Evaluation of Sequenced and Unsequenced English for Science and Technology Materials on a Web-Based Learning Content Management System Platform

This study evaluated sequenced online EST materials and unsequenced online EST materials by using a Learning Object Review Instrument (LORI) amongst-SPM students in Seri Kembangan, Selangor Darul Ehsan. The study also analyzed the materials design aspects of sequenced and unsequenced EST materials. Both categories of EST materials were analyzed into text types, language knowledge, and key visuals. The sample population comprised 30 post-SPM students split into 2 groups of 15 students each. The test subjects interacted with the EST materials and provided feedback through a two-stage process, namely pre-evaluation and post-evaluation. The first group interacted with LODAS unsequenced EST materials at the pre-evaluation stage and sequenced EST materials at the post-evaluation point a week later. The second group interacted with LODAS sequenced EST materials and unsequenced EST materials at the pre-evaluation and post-evaluation phase respectively a week later. An intra-group reliability test among the test subjects using Wilcoxon Signed Ranks Test in SPSS was conducted. The study showed clear preferences for sequenced EST materials when responses from the four subscales of LORI were analyzed. Intra-group reliability test were found to be reliable. On the issue of materials design, data analysis on both groups of test subjects supported the view that sequenced EST materials assisted in the EST materials design

Lane-Keeping Control of Autonomous Vehicles Through a Soft-Constrained Iterative LQR

The accurate prediction of smooth steering inputs is crucial for autonomous vehicle applications because control actions with jitter might cause the vehicle system to become unstable. To address this problem in automobile lane-keeping control without the use of additional smoothing algorithms, we developed a soft-constrained iterative linear-quadratic regulator (soft-CILQR) algorithm by integrating CILQR algorithm and a model predictive control (MPC) constraint relaxation method. We incorporated slack variables into the state and control barrier functions of the soft-CILQR solver to soften the constraints in the optimization process so that stabilizing control inputs can be calculated in a relatively simple manner. Two types of automotive lane-keeping experiments were conducted with a linear system dynamics model to test the performance of the proposed soft-CILQR algorithm and to compare its performance with that of the CILQR algorithm: numerical simulations and experiments involving challenging vision-based maneuvers. In the numerical simulations, the soft-CILQR and CILQR solvers managed to drive the system toward the reference state asymptotically; however, the soft-CILQR solver obtained smooth steering input trajectories more easily than did the CILQR solver under conditions involving additive disturbances. In the experiments with visual inputs, the soft-CILQR controller outperformed the CILQR controller in terms of tracking accuracy and steering smoothness during the driving of an ego vehicle on TORCS.Comment: 11 figures, 10 page

Price formation at the Palmerston North fresh vegetable auction market : a thesis presented in partial fulfilment of the requirements for the degree of Master of Horticultural Science in Horticultural Economics and Marketing at Massey University

The aim was to analyse the short term price fluctuation of fresh vegetables at the Palmerston North auction market. A brief review of the theoretical and methodological aspects in relation to this topic is outlined. An econometric recursive model was developed in the "inductive phase" to represent the past behaviour of the industry. The simulation model was developed in the "deductive phase" for testing the sensitivity of the model and policy assessment. The results indicated that: 1) The wholesale demand for cabbages and cauliflowers is relatively inelastic (-0.5034 and -0.8142 respectively) while that of lettuces (-1.434) was elastic. Carrots showed nonsignificant positive relationship between quantity purchased and price (+1.935). 2) The simulation model was relatively insensitive to changes in its parameters. It was proved that the supply of fresh vegetables was mainly governed by the seasonal factor. 3) The policy of supply rationalisation could reduce price variance and supply variance by 18% and 45% respectively, while the gross income and unweighted mean price could be increased by 8.7% and 0.3% respectively

Efficient Perception, Planning, and Control Algorithms for Vision-Based Automated Vehicles

Autonomous vehicles have limited computational resources; hence, their control systems must be efficient. The cost and size of sensors have limited the development of self-driving cars. To overcome these restrictions, this study proposes an efficient framework for the operation of vision-based automatic vehicles; the framework requires only a monocular camera and a few inexpensive radars. The proposed algorithm comprises a multi-task UNet (MTUNet) network for extracting image features and constrained iterative linear quadratic regulator (CILQR) and vision predictive control (VPC) modules for rapid motion planning and control. MTUNet is designed to simultaneously solve lane line segmentation, the ego vehicle's heading angle regression, road type classification, and traffic object detection tasks at approximately 40 FPS (frames per second) for 228 x 228 pixel RGB input images. The CILQR controllers then use the MTUNet outputs and radar data as inputs to produce driving commands for lateral and longitudinal vehicle guidance within only 1 ms. In particular, the VPC algorithm is included to reduce steering command latency to below actuator latency to prevent self-driving vehicle performance degradation during tight turns. The VPC algorithm uses road curvature data from MTUNet to estimate the correction of the current steering angle at a look-ahead point to adjust the turning amount. Including the VPC algorithm in a VPC-CILQR controller on curvy roads leads to higher performance than CILQR alone. Our experiments demonstrate that the proposed autonomous driving system, which does not require high-definition maps, could be applied in current autonomous vehicles.Comment: 10 figures, 13 page

Global logistics indicators, supply chain metrics, and bilateral trade patterns

Past research into the determinants of international trade highlighted the importance of the basic spatial gravity model augmented by additional variables representing sources of friction. Studies modeled many sources of friction using various proxies, including indices based on expert judgment in some cases. This paper focuses on logistics friction and draws on a data set recently compiled by the World Bank with specific quantitative metrics of logistics performance interms of time, cost, and variability in time. It finds that the new variables that relate directly to logistics performance have a statistically significant relationship with the level of bilateral trade. It also finds that a single logistics index can capture virtually all of the explanatory power of multiple logistics indicators. The findings should spur public and private agencies that have direct or indirect power over logistics performance to focus attention on reducing sources of friction so as to improve their country's ability to compete in today's global economy. Moreover, since the logistics metrics are directly related to operational performance, countries can use these metrics to target actions to improve logistics and monitor their progress.Common Carriers Industry,Transport and Trade Logistics,Economic Theory&Research,Free Trade,Trade Policy

Wearing Many (Social) Hats: How Different are Your Different Social Network Personae?

This paper investigates when users create profiles in different social networks, whether they are redundant expressions of the same persona, or they are adapted to each platform. Using the personal webpages of 116,998 users on About.me, we identify and extract matched user profiles on several major social networks including Facebook, Twitter, LinkedIn, and Instagram. We find evidence for distinct site-specific norms, such as differences in the language used in the text of the profile self-description, and the kind of picture used as profile image. By learning a model that robustly identifies the platform given a user's profile image (0.657--0.829 AUC) or self-description (0.608--0.847 AUC), we confirm that users do adapt their behaviour to individual platforms in an identifiable and learnable manner. However, different genders and age groups adapt their behaviour differently from each other, and these differences are, in general, consistent across different platforms. We show that differences in social profile construction correspond to differences in how formal or informal the platform is.Comment: Accepted at the 11th International AAAI Conference on Web and Social Media (ICWSM17