Catalyzing Coastal Management in Kenya and Zanzibar: Building Capacity and Commitment

Site-based projects were initiated in Chawka Bay-Paje, Zanzibar, and Nyali-Bamburi-Shanzu, Kenya, to demonstrate the benefits of an integrated coastal management (ICM) approach for addressing coastal issues such as tourism development and enhancement of resource-dependent village economies in eastern Africa. A two-year, multidonor project used three primary strategies to make rapid, but sustainable, progress toward ICM. These included using interagency government teams for ICM planning, adopting an internationally recognized framework for ICM as a project ''road map,'' and explicitly incorporating capacity-building strategies into all aspects of the project. Within two years, integrated ICM action strategies, prepared through participatory processes, were being implemented at both sites, and both teams were working to expand the scale and scope of ICM in their nation. More importantly, the project helped create committed, capable, interagency groups that continue to work together to address urgent ICM issues.     

Noaa's civil penalty policy: Time for a change

Abstract

This article explores the lack of uniform penalty assessment in the National Oceanic and Atmospheric Administration's (NOAA) civil penalty policy under the Fishery Conservation and Management Act (the Magnuson Act). The author sugests that NOAA's inconsistent penalty assessment invites noncompliance by fishers because they view the penalties as unfair and arbitrary. In particular, deterrence is undermined by the absence of a provision that removes the economic benefits of noncompliance. NOAA's policy is contrasted with the Environmental Protection Agency's (EPA) civil penalty policy, which uniformly assesses penalties while tailoring the penalty to the individual facts of the case and effectively removing the economic incentives of noncompliance. If NOAA implemented a policy similar to EPA's, NOAA would secure increased Magnuson Act compliance and higher penalty amounts.     

Pedestrian gap acceptance for mid-block street crossing

Abstract

This paper investigates pedestrians' traffic gap acceptance for mid-block street crossing in urban areas. A field survey was carried out at an uncontrolled mid-block location in Athens, Greece. Pedestrians' decisions and traffic conditions were videotaped in terms of the size of traffic gaps rejected or accepted, waiting times and crossing attempts and vehicle speeds. A lognormal regression model was developed to examine pedestrian gap acceptance. It was found that gap acceptance was better explained by the distance from the incoming vehicle, rather than its speed. Other significant effects included illegal parking, presence of other pedestrians and incoming vehicles’ size. A binary logistic regression model was developed to examine the effect of traffic gaps and other parameters on pedestrians' decisions to cross the street or not. The results reveal that this decision is affected by the distance from the incoming vehicles and the waiting times of pedestrians.     

An adaptive neural network-fuzzy linear regression approach for improved car ownership estimation and forecasting in complex and uncertain environments: the case of Iran

This paper applies a novel adaptive approach consisting of Artificial Neural Network (ANN) and Fuzzy Linear Regression (FLR) to improve car ownership forecasting in complex, ambiguous, and uncertain environments. This integrated approach is applied to forecast car ownership in Iran from 1930 to 2007. In this study, the level of car ownership is viewed as the result of demographic, politico-social, and urban structure factors including average family size, total population density, urban population density, urbanization rate, gross national product per capita, gasoline price, and total road length. To capture the potential complexity, uncertainty, and linearity relation between the car ownership function and its determinants, ANN and FLR (including eight well-known FLR) approaches are applied to the collected data. Next, the preferred ANN is selected based on sensitivity analysis results for the test data while the preferred FLR is identified with regard to ANOVA and MAPE results. The results obtained from the performance comparison demonstrate the considerable superiority of the preferred ANN over the preferred FLR regarding the nonlinear and complex nature of the car ownership function in Iran. This is the first study that presents an ANN-FLR approach for car ownership forecasting capable of handling complexity and non-linearity, uncertainty, pre-processing, and post-processing.     

Modeling residential sorting effects to understand the impact of the built environment on commute mode choice

This paper presents an examination of the significance of residential sorting or self selection effects in understanding the impacts of the built environment on travel choices. Land use and transportation system attributes are often treated as exogenous variables in models of travel behavior. Such models ignore the potential self selection processes that may be at play wherein households and individuals choose to locate in areas or built environments that are consistent with their lifestyle and transportation preferences, attitudes, and values. In this paper, a simultaneous model of residential location choice and commute mode choice that accounts for both observed and unobserved taste variations that may contribute to residential self selection is estimated on a survey sample extracted from the 2000 San Francisco Bay Area household travel survey. Model results show that both observed and unobserved residential self selection effects do exist; however, even after accounting for these effects, it is found that built environment attributes can indeed significantly impact commute mode choice behavior. The paper concludes with a discussion of the implications of the model findings for policy planning.

Analytical study to estimate the performance of the Power Shift Drive (PSD) Axle for a forklift

In this study, a new concept for a power delivery system is developed. Power Shift Drive (PSD) Axle vehicle modeling and dynamic movement analysis are performed via simulation. The dynamic vehicle model is constructed from data obtained from the derived equation, considering the specific characteristics of each part. The model is composed of a torque converter, a gear box, a differential, hub reduction and an engine, which is the power source of the 1st forward and reverse PSD-Axle. By unifying the mathematical equations for each component, a mathematical model of the 1st forward gear is derived. The system dynamic model is created using MATLAB/Simulink based on the mathematical model. Simulation is carried out using Simulink to estimate the dynamic behavior of the PSD-Axle. In addition, the dynamo test result is used to verify the model. Finally, a successful model is created. This study will be used to establish the basic conceptual design for the PSD-Axle multi-gear system.     

Effects of split injection,oxygen enriched air and heavy EGR on soot emissions in a diesel engine

The effects of split injection, oxygen enriched air, and heavy exhaust gas recirculation (EGR) on soot emissions in a direct injection diesel engine were studied using the KIVA-3V code. When split injection is applied, the second injection of fuel into a cylinder results in two separate stoichiometric zones, which helps soot oxidation. As a result, soot emissions are decreased. When oxygen enriched air is applied together with split injection, a higher concentration of oxygen causes higher temperatures in the cylinder. The increase in temperature promotes the growth reaction of acetylene with soot. However, it does not improve acetylene formation during the second injection of fuel. As more acetylene is consumed in the growth reaction with soot, the concentration of acetylene in the cylinder is decreased, which leads to a decrease in soot formation and thus soot emissions. A combination of split injection, a high concentration of oxygen, and a high EGR ratio shows the best results in terms of diesel emissions. In this paper, the split injection scheme of 75.8.25, in which 75% of total fuel is injected in the first pulse, followed by 8°CA of dwell time, and 25% of fuel is injected in the second pulse, with an oxygen concentration of 23% in volume and an EGR ratio of 30% shows a 45% reduction in soot emissions, with the same NOx emissions as in single injection.     

Multi-response optimization of diesel engine performance parameters using thumba biodiesel-diesel blends by applying the Taguchi method and grey relational analysis

This paper presents an experimental study that involves an application of the Taguchi method and grey relational analysis to determine the optimum factor level to obtain optimum multiple-performance characteristics of a diesel engine run with different low-percentage thumba biodiesel-diesel blends. Four factors, namely, low-percentage thumba biodiesel-diesel blend, compression ratio, nozzle opening pressure and injection timing were each considered at three levels. An L₉ orthogonal array was used to collect data for various engine performance- and emission-related responses under different engine loads. The signal-to-noise (S/N) ratio and grey relational analysis were used for data analysis. The results of the study revealed that the combination of a blend consisting of 30% thumba biodiesel (B30), a compression ratio of 14, a nozzle opening pressure of 250 bar and an injection timing of 20° produces maximum multiple performance of a diesel engine with minimum multiple emissions from the engine.     

Drive control system design for stability and maneuverability of a 6WD/6WS vehicle

This paper describes a drive controller designed to improve the lateral vehicle stability and maneuverability of a 6-wheel drive / 6-wheel steering (6WD/6WS) vehicle. The drive controller consists of upper and lower level controllers. The upper level controller is based on sliding control theory and determines both front and middle steering angle, additional net yaw moment, and longitudinal net force according to the reference velocity and steering angle of a manual drive, remotely controlled, autonomous controller. The lower level controller takes the desired longitudinal net force, yaw moment, and tire force information as inputs and determines the additional front steering angle and distributed longitudinal tire force on each wheel. This controller is based on optimal distribution control and takes into consideration the friction circle related to the vertical tire force and friction coefficient acting on the road and tire. Distributed longitudinal/lateral tire forces are determined as proportion to the size of the friction circle according to changes in driving conditions. The response of the 6WD/6WS vehicle implemented with this drive controller has been evaluated via computer simulations conducted using the Matlab/Simulink dynamic model. Computer simulations of an open loop under turning conditions and a closed-loop driver model subjected to double lane change have been conducted to demonstrate the improved performance of the proposed drive controller over that of a conventional DYC.     

Design and evaluation of sideslip angle observer for vehicle stability control

This paper presents a method for estimating the vehicle side slip angle, which is considered as a significant signal in determining the vehicle stability region in vehicle stability control systems. The proposed method combines the model-based method and kinematics-based method. Side forces of the front and rear axles are provided as a weighted sum of directly calculated values from a lateral acceleration sensor and a yaw rate sensor and from a tire model according to the nonlinear factor, which is defined to identify the degree of nonlinearity of the vehicle state. Then, the side forces are fed to the extended Kalman filter, which is designed based on the single-track vehicle model associated with a tire model. The cornering stiffness identifier is introduced to compensate for tire force nonlinearities. A fuzzy-logic procedure is implemented to determine the nonlinear factor from the input variables: yaw rate deviation from the reference value and lateral acceleration. The proposed observer is compared with a model-based method and kinematics-based method. An 8 DOF vehicle model and Dugoff tire model are employed to simulate the vehicle state in MATLAB/SIMULINK. The simulation results shows that the proposed method is more accurate than the model-based method and kinematics-based method when the vehicle is subjected to severe maneuvers under different road conditions.