Execution: the Critical “What’s Next?” in Strategic Human Resource Management

The Human Resource Planning Society’s 1999 State of the Art/Practice (SOTA/P) study was conducted by a virtual team of researchers who interviewed and surveyed 232 human resource and line executives, consultants, and academics worldwide. Looking three to five years ahead, the study probed four basic topics: (1) major emerging trends in external environments, (2) essential organizational capabilities, (3) critical people issues, and (4) the evolving role of the human resource function. This article briefly reports some of the study’s major findings, along with an implied action agenda – the “gotta do’s for the leading edge. Cutting through the complexity, the general tone is one of urgency emanating from the intersection of several underlying themes: the increasing fierceness of competition, the rapid and unrelenting pace of change, the imperatives of marketplace and thus organizational agility, and the corresponding need to buck prevailing trends by attracting and, especially, retaining and capturing the commitment of world-class talent. While it all adds up to a golden opportunity for human resource functions, there is a clear need to get to get on with it – to get better, faster, and smarter – or run the risk of being left in the proverbial dust. Execute or be executed

Frame Selection in a Connectionist Model Of High-Level Inferencing

Frame selection is a fundamental problem in high-level reasoning. Connectionist models have been unable to approach this problem because of their inability to represent multiple dynamic variable bindings and use them by applying general knowledge rules. These deficits have barred them from performing the high-level inferencing necessary for planning, reasoning, and natural language understanding. This paper describes a localist spreading-activation model, ROBIN, which solves a significant subset of these problems. ROBIN incorporates the normal semantic network su^ucture of previous localist networks, but has additional stfucture to handle variables and dynamic role-binding. Each concept in the network has a uniquely-identifying activation value, called its signature. A dynamic binding is created when a binding node receives the activation of a concept's signature. Signatures propagates across paths of binding nodes to dynamically instantiate candidate inference paths, which are selected by the evidential activation on the network's semantic structure. R O B I N is thus able to approach many of the high-level inferencing and frame selection tasks not handled by previous connectionist models

A Symbolic/Connectionist Script Applier Mechanism

We constructed a Modular Connectionist Architecture which consists of meiny different types of 3 layer feed-forward PDP network modules (auto-associative recurrent, hetero-associative recurrent, and heteroassociative) in order to do script-based story understanding. Our system, called DYNASTY (DYNAmic script-based STory understanding sYstem) has the following 3 major functions: (1) DYNASTY can learn distributed representations of concepts and events in everyday scriptal experiences, (2) DYNASTY can do script-based causal chain completion inferences according to the acquired sequential knowledge, and (3) DYNASTY performs script role association and retrieval while performing script application. Our purpose in constructing this system is to show that the learned internal representations, using simple encoder-type networks, can be used in higher-level modules to develop connectionist architectures for fairly complex cognitive tasks, such as script processing. Unlike other neurally inspired script processing models, DYNASTY can learn its own similanty-hased distributed representations from input script data using ARPDP (Autoassociative Recurrent PDP) architectures. Moreover DYNASTY'S role association network handles both script roles and fillers as full-fledged concepts^ so that it can learn the generalized associative knowledge between several script roles and fillers

Integrating Marker Passing and Connectionism for Handling Conceptual and Structureal Ambiguities

This paper discusses the problem of selecting the correct knowledge structures in parsing natural language texts which are conceptually and structurally ambiguous and require dynamic reinterpretation. An approach to this problem is presented which represnets all knowledge structures in a uniform manner and which uses a constrained marker passing mechanism augmented with elements of connectionist models. This approach is shown to have the advantage of completely integrating all parsing processes, while maintatining a simple, domain-independedt processing mechanis

Multi-Modal Courtship in the Peacock Spider, Maratus volans (O.P.-Cambridge, 1874)

The peacock spider, Maratus volans, has one of the most elaborate courtship displays in arthropods. Using regular and high-speed video segments captured in the lab, we provide detailed descriptions of complete male courtship dances. As research on jumping spiders has demonstrated that males of some species produce vibrations concurrently with visual displays, we also used laser vibrometry to uncover such elements for this species. Our recordings reveal and describe for the first time, that M. volans males use vibratory signals in addition to complex body ornaments and motion displays. The peacock spider and other closely related species are outstanding study organisms for testing hypotheses about the evolution and functional significance of complex displays, thus, this descriptive study establishes a new model system for behavioral ecology, one that certainly stands to make important contributions to the field

Analysis of a distributed fiber-optic temperature sensor using single-photon detectors

We demonstrate a high-accuracy distributed fiber-optic temperature sensor using superconducting nanowire single-photon detectors and single-photon counting techniques. Our demonstration uses inexpensive single-mode fiber at standard telecommunications wavelengths as the sensing fiber, which enables extremely low-loss experiments and compatibility with existing fiber networks. We show that the uncertainty of the temperature measurement decreases with longer integration periods, but is ultimately limited by the calibration uncertainty. Temperature uncertainty on the order of 3 K is possible with spatial resolution of the order of 1 cm and integration period as small as 60 seconds. Also, we show that the measurement is subject to systematic uncertainties, such as polarization fading, which can be reduced with a polarization diversity receiver

Graduate Student Orientation through a Professional Seminar

Traditional new student orientation programming is focused on the duality of academic preparation and social integration. For graduate students, especially doctoral students, much of the academic preparation has already been accounted for and social integration is often seen as secondary. The current study follows a cohort of new doctoral students through an orientation course, collecting relevant demographic data, and tracking them through completion of their dissertations

Female First-Year Students Preceptions of Orientation Programs

Female college students experience unique dimensions to their transition to college. Traditional orientation programming has begun to address the needs of female students, but these efforts have typically not provided the holistic attention deserving of this population. The current report was a case study of 605 female first-year college students, their perceptions of an orientation program based on the CAS Standards, and the differences between Multi-Ethnic and Caucasian females