Rethinking utility analysis: a strategic focus

Utility analysis is a technique which allows for the estimation of the financial impact of human resource (HR) interventions. While utility analysis methods have been available for decades, their application is still not widespread. Some argue that this is because managers do not understand the techniques and suggest that allowing managers to participate in the analysis would increase understanding and, as a results, use and acceptance of utility analysis. The current work posits that translating the value of HR interventions into financial terms may not be necessary. It may be more useful to determine the direct impact of HR programs on employee behaviors and attitudes. The impact of these changes on the bottom line may then be determined. Building upon the recently proposed multi-attribute utility analysis and the strategic perspective offered by the Balanced Scorecard, this paper presents a strategic utility analysis method. Strategic utility analysis requires that multiple outcomes, not only financial, be considered in order to determine the utility of a given HR intervention. It further stipulates that these outcomes should come directly from the company's business strategy. The strategy should imply certain organizational capabilities and strategic utility analysis should measure the contribution of HR interventions towards building these specific capabilities

Design improvement of toner cartridge using design for assembly method

DFMA or known as Design for Manufacture and Assembly, consists of two main components which are Design for Manufacturing and Design for Assembly. To review the design for product evaluation, DFMA is an important methodolgy to be used. Reducing the number of parts to be assembled in a product is very significant. This can contribute to reducing the cost of assembly and assembly time for manufacturer. DFMA methodology is therefore applied to reduce the cost of the product by selecting a consumer product which is a toner cartridge as a case study of the product. The DFA Worksheet table is used for product evaluation and the original product design is reviewed, improved and re-evaluated. The significant result shows the new toner cartridge design is achievable with fewer parts from 32 to 27 parts. This method is also eligible for application to manufacturing industries to improve the effectiveness of their design

AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows

Given datasets from multiple domains, a key challenge is to efficiently exploit these data sources for modeling a target domain. Variants of this problem have been studied in many contexts, such as cross-domain translation and domain adaptation. We propose AlignFlow, a generative modeling framework that models each domain via a normalizing flow. The use of normalizing flows allows for a) flexibility in specifying learning objectives via adversarial training, maximum likelihood estimation, or a hybrid of the two methods; and b) learning and exact inference of a shared representation in the latent space of the generative model. We derive a uniform set of conditions under which AlignFlow is marginally-consistent for the different learning objectives. Furthermore, we show that AlignFlow guarantees exact cycle consistency in mapping datapoints from a source domain to target and back to the source domain. Empirically, AlignFlow outperforms relevant baselines on image-to-image translation and unsupervised domain adaptation and can be used to simultaneously interpolate across the various domains using the learned representation.Comment: AAAI 202

A Developmental Organization for Robot Behavior

This paper focuses on exploring how learning and development can be structured in synthetic (robot) systems. We present a developmental assembler for constructing reusable and temporally extended actions in a sequence. The discussion adopts the traditions of dynamic pattern theory in which behavior is an artifact of coupled dynamical systems with a number of controllable degrees of freedom. In our model, the events that delineate control decisions are derived from the pattern of (dis)equilibria on a working subset of sensorimotor policies. We show how this architecture can be used to accomplish sequential knowledge gathering and representation tasks and provide examples of the kind of developmental milestones that this approach has already produced in our lab