Search results for: Randa M. Alarousy
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7

Search results for: Randa M. Alarousy

7 Incidence of Fungal Infections and Mycotoxicosis in Pork Meat and Pork By-Products in Egyptian Markets

Authors: Ashraf S. Hakim, Randa M. Alarousy

Abstract:

The consumption of food contaminated with molds (microscopic filamentous fungi) and their toxic metabolites results in the development of food-borne mycotoxicosis. The spores of molds are ubiquitously spread in the environment and can be detected everywhere. Ochratoxin A is a toxic and potentially carcinogenic fungal toxin found in a variety of food commodities. In this study, the mycological quality of various ready-to-eat local and imported pork meat and meat byproducts sold in Egyptian markets were assessed and the presence of various molds was determined in pork used as a raw material, edible organs as liver and kidney as well as in fermented raw meat by-products. The study assessed the mycological quality of pork raw meat and their by-products sold in commercial shops in Cairo, Egypt. Mycological analysis was conducted on (n=110) samples which included pig’s livers and kidneys from Egyptian Bassatin slaughter house; local and imported processed pork meat by-products from Egyptian pork markets. The isolates were identified using traditional mycological and biochemical tests. All kidney and liver samples were positive to molds growth while all byproducts were negative. Ochratoxin A levels were quantitatively analyzed using the high performance liquid chromatography (HPLC) and the highest results were present in kidney 7.51 part per billion (ppb) followed by minced meat 6.19 ppb generally the local samples showed higher levels than the imported ones. To the best of our knowledge, this is the first report on mycotoxins detection and quantification from pork by-products in Egypt.

Keywords: Egypt, imported pork by-products, local, mycotoxins.

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6 Hand Vein Image Enhancement With Radon Like Features Descriptor

Authors: Randa Boukhris Trabelsi, Alima Damak Masmoudi, Dorra Sellami Masmoudi

Abstract:

Nowadays, hand vein recognition has attracted more attentions in identification biometrics systems. Generally, hand vein image is acquired with low contrast and irregular illumination. Accordingly, if you have a good preprocessing of hand vein image, we can easy extracted the feature extraction even with simple binarization. In this paper, a proposed approach is processed to improve the quality of hand vein image. First, a brief survey on existing methods of enhancement is investigated. Then a Radon Like features method is applied to preprocessing hand vein image. Finally, experiments results show that the proposed method give the better effective and reliable in improving hand vein images.

Keywords: Hand Vein, Enhancement, Contrast, RLF, SDME

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5 Simultaneous Segmentation and Recognition of Arabic Characters in an Unconstrained On-Line Cursive Handwritten Document

Authors: Randa I. Elanwar, Mohsen A. Rashwan, Samia A. Mashali

Abstract:

The last two decades witnessed some advances in the development of an Arabic character recognition (CR) system. Arabic CR faces technical problems not encountered in any other language that make Arabic CR systems achieve relatively low accuracy and retards establishing them as market products. We propose the basic stages towards a system that attacks the problem of recognizing online Arabic cursive handwriting. Rule-based methods are used to perform simultaneous segmentation and recognition of word portions in an unconstrained cursively handwritten document using dynamic programming. The output of these stages is in the form of a ranked list of the possible decisions. A new technique for text line separation is also used.

Keywords: Arabic handwriting, character recognition, cursive handwriting, on-line recognition.

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4 OHASD: The First On-Line Arabic Sentence Database Handwritten on Tablet PC

Authors: Randa I. M. Elanwar, Mohsen A. Rashwan, Samia A. Mashali

Abstract:

In this paper we present the first Arabic sentence dataset for on-line handwriting recognition written on tablet pc. The dataset is natural, simple and clear. Texts are sampled from daily newspapers. To collect naturally written handwriting, forms are dictated to writers. The current version of our dataset includes 154 paragraphs written by 48 writers. It contains more than 3800 words and more than 19,400 characters. Handwritten texts are mainly written by researchers from different research centers. In order to use this dataset in a recognition system word extraction is needed. In this paper a new word extraction technique based on the Arabic handwriting cursive nature is also presented. The technique is applied to this dataset and good results are obtained. The results can be considered as a bench mark for future research to be compared with.

Keywords: Arabic, Handwriting recognition, on-line dataset.

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3 A New Biometric Human Identification Based On Fusion Fingerprints and Finger Veins Using monoLBP Descriptor

Authors: Alima Damak Masmoudi, Randa Boukhris Trabelsi, Dorra Sellami Masmoudi

Abstract:

Single biometric modality recognition is not able to meet the high performance supplies in most cases with its application become more and more broadly. Multimodal biometrics identification represents an emerging trend recently. This paper investigates a novel algorithm based on fusion of both fingerprint and fingervein biometrics. For both biometric recognition, we employ the Monogenic Local Binary Pattern (MonoLBP). This operator integrate the orginal LBP (Local Binary Pattern ) with both other rotation invariant measures: local phase and local surface type. Experimental results confirm that a weighted sum based proposed fusion achieves excellent identification performances opposite unimodal biometric systems. The AUC of proposed approach based on combining the two modalities has very close to unity (0.93).

Keywords: fingerprint, fingervein, LBP, MonoLBP, fusion, biometric trait.

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2 Unconstrained Arabic Online Handwritten Words Segmentation using New HMM State Design

Authors: Randa Ibrahim Elanwar, Mohsen Rashwan, Samia Mashali

Abstract:

In this paper we propose a segmentation system for unconstrained Arabic online handwriting. An essential problem addressed by analytical-based word recognition system. The system is composed of two-stages the first is a newly special designed hidden Markov model (HMM) and the second is a rules based stage. In our system, handwritten words are broken up into characters by simultaneous segmentation-recognition using HMMs of unique design trained using online features most of which are novel. The HMM output characters boundaries represent the proposed segmentation points (PSP) which are then validated by rules-based post stage without any contextual information help to solve different segmentation errors. The HMM has been designed and tested using a self collected dataset (OHASD) [1]. Most errors cases are cured and remarkable segmentation enhancement is achieved. Very promising word and character segmentation rates are obtained regarding the unconstrained Arabic handwriting difficulty and not using context help.

Keywords: Arabic, Hidden Markov Models, online handwriting, word segmentation

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1 Attitude and Knowledge of Primary Health Care Physicians and Local Inhabitants about Leishmaniasis and Sandfly in West Alexandria

Authors: Randa M. Ali, Naguiba F. Loutfy, Osama M. Awad

Abstract:

Leishmaniasis is the collective name for a number of diseases caused by protozoan flagellates of the genus Leishmania, which is transmitted by Phlebotomine sandfly, the disease has diverse clinical manifestations and found in many areas of the world, particularly in Africa, Latin America, South and Central Asia, the Mediterranean basin and the Middle East. This study was done to assess primary health care physicians’ knowledge (PHP) and attitude about leishmaniasis and to assess awareness of local inhabitants about the disease and its vector in four areas in west Alexandria, Egypt. It is a cross sectional survey that was conducted in four PHC units in west Alexandria. All physicians currently working in these units during the study period were invited to participate in the study; only 20 PHP completed the questionnaire. 60 local inhabitants were selected randomly from the four areas of the study, 15 from each area; Data was collected through two different specially designed questionnaires. Results showed that 11 (55%) percent of the physicians had satisfactory knowledge; they answered more than 9 (60%) questions out of a total 14 questions about leishmaniasis and sandfly. On the other hand when attitude of the primary health care physicians about leishmaniasis was measured, results showed that 17 (85%) had good attitude and 3 (15%) had poor attitude. The second questionnaire showed that the awareness of local inhabitants about leishmaniasis and sandfly as a vector of the disease is poor and needs to be corrected. (90%) of the interviewed inhabitants had not heard about leishmaniasis, Only 3 (5%) of them said they know sandfly and its role in transmission of leishmaniasis. Thus we conclude that knowledge and attitudes of physicians are acceptable. However, there is, room for improvement and could be done through formal training courses and distribution of guidelines. In addition to raising the awareness of primary health care physicians about the importance of early detection and notification of cases of leishmaniasis, health education for raising awareness of the public regarding the vector and the disease is necessary because related studies have demonstrated that for inhabitants to take enough protective measures against the vector, they should perceive that it is responsible for causing a disease.

Keywords: Attitude, knowledge, PHP, leishmaniasis, sandfly, local inhabitants, inside and outside housing conditions.

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