• Journal of Forest and Environmental Science
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• 제25권1호
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• pp.49-55
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• 2009

The present study analyses the effect of land use on the vegetation of some desert ecosystems in Abu Dhabi, United Arab Emirates (UAE). Three sites were selected to represent different types of land use, inside Umm Al-Banadeq forest, outside the forest and along Abu Dhabi-Al Ain Trucks Road. In total, fifty-two stands were examined; including a matrix of 14 species ${\times}$ 52 stands. Based on species cover data, stands were classified using TWINSPAN and ordinated using DCA. Four vegetation groups were generated at level three of classification. Zygophyllum mandavillei was dominant in most vegetation groups; Heliotropium bacciferum dominated vegetation groups inhabited the forest. Species richness, species turnover, relative evenness and relative concentration of dominance of forest vegetation groups were 2.8, 5.7, 0.7, and 2.0, respectively. The differences were attributed to both natural variability and forestry-induced changes, including change in land use, drainage and ploughing and shading by trees. Vegetation group inhabited Abu Dhabi-Al Ain Trucks Road, that were dominated by Haloxylon salicornicum and Zygophyllum mandavillei have high total cover (8.8 m per $m^{-1}$). Most community and vegetation attributes were significantly higher inside the forest than outside. Human interventions and environmental factors affected species diversity and abundance of these communities.

• 한국측량학회지
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• 제34권4호
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• pp.383-390
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• 2016

Remote sensing data has been widely used in the estimation of crop yields by employing statistical methods such as regression model. Machine learning, which is an efficient empirical method for classification and prediction, is another approach to crop yield estimation. This paper described the corn yield estimation in Iowa State using four machine learning approaches such as SVM (Support Vector Machine), RF (Random Forest), ERT (Extremely Randomized Trees) and DL (Deep Learning). Also, comparisons of the validation statistics among them were presented. To examine the seasonal sensitivities of the corn yields, three period groups were set up: (1) MJJAS (May to September), (2) JA (July and August) and (3) OC (optimal combination of month). In overall, the DL method showed the highest accuracies in terms of the correlation coefficient for the three period groups. The accuracies were relatively favorable in the OC group, which indicates the optimal combination of month can be significant in statistical modeling of crop yields. The differences between our predictions and USDA (United States Department of Agriculture) statistics were about 6-8 %, which shows the machine learning approaches can be a viable option for crop yield modeling. In particular, the DL showed more stable results by overcoming the overfitting problem of generic machine learning methods.

• 한국환경복원기술학회지
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• 제10권6호
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• pp.53-61
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• 2007

Most of the plants and trees are landscaping plants at the university campus, Thus, the natural flora can be found on sidewalks like urban area. In order to investigate the flora on sidewalks of the university campus, the vegetation survey was done. The study site is Natural Science Campus, Sungkyunkwan University which is located at Suwon, Korea. Vascular plants surveyed were consisted of 130 taxa, 39 families, 99 genera, 115 species, 15 varieties. Indigenous weeds was 101 species (77.7%). Naturalized weeds was 29 species (22.3%). In the families, Compositae 30 species (23%), Gramineae 18 species (14%), Leguminosae 9 species (7%), Caryophyllaceae 8 species (6%), Cruciferae 8 species (6%), Polygonaceae 5 species (4%), Euphorbiaceae 5 species (4%), Scrophulariaceae 4 species (3%), Rosaceae 3 species (2%), Violaceae 3 species (2%), Convolvulaceae 3 species (2%) and etc. 34 species (27%). Life Form of flora in the site by Raunkiaer classification was Therophytes 67 species (51.5%), Hemicryptophytes 46 species (35.4%), Geophytes 8 species (6.2%), Nanophanerophytes 4 species (3.1%), Phanerohytes 3 species (2.3%) and Chamaephytes 2 species (1.5%). Naturalized Ratios was 10.7%.

• Animal cells and systems
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• 제13권4호
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• pp.453-460
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• 2009

Morphological and molecular classifications were attempted in an effort to establish species-specific classifications of three species of the genus Pholis in Korea; these species were subjected to morphological and molecular methodologies using body measurements, RFLP, RAPD, and phylogenetic trees using the nucleotide sequences of mitochondrial 16S and 12S ribosomal DNAs, cytochrome c oxidase I, and cytochrome b. The data demonstrated that the three species of genus Pholis are distinct from each other, both morphologically and genetically.

• 한국자원식물학회:학술대회논문집
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• 한국자원식물학회 2001년도 The 8th International Symposium
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• pp.9-14
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• 2001

Today information is important for man and total fields. Science field is not exception. Currently information age things of information is only useful for man and total industry. So bioinformation is necessary of biodiversity in broadly wide and detailed information. Among information, bioinformation of biodiversity is important and utilization of living things. Among them, the mushroom(higher fungi) are an Important part in ecosystem as a decomposer responsible for recycling materials . Many living things today, however, have endangered by environmental pollution and ecological destruction. The higher fungi also are not exception. Mushroom has been used for food sources, pharmacy and forests resources from ancient times. Among biodiversity, database of mushroom is very necessary for university, institute and industry. This DB contains four items of native mushroom(higher fungi) from Korea. first item contain species, genus, family, order class, ad division according to the classification. Second item contain pharmaceutical purpose, food source, culture, toxic, anti-cancer of the application. Third item contain symbiosis, rotten trees of the ecological resources. Fourth item contain geographical distribution and illustrated literature. Information system is also available using KRISTAL II for searches on the WEB in URL http://ruby. kisti. re. kr/～mushroom

• 한국안전학회지
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• 제31권3호
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• pp.34-41
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• 2016

The purpose of this paper is to conduct ETA on six items of ESS: the whole system, battery, BMS, PCS, ESS and cable. To achieve that, ESS work flow and its components are categorized. Based on performance, human, environmental, management, and safety, this paper drew initiation events (IE) and end states (ES). ETA is applied to the main functions of each item, and the end states that may occur in one initiation event are suggested. In addition, detailed classification was performed to induce various end states on the basis of the suggested initiation events ; loss of grid electricity of ESS, loss of battery electricity(DC) of battery, impairment of electric function of BMS, loss of grid electricity(AC) of PCS, loss of data of EMS, Mechanical damage of cable, event sequence analysis conducted on the basis of event trees. If the suggested IEs and ESs are applied on the basis of ESS event cases, it is expected to prevent the same kinds of accident and operate ESS safely.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.744-746
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• 2003

A 3D modeling of urban area can be composed the terrain modeling that can express specific and shape of the terrain and the object modeling such as buildings, trees and facilities which are found in urban areas. Especially in a 3D modeling of building, it is very important to make a unit model by simplifying 3D structure and to take a texture mapping, which can help visualize surface information. In this study, the texture mapping technique, based on library for 3D urban modeling, was used for building modeling. This technique applies the texture map in the form of library which is constructed as building types, and then take mapping to the 3D building frame. For effectively apply, this technique, we classified buildings automatically using LiDAR data and made 3D frame using LiDAR and digital map. To express the realistic building texture, we made the texture library using real building photograph.

• ALGAE
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• 제21권2호
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• pp.175-183
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• 2006

Recent phylogenetic studies of scytosiphonacean brown algae show many conflicts with current classification. In order to clearly define the phylogenetic relationships of the family, we newly sequenced the photosystem I coding psaA gene (1488 base pairs) from 13 taxa (15 samples), of the family, and, for comparison, rbcL from four taxa. The psaA region has more informative sites (17.9%) than the rbcL (13.1%) and the number of nodes supported by over 50% bootstrap values is more in the psaA phylogeny (53 /57 nodes; 93%) than in the rbcL (47/63 nodes; 74.6%). The psaA phylogenies are basically congruent with the rbcL trees, recognizing two major groups in the monophyletic Scytosiphonaceae. The first group included Myelophycus, Petalonia, Scytosiphon, and elongate sack-shaped species of Colpomenia, primarily cold temperate elements with unilocular zoidangia on sporophytes. The second group, although not resolved, consisted of Hydroclathrus, Chnoospora, Rosenvingea, and ball-shaped Colpomenia, primarily warm-temperate taxa with both unilocular and plurilocular zoidangia on sporophytes. Chnoospora is not monophyletic, as was previously shown the paraphyly of Colpomenia, Petalonia, and Scytosiphon. Hydroclathrus clathratus from Korea and Japan was not monophyletic. Our studies show that gametophytic characters are the main source of conflict for the present taxonomy of the family. The psaA region is a useful tool for resolution of phylogenetic relationships within the Scytosiphonaceae.

• International Journal of Computer Science & Network Security
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• 제21권1호
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• pp.40-48
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• 2021

Content-Based Image Retrieval (CBIR) system plays a vital role to retrieve the relevant images as per the user perception from the huge database is a challenging task. Images are represented is to employ a combination of low-level features as per their visual content to form a feature vector. To reduce the search time of a large database while retrieving images, a novel image retrieval technique based on feature dimensionality reduction is being proposed with the exploit of metaheuristic optimization techniques based on Genetic Algorithm (GA), Extended Binary Cuckoo Search (EBCS) and Whale Optimization Algorithm (WOA). Each image in the database is indexed using a feature vector comprising of fuzzified based color histogram descriptor for color and Median binary pattern were derived in the color space from HSI for texture feature variants respectively. Finally, results are being compared in terms of Precision, Recall, F-measure, Accuracy, and error rate with benchmark classification algorithms (Linear discriminant analysis, CatBoost, Extra Trees, Random Forest, Naive Bayes, light gradient boosting, Extreme gradient boosting, k-NN, and Ridge) to validate the efficiency of the proposed approach. Finally, a ranking of the techniques using TOPSIS has been considered choosing the best feature selection technique based on different model parameters.

• International Journal of Computer Science & Network Security
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• 제23권9호
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• pp.120-128
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• 2023

In this work, we have presented ATSA, a hierarchical attention deep learning model for Arabic sentiment analysis. ATSA was proposed by addressing several challenges and limitations that arise when applying the classical models to perform opinion mining in Arabic. Arabic-specific challenges including the morphological complexity and language sparsity were addressed by modeling semantic composition at the Arabic morphological analysis after performing tokenization. ATSA proposed to perform phrase-chunks sentiment embedding to provide a broader set of features that cover syntactic, semantic, and sentiment information. We used phrase structure parser to generate syntactic parse trees that are used as a reference for ATSA. This allowed modeling semantic and sentiment composition following the natural order in which words and phrase-chunks are combined in a sentence. The proposed model was evaluated on three Arabic corpora that correspond to different genres (newswire, online comments, and tweets) and different writing styles (MSA and dialectal Arabic). Experiments showed that each of the proposed contributions in ATSA was able to achieve significant improvement. The combination of all contributions, which makes up for the complete ATSA model, was able to improve the classification accuracy by 3% and 2% on Tweets and Hotel reviews datasets, respectively, compared to the existing models.