Design of a Feedback-Controlled Wireless Converter for Electric Vehicle Wireless Charging Applications

Electric vehicles (EVs) have played an important role in the modern transporta-tion system in recent years. However, current generations of EVs face unsolved drawbacks such as short driving range, long charging time, and high cost due to expensive battery systems. Wireless Power Transfer (WPT) is a promising technology that is able to mitigate the drawbacks EVs are facing. This paper focuses on investigating and building a complete high-efficiency WPT system that is capable of efficiently charging electric vehicles. The goal is to design and ap-ply two different configurations of compensation networks to the WPT system. In this paper, the two compensation network configurations studied are LLC and LCC. After comparing their operational characteristics and efficiencies, the most suitable configuration is proposed. Moreover, a phase-shifted controller is applied in order to regulate the power transferred through the WPT system

A framework for identifying uncertainties in long-term digital preservation

With the current expansion in digital information comes an increasing need to preserve such assets. The ENSURE (Enabling knowledge Sustainability, Usability and Recovery for Economic value) pro-ject, a research project under the European Community's Seventh Framework Programme, is the par-ent project to this research area and its aim is to conduct advanced research to address the challenges of Long Term Digital Preservation (LTDP) to ensure the successful preservation, availability and ac-cessibility of preserved data in the future. Focusing on identifying uncertainties in the LTDP activities and their impact on cost and economic performance of digital preservation systems, this paper dis-cusses a framework to identify uncertainties in LTDP for business sectors interested

A cost engine system for estimating whole-life cycle cost of long-term digital preservation activities

This research paper presents a cost engine system that estimates the whole life cycle cost of long-term digital preservation (LTDP) activities using cloud-based technologies. A qualitative research methodology has been employed and the activity based costing (ABC) technique has been used to develop the cost model. The unified modelling language (UML) notation and the object oriented paradigm (OOP) are utilised to design the architecture of the software system. In addition, the service oriented architecture (SOA) style has been used to deploy the function of the cost engine as a web service in order to ensure its accessibility over the web. The cost engine is a module that is part of a larger digital preservation system and has been validated qualitatively through experts’ opinion. Its benefits are realised in the accurate and detailed estimation of cost for companies wishing to employ LTDP activities

Towards a framework for predicting whole life-cycle cost for long-term digital preservation

Estimating the costs for the whole lifecycle of long-term digital preservation (LTDP) activities ena-bles decision makers to choose carefully what data to preserve, duration of preservation and type of preservation techniques best applied for their information. To address this need, a framework is de-veloped to generate a cost model that will estimate costs for long-term digital preservation activities using storage in the cloud and taking into consideration the impact of mitigating uncertainties, espe-cially obsolescence issues on future costs. This cost estimating framework is part of the European pro-ject entitled ‘Enabling kNowledge Sustainability Usability and Recovery for Economic value’ which aims to provide a total long-term digital preservation solution for companies and public sector organi-sations interested in keeping their digital information alive for the long-term within the healthcare, fi-nancial and the clinical trials business sectors

Assessment of bridges\u27 expansion joints in Egypt

Bridges play a vital role in resolving transportation problems in Egypt. The objective of this research is to predict the conditions of bridges expansion joints, with the aim of proposing appropriate maintenance and repair strategies in order to extend their lifespans. A thorough literature review of existing bridges expansion joints maintenance and repair strategies are conducted. Furthermore, visual inspections and surveying of existing bridges expansion joints in Egypt are conducted, with the findings of such observations documented and recorded. Moreover, an expansion joint management system (EJMS) is developed with the aim of recommending the optimum maintenance strategy for bridges that optimizes annual condition index (ACI) and cost. This model uses a combination of Fuzzy Logic (FL) and Genetic Algorithm (GA) in order to provide optimal recommendations. In addition, a transition matrix for predicting deterioration of expansion joints EJ using Markov Chain (MC) is developed. In order to test the model, several case studies of existing bridges in Egypt are used and the results are assessed against those documented through visual inspection. The comparison indicated that the developed EJMS is efficient in predicting the bridge EJs condition, where there is a deviation of 5% between the predicted condition from EJMS and the actual conditions observed through visual inspections. In addition, EJMS can play an important role in supporting decision makers in selecting the optimum maintenance and repair strategy that would maximizes the overall condition of expansion joints while meeting a certain budget constraint

Heparin versus No Heparin before Endoscopic Vein Harvesting using Angioscopy

Background: Endoscopic vein harvesting (EVH) became a standard technique with several advantages over open vein harvesting (OVH). Thrombus formation inside the vein lumen is one of the main concerns after EVH. It is not known whether heparin use before EVH could prevent this complication. The study aimed to assess the safety of not giving intravenous heparin before starting the open system EVH procedure using the PeriVu™ Disposable Angioscopy (LeMaitre® VASCULAR- France) as a modality to assess the intraluminal vein clots. Methods: This research is a randomized study that compared two groups of patients undergoing CABG. One group had 2500 IU heparin before EVH using (Virtusaph plus, Terumo) (n=50) and the other group had EVH without giving heparin (n=50). Intraluminal clots in the vein segments were evaluated using PeriVu Disposable Angioscopy ( LeMaitre-VASCULAR).  Results: Preoperative data were comparable between groups with no statistically significant difference. The mean duration of the procedure in the heparin group versus the non-heparin group was 30.6±5.8 and 28.7±5.9, respectively (P= 0.11). Intraluminal clots were detected in two segments out of 103 segments (1.94%) in the No heparin group, while none was detected in the heparin group (P= 0.24).  Conclusion: There was no difference between heparin versus no heparin during endoscopic vein harvest regarding intraluminal thrombus formation. Further studies are recommended to confirm our findings

Secret Key Generation Based on AoA Estimation for Low SNR Conditions

In the context of physical layer security, a physical layer characteristic is used as a common source of randomness to generate the secret key. Therefore an accurate estimation of this characteristic is the core for reliable secret key generation. Estimation of almost all the existing physical layer characteristic suffer dramatically at low signal to noise (SNR) levels. In this paper, we propose a novel secret key generation algorithm that is based on the estimated angle of arrival (AoA) between the two legitimate nodes. Our algorithm has an outstanding performance at very low SNR levels. Our algorithm can exploit either the Azimuth AoA to generate the secret key or both the Azimuth and Elevation angles to generate the secret key. Exploiting a second common source of randomness adds an extra degree of freedom to the performance of our algorithm. We compare the performance of our algorithm to the algorithm that uses the most commonly used characteristics of the physical layer which are channel amplitude and phase. We show that our algorithm has a very low bit mismatch rate (BMR) at very low SNR when both channel amplitude and phase based algorithm fail to achieve an acceptable BMR

Practical Secrecy at the Physical Layer: Key Extraction Methods with Applications in Cognitive Radio

The broadcast nature of wireless communication imposes the risk of information leakage to adversarial or unauthorized receivers. Therefore, information security between intended users remains a challenging issue. Currently, wireless security relies on cryptographic techniques and protocols that lie at the upper layers of the wireless network. One main drawback of these existing techniques is the necessity of a complex key management scheme in the case of symmetric ciphers and high computational complexity in the case of asymmetric ciphers. On the other hand, physical layer security has attracted significant interest from the research community due to its potential to generate information-theoretic secure keys. In addition, since the vast majority of physical layer security techniques exploit the inherent randomness of the communication channel, key exchange is no longer mandatory. However, additive white Gaussian noise, interference, channel estimation errors and the fact that communicating transceivers employ different radio frequency (RF) chains are among the reasons that limit utilization of secret key generation (SKG) algorithms to high signal to noise ratio levels. The scope of this dissertation is to design novel secret key generation algorithms to overcome this main drawback. In particular, we design a channel based SKG algorithm that increases the dynamic range of the key generation system. In addition, we design an algorithm that exploits angle of arrival (AoA) as a common source of randomness to generate the secret key. Existing AoA estimation systems either have high hardware and computation complexities or low performance, which hinder their incorporation within the context of SKG. To overcome this challenge, we design a novel high performance yet simple and efficient AoA estimation system that fits the objective of collecting sequences of AoAs for SKG. Cognitive radio networks (CRNs) are designed to increase spectrum usage efficiency by allowing secondary users (SUs) to exploit spectrum slots that are unused by the spectrum owners, i.e., primary users (PUs). Hence, spectrum sensing (SS) is essential in any CRN. CRNs can work both in opportunistic (interweaved) as well as overlay and/or underlay (limited interference) fashions. CRNs typically operate at low SNR levels, particularly, to support overlay/underlay operations. Similar to other wireless networks, CRNs are susceptible to various physical layer security attacks including spectrum sensing data falsification and eavesdropping. In addition to the generalized SKG methods provided in this thesis and due to the peculiarity of CRNs, we further provide a specific method of SKG for CRNs. After studying, developing and implementing several SS techniques, we design an SKG algorithm that exploits SS data. Our algorithm does not interrupt the SS operation and does not require additional time to generate the secret key. Therefore, it is suitable for CRNs