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clustering,spatial information,remote sensing image,fuzzy clustering",{"VOID":513},"2",{"EN":515},"Spectral clustering is a clustering method based on algebraic graph theory. The clustering effect by using spectral method depends heavily on the description of similarity between instances of the datasets. Althought, spectral clustering has been significant interest in recent times, but the raw spectral clustering is often based on Euclidean distance, but it is impossible to accurately reflect the complexity of the data. Despite having a well-defined mathematical framework, good performance and simplicity, it suffers from several drawbacks, such as it is unable to determine a reasonable cluster number, sensitive to initial condition and not robust to outliers. In this paper, we present a new approach named spatial-spectral fuzzy clustering which combines spectral clustering and fuzzy clustering with spatial information into a unified framework to solve these problems, the paper consists of three main steps: Step 1, calculate the spatial information value of the pixels, step 2 applies the spectral clustering algorithm to change the data space from the color space to the new space and step 3 clusters the data in new data space by fuzzy clustering algorithm. Experimental results on the remote sensing image were evaluated based on a number of indicators, such as IQI, MSE, DI and CSI, show that it can improve the clustering accuracy and avoid falling into local optimum. ",{"EN":517},"Spatial-spectral fuzzy k-means clustering for remote sensing image 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56 No. 2","Tập 56 Số 2",{"VOID":505},{"total":246,"publishYear":635,"statisticByYear":25},2018,"2018-04-12","ERROR_IN_GET_PLATFORM_ID","2026-04-17T16:53:00.014+00:00",[73],{"id":641,"createTime":642,"updateTime":643,"relativeEntities":644,"slug":645,"properties":646,"entityType":218,"verifyStatus":23,"verifyTime":642,"verifyNote":520,"languages":25,"translateLanguages":25,"viewCount":158,"primaryUrl":659,"fullTextUrl":660,"authors":661,"publicationType":260,"publisherRelationship":677,"citationCount":738,"citationInfo":739,"publishDate":742,"publishYear":740,"citationAnalyzeStatus":637,"lastCitationAnalyze":25,"indexDatabases":743,"openAccess":25,"references":25,"isForceReanalyzing":318},"53215c01-5f04-447c-bddb-17ebc0661375","2023-06-13T15:42:17.488+00:00","2026-08-20T00:22:17.234+00:00",[],"Microplastic-contamination-in-commercial-sea-salt-of-Vietnam",{"abstract":647,"title":649,"gsPaper":651,"keywords":653,"references":655,"doi":657},{"EN":648},"This is the first study which assessed the microplastic pollution of sea salt products from Vietnam. The results obtained from 9 iodate fine table sea salt and 4 raw sea salt samples collected from different regions in Vietnam showed that microplastic were present in 100% of the salts samples. The mean concentration of microplastic was 787±101 items\u002Fkg and 340±26 items\u002Fkg for raw and fine sea salts, respectively.  For both raw and fine sea salt, fibers were the predominant type of microplastic, accounted more 60% of total microplastic particles. In added, three types of polymer were detected in 12 microplastic particles by FTIR, including polyethylene (PE), polypropylene (PP) and polystyrene, in which, the most common is PE (accounted 67%). With a mean daily salt consumption of 5-10g\u002Fday, the annual number of microplastic particles ingested per Vietnamese adult varies from 637 to 1241 particles from salt alone.",{"EN":650},"Microplastic contamination in commercial sea salt of Vietnam",{"VOID":652},"5909994989158974315",{"EN":654},"Microplastic,contamination,sea salt,Vietnam",{"VOID":656},". UNEP Annual Report (2018), Development of national action plan on marine plastic debris management, International Consulting Workshop, December 2018, 20p.\nStrady E., Dang TH., Dao TD., Dinh HN., Do TTD., Duong TN., Duong TT., Hoang DA., Kieu-Le TC., Le TPQ., Mai H., Dang MT., Nguyen QH., Tran-Nguyen QA., Tran QV., Truong TQS., Chu VH., Vo VC. (2020) Baseline assessment of microplastic concentrations in marine and freshwater environments of a developing Southeast Asian country, Viet Nam, Marine Pollution Bulletin, Article in press, DOI: 10.1016\u002Fj.marpolbul.2020.111870.\nRenzi M., Blaskovic A., 2018, Litter and microplastics features in table salts from marine origin: Italian versus Croatian brands. Marine pollution bulletin, 135, 62-68. DOI:10.1016\u002Fj.marpolbul.2018.06.065.\nKim J.S., Lee H.J., Kim SK., Kim HJ., 2018, Global pattern of microplastics (MPs) in commercial food-grade salts: sea salt as an indicator of seawater MP pollution, Environmental science and technology, 52, 12819-12828, DOI:10.1021\u002Fasc.est.8b04180.\nIniguez ME., Conesa JA., Fullane A., 2017, Microplastic in Spanish table salt. Science reports, 7, 1-7, DOI:10.1038\u002Fs41598-017-09128-x.\nPeixoto D., Pinheiro C., Amorim J., Oliva-Teles L., Guilhermino L., and Vieira MN., 2019, Microplastic pollution in commercial salt for human consumption: a review, Estuarine, Coastal and Shelf science, 219, 161-168, DOI:10.1016\u002Fj.ecss.2019.02.018.\nYang D., Shi H., Li L., Li J., Jabeen K., Kolandhasamy P., 2015, Microplastic pollution in table salts from China, Environ. Sci. Technol., 49, 13622-13627, DOI:10.1021\u002Fasc.est.5b03163.\nKarami A., Golieskardi A., Keong CC., Larat V., Galloway TS., and Salamatinia B., 2017, The presence of microplastic in commercial salts from different countries, Sci.Rep., 7, DOI:10.1038\u002Fsrep46173.\nLee H., Kunz A., Shim WJ., and Walther BA., 2019, Microplastic contamination of table salts from Taiwan, including a global review, Scientific reports, 9:10145, DOI:10.1038\u002Fs41598-019-46417-z.\nQiu Q., Tan Z., Wang J., Peng J., Li M. and Zhan Z., 2016, Extraction, enumeration and identification methods for monitoring microplastics in the environment, Estuar. Coast. Shelf Sci., 176, 102-109, DOI:10.1016\u002Fj.ecss.2016.04.012.\nCole M., 2016, A novel method for preparing microplastic fibers, Sci. Rep. 6, 1–7, DOI:10.1038\u002Fsrep34519.\nSoares A.S., Pinheiro C., Oliveira U. and Vieira M.N., 2020, Microplastic pollution in Portuguese saltworks, DOI:10.5772\u002Fintechopen.91476.\nSeth CK. And Shriwastav A., 2018, Contamination of India sea salts with microplastics and a potential prevention strategy. Environ. Sci. Pollut. Res. DOI:10.1007\u002Fs11356-018-3028-5.\nBarboza L.G. and Gimenez BCG., 2015, Microplastic in the marine environment: current trends and future perspectives, Mar. Pollut. Bull., 97, 5-12.\nMa Y., Huang A., Cao S., Wang L., Guo H., and Ji R., 2016, Effects of nanoplastics and microplastics on toxicity, bioaccumulation, and environmental fate of phenanthreen in fresh water, Environ. Pollut., 219, 166-173, DOI:10.1016\u002Fj.envpol.2016.10.061.\nLusher AL., Welden NA., Sobral P., Cole, M., 2017a, Sampling, isolating and identifying microplastics ingested by fish and invertebrates. Anal. Meth.9, 1346–1360. https:\u002F\u002F doi.org\u002F10.1039\u002Fc6ay02415g.\nLusher AL., Hollman PCH., Mendoza-Hill JJ., 2017b, Microplastics in Fisheries and Aquaculture - Status of Knowledge on Their Occurrence and Implications for Aquatic Organisms and Food Safety. FAO, Fisheries and Aquaculture Techincal paper978-92- 5-109882-0.\nSmith M, Love DC., Rochman CM., Neff RA., 2018, Microplastics in seafood and the implications for human health. Curr. Environ. Heal. Rep. 5, 375–386, DOI:10.1007\u002Fs40572-018-0206-z.\nGundogdu S., 2018, Contamination of table salts from Turkey with microplastics, Food Addit.Contam., part A 35(5), 1006-1014, DOI:10.1080\u002F19440049.2018.\nBouwmeester H., Hollman PCH., Peters RJB., 2015, Potential health impact of environmental released micro- and nanoplastics in the human food production chain: experiences from nanotoxicology, Environ.Sci.Technol., 49, 8932-8947, DOI:10.1021\u002Fasc.est.5b01090.\nWaring RH., Harris RM., and Mitchell SC., 2018, Plastic contamination of the food chain: a threat to human health? Maturitas 115, 64-68, DOI:101016\u002Fj.maturitas.2018.06.010.\nLi J., Yang D., Li, L., Jabeen K., Shi H., 2015. Microplastics in commercial bivalves from China. Environ. Pollut. 207, 190–195. DOI:10.1016\u002Fj.envpol.2015.09. 018.\nLima ARA., Barletta M., Costa MF., 2015, Seasonal distribution and interactions between plankton and microplastics in a tropical estuary, Estuar. Coast Shelf Sci. 165, 213–225, DOI:10.1016\u002Fj.ecss.2015.05.018.\nEo S. et al., 2018, Abundance, composition, and distribution of microplastics larger than 20µm in sand beaches of South Korea, Environ. Pollut., 238, 894-902.\nWright S.L., Thompson R.C., Galloway, T.S., 2013b. The physical impacts of microplastics on marine organisms: a review. Environ. Pollut. 178, 483–492. DOI:10.1016\u002Fj.envpol.2013.02.031.\nSetälä O., Fleming-Lehtinen V., Lehtiniemi, M., 2014. Ingestion and transfer of microplastics in the planktonic food web. Environ. Pollut. 185, 77–83. DOI:10. 1016\u002Fj.envpol.2013.10.013.\nLebreton L.C.M., Van Der Zwet J., Damsteeg J.W., Slat, B., Andrady, A., Reisser, J., 2017. River plastic emissions to the world's oceans. Nat. Commun. 8, 1–10. 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Hiện nay, trên thế giới có trên 700 công ty giống cây trồng áp dụng công nghệ nuôi cấy mô, cơ quan và  tế bào  thực vật để sản xuất hàng  trăm  triệu giống cây  trồng  sạch bệnh mỗi năm  (cây dược  liệu, cây ăn quả, cây  lương  thực, cây hoa, cây cảnh, cây rừng) và đã mang lại hiệu quả kinh tế cao so với việc sử dụng các phương pháp truyền thống khác, góp phần bảo vệ an ninh  lương  thực và chống biến đổi khí hậu  toàn cầu. Ở Việt Nam, hiện tại có trên 100 phòng thí nghiệm sử dụng kĩ thuật này và đã sản xuất gần 30 triệu cây giống vô tính; riêng Đà Lạt, thành phố đi đầu trong cả nước đã sản xuất hơn 26 triệu giống và là nơi có phòng thí nghiệm tư nhân có quy mô thuộc loại hàng đầu thế giới. 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paper presents the analysis of the effect of urban green space types on land surface temperature in Hue city. Data are collected with temperature monitoring results from each green space type and the interpretation of surface temperature based on Landsat 8 satellite image data to determine temperatures at different times of the year. Results showed that there was a significant correlation between types of urban green space and the surface temperature. Types of green space with a large area and vegetation indexes have a greater effect on temperature than areas with a smaller green space do. Green space types including forest green space, dedicated green space and agriculture green space have the most effect on the surface temperature. The forest area has the greatest influence on the temperature with a temperature difference of more than 1.6 degrees Celsius at 9: 00 in the daytime. Besides, the results …",{"VI":1170},"The effect of green space on the land surface temperature in Hue city",{"VOID":1172},"2227410414831975342",{"VOID":1174},"4C","https:\u002F\u002Fscholar.google.com\u002Fscholar?cluster=2227410414831975342&hl=en&oi=scholarr",[1177],{"id":1178,"sortIndex":102,"researcher":25,"roles":1179,"affiliations":1180,"properties":1181,"displayName":1183,"givenName":25,"familyName":25},"eff9b490-e6fd-4858-b1e9-74e40fea90a1",[224],[],{"title":1182},{"VI":1183},"NB Giang",{"url":25,"publisher":1185,"properties":25},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1186,"slug":10,"properties":1187,"entityType":22,"verifyStatus":23,"verifyTime":24,"verifyNote":25,"languages":25,"translateLanguages":25,"viewCount":26,"subjectFields":1193,"manageAffiliations":1200,"indexDatabases":1214,"url":100,"thumbnailPath":25,"statistic":1229,"gsStatistic":1234,"type":204,"analyzePriority":25},[],{"country":1188,"eissn":1189,"issn":1190,"title":1191,"gsId":1192},{"VOID":13},{"VOID":15},{"VOID":17},{"EN":19},{"VOID":21},[1194,1197],{"id":29,"createTime":25,"updateTime":25,"relativeEntities":1195,"label":1196,"description":25,"parentId":25,"standard":25,"scholarHubFieldId":25},[],{"EN":32},{"id":34,"createTime":25,"updateTime":25,"relativeEntities":1198,"label":1199,"description":25,"parentId":25,"standard":25,"scholarHubFieldId":25},[],{"EN":37},[1201,1208],{"id":40,"createTime":25,"updateTime":25,"relativeEntities":1202,"slug":25,"properties":1203,"entityType":25,"verifyStatus":25,"verifyTime":25,"verifyNote":25,"languages":25,"translateLanguages":25,"viewCount":25,"url":49,"parentIds":1207,"statistic":25},[],{"title":1204,"country":1205,"abbreviation":1206},{"EN":44,"VI":45},{"VOID":13},{"VOID":48},[],{"id":52,"createTime":25,"updateTime":25,"relativeEntities":1209,"slug":25,"properties":1210,"entityType":25,"verifyStatus":25,"verifyTime":25,"verifyNote":25,"languages":25,"translateLanguages":25,"viewCount":25,"url":59,"parentIds":1213,"statistic":25},[],{"title":1211,"country":1212},{"EN":56,"VI":57},{"VOID":13},[40],[1215,1222],{"id":63,"indexDatabase":1216,"url":74,"indexYears":75,"academicFieldIds":1221,"indexDatabaseRanking":25},{"id":65,"createTime":25,"updateTime":25,"relativeEntities":1217,"label":1218,"description":1219,"key":71,"publicationTags":1220,"standard":25},[],{"EN":68,"VI":68},{"EN":70,"VI":70},[73],[77,78,79,80,81],{"id":83,"indexDatabase":1223,"url":94,"indexYears":95,"academicFieldIds":1228,"indexDatabaseRanking":99},{"id":85,"createTime":25,"updateTime":25,"relativeEntities":1224,"label":1225,"description":1226,"key":91,"publicationTags":1227,"standard":25},[],{"EN":88,"VI":88},{"EN":88,"VI":90},[93],[97,98],{"impactFactor":102,"impactFactorByYear":1230,"i10Index":113,"i10IndexLast5Year":114,"totalPublication":115,"totalPublicationByYear":1231,"totalCitation":128,"totalCitationByYear":1232,"totalCitationPerPublication":140,"totalCitationPerPublicationByYear":1233,"hindexLast5Year":153,"hindex":153},{"2013":104,"2014":104,"2015":104,"2016":105,"2017":106,"2018":107,"2019":108,"2020":109,"2021":110,"2022":109,"2023":111,"2024":112},{"2012":117,"2014":118,"2015":118,"2016":119,"2017":120,"2018":121,"2019":122,"2020":123,"2021":124,"2022":125,"2023":126,"2024":127},{"2012":126,"2014":130,"2015":131,"2016":132,"2017":133,"2018":134,"2019":135,"2020":136,"2021":137,"2022":138,"2023":139},{"2012":142,"2014":143,"2015":144,"2016":145,"2017":146,"2018":147,"2019":148,"2020":149,"2021":150,"2022":151,"2023":152},{"impactFactor":25,"impactFactorByYear":25,"i10Index":155,"i10IndexLast5Year":119,"totalPublication":156,"totalPublicationByYear":1235,"totalCitation":175,"totalCitationByYear":1236,"totalCitationPerPublication":189,"totalCitationPerPublicationByYear":1237,"hindexLast5Year":202,"hindex":203},{"0":127,"1994":158,"1995":158,"1996":158,"2003":158,"2004":158,"2005":159,"2008":158,"2009":158,"2010":160,"2011":161,"2012":162,"2013":118,"2014":163,"2015":123,"2016":164,"2017":165,"2018":166,"2019":167,"2020":168,"2021":169,"2022":170,"2023":171,"2024":172,"2025":173,"2026":174},{"2014":177,"2015":178,"2016":138,"2017":179,"2018":180,"2019":181,"2020":182,"2021":183,"2022":184,"2023":185,"2024":186,"2025":187,"2026":188},{"2014":107,"2015":108,"2016":191,"2017":192,"2018":193,"2019":194,"2020":195,"2021":196,"2022":197,"2023":198,"2024":199,"2025":200,"2026":201},{"total":158,"publishYear":393,"statisticByYear":25},"2026-06-19T16:20:10.584+00:00",[73]]