Age replacement policy in a random environment using systemability

Preventive maintenance is a group of maintenance policies based on preventive actions in order to predate the failure of a component or a system. Usually, these policies are designed using a series of data related to the studied units. All policies do not consider the effect of the environment where the components or systems operate. In this article, one of the most used policies, the age replacement policy, is also discussed taking into consideration the environmental effects using an innovative concept, introduced by Pham, called systemability. Several numerical examples are carried out in order to illustrate the aim of this work. The importance of environmental factors is also demonstrated thanks to the application to a real case.     

Accurate junction detection and characterization in line-drawing images

In this paper, we present a new approach for junction detection and characterization in line-drawing images. We formulate this problem as searching for optimal meeting points of median lines. In this context, the main contribution of the proposed approach is three-fold. First, a new algorithm for the determination of the support region is presented using the linear least squares technique, making it robust to digitization effects. Second, an efficient algorithm is proposed to detect and conceptually remove all distorted zones, retaining reliable line segments only. These line segments are then locally characterized to form a local structure representation of each crossing zone. Finally, a novel optimization algorithm is presented to reconstruct the junctions. Junction characterization is then simply derived. The proposed approach is very highly robust to common geometry transformations and can resist a satisfactory level of noise/degradation. Furthermore, it works very efficiently in terms of time complexity and requires no prior knowledge of the document content. Extensive evaluations have been performed to validate the proposed approach using other baseline methods. An application of symbol spotting is also provided, demonstrating quite good results.     

Process synthesis and optimization of biorefinery configurations

Recently, there has been a growing interest in the development of cost‐effective technologies for the production of biofuels. A common approach to biofuel research is to invent or improve a biochemical or thermochemical conversion step. Subsequently, other conversion and separation steps are added to form a complete biorefinery flowsheet. Because this approach is structured around a specific conversion step, it may limit the possibilities of configuring optimal and innovative biorefineries. This article proposes a novel and systematic two‐stage approach to the synthesis and optimization of biorefinery configurations, given available feedstocks and desired products. In the synthesis stage, a systems‐based approach is developed to create a methodical way for synthesizing integrated biorefineries. This method is referred to as “forward‐backward” approach. It involves forward synthesis of biomass to possible intermediates and reverse synthesis starting with the desired products and identifying necessary species and pathways leading to them. In the optimization stage, Bellman's principle of optimality is applied to decompose the optimization problem into subproblems in which an optimal policy of available technologies is determined for every conversion step. An optimization formulation is utilized to determine the optimal configuration based on screening and connecting the optimal policies and generating the biorefinery flowsheet. A case study of alcohol‐producing pathways from lignocellulosic biomass is solved to demonstrate the merits of the proposed approach. © 2011 American Institute of Chemical Engineers AIChE J, 2012     

Pd coated one-dimensional Ag nanostructures: Controllable architecture and their electrocatalytic performance for ethanol oxidation in alkaline media

One-dimensional (1D) metal-coated Pd structures are efficient catalysts for the ethanol electro-oxidation and promising strategy for minimizing the Pd-loading toward commercialization of direct ethanol fuel cells (DEFCs). Herein, the decorated and core-shell architectures of a novel Pd coating on Ag nanowires (PdAg-NWs) are controllable by a two-step polyol method based on the galvanic replacement reaction. The integration of uniform shell with a low Pd concentration and partial hollow structure onto 1D PdAg-NWs exhibits the highest efficiency for ethanol oxidation reaction (EOR) in alkaline solution. In comparison with Pd nanoparticles (PdNPs/C), the PdAgNWs/C performes 11 times superior EOR activity, and the onset potential shifts 80 mV negatively. The presence of Ag in PdAg-NWs enhances the absorption capacity of ethanol molecules and hydroxyl ions on the active sites, and improves the catalyst tolerance to CO-like intermediates, making them a potential anodic catalyst for DEFCs.     

Flexible Piezoelectric Acoustic Sensors and Machine Learning for Speech Processing

Flexible piezoelectric acoustic sensors have been developed to generate multiple sound signals with high sensitivity, shifting the paradigm of future voice technologies. Speech recognition based on advanced acoustic sensors and optimized machine learning software will play an innovative interface for artificial intelligence (AI) services. Collaboration and novel approaches between both smart sensors and speech algorithms should be attempted to realize a hyperconnected society, which can offer personalized services such as biometric authentication, AI secretaries, and home appliances. Here, representative developments in speech recognition are reviewed in terms of flexible piezoelectric materials, self-powered sensors, machine learning algorithms, and speaker recognition.     

Mac-A-Mal: macOS malware analysis framework resistant to anti evasion techniques

Journal of Computer Virology and Hacking Techniques - With macOS increasing popularity, the number, and variety of macOS malware are rising as well. Yet, very few tools exist for dynamic analysis...     

Gene Discovery in Gelsemium Highlights Conserved Gene Clusters in Monoterpene Indole Alkaloid Biosynthesis

Genome mining is a routine technique in microbes for discovering biosynthetic pathways. In plants, however, genomic information is not commonly used to identify novel biosynthesis genes. Here, we present the genome of the medicinal plant and oxindole monoterpene indole alkaloid (MIA) producer Gelsemium sempervirens (Gelsemiaceae). A gene cluster from Catharanthus roseus, which is utilized at least six enzymatic steps downstream from the last common intermediate shared between the two plant alkaloid types, is found in G. sempervirens, although the corresponding enzymes act on entirely different substrates. This study provides insights into the common genomic context of MIA pathways and is an important milestone in the further elucidation of the Gelsemium oxindole alkaloid pathway.