Robust optimisation of sustainable food grain transportation with uncertain supply and intentional disruptions

The proliferating need for sustainability intervention in food grain transportation planning is anchoring the attention of researchers in the interests of stakeholders and environment at large. Uncertainty associated with food grain supply further intensifies the problem steering the need for designing robust, cost-efficient and sustainable models. In line with this, this paper aims to develop a robust and sustainable intermodal transportation model to facilitate single type of food grain commodity shipments while considering procurement uncertainty, greenhouse gas emissions, and intentional hub disruption. The problem is designed as a mixed integer non-linear robust optimisation model on a hub and spoke network for evaluating near optimal shipment quantity, route selection and hub location decisions. The robust optimisation approach considers minimisation of total relative regret associated with total cost subject to several real-time constraints. A version of Particle Swarm Optimisation with Differential Evolution is proposed to tackle the resulting NP-hard problem. The model is tested with two other state-of the art meta-heuristics for small, medium, and large datasets subject to different procurement scenarios inspired from real time food grain operations in Indian context. Finally, the solution is evaluated with respect to total cost, model and solution robustness for all instances.     

Pixel clustering for color image segmentation

Programming and Computer Software - Image segmentation using a hierarchical sequence of piecewise constant approximations that minimally differ from the original image in terms of the total squared...     

Lecture capture with real‐time rearrangement of visual elements: impact on student performance

The primary goal of this study is to create and test a lecture‐capture system that can rearrange visual elements while recording is still taking place, in such a way that student performance can be positively influenced. The system we have devised is capable of integrating and rearranging multimedia sources, including learning content, the instructor and students' images, into lecture videos that are embedded in a website for students to review after school. The present study employed a two‐group experimental design, with 153 participants (145 females and 8 males) making up an experimental group in which lecture courses were recorded using the new lecture‐capture system, and 149 participants (140 females and 9 males) forming a control group whose lectures were recorded by traditional means. All participants were in the freshman college and studying Introduction to Computer and Information Science in one of six classes, and were randomly assigned to one of the two groups. The participants' midterm examination and final examination scores were collected as indicators of their academic performance, with their mathematics entrance scores used as a pre‐test. The findings obtained from analysis of covariance (ANCOVA) suggest that appropriate rearrangement of visual elements in lecture videos can significantly impact students' learning performance.