No abstract

Abstract:The growth of the blueberry industry in the past three decades has been remarkably robust. However, a labor shortage for hand harvesting, increasingly higher labor costs, and low harvest efficiencies are becoming bottlenecks for sustainable development of the fresh market blueberry production. In this study, we evaluated semi-mechanical harvesting systems consisting of a harvest-aid platform with soft fruit catching surfaces that collected the fruit detached by portable, hand-held, pneumatic shakers. The softer fruit catching surfaces were not glued to the hard sub-surfaces of the harvest-aid platform, but suspended over them. Also, the ergonomic aspect of operating powered harvesting equipment was determined. The pneumatic shakers removed 3.5 to 15 times more fruit (g/min) than by hand. Soft fruit catching surfaces reduced impact force and bruise damage. Fruit firmness was higher in fruit harvested by hand compared to that by pneumatic shakers in some cultivars. The bruise area was less than 8% in fruit harvested by hand and with semi-mechanical harvesting system. The percentage of blue, packable fruit harvested by pneumatic shakers comprised as much as 90% of the total, but less than that of hand-harvested fruit. The ergonomic analysis by electromyography showed that muscle strain in the back, shoulders, and forearms was low in workers operating the light-weight, pneumatic shakers that were tethered to the platform with a tool balancer. The new harvesting method can reduce the labor requirement to about 100 hour/hectare/year and help to mitigate the rising labor cost and shortage of workers for harvesting fresh-market quality blueberries.

The timetabling problem is concerned with the allocation, subject to constraints, of given resources to objects in space and time in such way as to satisfy as nearly as possible a set of desirable objectives. This problem is known to be NP-complete and as such only combinatorial optimization methods can guarantee an optimal timetable. In this paper we propose a sector-based genetic algorithm for solving a university weekly courses timetabling problem. Preliminary experimental results indicate that the algorithm is promising.

User authentication based on keystroke dynamics is concerned with accepting or rejecting someone based on the way the person types. A timing vector is composed of the keystroke duration times interleaved with the keystroke interval times. Which times or features to use in a classifier is a classic feature selection problem. Genetic algorithm based wrapper approach does not only solve the problem, but also provides a population of "fit" classifiers which can be used in ensemble. In this paper, we propose to add uniqueness term in the fitness function of genetic algorithm. Preliminary experiments show that the proposed approach performed better than two phase ensemble selection approach and prediction based diversity term approach.

Prolonged seated posture in a sedentary office workstation is one of the major reasons that is causing the rising trend in obesity. To promote exercise in the office, this study investigates in using a desk-compatible recumbent bike in a workstation from two aspects. One is to provide workstation design guidelines that would accommodate 95% of the U.S. population. The other is to see if reading and typing can be carried out without hindrance. Twelve participants were required to select their preferred workstation settings and perform the reading and typing tasks while pedaling at three different conditions: no cycling, 10 and 25 watts. By using the anthropometric variability and the user preference from the sample, the adjustable range of the workstation settings for the general U.S. population was derived: seat height 382-455 mm, desk clearance 692-835 mm, desk depth 595-832 mm, and required minimum total distance 1243-1487 mm. Repeated measures ANOVA revealed that reading comprehension was not affected while pedaling (> 0.05), but typing was affected at higher watts (< 0.001).