WORKPLACE HAPPINESS: ORGANIZATIONAL ROLE AND THE RELIABILITY OF SELF-REPORTING

Happier employees are more productive. Organizations across industry, no doubt, try to improve their employees’ happiness with the objective to achieve higher profitability and company value. While this issue has drawn increasing attention in high tech and other industries, little is known about the happiness of project management professionals. More research is needed to explore the current situation of workplace happiness of project management professionals and the driving factors behind it. This thesis explores the workplace happiness (subjective well-being) of project management professionals based on the exploratory statistical analysis of a survey 225 professionals in the state of Maryland, conducted in October 2014. The thesis applies Structural Equation Modeling and multiple regression analysis to the dataset and shows no significant impact of gender, age, work experience, and some other demographic traits on workplace happiness, also named well-being. Statistically significant factors for workplace happiness include: creating pleasant work environment, promoting open organization and well-managed team, and good organization to work for. With respect to the reliability of self-reporting, the study finds that the comprehensive appraisal tool designed by Happiness Works and New Economics Foundation can give a more reliable happiness evaluation. Two key factors, i.e. career perspectives and free to be self, can help alleviate the overconfidence of workplace happiness.

Mitigation of High Alkalinity in Leachates of Aged Steel Slag

Steel slag, an abundant by-product of the steel-making industry, after it is aged, has a huge potential for use as an aggregate in road construction. However, the high pH of steel slag seepage (pH≥12) is a major impediment in its beneficial use. Analyses on aged steel slag samples demonstrated that the alkalinity producing capacity of aged steel slag samples strongly correlated to Ca(OH)2 dissolution and that prolonged aging periods have marginal effects on overall alkalinity. Treatment methods that included bitumen-coating, bathing in Al(III) solutions and addition of an alum-based drinking water treatment residual (WTR) were evaluated based on reduction in pH levels and leachate alkalinity. 10% (wt./wt.) alum-based drinking water treatment residual (WTR) addition to slag was determined to be the most successful mitigation method, providing 65−70% reduction in alkalinity both in batch-type and column leach tests, but final leachate pH was only 0.5−1 units lower and leachates were contaminated by dissolved Al(+III) (≥3−4 mM). Based on the interpretation of calculated saturation indices and SEM and EDX analyses, formation of calcium sulfoaluminate phases (i.e., ettringite and monosulfate) was suggested as the mechanism behind alkalinity mitigation upon WTR-modification. The residual alkalinity in WTR-amended slag leachates was able to be completely eliminated utilizing a biosolids compost with high base neutralization capacity. In column leach tests, effluent pH levels below 7 were maintained for 58−74 pore volumes worth of WTR-amended slag leachate using 0.13 kg compost (dry wt.) per 1 kg WTR-amended slag on average; also, dissolved Al(+III) was strongly retained on the compost.

Design and Pilot Study for an Efficient High-Throughput Automated Computer-Vision Guided Intelligent De-Calyxing Machine for Post-Harvest Strawberry Processing

Strawberries harvested for processing as frozen fruits are currently de-calyxed manually in the field. This process requires the removal of the stem cap with green leaves (i.e. the calyx) and incurs many disadvantages when performed by hand. Not only does it necessitate the need to maintain cutting tool sanitation, but it also increases labor time and exposure of the de-capped strawberries before in-plant processing. This leads to labor inefficiency and decreased harvest yield. By moving the calyx removal process from the fields to the processing plants, this new practice would reduce field labor and improve management and logistics, while increasing annual yield. As labor prices continue to increase, the strawberry industry has shown great interest in the development and implementation of an automated calyx removal system. In response, this dissertation describes the design, operation, and performance of a full-scale automatic vision-guided intelligent de-calyxing (AVID) prototype machine. The AVID machine utilizes commercially available equipment to produce a relatively low cost automated de-calyxing system that can be retrofitted into existing food processing facilities. This dissertation is broken up into five sections. The first two sections include a machine overview and a 12-week processing plant pilot study. Results of the pilot study indicate the AVID machine is able to de-calyx grade-1-with-cap conical strawberries at roughly 66 percent output weight yield at a throughput of 10,000 pounds per hour. The remaining three sections describe in detail the three main components of the machine: a strawberry loading and orientation conveyor, a machine vision system for calyx identification, and a synchronized multi-waterjet knife calyx removal system. In short, the loading system utilizes rotational energy to orient conical strawberries. The machine vision system determines cut locations through RGB real-time feature extraction. The high-speed multi-waterjet knife system uses direct drive actuation to locate 30,000 psi cutting streams to precise coordinates for calyx removal. Based on the observations and studies performed within this dissertation, the AVID machine is seen to be a viable option for automated high-throughput strawberry calyx removal. A summary of future tasks and further improvements is discussed at the end.