Vehicular ad-hoc networks (VANETs) are the specific sort of ad-hoc networks that are utilized in intelligent transportation systems (ITS). VANETs have become one of the most reassuring, promising, and quickest developing subsets of the mobile ad-hoc networks (MANETs). They include smart vehicles, roadside units (RSUs), and on-board units (OBUs) which correspond through inconsistent wireless network. The current research in the vehicles industry and media transmission innovations alongside the remarkable multimodal portability administrations expedited center-wise ITS, of which VANETs increase considerably more attention. The particular characteristics of the software defined networks (SDNs) use the vehicular systems by its condition of the centralized art having a complete understanding of the network. Security is an important issue in the SDN-based VANETs, as a result of the effect the threats and vulnerabilities can have on driver’s conduct and personal satisfaction. This paper opens a discourse on the security attacks that future SDN-based VANETs should confront and examines how SDNs could be advantageous in building new countermeasures. SDN-based VANETs encourage us to dispose of the confinement and difficulties that are available in the traditional VANETs. It helps us to diminish the general burden on the system by dealing with the general system through a single wireless controller. While SDN-based VANETs provide us some benefits in terms of applications and services, they also have some important challenges which need to be solved. In this study we discuss and elaborate the challenges, along with the applications, and the future directions of SDN-based VANETs. At the end we provide the conclusion of the whole study.
This paper presents a system dedicated to monitoring the heart activity parameters using Electrocardiography (ECG) mobile devices and a Wearable Heart Monitoring Inductive Sensor (WHMIS) that represents a new method and device, developed by us as an experimental model, used to assess the mechanical activity of the hearth using inductive sensors that are inserted in the fabric of the clothes. Only one inductive sensor is incorporated in the clothes in front of the apex area and it is able to assess the cardiorespiratory activity while in the prior of the art are presented methods that predict sensors arrays which are distributed in more places of the body. The parameters that are assessed are heart data-rate and respiration. The results are considered preliminary in order to prove the feasibility of this method. The main goal of the study is to extract the respiration and the data-rate parameters from the same output signal generated by the inductance-to-number convertor using a proper algorithm. The conceived device is meant to be part of the “wear and forget” equipment dedicated to monitoring the vital signs continuously.
Targeted marketing strategy is a prominent topic that has received substantial attention from both industries and academia. Market segmentation is a widely used approach in investigating the heterogeneity of customer buying behavior and profitability. It is important to note that conventional market segmentation models in the retail industry are predominantly descriptive methods, lack sufficient market insights, and often fail to identify sufficiently small segments. This study also takes advantage of the dynamics involved in the Hadoop distributed file system for its ability to process vast dataset. Three different market segmentation experiments using modified best fit regression, i.e., Expectation-Maximization (EM) and K-Means++ clustering algorithms were conducted and subsequently assessed using cluster quality assessment. The results of this research are twofold: i) The insight on customer purchase behavior revealed for each Customer Lifetime Value (CLTV) segment; ii) performance of the clustering algorithm for producing accurate market segments. The analysis indicated that the average lifetime of the customer was only two years, and the churn rate was 52%. Consequently, a marketing strategy was devised based on these results and implemented on the departmental store sales. It was revealed in the marketing record that the sales growth rate up increased from 5% to 9%.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.