Development of the Modern Tanks

Development of the Modern Tanks

The tank is an all terrain AFV designed primarily to engage enemy forces by the

use of direct fire in the frontal assault role. Though several configurations have been tried,

particularly in the early experimental days of tank development, a standard, mature design

configuration has since emerged to a generally accepted pattern. This features a main

artillery gun, mounted in a fully rotating turret atop a tracked automotive hull, with

various additional machine guns throughout.

Philosophically, the tank is, by its very nature, a purely offensive weapon. Being a

protective encasement with at least one gun position, it is essentially a pillbox or small

fortress (though these are static fortificationsof a purely defensive nature) that can move

toward the enemy - hence its offensive utility.

Historically, tanks are divided into 3 categories: Light Tanks (small, thinly

armoured, weakly gunned, but highly mobile tanks intended for the armoured

reconnaissance role), Medium Tanks (mid-sized, adequately armoured, respectably

gunned, fairly mobile tanks intended to provide an optimum balance of characteristics for

manoeuvre combat, primarily against other tanks), and Heavy Tanks (large, thickly

armoured, powerfully gunned, but barely mobile tanks intended for the breakthrough role

against fortified lines, particularly in support of infantry formations). Other designations

(such as Cavalry Tank, Cruiser Tank, and Infantry Tank) have been used by various

countries to denote similar roles.

A modern main battle tank incorporates advances in automotive, artillery, and

armour technology to combine the best characteristics of all three historic types into a

single, all around type. It is distinguished by its high level of firepower, mobility and

armour protection relative to other vehicles of its era. It can cross comparatively rough

terrain at high speeds, but is fuel, maintenance, and ammunition-hungry which makes it

logistically demanding. It has the heaviest armour of any vehicle on the battlefield, and

carries a powerful weapon that may be able to engage a wide variety of ground targets. It

is among the most versatile and fearsome weapons on the battlefield, valued for its shock

action against other troops and high survivability.

ACHIEVING CUSTOMER SATISFACTION THROUGH BUSINESS PROCESS ANALYSIS

ACHIEVING CUSTOMER SATISFACTION THROUGH BUSINESS

PROCESS ANALYSIS:

ABSTRACT
The aim of the study is to check the customer satisfaction through business process analysis 
in all Mobile telecommunication Companies of Pakistan. A major aspect of this research 
study is considering the customer a part of the company while providing the right 
compensation and evaluation plans to encourage employees to serve the customers better. 
In this Research Study, all Mobile Telecommunication Companies are taken as whole 
business processes, in order to find the issues, which are required to be analyzed and 
improved to achieve customer satisfaction. 
For identifying the issues related to the Customer Satisfaction, this research starts from 
studying the companies’ business processes which is followed by a survey. A comparison 
and analysis is done among the business processes of the companies based on the survey 

conducted.  **full research paper will be provided on demand with authors permission. 

MULTIPLE OBJECTS TRACKING USING PARTICLE FILTER

MULTIPLE OBJECTS TRACKING USING PARTICLE
FILTER WITH PROBABILISTIC DATA ASSOCIATION
PROCESS :

The extended Kalman filter (EKF) and unscented Kalman filter (UKF) are
standard techniques for performing recursive nonlinear estimation. However, these
methods are far from being optimal. Non-Gaussian and non-linear estimation problems
are resolved in an optimal way (approximately) using recursive Monte Carlo methods or
Particle filters with better performance as compared to that of the EKF and UKF. In
multiple targets tracking, a difficulty arises in keeping track of the individual objects as
they come close to each other and then separate and also when new objects come into
view and/or existing ones disappear. Association of the available measurements to the
correct objects is the fore most important aspect in multiple objects tracking problems.
The data association process is helpful in such cases that helps tracker keep correct track
of individual objects. This thesis presents a tracking method based on the particle filter
and the probabilistic data association (PDA)hypothesis calculations. This algorithm is
used to estimate the position and size of multiple targets in noisy video sequences, thus
showing that it is able to answer the data association problem. The uncertainty of the
measurement origin can be handled by the proposed algorithm. A data association
technique based on the joint probabilistic  data association (JPDA) is utilized. A
comparison of tracking with classical Kalman Filter with PDAF, SSRLS with PDAF and
Particle filter with JPDA is carried out. Performance comparison of tracking using
Particle filters with and without JPDA is also demonstrated through simulations.
In most of the practical applications, it is observed that the recorded videos have
some noise which may be due to bad weather (light, wind, etc.) or due to problems in
sensors. Moreover, when a video is transmitted or stored from one data storage location
to another loss of some information and addition of some noise generally takes place. A
comparison of tracking with various noise levels is also made through simulations.