The technology in continuous and quick development, that reflects in all parts of our life and interred both scientific and practical fields. Marketing is one of them, a customer’s way to deal with choosing and demanding the product deferent from the traditional way. Some of the buying processes are electronic now, therefore the current research is identifying the digital channels that entered the world of marketing and influenced the activities and types that fall under this name and how it affects in positioning strategy, which is how to install the product or brand in the mind of the customer and was dimensions (brand identity, brand personality, brand communication, brand awareness, brand image), The researcher took t

Objective(s): Biocompatibility, non-toxicity, minimal allergenicity, and biodegradability are all characteristics of chitosan. Other biological properties of chitosan have been reported, including antitumor, antimicrobial and antioxidant activities. This research aim is the synthesis of drug compounds by preparation and characterization of polymer chitosan Schiff base and chitosan Schiff base / Poly vinyl alcohol / poly vinyl pyrrolidone Nanocomposite and study applications (anticancer cell line, antimicrobial agents). Methods: Chitosan Schiff base was prepared from the reaction of chitosan with carbonyl group of 4-nitro benzaldehyde. Polymer blend have been prepared by solution casting method. Chitosan Schiff base mixing with PVA and PVP

This study aims to explore the relationship between the degree of application of digital leadership and the development of administrative work at the University of Tabuk. It further aims to examine the presence of statistically significant differences between the average responses of faculty members and employees at the University of Tabuk regarding the study axes that are attributed to the following variables: (scientific rank, gender, and job), the study used the descriptive approach in its correlative style, and the questionnaire was used as a tool for data collection, as it was applied to a simple random of (310) members of the faculty and staff. University of Tabuk. The results showed that the degree of digital leadership applicatio

Aspect categorisation and its utmost importance in the eld of Aspectbased Sentiment Analysis (ABSA) has encouraged researchers to improve topic model performance for modelling the aspects into categories. In general, a majority of its current methods implement parametric models requiring a pre-determined number of topics beforehand. However, this is not e ciently undertaken with unannotated text data as they lack any class label. Therefore, the current work presented a novel non-parametric model drawing a number of topics based on the semantic association present between opinion-targets (i.e., aspects) and their respective expressed sentiments. The model incorporated the Semantic Association Rules (SAR) into the Hierarchical Dirichlet Proce

The choice of binary Pseudonoise (PN) sequences with specific properties, having long period high complexity, randomness, minimum cross and auto- correlation which are essential for some communication systems. In this research a nonlinear PN generator is introduced . It consists of a combination of basic components like Linear Feedback Shift Register (LFSR), ?-element which is a type of RxR crossbar switches. The period and complexity of a sequence which are generated by the proposed generator are computed and the randomness properties of these sequences are measured by well-known randomness tests.

Cancer is in general not a result of an abnormality of a single gene but a consequence of changes in many genes, it is therefore of great importance to understand the roles of different oncogenic and tumor suppressor pathways in tumorigenesis. In recent years, there have been many computational models developed to study the genetic alterations of different pathways in the evolutionary process of cancer. However, most of the methods are knowledge-based enrichment analyses and inflexible to analyze user-defined pathways or gene sets. In this paper, we develop a nonparametric and data-driven approach to testing for the dynamic changes of pathways over the cancer progression. Our method is based on an expansion and refinement of the pathway bei

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

This paper presents a new algorithm in an important research field which is the semantic word similarity estimation. A new feature-based algorithm is proposed for measuring the word semantic similarity for the Arabic language. It is a highly systematic language where its words exhibit elegant and rigorous logic. The score of sematic similarity between two Arabic words is calculated as a function of their common and total taxonomical features. An Arabic knowledge source is employed for extracting the taxonomical features as a set of all concepts that subsumed the concepts containing the compared words. The previously developed Arabic word benchmark datasets are used for optimizing and evaluating the proposed algorithm. In this paper,

This paper interest to estimation the unknown parameters for generalized Rayleigh distribution model based on censored samples of singly type one . In this paper the probability density function for generalized Rayleigh is defined with its properties . The maximum likelihood estimator method is used to derive the point estimation for all unknown parameters based on iterative method , as Newton – Raphson method , then derive confidence interval estimation which based on Fisher information matrix . Finally , testing whether the current model ( GRD ) fits to a set of real data , then compute the survival function and hazard function for this real data.