Exploring the Cognitive Nature of Boards of Directors and Its Implication for Board Effectiveness

In this paper we propose a theoretical framework that emphasizes the development of a shared mental model (SMM) of a board of directors and its impact on board effectiveness and suggest that the accuracy and scope of the SMM in a board will moderate the relationship between a board’s SMM and board effectiveness. Also, we examine the impact of task and relationship conflict on the development of a SMM. Finally, we examine three board attributes (board size, CEO duality, and the proportion of outside directors on a board) as antecedents to the development of conflict among board members.Boards of directors, corporate governance, shared mental models

A CRITICAL REVIEW OF THE ENVIRONMENTAL UNCERTAINTY LITERATURE SINCE 1987

Environmental uncertainty has been a central construct of organizational theorists and strategic management researchers for many decades. The number of empirical studies using the uncertainty construct also continues to be significant. However, the confusion surrounding the conceptualization and measurement of the uncertainty construct remains a subject of scholarly debate. Through our comprehensive review of 77 empirical studies over the last 20 years and related theoretical and methodological work, we intend to (1) review the conceptualization trends and persisting issues that are apparent in uncertainty research, (2) review empirical issues particularly important to uncertainty work and illustrate how researches have or have not overcome some of these challenges, and (3) suggest directions for future research using the uncertainty construct.

Towards Zero-Waste Furniture Design

In traditional design, shapes are first conceived, and then fabricated. While this decoupling simplifies the design process, it can result in inefficient material usage, especially where off-cut pieces are hard to reuse. The designer, in absence of explicit feedback on material usage remains helpless to effectively adapt the design -- even though design variabilities exist. In this paper, we investigate {\em waste minimizing furniture design} wherein based on the current design, the user is presented with design variations that result in more effective usage of materials. Technically, we dynamically analyze material space layout to determine {\em which} parts to change and {\em how}, while maintaining original design intent specified in the form of design constraints. We evaluate the approach on simple and complex furniture design scenarios, and demonstrate effective material usage that is difficult, if not impossible, to achieve without computational support

Attitude Confidence and User Resistance for Purchasing Wearable Devices on VR: VR Headset Perspective

The Virtual Reality (VR) has been issued by IT business of the 21st century. There has been a quick diffusion of smart devices and applying various industrial sites. However, there is a lack of innovation resistance studies of influencing new technology’s adoption & diffusion including VR. The research questions follow. First, do attitude confidence and innovativeness resistance affect consumer intention to use? Next, what factors affect among brand, contents and the above variable like attitude confidence? Finally, are there different factors as functional characteristics in VR? This study collected data from respondents who have prior experiences taking VR headset in Korea. The result of this study explained that user innovation resistance (-) and attitude confidence (+) directly-opposed influence consumer intention to use VR headset. Especially, seeing that attitude confidence is highly strong effect to the Use intention. Thus, high-belied of attitude improve behavior intention in the innovative product

3D Shape Variational Autoencoder Latent Disentanglement via Mini-Batch Feature Swapping for Bodies and Faces

Learning a disentangled, interpretable, and structured latent representation in 3D generative models of faces and bodies is still an open problem. The problem is particularly acute when control over identity features is required. In this paper, we propose an intuitive yet effective self-supervised approach to train a 3D shape variational autoencoder (VAE) which encourages a disentangled latent representation of identity features. Curating the mini-batch generation by swapping arbitrary features across different shapes allows to define a loss function leveraging known differences and similarities in the latent representations. Experimental results conducted on 3D meshes show that state-of-the-art methods for latent disentanglement are not able to disentangle identity features of faces and bodies. Our proposed method properly decouples the generation of such features while maintaining good representation and reconstruction capabilities

Heterogeneous reconstruction of deformable atomic models in Cryo-EM

Cryogenic electron microscopy (cryo-EM) provides a unique opportunity to study the structural heterogeneity of biomolecules. Being able to explain this heterogeneity with atomic models would help our understanding of their functional mechanisms but the size and ruggedness of the structural space (the space of atomic 3D cartesian coordinates) presents an immense challenge. Here, we describe a heterogeneous reconstruction method based on an atomistic representation whose deformation is reduced to a handful of collective motions through normal mode analysis. Our implementation uses an autoencoder. The encoder jointly estimates the amplitude of motion along the normal modes and the 2D shift between the center of the image and the center of the molecule . The physics-based decoder aggregates a representation of the heterogeneity readily interpretable at the atomic level. We illustrate our method on 3 synthetic datasets corresponding to different distributions along a simulated trajectory of adenylate kinase transitioning from its open to its closed structures. We show for each distribution that our approach is able to recapitulate the intermediate atomic models with atomic-level accuracy.Comment: 8 pages, 1 figur

The value of Augmented Reality in surgery — A usability study on laparoscopic liver surgery

Augmented Reality (AR) is considered to be a promising technology for the guidance of laparoscopic liver surgery. By overlaying pre-operative 3D information of the liver and internal blood vessels on the laparoscopic view, surgeons can better understand the location of critical structures. In an effort to enable AR, several authors have focused on the development of methods to obtain an accurate alignment between the laparoscopic video image and the pre-operative 3D data of the liver, without assessing the benefit that the resulting overlay can provide during surgery. In this paper, we present a study that aims to assess quantitatively and qualitatively the value of an AR overlay in laparoscopic surgery during a simulated surgical task on a phantom setup. We design a study where participants are asked to physically localise pre-operative tumours in a liver phantom using three image guidance conditions — a baseline condition without any image guidance, a condition where the 3D surfaces of the liver are aligned to the video and displayed on a black background, and a condition where video see-through AR is displayed on the laparoscopic video. Using data collected from a cohort of 24 participants which include 12 surgeons, we observe that compared to the baseline, AR decreases the median localisation error of surgeons on non-peripheral targets from 25.8 mm to 9.2 mm. Using subjective feedback, we also identify that AR introduces usability improvements in the surgical task and increases the perceived confidence of the users. Between the two tested displays, the majority of participants preferred to use the AR overlay instead of navigated view of the 3D surfaces on a separate screen. We conclude that AR has the potential to improve performance and decision making in laparoscopic surgery, and that improvements in overlay alignment accuracy and depth perception should be pursued in the future