A methodology to measure the interface shear strength by means of the fiber push-in test

A methodology is presented to measure the fiber/matrix interface shear strength in composites. The strategy is based on performing a fiber push-in test at the central fiber of highly-packed fiber clusters with hexagonal symmetry which are often found in unidirectional composites with a high volume fraction of fibers. The mechanics of this test was analyzed in detail by means of three-dimensional finite element simulations. In particular, the influence of different parameters (interface shear strength, toughness and friction as well as fiber longitudinal elastic modulus and curing stresses) on the critical load at the onset of debonding was established. From the results of the numerical simulations, a simple relationship between the critical load and the interface shear strength is proposed. The methodology was validated in an unidirectional C/epoxy composite and the advantages and limitations of the proposed methodology are indicated.

Detailed damage mechanisms assessment in composite materials by means of X-ray tomography

This research focused on the evaluation of damage formation on ±45º carbon fiber laminates subjected to tensile tests. The damage was evaluated by means of X-ray tomography. A high density of cracks developed during the plateau of the stress-strain curve and were qualitatively analyzed, showing that the inner plies eventually developed a higher crack concentration than the outer plies. Delamination started to occur in the outermost ply interface when the slope after the plateau of the stress-strain curve began to increase.

Adaptive neuro-fuzzy inference systems (ANFIS) for supervised classification of competence in MIS based on psychomotor skills

INTRODUCTION: Objective assessment of motor skills has become an important challenge in minimally invasive surgery (MIS) training.Currently, there is no gold standard defining and determining the residents' surgical competence.To aid in the decision process, we analyze the validity of a supervised classifier to determine the degree of MIS competence based on assessment of psychomotor skills METHODOLOGY: The ANFIS is trained to classify performance in a box trainer peg transfer task performed by two groups (expert/non expert). There were 42 participants included in the study: the non-expert group consisted of 16 medical students and 8 residents (< 10 MIS procedures performed), whereas the expert group consisted of 14 residents (> 10 MIS procedures performed) and 4 experienced surgeons. Instrument movements were captured by means of the Endoscopic Video Analysis (EVA) tracking system. Nine motion analysis parameters (MAPs) were analyzed, including time, path length, depth, average speed, average acceleration, economy of area, economy of volume, idle time and motion smoothness. Data reduction was performed by means of principal component analysis, and then used to train the ANFIS net. Performance was measured by leave one out cross validation. RESULTS: The ANFIS presented an accuracy of 80.95%, where 13 experts and 21 non-experts were correctly classified. Total root mean square error was 0.88, while the area under the classifiers' ROC curve (AUC) was measured at 0.81. DISCUSSION: We have shown the usefulness of ANFIS for classification of MIS competence in a simple box trainer exercise. The main advantage of using ANFIS resides in its continuous output, which allows fine discrimination of surgical competence. There are, however, challenges that must be taken into account when considering use of ANFIS (e.g. training time, architecture modeling). Despite this, we have shown discriminative power of ANFIS for a low-difficulty box trainer task, regardless of the individual significances between MAPs. Future studies are required to confirm the findings, inclusion of new tasks, conditions and sample population.

Control of a solar dryer through using a fuzzy logic and low-cost model-based sensor

Solar drying is one of the important processes used for extending the shelf life of agricultural products. Regarding consumer requirements, solar drying should be more suitable in terms of curtailing total drying time and preserving product quality. Therefore, the objective of this study was to develop a fuzzy logic-based control system, which performs a ?human-operator-like? control approach through using the previously developed low-cost model-based sensors. Fuzzy logic toolbox of MatLab and Borland C++ Builder tool were utilized to develop a required control system. An experimental solar dryer, constructed by CONA SOLAR (Austria) was used during the development of the control system. Sensirion sensors were used to characterize the drying air at different positions in the dryer, and also the smart sensor SMART-1 was applied to be able to include the rate of wood water extraction into the control system (the difference of absolute humidity of the air between the outlet and the inlet of solar dryer is considered by SMART-1 to be the extracted water). A comprehensive test over a 3 week period for different fuzzy control models has been performed, and data, obtained from these experiments, were analyzed. Findings from this study would suggest that the developed fuzzy logic-based control system is able to tackle difficulties, related to the control of solar dryer process.

Hybrid incremental modeling based on least squares and fuzzy K-NN for monitoring tool wear in turning processes

There is now an emerging need for an efficient modeling strategy to develop a new generation of monitoring systems. One method of approaching the modeling of complex processes is to obtain a global model. It should be able to capture the basic or general behavior of the system, by means of a linear or quadratic regression, and then superimpose a local model on it that can capture the localized nonlinearities of the system. In this paper, a novel method based on a hybrid incremental modeling approach is designed and applied for tool wear detection in turning processes. It involves a two-step iterative process that combines a global model with a local model to take advantage of their underlying, complementary capacities. Thus, the first step constructs a global model using a least squares regression. A local model using the fuzzy k-nearest-neighbors smoothing algorithm is obtained in the second step. A comparative study then demonstrates that the hybrid incremental model provides better error-based performance indices for detecting tool wear than a transductive neurofuzzy model and an inductive neurofuzzy model.

Woolliness assessment in peaches (Cv. Springcrest) by sensory and instrumental means.

Mealiness is a negative attribute of sensory texture, characterised by the lack of juiciness without variation of total water content in the tissues. In peaches, mealiness is also known as "woolliness" and "leatheriness". This internal disorder is characterised by the lack of juiciness and flavour. In peaches, it is associated with interna browning near the stone and the incapacity of ripening although there is externa ripe appearance. Woolliness is associated with inadequate cold storage and is considered as a physiological disorder that appears in stone fruits when an unbalanced pectolitic enzyme activity during storage occurs (Kailasapathy and Melton, 1992). Many attempts have been carried out to identify and measure mealiness and woolliness in fruits. The texture of a food product is composed by a wide spectrum of sensory attributes. Consumer defines the texture integrating simultaneously all the sensory attributes. However, an instrument assesses one or several parameters related to a fraction of the texture spectrum (Kramer, 1973). The complexity of sensory analysis by means of trained panels to assess the quality of some producing processes, supports the attempt to estimate texture characteristics by instrumental means. Some studies have been carried out comparing sensory and instrumental methods to assess mealiness and woolliness. The current study is centered on analysis and evaluation of woolliness in peaches and is part of the European project FAIR CT95 0302 "Mealiness in fruits: consumer perception and means for detection". The main objective of this study was to develop procedures to detect woolly peaches by sensory and by instrumental means, as well as to compare both measuring procedures.

A fuzzy approach to risk analysis in information systems

Assets are interrelated in risk analysis methodologies for information systems promoted by international standards. This means that an attack on one asset can be propagated through the network and threaten an organization's most valuable assets. It is necessary to valuate all assets, the direct and indirect asset dependencies, as well as the probability of threats and the resulting asset degradation. These methodologies do not, however, consider uncertain valuations and use precise values on different scales, usually percentages. Linguistic terms are used by the experts to represent assets values, dependencies and frequency and asset degradation associated with possible threats. Computations are based on the trapezoidal fuzzy numbers associated with these linguistic terms.

A fuzzy MCDA framework for safety assessment in the remediation of a uranium mill tailings site in Ukraine

The Pridneprovsky Chemical Plant was one of the largest uranium processing enterprises in the former USSR, producing a huge amount of uranium residues. The Zapadnoe tailings site contains most of these residues. We propose a theoretical framework based on multicriteria decision analysis and fuzzy logic to analyze different remediation alternatives for the Zapadnoe tailings, which simultaneously accounts for potentially conflicting economic, social and environmental objectives. We build an objective hierarchy that includes all the relevant aspects. Fuzzy rather than precise values are proposed for use to evaluate remediation alternatives against the different criteria and to quantify preferences, such as the weights representing the relative importance of criteria identified in the objective hierarchy. Finally, we suggest that remediation alternatives should be evaluated by means of a fuzzy additive multi-attribute utility function and ranked on the basis of the respective trapezoidal fuzzy number representing their overall utility.

A fuzzy extension of MAGERIT methodology for risk analysis in information systems

We propose a fuzzy approach to deal with risk analysis for information systems. We extend MAGERIT methodology that valuates the asset dependencies to a fuzzy framework adding fuzzy linguistic terms to valuate the different elements (terminal asset values, asset dependencies as well as the probability of threats and the resulting asset degradation) in risk analysis. Computations are based on the trapezoidal fuzzy numbers associated with these linguistic terms and, finally, the results of these operations are translated into a linguistic term by means of a similarity function.

Evaluation of the reliability of commercial concentrator triple-junction solar cells by means of accelerated life tests (ALT)

A temperature accelerated life test on commercial concentrator lattice-matched GaInP/GaInAs/Ge triple-junction solar cells has been carried out. The solar cells have been tested at three different temperatures: 119, 126 and 164 °C and the nominal photo-current condition (820 X) has been emulated by injecting current in darkness. All the solar cells have presented catastrophic failures. The failure distributions at the three tested temperatures have been fitted to an Arrhenius-Weibull model. An Arrhenius activation energy of 1.58 eV was determined from the fit. The main reliability functions and parameters (reliability function, instantaneous failure rate, mean time to failure, warranty time) of these solar cells at the nominal working temperature (80 °C) have been obtained. The warranty time obtained for a failure population of 5 % has been 69 years. Thus, a long-term warranty could be offered for these particular solar cells working at 820 X, 8 hours per day at 80 °C.

Vibration reduction for vision systems on board unmanned aerial vehicles using a neuro-fuzzy controller

In this paper, an intelligent control approach based on neuro-fuzzy systems performance is presented, with the objective of counteracting the vibrations that affect the low-cost vision platform onboard an unmanned aerial system of rotating nature. A scaled dynamical model of a helicopter is used to simulate vibrations on its fuselage. The impact of these vibrations on the low-cost vision system will be assessed and an intelligent control approach will be derived in order to reduce its detrimental influence. Different trials that consider a neuro-fuzzy approach as a fundamental part of an intelligent semi-active control strategy have been carried out. Satisfactory results have been achieved compared to those obtained by means of vibration reduction passive techniques.

Fuzzy MCDA for remediation of a uranium tailing

The Pridneprovsky Chemical Plant was a largest uranium processing enterprises, producing a huge amount of uranium residues. The Zapadnoe tailings site contains the majority of these residues. We propose a theoretical framework based on Multi-Criteria Decision Analysis and fuzzy logic to analyse different remediation alternatives for the Zapadnoe tailings, in which potentially conflicting economic, radiological, social and environmental objectives are simultaneously taken into account. An objective hierarchy is built that includes all the relevant aspects. Fuzzy rather than precise values are proposed for use to evaluate remediation alternatives against the different criteria and to quantify preferences, such as the weights representing the relative importance of criteria identified in the objective hierarchy. Finally, it is proposed that remediation alternatives should be evaluated by means of a fuzzy additive multi-attribute utility function and ranked on the basis of the respective trapezoidal fuzzy number representing their overall utility.

The Balanced Cross-Layer Design Routing Algorithm in Wireless Sensor Networks Using Fuzzy Logic

Recently, the cross-layer design for the wireless sensor network communication protocol has become more and more important and popular. Considering the disadvantages of the traditional cross-layer routing algorithms, in this paper we propose a new fuzzy logic-based routing algorithm, named the Balanced Cross-layer Fuzzy Logic (BCFL) routing algorithm. In BCFL, we use the cross-layer parameters’ dispersion as the fuzzy logic inference system inputs. Moreover, we give each cross-layer parameter a dynamic weight according the value of the dispersion. For getting a balanced solution, the parameter whose dispersion is large will have small weight, and vice versa. In order to compare it with the traditional cross-layer routing algorithms, BCFL is evaluated through extensive simulations. The simulation results show that the new routing algorithm can handle the multiple constraints without increasing the complexity of the algorithm and can achieve the most balanced performance on selecting the next hop relay node. Moreover, the Balanced Cross-layer Fuzzy Logic routing algorithm can adapt to the dynamic changing of the network conditions and topology effectively.

Determination of spectral variations by means of component cells useful for CPV rating and design

A methodology is presented to determine both the short-term and the long-term influence of the spectral variations on the performance of Multi-Junction (MJ) solar cells and Concentrating "This is the peer reviewed version of the following article: R. Núñez, C. Domínguez, S. Askins, M. Victoria, R. Herrero, I. Antón, and G. Sala, “Determination of spectral variations by means of component cells useful for CPV rating and design,” Prog. Photovolt: Res. Appl., 2015., which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/pip.2715/full. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving [http://olabout.wiley.com/WileyCDA/Section/id-820227.html#terms]." Photovoltaic (CPV) modules. Component cells with the same optical behavior as MJ solar cells are used to characterize the spectrum. A set of parameters, namely Spectral Matching Ratios (SMRs), is used to characterize spectrally a particular Direct Normal Irradiance (DNI) by comparison to the reference spectrum (AM1.5D-ASTM-G173-03). Furthermore, the spectrally corrected DNI for a given MJ solar cell technology is defined providing a way to estimate the losses associated to the spectral variations. The last section analyzes how the spectrum evolves throughout a year in a given place and the set of SMRs representative for that location are calculated. This information can be used to maximize the energy harvested by the MJ solar cell throughout the year. As an example, three years of data recorded in Madrid shows that losses lower than 5% are expected due to current mismatch for state-of-the-art MJ solar cells.

Hepatitis C virus and other Flaviviridae viruses enter cells via low density lipoprotein receptor

Endocytosis of the Flaviviridae viruses, hepatitis C virus, GB virus C/hepatitis G virus, and bovine viral diarrheal virus (BVDV) was shown to be mediated by low density lipoprotein (LDL) receptors on cultured cells by several lines of evidence: by the demonstration that endocytosis of these virus correlated with LDL receptor activity, by complete inhibition of detectable endocytosis by anti-LDL receptor antibody, by inhibition with anti-apolipoprotein E and -apolipoprotein B antibodies, by chemical methods abrogating lipoprotein/LDL receptor interactions, and by inhibition with the endocytosis inhibitor phenylarsine oxide. Confirmatory evidence was provided by the lack of detectable LDL receptor on cells known to be resistant to BVDV infection. Endocytosis via the LDL receptor was shown to be mediated by complexing of the virus to very low density lipoprotein or LDL but not high density lipoprotein. Studies using LDL receptor-deficient cells or a cytolytic BVDV system indicated that the LDL receptor may be the main but not exclusive means of cell entry of these viruses. Studies on other types of viruses indicated that this mechanism may not be exclusive to Flaviviridae but may be used by viruses that associate with lipoprotein in the blood. These findings provide evidence that the family of LDL receptors may serve as viral receptors.