Study of the degree of III conditioning of the phase space of pencil-beam radiotherapy using singular value decomposition

Dose distribution optimization algorithms are necessary in pencil-beam radiotherapy to exploit efficiently the multiple parameters of this powerful irradiation technique. We propose as an optimization technique singular value decomposition (SVD) analysis, which allows the measurement of ill conditioning of the stereotactic radiotherapy inverse problem and yields optimal weights for conformal treatment. Our approach to dose distribution optimization is to recover estimates of the minibeams weights from well-defined previsional dose matrices to study the influence of the different parameters on the stereotactic radiotherapy inverse procedure. The adjustment of the different parameters of the stereotactic irradiation to the “SVD optimizer” procedure is realized taking into account the ratio of the quality reconstruction to the calculation time. It will permit a more efficient use of the SVD optimizer in clinical applications with real three-dimensional lesions. We show the efficiency of the SVD optimizer in analyzing and predicting ill conditioning in stereotactic radiotherapy and in recognizing the topography of the different beams to create an optimal vector containing the beam weights (reconstructed weighting vector).     

A linear 60 GHz 65 nm-CMOS power amplifier realization and characterization for OFDM signal

A millimeter-wave Power Amplifier (PA) based on a 65nm CMOS technology from STMicroelectronics has been designed. The targeted feature is the unlicensed band around 60 GHz suitable for wireless personal area network application (WPAN). To optimize the linearity, the PA is designed under class A biasing to have an output compression point (OCP₁) close to its saturated Power (P _sat). S-parameters and large signal measurement results are demonstrated and compared with electromagnetic simulations. The PA offers a P _sat of 8.3 dBm, an OCP₁ of 6 dBm and a gain of 6.7 dB. The die area is 0.29 mm² with pads. Considering those results, one-tone simulations are not sufficient to characterize the linearity performances of the PA in its real conditions of use. Consequently, two-tone simulations are firstly performed. After, linearity figures of merit (FoM) are discussed applying an orthogonal frequency-division multiplexing (OFDM) modulated signal. The PA offers an adjacent channel power ratio (ACPR) of 15 dB and an error vector magnitude (EVM) of 20% at PA compression operating mode.     

Enhanced EDCA with Deterministic Transmission Collision Resolution for Real-Time Communication in Vehicular Ad Hoc Networks

The collision prevention system is one of most important research issues on vehicle safety technology. Sending worming messages within the right time and reliable transmission will get prevention of a possible vehicle accident. The communication standards of vehicular networks (VANET) are unable to guarantee the delivery of critical messages within tight deadlines. Indeed, the transmission collisions are handled with probabilistic manner that can reduce the transmission latency; however, it is inept to predict an upper bound value of this delay to verify the deadline. In this paper, we propose a medium access protocol that ensures the delivery of critical messages within a deadline. It is a hard real-time system with delay constant guarantee. We are focusing on improving the EDCA medium access protocol to prioritize critical messages and to get access to the transmission channel within a predictable communication delay. We create a new enhanced access protocol that is compatible with the IEEE 802.11p VANET standards and adapted to real-time communication requirements related to the vehicle collision avoidance problem.     

Cooperative Association/Re-association Approaches to Optimize Energy Consumption for Real-Time IEEE 802.15.4/ZigBee Wireless Sensor Networks

The major challenge of real-time Wireless Sensor Networks stills the optimization of both constraints: energy consumption, to get long network lifetime and the communication delay, to meet real-time requirements. In the context of IEEE 802.15.4/ZigBee networks, the association procedure has a direct effect on building paths optimizing those constraints. In this paper, we are interested on the definition of an ideal approach of load balancing to fairly distribute energy consumption among nodes in IEEE 802.15.4/ZigBee WSNs. This approach leads to conserve energy of each node in order to extend the network lifetime. To be closer to this ideal, we propose new dynamic association/re-association approaches allowing path alternation relative to association criteria and their threshold parameters. The implementation of those approaches in NS2 simulator highlights the efficiency of cooperative and dynamic association criteria particularly the one based on the sum of the inverses of remaining energy. Indeed, this approach gives better results with regard to energy distribution according to ideal approach which leads to a longer lifetime. It also performs lower latency for real time communication.     

Quantized based image watermarking in an independent domain

This paper presents a performance study for two well known quantized based watermarking schemes Scalar Costa Scheme (SCS), and Trellis Coded Quantization scheme (TCQ) in an independent domain. For our study, the independent domain is obtained by the combination of the cited schemes with Independent Component Analysis (ICA). The Independent Component Analysis is used while inserting and extracting the message. Thus a performance compromise improvement of the original SCS and TCQ schemes in terms of robustness, capacity, and security is shown. Then the obtained schemes performances are compared to the Spread Transform (ST) based scheme well known for its proven good robustness properties. Our results show that, using watermarking with side information in independent domain permits to improve the global SCS and TCQ schemes performances. For example, in the case of SCS, by studying the Bit Error Rate (BER) in function of the watermark to noise ratio (WNR), the robustness has been improved by 20 dB (1 decade) when WNR is equal to 0 dB. Moreover, the capacity study shows for the same WNR=0 dB, the amount of information to be transmitted without error for a given noise level of the proposed SCS combined with ICA scheme (SCS-ICA) is much higher than that of the existing schemes. Finally, the study of the probability density functions (PDF) of the original and marked signals has shown that the Cachin-security level of the TCQ in an independent domain scheme (TCQ-ICA) is the best one compared to the other known schemes.     

Self-organizing technique for improving coverage in connected mobile objects networks

Despite the multiple benefits offered today by connected mobile objects networks (CMONs), some constraints continue to limit their development and to degrade their applications and services’ performance. Given their limited energy, some or many objects may stop functioning which leads to the deterioration of network functionalities such as monitoring, detection and transfer of data. It is in this context that our work is situated, namely the improvement of applications performance and the quality of service (QoS) within CMONs, by exploiting some communication environment parameters and geometry techniques. We propose a new technique called self-organization area coverage (SOAC) for CMONs which aims to ensure maximum coverage in the network while optimizing the exploited resources. SOAC has been evaluated and compared not only to the network without improvement but to two other solutions proposed in the literature. The obtained results show a clear improvement in terms of network coverage and several QoS parameters.     

Revisiting Johnson and Jackson boundary conditions for granular flows

In this article, we revisit Johnson and Jackson boundary conditions for granular flows. The oblique collision between a particle and a flat wall is analyzed by adopting the classic rigid‐body theory and a more realistic semianalytical model. Based on the kinetic granular theory, the input parameter for the partial‐slip boundary conditions, specularity coefficient, which is not measurable in experiments, is then interpreted as a function of the particle‐wall restitution coefficient, the frictional coefficient, and the normalized slip velocity at the wall. An analytical expression for the specularity coefficient is suggested for a flat, frictional surface with a low frictional coefficient. The procedure for determining the specularity coefficient for a more general problem is outlined, and a working approximation is provided. Published 2011 American Institute of Chemical Engineers, 2012     

Numerical modelling of rotating packed beds used for CO2 capture processes: A review

Over the last decades, renewable and clean energy sources are being rigorously adopted along with carbon capture technologies to tackle the increasing carbon dioxide (CO₂) concentration level in the environment. CO₂ capture is a quintessential option for tackling global warming issues. In this context, the present paper has reviewed the process intensification equipment called a rotating packed bed (RPB), which is highly industry applicable due to high gravity (HiGee) force. This facilitates strong mass transfer characteristics, a compact design, and low energy consumption. In this review, the current research scenario of RPBs using numerical, computational fluid dynamics (CFD), and mathematical modelling, along with different machine learning approaches in the CO₂ capture process, has been reviewed. The different geometry designs, hydrodynamic characteristics, performance parameters, research methods, and their effects on CO₂ removal efficiency have been discussed. Furthermore, the latest experimental studies are also summarized, especially in the absorption and adsorption domain. Finally, recommendations have been given to support the RPBs in different industrial and commercial applications of CO₂ removal.     

Improving the time resolution and signal noise ratio of ultrasonic testing of welds by the wavelet packet

In ultrasonic testing of welds, detection of small flaws is often difficult by the superimposed noise due to the grain structure of the material. The scattering of ultrasonic waves from grain boundaries can interfere and introduce disturbance in the received signal that can sometimes mask indications due to a small but potentially dangerous defect. However, to enhance the flaw characterization, methods based on ‘thresholding’ have given good results only when the signal to noise ratio is high, and since bandwidth of the reflected signal as well as its principal frequency is subject to wide variation, it is impossible to create an appropriate band pass filter. So linear filtering does not provide good results, because both, the structure noise and flaw signal concentrate energy in the same frequency band. Non-linear filtering can be used to reduce or suppress the noise from ultrasonic signals. One way out is to use the time frequency transforms, the method is based on the wavelet packet decomposition. The Debauchee function of order 8 [Daubauchee I. Orthogonal bases of capacity wavelets. Commun Pure Appl Math 1998;41] has been chosen as the analyzing function, and each measured ultrasonic signal is analyzed by a filter bank through only three levels of decomposition. This work demonstrates that the following analysis is very efficient with respect to signal recovery from noisy data. The experimental results have shown that the proposed method has excellent performances on SNR enhancements.     

Neural Computation to Estimate Heat Flux in an Atmospheric Plasma Spray Process

Temperature is a key parameter in the thermal spray process and is a consequence of the heat flux experienced by the workpiece. This paper deals with the estimation of the heat flux transmitted to a workpiece from an atmospheric plasma spray torch during the preheating process often implemented in thermal spraying. An inverse heat conduction problem solution using a conjugate gradient method was considered to determine the heat flux starting from a known temperature distribution. Results from the later method were used to train an artificial neural network to discover correlations between selected processing parameters and heat flux.