Assessing Students’ Learning in MIS using Concept Mapping

The work described here draws on the emerging need to internationalize the curriculum in higher education. The focus of the study is on the evaluation of a Management Information Systems (MIS) Module, and the specification of appropriate course of action that would support its internationalization. To realize this goal it is essential to identify the possible learning needs of the two dominant cultural groups that compose the university student population in Britain, specifically European and Asian (UUK, 2005). Identification of knowledge patterns among these cultural groups is achieved through the application of a concept mapping technique. The main research questions addressed are: (1) How to internationalize the MIS module’s content and teaching methods to provide for students from different cultural backgrounds? (2) What are the main gaps in knowledge of students in MIS? The paper presents the results of this study and proposes actions needed to streamline the current teaching methods towards improving the quality of the students’ learning experience

V2X communication coverage analysis for connected vehicles in intelligent transportation networks: A case study for the city of Xanthi, Greece

Intelligent transportation systems (ITS) have been developed to improve traffic flow, efficiency, and safety in transportation. Technological advancements in communication such as the Vehicle-to-Everything (V2X), Vehicle-to-Vehicle (V2V) and Vehicle-to Infrastructure (V2I) enable the real-time exchange of information between vehicles and other entities on the road network, and thus play a significant role in their safety and efficiency. This paper presents a simulation study that models V2V and V2I communication to identify the most suitable range of data transmission between vehicles and infrastructure. The provincial city of Xanthi, Greece is used as a cases study, and the goal is to evaluate whether the proposed placement of Road Side Unit (RSU) provided adequate communication coverage on the city's road network. An analysis through different scenarios identified improvements in traffic management, driving behavior and environmental conditions under different RSU coverage. The results highlight that the communication range of 400 meters is the most adequate option for optimum traffic management in the city of Xanthi.Comment: Wireless World Research Forum, Meeting 49, March 28th-30th 2023, Pozna\'n, Poland, Towards sustainable and automated communication

Human Requirements Validation for Complex Systems Design

AbstractOne of the most critical phases in complex systems design is the requirements engineering process. During this phase, system designers need to accurately elicit, model and validate the desired system based on user requirements. Smart driver assistive technologies (SDAT) belong to a class of complex systems that are used to alleviate accident risk by improving situation awareness, reducing driver workload or enhancing driver attentiveness. Such systems aim to draw drivers’ attention on critical information cues that improve decision making. Discovering the requirements for such systems necessitates a holistic approach that addresses not only functional and non-functional aspects but also the human requirements such as drivers’ situation awareness and workload. This work describes a simulation-based user requirements discovery method. It utilizes the benefits of a modular virtual reality simulator to model driving conditions to discover user needs that subsequently inform the design of prototype SDATs that exploit the augmented reality method. Herein, we illustrate the development of the simulator, the elicitation of user needs through an experiment and the prototype SDAT designs using UNITY game engine

Nonfunctional Requirements Validation-A Game Theoretic Approach

Abstract-Network Security requirements have recently gained widespread attention in the requirements engineering community. Despite this, it is not yet clear how to systematically validate these requirements given the complexity and uncertainty characterizing modern networks. Traditionally, network security requirements specification has been the results of a reactive process. This however, limited the immunity property of the software systems that depended on these networks. Security requirements specification prerequisite a proactive approach. Networks' infrastructure is constantly under attack by hackers and malicious software that aim to break into computers. To combat these threats, network designers need sophisticated security validation techniques that will guarantee the minimum level of security for their future networks. To that end, this paper presents a game-theoretic approach to security requirements validation. An introduction to game theory is presented along with a case study that demonstrates the application of the approach in a hypothetical network topology

Road safety assessment using Bayesian belief networks and agent-based simulation

Road safety performance constitutes an important issue in road traffic management. Systems have been developed for assessing safety performance; however, these provide only historical or retrospective analyses. Effective safety management requires a prospective viewpoint. The main goal of this research is the integration of microscopic road network simulation with Bayesian Belief Network (BBN) technology for improved prediction of road accident risk. The paper describes the method along with the current state of the development of an accident prediction system. Preliminary validation studies of the road network simulation and BBN models are illustrated.

Extracting Traffic Safety Knowledge from Historical Accident Data

This paper presents a method and a tool for analyzing historical traffic accident records using data mining techniques for the extraction of valuable knowledge for traffic safety management. The knowledge is dis-tilled using spatio-temporal analysis of historical accidents records. Raw accident data, obtained from Police records, underwent pre-processing and subsequently integrated with secondary traffic-flow data from a mesoscopic simulation. Clustering analysis was performed with self-organizing maps (SOM) to identify accident black spots on the road network and visualizethis on a map. Distilled knowledge is used to develop a prototype mobile application to warn drivers of accident risk in real tim

Towards a user-centred road safety management method based on road traffic simulation

One of the most important gaps in road safety management practises is the lack of mature methods for estimating reliability. Road safety performance assessment systems have been developed; however, these provide only historical or retrospective analyses. Effective safety management requires a prospective viewpoint. The main goal of this research is to assist in reducing accident rates in Cyprus by providing ample time to the authorities to react to high risk situations through a safety prediction early warning system. This ultimately will prevent accidents from occurring which subsequently could save lives. Traditional approaches focuses solidly on empirical data concerning road network dynamic properties, despite the fact that the most vulnerable component of the system is the human element. This paper described the integration of agent-based simulation with Bayesian Belief Networks (BBN) for improved quantification of accident probability. The BBN is developed using multidisciplinary influences

Traffic accidents analysis using self-organizing maps and association rules for improved tourist safety

Traffic accidents is the most common cause of injury among tourists. This paper presents a method and a tool for analysing historical traffic accident records using data mining techniques for the development of an application that warns tourist drivers of possible accident risks. The knowledge necessary for the specification of the application is based on patterns distilled from spatiotemporal analysis of historical accidents records. Raw accident obtained from Police records, underwent pre-processing and subsequently was integrated with secondary traffic-flow data from a mesoscopic simulation. Two data mining techniques were applied on the resulting dataset, namely, clustering with self-organizing maps (SOM) and association rules. The former was used to identify accident black spots, while the latter was applied in the clusters that emerged from SOM to identify causes of accidents in each black spot. Identified patterns were utilized to develop a software application to alert travellers of imminent accident risks, using characteristics of drivers along with real-time feeds of drivers' geolocation and environmental conditions