ScholarWorks@Gyeongsang National University: Shin, Seung Gu

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Shin, Seung Gu (신승구)

공과대학 (에너지공학과)

Research Area: 바이오가스, 유기성 자원순환, 물-에너지 융합, Biogas, Organic Resources Recycling, Water-Energy Nexus

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Anaerobic digestion:10||anaerobic digestion:8||Microbial community:5||realtime PCR:4||Antibiotic resistance genes (ARGs):4||Nextgeneration sequencing:4||Machine learning:3||sewage sludge:3||Codigestion:3||methane production:3||Network analysis:3||Ammonia:3||Methanogen:2||Anaerobic ceramic membrane bioreactor:2||Coenzyme M:2||Methylene blue:2||Thermophilic anaerobic digestion:2||메탄 수율:2||Halloysite:2||Microbial communities:2||microbial community:2||microbial electrolysis cell:2||food waste leachate:2||UASBr:2||Highthroughput sequencing:2||Food waste:2||Microbial electrolysis cell:2||Food waste recycling wastewater:2||organic loading rate:2||Domestic wastewater:2||SMA test:2||LabVIEW:2||Fullscale:2||Sewage sludge:2||Bioaugmentation:2||primary sewage sludge:2||Magnetite particles:2||혐기소화:2||Biomethanation:2||흡착:2||BSM1:2||Adsorption:2||Sodium:2||할로이사이트:2||ANOVA:2||Hydrogen:2||Methane production:2||Biogas:2||Dewatered anaerobic sludge treatment:1||Digester type:1||Doping:1||Electrobiofuel:1||Electrochemically active bacteria:1||Elemental Analysis:1||Energy efficiency:1||Energy potential:1||Enterococcus spp.:1||Environmental factor:1||Ethanol:1||External carbon source:1||Feed composition:1||Filamentous fungi:1||Food wastewater (FWW):1||Fullscale anaerobic digestion:1||Fullscale anaerobic digestion plant:1||Granular sludge:1||H<sub>2</sub>S:1||Halloysite nanotubes:1||Heavy metal ions:1||Hybrid machine learning:1||Hybrid materials:1||Hydrogen producing granules:1||Hydrogenotrophic methanogenesis:1||Hydrogenotrophic methanogens:1||Image analysis:1||Inoculation:1||Internal circulation (IC) bioreactor:1||Interpretable models:1||Lactic acid:1||Lactobacillus:1||Lignocellulose:1||Lipid:1||Lowstrength ultrasonication:1||Machine Learning:1||Magnesium silicate:1||Magnetite:1||Manometer:1||Mass reduction:1||Metagenomics:1||Methane Yield:1||Methanoculleus:1||Methanogenesis:1||Methanogenesis control:1||Microbial community structure:1||Microbial dynamics:1||Microbial electrolysis cells:1||Mixed fermentation:1||Multicollinearity:1||Multiple linear regression (MLR):1||Multivariate analysis:1||Next generation sequencing:1||Nextgeneration Sequencing:1||Organic Content:1||Organic composition:1||Organic loading rate:1||Organic solid waste:1||P fractionation:1||P mass balance:1||Parachlorella:1||Phenol:1||Phosphorus (P) dissolution:1||Polymerized anode material:1||Pork:1||Powertogas:1||Prediction model:1||Process parameter:1||Process recovery:1||Propionate:1||Protein:1||Psychrophilic:1||Pyrosequencing:1||Quantitative PCR (qPCR):1||Regression:1||Roundness:1||Rumen culture:1||Saccharomyces cerevisiae:1||Seasonal variation:1||Shapley additive explanations:1||Silicon carbide membrane:1||Simulation:1||Slaughterhouse byproduct:1||Sludge:1||Solidstate digestion:1||Solubilization rate:1||Startup:1||Strategy modeling:1||Stratification:1||Sulfide inhibition:1||Supervised learning:1||Symbiosis:1||Syntrophic propionate oxidizing bacteria:1||Syntrophomonadaceae:1||TA ratio:1||TS content:1||Tannery wastewater:1||Temperature:1||Temporal Resolution:1||Thermal stability:1||Tubular media:1||16S rRNA gene:1||Upflow anaerobic sludge blanket:1||Upgrading:1||VFA:1||Volatile fatty acids:1||Volatile solids removal:1||Wastewater treatment plants (WWTPs):1||Water industry:1||Water treatment:1||Wheat straw:1||ammonia loss:1||anaerobic digestion effluent:1||animal manure:1||applied voltage:1||bioaugmentation:1||bioelectrochemical technology:1||central composite design:1||coagulation:1||coalrelated humic substances:1||coastal water quality:1||combined alkalineultrasound pretreatment:1||combined sewage overflow:1||energy balance:1||energy recovery:1||food waste:1||highthroughput sequencing:1||hydraulic retention time:1||hydrolysis:1||hydroponic cultivation:1||inhibition:1||iron powder:1||metagenomeassembled genome:1||methane gas:1||methane yield:1||microbial volatile organic compounds:1||mixedculture microalgae cultivation:1||net growth rate:1||novel species:1||open circuit voltage:1||optimization:1||pH:1||pH control:1||phosphate:1||plant abiotic stress:1||plant growth promoting microbe:1||plug flow:1||propionate:1||rDNA sequencing:1||rRNA sequencing:1||rainfall event:1||reaction temperature:1||recovery:1||response surface analysis:1||response surface methodology:1||sequencing batch reactor:1||struvite:1||swine wastewater:1||syntrophism:1||volatile fatty acid:1||가축분뇨:1||계층화:1||관형 담체:1||규산마그네슘:1||그래뉼 슬러지:1||기계학습:1||데이터 재표본화:1||도축부산물:1||머신러닝:1||메타지노믹스:1||메탄 생산량:1||메탄가스:1||메탄생산:1||메틸렌 블루:1||메틸렌블루:1||물 산업:1||미생물전기분해전지:1||바이오매스 맵핑:1||반응 온도:1||병합 소화:1||병합소화:1||생물전기화학:1||소성:1||에너지 수지:1||에너지 잠재량:1||에너지회수율:1||예측 모델:1||원소 분석:1||유기물 함량:1||인가전압:1||인공신경망:1||인공지능:1||중금속:1||차세대염기서열분석:1||하수슬러지:1||하이브리드 머신러닝:1||혐기성 소화:1||혐기성소화:1||Twostage process:1||2bromoethanesulfonate:1||454 pyrosequencing:1||A pilotscale onsite system:1||Acclimatized granular sludge:1||Accumulation:1||Acetate:1||Acetic acid:1||Acidogen:1||Amplicon sequencing:1||Anaerobic Digestion:1||Anaerobic digestion (AD):1||Analysis of variance:1||Antibiotic resistance genes:1||Antibioticresistance genes:1||Apparent density:1||Artificial intelligence:1||Artificial neural network:1||BMP 테스트:1||Bacteria:1||Bacterial community:1||Benzoate:1||Biochemical Methane Potential Test:1||Biochemical methane potential:1||Biocompatibility:1||Bioelectrochemical system:1||Biofuel:1||Biological nitrogen removal:1||Biological nutrient removal (BNR) process:1||Biomass mapping:1||Biomethane:1||Byproduct:1||C/N ratio:1||Cheese whey:1||Coinhibition:1||Coastal aquaculture:1||Codigestion:1||Correlation:1||Cumulative importance features:1||DNA Extraction:1||DNA 추출:1||Dairy wastewater:1||Data Resampling:1||Deeplearning algorithms:1||Defluiviitoga:1||Degassing effect:1||Denitrification:1||Dewatered anaerobic sludge:1||

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