Exam Conduction and Proctoring System Using Face Detection

The Online Examination Portal is a web application for taking an online test productively along with face recognition capabilities to perform live proctoring, and there is no time wasted for checking the paper. This report will incorporate all highlights and procedures which are required to develop this portal. This document incorporates details about the objective of the system, approximately targets of the system, system scope confinement, essential system requirements, group advancement, likely venture risks, schedule of the deployment, and finally observing and reporting mechanisms for the whole system. Online Examination Conducting Portal is exceptionally useful for Instructive Institute's to prepare a complete exam, conduct proctoring to prevent misconduct, secure the time that will take to check the paper, and plan check sheets. Online Examination Portal will help the Institutes to test understudies and develop their abilities. But the impediments for the Online Exam systems, it takes more time when the user prepares the exam at the primary time for utilization. To conduct the exam we require the number of computers with the same number of students. With the successful use of the Examination Portal, the facilitator can utilize this system to create the tests as their requirements and we can get accurate results and save time once deployed.

Internet of Things Monitoring System of a Modeled Cleanroom

The development of a cleanroom monitoring system needs more concentrated consideration consistently. There is a challenge to prove that the cleanroom operates following the specifications, in other words, users do not see the software error, they see failures in execution. This paper aims to design a smart monitoring system to monitor important parameters inside the cleanroom, i.e. temperature, humidity, and pressure to produce a good quality of work or experiment inside the cleanroom. The observing framework utilizes Arduino Mega as a microcontroller, ESP 8266 Wi-Fi module, DHT 11 as an integrated temperature and humidity sensor, HX710B as a pressure sensor, and Blynk application as a monitoring system to record and show information including provide fault notification. The project is tested on a modeled cleanroom to monitor important parameters via smartphone anytime and anywhere. From the experimental results, the Cleanroom IoT Monitoring System successfully read all parameters based on the system requirements and displays data of parameters in real-time and stored historical data. This system is also successful to provide failures notification of humidity, temperature, and pressure in real-time if any of the parameters are out of range from the system requirements. Lastly, users can monitor the condition of the cleanroom anytime and anywhere including receiving real-time failures notifications. This concept can avoid or reduce cleanroom working out of the criteria that can cause testing or experiment inside the cleanroom to be inaccurate. By observing and controlling the prerequisite development for IoT monitoring systems, great nature and better quality of performance of operational cleanrooms can be delivered.

Primary preservice teachers' perspectives of their literacy mentoring experiences during professional placement

PurposeBeing literate can change the lives of Australian students. Therefore, graduating effective teachers of literacy is an imperative for Australian schools. Professional experience provides an opportunity for preservice teachers to refine their skills for teaching literacy under the guidance of a mentor teacher. This study investigates from the perspective of preservice teachers, the attributes and practices primary mentor teachers demonstrate when mentoring literacy teaching during professional experience.Design/methodology/approachThis investigation utilised survey design to gather data from primary preservice teachers (n = 402) from seven Australian universities. The 34 survey items were underpinned by the Five Factor Model of Mentoring and literacy practices prescribed by the Australian curriculum. Preservice teachers self-reported their responses about their literacy mentoring experiences on a five-point Likert scale. The Five Factor Model of Mentoring provided a framework to analyse and present the data using descriptive statistics.FindingsFindings revealed 70% or more of preservice teachers agreed or strongly agreed mentor teachers had the personal attributes, shared the pedagogical knowledge, modelled best practice and provided feedback for effective literacy teaching. Conversely, only 58.7% of the participants reported their mentor teachers shared the system requirements for effective literacy teaching.Research limitations/implicationsThe preservice teachers self-reported their experiences, and although this may be their experience, it does not necessarily mean the mentor teachers did not demonstrate the attributes and practices reported, it may mean they were not identified by the preservice teachers. While there were 402 participants in this study, the viewpoints of these preservice teachers' may or may not be indicative of the entire population of preservice teachers across Australia. This study included primary preservice teachers, so the experiences of secondary and early childhood teachers have not been reported. An extended study would include secondary and early childhood contexts.Practical implicationsThis research highlighted that not all mentor teachers shared the system requirements for literacy teaching with their mentee. This finding prompts a need to undertake further research to investigate the confidence of mentor teachers in their own ability to teach literacy in the primary school. Teaching literacy is complex, and the curriculum is continually evolving. Providing professional learning in teaching literacy will position mentor teachers to better support preservice teachers during professional experience. Ultimately, the goal is to sustain high quality literacy teaching in schools to promote positive outcomes for all Australian school students.Originality/valueWhile the role of mentor teacher is well recognised, there is a dearth of research that explores the mentoring of literacy during professional experience. The preservice teachers in this study self-reported inconsistencies in mentor teachers' attributes and practices for mentoring literacy prompting a need for further professional learning in this vital learning area.

PERTEKMA Financial Reporting Tool

A financial management system is essential for any organization to manage its cash flow and keep track of its spending and earnings. Currently, our faculty-student organization, Persatuan Teknologi Maklumat (PERTEKMA), still uses multiple Excel spreadsheets to log in financial records and depend on physical ledgers printed from the Excel sheet to keep track of its accounts. This project aims to develop a web-based system that keeps track of the PERTEKMA association's revenue and spending and prevents inconsistencies between different ledgers such as activity and kiosk ledgers maintained by various executive committees (Exco) members of PERTEKMA. The system's targeted users are PERTEKMA Exco members and the lecturers responsible for supervising PERTEKMA. The methodology used to develop the proposed project is the Rapid Application Development (RAD) model. An interview was carried out with two treasurers in PERTEKMA to obtain the requirements, and their suggestions were used to develop and design the proposed system. In addition, an interview session was carried out with two PERTEKMA advisors to collect the system requirements to design the system. The system developed aims to replace the current approach to managing financial records through a centralized online platform.

New goal-oriented requirements extraction framework for e-health services: a case study of diagnostic testing during the COVID-19 outbreak

PurposeThis paper aims to introduce the goal-oriented requirements extraction approach (GOREA). It is an elicitation approach that uses, specifically, healthcare business goals to derive the requirements of e-health system to be developed.Design/methodology/approachGOREA consists of two major phases: (1) modelling e-health business requirements phase and (2) modelling e-health information technology (IT) and systems requirements phase. The modelling e-health business requirements phase is divided into two main stages: (1) model e-health business strategy stage and (2) model e-health business environment stage. The modelling e-health IT and systems requirements phase illustrates the process of obtaining requirements of e-health system from the organizational goals that are determined in the previous phase. It consists of four main steps that deal with business goals of e-health system: (1) modelling e-health business process (BP) step; (2) modelling e-health business goals step; (3) analysing e-health business goals step; and (4) eliciting e-health system requirements step. A case study based on the basic operations and services in hospital emergency unit for checking patient against COVID-19 virus and taking its diagnostic testing has been set and used to examine the validity of the proposed approach by achieving the conformance of the developed system to the business goals.FindingsThe results indicate that (1) the proposed GOREA has a positive influence on the system implementation according to e-health business expectations; and (2) it can successfully fulfil the need of e-health business in order to save the citizens life by checking them against COVID-19 virus.Research limitations/implicationsThe proposed approach has some limitations. For example, it is only validated using one e-health business goal and thus it has to be authenticated with different e-health business goals in order to address different e-health problems.Originality/valueMany e-health projects and innovations are not established based on robust system requirements engineering phase. In order to ensure the success delivery of e-health services, all characteristics of e-health systems and applications must be understood in terms of technological perspectives as well as the all system requirements.

Automatic Generation Mechanism of Cause-Effect Graph with Informal Requirement Specification Based on the Korean Language

In requirement engineering, an important issue is how to transform and tailor the informal system requirements of users or customers into more structured specification documents, which are then used by the software developers. In addition, it is both challenging and necessary to redefine and analyze, from ill-defined or unknown requirements, specifications correctly and automatically generate test cases with them. There are few kinds of research in Korea for automatically reducing requirement complexity and developing test cases of the Korean language-based requirement specifications. Why do we need requirement simplification? Requirement complexity causes analyzers less readability and low understandability. To do this, we propose the automatic cause-effect generation via a requirement simplification mechanism of informal requirement specifications with the Korean language, which works the following procedures: (1) the automatic simplification of informal requirement sentences, (2) the generation of Condition/Conjunction/Clause Tree (C3Tree) Model, (3) and the Cause-effect generation.

Opening up safely: public health system requirements for ongoing COVID-19 management based on evaluation of Australia's surveillance system performance

Background Ongoing management of COVID-19 requires an evidence-based understanding of the performance of public health measures to date, and application of this evidence to evolving response objectives. This paper aims to define system requirements for COVID-19 management under future transmission and response scenarios, based on surveillance system performance to date. Methods From 1st November 2020 to 30th June 2021 community transmission was eliminated in Australia, allowing investigation of system performance in detecting novel outbreaks, including against variants of concern (VoCs). We characterised surveillance systems in place from peer-reviewed and publicly available data, analysed the epidemiological characteristics of novel outbreaks over this period, and assessed surveillance system sensitivity and timeliness in outbreak detection. These findings were integrated with analysis of other critical COVID-19 public health measures to establish requirements for future COVID-19 management. Findings Australia reported 25 epidemiologically distinct outbreaks and 5 distinct clusters of cases in the study period, all linked through genomic sequencing to breaches in quarantine facilities housing international travellers. Most (21/30, 70%) were detected through testing of those with acute respiratory illness in the community, and 9 through quarantine screening. For the 21 detected in the community, the testing rate (percent of the total State population tested in the week preceding detection) was 2.07% on average, was higher for those detected while prior outbreaks were ongoing. For 17/30 with data, the delay from the primary case to detection of the index case was, on average 4.9 days, with 10 of the 17 outbreaks detected within 5 days and 3 detected after > 7days. One outbreak was preceded by an unexpected positive wastewater detection. Of the 24 outbreaks in 2021, 20 had publicly available sequencing data, all of which were VoCs. Surveillance for future VoCs using a similar strategy to that used for detecting SARS-CoV-2 to date would necessitate a 100-1,000-fold increase in capacity for genomic sequencing. Interpretation Australia's surveillance systems performed well in detecting novel introduction of SARS- CoV-2 in a period when community transmission was eliminated, introductions were infrequent and case numbers were low. Detection relied on community surveillance in symptomatic members of the general population and quarantine screening, supported by comprehensive genomic sequencing. Once vaccine coverage is maximised, the priority for future COVID-19 control will shift to detection of SARS-CoV-2 VoCs associated with increased severity of disease in the vaccinated and vaccine ineligible. This will require ongoing investment in maintaining surveillance systems and testing of all international arrivals, alongside greatly increased genomic sequencing capacity. Other essential requirements for managing VoCs are maintaining outbreak response capacity and developing capacity to rapidly engineer, manufacture, and distribute variant vaccines at scale. The most important factor in management of COVID-19 now and into the future will continue to be how effectively governments support all sectors of the community to engage in control measures.

E-Government Information Systems (IS) Project Failure in Developing Countries: Lessons from the Literature

E-government information systems (IS) projects experience numerous challenges that can lead to total or partial failure. The project failure factors have been identified and studied by numerous researchers, but the root causes of such failures are not well-articulated. In this study, literature on e-government IS project failures in developing-world contexts is reviewed through the application of qualitative meta-synthesis, design–reality gap analysis, and root cause analysis. In the process, 18 causal factors and 181 root causes are identified as responsible for e-government IS project failures. The most prevalent of the 18 causal factors are found to be inadequate system requirements engineering (with 22 root causes), inadequate project management (19 root causes), and missing or incomplete features (16 root causes). These findings can be of use to future researchers, policymakers, and practitioners seeking to identify methods of avoiding e-government IS failures, particularly in developing-world contexts.