Arabic text categorization for pattern recognitions is challenging. We propose for the first time a novel holistic method based on clustering for classifying Arabic writer. The categorization is accomplished stage-wise. Firstly, these document images are sectioned into lines, words, and characters. Secondly, their structural and statistical features are obtained from sectioned portions. Thirdly, F-Measure is used to evaluate the performance of the extracted features and their combination in different linkage methods for each distance measures and different numbers of groups. Finally, experiments are conducted on the standard KHATT dataset of Arabic handwritten text comprised of varying samples from 1000 writers. The results in the generation step are obtained from multiple runs of individual clustering methods for each distance measures. The best results are achieved when intensity, lines slope and their
This work presents a novel technique for the detection of oil aging in electrical transformers using a single mode optical fiber sensor based on surface plasmon resonance (SPR). The aging of insulating oil is a critical issue in the maintenance and performance of electrical transformers, as it can lead to reduce insulation properties, increase risk of electrical breakdown, and decrease operational lifespan. Many parameters are calculated in this study in order to examine the efficiency of this sensor like sensitivity (S), signal to noise ratio (SNR), resolution (refractive index unit) and figure of merit (FOM) and the values are for figure of merit is 11.05, the signal to noise ratio is 20.3, the sensitivity is 6.63, and the resolution is 3
... Show MoreTo evaluate the cost-effectiveness of emicizumab compared to recombinant activated factor VII (rFVIIa) in Iraqi patients with hemophilia A and inhibitors.
A retrospective cost-effectiveness analysis was conducted on 46 male patients with hemophilia A and inhibitors treated at a public children’s hospital in Baghdad. Data collection was conducted between November 2024 and March 2025. Clinical and economic data were retrospectively collected for a 12-m
This work is devoted to a comparative study of the phenomenon of enantiosemy in Russian and Arabic.Everyone knows the term antonyms - words of the same part of speech, opposite in meaning, such as: Day and night, white and black, truth and lies. But in Russian, Arabic and other languages there is an interesting phenomenon, which consists in the fact that one word has two opposite meanings. Such a phenomenon in linguistics is called enantiosemy (from the Greek words enantios - "opposite" and sema - "sign")
Socio-scientific issues provide a great platform to both engage students in scientific topics and assess their understanding of scientific concepts. Nancy R. Singer, Amy Lannin, Maha Kareem, William Romine, and Katie Kline report on the STEM Literacy Project, a three-year National Science Foundation grant that aimed to improve STEM teachers’ knowledge and integration of literacy in their classrooms. They describe teachers’ professional learning, scenario-based assessments and other strategies they incorporated in their STEM classrooms, and how writing enables students to understand real-world issues.
Polyaniline Multi wall Carbon nanotube (PANI/MWCNTs) nanocomposite thin films have been prepared by Plasma jet polymerization at low frequency on glass substrate with preliminary deposited aluminum electrodes to form Al/PANI-MWCNT/Al surface-type capacitive humidity sensors, the gap between the electrodes about 50 μm and the MWCNTs weight concentration varied between 0, 1, 2, 3, 4%. The diameter of the MWCNTs was in the range of 8-15 nm and the length 10-55 μm. The capacitance-humidity relationships of the sensors were investigated at humidity levels from 35 to 90% RH. The electrical properties showed that the capacity increased with increasing relative humidity, and that the sensitivity of the sensor increases with the increase of the
... Show MoreRecommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o
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