Selection of materials for marine instruments

The paper describes the selection of materials for the reliable operation of oceanographic instruments. For selecting the material, raft immersion tests were carried out for one year. Results of the tests are presented. Comparisons between metals were discussed.

Computer-based selection of joining processes

The assembly of any manufactured product involves joining. This paper describes ways of selecting processes for joining. The method allows discrimination of the joint geometry, joint loading, material, and other attributes of the joint itself, identifying the subset of available processes capable of meeting a given set of design constraints. A relational database containing data-tables for joining processes, materials to be joined, and joint geometry and mode of loading, allows the attributes of each of these to be stored in an appropriate format, and permits links to be created between those that are related. A search engine isolates the processes that meet design requirements on material, joint geometry and loading. The method is illustrated in Part 2 by case studies, utilising software that embodies the method.

Determination of some dominant genetic characteristics and morpho-meristic features for selection of rainbow trout (Oncorhynchus mykiss) broodstocks

In this study, Iranian and French male and female Oncorhynchus mykiss broodstocks were divided into two groups 50 and 24 respectively in Research center of genetic and breeding of coldwater fishes, Yasouj, Iran and the genetic structure of them was investigated using 6 microsatellite markers. Then 19 morphometric and 5 meristic of broodstock were measured and compared in two populations. Along with broodstock maturation, fertilization 1:1(female:male) were randomly assigned and occurred in 25 of 12 Iranian and French treatment respectively. Reproductive parameters were recorded for the whole family. Average number of observed alleles in Iranian and French stocks was 6.68 and 6.83, respectively. Average number of effective alleles in Iranian and French stocks was 3.13 and 3.45 respectively. Fixation index Fst was calculated based on allelic frequency between two stocks was 0.058 with significant difference between 2 stocks. Morphometric analysis showed significant difference between two stocks in 8 characteristics. Meristic characters was without significant difference in broodstock groups. Eyed percentage for french broodstock calculated zero and deleted. Fertilization rate (100-0), the eyed percentage (98- 0), The hatch rate (98-0), the average fecundity 4114.708, the average eggs size 4.88 mm, Survival in the first three months 19-73% calculated for Iranian broodstocks. Considering the quality of eggs and larvae at different stages and selection between the different family and the within family remained 10 treatments and are kept as future broodstocks. The relationship between fecundity - egg size, fecundity - weight , fecundity - length, egg size- weight was performed using regression. The results showed that Fecundity was influenced more by weight and productive length. The research is beginning to ID the broodstock in our country.

Face-based Selection of Corners in 3D Substructuring

In most recent substructuring methods, a fundamental role is played by the coarse space. For some of these methods (e.g. BDDC and FETI-DP), its definition relies on a 'minimal' set of coarse nodes (sometimes called corners) which assures invertibility of local subdomain problems and also of the global coarse problem. This basic set is typically enhanced by enforcing continuity of functions at some generalized degrees of freedom, such as average values on edges or faces of subdomains. We revisit existing algorithms for selection of corners. The main contribution of this paper consists of proposing a new heuristic algorithm for this purpose. Considering faces as the basic building blocks of the interface, inherent parallelism, and better robustness with respect to disconnected subdomains are among features of the new technique. The advantages of the presented algorithm in comparison to some earlier approaches are demonstrated on three engineering problems of structural analysis solved by the BDDC method.

Neuro-Fuzzy genetic system for selection of construction project managers

Choosing a project manager for a construction project—particularly, large projects—is a critical project decision. The selection process involves different criteria and should be in accordance with company policies and project specifications. Traditionally, potential candidates are interviewed and the most qualified are selected in compliance with company priorities and project conditions. Precise computing models that could take various candidates’ information into consideration and then pinpoint the most qualified person with a high degree of accuracy would be beneficial. On the basis of the opinions of experienced construction company managers, this paper, through presenting a fuzzy system, identifies the important criteria in selecting a project manager. The proposed fuzzy system is based on IF-THEN rules; a genetic algorithm improves the overall accuracy as well as the functions used by the fuzzy system to make initial estimates of the cluster centers for fuzzy c-means clustering. Moreover, a back-propagation neutral network method was used to train the system. The optimal measures of the inference parameters were identified by calculating the system’s output error and propagating this error within the system. After specifying the system parameters, the membership function parameters—which by means of clustering and projection were approximated—were tuned with the genetic algorithm. Results from this system in selecting project managers show its high capability in making high-quality personnel predictions