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AlSabban, Wesam H.,Alotaibi, Saud S.,Farag, Abdullah Tarek,Rakha, Omar Essam,Al Sallab, Ahmad A.,Alotaibi, Majid International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.9
The Islamic jurisprudential legal system represents an essential component of the Islamic religion, that governs many aspects of Muslims' daily lives. This creates many questions that require interpretations by qualified specialists, or Muftis according to the main sources of legislation in Islam. The Islamic jurisprudence is usually classified into branches, according to which the questions can be categorized and classified. Such categorization has many applications in automated question-answering systems, and in manual systems in routing the questions to a specialized Mufti to answer specific topics. In this work we tackle the problem of automatic categorisation of Islamic jurisprudential legal questions using deep learning techniques. In this paper, we build a hierarchical deep learning model that first extracts the question text features at two levels: word and sentence representation, followed by a text classifier that acts upon the question representation. To evaluate our model, we build and release the largest publicly available dataset of Islamic questions and answers, along with their topics, for 52 topic categories. We evaluate different state-of-the art deep learning models, both for word and sentence embeddings, comparing recurrent and transformer-based techniques, and performing extensive ablation studies to show the effect of each model choice. Our hierarchical model is based on pre-trained models, taking advantage of the recent advancement of transfer learning techniques, focused on Arabic language.
Prognostic and Oncologic Significance of Perineural Invasion in Sporadic Colorectal Cancer
Alotaibi, A. M.,Lee, J. L.,Kim, J.,Lim, S. B.,Yu, C. S.,Kim, T. W.,Kim, J. H.,Kim, J. C. Springer Science + Business Media 2017 Annals of Surgical Oncology Vol.24 No.6
<P>PNI positivity is an independent predictor of aggressive behavior and unfavorable prognosis in CRC. Further evaluation is needed to confirm the impact of PNI status on survival in stage IIA CRC.</P>
Evaluating Conversion Rate from Advertising in Social Media using Big Data Clustering
Alyoubi, Khaled H.,Alotaibi, Fahd S. International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.7
The objective is to recognize the better opportunities from targeted reveal advertising, to show a banner ad to the consumer of online who is most expected to obtain a preferred action like signing up for a newsletter or buying a product. Discovering the most excellent commercial impression, it means the chance to exhibit an advertisement to a consumer needs the capability to calculate the probability that the consumer who perceives the advertisement on the users browser will acquire an accomplishment, that is the consumer will convert. On the other hand, conversion possibility assessment is a demanding process since there is tremendous data growth across different information dimensions and the adaptation event occurs infrequently. Retailers and manufacturers extensively employ the retail services from internet as part of a multichannel distribution and promotion strategy. The rate at which web site visitors transfer to consumers is low for online retail, out coming in high customer acquisition expenses. Approximately 96 percent of web site users concluded exclusive of no shopper purchase[1].This category of conversion rate is collected from the advertising of social media sites and pages that dataset must be estimating and assessing with the concept of big data clustering, which is used to group the particular age group of people along with their behavior. This makes to identify the proper consumer of the production which leads to improve the profitability of the concern.
Effect of ZrC additives on the microstructure and hardness of ZrN-ZrSi2 composite
Z. I. Zaki,S. H. Alotaibi,M. Alsawat,B. A. Alhejji 한양대학교 세라믹연구소 2021 Journal of Ceramic Processing Research Vol.22 No.4
High-density zirconium nitride ZrN/ZrSi2 composite reinforced with different fractions of insitu formed ZrC were synthesizedby dynamic-compaction combustion synthesis from Zr–Si3N4–C powder blends. The effect of ZrC fractions, compressionloads, and delay time on the composite properties was investigated. ZrC additives were found to decrease the sample porosityand improve the sample hardness. Increasing the compression load greatly enhanced the sample hardness and reduced thesample porosity. The samples were characterized using XRD, SEM, hardness and porosity. The attained composite having 20wt% ZrC was found to furnish a highly homogeneous microstructure with less than 1.0 vol open porosity and a maximumhardness value of 1308 HV achieved at 234 MPa compression load.
Studying the self-healing reaction based on zirconium silicide in the Thermal Barrier Coating system
Z. I. Zaki,Q. Mohsen,S. H. Alotaibi,M. H. El-Sadek 한양대학교 세라믹연구소 2020 Journal of Ceramic Processing Research Vol.21 No.2
This work investigated the behaviour of introducing ZrSi2 layer between the top coat layer Yttria-stabilized zirconia (YSZ)and the bond coat layer CoNiCrAlY in thermal barrier coatings where ZrSi2 layer helped self-healing of the cracks. Powdermixtures of ZrSi2/8YSZ and ZrSi2 /CoNiCrAlY were used to imitate the real case. At 800 °C under argon, there was no changein the chemical composition of both ZrSi2 and 8YSZ. ZrSi2 was oxidized in case of treatment in air atmosphere at 800 °C withno evidence for any self-healing reactions. At 1000 and 1200 °C under argon the formation of ZrSiO4 phase was detected whichwas a strong evidence of self-healing reaction. ZrSiO4 phase was also detected at 1200 °C in air with the appearance of SiO2phase. A limited interaction was detected at 1000 °C between ZrSi2 and CoNiCrAlY under vacuum. Si was detected in thesurface of CoNiCrAlY grains and Ni was detected in the composition of ZrSi2. This behavior could contribute to a chemicalbonding between ZrSi2 and CoNiCrAlY layers. The obtained data were confirmed by XRD, SEM and EDX analyses.