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A New Approach Based on Set Partitioning in Hierarchical Tree Algorithm for Image Compression

Computer Technology and Application 2011年第4期2卷 270-279页

作者： Zitouni Athmane Baarir Zine Eddine ouafi abd elkarim Taleb Ahmed abdelmalik LESIA Laboratory of Research Electronic Department University of Biskra Algeria Universite of Valenciennes and Hainaut Cambrdsis FRE CNRS 3304 UVHC LAMIH le mont houy 59313 Valenciennes Cedex 9 France

In this paper, the authors propose a new approach to image compression based on the principle of Set Partitioning in Hierarchical Tree algorithm （SPIHT）. Our approach, the modified SPIHT （MSPIHT）, distributes entropy differently than SPIHT and also optimizes the coding. This approach can produce results that are a significant improvement on the Peak Signal-to-Noise Ratio （PSNR） and compression ratio obtained by SPIHT algorithm, without affecting the computing time. These results are also comparable with those obtained using the Embedded Zerotree Wavelet （EZW） and Joint Photographic Experts Group 2000 （JPG2） algorithms.

关键词： Image compression set partitioning in hierarchical tree (SPIHT) MSPIHT entropy coding peak signal-to-noise ratio (PSNR) compression ratio.

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Association of SCN1A Mutations with Epilepsy among Sudanese Patients

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Neuroscience & Medicine 2021年第3期12卷 90-102页

作者： Sanaa abdalaziz Mohamed Sawsan A.H. Aldeaf Rasha Elhassan Abasshar Hussein Alsadig Gassoum abd elkarim A. abdrabo Department of Clinical Chemistry Faculty of Medical Laboratory Sciences Al-Neelain University Khartoum Sudan National Center of Neurological Science Khartoum Sudan Almadain College for Medical Science and Technology Khartoum Sudan Department of Medicine Faculty of Medicine University of Khartoum Khartoum Sudan

Background: Genetics research of humans has established that a genetic basis contributes to the susceptibility to epilepsy for a majority of the cases. Although many epilepsies are secondary to injury or another illness, approximately 40% are idiopathic, meaning that the original cause is unknown. It is presumed that most idiopathic epilepsies result from genetic abnormalities, with the majority likely caused by mutations in multiple currently unidentified genes. However, research has revealed a growing number of single-gene mutations that cause epilepsy. Objective: To detect some of the genetic mutations which may cause idiopathic epilepsy. Methods: The current study is a cross-sectional study that had been performed at Sheikh Mohamed Khair center, Banat, Omdurman, and National Centre for Neurological Sciences (NCNS) Khartoum state, during the period 2016 to 2019. Ninety-nine participants were enrolled in this study. Demographic data were collected in a predesigned questionnaire blood samples were analyzed for biochemical and molecular tests. Results: Ninety-nine patients diagnosed with idiopathic epilepsy were recruited in this study. The most affected age group was 18 - 40 years accounted for 55% of patients. Females were the majority with 53%. Fifty percent of the patients had the first seizure at age less than 5 years. Ninety percent of the patients have no Family history with epilepsy. All sequenced samples showed genetic mutations, deletion mutation was detected in 71% of the samples. Bioinformatics tools detected a frameshift mutation in the chain of the amino acids. Conclusion: The current study detected deletion mutations in SCN1A gene (frameshift) can cause epilepsy by changing some amino acids with residues that can affect neuronal stability indirectly.

关键词： Epilepsy National Centre for Neurological Science Sudan SCN1A

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Association of SCN1A Mutations with Epilepsy among Sudanese Patients

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Neuroscience & Medicine（神经系统科学与医药） 2021年第3期

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