Seeds of Change: Impact of Interventions by Bayer and Monsanto on the Elimination of Child Labour on Farms Producing Hybrid Cottonseed in India

seeds_of_change_final.pdf: 700 downloads, before Oct. 1, 2020

Task- and Risk-Mapping Study of Hybrid Vegetable Seed Production in India

Gives an overview of vegetable seed production in India, followed by recommendations for monitoring high-risk tasks, training, and capacity building to improve labor compliance

Child Labour in Carpet Industry in India: Recent Developments

ILRF_child_labor_in_carpet_industry_122706.pdf: 1034 downloads, before Oct. 1, 2020

Child Bondage Continues in Indian Cotton Supply Chain: More than 400,000 Children in India Involved in Hybrid Cottonseed Cultivation

The study was commissioned by OECD Watch, Deutsche Welthungerhilfe (DWHH), India Committee of the Netherlands (ICN), Eine Welt Netz NRW (EWN NRW), and International Labor Rights Forum (ILRF)This document is part of a digital collection provided by the Martin P. Catherwood Library, ILR School, Cornell University, pertaining to the effects of globalization on the workplace worldwide. Special emphasis is placed on labor rights, working conditions, labor market changes, and union organizing.ILRF_ChildBondage_India_2007.pdf: 226 downloads, before Oct. 1, 2020

Hemorrhage Detection and Analysis in Traumatic Pelvic Injuries

Traumatic pelvic injuries associated with high-energy pelvic fractures are life-threatening injuries. Extensive bleeding is relatively common with pelvic fractures. However, bleeding is especially prevalent with high-energy fractures. Hemorrhage remains the major cause of death that occur within the first 24 hours after a traumatic pelvic injury. Emergent-life saving treatment is required for high-energy pelvic fractures associated with hemorrhage. A thorough understanding of potential sources of bleeding within a short period is essential for diagnosis and treatment planning. Computed Tomography (CT) images have been widely in use in identifying the potential sources of bleeding. A pelvic CT scan contains a large number of images. Analyzing each slice in a scan via simple visual inspection is very time consuming. Time is a crucial factor in emergency medicine. Therefore, a computer-assisted pelvic trauma decision-making system is advantageous for assisting physicians in fast and accurate decision making and treatment planning. The proposed project presents an automated system to detect and segment hemorrhage and combines it with the other extracted features from pelvic images and demographic data to provide recommendations to trauma caregivers for diagnosis and treatment. The first part of the project is to develop automated methods to detect arteries by incorporating bone information. This part of the project merges bone edges and segments bone using a seed growing technique. Later the segmented bone information is utilized along with the best template matching to locate arteries and extract gray level information of the located arteries in the pelvic region. The second part of the project focuses on locating the source of hemorrhage and its segmentation. The hemorrhage is segmented using a novel rule based hemorrhage segmentation approach. This approach segments hemorrhage through hemorrhage matching, rule optimization, and region growing. Later the position of hemorrhage in the image and the volume of the hemorrhage are determined to analyze hemorrhage severity. The third part of the project is to automatically classify the outcome using features extracted from the medical images and patient medical records and demographics. A multi-stage feature selection algorithm is used to select the predominant features among all the features. Finally, boosted logistic model tree is used to classify the outcome. The methods are tested on CT images of traumatic pelvic injury patients. The hemorrhage segmentation and classification results seem promising and demonstrate that the proposed method is not only capable of automatically segmenting hemorrhage and classifying outcome, but also has the potential to be used for clinical applications. Finally, the project is extended to abdominal trauma and a novel knowledge based heuristic technique is used to detect and segment spleen from the abdominal CT images. This technique is tested on a limited number of subjects and the results are promising

ML-Based User Authentication Through Mouse Dynamics

Increasing reliance on digital services and the limitations of traditional authentication methods have necessitated the development of more advanced and secure user authentication methods. For user authentication and intrusion detection, mouse dynamics, a form of behavioral biometrics, offers a promising and non-invasive method. This paper presents a comprehensive study on ML-Based User Authentication Through Mouse Dynamics. This project proposes a novel framework integrating sophisticated techniques such as embeddings extraction using Transformer models with cutting-edge machine learning algorithms such as Recurrent Neural Networks (RNN). The project aims to accurately identify users based on their distinct mouse behavior and detect unauthorized access by utilizing the hybrid models. Using a mouse dynamics dataset, the proposed framework’s performance is evaluated, demonstrating its efficacy in accurately identifying users and detecting intrusions. In addition, a comparative analysis with existing methodologies is provided, highlighting the enhancements made by the proposed framework. This paper contributes to the development of more secure, reliable, and user-friendly authentication systems that leverage the power of machine learning and behavioral biometrics, ultimately augmenting the privacy and security of digital services and resources

Light as quantum back-action nullifying meter

We propose a new method to overcome quantum back-action in a measurement process using oscillators. An optical oscillator is used as a meter to measure the parameters of another open oscillator. The optical oscillator is synthesized such that the optical restoring force counters any perturbations induced by the quantum back-action phenomena. As a result, it is shown that the quantum back-action in continuous measurement is suppressed in the low frequency regime i.e., for frequencies much smaller than the resonance frequency of the open oscillator. As the meter plays the role of measuring parameters as well as suppressing the quantum back-action, we call it as quantum back-action nullifying meter. As an application of this method, synthesis of quantum back-action nullifying optical oscillator for suppressing radiation pressure force noise in linear and non-linear optomechanics is described.Comment: 6 pages, 1 figur

Impact of spallation and internal radiation on fibrous ablative materials

Space vehicles are equipped with Thermal Protection Systems (TPS) that encounter high heat rates and protect the payload while entering a planetary atmosphere. For most missions that interest NASA, ablative materials are used as TPS. These materials undergo several mass and energy transfer mechanisms to absorb intense heat. The size and construction of the TPS are based on the composition of the planetary atmosphere and the impact of various ablative mechanisms on the flow field and the material. Therefore, it is essential to quantify the rates of different ablative phenomena to model TPS accurately. In this work, the impact of two ablative mechanisms is studied. The first ablative mechanism studied is spallation, a phenomenon in which the TPS material ejects particles when exposed to atmospheric entry conditions. It is typically modeled as an added percentage of safety based on the overall ablation rate. A data-driven adaptive technique was performed to numerically reconstruct particle trajectories from spallation experiments at the NASA HyMETS facility to evaluate the effects of spallation on ablative materials. Several numerical models were developed and integrated into a Lagrangian particle trajectory code to ensure accurate results of this reconstruction. More specifically, a blended drag coefficient model to compute accurate particle dynamics, a non-sphericity model to account for irregular shapes of the particles, and a backtracking model to simulate the trajectories reversed in time from the first experimental point to the ejection location on the sample were developed. The reconstructed results were analyzed statistically to provide more information on these spalled particles\u27 size and ejection parameters. The results would estimate the mass loss due to spallation and probable causes for the ejection of particles. In addition, coupling was performed between the trajectory code and a hypersonic aerothermodynamic code to evaluate the effect of these hot, chemically reactive spalled particles on the flow field. This comprehensive study in spallation provides more insights into the phenomenon and tools to quantify its impact. The second mechanism studied in this work is internal radiation. Recent laser heating experiments have concluded that spectral radiative heat fluxes penetrate the ablative materials. The penetration distance is inversely proportional to the absorption coefficient of the material at the corresponding wavelength. Since the shock layer produced at the atmospheric entry conditions around the material can be expressed as a group of lasers of different wavelengths, the radiation penetration might be significant, especially in radiation-dominated entries. A radiation transfer equation is fully coupled to the in-house material response code to evaluate the impact of radiation penetration. In addition, a band model of unequal widths for the material was developed to investigate the effect of shock layer radiation within the material. The results showed high internal temperatures and internal decomposition. The tools developed in this work can be useful in accurately modeling the heat transfer through the material