Design structure matrix (DSM) method application to issue of modeling and analyzing the fault tree of a wind energy asset

The perpetual energy production of a wind farm could be accomplished (under proper weather conditions) if no failures occurred. But even the best possible design, manufacturing, and maintenance of a system cannot eliminate the failure possibility. In order to understand and minimize the system failures, the most crucial components of the wind turbines, which are prone to failures, should be identified. Moreover, it is essential to determine and classify the criticality of the system failures according to the impact of these failure events on wind turbine safety. The present study is processing the failure data from a wind farm and uses the Fault Tree Analysis as a baseline for applying the Design Structure Matrix technique to reveal the failure and risk interactions between wind turbine subsystems. Based on the analysis performed and by introducing new importance measures, the “readiness to fail” of a subsystem in conjunction with the “failure riskiness” can determine the “failure criticality.” The value of the failure criticality can define the frame within which interventions could be done. The arising interventions could be applied either to the whole system or could be focused in specified pairs of wind turbine subsystems. In conclusion, the method analyzed in the present research can be effectively applied by the wind turbine manufacturers and the wind farm operators as an operation framework, which can lead to a limited (as possible) design‐out maintenance cost, failures' minimization, and safety maximization for the whole wind turbine system.     

Detection and mitigation of monitor identification attacks in collaborative intrusion detection systems

Collaborative defensive approaches such as collaborative intrusion detection system (CIDS) have emerged as a response to the continuous increase in the sophistication of cyberattacks. Such systems utilize a plethora of heterogeneous monitors to create a holistic picture of the monitored network. A number of research institutes deploy CIDSs that publish their alert data publicly over the Internet. This is important for researchers and security administrators, as such systems provide a source of real‐world alert data for experimentation. However, a class of identification attacks exists, namely probe‐response attacks (PRAs), which can significantly reduce the benefits of a CIDS. In particular, such attacks allow an adversary to detect the network location of the monitors of a CIDS. This article discusses the state of the art, with an emphasis on our previous and ongoing work, with regard to the detection and the mitigation of PRAs. We compare the most promising defensive mechanisms with respect to their effectiveness and the possible negative effects they might introduce to the CIDS. Finally, we provide a thorough discussion of research gaps and possible future directions for the field.     

SLAM for autonomous planetary rovers with global localization

This paper describes a novel approach to simultaneous localization and mapping (SLAM) techniques applied to the autonomous planetary rover exploration scenario to reduce both the relative and absolute localization errors, using two well‐proven techniques: particle filters and scan matching. Continuous relative localization is improved by matching high‐resolution sensor scans to the online created local map. Additionally, to avoid issues with drifting localization, absolute localization is globally corrected at discrete times, according to predefined event criteria, by matching the current local map to the orbiter's global map. The resolutions of local and global maps can be appropriately chosen for computation and accuracy purposes. Further, the online generated local map, of the form of a structured elevation grid map, can also be used to evaluate the traversability of the surrounding environment and allow for continuous navigation. The objective of this study is to support long‐range low‐supervision planetary exploration. The implemented SLAM technique has been validated with a data set acquired during a field test campaign performed at the Teide Volcano on the island of Tenerife, representative of a Mars/Moon exploration scenario.     

Efficient Money Burning in General Domains

We study mechanism design where the objective is to maximize the residual surplus, i.e., the total value of the outcome minus the payments charged to the agents, by truthful mechanisms. The motivation comes from applications where the payments charged are not in the form of actual monetary transfers, but take the form of wasted resources. We consider a general mechanism design setting with m discrete outcomes and n multidimensional agents. We present two randomized truthful mechanisms that extract an O(logm) fraction of the maximum social surplus as residual surplus. The first mechanism achieves an O(logm)-approximation to the social surplus, which is improved to an O(1)-approximation by the second mechanism. An interesting feature of the second mechanism is that it optimizes over an appropriately restricted space of probability distributions, thus achieving an efficient tradeoff between social surplus and the total amount of payments charged to the agents.     

A wavelet-based Markov random field segmentation model in segmenting microarray experiments

In the present study, an adaptation of the Markov Random Field (MRF) segmentation model, by means of the stationary wavelet transform (SWT), applied to complementary DNA (cDNA) microarray images is proposed (WMRF). A 3-level decomposition scheme of the initial microarray image was performed, followed by a soft thresholding filtering technique. With the inverse process, a Denoised image was created. In addition, by using the Amplitudes of the filtered wavelet Horizontal and Vertical images at each level, three different Magnitudes were formed. These images were combined with the Denoised one to create the proposed SMRF segmentation model. For numerical evaluation of the segmentation accuracy, the segmentation matching factor (SMF), the Coefficient of Determination (r²), and the concordance correlation (p_c) were calculated on the simulated images. In addition, the SMRF performance was contrasted to the Fuzzy C Means (FCM), Gaussian Mixture Models (GMM), Fuzzy GMM (FGMM), and the conventional MRF techniques. Indirect accuracy performances were also tested on the experimental images by means of the Mean Absolute Error (MAE) and the Coefficient of Variation (CV). In the latter case, SPOT and SCANALYZE software results were also tested. In the former case, SMRF attained the best SMF, r², and p_c (92.66%, 0.923, and 0.88, respectively) scores, whereas, in the latter case scored MAE and CV, 497 and 0.88, respectively. The results and support the performance superiority of the SMRF algorithm in segmenting cDNA images.     

Digital Cities: Towards an integrated decision support methodology

This paper deals with the problem of the low ICT adoption rate by many cities or urban regions. The consequences of the poor ICT environment in these authorities may be summarized into (i) the cutback of local business competitiveness, (ii) the incapability of attracting new business investments, (iii) the poor service of citizens needs (living in the local area or abroad – a foreign country or another city, namely emigrants), (iv) the poor service of visitors that have or want to have transactions in the local area. The main shortcomings of local authorities refer to lack of capabilities and expertise, negligence of local needs and urban characteristics, absence of ICT adoption models to local needs, ignorance of development and exploitation models etc. These regions need support so as to select the most appropriate ICT best practices, integrated them into their strategic plans and implement them with success. This procedure is particularly complex, since many factors and restrictions have to be considered. The overall objective of this paper is to illustrate the Digital City concept and to propose an integrated methodology for Digital City development that will act in a supportive way for the regions or cities that have low rates in ICT penetration and try to adopt ICT best practices into their core functions and services.     

Comparison of direct steam injection and steam-jacketed heating in squid protein hydrolysis for energy consumption and hydrolysis performance

Direct steam injection (DSI) and conventional steam-jacketed (SJ) heating systems were compared for energy consumption and hydrolysis performance in producing squid hydrolysates (SH). Hydrolysis was carried out with endogenous enzymes at 55 °C for 90 min and native pH (6.5 ± 0.2), followed by pasteurization at 75 °C for 30 min. Hydrolysis performance was evaluated by monitoring the changes in viscosity, degree of hydrolysis (DH), and protein profile during the course of hydrolysis. The DSI heating process was more energy efficient than SJ heating with significantly less energy usage (∼30% energy reduction), shorter come-up times, and total processing time. While considerable fouling was evident with SJ heating, no fouling was observed with DSI heating. No appreciable differences in hydrolysis performance were observed between DSI and SJ heating, although the DSI-treated hydrolysate exhibited slightly lower values in viscosity and DH, as well as weaker protein band intensities due to dilution caused by steam condensation. The use of a steam filtration unit in DSI not only filtered the incoming steam, but also reduced condensation. Results suggest that DSI heating with steam filtration is an energy efficient and fouling-free process for preparing SH and potentially for other type of enzymatic protein hydrolysates.     

Femtosecond Dynamics in Single Wall Carbon Nanotube/Poly(3-Hexylthiophene) Composites

Femtosecond transient absorption measurements on single wall carbon nanotube/poly(3-hexylthiophene) composites are used to investigate the relaxation dynamics of this blended material. The influence of the addition of nanotubes in polymer matrix on the ultrashort relaxation dynamics is examined in detail. The introduction of nanotube/polymer heterojunctions enhances the exciton dissociation and quenches the radiative recombination of composites. The relaxation dynamics of these composites are compared with the fullerene derivative-polymer composites with the same matrix. These results provide explanation to the observed photovoltaic performance of two types of composites.     

Giant Ferroelectric Polarization in Ultrathin Ferroelectrics via Boundary‐Condition Engineering

Tailoring and enhancing the functional properties of materials at reduced dimension is critical for continuous advancement of modern electronic devices. Here, the discovery of local surface induced giant spontaneous polarization in ultrathin BiFeO₃ ferroelectric films is reported. Using aberration‐corrected scanning transmission electron microscopy, it is found that the spontaneous polarization in a 2 nm‐thick ultrathin BiFeO₃ film is abnormally increased up to ≈90–100 µC cm^?2 in the out‐of‐plane direction and a peculiar rumpled nanodomain structure with very large variation in c /a ratios, which is analogous to morphotropic phase boundaries (MPBs), is formed. By a combination of density functional theory and phase‐field calculations, it is shown that it is the unique single atomic Bi₂O_3?x layer at the surface that leads to the enhanced polarization and appearance of the MPB‐like nanodomain structure. This finding clearly demonstrates a novel route to the enhanced functional properties in the material system with reduced dimension via engineering the surface boundary conditions.