This document discusses organization development in non-industrial settings such as healthcare, school systems, the public sector, and family-owned businesses. Specifically, it focuses on organization development in healthcare, noting trends like the growth of healthcare as an industry, the complexity of the system, and challenges around capacity and connecting different providers. It also discusses opportunities for organization development practice in healthcare around creating effective cultures, human resource systems, job design, and restoring trust among stakeholders.
This document discusses organization development in family-owned businesses. It begins by defining the family business system as consisting of the business, ownership, and family systems. It then outlines some critical issues facing family firms, such as conflicts during generational transitions of leadership and ownership. The document concludes by describing some typical organization development interventions that practitioners can use when working with a family business, such as facilitating family meetings, addressing both business and family systems issues, and building trust throughout the engagement.
This document discusses predicting student performance in higher education using video learning analytics and data mining techniques. The study analyzed data from 772 students' interactions in an LMS, student information system, and mobile video application to predict end-of-semester performance. Eight classification algorithms were tested and random forest accurately predicted successful students 88.3% of the time. Feature selection techniques like genetic search and principle component analysis were also able to further improve performance. The results suggest video learning analytics combined with data mining can help educators identify at-risk students and make decisions to improve student success.
This document discusses predicting student performance in higher education using video learning analytics and data mining techniques. The study analyzed data from 772 students' interactions in an LMS, student information system, and mobile video application to predict end-of-semester performance. Eight classification algorithms were tested and random forest accurately predicted successful students 88.3% of the time. Feature selection techniques like genetic search and principle component analysis were also able to further improve performance. The results suggest video learning analytics combined with data mining can help educators identify at-risk students and improve learning outcomes.
The document describes the development of an online examination system using Java Web technologies. The system provides functions for question management, randomly generating exam papers based on predefined structures, and online testing. It was developed using the JSP Model 1 architecture with the business logic in JSP pages and data stored in a database. Key technologies included using JavaScript on the client side and JSP on the server side to distinguish submission buttons and appropriately process exam questions.
This article summarizes a literature review on e-mentoring programs in higher education from 2009-2019. The review identified 20 high-quality studies that met the inclusion criteria. Key findings include that e-mentoring programs help students succeed academically and develop skills for their careers. However, little research has examined e-mentoring for students in off-site internships. The review establishes a need for more research on effective e-mentoring program design and implementation for internship students.
This document discusses the design and development of an electronic voting system for university management. It analyzes the requirements, designs the system architecture and modules. The key modules include user management, voting themes, options, counting of results. It was developed using .NET and SQL Server. The system allows real-time voting via computers and mobile apps. It aims to improve efficiency over traditional paper voting while ensuring security, flexibility and ease of use.
This document discusses predicting student performance in higher education using video learning analytics and data mining techniques. The study analyzed data from 772 students' interactions in an LMS, student information system, and mobile video application to predict end-of-semester performance. Eight classification algorithms were tested on the data, along with feature selection techniques like genetic search and principle component analysis. The Random Forest algorithm most accurately predicted student performance at 88.3% accuracy using an equal width feature selection method. The results indicate that analyzing interaction data from multiple systems using classification techniques can help predict student outcomes.
This document discusses organization development in non-industrial settings such as healthcare, school systems, the public sector, and family-owned businesses. Specifically, it focuses on organization development in healthcare, noting trends like the growth of healthcare as an industry, the complexity of the system, and challenges around capacity and connecting different providers. It also discusses opportunities for organization development practice in healthcare around creating effective cultures, human resource systems, job design, and restoring trust among stakeholders.
This document discusses organization development in family-owned businesses. It begins by defining the family business system as consisting of the business, ownership, and family systems. It then outlines some critical issues facing family firms, such as conflicts during generational transitions of leadership and ownership. The document concludes by describing some typical organization development interventions that practitioners can use when working with a family business, such as facilitating family meetings, addressing both business and family systems issues, and building trust throughout the engagement.
This document discusses predicting student performance in higher education using video learning analytics and data mining techniques. The study analyzed data from 772 students' interactions in an LMS, student information system, and mobile video application to predict end-of-semester performance. Eight classification algorithms were tested and random forest accurately predicted successful students 88.3% of the time. Feature selection techniques like genetic search and principle component analysis were also able to further improve performance. The results suggest video learning analytics combined with data mining can help educators identify at-risk students and make decisions to improve student success.
This document discusses predicting student performance in higher education using video learning analytics and data mining techniques. The study analyzed data from 772 students' interactions in an LMS, student information system, and mobile video application to predict end-of-semester performance. Eight classification algorithms were tested and random forest accurately predicted successful students 88.3% of the time. Feature selection techniques like genetic search and principle component analysis were also able to further improve performance. The results suggest video learning analytics combined with data mining can help educators identify at-risk students and improve learning outcomes.
The document describes the development of an online examination system using Java Web technologies. The system provides functions for question management, randomly generating exam papers based on predefined structures, and online testing. It was developed using the JSP Model 1 architecture with the business logic in JSP pages and data stored in a database. Key technologies included using JavaScript on the client side and JSP on the server side to distinguish submission buttons and appropriately process exam questions.
This article summarizes a literature review on e-mentoring programs in higher education from 2009-2019. The review identified 20 high-quality studies that met the inclusion criteria. Key findings include that e-mentoring programs help students succeed academically and develop skills for their careers. However, little research has examined e-mentoring for students in off-site internships. The review establishes a need for more research on effective e-mentoring program design and implementation for internship students.
This document discusses the design and development of an electronic voting system for university management. It analyzes the requirements, designs the system architecture and modules. The key modules include user management, voting themes, options, counting of results. It was developed using .NET and SQL Server. The system allows real-time voting via computers and mobile apps. It aims to improve efficiency over traditional paper voting while ensuring security, flexibility and ease of use.
This document discusses predicting student performance in higher education using video learning analytics and data mining techniques. The study analyzed data from 772 students' interactions in an LMS, student information system, and mobile video application to predict end-of-semester performance. Eight classification algorithms were tested on the data, along with feature selection techniques like genetic search and principle component analysis. The Random Forest algorithm most accurately predicted student performance at 88.3% accuracy using an equal width feature selection method. The results indicate that analyzing interaction data from multiple systems using classification techniques can help predict student outcomes.
This document discusses a study that proposes an algorithm called PPP to predict students' performance through their procrastination behaviors using assignment submission data from an online course. The study builds feature vectors from students' submission behaviors, uses clustering to categorize students, and employs classification methods to predict performance. It finds that PPP can successfully predict performance with 96% accuracy, and that linear support vector machines perform best with continuous features while neural networks perform best with categorical features. The predictive power of all methods decreases with more student clusters.
This document reviews the sustainability impacts of online food delivery platforms. It discusses the economic, social, and environmental impacts based on an interdisciplinary review of over 60 sources. Economically, online food delivery provides jobs but is criticized for high commission charges to restaurants and working conditions of delivery people. Socially, it affects consumer-food relationships and public health, as well as traffic. Environmentally, it generates significant waste and has a high carbon footprint. Stakeholders must address negative impacts and promote positive ones to ensure sustainability.
The document proposes a web based college admission system with the following key points:
1. The system aims to automate the entire college admission process which is currently done manually using paper, in order to reduce time and efforts.
2. The system will have different sections for administration, students, office functions like exams, accounts etc. The administrator can manage student accounts and details while various sections can access student information as required.
3. A mobile application will also be developed to provide notifications to users (students and teachers) regarding notices and updates from the college through their smartphones.
The document discusses factors that influence customer satisfaction, revisit intention, and recommendation for Mongolian and global fast food restaurants. It examines how food quality, service quality, atmosphere, and price affect customer satisfaction using surveys of customers in Mongolia and Korea. The results show these four factors positively influence satisfaction, and satisfaction positively influences revisit intention and recommendation. However, the factors' influence depends on whether a customer visits a Mongolian or global fast food chain.
The document discusses a study on students' perspectives of online teaching and learning during the COVID-19 pandemic at Romanian universities. It provides context on universities quickly transitioning to exclusive online learning due to the pandemic. The study examined how the learning process was affected and students' views on using e-learning platforms and their impact on understanding information. The results showed that Romanian universities were unprepared for exclusive online learning. Technical issues were the primary problem reported by students, along with teachers' lack of technical skills and teaching styles not suited for online learning. However, students reported interaction with teachers as the lowest concern. The findings provide implications to help improve universities' e-learning systems.
This document summarizes a 2006 thesis from the University of Wollongong titled "Turning user into first level support in help desk: development of web-based user self-help knowledge management system". The thesis investigates using knowledge management techniques and software agent technology to develop a web-based user self-help system to improve the support process for routine and simple technical inquiries in IT help desks. A survey was conducted to identify inquiries that could be solved by users themselves with sufficient online information. The results also showed that providing online information, training, guidelines and documentation could decrease incoming inquiries to the help desk. A prototype was developed to demonstrate providing solutions to simple and routine inquiries through an ontology and software agents.
The study aimed to determine the levels of kinesthetic, verbal and visual intelligences among mechanical engineering students and examine their relationship with learning styles and academic performance. A questionnaire was administered measuring these three types of intelligences based on Gardner's theory of multiple intelligences. The results showed that 33% of students strongly dominated in kinesthetic intelligence, while 29% were strong in both kinesthetic and visual intelligences. There was a statistically significant correlation found between the three intelligences, learning styles, and academic performance.
This plagiarism scan report from November 2021 found 0% plagiarism and 100% unique content in a 12-word, 69-character sample. The content checked, "System have no qrcode for outsiders but just google fillup forms only", was determined to not be plagiarized.
This document discusses a study that proposes an algorithm called PPP to predict students' performance through their procrastination behaviors using assignment submission data from an online course. The study builds feature vectors from students' submission behaviors, uses clustering to categorize students, and employs classification methods to predict performance. It finds that PPP can successfully predict performance with 96% accuracy, and that linear support vector machines perform best with continuous features while neural networks perform best with categorical features. The predictive power of all methods decreases with more student clusters.
This document reviews the sustainability impacts of online food delivery platforms. It discusses the economic, social, and environmental impacts based on an interdisciplinary review of over 60 sources. Economically, online food delivery provides jobs but is criticized for high commission charges to restaurants and working conditions of delivery people. Socially, it affects consumer-food relationships and public health, as well as traffic. Environmentally, it generates significant waste and has a high carbon footprint. Stakeholders must address negative impacts and promote positive ones to ensure sustainability.
The document proposes a web based college admission system with the following key points:
1. The system aims to automate the entire college admission process which is currently done manually using paper, in order to reduce time and efforts.
2. The system will have different sections for administration, students, office functions like exams, accounts etc. The administrator can manage student accounts and details while various sections can access student information as required.
3. A mobile application will also be developed to provide notifications to users (students and teachers) regarding notices and updates from the college through their smartphones.
The document discusses factors that influence customer satisfaction, revisit intention, and recommendation for Mongolian and global fast food restaurants. It examines how food quality, service quality, atmosphere, and price affect customer satisfaction using surveys of customers in Mongolia and Korea. The results show these four factors positively influence satisfaction, and satisfaction positively influences revisit intention and recommendation. However, the factors' influence depends on whether a customer visits a Mongolian or global fast food chain.
The document discusses a study on students' perspectives of online teaching and learning during the COVID-19 pandemic at Romanian universities. It provides context on universities quickly transitioning to exclusive online learning due to the pandemic. The study examined how the learning process was affected and students' views on using e-learning platforms and their impact on understanding information. The results showed that Romanian universities were unprepared for exclusive online learning. Technical issues were the primary problem reported by students, along with teachers' lack of technical skills and teaching styles not suited for online learning. However, students reported interaction with teachers as the lowest concern. The findings provide implications to help improve universities' e-learning systems.
This document summarizes a 2006 thesis from the University of Wollongong titled "Turning user into first level support in help desk: development of web-based user self-help knowledge management system". The thesis investigates using knowledge management techniques and software agent technology to develop a web-based user self-help system to improve the support process for routine and simple technical inquiries in IT help desks. A survey was conducted to identify inquiries that could be solved by users themselves with sufficient online information. The results also showed that providing online information, training, guidelines and documentation could decrease incoming inquiries to the help desk. A prototype was developed to demonstrate providing solutions to simple and routine inquiries through an ontology and software agents.
The study aimed to determine the levels of kinesthetic, verbal and visual intelligences among mechanical engineering students and examine their relationship with learning styles and academic performance. A questionnaire was administered measuring these three types of intelligences based on Gardner's theory of multiple intelligences. The results showed that 33% of students strongly dominated in kinesthetic intelligence, while 29% were strong in both kinesthetic and visual intelligences. There was a statistically significant correlation found between the three intelligences, learning styles, and academic performance.
This plagiarism scan report from November 2021 found 0% plagiarism and 100% unique content in a 12-word, 69-character sample. The content checked, "System have no qrcode for outsiders but just google fillup forms only", was determined to not be plagiarized.
1. Introduction
Payroll is the process by which a company pays its employees for work done during a
specific time period. A payroll system enables businesses to follow a predefined set of
processes in order to make timely, correct payments in accordance with government
regulations. A payroll system can be manual or computerized, and it can be handled in-
house or outsourced to another provider.
Theoretical Framework
Payroll processing is critical to a company's survival. Inability to pay completely and
on time can lead to a rapid exodus of a company's workforce. However, payroll is more than
just delivering checks on time. Although payroll principles do not occupy academic tomes
with formal theories, companies all over the world use them when developing and
implementing payroll systems.
Some economists argue that payroll taxes have a large and significant impact on
employment and the labor force. A reduction in payroll taxes, for example, relieves
employers' financial burdens and may create incentives for them to hire more employees
with their cost savings. Similarly, lower payroll withholding may encourage employees to
work more hours during a given tax year, increasing industrial output across the board.
Scope
1.The proposed system is for local government unit which uses programming language
JAVA as the front-end and MYSQL as the back-end.
2.Categorizing of employee based on their status. If the employee is contractual or
permanent.
3.Adjusting of salary when the employee gets promoted or demoted.
4.Filtering of payroll report per department.
5.The proposed system has an active or inactive indicator of employee who terminated, end
of contract, resigned or retired.
6.Importing or exporting of attendance report.