The ALISA delta(CRC) classifier for natural surfaces: Viewpoint-invariant and illumination-invariant classification of natural surfaces using general-purpose color and texture features with the ALISA delta(CRC) classifier

The objective of this research is to develop a classifier that can reliably and accurately discriminate among a large number of different natural-surfaces in color images using only general-purpose color and texture features. The general-purpose color and texture features are those which exhibit the least sensitivity to illumination and viewpoint variation in a broad range of applications for which color and texture are a reasonable basis for classification. The feature probability density function (PDF) distributions of natural-surface classes are most definitely not disjoint, which instantly obviates the appropriate use of Bayes' Decision Rule, which is profoundly confused by classes that are heavily overlapped in feature space. Therefore, it was also necessary to develop a new ALISA δCRC classifier that would not be confused by the many different and often highly similar natural-surface classes. A series of experiments have been designed and conducted using the CUReT image database, Caltech facial photo images, and natural images. An ALISA δ CRC classifier was trained with up to 61 classes in the CUReT image database, which presents each class in 205 different and carefully controlled viewpoint and illumination conditions. The results with images not in the training set yielded classification accuracies well above 95%. This research then extended the classifier feasibility tests and accuracy measurement using mosaic images made up from different CUReT material surface classes. Next, a skin classification experiment was conducted using Caltech facial photo images that had a single class of interest with complex backgrounds. Finally, a natural image-content classification experiment was performed using natural scenery images that had several classes of interest and irregular class boundaries

Fingerprint and Face Identification for Large User Population

The main objective of this paper is to present the state-of-the-art of the current biometric (fingerprint and face) technology, lessons learned during the investigative analysis performed to ascertain the benefits of using combined fingerprint and facial technologies, and recommendations for the use of current available fingerprint and face identification technologies for optimum identification performance for applications using large user population. Prior fingerprint and face identification test study results have shown that their identification accuracies are strongly dependent on the image quality of the biometric inputs. Recommended methodologies for ensuring the capture of acceptable quality fingerprint and facial images of subjects are also presented in this paper

An investigation into sustainable materials for reusable cutlery

It is important to look at many different aspects when improving sustainability in the world. Cutlery is one main concern for use in the SUB and many buildings across UBC. Plastic cutlery has been used for a long time due to its low economic costs, but it also generates a lot of waste to landfills. The purpose of this report is to find material that is suitable to replace the plastic cutlery. It will focus on 3 reusable materials for replacing plastic cutlery used in UBC. They are bamboo, stainless steel, and plant starch. Each material is covered in-depth from research through several articles and sources. The three materials are compared by using triple-bottom line assessment. It was found that stainless steel is very durable, but it came with a high price. It also damages the local environment due to the waste it generates at the end of its life cycle. Plant starch is reusable and it is quite cheap; however, it is not as durable compared to bamboo and stainless steel. Furthermore, its plastic-like appearance may cause some concerns from consumers who would question the reusability. Over all, bamboo is the most suitable material because it’s environmentally friendly, economically practical, and socially acceptable. Bamboo is a type of grass, so it does not need to be reseeded after its initial planting. Bamboo also produces 40% more oxygen than trees, which reduce the CO₂ in the air. Bamboo cutlery is reusable and completely biodegradable. Disclaimer: “UBC SEEDS provides students with the opportunity to share the findings of their studies, as well as their opinions, conclusions and recommendations with the UBC community. The reader should bear in mind that this is a student project/report and is not an official document of UBC. Furthermore readers should bear in mind that these reports may not reflect the current status of activities at UBC. We urge you to contact the research persons mentioned in a report or the SEEDS Coordinator about the current status of the subject matter of a project/report.”Applied Science, Faculty ofUnreviewedUndergraduat

Pricing and hedging short sterling options using artificial neural networks

This paper compares the performance of artificial neural networks (ANNs) with that of the modified Black model in both pricing and hedging Short Sterling options. Using high frequency data, standard and hybrid ANNs are trained to generate option prices. The hybrid ANN is significantly superior to both the modified Black model and the standard ANN in pricing call and put options. Hedge ratios for hedging Short Sterling options positions using Short Sterling futures are produced using the standard and hybrid ANN pricing models, the modified Black model, and also standard and hybrid ANNs trained directly on the hedge ratios. The performance of hedge ratios from ANNs directly trained on actual hedge ratios is significantly superior to those based on a pricing model, and to the modified Black model

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licenseBackground: Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide. Methods: A multimethods analysis was performed as part of the GlobalSurg 3 study—a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital. Findings: Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3·85 [95% CI 2·58–5·75]; p<0·0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63·0% vs 82·7%; OR 0·35 [0·23–0·53]; p<0·0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer. Interpretation: Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised. Funding: National Institute for Health and Care Research

Global variation in postoperative mortality and complications after cancer surgery: a multicentre, prospective cohort study in 82 countries

© 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 licenseBackground: 80% of individuals with cancer will require a surgical procedure, yet little comparative data exist on early outcomes in low-income and middle-income countries (LMICs). We compared postoperative outcomes in breast, colorectal, and gastric cancer surgery in hospitals worldwide, focusing on the effect of disease stage and complications on postoperative mortality. Methods: This was a multicentre, international prospective cohort study of consecutive adult patients undergoing surgery for primary breast, colorectal, or gastric cancer requiring a skin incision done under general or neuraxial anaesthesia. The primary outcome was death or major complication within 30 days of surgery. Multilevel logistic regression determined relationships within three-level nested models of patients within hospitals and countries. Hospital-level infrastructure effects were explored with three-way mediation analyses. This study was registered with ClinicalTrials.gov, NCT03471494. Findings: Between April 1, 2018, and Jan 31, 2019, we enrolled 15 958 patients from 428 hospitals in 82 countries (high income 9106 patients, 31 countries; upper-middle income 2721 patients, 23 countries; or lower-middle income 4131 patients, 28 countries). Patients in LMICs presented with more advanced disease compared with patients in high-income countries. 30-day mortality was higher for gastric cancer in low-income or lower-middle-income countries (adjusted odds ratio 3·72, 95% CI 1·70–8·16) and for colorectal cancer in low-income or lower-middle-income countries (4·59, 2·39–8·80) and upper-middle-income countries (2·06, 1·11–3·83). No difference in 30-day mortality was seen in breast cancer. The proportion of patients who died after a major complication was greatest in low-income or lower-middle-income countries (6·15, 3·26–11·59) and upper-middle-income countries (3·89, 2·08–7·29). Postoperative death after complications was partly explained by patient factors (60%) and partly by hospital or country (40%). The absence of consistently available postoperative care facilities was associated with seven to 10 more deaths per 100 major complications in LMICs. Cancer stage alone explained little of the early variation in mortality or postoperative complications. Interpretation: Higher levels of mortality after cancer surgery in LMICs was not fully explained by later presentation of disease. The capacity to rescue patients from surgical complications is a tangible opportunity for meaningful intervention. Early death after cancer surgery might be reduced by policies focusing on strengthening perioperative care systems to detect and intervene in common complications. Funding: National Institute for Health Research Global Health Research Unit