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A new robust blind image watermarking method based on lifting wavelet transform (LWT), and Schur decomposition in combination with discrete cosine transform (DCT), and entropy analysis for copyright protection of multimedia information is introduced in this paper. At first, the 2-level LWT is applied to the original image to improve the invisibility of the watermarking method and then the high-frequency sub-band of 2-level LWT is decomposed by DCT. Then, the DCT coefficients are divided into 4×4 non-overlapping blocks. After that, Schur decomposition applies to each selected block, while the first row, the first column element of the upper triangular matrix is used to embed the watermark. For evaluation, the invisibility and robustness of the proposed watermarking method, the peak signal to noise ratio (PSNR), and normalized cross-correlation (NC) are used to measure the quality and the ability of the proposed watermarking method to be robust against signal processing operations and geometric attacks. Experimental results have demonstrated that the proposed method is achieved a very good tradeoff between invisibility and robustness. The comparisons with other scheme have shown that the proposed digital watermarking scheme has a superior performance in terms of invisibility than other. 

Abstract:

In this research study, we investigate the effectiveness of a proposed automated framework that leverages AI algorithms to improve the accuracy, scalability, and efficiency of data analysis. We compare the performance of the proposed framework to traditional data analysis methods in terms of accuracy, time and effort required for data analysis, and scalability. We conducted a questionnaire-based survey to collect data on the application of the proposed framework and traditional data analysis methods in real-world scenarios. We used statistical analyses, including t-tests and regression analyses, to analyze the data and draw conclusions. Our findings indicate that the proposed automated framework outperforms traditional data analysis methods in terms of accuracy, reduces the time and effort required for data analysis, and has better scalability for processing large datasets in real-time. Our results suggest that the proposed framework offers significant benefits for organizations seeking to improve their data analysis processes. However, we also note the importance of considering the costs and benefits of implementing the framework, as well as any ethical or legal implications. Further research is recommended to confirm the findings and to investigate the effectiveness of the proposed framework in different contexts and with different datasets.

Abstract

Background: Cutaneous Leishmaniasis (CL) is a disease transmitted by infected sandflies in tropical and subtropical areas of the world. Over 12 million people are infected with CL, with 90% of cases occurring in Afghanistan, Iran, Algeria, Brazil, Peru, Saudi Arabia, Syria, and Libya. CL causes localized skin lesions that may disappear without treatment or persist, causing severe tissue damage, permanent disfigurement, and serious disability. Physical methods such as cryotherapy, heat therapy, photodynamic therapy, laser, and radiofrequency have shown promising results in treating CL. However, none of the suggested treatments are universally effective, and many of them are associated with serious local and systemic side effects. Early diagnosis and treatment can cure the disease, prevent psychological impact, and help in the prevention of transmission. Different therapeutic modalities (monotherapy or combined therapy) were used in patient treatment, with different approaches planned according to the severity and duration of the condition.

Patients and methods: The study was conducted on 60 Patients who were divided into three groups: 20 patients treated with dapsone tab 100mg once daily for one month and 20 with radiofrequency, the third group, 20 Patients were treated with a combination of dapsone tab 100mg and radiofrequency. Treatment sessions were scheduled 1 session every 2 weeks. Statistical analysis was carried out using SPSS software version 18 (USA).

Results and Discussion: Patients underwent weekly physical exams to evaluate clinical response and adverse effects. Clinical response was classified as complete, good, or poor. Data were analyzed using one-way NOVA, Turkey's test, chisquare test, ANOVA, and Fischer's exact test. There was no significant difference among studied groups regarding demographic data. Patients treated with dapsone and radiofrequency were significantly more cleared in 1-2 months than those treated with radiofrequency alone. Conclusion: Patients had weekly physical exams to evaluate the clinical response and adverse effects. Clinical response was classified as complete, good, or poor. Data was analyzed using various tests. Dapsone and radiofrequency-treated patients cleared more in 1-2 months.

Keywords: Cutaneous leishmaniasis; Dapsone; Radiofrequency; Aalgabal algarby; Libya

This study investigated the challenges facing 4^th year Health Sciences College students in Gharyan University in translating/ learning English medical terms into Arabic. Two types of instruments were used to collect quantitative data needed for answering the research questions. The study participants were asked to translate and analyse some given medical English terms into Arabic, and via a questionnaire items they were asked to select the strategies they used to translate and analyse the given terms. The results revealed that many of the participants failed to translate the given medical terms into Arabic and most of them failed to analyse the terms into their individual segments. The analysed questionnaire data showed that most of the participants prefer to use bilingual dictionaries in translating the given terms. Explicit teaching of the medical terms translation with the focus on the meaning of the affixes and the roots of the terms may help in achieving correct translation of any English medical terms into Arabic language.  

Key words: challenges, medical terms, quantitative data, questionnaire.