Modeling and Analysis of Unmanned Aerial Vehicle System Leveraging Systems Modeling Language (SysML)

The use of unmanned aerial vehicles (UAVs) has seen a significant increase over time in several industries such as defense, healthcare, and agriculture to name a few. Their affordability has made it possible for industries to venture and invest in UAVs for both research and commercial purposes. In spite of their recent popularity; there remain a number of difficulties in the design representation of UAVs, including low image analysis, high cost, and time consumption. In addition, it is challenging to represent systems of systems that require multiple UAVs to work in cooperation, sharing resources, and complementing other assets on the ground or in the air. As a means of compensating for these difficulties; in this study; we use a model-based systems engineering (MBSE) approach, in which standardized diagrams are used to model and design different systems and subsystems of UAVs. SysML is widely used to support the design and analysis of many different kinds of systems and ensures consistency between the design of the system and its documentation through the use of an object-oriented model. In addition, SysML supports the modeling of both hardware and software, which will ease the representation of both the system’s architecture and flow of information. The following paper will follow the Magic Grid methodology to model a UAV system across the SysML four pillars and integration of SysML model with external script-based simulation tools, namely, MATLAB and OpenMDAO. These pillars are expressed within standard diagram views to describe the structural, behavior, requirements, and parametric aspect of the UAV. Finally, the paper will demonstrate how to utilize the simulation capability of the SysML model to verify a functional requirement

Improving social performance through innovative small green businesses: knowledge sharing and green entrepreneurial intention as antecedents

Small businesses are thought to be largely responsible for environmental pollution despite the fact that businesses of all shapes and sizes contribute to this issue. This research explores how important factors such as knowledge sharing (KS) and green entrepreneurial intention (GEI) might help small businesses in Saudi Arabia develop and implement green innovation (GI). It also seeks to determine whether GI is a mediating variable that explains the connection between GEI, KS, and social performance (SP). Accordingly, an online survey was used to collect responses from 284 small entrepreneurs in Saudi Arabia engaged in various types of business activities. The study used partial least squares structural equation modelling for data analysis and hypothesis testing. The results show that GI considerably influences SP while also having a significant link with both GEI and KS. Further, the study reveals that the relationship between GEI, KS, and SP is mediated by GI. The study offers a plethora of suggestions to various stakeholders generally and to Saudi authorities specifically

A Standard Methodology Enabling Execution of Models Described in Sysml Demonstrated in a Model Based Systems Engineering Approach Toward Developing a Space Situational Awareness System Implemented in Cubesats

As systems grow in complexity, Systems Engineers have embraced Model-Based Systems Engineering (MBSE) to tackle this complexity. The Systems Modeling Language (SysML) is the most commonly used language by the Systems Engineers to implement MBSE. SysML can highly express conceptual models, but struggles to demonstrate executable models. In order to perform requirements/behavior verifications, systems engineers/designers mostly use separate simulation tools. Hence, the efficiency of the systems engineering process is often reduced due to the isolated and consecutive use of both SysML modeling tool and other simulation tools, for example defining simulation inputs to each simulation tool separately. Hence, Executable SysML is the next logical step towards achieving true MBSE support for all Systems Engineering activities in the life cycle phases- system requirements, analysis, design, implementation, integration, verification, transition, validation, acceptance testing, training and maintenance. Therefore, various research efforts are being conducted to develop executable SysML Modeling approaches. This thesis paper develops a SysML Executable Modeling Methodology (SEMM), which is demonstrated by modeling a CubeSat based Space Situational Awareness (SSA) system in SysML. The SysML SSA-CubeSat System model is made executable by integrating with Commercial-Off-The-Shelf (COTS) simulation software, namely - Systems Tool Kit (STK) and MATLAB, following the approaches defined in the SEMM

Modeling and Analysis of Unmanned Aerial Vehicle System Leveraging Systems Modeling Language (SysML)

The use of unmanned aerial vehicles (UAVs) has seen a significant increase over time in several industries such as defense, healthcare, and agriculture to name a few. Their affordability has made it possible for industries to venture and invest in UAVs for both research and commercial purposes. In spite of their recent popularity; there remain a number of difficulties in the design representation of UAVs, including low image analysis, high cost, and time consumption. In addition, it is challenging to represent systems of systems that require multiple UAVs to work in cooperation, sharing resources, and complementing other assets on the ground or in the air. As a means of compensating for these difficulties; in this study; we use a model-based systems engineering (MBSE) approach, in which standardized diagrams are used to model and design different systems and subsystems of UAVs. SysML is widely used to support the design and analysis of many different kinds of systems and ensures consistency between the design of the system and its documentation through the use of an object-oriented model. In addition, SysML supports the modeling of both hardware and software, which will ease the representation of both the system’s architecture and flow of information. The following paper will follow the Magic Grid methodology to model a UAV system across the SysML four pillars and integration of SysML model with external script-based simulation tools, namely, MATLAB and OpenMDAO. These pillars are expressed within standard diagram views to describe the structural, behavior, requirements, and parametric aspect of the UAV. Finally, the paper will demonstrate how to utilize the simulation capability of the SysML model to verify a functional requirement

Impact of timing on wound dressing removal after caesarean delivery: a multicentre, randomised controlled trial

We compared wound dressing removal at 24 hours versus 48 hours following low-risk caesarean deliveries. This multicentre, randomised, controlled study included patients 18−44 years of age with low-risk term, singleton pregnancies. The randomisation was done weekly. Scheduled caesarean deliveries without labour were included. For comparison, the Additional treatment, Serous discharge, Erythema, Purulent exudate, Separation of deep tissues, Isolation of bacteria, Stay in hospital > 14 days (ASEPSIS) score for wound healing assessment was modified. The absolute scores were obtained based on a one-day reading rather than the five-day reading used in ASEPSIS. Zero (“0”) was assigned as a complete healing. Higher scores were associated with more severe disruption of healing. The patients were enrolled between March 2015 and February 2017. The demographics were not statistically different. The wound scoring was similar in the groups at discharge and first-week evaluation. At the six weeks post-surgery, the wound scoring was significantly less in the 48-hour (3.9%) versus the 24-hour group (9%; p = .002). Dressing removal at 48 hours had a lower scoring in the low-risk population with scheduled caesarean deliveries.IMPACT STATEMENT What is already known on this subject? Surgical dressings are used to provide suitable conditions to heal caesarean incisions. There has been a limited number of studies on the evaluation of ideal timing on wound dressing removal after a caesarean delivery. These studies concluded there are no increased wound complications with removal at six hours versus 24 hours or within or beyond 48 hours after surgery. What do the results of this study add? The postoperative removal of the wound dressing at 48 hours had a lower wound score at six weeks than the removal at 24 hours for women with uncomplicated scheduled caesarean deliveries. What are the implications of these findings for clinical practice and/or further research? Early discharge after caesarean delivery is becoming more common. Dressing removal at 24 hours versus 48 hours becomes more crucial and needs to be clarified. Besides, high-risk populations, different skin closure techniques, and patients in labour should be addressed separately

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

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