DETECTION OF GRANULATION TISSUE FOR HEALING ASSESSMENT OF CHRONIC ULCERS

Wounds that fail to heal within an expected period develop into ulcers that cause severe pain and expose patients to limb amputation. Ulcer appearance changes gradually as ulcer tissues evolve throughout the healing process. Dermatologists assess the progression of ulcer healing based on visual inspection of ulcer tissues, which is inconsistent and subjective. The ability to measure objectively early stages of ulcer healing is important to improve clinical decisions and enhance the effectiveness of the treatment. Ulcer healing is indicated by the growth of granulation tissue that contains pigment haemoglobin that causes the red colour of the tissue. An approach based on utilising haemoglobin content as an image marker to detect regions of granulation tissue on ulcers surface using colour images of chronic ulcers is investigated in this study. The approach is utilised to develop a system that is able to detect regions of granulation tissue on ulcers surface using colour images of chronic ulcers

Novel Semi-Automatic Method to Optimize Multi-Lamp High Flux Solar Simulators

For multi-lamp high flux solar simulators (HFSS), it is often difficult to obtain a required flux distribution by manipulating the lamp position of multiple lamps at once. Each lamp has three degree of freedom. Thus manual optimization can be tedious for human operators. Thus, this project aims to create a semi-automatic method to determine the optimal location of the lamps to give the required flux distribution. A convolutional neural network is used to develop a mathematical model that performs the above function. At the same time, an automated method to collect data from the HFSS was devised. Furthermore, an in-house algorithm to characterize the irradiance was developed. Since large amount of data was required, an optical simulator called TracePro was used to generate the data for training as well as validation. This project serves as proof of concept of using machine learning to optimize HFSS. In the long term, the proposed methodology is expected to facilitate initial deployment of the HFSS. It will also assist on the dynamic control of reactor conditions i.e. emulating variable overcast or daily sunlight variability

Planning, operation, and design of market-based virtual power plant considering uncertainty

The power systems of today seem inseparable from clean energy sources such as wind turbines (WTs) and photovoltaics (PVs). However, due to their uncertain nature, operational challenges are expected when WT and PV energy is added to the electricity network. It is necessary to introduce new technologies to compensate for the intermittent nature of renewable energy sources (RESs). Therefore, rationally implementing a demand response (DR) program with energy storage systems (ESSs) in a virtual power plant (VPP) environment is recommended as a way forward to minimize the volatile nature of RESs and improve power system reliability. Our proposed approach aims to maximize social welfare (SW) (i.e., maximization of consumer benefits while minimizing energy costs). Our method assesses the impact of the DR program on SW maximization. Two scenarios are examined, one with and one without a DR program. Stochastic programming theory is used to address the optimization problem. The uncertain behavior of WTs, PVs, and load demand is modeled using a scenario-based approach. The correctness of the proposed approach is demonstrated on a 16-bus UK generic distribution system. Our results show that SW and active power dispatch capacity of WT, PV, and ESS are fairly increased using the proposed approach

Trends and Patterns in Artificial Intelligence Research for Oil and Gas Industry: A Bibliometric Review

Purpose: This paper aims to outline a broad-spectrum perspective of the structure of research in artificial intelligence (AI), in the oil and gas industry (OGI) based on bibliometric and distance-based visualisation of similarities (VOS) analysis.   Theoretical framework: The OGI has been one of the major contributors to the world economy. With the increasing energy demand, it has become necessary for the industry to adopt the latest technologies to enhance efficiency, reduce costs, and improve safety. One such technology is AI, which has the potential to revolutionise OGI.   Design/methodology/approach: The paper uses the data from Scopus online database as of April 2023. Based on “key-terms” search results, 251 valid documents were obtained for further analysis using VOS viewer software and Harzing’s Publish or Perish for citation metrics and analysis.   Findings: The finding shows that the Journal of Petroleum Science and Engineering is the field's most relevant journal, with 14 (5.58) published Articles. The People's Republic of China is the most productive country regarding AI research in the OGI. El-Sebakhy's (2009) article is the most cited article, with 113 citations and an average of 8.07 citations per year.   Research, Practical & Social implications: AI could transform OGI. Thus, adopting AI technologies can increase efficiency, reduce costs, and improve safety, also may increase productivity and economic benefits in AI research-intensive countries.   Originality/value: This study provides a comprehensive analysis of the existing AI research in the OGI, utilising bibliometric data and graphical networks

Optimization of the Urban Green Area in Erbil Territory for Sustainable Development

This research paper studies the status and condition of the green areas in the city of Erbil, for this purpose all green areas in the city (763 plots) and all population number according to 12 sectors are collected according to their locations and are analyzed spatially by GIS program (Moran I). The researchers have proved that distribution of green areas is random. Moreover, this distribution is not based on the urban planning basics and its criteria: green area per person (GAPP) and green area to the city ratio (GAR) also not based on the basics of urban planning for two criteria , GAPP is optimized from 9.3 to 14 and GAR optimized from 0.06 to 0.09 while the equilateral tringle adopted as optimum distribution for green area units GAU, for 12 sectors adopted combined standards together and the solution was the population density ratio must be 0.01 or less, to obtain criteria and this must preserved and adhered to the planning and laws and regulations strictly. This method can be applied to the study of the spatial distribution in order to compare it with the distribution of schools, health centers and other services or infrastructures

Exploring the Factors Affecting Online Trust in B2C E-Commerce Transactions in India: an Empirical Study

Purpose: The COVID-19 pandemic has led to a surge in e-commerce as millions of people were forced to stay at home and adopt digital channels for their purchases to avoid crowded supermarkets. It made the whole world look towards e-commerce as a one-stop solution for keeping markets alive. However, it came as an opportunity for digital fraudsters as a huge number of digital frauds were reported during this pandemic. Such incidents raised questions about online trust-related issues. Fake websites, insecure payment mechanisms, data theft, privacy breach, product reliability, etc., are a few of the reasons why many people are still not confident about using e-commerce platforms. When customers cannot physically touch, feel, and see the products, it becomes even more suspicious and raises serious uncertainty about the quality of the promised product and transaction setup in the e-commerce framework.   Design/Methodology/Approch: In this study, primary data was collected through structured questionnaires from e-commerce website users belonging to Generation Z and analyzed using Structural Equation Modelling and Path Analysis in IBM SPSS AMOS version 24.   Findings: Online Security, Online Privacy, and Website appearance were studied and found to have a significant positive impact on online trust. Online trust was also found to be a predictor of purchase intention. Online trust was also found to act as a full mediator between online security and purchase intention, online privacy, and purchase intention, and as a partial mediator between website appearance and purchase intention.   Research, Practical & Social Implications: The cross-sectional nature of this study makes it difficult for making inferences about causal relationships so new studies can adopt and check the utility of a longitudinal approach in this area. Furthermore, the data collected using convenience sampling had all young generation respondents, mostly college/university students. This current study takes only three antecedents of online trust with reference to a young generation; an exploratory study is needed here to find out new possible antecedents of developing online trust. Moreover, the appearance of the website is altogether a vast area to investigate for further development; very limited dimensions of the appearance of e-commerce websites are covered in this study

Nonsurgical Maxillary Expansion in Adults: Report of Two Cases

Correction of maxillary transverse discrepancy requires expansion of palate by combination of orthopedic and orthodontic movements. Isolated maxillary transverse deficiency can be treated either orthodontically or surgically with assisted rapid maxillary expansion (RME). Nonsurgical expansion modalities include rapid maxillary expansion and slow maxillary expansion. Haas popularized the idea of orthodontic palatal expansion in the 1960s, and since then transverse deficiencies have been treated successfully  in children and adolescents. The use of palatal expanders in adults was widely frowned upon and was generally considered to be unsuccessful. Handelman published a clinical review in 1997, proving a nonsurgical expansion in adults was possible