ABSTRACT
The climate in urban centers can differ significantly from the immediate surrounding areas;this can pose health risks to the elderly who have spent much of their lives in urban centers and then move to more rural areas for retirement. Therefore, there is a need to develop educational software applications for the elderly that needs to account for their life experiences aside from physiological restrictions. This research created a connected wireframe for an educational assistant to make the elderly aware of the climate differences between their urban and rural residences. To address the difficulty of recruiting vulnerable subjects, especially during the COVID-19 pandemic, we evaluated our wireframe using a combination of heuristic evaluation and a variation of the Delphi process, an expert consensus-building tool typically used for market forecasting. © ICCE 2022.All rights reserved.
ABSTRACT
As a result of the COVID-19 pandemic, the need for remote computer connection has drastically increased. This need is also anticipated to increase in the future as many institutes allow working remotely. This paper reports on a development of a software called “iCtrl”, which started in late 2020. iCtrl is a desktop remote-control application that allows remote connection to an institute's computer facilities. iCtrl application supports Virtual Network Computing (VNC) connection on both Windows and macOS operating systems. It offers a user-friendly interface to eliminate complicated setup processes. iCtrl has been used for over two years and received positive ratings from undergraduate students in a first-year programming language course and a third-year computer network course. Feedback provided by students suggested a few potential improvements such as cross-platform support and Secure Shell (SSH) connections. This motivated us to design a web-based version for iCtrl in summer 2021 that supported cross-OS platform access, SSH and VNC connection, while providing an industry-leading file management interface design with reference to Google Drive and Microsoft OneDrive. This allowed not only to transfer responsibilities of platform support to the browser developers but also to design a more intuitive interface for the students to upload, retrieve and manage files using the SSH File Transfer Protocol (SFTP). The latest survey noted an 86.2% approval of our application over the traditional methods, and the download count of the application is now 10 times of the old version after we applied engineering practices. © American Society for Engineering Education, 2022.
ABSTRACT
During the COVID-19 pandemic, humanity faced various health problems. One of the most common diseases is pneumonia. The life of every person depends on the correct and effective diagnosis of the disease. Currently, a large number of software applications with elements of artificial intelligence are being developed, which can reduce the time of patient care, improve the methodology and efficiency of disease diagnosis. With our research, we strive to contribute to the development of such software applications, namely, to develop software tools with elements of fuzzy logic. To develop a decision-making system, scales and algorithms in order to assess we considered the prognosis of the severity of community-acquired pneumonia PORT(PSI), CURB/CRB-65 and SMART-COP/SMART-CO. To improve the quality of processing fuzzy production rules of knowledge base, the logic programming language Prolog was used. The created application is planned to be integrated into medical information systems. © 2022 CURRAN-CONFERENCE. All rights reserved.
ABSTRACT
We present in this paper a suite of four software applications that will help a user to learn the basic vocabulary (about 6000 words) of the English language. The software program asks the user to choose a word from a list of other words. The originality of these applications consists mainly in the modality in which the choices for a tested word are selected. The software applications are graphical applications written in Java programming language. Applications can be modified so that the user can learn other foreign languages. They can also be integrated on e-learning platforms. In the context of the COVID pandemic, online learning has grown. © 2022 IEEE.
ABSTRACT
This research paper gives the precise detail about an important way of detection and recognition of human faces using python and importing OpenCV as a main library in the python language. A brief idea of the report contains the ways where in a proposed system to keep on tracking the face of people right from the starting of the execution and continuously detect via the camera which is accessed by an OpenCV package and measure the distance using an algorithm And once if the distance gets decreases or comes less than the proposed limit, an alert message with a sound producing an alarm using the play sound library is given as the output. The practical working of this concept takes place between multiple faces and output will be produced based on the distance among faces, which will be wise enough for the people to get maintained social distancing through facial recognition for the better prevention of COVID-19 in impromptu in real time. This method could be an useful or an advisable one compared to the other several ways of facial recognition for the social distancing. And hence this execution can be utilized or brought out in various new strategies in machineries, smartphones, and also in several software applications. © 2021 IEEE.
ABSTRACT
The rising of technology in the 21st century grows in a way that we never thought of before. The COVID-19 pandemic shifted many organizations in different sizes, specialties, and sectors to work online, resulting in a critical need to secure their software, applications, and web-based applications. Furthermore, Organizations that do not implement security in the Software Development Life Cycle (SDLC) process often discover that their applications suffer from security flaws and security bugs, thus exposing their applications to attacks. Applying security measures to the SDLC will ensure that applications are secure from the early planning stages until release. Penetration testing is an essential security measure and is counted as one of the best security practices applied to applications because it focuses on the technical part of application security. Each kind of application the organization uses, in-house developed applications or on-the-shelf applications, has its method for penetration testing. This paper is a systematic literature review that examines the web application security measures and the penetration testing methods and tools to detect vulnerabilities on web applications. Moreover, it gives a general view of adapting penetration testing as a security approach to the SDLC. © 2021 IEEE.
ABSTRACT
The importance of software applications in organisations and society at large is well established, especially in the post Covid-19 period where IT systems plays an important role in the online mode of business operations and interaction with consumers that is being adopted across the board. Organisations use software applications for many purposes, including to generate revenues by increasing productivity and most importantly ensuring customer satisfaction. Society uses software applications to among others, enhance their day-to-day activities. Some of these software applications are used in life threatening situations, thus raising the need of building quality within these software applications throughout the development processes. The aim of this study is to assess the quality practices used in agile development methodology and how these are applied and measured to ensure that the final product meet the required quality. A quantitative approach was adopted for this research coupled with online survey design using google forms. The results of the study reveals that while some quality testing techniques and metrics are used in agile projects, majority of organisations do not follow a specific quality standard against which their practices are benchmarked. A set of factors are identified as major stumbling blocks that affect quality practices in these environments where emphasise is made on flexibility and fast delivery. Looking at testing component of Agile methodology, the TDD approach is mostly being used which allows testing to start from development by use of unit testing. In fact test packs are being prepare together with requirements analysis so that it will be easier for developer to develop unit tests. Even though the sprint cycle is very short but the use of automated testing ensures quality of software in term of functionality, usability and operability. Copyright © 2021 by Naudé Scribante. Permission granted to IAMOT to publish and use.
ABSTRACT
PURPOSE: To test the association between death and both qualitative and quantitative CT parameters obtained visually and by software in coronavirus disease (COVID-19) early outbreak. METHODS: The study analyzed retrospectively patients underwent chest CT at hospital admission for COVID-19 pneumonia suspicion, between February 21 and March 6, 2020. CT was performed in case of hypoxemia or moderate-to-severe dyspnea. CT scans were analyzed for quantitative and qualitative features obtained visually and by software. Cox proportional hazards regression analysis examined the association between variables and overall survival (OS). Three models were built for stratification of mortality risk: clinical, clinical/visual CT evaluation, and clinical/software-based CT assessment. AUC for each model was used to assess performance in predicting death. RESULTS: The study included 248 patients (70% males, median age 68 years). Death occurred in 78/248 (32%) patients. Visual pneumonia extent > 40% (HR 2.15, 95% CI 1.2-3.85, P = 0.01), %high attenuation area - 700 HU > 35% (HR 2.17, 95% CI 1.2-3.94, P = 0.01), exudative consolidations (HR 2.85-2.93, 95% CI 1.61-5.05/1.66-5.16, P < 0.001), visual CAC score > 1 (HR 2.76-3.32, 95% CI 1.4-5.45/1.71-6.46, P < 0.01/P < 0.001), and CT classified as COVID-19 and other disease (HR 1.92-2.03, 95% CI 1.01-3.67/1.06-3.9, P = 0.04/P = 0.03) were significantly associated with shorter OS. Models including CT parameters (AUC 0.911-0.913, 95% CI 0.873-0.95/0.875-0.952) were better predictors of death as compared to clinical model (AUC 0.869, 95% CI 0.816-0.922; P = 0.04 for both models). CONCLUSIONS: In COVID-19 patients, qualitative and quantitative chest CT parameters obtained visually or by software are predictors of mortality. Predictive models including CT metrics were better predictors of death in comparison to clinical model.