The mobile phone is widespread all over the world. This technology is one of the most widespread with more than five billion subscriptions making people describe this interaction system as Wireless Intelligence. Mobile phone networks become the focus of attention of researchers, organizations and governments due to its penetration in all life fields. Analyzing mobile phone traces allows describing human mobility with accuracy as never done before. The main objective in this contribution is to represent the people density in specific regions at specific duration of time according to raw data (mobile phone traces). This type of spatio-temporal data named CDR (Call Data Records), which have properties of the time and spatial indications for the elaborated environment. City life understandings help urban planners, decision makers, and scientists of different fields to resolve their questions about human mobility. Such studies are using a very cheap, most spread tool that is the mobile phone. Mobile phone traces analysis gives conceptual views about human density, connections and mobility patterns. In this study, the mobile phone traces concern an ephemeral event called Armada, where important densities of people are observed during 12 days in the French city of Rouen. To better understand how people attracted by this event, city area during these days of this ephemeral event, is used. Armada mobile phone database is analyzed using a computing platform integrating various applications for huge database management, visualization and analysis, in order to explore the urban pulse generated by this event. As result, city pulsation and life patterns are explored and visualized for specified regions.
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Cryptography algorithms play a critical role in information technology against various attacks witnessed in the digital era. Many studies and algorithms are done to achieve security issues for information systems. The high complexity of computational operations characterizes the traditional cryptography algorithms. On the other hand, lightweight algorithms are the way to solve most of the security issues that encounter applying traditional cryptography in constrained devices. However, a symmetric cipher is widely applied for ensuring the security of data communication in constraint devices. In this study, we proposed a hybrid algorithm based on two cryptography algorithms PRESENT and Salsa20. Also, a 2D logistic map of a chaotic system is a
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The aim of this work is to shed light on the importance of medicinal plants, especially those that have extracts that have a direct effect on human health. The study and identification of botany is necessary because human life has become closely linked to the life of plants as food . In addition to using plants as food, primitive man did not stop at this point, but rather developed their use to hunt prey and also used toxic plant materials in wars. With the passage of time, the ancient man was able to link the wild plants that cover the surface of the earth and the diseases that afflict him, so he used these plants or Parts of it are for treatment. A medicinal plant is defined as one or more of its parts that contain one or more che
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This study reports the formation, characterisation and biological evaluation of a Schiff base ligand and its corresponding metal complexes. The Schiff base ligand (HL) was prepared through a condensation reaction involving isonicotinohydrazide and N'-((1R,2R,4R,5S, E)-2,4-bis(4-chlorophenyl)-3-azabi cyclo[3.3.1]nonan-9-ylidene) isonicotinohydrazide (M) in EtOH solvent and (3-5) drops of conc. HCl. The interaction of HL with selected metal chlorides including Mn(+2), Co(+2), Ni(+2), Cu(+2) and Zn(+2) in a 2:1 (L:M) mole ratio resulted in the synthesis of complexes with the general formula [M(HL)Cl2] (where: M = Mn(+2),Co(+2) and Ni(+2)) and [M`(HL)Cl2] (where M` = Cu(+2) and Zn(+2)). The characterisation of the prepared compounds w
... Show MoreBackground: Rheumatoid arthritis (RA) is a chronic and systemic autoimmune disease that is characterized by severe synovial inflammation, cartilage erosion, bone loss, and generalized vasculopathy. Although the immunologic mechanism of RA is still unclear, it is now thought to be a primarily Th17-driven disease. Along with other factors, IL-23 stimulates the expansion of Th17 cells from naive CD4+ T cells.
Objective: The objective of this study is to assess the circulating levels of interleukin (IL)-23 in rheumatoid arthritis (RA) and determine the correlation between plasma/serum IL-23 levels and disease activity. So, we performed a systematic review with meta-analysis comparing
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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
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The aim of this paper is to derive a posteriori error estimates for semilinear parabolic interface problems. More specifically, optimal order a posteriori error analysis in the - norm for semidiscrete semilinear parabolic interface problems is derived by using elliptic reconstruction technique introduced by Makridakis and Nochetto in (2003). A key idea for this technique is the use of error estimators derived for elliptic interface problems to obtain parabolic estimators that are of optimal order in space and time.
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