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Flag of Japan Yonezawa City,yamagata Prefecture,, Japan
Member since October 17, 2016
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I am a trilingual Postgraduate Engineer in Information Technology with interdisciplinary research experience in the field of Pattern Recognition and Machine Learning. Also, I have an expireince in developing new systems such: 1) Desktop applications. (using C#) 2) MS SQL server-based applications. (using C#) 3) Networking applications. (using C#) Also, I have interdisciplinary research experience in pattern recognition,computational neuroscience be . All research related knoledge was done using MATLAB. Thus, I am intersted in the following works: 1) Acadmic typing including (Latex). 2) IT-related article writing. 3) Acadmic proofreading, . I can do translation jobs in Arabic, English and Japanese. 1. Arabic. (Mother Tongue) 2. English. (Fluent) (Proof Test: IELTS 6.5 band Score –Test Date: 2014/03/20–Tokyo) 3. Japanese. (Moderate) (Proof Test: JLPT N3 Level –Test Date: 2015/12/6–Sendai) If you like our support, feel free to endorse me.
$25 USD/hr
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Postgraduate Engineer in Information Systems

Apr 2015 - Apr 2014 (1 month)

Giving lectures in image and signal processing to graduate and undergraduate students in English language and assisting students in research-related activities.

Postgraduate Software Systems Developing

Apr 2014 - Mar 2015 (11 months)

Web-based applications and software developing.

Postdoctoral Research Fellow

Sep 2013 - Mar 2014 (6 months)

Giving lectures in image and signal processing to graduate and undergraduate students in English language and assisting students in research-related activities.


Doctor of Engineering

2010 - 2013 (3 years)


IELTS (2014)

British Council-JAPAN

This is International English Language Testing Seystems to test the English language professioncy.

JLPT- N3 (2015)

Japan Foundation and Japan Educational Exchanges and Services

The Japanese-Language Proficiency Test (JLPT) has been offered by the Japan Foundation and Japan Educational Exchanges and Services (formerly Association of International Education, Japan) since 1984 as a reliable means of evaluating and certifying the Japanese proficiency of non-native speakers.

Cisco Certified Network Academy (CCNA1) (2010)

Cisco Networking Academy

The CCNA certification indicates knowledge of networking for the small office, and the ability to work in small businesses or organizations using networks that have fewer than 100 nodes. Install and configure Cisco switches and routers in multiprotocol environments using LAN and WAN interfaces. Other skills were learnt: Networking mathematics, terminology, and models Testing and cabling LANs and WANs Ethernet Switching IP addressing and subnetting IP, TCP, UDP, and application layer protocols


Quantification of subjects’ wakefulness state during routine EEG examination.

The wakefulness state of healthy subjects tends to be an early drowsy state because of the prolonged times required for electroencephalography (EEG) measurements. In such cases, clinicians should consider accurate diagnosis of the wakefulness state of the subjects in order to interpret EEG signals accurately. The aim of the present study was to quantitatively evaluate the wakefulness state (early drowsy or fully awake) using a novel index over the occipital lobe.

Effects of subject’s wakefulness state and health status on ApEn during eye opening and closure

This study tested a novel method designed to provide useful information for medical diagnosis and treatment. We measured electroencephalography (EEG) during a test of eye opening and closing, a common test in routine EEG examination. This test is mainly used for measuring the degree of alpha blocking and sensitivity during eyes opening and closing.

A neural network based human identification framework using ear

This paper presents a framework that uses ear images for human identification. The framework makes use of Principal Component Analysis (PCA) for ear image feature extraction and Multilayer Feed Forward Neural Network for classification. Framework are proposed to improve recognition accuracy of human identification. The framework was tested on an ear image database to evaluate its reliability and recognition accuracy.

Quantitative evaluation for the wakefulness state using complexity-based decision threshold value.

Fully awake state of the subjects tends to be an early drowsy state as a result from the prolonged time of electroencephalography (EEG) measurements. Such situations can complicate the interpretation of EEG signals Thus, in this study, a new index for quantitative evaluation of the wakefulness state of subjects using a complexity based decision threshold value was developed. This index was evaluated and showed more superiority than other conventional spectral-based indices

Quantitative comparison between ApEn and spectral measures in evaluating wakefulness state.

Wakefulness state estimation prior electroencephalography (EEG) measurements is important for more precise interpretation of those signals. Thus, a new method based on approximate entropy (ApEn) using a new range of ApEn parameter values was used to be compared with different spectral-based measures. the superiority of ApEn was proved by making comparisons where each of which was based on cross validation method.


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