cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3884398
title: GECCO Industrial Challenge 2018 Dataset: A water quality dataset for the 'Internet of Things: Online Anomaly Detection for Drinking Water Quality' competition at the Genetic and Evolutionary Computation Conference 2018, Kyoto, Japan.

description: Dataset of the 'Internet of Things: Online Anomaly Detection for Drinking Water Quality' competition hosted at The Genetic and Evolutionary Computation Conference (GECCO) July 15th-19th 2018, Kyoto, Japan The task of the competition was to develop an anomaly detection algorithm for a water- and environmental data set. Included in zenodo: - dataset of water quality data - additional material and descriptions provided for the competition The competition was organized by: F. Rehbach, M. Rebolledo, S. Moritz, S. Chandrasekaran, T. Bartz-Beielstein (TH Köln) The dataset was provided by: Thüringer Fernwasserversorgung and IMProvT research project GECCO Industrial Challenge: 'Internet of Things: Online Anomaly Detection for Drinking Water Quality' Description: For the 7th time in GECCO history, the SPOTSeven Lab is hosting an industrial challenge in cooperation with various industry partners. This years challenge, based on the 2017 challenge, is held in cooperation with "Thüringer Fernwasserversorgung" which provides their real-world data set. The task of this years competition is to develop an anomaly detection algorithm for the water- and environmental data set. Early identification of anomalies in water quality data is a challenging task. It is important to identify true undesirable variations in the water quality. At the same time, false alarm rates have to be very low.<br> Additionally to the competition, for the first time in GECCO history we are now able to provide the opportunity for all participants to submit 2-page algorithm descriptions for the GECCO Companion. Thus, it is now possible to create publications in a similar procedure to the Late Breaking Abstracts (LBAs) directly through competition participation! Accepted Competition Entry Abstracts<br> - Online Anomaly Detection for Drinking Water Quality Using a Multi-objective Machine Learning Approach (Victor Henrique Alves Ribeiro and Gilberto Reynoso Meza from the Pontifical Catholic University of Parana)<br> - Anomaly Detection for Drinking Water Quality via Deep BiLSTM Ensemble (Xingguo Chen, Fan Feng, Jikai Wu, and Wenyu Liu from the Nanjing University of Posts and Telecommunications and Nanjing University)<br> - Automatic vs. Manual Feature Engineering for Anomaly Detection of Drinking-Water Quality (Valerie Aenne Nicola Fehst from idatase GmbH) Official webpage: http://www.spotseven.de/gecco/gecco-challenge/gecco-challenge-2018/
DOI: 10.7910/dvn/9argzn/8t4qcd
title: Model_ic_42_M&A (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/au2seh
title: Model_ic_20_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/hblfxm
title: Model_oc_3_V3 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/pcey4b
title: Model_oc_60_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/rw6qyy
title: Model_oc_51_V2 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/tbaqiv
title: Model_oc_62_V3 (v0=1e14).tab

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DOI: 10.7910/dvn/9argzn/uced1q
title: Model_oc_72_V3 (v0=1e14).tab

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DOI: 10.7910/dvn/9argzn/bd7l9c
title: Model_oc_76_M&A (v0=1e13).tab

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DOI: 10.7910/dvn/9argzn/d5nwqy
title: Model_oc_33_V1 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/dpcrs2
title: Model_ic_62_V1 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/eykckm
title: Model_oc_57_V3 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/kmn3q3
title: Model_oc_84_M&A (v0=1e12).tab

description: :unav
DOI: 10.7910/dvn/9argzn/mgxglr
title: Model_ic_38_V2 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/odnif7
title: Model_ic_43_V3 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/p1no9i
title: Model_ic_33_V2 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/apjcyj
title: Model_oc_7_M&A (v0=1e12).tab

description: :unav
DOI: 10.7910/dvn/9argzn/hi0bli
title: Model_oc_32_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/jciuyd
title: Model_ic_41_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/l3slmw
title: Model_ic_38_M&A (v0=1e12).tab

description: :unav
DOI: 10.7910/dvn/9argzn/ljknd7
title: Model_ic_52_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/qvnx85
title: Model_ic_13_M&A (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/rhwu9x
title: Model_oc_54_M&A (v0=1e12).tab

description: :unav
DOI: 10.7910/dvn/9argzn/rqlmoa
title: Model_ic_24_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/sqttop
title: Model_ic_17_V1 (v0=1e14).tab

description: :unav
DOI: 10.5519/qd.en89kzcj
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.7910/dvn/9argzn/0iybo4
title: Model_oc_62_V1 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/dx0tzg
title: Model_oc_42_V3 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/ncg7pu
title: Model_ic_46_M&A (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/ohno5y
title: Model_ic_27_V1 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/pfptmz
title: Model_oc_61_M&A (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/r7cwmu
title: Model_ic_21_V2 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/savy0v
title: Model_oc_95_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/w4prqi
title: Model_oc_98_V1 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/ceut5c
title: Model_oc_52_M&A (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/fxkhkz
title: Model_oc_50_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/mmnxfy
title: Model_oc_46_V3 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/puowgb
title: Model_oc_51_V3 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/tyakdr
title: Model_oc_58_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/zmdxg7
title: Model_ic_54_M&A (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/4ggp1s
title: Model_oc_81_V3 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/hmocie
title: Model_ic_44_M&A (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/knvtba
title: Model_oc_66_V3 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/olvbey
title: Model_oc_91_V3 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/opqdrx
title: Model_ic_59_M&A (v0=1e12).tab

description: :unav
DOI: 10.7910/dvn/9argzn/w6v0uw
title: Model_oc_13_V1 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/wksxpj
title: Model_oc_8_V1 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/4golks
title: Model_oc_9_M&A (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/b3avah
title: Model_oc_47_V1 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/c7fwba
title: Model_oc_97_V2 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/ebuyni
title: Model_ic_49_M&A (v0=1e12).tab

description: :unav
DOI: 10.7910/dvn/9argzn/gdebht
title: Model_ic_35_M&A (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/ghmugo
title: Model_oc_35_V3 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/gjhcxu
title: Model_oc_83_M&A (v0=1e12).tab

description: :unav
DOI: 10.7910/dvn/9argzn/zbm13n
title: Model_ic_41_V2 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/znpqjl
title: Model_oc_58_M&A (v0=1e14).tab

description: :unav
DOI: 10.21227/kchn-yw77
title: Brazilian Flights Dataset

description: An integrated dataset containing data on departure and arrival data for Brazilian domestic flights comprising the period from the years 2000 to 2018.Composed of 13,823,630 records of flight data, each containing 50 attributes. The attributes include data regarding the airline, flight, airports, meteorological conditions, and scheduled and real times of departure and arrival.
DOI: 10.5281/zenodo.3884444
title: GECCO Industrial Challenge 2019 Dataset: A water quality dataset for the 'Internet of Things: Online Event Detection for Drinking Water Quality Control' competition at the Genetic and Evolutionary Computation Conference 2019, Prague, Czech Republic.

description: Dataset of the 'Internet of Things: Online Event Detection for Drinking Water Quality Control' competition hosted at The Genetic and Evolutionary Computation Conference (GECCO) July 13th-17th 2019, Prague, Czech Republic The task of the competition was to develop an anomaly detection algorithm for a water- and environmental data set. Included in zenodo: - dataset of water quality data - additional material and descriptions provided for the competition The competition was organized by: F. Rehbach, S. Moritz, T. Bartz-Beielstein (TH Köln) The dataset was provided by: Thüringer Fernwasserversorgung and IMProvT research project Internet of Things: Online Event Detection for Drinking Water Quality Control Description: For the 8th time in GECCO history, the SPOTSeven Lab is hosting an industrial challenge in cooperation with various industry partners. This years challenge, based on the 2018 challenge, is held in cooperation with "Thüringer Fernwasserversorgung" which provides their real-world data set. The task of this years competition is to develop an anomaly detection algorithm for the water- and environmental data set. Early identification of anomalies in water quality data is a challenging task. It is important to identify true undesirable variations in the water quality. At the same time, false alarm rates have to be very low. <br> Competition Opens: End of January/Start of February 2019<br> Final Submission: 30 June 2019 Official webpage: https://www.th-koeln.de/informatik-und-ingenieurwissenschaften/gecco-challenge-2019_63244.php
DOI: 10.7910/dvn/5fisnq/0dvdue
title: RPDN BR Diplomatic presence City-level release v2 070620.tab

description: Brazil's diplomatic presence, city-level (1995-2019)
DOI: 10.7910/dvn/5fisnq/lbaq2m
title: RPDN TR Presidential diplomacy release v2 070620.xlsx

description: Turkey's presidential diplomacy (1995-2018)
DOI: 10.7910/dvn/5fisnq/qpemcn
title: RPDN BR Presidential diplomacy release v2 070620.xlsx

description: Brazil's presidential diplomacy (1995-2018)
DOI: 10.7910/dvn/5fisnq/t92yty
title: RPDN SA Diplomatic presence City-level release v2 070620.tab

description: South Africa's diplomatic presence, city-level (2001-2019)
DOI: 10.7910/dvn/5fisnq/wnrwcj
title: RPDN SA Diplomatic presence Country-level release v2 070620.tab

description: South Africa's diplomatic presence, country-level (2001-2019)
DOI: 10.7910/dvn/5fisnq/yecgce
title: RPDN SA Presidential diplomacy release v2 070620.tab

description: South Africa's presidential diplomacy (1994-2019)
DOI: 10.7910/dvn/5fisnq/zn4eo5
title: RPDN BR Diplomatic presence Country-level release v2 070620.xlsx

description: Brazil's diplomatic presence, country-level (1995-2019)
DOI: 10.7910/dvn/9argzn/8b5yor
title: Model_oc_80_M&A (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/bwwrhd
title: Model_oc_77_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/ldvrlf
title: Model_ic_19_M&A (v0=1e12).tab

description: :unav
DOI: 10.7910/dvn/9argzn/lmtcps
title: Model_oc_83_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/ql9eyh
title: Model_oc_85_V2 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/udc1et
title: Model_oc_35_V1 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/x4znuy
title: Model_oc_67_V3 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/ynh0a5
title: Model_oc_10_V1 (v0=1e14).tab

description: :unav
DOI: 10.5281/zenodo.3883611
title: DataPipelineExecutionValidation-release-data

description: This dataset release supports the results of the data pipeline validation in the RADON H2020 Project The data pipeline is deployed on multiple Openstack instances that would read, preprocess, and store the image files. TOSCA Data pipeline to generate thumbnail of images in S3 bucket using Amazon lambda function. Push thumbnail to S3 bucket. RADON github repository: https://github.com/radon-h2020/demo-lambda-thumbgen-tosca-datapipeline More details at http://radon-h2020.eu/wp-content/uploads/2020/01/D5.5-Data-Pipeline-Orchestration-I.pdf
DOI: 10.5281/zenodo.3883612
title: DataPipelineExecutionValidation-release-data

description: This dataset release supports the results of the data pipeline validation in the RADON H2020 Project The data pipeline is deployed on multiple Openstack instances that would read, preprocess, and store the image files. TOSCA Data pipeline to generate thumbnail of images in S3 bucket using Amazon lambda function. Push thumbnail to S3 bucket. RADON github repository: https://github.com/radon-h2020/demo-lambda-thumbgen-tosca-datapipeline More details at http://radon-h2020.eu/wp-content/uploads/2020/01/D5.5-Data-Pipeline-Orchestration-I.pdf
DOI: 10.5281/zenodo.3884114
title: Census demographic data for the InMAP Source-Receptor Matrix (ISRM) dataset

description: The InMAP Source-Receptor Matrix (ISRM) estimates the air quality impacts of emissions released from any source location in the contiguous United States to any receptor location. Specifically, the values in the ISRM dataset are the change in PM<sub>2.5</sub> concentration (µg m<sup>-3</sup>) in any receptor grid cell per unit of emissions (µg sec<sup>-1</sup>) in any source grid cell. ISRM was created from repeated runs of the Intervention Model for Air Pollution (InMAP), isolating the impact of emissions from every grid cell in InMAP and from three emission heights representing ground-level, low-stack, and high-stack emissions. A file of the marginal impacts of emissions from each source location is also included ("marginal_values.csv"), which summarizes the estimates in ISRM by each source grid cell in terms of monetary damages ($ tonne<sup>-1</sup>), increased mortality (deaths tonne<sup>-1</sup>), and population exposure (population*µg m<sup>-3</sup> tonne<sup>-1</sup>). These files join US Census demographic information to the ISRM to facilitate future analyses. The original ISRM file can be found here: https://zenodo.org/record/3590127#.Xt0Z4GhKhPb
DOI: 10.5281/zenodo.3884115
title: Census demographic data for the InMAP Source-Receptor Matrix (ISRM) dataset

description: The InMAP Source-Receptor Matrix (ISRM) estimates the air quality impacts of emissions released from any source location in the contiguous United States to any receptor location. Specifically, the values in the ISRM dataset are the change in PM<sub>2.5</sub> concentration (µg m<sup>-3</sup>) in any receptor grid cell per unit of emissions (µg sec<sup>-1</sup>) in any source grid cell. ISRM was created from repeated runs of the Intervention Model for Air Pollution (InMAP), isolating the impact of emissions from every grid cell in InMAP and from three emission heights representing ground-level, low-stack, and high-stack emissions. A file of the marginal impacts of emissions from each source location is also included ("marginal_values.csv"), which summarizes the estimates in ISRM by each source grid cell in terms of monetary damages ($ tonne<sup>-1</sup>), increased mortality (deaths tonne<sup>-1</sup>), and population exposure (population*µg m<sup>-3</sup> tonne<sup>-1</sup>). These files join US Census demographic information to the ISRM to facilitate future analyses. The original ISRM file can be found here: https://zenodo.org/record/3590127#.Xt0Z4GhKhPb
DOI: 10.7910/dvn/9argzn/46fqu7
title: Model_oc_101_V2 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/6pzeeh
title: Model_oc_300_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/anob0c
title: Model_oc_70_V1 (v0=1e14).tab

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DOI: 10.7910/dvn/9argzn/jkb2nn
title: Model_ic_12_V2 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/na5oo7
title: Model_ic_14_M&A (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/q4czxq
title: Model_oc_221_V2 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/rporto
title: Model_oc_16_M&A (v0=1e12).tab

description: :unav
DOI: 10.7910/dvn/9argzn/svqsyv
title: Model_oc_6_V3 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/t4y7kr
title: Model_oc_22_V1 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/vlegkx
title: Model_oc_24_V1 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/wnjxmn
title: Model_ic_24_M&A (v0=1e12).tab

description: :unav
DOI: 10.7910/dvn/9argzn/wxxh9y
title: Model_oc_148_V2 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/xnilag
title: Model_oc_213_M&A (v0=1e12).tab

description: :unav
DOI: 10.14457/cu.res.2000.13
title: การประเมินประสิทธิภาพการผลิตและพันธุกรรมโคนมของสหกรณ์โคนมวังน้ำเย็น จังหวัดสระแก้ว
DOI: 10.14457/cu.res.2012.133
title: โครงการบทบาทของเงินลงทุนทางตรงระหว่างประเทศจากญี่ปุ่นที่มีต่อการพัฒนาทางเศรษฐกิจในกลุ่มประเทศอนุภูมิภาคลุ่มแม่น้ำโขงและผลกระทบต่อไทย
DOI: 10.14457/cu.res.2016.63
title: การใช้ฟังก์ชันนัลโคพอลิเมอร์บรัชสำหรับประยุกต์ทางการตรวจวัดทางชีวภาพและชีวการแพทย์
DOI: 10.14457/cu.res.2018.26
title: การตรวจวัด โลหะหนักหลายชนิดด้วยพอร์ไฟรินที่ถกู ตรึงบน เซ็นเซอร์จากกระดาษ
DOI: 10.17632/2ss6rkrz34.1
title: Data for: Application of packed bed reactor theory and Bayesian inference to upweller culture of juvenile oysters.

description: Executable python code for Bayesian model.
DOI: 10.7910/dvn/9argzn/01quff
title: Model_oc_193_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/0fulwv
title: Model_oc_133_V3 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/3wrpn7
title: Model_oc_246_M&A (v0=1e12).tab

description: :unav
DOI: 10.7910/dvn/9argzn/hglpur
title: Model_ic_23_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/ifaufp
title: Model_oc_270_V1 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/kolwfh
title: Model_oc_155_V2 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/kvqxqi
title: Model_oc_174_M&A (v0=1e12).tab

description: :unav
DOI: 10.7910/dvn/9argzn/kwb0go
title: Model_oc_190_M&A (v0=1e12).tab

description: :unav
DOI: 10.7910/dvn/9argzn/mxbnfc
title: Model_oc_44_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/pthxja
title: Model_oc_201_M&A (v0=1e12).tab

description: :unav
DOI: 10.7910/dvn/9argzn/q342iu
title: Model_ic_7_V1 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/qiublx
title: Model_ic_54_V1 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/swbb9m
title: Model_oc_174_V3 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/tc8p4g
title: Model_oc_59_M&A (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/uawjrq
title: Model_oc_277_V2 (v0=1e14).tab

description: :unav
DOI: 10.14457/cu.res.2013.104
title: โครงการการถักทออนาคตสู่โลกข้ามพรมแดน : แนวทางส่งเสริมการศึกษาของเด็กและเยาวชนผู้อพยพในอำเภอแม่สอด จังหวัดตาก
DOI: 10.14457/cu.res.2016.64
title: การพัฒนาระบบสารสนเทศสนับสนุนการวางแผนจัดทำงบประมาณระดับจังหวัดด้านทรัพยากรน้ำและเกษตร
DOI: 10.14457/cu.res.2017.34
title: โครงการ การพัฒนาศักยภาพอุตสาหกรรมการท่องเที่ยวเชิงสุขภาพของไทย เพื่อเป็นศูนย์กลางการท่องเที่ยวเชิงสุขภาพในเอเชีย
DOI: 10.14457/cu.res.2017.35
title: การพัฒนาวิธีทดสอบโคซี่สำหรับตรวจกรองโรคนิ่วปัสสาวะ
DOI: 10.5281/zenodo.3884127
title: BPlusPlusSmallMedium

description: Data to reproduce results
DOI: 10.5281/zenodo.3884128
title: BPlusPlusSmallMedium

description: Data to reproduce results
DOI: 10.7910/dvn/9argzn/0lbfy3
title: Model_oc_271_M&A (v0=1e12).tab

description: :unav
DOI: 10.7910/dvn/9argzn/1yq6ac
title: Model_oc_269_M&A (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/ailjcs
title: Model_oc_131_M&A (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/bj7f9j
title: Model_oc_54_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/ehj1mp
title: Model_oc_66_V2 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/eisddv
title: Model_oc_161_V1 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/i7dqfn
title: Model_oc_48_V3 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/ohhiic
title: Model_ic_55_V3 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/oktw9t
title: Model_oc_105_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/qrmpne
title: Model_oc_107_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/sadeob
title: Model_oc_207_M&A (v0=1e14).tab

description: :unav
DOI: 10.14457/cu.res.2010.132
title: โครงการ สารยับยั้งอะไมเลสจากผลไม้ไทย
DOI: 10.14457/cu.res.2012.134
title: โครงการ การผลิตสารต้านเชื้อราจากยีสต์ Aureobasidium pullulans สายพันธุ์เขตร้อนที่คัด แยกได้ในประเทศไทย
DOI: 10.14457/cu.res.2012.135
title: โครงการการกำจัดและการนำกลับสารประกอบเพอร์ฟลูออริเนท จากน้ำเสียโดยตัวกลางดูดซับชนิดซิลิเกต
DOI: 10.14457/cu.res.2014.107
title: โครงการ ภาวะเสี่ยงต่อการเกิดนิ่วทางเดินปัสสาวะและปัจจัยยับยั้งนิ่วในผู้ป่วยภาคตะวันออกเฉียงเหนือและบุคคลในครอบครัว
DOI: 10.7910/dvn/5fisnq/0azufj
title: RPDN BR Diplomatic presence Country-level release v2 070620-1.tab

description: Brazil's diplomatic presence, country-level (1995-2019)
DOI: 10.7910/dvn/5fisnq/2on0ed
title: RPDN TR Presidential diplomacy release v2 070620-1.tab

description: Turkey's presidential diplomacy (1995-2018)
DOI: 10.7910/dvn/5fisnq/jgbybs
title: RPDN SA Presidential diplomacy release v2 070620.tab

description: South Africa's presidential diplomacy (1994-2019)
DOI: 10.7910/dvn/5fisnq/uyfkso
title: RPDN BR Presidential diplomacy release v2 070620-1.tab

description: Brazil's presidential diplomacy (1995-2018)
DOI: 10.7910/dvn/9argzn/513uid
title: Model_oc_283_V2 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/6qub6k
title: Model_oc_155_V3 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/bjuvbn
title: Model_oc_73_M&A (v0=1e12).tab

description: :unav
DOI: 10.7910/dvn/9argzn/g55fdw
title: Model_oc_215_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/h9yjq3
title: Model_ic_34_M&A (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/jtnb2b
title: Model_oc_198_M&A (v0=1e12).tab

description: :unav
DOI: 10.7910/dvn/9argzn/nq1ae9
title: Model_oc_122_V1 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/nueiwz
title: Model_oc_229_V3 (v0=1e14).tab

description: :unav
DOI: 10.7910/dvn/9argzn/prmcqi
title: Model_oc_230_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/resagv
title: Model_oc_157_M&A (v0=1e13).tab

description: :unav
DOI: 10.7910/dvn/9argzn/vp8zrm
title: Model_oc_20_V1 (v0=1e14).tab

description: :unav
DOI: 10.14457/cu.res.2005.65
title: การปลดปล่อยมีเทนในระบบการปลูกข้าวแบบตามกัน ข้าว - ปล่อยที่ว่างเปล่า - ข้าว บริเวณที่ลุ่มภาคกลางประเทศไทย
DOI: 10.14457/cu.res.2007.100
title: โครงการ สู่สังคมไทยเสมอหน้าการศึกษาโครงสร้างความมั่งคั่งและโครงสร้างอำนาจเพื่อการปฏิรูป
DOI: 10.14457/cu.res.2016.65
title: โครงการ การศึกษาด้านแหล่งน้ำเพื่อการจัดการน้ำของลุ่มน้ำน่านเชิงกลยุทธ์ (การพัฒนาระบบการบริหารจัดการน้ำในลุ่มน้ำเชิงกลยุทธ์ภายใต้ความเสี่ยงใหม่และจัดทำข้อเสนอแนะเชิงกลยุทธ์)