species were distinguished by degree of powderiness, tearing gap, radial structure in the cross section and existence of protrusion of outer epidermis. 3) Internal morphology : Licorice species were distinguished by the degree of development of phloem fiber bundle, development of obliterated sieve, whether the secondary medullary ray are branched. In the case of interspecific hybrids, the characteristics of both species used for hybridization were mixed in all observation methods. Conclusions : These results suggest that the interspecific crossbred licorice is suitable for the pharmacopoeial standard. Therefore, it can be applied as a herbal medicine through additional supplementary study.

• Journal of Forest and Environmental Science
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• v.40 no.1
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• pp.1-8
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• 2024

Recently, intensive research has been conducted to develop innovative methods for diagnosing plant diseases based on hyperspectral technologies. Hyperspectral analysis is a new subject that combines optical spectroscopy and image analysis methods, which makes it possible to simultaneously evaluate both physiological and morphological parameters. Among the physiological and morphological parameters are classifying healthy and diseased plants, assessing the severity of the disease, differentiating the types of pathogens, and identifying the symptoms of biotic stresses at early stages, including during the incubation period, when the symptoms are not visible to the human eye. Plant diseases cause significant economic losses in agriculture around the world as the symptoms of diseases usually appear when the plants are infected severely. Early detection, quantification, and identification of plant diseases are crucial for the targeted application of plant protection measures in crop production. Hence, this can be done by possible applications of hyperspectral sensors and platforms on different scales for disease diagnosis. Further, the main areas of application of hyperspectral sensors in the diagnosis of plant diseases are considered, such as detection, differentiation, and identification of diseases, estimation of disease severity, and phenotyping of disease resistance of genotypes. This review provides a deeper understanding, of basic principles and implementation of hyperspectral sensors that can measure pathogen-induced changes in plant physiology. Hence, it brings together critically assessed reports and evaluations of researchers who have adopted the use of this application. This review concluded with an overview that hyperspectral sensors, as a non-invasive system of measurement can be adopted in early detection, identification, and possible solutions to farmers as it would empower prior intervention to help moderate against decrease in yield and/or total crop loss.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.5
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• pp.696-704
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• 2010

The objective of this study was analysis of two methods of land suitability classification for wild edible green. One method was Maximum limiting factor method (MLFM) and the other was Multi-regression method (MRM) for land suitability classification for wild edible green. The investigation was carried out in Pyeongchang, Hongcheong, Hoeingseong, and Yanggu regions in Korea. The obtained results showed that factors related to the decision classification of the land suitability for wild edible green cultivation were land slope, altitude, soil morphology and gravel contents so on. The classification of the best suitability soil for wild edible greens were fine loamy (silty), valley or fan of soil morphology, well drainage class, B-slope (2~7%), available soil depth deeper than 100cm, and altitude higher than 501m. Contribution of soil that influence to crop yields using Multi-regression method were slope 0.30, altitude 0.22, soil morphology 0.13, drainage classes 0.09, available soil depth 0.07, and soil texture 0.01 orders. Using MLFM, area of best suitable land was 0.2%, suitable soil 15.0%, possible soil 16.7%, and low productive soil 68.0% in Hongcheon region of Gangwon province. But, area of best suitable land was 35.1%, suitable soil 30.7%, possible soil 10.3%, and low productive soil 23.9% by MRM. There was big difference of suitable soil area between two methods (MLFM and MRM). When decision classificatin of the land suitability for wild edible green cultivation should consider enough analysis methods. Furthermore, to establishment of land suitability classification for crop would be better use MRM than MLFM.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.47
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• pp.63-94
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• 2002

On the purpose to suggest an advanced scheme in assessing the domestic wheat quality, this paper reviewed the inspection systems of wheat in major wheat producing countries as well as the quality criteria which are being used in wheat grading and classification. Most wheat producing countries are adopting both classifications of class and grade to provide an objective evaluation and an official certification to their wheat. There are two main purposes in the wheat classification. The first objectives of classification is to match the wheat with market requirements to maximize market opportunities and returns to growers. The second is to ensure that payments to glowers aye made on the basis of the quality and condition of the grain delivered. Wheat classes has been assigned based on the combination of cultivation area, seed-coat color, kernel and varietal characteristics that are distinctive. Most reputable wheat marketers also employ a similar approach, whereby varieties of a particular type are grouped together, designed by seed coat colour, grain hardness, physical dough properties, and sometimes more precise specification such as starch quality, all of which are genetically inherited characteristics. This classification in simplistic terms is the categorization of a wheat variety into a commercial type or style of wheat that is recognizable for its end use capabilities. All varieties registered in a class are required to have a similar end-use performance that the shipment be consistent in processing quality, cargo to cargo and year to year, Grain inspectors have historically determined wheat classes according to visual kernel characteristics associated with traditional wheat varieties. As well, any new wheat variety must not conflict with the visual distinguishability rule that is used to separate wheats of different classes. Some varieties may possess characteristics of two or more classes. Therefore, knowledge of distinct varietal characteristics is necessary in making class determinations. The grading system sets maximum tolerance levels for a range of characteristics that ensure functionality and freedom from deleterious factors. Tests for the grading of wheat include such factors as plumpness, soundness, cleanliness, purity of type and general condition. Plumpness is measured by test weight. Soundness is indicated by the absence or presence of musty, sour or commercially objectionable foreign odors and by the percentage of damaged kernels that ave present in the wheat. Cleanliness is measured by determining the presence of foreign material after dockage has been removed. Purity of class is measured by classification of wheats in the test sample and by limitation for admixtures of different classes of wheat. Moisture does not influence the numerical grade. However, it is determined on all shipments and reported on the official certificate. U.S. wheat is divided into eight classes based on color, kernel Hardness and varietal characteristics. The classes are Durum, Hard Red Spring, Hard Red Winter, Soft Red Winter, Hard White, soft White, Unclassed and Mixed. Among them, Hard Red Spring wheat, Durum wheat, and Soft White wheat are further divided into three subclasses, respectively. Each class or subclass is divided into five U.S. numerical grades and U.S. Sample grade. Special grades are provided to emphasize special qualities or conditions affecting the value of wheat and are added to and made a part of the grade designation. Canadian wheat is also divided into fourteen classes based on cultivation area, color, kernel hardness and varietal characteristics. The classes have 2-5 numerical grades, a feed grade and sample grades depending on class and grading tolerance. The Canadian grading system is based mainly on visual evaluation, and it works based on the kernel visual distinguishability concept. The Australian wheat is classified based on geographical and quality differentiation. The wheat grown in Australia is predominantly white grained. There are commonly up to 20 different segregations of wheat in a given season. Each variety grown is assigned a category and a growing areas. The state governments in Australia, in cooperation with the Australian Wheat Board(AWB), issue receival standards and dockage schedules annually that list grade specifications and tolerances for Australian wheat. AWB is managing "Golden Rewards" which is designed to provide pricing accuracy and market signals for Australia's grain growers. Continuous payment scales for protein content from 6 to 16% and screenings levels from 0 to 10% based on varietal classification are presented by the Golden Rewards, and the active payment scales and prices can change with market movements.movements.

• Korean Journal of Soil Science and Fertilizer
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• v.17 no.2
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• pp.96-100
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• 1984

To give basic information on the agricultural mechanization and multiple cropping adoptability of the paddified clayey terrace soils which have poor permeability and poor adoptability to mechanization, a scheme of drainage classification as well as taxonomic classification was intended. 1. The degrees of gleization of terrace paddy soils were well distinguished by the comparison of "Redness rating" of their profiles. 2. When the criteria of "Imperfectly drained" soils were defined as follows; Soils have more than 50cm of accumulated depth which has less than 0.5 in Redness rating within 1.2m of the profile, the Geugrag series could be classified to "Imperfectly drained." The tentative classification of drainage class of Geugrag soils seemed to well matching with land suitability groups, and give possibility of drainage recommendation in the case of dry land crop cultivation. 3. The Geugrag soil which was well paddified by artificial surface irrigation, could be proposed to classify "Anthroaquic Ochraqualfs."

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.581-589
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• 2021

Using visible-near infrared(Vis-NIR) spectra combined with machine learning methods, the feasibility of quick and non-destructive classification of Convolvulaceae species was studied. The main aim of this study is to classify six Convolvulaceae species in the field in different geographical regions of South Korea using a handheld spectrometer. Spectra were taken at 1.5 nm intervals from the adaxial side of the leaves in the Vis-NIR spectral region between 400 and 1,075 nm. The obtained spectra were preprocessed with three different preprocessing methods to find the best preprocessing approach with the highest classification accuracy. Preprocessed spectra of the six Convolvulaceae sp. were provided as input for the machine learning analysis. After cross-validation, the classification accuracy of various combinations of preprocessing and modeling ranged between 43.4% and 98.6%. The combination of Savitzky-Golay and Support vector machine methods showed the highest classification accuracy of 98.6% for the discrimination of Convolvulaceae sp. The growth stage of the plants, different measuring locations, and the scanning position of leaves on the plant were some of the crucial factors that affected the outcomes in this investigation. We conclude that Vis-NIR spectroscopy, coupled with suitable preprocessing and machine learning approaches, can be used in the field to effectively discriminate Convolvulaceae sp. for effective weed monitoring and management.

• Korean Journal of Environmental Agriculture
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• v.36 no.3
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• pp.184-192
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• 2017

BACKGROUND: This study was performed to evaluate the residue dissipation of boscalid and spinetoram on crown daisy and sweet pepper affected by the morphology of the crop. The half-lives and dissipation rate constants for boscalid and spinetoram on crown daisy and sweet pepper were calculated. And then lower limit of 95% confidence interval for dissipation rate constant could be used to propose the pre-harvest residue limit. METHODS AND RESULTS: The pesticide products diluted according to the pesticide label were applied one time on crown daisy and sweet pepper at 2 field sites, respectively. Initial concentration of boscalid and spinetoram on crown daisy after application were in the range of 72.80~117.15 mg/kg and 2.82~4.67 mg/kg, respectively. And Initial concentration of boscalid and spinetoram on sweet pepper were in the range of 1.58~1.62 mg/kg and 0.10~0.21 mg/kg, respectively. Boscalid and spinetoram for crown daisy dissipted below the maximum residue limit(MRL) at 10 and 2 days after application, respectively. All residues concentration of boscalid and spinetoram for sweet pepper below the MRL at 0 day after application. The half-lives based on dissipation rate constant for boscalid and spinetoram on crown daisy were 4.2~4.9 days and 3.0~2.4 days respectively. And the half-lives for boscalid and spinetoram on sweet pepper were 6.7~7.0 days and 2.8~4.0 days respectively. CONCLUSION: The difference in initial concentration of boscalid and spinetoram among crop commodities were due to different crop morphology with larger surface areas. This study was suggested that pre-harvest residue limit would be calculated from lower limit of 95% confidence interval for dissipation rate constant and would be useful to protect consumers by controlling the pesticide residues in crop.