Non-saturation Throughput of S-ALOHA Using the Time-Scale Decomposition Technique

S-ALOHA （Slotted ALOHA） random access protocol is a widely used protocol mainly for the transmission of short packets in wireless networks. Most papers consider either an infinite population model where the impact of the backoff protocol cannot be adequately evaluated or a finite population model where the number of nodes is fixed. In this letter, a combination of both models is proposed using the time-scale decomposition technique. This methodology allows to study the system under more realistic conditions where the dynamics of users enter and leaving the system are reflected on the performance of the system as well as the impact of the backoff protocol. Also, it allows studying the system in non-saturation conditions. The proposed methodology divides the analysis in two parts： packet-level and connection-level. This analysis renders suitable results when the time scale of the packet level and connection level statistics is different. On the other hand, when these scales are similar, the proposed methodology is no longer suited.     

RF Power Amplifier Behavioral Modeling Based on Takenaka–Malmquist–Volterra Series

In this paper, a Takenaka–Malmquist–Volterra (TMV) model structure is employed to improve the approximations in the low-pass equivalent behavioral modeling of radio frequency (RF) power amplifiers (PAs). The Takenaka–Malmquist basis generalizes the orthonormal basis functions previously used in this context. In addition, it allows each nonlinearity order in the expanded Volterra model to be parameterized by multiple complex poles (dynamics). The state-space realizations for the TMV models are introduced. The pole sets for the TMV model and also for the previous Laguerre–Volterra (LV) and Kautz–Volterra (KV) models are obtained using a constrained nonlinear optimization approach. Based on experimental data measured on a GaN HEMT class AB RF PA excited by a WCDMA signal, it is observed that the TMV model reduces the normalized mean-square error and the adjacent channel error power ratio for the upper adjacent channel (upper ACEPR) by 1.6 dB when it is compared to the previous LV and KV models under the same computational complexity.     

Mathematical Morphology on the Spherical CIELab Quantale with an Application in Color Image Boundary Detection

Mathematical morphology is a theory with applications in image processing and analysis. This paper presents a quantale-based approach to color morphology based on the CIELab color space in spherical coordinates. The novel morphological operations take into account the perceptual difference between color elements by using a distance-based ordering scheme. Furthermore, the novel approach allows for the use of non-flat structuring elements. An illustrative example reveals that non-flat dilations and erosions may preserve more features of a color image than their corresponding flat operations. Furthermore, the novel non-flat morphological operators yielded promising results on experiments concerning the detection of the boundaries of objects on color images.     

Part-by-part dimensional error compensation in compliant sheet metal assembly processes

Dimensional variation in assembly processes is one of the most important issues that affect quality. Although robust design and statistical process quality control help to reduce this problem, they cannot be used for instant variation reduction during assembly operations, especially during process ramp-up. This paper introduces a complete methodology for dimensional-related error compensation in compliant sheet metal assembly processes. The proposed methodology is divided into two steps: (1) an off-line error control-learning module using virtual assembly models to determine necessary adjustments; and (2) an in-line control implementation using a feed-forward control strategy based on the learned adjustments. The off-line learning step focuses on determining control actions or corrections to compensate for the negative effects incoming part errors have on Key Product Characteristics. Specifically, it utilizes a newly developed iterative sampling method based on Kriging fitting to efficiently determine optimal control actions. The in-line feed-forward control identifies appropriate part-by-part adjustments using these learned control actions and incoming assembly component measurements. In this paper, two case studies are presented. First, a mathematical case study presents an empirical proof for the feasibility of the Iterative Sampling and Fitting Algorithm. Second, a simulation-based case study illustrates the effectiveness of the proposed methodology to improve dimensional quality in assembly operations for compliant sheet metal parts.     

NiMo/C Used as Magnetic Support for SILP Catalysts

In this work, supported ionic liquid (IL) phases catalysts were prepared based on Pd dispersed in IL phases supported on magnetic particles of nickel/molybdenum covered with carbon (NiMo/C). The magnetic support was prepared via CVD method at 800 °C. XRD analysis showed the phases of metallic nickel and molybdenum carbide. The presence of carbon in these materials was confirmed by TEM/EDS and thermogravimetric analysis (TG) analysis. Pd particles were dispersed in 1 and 2.5 wt% of the IL 1-butyl-3-methylimidazolium tetrafluoroborate (BMIm·BF₄), which were immobilized on the support surface via impregnation method. TG analysis shows a weight loss between 300 and 420 °C attributed to the BMIm·BF₄, confirming the existence of IL on the support surface. The prepared materials were investigated in hydrogenations reactions of 1,5-cyclooctadiene and nitrobenzene, and the influence of IL on the activity and selectivity of these catalysts were observed. These materials have great potential for catalysis applications, because they bring together the advantages of the IL in the catalyst surface and the facility of magnetic materials separation.     

Energy storage and control optimization for an electric vehicle

Two big issues involving electric vehicles are energy supply and power management control. To deal with the energy supply problem, this paper proposes the application of a hybrid energy source system, composed of battery pack and ultracapacitor bank. The power management control between the energy supplies was defined by a fuzzy logic with inference rules optimized through genetic algorithm. The genetic algorithm optimizes lower and upper limits of membership functions aiming to reduce the hybrid energy source system total mass while maximizing the electric vehicle drive range and performance. Through the Pareto frontier, we found the best trade‐off solution.     

ISO 9001 certification in the American Continent: a statistical analysis and modelling

The ISO 9001 standard is considered as an effective tool to support a quality management system (QMS). A steady growth in the number of ISO 9001 issued certificates is observed worldwide, confirming the interest of companies in this approach. However, information regarding this behaviour over time in the American Continent is scarce. This paper presents a set of qualitative and quantitative analyses related to the ISO 9001 certification (globally and at the country level of the Americas), the use of this standard in countries that were part of the ISO Survey 2011 and modelling the ISO 9001 certification for American countries, in order to characterise through mathematical models, the evolution of the certification process and to identify factors that influence the ISO 9001 issued certificates in the various countries analysed. Based on the work developed, a positive relationship was found between the number of issued certificates in each country per 1000 inhabitants and the indicators of economic development (Gross National Income Per Capita). It is determined that the total reserves of a country is an economic variable that directly affects the number of issued certificates, a finding not observed in other forecasting models.     

Parking at the UC campus: Problems and solutions

This study underscores the importance of adopting integrated parking management policies that ensure not only more rational use of the available parking spaces, evenly balancing supply and demand and bringing in revenues to cover the parking facilities costs, but also the improved attractiveness of alternative transportation modes. Parking supply and demand flows within the UC campus are estimated. The results indicate that the parking facility is underpriced and that there is overcrowding. To reflect critically on these issues and identify research areas to address their socioeconomic implications, a survey regarding the characterization of campus commuters and their travel options is presented. Logistic regression modelling is applied to determine the relative importance of UC campus commuters’ attributes in their level of willingness to pay to have reserved parking on the campus. Finally, some policy proposals are discussed.