Artificial intelligence enabled automatic traffic monitoring system

The rapid advancement in the field of machine learning and high-performance computing have highly augmented the scope of video-based traffic monitoring systems. In this study, an automatic traffic monitoring system is proposed that deploys several state-of-the-art deep learning algorithms based on the nature of traffic operation. Taking advantage of a large database of annotated video surveillance data, deep learning-based models are trained to track congestion, detect traffic anomalies and tabulate vehicle counts. To monitor traffic queues, this study implements a Mask region-based convolutional neural network (Mask R-CNN) that predicts congestion using pixel-level segmentation masks on classified regions of interest. Similarly, the model was used to accurately extract traffic queue-related information from infrastructure mounted video cameras. The use of infrastructure-mounted CCTV cameras for traffic anomaly detection and verification is further explored. Initially, a convolutional neural network model based on you only look once (YOLO), a popular deep learning framework for object detection and classification is deployed. The following identification model, together with a multi-object tracking system (based on intersection over union -- IOU) is used to search for and scrutinize various traffic scenes for possible anomalies. Likewise, several experiments were conducted to fine-tune the system's robustness in different environmental and traffic conditions. Some of the techniques such as bounding box suppression and adaptive thresholding were used to reduce false alarm rates and refine the robustness of the methodology developed. At each stage of our developments, a comparative analysis is conducted to evaluate the strengths and limitations of the proposed approach. Likewise, IOU tracker coupled with YOLO was used to automatically count the number of vehicles whose accuracy was later compared with a manual counting technique from CCTV video feeds. Overall, the proposed system is evaluated based on F1 and S3 performance metrics. The outcome of this study could be seamlessly integrated into traffic system such as smart traffic surveillance system, traffic volume estimation system, smart work zone management systems, etc.by Vishal MandalIncludes bibliographical reference

Effect of in situ Rainwater Harvesting and Mulching on Growth, Yield and Fruit Quality in Mango Var. Arka Neelachal Kesri in Eastern India

A field study was conducted at Central Horticultural Experiment Station (ICAR-IIHR), Bhubaneswar, India, during 2007-2013 in a new mango orchard of the variety 'Arka Neelachal Kesri' at 5m x 5m spacing, to conserve rain-water and to enhance soil moisture availability during dry periods for augmenting plant growth and fruit production. Among the four in situ rain-water harvesting techniques (cup-and-plate, half-moon, full-moon, and trench) evaluated in combination with three types of mulch (no mulch, inorganic mulch, and organic mulch), the cup-and-plate system resulted in maximum annual increment in vegetative growth and fruit yield (4.67kg/plant), while, organic (paddy straw) and inorganic (black polythene, 100μ thickness) mulches improved vegetative growth, fruit yield and TSS in fruit significantly over no mulch

Molecular Epidemiology of HIV-1 Subtypes in India: Origin and Evolutionary History of the Predominant Subtype C

This thesis describes the translational genomics of HIV-1subtype C in India from its origin to therapeutic response with the aim to improve our knowledge for better therapeutic and preventive strategies to combat HIV/AIDS. In a systemic approach, we identified the molecular phylogeny of HIV-1 subtypes circulating in India and the time to most recent common ancestors (tMRCA) of predominant HIV-1 subtype C strains. Additionally, this thesis also studied drug resistance mutations in children, adolescents and adults, the role of host factors in evolution of drug resistance, and population dynamics of viremia and viral co-receptor tropism in perinatal transmission. Finally, the long term therapeutic responses on Indian national first-line antiretroviral therapy were also studied. In Paper I, we reported an increase in the HIV-1 recombinant forms in the HIV-1 epidemiology using a robust subtyping methodology. While the study confirmed HIV- 1 subtype C as a dominant subtype, its origin was dated back to the early 1970s from a single or few genetically related strains from South Africa, whereafter, it has evolved independently. In Paper II, the lethal hypermutations due to the activity of human apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3G (hA3G) was significantly associated with antiretroviral therapy (ART) failure in Indian HIV-1 subtype C patients. The presence of M184I and M230I mutations were observed due to the editing of hA3G in the proviral compartment but stop codons were also found in the open reading frames and the same drug resistance mutations were absent in plasma virus. Therefore, it is unlikely that the viral variants which exhibit hypermutated sequences and M184I and/or M230I will mature and expand in vivo and hence are unlikely to have any clinical significance. The high concordance of drug resistance genotyping in the plasma and proviral compartments in therapy-naïve patients, gives weight to the idea of using whole blood for surveillance of drug resistance mutations which precludes logistic challenges of cold chain transport. In Papers III and IV, we identified a substantial proportion of HIV-1 subtype C perinatally-infected older children who had a high burden of plasma viremia but also had high CD4+ T-cell counts. In addition, older children with HIV-1 subtype C infection presented a high prevalence of predicted X4 and R5/X4 tropic strains which indicates that HIV-1 subtype C strains required longer duration of infection and greater disease progression to co-receptor transition from R5- to X4-tropic strains (IV). Our studies also indicate that transmitted drug resistance is low among Indian HIV-1 infected children, adolescents (III) and adults (II). In Paper V, in a longitudinal cohort study, a good long-term response to the Indian national first-line therapy for a median of nearly four years with 2.8% viral failure, indicating the overall success of the Indian ART program. Our study also showed that three immunologically well patients with virological rebound and major viral drug resistance mutations (M184V, K103N and Y181C) during one study visit had undetectable viral load at their next visit. These findings suggest that use of multiple parameters like patients’ immunological (CD4+ T-cell count), virological (viral load) and drug resistance data should all be used to optimize the treatment switch to second line therapy. In conclusion, this translational genomics study enhances our knowledge about the HIV-1 subtype C strains circulating in India which are genetically distinct from prototype African subtype C strains. Considerably more research using appropriate models need to be performed to understand the phenotypic and biological characteristics of these strains to guide efficient disease intervention and management strategies

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Not AvailableA field study was conducted at Central Horticultural Experiment Station (ICAR-IIHR), Bhubaneswar, India, during 2007-2013 in a new mango orchard of the variety ‘Arka Neelachal Kesri’ at 5m x 5m spacing, to conserve rain-water and to enhance soil moisture availability during dry periods for augmenting plant growth and fruit production. Among the four in situ rain-water harvesting techniques (cup-and-plate, half-moon, full-moon, and trench) evaluated in combination with three types of mulch (no mulch, inorganic mulch, and organic mulch), the cup-and-plate system resulted in maximum annual increment in vegetative growth and fruit yield (4.67kg/plant), while, organic (paddy straw) and inorganic (black polythene, 100μ thickness) mulches improved vegetative growth, fruit yield and TSS in fruit significantly over no mulch.Not Availabl

Optimal allocation of near-expiry food in a retailer-foodbank supply network with economic and environmental considerations: an aggregator's perspective

Wastage of perishable food products is a severe concern to society and needs to be addressed to ensure food security for all. Moreover, the food waste when sent to landfills, decomposes to produce greenhouse gases like methane and carbon dioxide. The emergence of food banks and aggregators has abated the problem of food wastage to a certain extent. An aggregator, which connects the retailers to the food banks, plays a critical role in ensuring that the food reaches the food banks on time. However, to ensure food security and reduce wastage of food, it is essential that food aggregators remain profitable. The aggregator has to determine the number of heterogeneous vehicles to hire from the market and allocate them their route on a daily basis depending on donations committed by the retailers and also take into account potential environmental impact from the decomposition of food waste and carbon emitted from hired vehicles. Hence, we propose decision support for aggregators, using data from an aggregator based in Turkey, which can help in reducing food wastage by allocating the donated food items from retailers to food banks while maximizing the profitability of the aggregator and minimizing the environmental impact. We have also analyzed how the availability of different types of vehicles can impact the aggregator's profit. Furthermore, the effect of various model parameters such as transportation cost, and percentage of retailers' gain paid to the aggregator on the total profit along with the impact of distances on types of vehicles hired is also analyzed. We have compared two strategies that the aggregator could possibly employ and generate managerial insights