Weak convergence to a modified fractional Brownian motion

This article discusses the weak convergence of a particular version of a fractional process (appropriately normalized) to a modified fractional Brownian motion which has not been previously reported in the literature. Additionally, we illustrate a specific case in which this type of fractional Brownian motion characterizes the limiting behaviour of processes which might arise in practice. This is related to the situation termed by Hualde (2006) as ‘unbalanced cointegration’, where the integration orders of the observables are different, but their corresponding balanced versions (where one of the series is filtered adequately so it has identical integration order to the other one) are cointegrated in the usual sense.     

Construction of interval-valued fuzzy entropy invariant by translations and scalings

In this paper, we propose a method to construct interval-valued fuzzy entropies (Burillo and Bustince 1996). This method uses special aggregation functions applied to interval-contrasts. In this way, we are able to construct interval-valued fuzzy entropies from automorphisms and implication operators. Finally, we study the invariance of our constructions by scaling and translation.     

双侧延伸端板半刚性组合节点的抗震性能(1):试验研究

与钢结构相比,相同延性下,组合结构具有较高的刚度及较好的抗火性能。因此,在地震高发区大量采用组合结构。研究了双侧延伸端板半刚性组合节点的抗震性能,对节点进行单调、循环、准静力试验,以描述这种节点的抗震性能。试验包括内节点和外节点,并提供了关于节点延性、能量耗散、退化影响的实用数据。采用这些数据构建和校验基于构件的节点模型。节点由双向弹簧组成,其中一个代表剪切板的性能,另一个代表连接的性能。模型能精确模拟节点的性能及在循环荷载下的破坏形式。     

Partition-Based Lower Bound for Max-CSP

In this paper we address Max-CSP, a constraint optimization problem typically solved using a branch and bound scheme. It is well known that the efficiency of branch and bound greatly depends on the quality of the available lower bound. Previous approaches aggregate to the lower bound individual contributions of unassigned variables. In this paper, we augment this approach by adding global contributions of disjoint subsets of unassigned variables, which requires a partition of the set of unassigned variables. Using this idea, we introduce the partition-based lower bound. It improves previous approaches based on individual contributions in the sense that our method can be added up to previous bounds, possibly increasing their value. We demonstrate our method presenting two new algorithms, PFC-PRDAC and PFC-MPRDAC, which are the natural successors of PFC-RDAC and PFC-MRDAC augmented with our approach. We provide experimental evidence for the superiority of the new algorithms on random problems and real instances of weighted over-constrained problems.     

MMALE—A Methodology for Malware Analysis in Linux Environments

In a computer environment, an operating system is prone to malware, and even the Linux operating system is not an exception. In recent years, malware has evolved, and attackers have become more qualified compared to a few years ago. Furthermore, Linux-based systems have become more attractive to cybercriminals because of the increasing use of the Linux operating system in web servers and Internet of Things (IoT) devices. Windows is the most employed OS, so most of the research efforts have been focused on its malware protection rather than on other operating systems. As a result, hundreds of research articles, documents, and methodologies dedicated to malware analysis have been reported. However, there has not been much literature concerning Linux security and protection from malware. To address all these new challenges, it is necessary to develop a methodology that can standardize the required steps to perform the malware analysis in depth. A systematic analysis process makes the difference between good and ordinary malware analyses. Additionally, a deep malware comprehension can yield a faster and much more efficient malware eradication. In order to address all mentioned challenges, this article proposed a methodology for malware analysis in the Linux operating system, which is a traditionally overlooked field compared to the other operating systems. The proposed methodology is tested by a specific Linux malware, and the obtained test results have high effectiveness in malware detection.     

Virtual center for renal support: technological approach to patient physiological image

The patient physiological image (PPI) is a novel concept which manages the knowledge of the virtual center for renal support (VCRS), currently being developed by the Biomedical Engineering Group of the University of Seville. PPI is a virtual "replica" of the patient, built by means of a mathematical model, which represents several physiological subsystems of a renal patient. From a technical point of view, PPI is a component-oriented software module based on cutting-edge modeling and simulation technology. This paper provides a methodological and technological approach to the PPI. Computational architecture of PPI-based VCRS is also described. This is a multi-tier and multi-protocol system. Data are managed by several ORDBMS instances. Communications design is based on the virtual private network (VPN) concept. Renal patients have a minimum reliable access to the VCRS through a public switch telephone network--X.25 gateway. Design complies with the universal access requirement, allowing an efficient and inexpensive connection even in rural environments and reducing computational requirements in the patient's remote access unit. VCRS provides support for renal patients' healthcare, increasing the quality and quantity of monitored biomedical signals, predicting events as hypotension or low dialysis dose, assisting further to avoid them by an online therapy modification and easing diagnostic tasks. An online therapy adjustment experiment simulation is presented. Finally, the presented system serves as a computational aid for research in renal physiology. This is achieved by an open and reusable modeling and simulation architecture which allows the interaction among models and data from different scales and computer platforms, and a faster transference of investigation models toward clinical applications.     

Propagation of measurement noise through backprojection reconstruction in electrical impedance tomography

A framework to analyze the propagation of measurement noise through backprojection reconstruction algorithms in electrical impedance tomography (EIT) is presented. Two measurement noise sources were considered: noise in the current drivers and in the voltage detectors. The influence of the acquisition system architecture (serial/semi-parallel) is also discussed. Three variants of backprojection reconstruction are studied: basic (unweighted), weighted and exponential backprojection. The results of error propagation theory have been compared with those obtained from simulated and experimental data. This comparison shows that the approach provides a good estimate of the reconstruction error variance. It is argued that the reconstruction error in EIT images obtained via backprojection can be approximately modeled as a spatially nonstationary Gaussian distribution. This methodology allows us to develop a spatial characterization of the reconstruction error in EIT images.     

Enantiomer separation by countercurrent chromatography using cinchona alkaloid derivatives as chiral selectors

Cinchona-derived anion-exchange-type chiral selectors have been adapted and employed in countercurrent chromatography (CCC) for the separation of enantiomers of N-derivatized amino acids and 2-aryloxypropionic acids. The accurate optimization of the enantioseparation in terms of solvent system composition, pH values, ionic strength, and CCC operating conditions was performed. A wide range of solvent mixtures was evaluated. Successful resolutions were achieved in systems such as ammonium acetate buffer/tert-amyl alcohol/methanol/heptane and especially ammonium acetate buffer/methyl isobutyl ketone or diisopropyl ether. Up to 300 mg (0.92 mmol) of N-(3,5-dinitrobenzoyl)-(+/-)-leucine was totally resolved in a single run using a 10 mM concentration of chiral selector in 122 mL of stationary phase. This amount could be increased up to 900 mg (2.77 mmol) when pH-zone-refining mode was applied. The results here presented account for the high potential of CCC as a preparative enantiomer separation technique.