121 research outputs found
Exploring Nitrogen Leaching using Uncertainty Visualization
No full textNitrogen (N) is an essential nutrient for many crops including corn and soybean. However, its leaching into groundwater is a serious cause of concern for environmental and public health. The amount of N leaching is closely linked to soil water drainage and rainfall. Prediction of N leaching in cropping systems is critical to the improvement of crop management through the reduction of N leaching. Visualizations can help understand uncertainty in the prediction of N leaching in soil. The uncertainty in N leaching originates from uncertainty in many parameters, such as weather predictions, soil properties, and the information entered by the user (e.g. N fertilizer). We have developed a platform to assist comprehending the relationship between various input parameters and N leaching. Our platform can reveal N leaching with uncertainty analysis and visualization of different parameters.
Adviser: Professors Haishun Yang and Hongfeng Y
A Web Based Real Time Nitrogen Leaching Calculator
Get PDFWhile nitrogen (N) is an essential nutrient for corn, its leaching to ground water is an serious environmental issue and a hazard to public health. N leaching is closely linked to weather factors, especially rainfall. Prediction of N leaching in cropping systems is critical to improvement of crop management and reduction of N leaching. The objective of this project is to develop a web app that predicts in real-time mode N leaching across Nebraska using real-time weather data.
We are in the processing of developing the web app and expect a prototype to be running in 2017 cropping season. Field research will be carried out to test and validate the app predictions. Once completed, the app can help farmers understand better the fate of soil N, improve fertilizer management, and reduce N leaching losses
Evaluation of Ground Water Pollution Potential by Employing the AQUIPRO Method and Verification and Validation of the Method through the Distribution of Nitrate Concentration
No full textThe AQUIPRO method was used to assess aquifer vulnerability using the operating water well logs. The AQUIPRO model is a parameter/factor weighting system for rating the pollution potential of aquifers. This method uses the water depth in well, as well as the clay and partial clay thickness in a well, to generate pollution potential scores. In this model, aquifer protection increases as the AQUIPRO vulnerability scores increase and ground water pollution potential decreases. Logs of 30 wells with chemical analyses of nitrate concentrations in these wells were used to determine the ground water pollution potential of Ajabshir Aquifer, East Azerbaijan. Theoretically, low AQUIPRO pollution potential scores should have more frequent occurrences of ground water contamination events than areas with high AQUIPRO scores with similar land-use, well construction, and well densities. The relative AQUIPRO scores were compared with the nitrate concentration in ground water. The results indicated that wells containing more nitrate showed a decrease of AQUIPRO vulnerability scores. The average nitrate-N concentrations within each relative AQUIPRO vulnerability scores category were also compared. The results indicated that as the relative AQUIPRO (R2 = 0.97) vulnerability scores increase, the mean nitrate concentrations also increase. Accordingly, comparison of the AQUIPRO method with the distribution of nitrate, and comparison of average nitrate concentrations in the every classification and relative AQUIPRO vulnerability scores confirmed the accuracy and validity of the method in the region
New Mexico pecan production
Get PDFPresented at Urbanization of irrigated land and water transfers: a USCID water management conference on May 28-31, 2008 in Scottsdale, Arizona.Pecans are a major agricultural crop in New Mexico. Currently there are approximately 11,000 hectares of pecans in the Elephant Butte Irrigation District, consuming more than one third of the annual diversion. The research presented here provides previously unavailable broad-scale estimates of pecan ET and pecan yield response to water. The data at the foundation of this paper were generated using the Regional ET Estimation Model (REEM) developed at New Mexico State University for agricultural and riparian vegetation (Samani et al. 2005, 2006, 2007). REEM uses remotely sensed satellite data to calculate ET as a residual of the energy balance. This research extends the results of REEM to an analysis of yield response to water in irrigated pecan production in the EBID. The study region is rapidly urbanizing and experiencing growing competition for scarce surface and groundwater supplies. The results of this research provide new insight into pecan water use and yields. This research illustrates the linkages that can be made between remote sensing technology, farm-level water management, and yield outcomes. This research sheds new light on the long-standing practice of deficit irrigation in pecans, the yield and conservation impacts of this practice, as well as water conservation policy implications
EFEKTIVITAS PEMBELAJARAN REMEDIAL DALAM MENINGKATKAN HASIL BELAJAR PESERTA DIDIK PADA MATA PELAJARAN IPS DI MTs NEGERI 1 PALU
Get PDFEFEKTIVITAS PEMBELAJARAN REMEDIAL DALAM MENINGKATKAN HASIL BELAJAR PESERTA DIDIK PADA MATA PELAJARAN IPS DI MTs NEGERI 1 PALU Moh. Israwan N. Samani Adawiyah Pettalongi Rizka Fadliah Nur
This article discusses the effectiveness of remedial learning in improving student learning outcomes in social studies subjects at MTs Negeri 1 Palu. The focus of the discussion in this study is how the effectiveness of remedial learning in improving student learning outcomes in social studies subjects at MTs Negeri 1 Palu and what factors hinder Remedial Learning in improving student learning outcomes in social studies subjects at MTs Negeri 1 Palu. The method that the author uses in this study is a qualitative research method. With data collection techniques including observation, interviews, and documentation. The results of this study indicate that in the effectiveness of remedial learning in improving student learning outcomes in social studies subjects at MTs Negeri 1 Palu, namely efforts to improve students are carried out if these students have not reached the minimum standard value, then students will be given remedial. because in this remedial learning students only repeat material that is not understood. Then the inhibiting factors in the effectiveness of remedial learning in improving student learning outcomes in social studies subjects at MTs Negeri 1 Palu, namely, the lack of attention from students, limited learning time carried out in schools as a result of the pandemic that is still endemic and the lack of communication between teachers and students. students to the problem of improving the value and efficiency of remedial learning in schools.
07 24 2022 28 38 https://creativecommons.org/licenses/by-nc-sa/4.0 10.24239/moderasi.Vol3.Iss1.54 https://moderasi.org/index.php/moderasi/article/view/54 https://moderasi.org/index.php/moderasi/article/download/54/43 https://moderasi.org/index.php/moderasi/article/download/54/4
Assessing the sustainability of groundwater quality for irrigation purposes using a fuzzy logic approach
No full textDeterioration of water quality poses significant threats to various aspects of life, particularly affecting agricultural irrigation, the primary source of food production for human consumption. In Iran, unregulated groundwater extraction for agriculture has resulted in a decline in groundwater quality, exemplified by a reduction in permitted wells for water exploitation in the Houmand-Absard aquifer from 47 to 20 over 18 years. Current water quality assessments for agricultural use often employ indicators focusing on specific ions, neglecting a comprehensive evaluation. This study introduces the Fuzzy Groundwater Quality Index (FGWQI), utilizing a fuzzy inference system model to appraise groundwater quality in the Houmand-Absard aquifer, specifically for irrigation in Iran. The FGWQI amalgamates five agriculture-oriented quality indicators: Sodium Adsorption Ratio (SAR), Sodium Percentage (Na%), Magnesium Hazard Ratio (MHR), Kelly's Index (KI), and Potential Salinity (PS). Comparative analyses between FGWQI and the widely used MHR were conducted on water samples collected from twenty stations during the 2021 seasons. Laboratory analyses of the samples determined parameters including Sodium, Calcium, Magnesium, Chloride, and Sulfate. The FGWQI model outperformed traditional indicators, notably MHR, demonstrating more realistic assessments. Despite MHR deeming water quality unsuitable in 47% of cases where FGWQI surpassed 60, FGWQI indicated permissible results (30–70), suggesting that, with proper groundwater management, a greater water resource allocation to agriculture is feasible. By adopting FGWQI over MHR, water wells deemed suitable for irrigation won't be decommissioned, offering farmers increased flexibility in groundwater utilization in the case study region
A preliminary analysis of the impact of autonomous maritime surface ships in marine technology education
Get PDFThis thesis is written to analyse the development of Maritime Autonomous Surface Ship its impact on technology and trends in shipping. The concept of Maritime Autonomous Surface Ship is introduced and projects that explore the concept and one which has been developed is reviewed. A review of Maritime Autonomous Surface Ships in Maritime Education and Training for seafarers is conducted to see the results of these studies.
The author analyses the courses taught at Aalto University to see how much of the Autonomous Ship concept is incorporated in the education of Naval Architecture students. A study of various courses offered at other universities is conducted and the technologies that are implemented in Maritime Autonomous Surface Ships are analysed. An evaluation of various education techniques is conducted to possibly formulate a plan to incorporate these techniques in the education of students of Marine and Arctic Technology at Aalto University.
Following the research, the viability of Maritime Autonomous Surface Ships to be incorporated is discussed and implementation of techniques in education are shown. A plan is formulated to see which technologies can be incorporated in which courses and a timeline is formulated to incorporate Maritime Autonomous Surface Ships in Marine and Artic Technology at Aalto University.
The author concludes that it is viable to incorporate Maritime Autonomous Surface Ships in education of Naval Architecture students by following the plan given
Dataset: A Cross-Platform and Cross-Interaction Study of User Personality based on Images on Twitter and Flickr
No full textThis folder contains the following dataset: Crossed-Linked Flickr and Twitter dataset.Psycho-Flickr consists of a set of users who answered the BFI survey. We collected profile and up to 300 posted and liked pictures for each user. Please contact Christina Segalin (http://www.cristinasegalin.com/) for access to these labels.Crossed-Linked Flickr and Twitter consists of a set of users with active accounts both on Flickr and Twitter.We used text mining approaches to predict personality traits for this set of users.We collected profile and up to 300 posted and liked picture for each user. Twitter or Flickr user ids with their text-predicted/BFI survey Big-Five personality scores are presented.Features extracted from profile images and averaged over posted and Liked Images are presented that include :Colors FeaturesCNN Generic Features: 4096 dim penultimate layer features of VGG_NetCNN object and scene categories:VGG_Net prediction on 1000 objects and 365 scene categoriesImagga tagsBig five personality traits are in this order:(ope: openness, con: conscientiousness, ext: extraversion, agr: agreeableness, and neu: neuroticism)For more information/questions about the dataset, please contact Sharath Chandra (chandrasg.github.io)If using this data set, please cite the following publication:@inproceedings{guntuku2017studying, title={Cross-platform and cross-interaction study of user personalitybased on images on Twitter and Flickr }, author={Zahra Riahi Samani, Sharath Chandra Guntuku, Mohsen Ebrahimi Moghaddam, DanielPreotiuc-Pietro, Lyle H. Ungar}, booktitle={Plos One Submission}, pages={}, year={2018}, organization={}}</div
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