Are East Asian companies benefiting from western board practices?

Since the Asian crisis, East Asian nations have strived to introduce corporate governance codes, directing companies how to best improve their corporate governance practices. However, these codes have not been universally accepted by East Asian companies. This study examines the adoption of major board-related corporate governance recommendations by large nonfinancial companies in seven East Asian nations and investigates whether improvements in these board governance mechanisms have been associated with increased operating performance and market value. The results indicate that family-owned companies started with worse board governance and have been least likely to improve their board governance since the crisis. Overall, bigger, faster growing, non-family-owned companies with less concentrated ownership have been more likely to improve their board governance. Splitting of the positions of Chairman and CEO, creation of audit and nomination committees and improvements in overall board governance were found to have a positive relationship with subsequent operating performance and/or market value.

Empirical investigation of interactive highway safety design model accident prediction algorithm : Rural intersections

One major gap in transportation system safety management is the ability to assess the safety ramifications of design changes for both new road projects and modifications to existing roads. To fulfill this need, FHWA and its many partners are developing a safety forecasting tool, the Interactive Highway Safety Design Model (IHSDM). The tool will be used by roadway design engineers, safety analysts, and planners throughout the United States. As such, the statistical models embedded in IHSDM will need to be able to forecast safety impacts under a wide range of roadway configurations and environmental conditions for a wide range of driver populations and will need to be able to capture elements of driving risk across states. One of the IHSDM algorithms developed by FHWA and its contractors is for forecasting accidents on rural road segments and rural intersections. The methodological approach is to use predictive models for specific base conditions, with traffic volume information as the sole explanatory variable for crashes, and then to apply regional or state calibration factors and accident modification factors (AMFs) to estimate the impact on accidents of geometric characteristics that differ from the base model conditions. In the majority of past approaches, AMFs are derived from parameter estimates associated with the explanatory variables. A recent study for FHWA used a multistate database to examine in detail the use of the algorithm with the base model-AMF approach and explored alternative base model forms as well as the use of full models that included nontraffic-related variables and other approaches to estimate AMFs. That research effort is reported. The results support the IHSDM methodology.

Development of accident prediction models for rural highway intersections

A study was done to develop macrolevel crash prediction models that can be used to understand and identify effective countermeasures for improving signalized highway intersections and multilane stop-controlled highway intersections in rural areas. Poisson and negative binomial regression models were fit to intersection crash data from Georgia, California, and Michigan. To assess the suitability of the models, several goodness-of-fit measures were computed. The statistical models were then used to shed light on the relationships between crash occurrence and traffic and geometric features of the rural signalized intersections. The results revealed that traffic flow variables significantly affected the overall safety performance of the intersections regardless of intersection type and that the geometric features of intersections varied across intersection type and also influenced crash type.

A comprehensive dual-scale wood torrefaction model : application to the analysis of thermal run-away in industrial heat treatment processes

A dual-scale model of the torrefaction of wood was developed and used to study industrial configurations. At the local scale, the computational code solves the coupled heat and mass transfer and the thermal degradation mechanisms of the wood components. At the global scale, the two-way coupling between the boards and the stack channels is treated as an integral component of the process. This model is used to investigate the effect of the stack configuration on the heat treatment of the boards. The simulations highlight that the exothermic reactions occurring in each single board can be accumulated along the stack. This phenomenon may result in a dramatic eterogeneity of the process and poses a serious risk of thermal runaway, which is often observed in industrial plants. The model is used to explain how thermal runaway can be lowered by increasing the airflow velocity, the sticker thickness or by gas flow reversal.

A multi-touch notice board fostering social interaction

We report on an alternative OCGM interface for a bulletin board, where a user can pin a note or a drawing, and actually shares contents. Exploiting direct and continuous manipulations, opposite to discrete gestures, to explore containers, the proposed interface supports a more natural and immediate interaction. It manages also the presence of different simultaneous users, allowing for the creation of local multimedia contents, the connection to social networks, providing a suitable working environment for cooperative and collaborative tasks in a multi-touch setup, such as touch-tables, interactive walls or multimedia boards

Open source computer-vision based guidance system for UAVs on-board decision making

The use of UAVs for remote sensing tasks; e.g. agriculture, search and rescue is increasing. The ability for UAVs to autonomously find a target and perform on-board decision making, such as descending to a new altitude or landing next to a target is a desired capability. Computer-vision functionality allows the Unmanned Aerial Vehicle (UAV) to follow a designated flight plan, detect an object of interest, and change its planned path. In this paper we describe a low cost and an open source system where all image processing is achieved on-board the UAV using a Raspberry Pi 2 microprocessor interfaced with a camera. The Raspberry Pi and the autopilot are physically connected through serial and communicate via MAVProxy. The Raspberry Pi continuously monitors the flight path in real time through USB camera module. The algorithm checks whether the target is captured or not. If the target is detected, the position of the object in frame is represented in Cartesian coordinates and converted into estimate GPS coordinates. In parallel, the autopilot receives the target location approximate GPS and makes a decision to guide the UAV to a new location. This system also has potential uses in the field of Precision Agriculture, plant pest detection and disease outbreaks which cause detrimental financial damage to crop yields if not detected early on. Results show the algorithm is accurate to detect 99% of object of interest and the UAV is capable of navigation and doing on-board decision making.