Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th

Abstract

    In order to enhance the efficiency of flat plate solar water collectors without changing in its original shape and with low additional cost, twisted strips are inserted inside its riser pipes. Three flat plate collectors are used for test. Family of twisted strips are inserted inside each collector risers with different twisted ratios (T_R=3,4,5). The collectors are connected in parallel mode (Z-Configuration) and are exposed to the same conditions (solar radiation and ambient temperature) .The experimental results show that, the highest heat transfer rate occurs at twisted ratio (3) .Consequently, for the same twisted ratio the daily efficiencies for the solar collector at d

In this study, nanocomposites have been prepared by adding
multiwall carbon nanotubes (MWCNTs) with weight ratios (0, 2, 3,
4, 5) wt% to epoxy resin. The samples were prepared by hand lay-up
method. Influence of an applied load before and after immersion in
sodium hydroxide (NaOH) of normality (0.3N) for (15 days) at
laboratory temperature on wear rate of Ep/MWCNTs
nanocomposites was studied. The results showed that wear rate
increases with increasing the applied load for the as prepared and
immersed samples and after immersion. It was also found that epoxy
resin reinforced with MWCNTs has wear rate less than neat epoxy.
The sample (Ep + 5wt% of MWCNTs) has lower wear rate. The
immersion effect in base so

This paper presents ABAQUS simulations of fully encased composite columns, aiming to examine the behavior of a composite column system under different load conditions, namely concentric, eccentric with 25 mm eccentricity, and flexural loading. The numerical results are validated with the experimental results obtained for columns subjected to static loads. A new loading condition with a 50 mm eccentricity is simulated to obtain additional data points for constructing the interaction diagram of load-moment curves, in an attempt to investigate the load-moment behavior for a reference column with a steel I-section and a column with a GFRP I-section. The result comparison shows that the experimental data align closely with the simulation

Background: Optimal root canal retreatment was required safe and efficient removal of filling material from root canal. The aim of this in vitro study was to compare the efficacy of reciprocating and continuous motion of four retreatment systems in removal of root canal filling material. Materials and Methods: Forty distal roots of the mandibular first molars teeth were used in this study, these roots were embedded in cold clear acrylic,roots were instrumented using crown down technique and rotary ProTaper systemize Sx to size F2 ,instrumentation were done with copiousirrigation of 2.5% sodium hypochlorite and 17% buffered solution of EDTA was used as final irrigant followed by distilledwater, roots were obturated with AH26 sealer and Prota

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi