An ontology for representing financial headline news

This paper presents the development of an ontology to represent financial headline news. This ontology is developed using the On-To-Knowledge methodology where the focus is on the design steps of the Knowledge Meta Process. This development is part of an ongoing project which aims to design a virtual stock market simulator based on multi-agent systems. The proposed ontology has 31 concepts and includes 201 attributes. The testing results conducted on reliable headline news show that 99% of these headline news can be properly represented by the attributes of the right category in the ontology. Unreliable headline news characterized by news having uncertainties, incompleteness, ill-definition, or imprecision cannot be represented by the proposed ontology. Approaches for representing these unreliable headline news are discussed.     

Effect of electrodeposition current density on the microstructure and the degradation of electroformed iron for degradable stents

Pure iron has become one of the most interesting candidate materials for degradable metallic stents due to its high mechanical properties and moderate degradation. In this work we studied the effect of electrodeposition current density on microstructure and degradation of pure iron films electrodeposited on Ti alloy substrate for degradable metallic stent application. Iron sheets were produced by electrodeposition using four different current densities 1, 2, 5 and 10 A dm⁻². The films were then studied by SEM (scanning electron microscope) and EBSD (electron backscatter diffraction) to observe the surface morphology, grain size and orientation. Potentiodynamic polarization and static immersion tests were used to determine the corrosion rate and to study the degradation behavior of iron films, respectively. The current density was found to significantly influence the texture, the grain size and the grain shape of the electrodeposited iron. At current densities of 1, 5 and 10 A dm⁻², weak textures corresponding to 〈1 0 1〉, 〈1 1 1〉 and 〈1 1 2〉 in the normal (electrodeposition) direction were obtained, respectively. At these current densities, average grain sizes smaller than 3 μm were also obtained. However, at 2 A dm⁻², a strong 〈1 1 1〉//ND texture with density of 7.4 MUD was obtained with larger average grain size of 4.4 μm. The microstructure of iron samples changed after annealing at 550 °C because of the induced recrystallization. Different corrosion rates were obtained from potentiodynamic polarization curves of iron films deposited at different current densities because of their microstructures. Fe-2 showed the lowest corrosion rate due to its larger grains size and its texture. The corrosion rates of all iron samples decreased after annealing. Static degradation showed lower corrosion rates for iron because of the formation of a degradation layer on samples surface which reduced the degradation reaction rate. The degradation morphology was uniform for Fe-2 due to its strong texture. On the other hand, microscopic pits were found for Fe-1, Fe-5 and Fe-10.     

Assessing sensor reliability for multisensor data fusion within the transferable belief model.

This paper presents a method for assessing the reliability of a sensor in a classification problem based on the transferable belief model. First, we develop a method for the evaluation of the reliability of a sensor when considered alone. The method is based on finding the discounting factor minimizing the distance between the pignistic probabilities computed from the discounted beliefs and the actual values of data. Next, we develop a method for assessing the reliability of several sensors that are supposed to work jointly and their readings are aggregated. The discounting factors are computed on the basis of minimizing the distance between the pignistic probabilities computed from the combined discounted belief functions and the actual values of data.     

An Innovative Genetic Algorithm for a Multi-Objective Optimization of Two-Dimensional Cutting-Stock Problem

This paper addressed an important variant of two-dimensional cutting stock problem. The objective was not only to minimize trim loss, as in traditional cutting stock problems, but rather to minimize the number of machine setups. This additional objective is crucial for the life of the machines and affects both the time and the cost of cutting operations. Since cutting stock problems are well known to be NP-hard, we proposed an approximate method to solve this problem in a reasonable time. This approach differs from the previous works by generating a front with many interesting solutions. By this way, the decision maker or production manager can choose the best one from the set based on other additional constraints. This approach combined a genetic algorithm with a linear programming model to estimate the optimal Pareto front of these two objectives. The effectiveness of this approach was evaluated through a set of instances collected from the literature. The experimental results for different-size problems show that this algorithm provides Pareto fronts very near to the optimal ones.     

Improvement of thermal performance of spiral heat exchanger on hydrogen storage by adding copper fins

The reaction time of hydrogen in metal-hydride vessels (MHVs for short) is strongly influenced by the heat transfer from/to the hydride bed. In the present work an experimental study of the geometric and the operating parameters of a finned spiral heat exchanger has been carried out to identify their influence on the performance of the charging process of the MHV. The experimental results show that the charge time of the reactor is considerably reduced, when finned spiral heat exchanger is used. In addition, the effect of different parameters (flow mass and temperature of the cooling fluid, applied pressure of hydrogen in the case of absorption and desorption) has been discussed and obtained results show that a good choice of these parameters is important.     

Numerical simulation of heat and mass transfer in metal hydride hydrogen storage tanks for fuel cell vehicles

This paper presents a two-dimensional mathematical model to optimized heat and mass transfer in metal hydride storage tanks (hereinafter MHSTs) for fuel cell vehicles, equipped with finned spiral tube heat exchangers. This model which considers complex heat and mass transfer was numerically solved and validated by comparison with experimental data and a good agreement is obtained.     

Synchronised interrelationship between lipid/protein oxidation analysis and sensory attributes in refrigerated minced beef meat formulated with Punica granatum peel extract

Microbiological, chemical and sensory effects of pomegranate peel ethanol extract (EE) at 0.1, 0.5 and 1% (w w⁻¹) on refrigerated minced beef meat were undertaken. Chemical analyses revealed that the treated meat underwent significant decrease (P < 0.05) of primary and secondary lipid oxidation. By the end of storage, EE at 1% reduced the MetMb, carbonyl group accumulation and the disappearance of sulphydryl proteins by 56.68, 65.71 and 59.69% respectively, compared with control samples. EE at 1% showed also the highest scores for colour, appearance, odour and overall acceptability (OA) attributes using a 9-point hedonic scale. Chemometric approaches showed that lipid/protein oxidation analysis, sensory attributes and storage time allowed the samples discrimination. Oxidative stability parameters were equally used to predict OA by linear regression analysis. The reported data provide an approach to strengthen the interpretation of sensory quality and how they are affected by chemical changes in newly formulated meat products.