Computational geometry

A comprehensive survey on support vector machine classification: Applications, challenges and trends

Indian script character recognition: a survey

Thank you very much for reading nonparametrics statistical methods based on ranks. Maybe you have knowledge that, people have look hundreds times for their favorite novels like this nonparametrics statistical methods based on ranks, but end up in harmful downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they are facing with some malicious virus inside their desktop computer.

Nonparametrics Statistical Methods Based On Ranks

Computer systems commonly cache the values of variables to gain efficiency. In applications where the goal is to track attributes of a continuously moving or deforming physical system over time, caching relations between variables works better than caching individual values. The reason is that, as the system evolves, such relationships are more stable than the values of individual variables.Kinetic data structures (KDSs) are a novel formal framework for designing and analyzing sets of assertions to cache about the environment, so that these assertion sets are at once relatively stable and tailored to facilitate or trivialize the computation of the attribute of interest. Formally, a KDS is a mathematical proof animated through time, proving the validity of a certain computation for the attribute of interest. KDSs have rigorous associated measures of performance and their design shares many qualities with that of classical data structures.The KDS framework has led to many new and promising algorithms in applications where the efficient modeling of motion is essential. Among these are collision detection for moving rigid and deformable bodies, connectivity maintenace in ad-hoc networks, local environment tracking for mobile agents, and visibility/occlusion maintenance. This talk will survey the general ideas behind KDSs and illustrate their application to simple geometric problems that arise in virtual and physical environments.

Data structures for mobile data (invited talk) (abstract only)

http://automatica.dei.unipd.it/public/Schenato/PSC/2009_2010/materiale/gruppo%206/Stato_dell_arte_TA/Varianti_KP/J29.pdf

Solving the multidimensional multiple-choice knapsack problem by constructing convex hulls

DPP-PseAAC: A DNA-binding protein prediction model using Chou’s general PseAAC

Many take advantage of software and hardware accessibility in the English language. However, for non native speakers, this inevitably becomes a problem; specifically for the complex Bangla language which is not easily integrated into the world of technology.Technical Challenges and Design Issues in Bangla Language Processing addresses the difficulties as well as the overwhelming benefits associated with creating programs and devices that are accessible to the speakers of the Bangla language. Professionals, students, and researchers interested in expanding the fields of computing, information and knowledge management, and communication technologies in the non-English realm will benefit from this comprehensive collection of research.

Technical Challenges and Design Issues in Bangla Language Processing

This paper presents a new model and solution for the multi-objective Vehicle Routing Problem with Soft Time Windows ( VRPSTW ) using a hybrid metaheuristic technique. The proposed methodology is developed on the basics of a new swarm based Artificial Bee Colony ( ABC ) algorithm combined with two-step constrained local search for neighborhood selection. VRPSTW involves computing the routes of a set of vehicles with fixed capacity from a central depot to a set of geographically dispersed customers with known demands and predefined time windows. Here, the time window constraints are relaxed into “soft”, that is penalty terms are added to the solution cost whenever a vehicle serves a customer outside of his time window. The solution of routing problems with soft time windows has valuable practical applications. This paper uses a direct interpretation of the VRPSTW as a multi-objective optimization problem where the total traveling distance, number of window violations and number of required vehicles are minimized while capacity and time window constraints are met. Our work aims at using ABC inspired foraging behavior of honey bees which balances exploration and exploitation to avoid local optima and reach the global optima. The algorithm is applied to solve the well known benchmark Solomon׳s problem instances. Experimental results show that our suggested approach is quite effective, as it provides solutions that are competitive with the best known results in the literature. Finally, we present an analysis of our proposed algorithm in terms of computational time.

Mohammad Kaykobad

Papers

Solving the multidimensional multiple-choice knapsack problem by constructing convex hulls

DPP-PseAAC: A DNA-binding protein prediction model using Chou’s general PseAAC

Technical Challenges and Design Issues in Bangla Language Processing

Solving the multi-objective Vehicle Routing Problem with Soft Time Windows with the help of bees

On Nonnegative Factorization of Matrices