Detecting Traffic Conditions Model Based On Clustering Nodes Situations In VANET

In the last decade, cooperative vehicular network has been one of the most studied areas for developing the intelligent transportation systems (ITS). It is considered as an important approach to share the periodic traffic situations over vehicular ad hoc networks (VANETs) to improve efficiency and safety over the road. However, there are a number of issues in exchanging traffic data over high mobility of VANET, such as broadcast storms, hidden nodes and network instability. This paper proposes a new model to detect the traffic conditions using clustering traffic situations that are gathered from the nodes (vehicles) in VANET. The model designs new principles of multi-level clustering to detect the traffic condition for road users. Our model (a) divides the situations of vehicles into clusters, (b) designs a set of metrics to get the correlations among vehicles and (c) detects the traffic condition in certain areas. These metrics are simulated using the network simulator environment (NS-3) to study the effectiveness of the model

An Intelligent Data Mining System to Detect Health Care Fraud

The chapter begins with an overview of the types of healthcare fraud. Next, there is a brief discussion of issues with the current fraud detection approaches. The chapter then develops information technology based approaches and illustrates how these technologies can improve current practice. Finally, there is a summary of the major findings and the implications for healthcare practice

Optimizing the location of weather monitoring stations using estimation uncertainty

In this article, we address the problem of planning a network of weather monitoring stations observing average air temperature (AAT). Assuming the network planning scenario as a location problem, an optimization model and an operative methodology are proposed. The model uses the geostatistical uncertainty of estimation and the indicator formalism to consider in the location process a variable demand surface, depending on the spatial arrangement of the stations. This surface is also used to express a spatial representativeness value for each element in the network. It is then possible to locate such a network using optimization techniques, such as the used methods of simulated annealing (SA) and construction heuristics. This new approach was applied in the optimization of the Portuguese network of weather stations monitoring the AAT variable. In this case study, scenarios of reduction in the number of stations were generated and analysed: the uncertainty of estimation was computed, interpreted and applied to model the varying demand surface that is used in the optimization process. Along with the determination of spatial representativeness value of individual stations, SA was used to detect redundancies on the existing network and establish the base for its expansion. Using a greedy algorithm, a new network for monitoring average temperature in the selected study area is proposed and its effectiveness is compared with the current distribution of stations. For this proposed network distribution maps of the uncertainty of estimation and the temperature distribution were created. Copyright (c) 2011 Royal Meteorological Societyinfo:eu-repo/semantics/publishedVersio

Does Information Technology Investment Influences Firm’s Market Value? The Case of Non-Publicly Traded Healthcare Firms

Managers make informed information technology investment decisions when they are able to quantify how IT contributes to firm performance. While financial accounting measures inform IT’s influence on retrospective firm performance, senior managers expect evidence of how IT influences prospective measures such as the firm’s market value. We examine the efficacy of IT’s influence on firm value combined with measures of financial performance for non-publicly traded (NPT) hospitals that lack conventional market-based measures. We gathered actual sale transactions for NPT hospitals in the United States to derive the q ratio, a measure of market value. Our findings indicate that the influence of IT investment on the firm is more pronounced and statistically significant on firm value than exclusively on the accounting performance measures. Specifically, we find that the impact of IT investment is not significant on return on assets (ROA) and operating income for the same set of hospitals. This research note contributes to research and practice by demonstrating that the overall impact of IT is better understood when accounting measures are complemented with the firm’s market value. Such market valuation is also critical in merger and acquisition decisions, an activity that is likely to accelerate in the healthcare industry. Our findings provide hospitals, as well as other NPT firms, with insights into the impact of IT investment and a pragmatic approach to demonstrating IT’s contribution to firm value

Context-awareness in mobile tourist information systems: challenges for user interaction

Context in mobile tourist information systems is typically captured as the current location of the user. Few systems consider the user's interests or wider context of the sights. This paper explores ideas of how to model, observe, evaluate, and exploit a richer notion of context in this application area. We discuss the influence of such a richer context model on the user interaction for both the capturing of context and the context-aware user/device interactions

A Human-centric Perspective on Digital Consenting: The Case of GAFAM

According to different legal frameworks such as the European General Data Protection Regulation (GDPR), an end-user's consent constitutes one of the well-known legal bases for personal data processing. However, research has indicated that the majority of end-users have difficulty in understanding what they are consenting to in the digital world. Moreover, it has been demonstrated that marginalized people are confronted with even more difficulties when dealing with their own digital privacy. In this research, we use an enactivist perspective from cognitive science to develop a basic human-centric framework for digital consenting. We argue that the action of consenting is a sociocognitive action and includes cognitive, collective, and contextual aspects. Based on the developed theoretical framework, we present our qualitative evaluation of the consent-obtaining mechanisms implemented and used by the five big tech companies, i.e. Google, Amazon, Facebook, Apple, and Microsoft (GAFAM). The evaluation shows that these companies have failed in their efforts to empower end-users by considering the human-centric aspects of the action of consenting. We use this approach to argue that their consent-obtaining mechanisms violate principles of fairness, accountability and transparency. We then suggest that our approach may raise doubts about the lawfulness of the obtained consent—particularly considering the basic requirements of lawful consent within the legal framework of the GDPR

IT Politics in the Domain of Knowledge Workers: A Chronological Analysis

Markus’s study of IT politics has been influential for the IT implementation literature since the 1980s. However, mistakes of the top-down implementation approach could still be easily found in many organizations. Derived from Markus’s notion of interaction theory and Drucker’s work on knowledge workers, this paper illustrates a LMS (learning management systems) implementation case that evolves from such traditional top-down approach. Based on a chronological analysis, the case study narrates how IT politics was shaped in a context where most stakeholders were highly skillful knowledge workers whose academic autonomy was largely overlooked. Reflective discussion suggests how the implementation process might have been better managed. Evidently, even decades after Markus’s and Drucker’s influential work, history still repeated itself and IT politics continued to provide lessons for contemporary IT managers and researchers. Future strategy and implementation approach for campus IT projects and LMS implementation in particular are recommended

A multi-level metadata approach for a public sector information data infrastructure

This paper describes an approach for representing and handling metadata about Public Sector Information data sets in a large scale data infrastructure as designed within ENGAGE, a project of the FP7 Research Infrastructures programme. A multi-level approach is adopted, allowing management of metadata at various levels of expressive power, and thus enabling different use cases and requirements to be served through a single platform. CERIF is being investigated as a common conceptual model to ensure information integra- tion from diverse sources without loss of meaning and furthermore as the basis for the generation of Linked Open Data. Through detailed mappings from common metadata schemata used for PSI it is shown that CERIF is a data model suitable for representing rich contextual metadata for the domain of governmental datasets