scholarly journals Enhancing Academic Advising In Credit Hours System Using Dss

2021 ◽  
Vol 6 (2) ◽  
pp. 97-110
Author(s):  
Alaa Salah ElDin Ghoneim ◽  
◽  
Salah ElDin Ismail Salah ElDin ◽  
Mohamed Sameh Hassanein ◽  
◽  
...  
Keyword(s):  
Decision Support ◽  
Academic Advising ◽  
Support System ◽  
Vital Role ◽  
Graduation Requirements ◽  
Data Preparation ◽  
Academic Advisor ◽  
Credit Hours ◽  
Data Layer ◽  
Preparation Layer

Academic advising plays a vital role in achieving higher educational institution’s purposes. Academic advising is a process where an academic advisor decides to select a certain number of courses for a student to register in each semester to fulfil the graduation requirements. This paper presents an Academic Advising Decision Support System (AADSS) to enhance advisors make better decisions regarding their students’ cases. AADSS framework divided into four layers, data preparation layer, data layer, processing layer and decision layer. The testing results from those participating academic advisors and students considered are that AADSS beneficial in enhancing their decision for selecting courses.

Design of a Decision Support System for a Home Telehealth Application

2013 ◽  
Vol 4 (3) ◽  
pp. 68-79 ◽  
Author(s):  
Mas S. Mohktar ◽  
Kezhang Lin ◽  
Stephen J. Redmond ◽  
Jim Basilakis ◽  
Nigel H. Lovell
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Open Source Software ◽  
Business Processes ◽  
Rule Engine ◽  
Clinical Support ◽  
Tier System ◽  
Home Telehealth ◽  
Data Layer

A decision support system (DSS) that has been designed to manage patients using a home telehealth system is presented. The DSS has been developed to assist home telehealth clinical support staff with their workload, and to provide more effective communication between multiple home telehealth users. The three-tier system architecture that consists of a data layer; a business logic layer; and a front-end layer employs business processes and uses a rule engine for its logic and knowledge base. This paper discusses the design considerations involved in the construction of a DSS for the purpose of home telehealth, and illustrates how it may be developed using entirely open source software.

GIS-Based Decision Support System for Village Level

2018 ◽  
pp. 275-295
Author(s):  
Subbu Lakshmi Esakki Pandian ◽  
Kiran Yarrakula ◽  
Probal Chaudhury
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Spatial Data ◽  
Rural Areas ◽  
Vital Role ◽  
Population Total ◽  
Rural Sector ◽  
Male And Female ◽  
Village Level

Decision support system (DSS) plays a vital role especially in rural areas to develop rural sector for sustainable development and socio-economic uplifting of the country. To make appropriate decisions and to develop village economy, decision support system is useful for the mandal revenue officer, collector, Surpanch, and different administrators. It deals both spatial and non-spatial data at village level and comprises various ancillary information including mandal maps and village-wise information of Anantapur and Kadapa districts of Andhra Pradesh such as number of houses, male and female, SC/ST/OBC/general (or) OC population, literate and illiterate population, total working and non-working population. Datasets are collected from district collector office, mandal revenue officer (MRO) and inserted in GIS database. This chapter makes an attempt to build features of various decisions at Anantapur and Kadapa districts by integrating various layers of information at village level.

A Decision Support System for Prescriptive Academic Advising

2002 ◽  
pp. 263-284 ◽  
Author(s):  
Louis A. Le Blanc ◽  
Conway T. Rucks ◽  
W. Scott Murray
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Academic Advising ◽  
Support System ◽  
Database Management System ◽  
System A ◽  
Computer Knowledge ◽  
Implementation Time ◽  
College Of Business ◽  
Career Options

A decision support system (DSS) was constructed to assist the academic advising staff of a college of business. The microcomputer-based system identifies any remaining unsatisfied degree program requirements, selects courses in which the student can enroll and then prioritizes them. Advisors are then able to spend time on more substantive or developmental advising issues, such as choice of electives, career options and life career goals. Using this system, a student with a minimum of computer knowledge can obtain an optimized course listing without the assistance of a human advisor in less than five minutes. A high-end spreadsheet (i.e., DSS generator) permits a workable and effective academic advising DSS. The database is the most significant part of this DSS. And, since the modeling component is difficult to separate from the structure of the data itself, a database management system might be a better choice as the DSS generator. This platform would provide a more flexible user interface as well as superior data handling capability but at some sacrifice in cost and implementation time.

Application of Multi-Dimensional Analysis Technology in Telecom Industry

2011 ◽  
Vol 219-220 ◽  
pp. 643-647
Author(s):  
Li Yong Chen ◽  
Xiu Ye Yin
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Dimensional Analysis ◽  
Support System ◽  
Rapid Development ◽  
Vital Role ◽  
The World ◽  
Telecom Industry ◽  
The Right ◽  
Leading Enterprises

With the rapid development of China's telecom industry, the management of domestic enterprises are constantly changing. Operate method was closed to internationalization constantly. In this process, the technology of OLAP plays a very vital role for the development of enterprises. China's telecom industry should depend on the technology of OLAP to get an efficient decision support system to make an accurate in time efficient decision if they want to survive in the world keen competition, and then leading enterprises moving in the right direction. This paper introduced Multi-dimensional analysis technology, Illustrates the application of drilling and rotation Combined with concrete examples. Hope to provide some help for the development of enterprises, promote the rapid development of China's telecom industry through this paper.

GIS-Based Decision Support System for Village Level

2019 ◽  
pp. 1384-1402
Author(s):  
Subbu Lakshmi Esakki Pandian ◽  
Kiran Yarrakula ◽  
Probal Chaudhury
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Spatial Data ◽  
Rural Areas ◽  
Vital Role ◽  
Population Total ◽  
Rural Sector ◽  
Male And Female ◽  
Village Level

Decision support system (DSS) plays a vital role especially in rural areas to develop rural sector for sustainable development and socio-economic uplifting of the country. To make appropriate decisions and to develop village economy, decision support system is useful for the mandal revenue officer, collector, Surpanch, and different administrators. It deals both spatial and non-spatial data at village level and comprises various ancillary information including mandal maps and village-wise information of Anantapur and Kadapa districts of Andhra Pradesh such as number of houses, male and female, SC/ST/OBC/general (or) OC population, literate and illiterate population, total working and non-working population. Datasets are collected from district collector office, mandal revenue officer (MRO) and inserted in GIS database. This chapter makes an attempt to build features of various decisions at Anantapur and Kadapa districts by integrating various layers of information at village level.

scholarly journals Decision Support System for Blockage Management in Fire Service

2014 ◽  
Vol 37 (1) ◽  
pp. 107-123 ◽  
Author(s):  
Adam Krasuski ◽  
Karol Kreński
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Language Processing ◽  
Support System ◽  
Probabilistic Models ◽  
Fire Service ◽  
Data Preparation ◽  
Fire Stations ◽  
Two Phases ◽  
In Fire

Abstract In this article we present the foundations of a decision support system for blockage management in Fire Service. Blockage refers to the situation when all fire units are out and a new incident occurs. The approach is based on two phases: off-line data preparation and online blockage estimation. The off-line phase consists of methods from data mining and natural language processing and results in semantically coherent information granules. The online phase is about building the probabilistic models that estimate the block-age probability based on these granules. Finally, the selected classifier judges whether a blockage can occur and whether the resources from neighbour fire stations should be asked for assistance.

scholarly journals A Decision Support System for Undecided and Exploratory Students

2021 ◽  
Vol 15 (1) ◽  
pp. 1
Author(s):  
Sobitha Samaranayake ◽  
Athula D. A. Gunawardena ◽  
Robert Meyer
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Graduation Requirements ◽  
Design And Implementation ◽  
Static Data ◽  
Visualization Tools ◽  
Program Costs ◽  
Undeclared Students ◽  
Personal Interests

Choosing a major can be a difficult choice for undeclared students, depending on personal interests, job markets, program costs, and the complexity of graduation requirements. The current procedure for exploring possible majors/minors involves a tedious and time-consuming exploration of static data presented in a convoluted format. This work considers the complexity of degree requirements and presents the design and implementation of an efficient decision support system (DSS) for exploring majors and/or minors. The DSS presents a tool that enables college students to map their already completed courses to degree requirements and then view the majors/minors that yield the shortest path for graduation. Secondly, the DSS system provides data visualization tools to assist students in selecting courses that satisfy the remaining requirements of a selected major/minor.

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