A resume is the first impression between you and a potential employer. Therefore, the importance of a resume can never be underestimated. Selecting the right candidates for a job within a company can be a daunting task for recruiters when they have to review hundreds of resumes. To reduce time and effort, we can use NLTK and Natural Language Processing (NLP) techniques to extract essential data from a resume. NLTK is a free, open source, community-driven project and the leading platform for building Python programs to work with human language data. To select the best resume according to the company’s requirements, an algorithm such as KNN is used. To be selected from hundreds of resumes, your resume must be one of the best. Therefore, our work also focuses on creating an automated system that can recommend the right skills and courses to help the desired candidates by using Natural Language Processing to analyze writing style (linguistic fingerprints) and also used to measure style and analyze word frequency from the submitted resume. Through semantic search and relying on individual resumes, forensic experts can query the huge semantic datasets provided to companies and institutions and facilitate the work of government forensics by obtaining official institutional databases. With global cybercrime and the increase in applicants seeking work and leveraging their multilingual data, Natural Language Processing (NLP) is making it easier. Through the important relationship between Natural Language Processing (NLP) and digital forensics, NLP techniques are increasingly being used to enhance investigations involving digital evidence and leverage the support of NLP for open-source data by analyzing massive amounts of public data.
The study attempts to assess water quality in Abu-Zirig Marsh which used epiphytic Diatom community for assessing water quality. Many of Diatom indices {Trophic diatom index (TDI), Diatom index (DI), Generic diatom index (GDI) have been used to give qualitative information about the status of the freshwater ecosystem(good, moderate, high pollution). In this study, the epiphytic diatoms on both host aquatic plants Phragmites australis and Typha domengensis were collected from Abu-Zirig Marsh within Thi-Qar Province at three sites in Autumn, 2018 and winter, 2019. Epiphytic diatoms were Identified by the preparation of permanent slides method, some species of epiphytic diatom showed dominance such as Cyclotella menegh
... Show MoreSuccessfully, theoretical equations were established to study the effect of solvent polarities on the electron current density, fill factor and efficiencies of Tris (8-hydroxy) quinoline aluminum (Alq3)/ ZnO solar cells. Three different solvents studied in this theoretical works, namely 1-propanol, ethanol and acetonitrile. The quantum model of transition energy in donor–acceptor system was used to derive a current formula. After that, it has been used to calculate the fill factor and the efficiency of the solar cell. The calculations indicated that the efficiency of the solar cell is influenced by the polarity of solvents. The best performance was for the solar cell based on acetonitrile as a solvent with electron current density of (5.0
... Show MoreA new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification
... 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
... Show MoreAbstract: Lymphoproliferative Disorders (LPDs) are a group of neoplasms affecting various cells within lymphoid system. Each type has different treatment a..70619
In this research local wheat peel was used as an adsorbent surface for removal of Azure B (AB) dye from the aqueous solution. The adsorption process was performed at different experimental parameters, equilibrium time, temperature, ionic strength and solution pH. The isotherms of adsorption are of H-type as compared with Giles curves and the adsorption data were coincide with Freundlich equation. The adsorption kinetic data were analyzed using pseudo- first and second order kinetic models. The effect of temperature was studied and the amount of dye adsorbed was found to increase with the increasing of temperature from 25 to 50 oC. The values of thermodynamic functions like enthalpy and entropy have been estimated. The quantity of adso
... Show MoreBP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.
Background: Salivary tumors are uncommon, being of low incidence worldwide. This study aimed to assess cases collected in this series of salivary gland tumors in regard to histopathological typing, in relation to age, site and gender. Materials and methods: This is a retrospective study; cases were collected from public and private laboratories. A total number of 171 cases were collected. The slides were reviewed and reclassified for histopathological typing according to WHO classification 2005. Results: Benign tumors were more common than malignant tumors. The most common histological type was benign mixed tumor, followed by Warthin’s tumor. The most common malignant tumor was adenoid cystic carcinoma. One hundred twenty three cases ou
... Show MoreThat the main feature of the economics many countries in general is a tendency towards defining the role of the public sector in economic activity and the tendency towards encourage the private sector to investment in public projects especially in countries those tendency towards market economy actually.
That increased economic development proven failure in achieving more economic growth both individually in many countries especially developing countries socialist, by researchers this led one way or another to direction of corrective reforms in their economic was one of them in Transformation of public companies into Shareholding companies contributes to the public sector in resources and expertise
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