Monthly Archives: March 2015

IERA Update 033115

New feature:

1. Anonymous posting is enabled in the forums.

2. In-site notification is improved. You can receive notifications for article comments in the main site.

3. You can fold/unfold the index of forums by clicking on the checkbox.

4. The size of each attachment in the forums is enlarged to 5 MB.

Other issues:

1. Considering the storage space and response speed, revision logging of topics and replies is disabled, and a maximum of 2 revisions will be stored for articles.

2. The display of the website in terms of font/color/size is improved.

3. User activities are disabled.… Read more

An introduction to Big Data Analytics

Author: Kaibo Liu

Editor: Kaibo Liu

In this article, I will give a brief introduction on Big Data analytics. The goal here is to provide a basic understanding for the general public without previous trainings in this field.

If using one sentence to explain this term “Big Data analytics” in my words, it refers to a scientific process of transforming from data-rich to decision-mart.

1. What is Big Data?

Big Data is often characterized by the following three “Vs” of challenges:

Volume: The size of the data is huge
Velocity: The speed of data collection is fast
Variety: The category of the data is diverse

Recently, some applications also put forward an additional “V” challenge in Big Data:

Veracity: The quality of the data is unreliable

To understand why we generate a Big Data scenario nowadays, I would recommend to take a look at the following video:

2.

IERA was published on Feb 19, 2015. We will continuously track the updates of the platform. Here, we introduce the basic structure, user roles, and other essential issues of this website. The website is composed by two main parts: the main site and the forums.

1. Website Structure

In the main site, we continuously post high-quality articles, concerning all areas in industrial engineering as well as the website itself. In the forums, users can have discussions.

Any user will have two roles with respect to the main site and the forums. Roles of the main site include:

Administrator: A role with the highest priority
Editor: Can publish & edit articles in the main site, including others’ articles
Author: Can publish & edit his own articles in the main site
Contributor: Can favorite & comment articles, can write their own articles in the main site but cannot directly publish articles

The four roles are sorted according to their priorities.… Read more

Visual Tracking of Tanks in Battle City Using Particles Filters

Author: Changyue Song

1. Introduction

1.1 Review of Visual Object Tracking

Visual object tracking is a rapidly developing area in computer vision community. The purpose of visual object tracking is to track objects of interests in video or consecutive images. It has various applications such as car surveillance [1], smart room [2], augmented reality [3], etc. The tracking of real-world objects is challenging as a result of environment noise, occlusion, objects interaction, object deformation, change of light, etc. Recently, Kevin Cannons made a comprehensive review of the models and techniques widely used in 2D visual tracking [4]. Other reviews in this field include [5], [6], and [7].… Read more

Unbiased Estimators

Author: Abdallah Chehade

Editor: Abdallah Chehade

Unbiased Estimators

In this article we will limit our-self to the class of estimators with the same bias for $\theta$.

\begin{equation} C_\tau = {W: E_\theta[W]=\tau(\theta)} \end{equation}

In this article we will first define an unbiased estimator. Then, we will go through different techniques to find the best unbiased estimator if it exists.

In many critical applications it is required to find unbiased estimators. For such applications it is preferred to find the best unbiased estimator.

1. Best Unbiased Estimator Definition

An estimator $W^*$ is best unbiased estimator for for $\tau(\theta)$ if it satisfies $E_\theta[W^*]=\tau(\theta)$ for all $\theta$ and for any other estimator $W$ satisfying $E_\theta[W]=\tau(\theta)$ for all $\theta$.… Read more