A Mosque Among the Stars

A Mosque Among The Stars was the first anthology that dealt with the subject of Muslim characters and/or Islamic themes and Science Fiction

A Mosque Among the Stars

A Mosque Among The Stars was the first anthology that dealt with the subject of Muslim characters and/or Islamic themes and Science Fiction

Creating Trustworthy LLMs: Dealing with Hallucinations in Healthcare AI

Large language models have proliferated across multiple domains in as short period of time. There is however hesitation in the medical and healthcare domain towards their adoption because of issues like factuality, coherence, and hallucinations. Give the high stakes nature of healthcare, many researchers have even cautioned against its usage until these issues are resolved. The key to the implementation and deployment of LLMs in healthcare is to make these models trustworthy, transparent (as much possible) and explainable. In this paper we describe the key elements in creating reliable, trustworthy, and unbiased models as a necessary condition for their adoption in healthcare. Specifically we focus on the quantification, validation, and mitigation of hallucinations in the context in healthcare. Lastly, we discuss how the future of LLMs in healthcare may look like

Customer churn prediction using composite deep learning technique

Customer churn, a phenomenon that causes large financial losses when customers leave a business, makes it difficult for modern organizations to retain customers. When dissatisfied customers find their present company\u27s services inadequate, they frequently migrate to another service provider. Machine learning and deep learning (ML/DL) approaches have already been used to successfully identify customer churn. In some circumstances, however, ML/DL-based algorithms lacks in delivering promising results for detecting client churn. Previous research on estimating customer churn revealed unexpected forecasts when utilizing machine learning classifiers and traditional feature encoding methodologies. Deep neural networks were also used in these efforts to extract features without taking into account the sequence information. In view of these issues, the current study provides an effective method for predicting customer churn based on a hybrid deep learning model termed BiLSTM-CNN. The goal is to effectively estimate customer churn using benchmark data and increase the churn prediction process\u27s accuracy. The experimental results show that when trained, tested, and validated on the benchmark dataset, the proposed BiLSTM-CNN model attained a remarkable accuracy of 81%

Microfacies Analysis and Depositional Environment of Middle Jurassic Samana Suk Formation, Chichali Nala Section, Surghar Range, Pakistan

The Middle Jurassic age Samana Suk Formation, exposed in Chichali Nala section of Surghar ranges has been investigated by field work, petrographic study and XRD analysis to understand the microfacies, depositional environment and fault related dolomitization of the Samana Suk Formation. This formation is widely distributed in the upper Indus basin of Pakistan and considered the most prominent stratigraphic unit of the Jurassic period. The project area lies in the Chichali Nala Section of Surghar range (Trans Indus Salt Ranges). In this section, Samana Suk Formation constitutes the lithology of carbonate having CaCo3 as a major mineral, where dolomite is present in minor amount, which is restricted to fluids along fault zone. During the study two major microfacies have been identified including the Grainstone microfacies and Mudstone-Wackestone microfacies. Samana Suk. Formation was formed under stormy influence in the environment of deposition of Formation. Its depositional environment is the inner-middle shelf which suggests the marine shelf depositional environment

Peringkat Daerah Rawan Pangan Berdasarkan Data Spasial Di Provinsi Aceh1 (Analise of Food Insecurity Base on Spatial in Nanggroe Aceh Darussalam Province)

Tujuan penelitian ini dalah untuk mengelompokkan daerah rawan pangan dan memetakanwilayah rawan pangan tingkat kabupaten/kota di Provinsi Aceh, mengidentifikasi karakteristik danfaktor-faktor penyebab rawan pangan pada setiap wilayah. Penelitian dilaksanakan di ProvinsiAceh yang meliputi 23 kabupaten/kota selama 8 bulan. Penelitian menggunakan metode survey,analisis secara deskriptif terhadap data sekunder yang meliputi : data pertanian, kesehatan, dan sosialekonomi. Hasil penelitian menunjukkan ada dua tingkatan wilayah rawan pangan di Provinsi Acehyaitu; tingkat kerawanan pangan sedang (21,7%), dan tingkat kerawanan tinggi (78,3%).Jumlah Kabupaten/kota dengan kategori kerawanan pangan tinggi lebih dari 3 kali lipatdibandingkan dengan daerah tingkat kerawanan sedang

2-[3-(4-Methoxyphen­yl)-1-phenyl-1H-pyrazol-5-yl]phenol

The title compound, C22H18N2O2, was derived from 1-(2-hydroxy­phen­yl)-3-(4-methoxy­phen­yl)propane-1,3-dione. The central pyrazole ring forms dihedral angles of 16.83 (5), 48.97 (4) and 51.68 (4)°, respectively, with the methoxy­phenyl, phenyl and hydroxy­phenyl rings. The crystal packing is stabilized by O—H⋯N hydrogen bonding