Uncertainty and Human Capital Decisions: Traditional Valuation Methods and Real Options Logic

As the importance of human capital increases in organizations, so does the need to develop more sophisticated financial valuation models. This paper reviews some of the major traditional financial decision making models used in costing employment mode choices. It then introduces the real options valuation approach for costing such choices. The advantage of the real options model is demonstrated to build flexibility into employment decisions

Contingency power for small turboshaft engines using water injection into turbine cooling air

Because of one engine inoperative requirements, together with hot-gas reingestion and hot day, high altitude takeoff situations, power augmentation for multiengine rotorcraft has always been of critical interest. However, power augmentation using overtemperature at the turbine inlet will shorten turbine life unless a method of limiting thermal and mechanical stresses is found. A possible solution involves allowing the turbine inlet temperature to rise to augment power while injecting water into the turbine cooling air to limit hot-section metal temperatures. An experimental water injection device was installed in an engine and successfully tested. Although concern for unprotected subcomponents in the engine hot section prevented demonstration of the technique's maximum potential, it was still possible to demonstrate increases in power while maintaining nearly constant turbine rotor blade temperature

Nutrient Overloading in the Chesapeake Bay : Structural Conditions in Poultry Production and the Socioecological Drivers of Marine Pollution

We examine socioecological drivers of nutrient overloading and eutrophication in the Chesapeake Bay associated with poultry production on the Delmarva Peninsula. We use a social metabolic analysis—rooted in a political-economy perspective—that highlights the interchange of matter and energy and the inextricable links within and between social and ecological systems, illuminating the social structural processes contributing to ecological changes. The concentration and consolidation of poultry production through integration, which involves contract farming, and geographic concentration of operations, have been associated with intensified and increased scale of chicken (broiler) production. These processes have had significant effects on waste accumulation, maintenance, and disposal, and this industry has become one of the major contributors of nutrient overloading in the Chesapeake Bay. This study, therefore, specifies social processes that are driving environmental changes between land and sea

Effects of fluency building in multiplication tables on the rate of learning to factorise quadratic equations

Fluency building in basic skills is a highly effective method of preventing and remediating learning difficulties in the classroom. Unfortunately this method is seldom used. One of the claimed consequences, for the learner, of fluency building in basic skills is that related complex skills may be learned more quickly. This experiment examined the relationship between fluent performance in a component skill, basic multiplication facts, and the rate of acquisition of a related complex skill, the factorising of quadratic equations. Two groups of students took part in the experiment. Students in the first group, the Tables Mastery Group, were fluent in basic multiplication facts. Students in the second group, the Tables Non Mastery Group, were not fluent in basic multiplication facts. The students in the Tables Mastery Group quickly achieved mastery level in factorising quadratic equations. The students in the Tables Non-Mastery Group were not able to do so. However, once the students in the Tables Non-Mastery Group had achieved a high level of fluency in basic multiplication facts, they were then able to achieve a fluent level of performance in factorising quadratic equations just as quickly as the students in the Tables Mastery Group. These results have important implications for the teaching of mathematics - especially to those students who are finding mathematics increasingly difficult

Foraging Preference by Wild Deer on Toyon (Heteromeles arbutifolia) from Santa Catalina Island versus Malibu

Our group collected samples of Heteromeles Arbutifolia from both Santa Catalina Island and Pepperdine University’s campus in Malibu, CA in order to compare the morphological differences and deer preference between them. In our experiment, we planted the H. Arbutifolia from both locations side by side on a hillside overlooked by the Thorton Administration Center building on Pepperdine’s campus. In the first trial the deer did not consume either of the samples; we believe this was due to the length of time from when the branches were collected from the island to when they were introduced to the deer on campus. However, after receiving fresh samples of H. Arbutifolia from the island, we immediately counted the leaves and introduced the branches to the same feeding site. The results from the second trial confirmed our hypothesis that deer have a preference for the H. Arbutifolia grown on Catalina Island over that grown in Malibu. The spine length on the leaves from both samples showed a significant difference; the spines from H. Arbutifolia grown on Pepperdine’s campus were consistently longer than those measured from the Catalina leaves. Overall, there was a clear difference in the morphological characteristics and herbivore preference for the H. Arbutifolia grown in Catalina over that found in Malibu

AdCorDA: Classifier Refinement via Adversarial Correction and Domain Adaptation

This paper describes a simple yet effective technique for refining a pretrained classifier network. The proposed AdCorDA method is based on modification of the training set and making use of the duality between network weights and layer inputs. We call this input space training. The method consists of two stages - adversarial correction followed by domain adaptation. Adversarial correction uses adversarial attacks to correct incorrect training-set classifications. The incorrectly classified samples of the training set are removed and replaced with the adversarially corrected samples to form a new training set, and then, in the second stage, domain adaptation is performed back to the original training set. Extensive experimental validations show significant accuracy boosts of over 5% on the CIFAR-100 dataset. The technique can be straightforwardly applied to refinement of weight-quantized neural networks, where experiments show substantial enhancement in performance over the baseline. The adversarial correction technique also results in enhanced robustness to adversarial attacks