Ahmed B. Profile

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$25 USD / hour

dawadmi,

saudi arabia

$25 USD / hour

It's currently 4:13 AM here

Joined October 13, 2017

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Ahmed B.

@abenjmaa

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(0 reviews)

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$25 USD / hour

dawadmi,

saudi arabia

$25 USD / hour

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Expert in ( LaTeX & Excel VBA )

** Profile ** - Doctor of computer sciences - Lecturer at Technical and Vocational Training Corporation, Saudi Arabia - +13 years of experience in scientific research - +10 years of experience in teaching field ** Expert in LaTeX and TikZ ** - I will format all types of documents (Scientific paper or journal, Books, Report ...) with LaTeX in different language (English, French and Arabic). I can convert any Ms Word document to LaTeX - I will create any design (title page, CV ...) with LaTeX (using TikZ package)) - I will edit any proceeding for conferences. ** Expert in Excel VBA ** - I will develop any macro and script with VBA ** MatLAB Developer ** - I will develop any script with MatLAB ** VB6 Developer ** - I will develop any management application

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Experience

Technical and Vocational Training Corporation, Saudi Arabia

Sep 2013 - Present

Modules Taught: - Database design and analysis. - Pricipales of database. - Computer system. - PHP programming. - IT security. - Advanced computer applications.

Ministry of Higher Education and Scientific Research, Tunisia

Sep 2005 - Sep 2013 (8 years)

Modules Taught: - Database Management System (SGBD Oracle). - Microsoft Access 2000. - Visual Basic. - Language C/C++. - Web server administration. - Language theory and compiler. - Human-machine Interaction. - Computer graphics (AutoCad 2D). - Certificate in Computers and Internet (C2I).

Invest Consulting And Training

Sep 2002 - Sep 2005 (3 years)

Design & programming software (Tools: Visual Basic 6, Oracle 8i and Crystal Report): - Production management. - Quality control of production. - Performance management. - Production management (Barcode system). - Movement of production lines (Mobile terminal). - Daily backup Tool. Networks administration: - Network installation and administration (50 workstations, 4 servers, 8 VLAN). - Administration of SMC Switch. - Security network management.

Education

Ph.D. in computer sciences

Université de Sfax,

Tunisia

2006 - 2017

(11 years)

M.Sc. in computer science

Université de Sfax,

Tunisia

2003 - 2005

(2 years)

B.Sc. in computer science

Université de Sfax,

Tunisia

1998 - 2002

(4 years)

Qualifications

Virtual University of Tunis, Tunisia

2010

- Microsoft Office (Word, Excel, Powerpoint, Access) - Internet

Publications

A new approach for digit recognition based on hand gesture analysis

International Journal of Computer Science and Information Security (IJCSIS09)

We present in this paper a new approach for hand gesture analysis that allows digit recognition based on extracting a set of features from a hand image. The most important features we extract from each image are the fingers locations, their heights and the distance between each pair of fingers. We identify the skin pixel for each input image. We remove all the hand components except the fingers. The histogram of the detected fingers extract features that will be used for digit recognition.

2DPCA fractal features and genetic algorithm for efficient face representation and recognition

EURASIP Journal on Information Security

In this article, we present an automatic face recognition system. We show that fractal features obtained from Iterated Function System allow a successful face recognition and outperform the classical approaches. We propose a new fractal feature extraction algorithm based on genetic algorithms to speed up the feature extraction step. In order to capture the more important information that is contained in a face with a few fractal features, we use a bi-dimensional principal component analysis.

A New Approach For Hand Gestures Recognition Based on Depth Map Captured by RGB-D Camera

Computación y Sistemas (CyS)

This paper presented a new approach for hand gestures recognition based on depth Map captured by an RGB-D Kinect camera. Although this camera provides two types of information ”Depth Map” and ”RGB Image”, only the depth data information was used to analyze and recognize the hand gestures. Given the complexity of this task, we first proposed a new method based on edge detection to eliminate the noise and segment the hand. Then we introduced new descriptors modeling the hand gesture.