539 research outputs found
INSPEC database analysis for Knowledge Management records
No full textThe study deals with the Knowledge Management papers covered in the INSPEC, an international database on Information Science, Physical Sciences, Engineering and Computer Sciences. The papers have been analysed in terms of their content and other scientometric parameters
Rice production and water requirement under climate change conditions - developing management strategies for a sustainable system for an agriculturally predominant region
Full text linkEmbargo set by: Seth Robbins for item 112320
Lift date: 2021-08-23T20:48:32Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemLimited Restriction Lifted for Item 112320 on 2021-08-24T09:15:28Z.Increasing crop production is an inevitable demand of current growing population all over the world. Implementation of field crop practices potentially enables farmers to achieve that desired increase in crop production estimated to be a 60% increase compared to current condition. The CERES-Rice model in DSSAT was used for this study in order to provide the water stress impact on crop production, and best management strategies to improve the rice yield, followed by the calibration and validation with collected field experimental data. Ten-years (2006-2015) of field experimental data were collected from the CIMMYT (International Maize and Wheat Improvement Centre)-BISA (Borlaug Institute for South Asia), Pusa, Bihar, India, research farm for calibration and validation of the CERES-Rice model. Predicted change in climate has significant impact on rice production in Bihar, and thus, will affect food security issues in India and other developing countries. Since rice is the primary food for the majority of Indian people, the focus of this study was to predict the changes in the (a) rice yield and phenological growth, and (b) irrigation water requirement for current yield level as well as 60% increase in rice yield by 2050s (2050-2059) as affected by climate change in the state of Bihar.
The genetic coefficients were developed for the rice variety, Rajendra Mahsuri (predominantly used by more than 90% rice farmers in Bihar), and used for validation of the model. The normalized root means square error (RMSEn) and d-index values were obtained to be 2.73% and 0.62, respectively, for prediction of yield with a model performance efficiency of 75%. The crop model simulation for water stress during vegetative and maturity phase showed to decrease in rice yield by 24% and 33%, respectively, from measured data. However, the water stress during reproductive stage showed the highest reduction in the yield by 43%. Considering the management strategies, where farmers do not need to invest a large amount of resources to increase the rice production, some factors were assessed by sensitivity analysis of the CERES-Rice model. The optimum transplanting date was found to be during the month of June to achieve the highest yield of Rajendra Mahsuri rice. Incorporation of crop residue up to 2500 kg/ha would increase the yield by 22%, compared to the management practices where no residue is applied in the field. Additionally, row spacing of 20 cm increased rice yield by 16-18%, compared to the yield obtained at spacing of 5 cm, and for maximum yield, optimum planting depth was found to be 2 to 4 cm. Keeping a ponding depth of 4-6 cm during crop duration would aid in maximizing the rice yield by 10-15%.
To study the climate change impact on rice yield and water requirement, four GCMs were used for all four climate change scenarios (RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5). The projected changes in climatic variables showed the change in future climate during 2020-2059 from baseline period (1980-2004). A Taylor diagram was constructed to analyze the relationship between the historical observed and simulated climate data; Mann-Kendall trend test for climate data of each GCM revealed the trend in climate from 2020-2059 for the climate change scenarios (RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5). Further, in order to increase the rice production by 60% during the 2050s, the irrigation requirement for all four climate change scenarios was computed based on the percentage of yield productivity from irrigation water. The results showed that the precipitation amount increased from 2020 to 2059, and hence, the irrigation requirement was predicted not to be as much higher as one would expect for a 60% increase in crop yield. Yield increase by the year of 2059 also partly accounted by an increase in CO2 concentration as predicted by all climate change scenarios. We investigated several strategies, such as conservation agriculture (direct-seeded rice with residue application) and reduction of post-harvest loss, to reduce the water requirement to produce 60% more rice by 2059. Moreover, if we combine both conservation agriculture and removal of 30% of postharvest losses, the irrigation requirement would be reduced by 26% (45 to 19%), 20% (44 to 24%), 21% (43 to 22%), 22% (39 to 17%), and 20% (41 to 21%) with current, RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 conditions, respectively.
The assessment on rice production with default value of CO2 concentration (400 ppm) during 2020-2059 demonstrated a decrease in rice yield and phenological days, but increase in water demand. The increase in water demand was found due to reduction in CO2 concentration, which increases the water use efficiency. Larger the differences between default and changed CO2 concentration (as predicted by the climate change scenarios), larger were the deviations between all the outputs. During 2050s, the maximum reduction in yield was 23% with RCP 8.5 and the lowest reduction of 15% was observed with RCP 2.6. Similarly, water demand increased due to decrease in CO2 concentration. The maximum decrease in phenological days was estimated to be 14 days with worst-case scenario (RCP 8.5).
Since most farmers in the state of Bihar only produce Rajendra Mahsuri rice variety, this information can help in planning for maximizing production of this rice variety and decreasing water requirement strategies in the state of Bihar, India and similar other locations, where water availability would be severely impacted by climate change.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-05-01The student, Ranjeet Kumar Jha, accepted the attached license on 2019-04-15 at 15:42.The student, Ranjeet Kumar Jha, submitted this Dissertation for approval on 2019-04-15 at 15:43.This Dissertation was approved for publication on 2019-04-17 at 11:50.DSpace SAF Submission Ingestion Package generated from Vireo submission #13638 on 2019-08-22 at 16:21:29Made available in DSpace on 2019-08-23T20:47:25Z (GMT). No. of bitstreams: 2
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Previous issue date: 2019-04-17Embargo set by: Seth Robbins for item 112320
Lift date: 2021-08-23T20:47:38Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD syste
Modeling and measurement of tile drain controls in intensively managed landscapes
Full text linkTile drains are widely used in the Midwestern United States to improve the productivity of poorly drained agricultural fields. Since a tile drain reduces vadose zone soil moisture by lowering the water table, and its outlets feed directly into streams and ditches, tile flow can affect various hydrologic, biotic and biogeochemical processes in the watershed the streams. However, the effects of spatially resolved micro-topographic variability, such depressions and roadside ditches, on tile flow and their accumulated impact on ecohydrologic and nutrient dynamics remain poorly understood. Here we present an explicit model of tile flow and incorporated into the integrated ecohydrologic-flow model, MLCan-GCSFlow, to investigate the impacts of tile drain on ecohydrologic and nutrient dynamics in intensively managed agricultural fields at lidar-resolution scales. Explicit coupling between subsurface and tile flow is obtained by modifications of variably saturated Richards equation to capture the impacts of tile drain on soil moisture. The coupling between subsurface and overland flow is obtained by prescribing a boundary condition switching approach at the top surface of the computational domain. Model results for study sites in Critical Zone Observatory for Intensively Managed Landscapes (IMLCZO) show the significance of tile drain flow on the vertical and spatial soil moisture distribution and coupled surface - sub-surface flow dynamics.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2018-05-01The student, Derek Wagner, accepted the attached license on 2016-04-25 at 13:44.The student, Derek Wagner, submitted this Thesis for approval on 2016-04-25 at 13:49.This Thesis was approved for publication on 2016-04-26 at 17:26.DSpace SAF Submission Ingestion Package generated from Vireo submission #9476 on 2016-07-07 at 13:50:47Made available in DSpace on 2016-07-07T20:28:00Z (GMT). No. of bitstreams: 2
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Previous issue date: 2016-04-26Embargo set by: Seth Robbins for item 93175
Lift date: 2018-07-07T20:28:14Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 93175
Lift date: 2018-07-07T20:35:34Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemU of I Only Restriction Lifted for Item 93175 on 2018-07-08T09:15:27Z
Predictability and trends of annual pollutant loads in Midwestern watersheds
Full text linkThe effect of multiple stressors on global water resources have been increasing rapidly over the past few decades. Anthropogenic activities such as rapid industrialization, urbanization, deforestation and increased application of agricultural nutrients have led to a decline in overall quality of our aquatic environment. Additionally, these activities have increased greenhouse gas concentrations globally, warming the earth’s atmosphere and eventually having a detrimental effect on global water and energy balances. The global water cycle has been altered, leading to its overall intensification and an increase in frequency of extreme events and such as floods and droughts. Also, the demands of higher quality water have been rising globally attributed to a burgeoning world population, further stressing the water resources. To address the increased water demands worldwide coupled with declining water quality and depletion of water resources requires new approaches in water management along with improvement in water use efficiencies.
To facilitate development of newer approaches of water management and solutions to alleviate global water problems requires an overall comprehensive assessment of our water resources. A key step in these assessments is water quality monitoring which will help improve our ability to predict water quantity, quality and distribution on a global scale. In this research, I aim to improve our knowledge of anthropogenic and natural impacts on global water resources, largely focusing on water quality monitoring by evaluating and refining the science of predicting pollutant (nutrient and sediment) export from large scale watersheds. To enable these goals, this research is centered on large watersheds in Midwestern United States, which have been some of the primary sources of nutrient and sediment export to downstream water bodies such as the Gulf of Mexico and Lake Erie leading to massive eutrophication. In total, fourteen watersheds with extensive water quality datasets are analyzed in different stages of this research. Typically, these large watersheds are predominantly agricultural with intensive row-cropped farmlands having a network of sub-surface tile drain systems.
The science of pollutant export and various hydrological processes associated with it have been simulated using three major modeling approaches namely statistical and empirical modeling, physically-based modeling and data mining methods. In this research I improve, apply or evaluate all three approaches to meet specific objectives related to annual pollutant load predictions and trend assessments. In the first part of this research, I use regression techniques to assess the role of large load events in predicting annual pollutant (Suspended Solids (SS), Total Phosphorus (TP) and Nitrate-Nitrogen (NO3-N)) loads. In doing so, a novel baseflow separation technique based on mechanistic differences in nutrient and sediment export is proposed and applied. Then, I assess the spatio-temporal patterns of pollutant export from large Midwestern watersheds using circular statistics. This enables identification of critical periods of high load export and also gaging impacts of landuse, management practices, and sources of pollution on overall annual loads. These analyses constitute the first such application of these approaches on a large spatio-temporal scale especially for nutrient export dynamics. I next calibrate a physically-based SWAT model for hydrology and water quality predictions in the largest watershed in the Lake Erie basin. I use this calibrated model to gage the impacts of future projected climate changes from the mid-century and late-century time periods on the hydrology and water quality in the watershed. Further, I evaluate two data mining techniques namely the nearest-neighbor method and decision trees which have scarcely been used in hydrology to predict missing NO3-N concentrations for two extensively monitored watersheds in the Lake Erie basin. Lastly, I evaluate the impacts of available water quality data for concentration and load predictions and trend calculations based on traditional statistical methods and some new improved and modified approaches which have not yet been applied extensively.Item withdrawn by Laura Spradlin ([email protected]) on 2013-12-04T14:19:01Z
Item was in collections:
University of Illinois Theses & Dissertations (ID: 1)
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Original Data
Group with Access UIUC Users [automated]
Release Date: 2016-01-16 12:19:34 UTC
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemItem marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Seth Robbins ([email protected]) on 2014-01-16T18:19:49Z
Item is restricted until 2016-01-16T18:19:34ZU of I Only Restriction Lifted for Item 46870 on 2016-01-16T11:01:04Z
Anterior cruciate ligament reconstruction in patients with generalized joint laxity.
Full text linkGeneralized joint laxity is a genetically determined component of overall joint flexibility. The incidence of joint laxity in the overall population is approximately 5% to 20%, and its prevalence is higher in females. Recently it was noticed that individuals with generalized joint laxity are not only prone to anterior cruciate ligament injuries but also have inferior results after a reconstruction. Therefore, an anterior cruciate ligament reconstruction in patients with generalized laxity should be undertaken with caution due to the higher expected failure rate from the complexity of problems associated with this condition. It is also necessary to identify the risk factors for the injury as well as for the post operative outcome in this population. A criterion that includes all the associated components is necessary for the proper screening of individuals for generalized joint laxity. Graft selection for an anterior cruciate reconstruction in patients with ligament laxity is a challenge. According to the senior author, a hamstring autograft is an inferior choice and a double bundle reconstruction with a quadriceps tendon-bone autograft yields better results than a single bundle bone-patella tendon-bone autograft. Future studies comparing the different grafts available might be needed to determine the preferred graft for this subset of patients. Improved results after an anterior cruciate ligament reconstruction can be achieved by proper planning and careful attention to each step beginning from the clinical examination to the postoperative rehabilitation.ope
Characterizing vegetation structure using waveform LiDAR
Full text linkThe structure of light penetration through the canopy plays an important role in water, carbon, and energy fluxes between the biosphere and the atmosphere. Total foliage and foliage distribution are major aspects of canopy structure that significantly influence light and vegetation interaction. Waveform airborne LiDAR data contains large amounts of vegetation structural information, and is the best tool available for providing detailed physical information for large areas of vegetation.
In this thesis, we first provide a complete work flow that extracts and processes waveform LiDAR data for an area of interest. Then we test the feasibility of using waveform LiDAR data to estimate individual tree biomass with limited field samples. We use a voxelization method to generate pseudo-waveforms for individual trees and apply a stepwise regression to find the relationship between pseudo-waveform structural characteristics and biomass estimated by allometric equations using tree survey data. Next, we present a method for describing physical canopy clumping structure for individual trees that provides detailed spatial clumping variations. We utilize the K-means clustering algorithm to extract structure from the large amount of canopy architecture information provided by full-waveform LiDAR. Finally we use representative cluster traits to identify structurally significant clusters.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2018-08-01The student, Kunxuan Wang, accepted the attached license on 2016-07-22 at 12:30.The student, Kunxuan Wang, submitted this Thesis for approval on 2016-07-22 at 12:33.This Thesis was approved for publication on 2016-07-22 at 14:03.DSpace SAF Submission Ingestion Package generated from Vireo submission #9982 on 2016-11-10 at 12:25:29Made available in DSpace on 2016-11-10T18:43:03Z (GMT). No. of bitstreams: 2
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Previous issue date: 2016-07-22Embargo set by: Seth Robbins for item 95494
Lift date: 2018-11-10T18:43:22Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemU of I Only Restriction Lifted for Item 95494 on 2018-11-11T10:15:28Z
Analysis of long-term precipitation sequencing patterns in North America
Full text linkPrecipitation sequencing, or the overall temporal pattern of precipitation events and the persistence of those events, is an important factor in describing nonstationarity in climate variability. It is a vital, yet often overlooked part of developing long-term climate predictions. Precipitation sequencing, which is based on rainfall of all magnitudes, is not well understood in part because much of recent research has focused on changes solely in extreme precipitation. This study examines precipitation sequencing pattern changes in North America over a study period of 1880-2010, and compares sequencing changes for both nonextreme and extreme rainfall. Results reveal nonstationarity in precipitation sequencing in North America and indicate that changes in non-extreme rainfall are greater in magnitude and more prevalent than those in extreme rainfall. Analysis of the spatial variation of non-extreme precipitation sequencing reveals both continent-scale trends and, unexpectedly, strongly localized, regional trends. Results not only validate questions about the assumption of stationarity in climate models and studies but illustrate the importance of conducting precipitation studies at the proper scale in order to capture significant local trends. Incorporation of both elements into climate models can improve the robustness of long-term predictions. Results from this analysis reveal the need for increased study of non-extreme rainfall and for moving away from the assumption of stationarity in precipitation patterns when developing climate predictions. Additionally, results may shed light on the regional nature of precipitation sequencing changes and its drivers, which may help scientists make better decisions when choosing which climate models fit their studies.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2018-05-01The student, Susana Roque, accepted the attached license on 2016-04-27 at 17:00.The student, Susana Roque, submitted this Thesis for approval on 2016-04-27 at 17:06.This Thesis was approved for publication on 2016-04-28 at 10:02.DSpace SAF Submission Ingestion Package generated from Vireo submission #9461 on 2016-07-07 at 14:17:57Made available in DSpace on 2016-07-07T21:18:02Z (GMT). No. of bitstreams: 2
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Previous issue date: 2016-04-28Embargo set by: Seth Robbins for item 93309
Lift date: 2018-07-07T21:18:16Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemLimited Restriction Lifted for Item 93309 on 2018-07-08T09:15:36Z
An experimental and modeling synthesis to determine seasonality of hydraulic redistribution in semi-arid region with multispecies
Full text linkA key challenge in critical zone science is to understand and predict the interaction
between aboveground and belowground eco-hydrologic processes. Roots play an important role
in linking aboveground plant ecophysiological processes, such as carbon, water and energy
exchange with the atmosphere, and the belowground processes associated with soil moisture and
carbon, and microbial and nutrient dynamics. In this study, I have analyzed aboveground and
belowground interaction through hydraulic redistribution (HR), a phenomenon that roots serve as
preferential pathways for water movement from wet to dry soil layers. HR process is simulated
by multi-layer canopy model (MLCan) and compared with relative measurements from the field
to study effect of HR on different plant species where Posopis velutina Woot. (velvet mesquite)
and understory co-exist and share resources. The study site is one of Ameriflux sites: Santa Rita
Mesquite savanna, AZ, with a distinct dry season that indicates occurrence of HR. The model is
modified to better represent Santa Rita Mesquite site where fractions of plants and soil coverage
change from season to season.
I analyzed how two plants share and utilize the limited amount of water by HR in both
dry and wet seasons. During dry season, water moves from deep layer to shallow layer through
roots and hydraulic lift (HL) occurs. During wet season, water moves from shallow layer to deep
layer through roots and hydraulic descent (HD) occurs. Mesquites deposit water to deeper soil
through their roots right after rain to prevent water loss due to surface evaporation. About 40%
of precipitation is transferred to deep soil layer with HD and 15% of that is transported back to
shallow soil layer with HL in dry season. Assuming water supplied through HL supports
evapotranspiration of plants, HL supports 10% of evapotranspiration. The ratio of mesquite and
understory root conductivities is an important factor that determines how two plant species
interact and share resources in water-limited environment. The sensitivity analysis of root
conductivities suggests that high understory root conductivity facilitates water transported by HR and increases mesquite transpiration and photosynthesis. Understory transpiration and
photosynthesis show increase with HR only in dry season when water is supplied to shallow
layer through HL. With low understory root conductivity, understory looses the competition for
water against mesquite and show decrease in transpiration and photosynthetic fluxes when HR is
allowed.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2018-08-01The student, Esther Lee, accepted the attached license on 2016-07-22 at 09:49.The student, Esther Lee, submitted this Thesis for approval on 2016-07-22 at 12:00.This Thesis was approved for publication on 2016-07-22 at 14:45.DSpace SAF Submission Ingestion Package generated from Vireo submission #9902 on 2016-11-10 at 12:25:18Made available in DSpace on 2016-11-10T18:42:59Z (GMT). No. of bitstreams: 2
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Previous issue date: 2016-07-22Embargo set by: Seth Robbins for item 95481
Lift date: 2018-11-10T18:43:22Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemU of I Only Restriction Lifted for Item 95481 on 2018-11-11T10:15:19Z
Marketing Research in Libraries and Information Centers
Full text linkThe concept of marketing of information services and products has made a great impact on relationship of libraries, librarians and library users. The use of information sources, services and products has been accelerated through adoption of marketing strategies especially because of emergence of new technologies and availability of information in e-formats. This study highlight the important, scope and the various steps of marketing in the domain of Library and Information Centres The use of information sources, services and products has been accelerated through adoption of marketing strategies
On the Effect of Clock Frequency on Voltage and Electromagnetic Fault Injection
No full textWe investigate the influence of clock frequency on the success rate of a fault injection attack. In particular, we examine the success rate of voltage and electromagnetic fault attacks for varying clock frequencies. Using three different tests that cover different components of a System-on-Chip, we perform fault injection while its CPU operates at different clock frequencies. Our results show that the attack’s success rate increases with an increase in clock frequency for both voltage and EM fault injection attacks. As the technology advances push the clock frequency further, these results can help assess the impact of fault injection attacks more accurately and develop appropriate countermeasures to address them.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Cyber Securit
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