Thermal response analysis from in-cylinder combustion to exhaust aftertreatment.

The thermal response from in-cylinder combustion to exhaust aftertreatment was investigated for a 4-stroke single cylinder Yanmar diesel engine. The thermal characteristics of late post-injection inside the cylinder for enabling aftertreatment operations were simulated and experimentally verified. The cylinder head of the Yanmar engine was modified for measurement of in-cylinder pressure and temperature. A real-time heat release model was developed for analyzing the diesel combustion based upon the acquired cylinder pressure. However, the in-cylinder measurements could not be realized due to limitations of the thermocouple signal conditioning system. The thermal response from in-cylinder combustion to exhaust aftertreatment for the Yanmar diesel engine was characterized in terms of a heat loss coefficient and a time constant. Moreover, the effect of mass flowrate on both these factors was also evaluated. The procedure for quantifying the overall thermal response has been reported in detail. (Abstract shortened by UMI.)Dept. of Mechanical, Automotive, and Materials Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2006 .A83. Source: Masters Abstracts International, Volume: 45-01, page: 0446. Thesis (M.A.Sc.)--University of Windsor (Canada), 2006

Advanced Diagnostics, Control and Testing of Diesel Low Temperature Combustion

The conventional high temperature diesel combustion is constrained by the classical NOx-soot trade-off, so that any technique to reduce one emission generally increases the other. The simultaneous low NOx and soot can be achieved by lowering the combustion temperature and by preparing a cylinder charge of high homogeneity. However, the lowered combustion temperature may significantly reduce the fuel efficiency of such combustion cycles. Therefore, the overall objective of this work was to conduct a detailed analysis of the diesel LTC cycles that result in simultaneous low NOx and low soot, and to improve the LTC performance through advanced diagnostics and combustion control strategies. The empirical and analytical analyses in this dissertation provide an in-depth understanding of diesel LTC and present an effective strategy for navigating the narrow LTC corridors. The in-cylinder gas sampling tests culminated with the identification of an LTC NOx mechanism whereby the NOx reduction in the presence of combustibles was quantified on a crank angle-resolved basis. The intake gas treatment through catalytic oxidation and fuel reforming of EGR stabilized the LTC cycles. Novel flow management strategies were applied to improve the thermal response and the energy efficiency of the reforming operation. Adaptive combustion control techniques were developed to improve the fuel efficiency of the LTC cycles and to enable navigation within the narrow LTC corridors. A computationally efficient `Pressure Departure Ratio\u27 algorithm for estimating the combustion phasing in real-time was proposed along with a methodology for engine load management within-the-same-cycle, and were shown to improve the LTC operational stability. The detailed EGR analysis helped to develop a systematic LTC control strategy by quantifying the effects of intake charge dilution and boost pressure on the LTC performance metrics. Based on the empirical and analytical analyses, the load management and efficiency improvements of the LTC cycles were demonstrated with three different fuelling strategies as follows: (1) Single-injection LTC with heavy EGR at low loads, (2) Multi-shot LTC (early HCCI) with moderate EGR for mid-load operation, and (3) Split burning LTC for higher engine loads with DPF-tolerant soot

Application of the Mathematical Model of Tumor-Immune Interactions for IL-2 Adoptive Immunotherapy to Studies on Patients with Metastatic Melanoma or Renal Cell Cancer

Recent developments in Adoptive Immunotherapy for cancer management have lead clinicians to employ these techniques in hospital settings. Much data has been produced that indicates the effectiveness of introducing enhanced and expanded immune systems into cancer hosts. In this retrospective study we take another look at the Kirschner mathematical model for immune-tumor interactions in light of data presented by Rosenburg on patients with Metastatic Melanoma or Renal Cell Cancer

Service innovation in bottom of the pyramid markets

Master'sMASTER OF ENGINEERIN

PRELIMINARY FEASIBILTY STUDY OF SPECIAL SEAPORT FOR IRON PLANT IN OBI ISLAND, INDONESIA

The objective of the survey is to acquire the optimum location for iron plant and special seaport among alternative locations which will be followed with detailed topography, geotechnical, and oceanography surveys. The study was conducted in Obi Island, Province of Maluku, Indonesia. Initial feasibility study based on secondary data and survey found suitable location for jetty seaport. All of the proposed sites are not representing the ideal natural port; some aspects/components need to be improved to represent semi-natural port. Condition of Obi Island is hilly area; thus, site with large and flatten area requires large quantity of cut and fill and soil improvement. These cause large additional cost

Automated grading of chest x-ray images for viral pneumonia with convolutional neural networks ensemble and region of interest localization

Following its initial identification on December 31, 2019, COVID-19 quickly spread around the world as a pandemic claiming more than six million lives. An early diagnosis with appropriate intervention can help prevent deaths and serious illness as the distinguishing symptoms that set COVID-19 apart from pneumonia and influenza frequently don't show up until after the patient has already suffered significant damage. A chest X-ray (CXR), one of many imaging modalities that are useful for detection and one of the most used, offers a non-invasive method of detection. The CXR image analysis can also reveal additional disorders, such as pneumonia, which show up as anomalies in the lungs. Thus these CXRs can be used for automated grading aiding the doctors in making a better diagnosis. In order to classify a CXR image into the Negative for Pneumonia, Typical, Indeterminate, and Atypical, we used the publicly available CXR image competition dataset SIIM-FISABIO-RSNA COVID-19 from Kaggle. The suggested architecture employed an ensemble of EfficientNetv2-L for classification, which was trained via transfer learning from the initialised weights of ImageNet21K on various subsets of data (Code for the proposed methodology is available at: https://github.com/asadkhan1221/siim-covid19.git). To identify and localise opacities, an ensemble of YOLO was combined using Weighted Boxes Fusion (WBF). Significant generalisability gains were made possible by the suggested technique's addition of classification auxiliary heads to the CNN backbone. The suggested method improved further by utilising test time augmentation for both classifiers and localizers. The results for Mean Average Precision score show that the proposed deep learning model achieves 0.617 and 0.609 on public and private sets respectively and these are comparable to other techniques for the Kaggle dataset

Pneumoperitoneum, pneumoretroperitoneum, pneumomediastinum and extensive subcutaneous emphysema in a patient with ulcerative colitis: a case report.

Abstract INTRODUCTION: Pneumo-mediastinum and subcutaneous emphysema are rare presentations of lower gastrointestinal tract perforation. PRESENTATION OF CASE: We are presenting the case of a middle aged man diagnosed with UC who presented with dyspnea and subcutaneous emphysema, attributed to multiple perforations including the stomach and colon. CASE DISCUSSION: Patients with ulcerative colitis (UC) are at an increased risk of perforations due to friability of colonic mucosa given the chronic inflammation and relapsing flares. Chronic use of steroids further predisposes to stress ulcers. These pathologies sometimes coexist and identification of each is crucial for the appropriate treatment plan. CONCLUSION: The case allows for a learning opportunity focusing on coexisting pathologies which may be differentiated based on anatomical knowledge and patient presentation. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserve

Road Traffic Accident Analysis and Identification of Black Spot Locations on Highway

Road safety is the main problem in developing countries. Every year, millions of people die in road traffic accidents, resulting in huge losses of humankind and the economy. This study focuses on the road traffic accident analysis and identification of black spots on the Lahore-Islamabad Highway M-2. Official data of road traffic accidents were collected from National Highway and Highway Police (NH & MP) Pakistan. The data was digitized on MS Excel and Origin Pro. The accident Point weightage (APW) method was employed to identify the black spots and rank of the top ten black spots. The analysis shows that the trend of road traffic accidents on M-2 was characterized by a high rate of fatal accidents of 35.3%. Human errors account for 66.8% as the major contributing factors in road traffic accidents, while vehicle errors (25.6%) and environmental factors (7.6%) were secondary and tertiary contributing factors. The main causes of road traffic accidents were the dozing on the wheel (27.9%), the careless driving (24.6%), tyre burst (11.7%), and the brakes failure (7.4%). Kallar Kahar (Salt Range) was identified as a black spot (223 km, 224 km, 225 km, 229 km, and 234 km) due to vehicle brake failure. The human error was a major contributory factor in road traffic accidents, therefore public awareness campaign on road safety is inevitable and use of the dozen alarm to overcome dozing on the wheel. Doi: 10.28991/cej-2020-03091629 Full Text: PD