A Government Decision Analytics Framework Based on Citizen Opinion

This ongoing research aims to develop a Government Decision Support Framework that employs citizen opinions and sentiments to predict the level of acceptance of newly proposed policies. The system relies on a knowledge base of citizen opinions and an Ontological Model comprising aspects and related terms of different policy domains as an input and a Bayesian predictive procedure. The work proceeds in four basic steps. The first step involves developing domain models comprising aspects for different policy domains in government and automatically acquiring semantically related terms for these aspects from associated policy documents. The second step involves computing citizen sentiments and opinions for the different policy aspects. The third involves updating the ontology with the computed sentiments and the last step involves employing a Bayesian Predictive Process to predict likely citizen opinion for a new proposal (policy) based on information available in the ontology. We provide some background to this work, describe our approach in some detail and discuss the progress mad

A predictive government decision based on citizen opinions - tools & results

Research on citizen satisfaction with respect to public policies has significant public and political value. Politicians are generally seeking effective public policies that favourably impacts citizens’ satisfaction. Citizen satisfaction index is a plausible mechanism for public policy makers to monitor and evaluate the public policies. While surveys on citizen satisfaction are common among agile and progressive public administration and governments, automating the computation of citizen's’ satisfaction is challenging. Given that surveys and evaluations related to citizen satisfaction are retrospective, remedial actions when necessary are always somewhat late. We describe in this poster a predictive analytics framework for citizen satisfaction with respect to public policy based on the previous citizen sentiments past related policies

A Utilization-based Genetic Algorithm for Solving the University Timetabling Problem (UGA)

Building university timetables is a complex process that considers varying types of constraints and objectives from one institution to another. The problem solved in this paper is a real one featuring a number of hard and soft constraints that are not very conventional. The pursued objective is also novel and considers maximizing resource utilization. This paper introduces a genetic algorithm that uses some heuristics to generate an initial population of feasible good quality timetables. The algorithm uses a simple weighted sum formula to respect professors’ preferences and handle conflicts. In order to reduce waste, a crossover type focusing on the utilization rates of learning spaces is introduced. A targeted mutation operator that uses a local search heuristic is also employed. The algorithm applies a composite fitness function that considers space utilization, gaps between events and a maximum number of lectures per day. A large dataset with real data from the Faculty of Commerce, Alexandria University in Egypt was used to test the contributed algorithm. The algorithm was also tested against two difficult benchmark problems from the literature. Testing proved that the developed algorithm is an effective tool for managing timetables and resources in universities. It performed remarkedly well on the large datasets of the two benchmark problems and it also respected more constraints than those stated in the initial problem statement of the two benchmark datasets

An information visibility-based university timetabling for efficient use of learning spaces (IVUT)

Academic institutions have limited resources that need judicious management. Building university timetables is a complex process that considers a big number of resources. Sometimes, allocating events takes place without seeing the full picture of the available resources. This leads to inefficiencies in utilization, especially with the absence of reevaluation techniques for timetables. Spaces could be underutilized or over-utilized but kept obscure due to lack of timely information. Providing updated information about spaces occupancy and utilization is important to construct resilient and adaptive timetables. Information visibility triggers re-scheduling and reallocation decisions. This paper introduces a new approach to construct resilient university timetables using genetic algorithms and data capturing technologies. The contributed approach adds a new dimension to solving the NP-hard timetabling and space allocation problems. It enables handling dynamic attendance patterns. By conducting periodical timetable assessments, appropriate spaces can be reallocated to suit the number of attendees in each event. This helps avoiding chaotic consequences resulting from space over-occupation as well as preventing the inability to use a space under the impression that is fully utilized. The developed solution relies on the use of RFID technology to enable information visibility. A case study was conducted at the Faculty of Commerce, Alexandria University, and the results are presented. Compared to current practices, the new concept proves to be an effective tool for managing timetables and resources in universities

The Influence of SCADA Information Technology System Application on Improving Performance Efficiency (Field study on the Ministry of Electricity and Oil of the Kurdistan Region of Iraq)

This paper aims to show SCADA's (Supervisory Control and Data Acquisition) influence on performance efficiency in Iraqi Kurdistan Region’s Electricity and Natural Resources ministries. SCADA system is a technological tool that improves performance efficiency. Supervisory Control and Data Acquisition can be prescribed as a monitoring plan. The execution of the control strategy and the decided actions constitute a process control loop. This research studies the relationship between SCADA as an independent variable and performance efficiency as a dependent variable. Hence, to answer the research questions and test the hypotheses, the study has mainly adopted quantitative research with a questionnaire to collect primary data. 366 employees working in the ministries in different positions, as a sample, have completed this questionnaire. This study recommends additional training on SCADA for employees to guarantee its sustainable use and system integration in all work details to grant the ministries flexibility in making decisions and enhancing performance