Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

The aim of this study is to develop a novel framework for managing risks in smart supply chains by enhancing business continuity and resilience against potential disruptions. This research addresses the growing uncertainty in supply chain environments, driven by both natural phenomena-such as pandemics and earthquakes—and human-induced events, including wars, political upheavals, and societal transformations. Recognizing that traditional risk management approaches are insufficient in such dynamic contexts, the study proposes an adaptive framework that integrates proactive and remedial measures for effective risk mitigation. A fuzzy risk matrix is employed to assess and analyze uncertainties, facilitating the identification of disr

The study aims to examine the problem of forced displacement and its social and economic problems in light of the Syrian crisis. Such an aim helps to know the difficulties and challenges facing the children of displaced families in learning, and the reasons for their lack of enrolment. It also clarifies whether there are significant statistical differences at  among the attitudes of the children of the displaced families towards education regarding the following variables: (the work of the head of the family, the economic level of the family, and the work of the children). The study has adopted the descriptive-analytical approach;  a questionnaire was adopted as a tool to collect information. The study was applied to a sample o

This work presents a completely new develop an analyzer, named NAG-5SX1-1D-SSP, that is simple, accurate, reproducible, and affordable for the determination of cefotaxime sodium (CFS) in both pure and pharmaceutical drugs. The analyzer was designed according to flow injection analysis, and conducted to turbidimetric measurements. Ammonium cerium nitrate was utilized as a precipitating agent. After optimizing the conditions, the analysis system exhibited a linear range of 0.008-27 mmol. L-1 (n=29), with a limit of detection of 439.3 ng/sample, a limit of quantification of 0.4805 mg/sample, and a correlation coefficient of 0.9988. The repeatability of the responses was assessed by performing six successive injections of CFS at concentra

The gas sensing properties of Co3O4and Co3O4:Y nano structures were investigated. The films were synthesized using the hydrothermal method on a seeded layer. The XRD, SEM analysis and gas sensing properties were investigated for Co3O4and Co3O4:Y thin films. XRD analysis shows that all films are polycrystalline in nature, having a cubic structure, and the crystallite size is (11.7)nm for cobalt oxide and (9.3)nm for the Co3O4:10%Y. The SEM analysis of thin films obviously indicates that Co3O4possesses a nanosphere-like structure and a flower-like structure for Co3O4:Y.The sensitivity, response time and recovery time to a H2S reducing gas were tested at different operating

Most studies on deep beams have been made with reinforced concrete deep beams, only a few studies investigate the response of prestressed deep beams, while, to the best of our knowledge, there is not a study that investigates the response of full scale (T-section) prestressed deep beams with large web openings. An experimental and numerical study was conducted in order to investigate the shear strength of ordinary reinforced and partially prestressed full scale (T-section) deep beams that contain large web openings in order to investigate the prestressing existence effects on the deep beam responses and to better understand the effects of prestressing locations and opening depth to beam depth ratio on the deep beam performance and b