Aerodynamic optimization via multi-objective micro-genetic algorithm with range adaptation,knowledge-based reinitialization,crowding and ε-dominance

In this study, an optimization of the airfoil of a sailplane is carried out by a recently developed multi-objective genetic algorithm based on microevolution, containing crowding, range adaptation, knowledge-based reinitialization and ε-dominance. Its efficiency was tested on a set of test problems. The results are encouraging, suggesting that very small populations can be used effectively to solve real-world multi-objective optimization problems in many cases of interest.     

Plastic strain-controlled short crack growth and fatigue life

Constant plastic strain-controlled and constant stress-controlled tests were performed on smooth and lightly notched specimens machined from a massive forging of 42CrMo4 steel. Comparison of the fatigue life curves plotted as function of the plastic strain amplitude and stress amplitude shows a decisive role of plastic strain amplitude. Crack initiation and the kinetics of short crack growth were studied in constant plastic strain amplitude loading and the relation between the crack growth coefficient and plastic strain amplitude was established. This is equivalent to the Coffin–Manson law and shows that the Coffin–Manson law can be interpreted in terms of short crack growth.     

Distributed algorithms for barrier coverage using relocatable sensors

We study the barrier coverage problem using relocatable sensor nodes. We assume each sensor can sense an intruder or event inside its sensing range. Sensors are initially located at arbitrary positions on the barrier and can move along the barrier. The goal is to find final positions for sensors so that the entire barrier is covered. In recent years, the problem has been studied extensively in the centralized setting. In this paper, we study a barrier coverage problem in the distributed and discrete setting. We assume that we have n identical sensors located at grid positions on the barrier, and that each sensor repeatedly executes a Look-Compute-Move cycle: based on what it sees in its vicinity, it makes a decision on where to move, and moves to its next position. We make two strong but realistic restrictions on the capabilities of sensors: they have a constant visibility range and can move only a constant distance in every cycle. In this model, we give the first two distributed algorithms that achieve barrier coverage for a line segment barrier when there are enough nodes in the network to cover the entire barrier. Our algorithms are synchronous, and local in the sense that sensors make their decisions independently based only on what they see within their constant visibility range. One of our algorithms is oblivious whereas the other uses two bits of memory at each sensor to store the type of move made in the previous step. We show that our oblivious algorithm terminates within \(\varTheta (n^2)\) steps with the barrier fully covered, while the constant-memory algorithm is shown to take \(\varTheta (n)\) steps to terminate in the worst case. Since any algorithm in which a sensor can only move a constant distance in one step requires \(\varOmega (n)\) steps on some inputs, our second algorithm is asymptotically optimal.     

Mechanochemical synthesis of ternary chalcogenide chalcostibite CuSbS2 and its characterization

Journal of Materials Science: Materials in Electronics - In this work, the very rapid one-step mechanochemical synthesis of nanocrystalline ternary chalcogenide chalcostibite CuSbS2 prepared from...     

Automated resolution of connector architectures using constraint solving (ARCAS method)

In current software systems, connectors play an important role by encapsulating the communication and coordination logic. Since they share common patterns (elements) depending on characteristics of the connections, the elements can be predefined and reused. A method of connector implementation based on a composition of predefined elements naturally comprises two steps: resolution of the connector architecture, and creation of the actual connector code based on the architecture. However, manual resolution of a connector architecture is very difficult due to the number of factors to be considered. Thus, the challenge is to come up with an automated method, able to address all the important factors. In this paper, we present a method for automated resolution of connector architectures based on constraint solving techniques. We exploit a propositional logic with relational calculus for defining a connector theory, a constraint specification reflecting both the predefined parts and the important resolution factors, and employ a constraint solver to find a suitable connector architecture as a model of the theory. As a proof of the concept, we show how the theory can be captured in the Alloy language and resolved via the Alloy Analyzer.     

Variation in fatty acid composition of ewes' colostrum and mature milk fat

Temporal content variations of approximately 70 C4–C24 fatty acids (FA) in colostrum and milk of ewes consuming winter diet were determined by gas chromatography. The content of monounsaturated, polyunsaturated and straight-chain saturated FA 14:0–16:0 in colostrum was higher whereas the content of 4:0–12:0, 18:0 and branched-chain saturated FA 15:0–17:0 was lower than that in mature milk. The effect of ewe breed on the FA profiles was not significant. The composition of FA changed most significantly 1–2 days after lambing in agreement with the time schedule of colostrum formation. Nevertheless, the content of FA further successively changed up to approximately the 6th day of lactation, whereas further changes up to the 60th day of lactation were smaller. This is consistent with the recommendation that ewes' milk is suitable for human consumption after six-to-eight days of lactation. The higher contents of palmitic and myristic acids in colostrum compared with mature milk suggest that FA composition in colostrum matches the changing needs of the growing lambs.