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
Style of Dostoevsky - it is a style that clearly emerges the desire for stimulating thought reader stage. It's a style calculated to provoke the reader to their findings, conclusions and reflections. Dostoevsky hints, expressed as like inaccurate and at the same time with some startling sophistication. It makes the readers think and draw their own conclusions.
Аннотация
Стиль Достоевского - этостиль, в которомясноотмечаетсястремлениек стимулированиюзаконченного мыслячитателя
... Show MoreThe Land Use/ Land Cover (LULC) is an essential application in many remotely sensed projects and problems. Land use is simply man-made objects such as urban, road complex targets, etc., while land covers are defined as any target and phenomenon that appear neutral. The LULC study is essential for all current and future engineering projects, as it shows the nature of the land's components, which is evident in studying and modernizing residential areas. One of the essential operations for studying LULC is the heterogeneity detection and classification calculations of satellite images and topographic maps. A part of the Baghdad, Iraq region was selected for the Landsat satellite group at different periods to detect variance and mak
... Show MoreClustering is an unsupervised learning method that classified data according to similarity probabilities. DBScan as a high-quality algorithm has been introduced for clustering spatial data due to its ability to remove noise (outlier) and constructing arbitrarily shapes. However, it has a problem in determining a suitable value of Eps parameter. This paper proposes a new clustering method, termed as DBScanBAT, that it optimizes DBScan algorithm by BAT algorithm. The proposed method automatically sets the DBScan parameters (Eps) and finds the optimal value for it. The results of the proposed DBScanBAT automatically generates near original number of clusters better than DBScanPSO and original DBScan. Furthermore, the proposed method
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Francisco de Quevedo is a well-known man of letters in the Golden Age of Spanish literature. He is the witness who related to us, in his works, the Spanish community in that era. He showed in most of his writings the political weakness of Spain, and made prominent the remarkable literary aspect of Spain. He had a very good tlent for poetry, and a rather polite style in exploiting colloquialisms in his literary writings. He wrote about philosophy, where his most prominent work was "The cradle and the grave". The writer was also very well-known for his puns which were employed to clarify his inner thoughts regarding the Spanish situation at that time.
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... Show MoreTourism plays an important role in Malaysia’s economic development as it can boost business opportunity in its surrounding economic. By apply data mining on tourism data for predicting the area of business opportunity is a good choice. Data mining is the process that takes data as input and produces outputs knowledge. Due to the population of travelling in Asia country has increased in these few years. Many entrepreneurs start their owns business but there are some problems such as wrongly invest in the business fields and bad services quality which affected their business income. The objective of this paper is to use data mining technology to meet the business needs and customer needs of tourism enterprises and find the most effective
... Show MoreThe objective that the researcher seeks to achieve through this research is to clarify the relationship between strategic management accounting techniques and the reliability of financial statements, and to measure the impact of these techniques as an independent variable with its three dimensions, which are: activities-based cost, target cost, and benchmarking on the reliability of financial statements as a dependent variable. To achieve this objective, the researcher did the following: First: Determine the research problem through the following question: Do strategic management accounting techniques affect the reliability of financial statements in industrial companies listed on the Palestine Exchange? Second: Making the analytical des
... Show MoreMillions of lives might be saved if stained tissues could be detected quickly. Image classification algorithms may be used to detect the shape of cancerous cells, which is crucial in determining the severity of the disease. With the rapid advancement of digital technology, digital images now play a critical role in the current day, with rapid applications in the medical and visualization fields. Tissue segmentation in whole-slide photographs is a crucial task in digital pathology, as it is necessary for fast and accurate computer-aided diagnoses. When a tissue picture is stained with eosin and hematoxylin, precise tissue segmentation is especially important for a successful diagnosis. This kind of staining aids pathologists in disti
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The great scientific progress has led to widespread Information as information accumulates in large databases is important in trying to revise and compile this vast amount of data and, where its purpose to extract hidden information or classified data under their relations with each other in order to take advantage of them for technical purposes.
And work with data mining (DM) is appropriate in this area because of the importance of research in the (K-Means) algorithm for clustering data in fact applied with effect can be observed in variables by changing the sample size (n) and the number of clusters (K)
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