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.
Domesticated translation has been for a long time the norm in cultural communication between nations all over the world. The texts are translated mainly into English (being the dominant language) in terms dictated principally by the requirements of the target language (English). The claim has been that fluency, readability, and immediate intelligibility can be guaranteed as far as the reader of the target language is concerned (English). The foreignness of the text (of the culture which produced it) would be not preserved. Not only this. Being the language of predominant cultures, English has become number one among languages into which texts are translated. The imbalance has been noticeable between the volumes of works translated from a
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreIn this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreThe Internet image retrieval is an interesting task that needs efforts from image processing and relationship structure analysis. In this paper, has been proposed compressed method when you need to send more than a photo via the internet based on image retrieval. First, face detection is implemented based on local binary patterns. The background is notice based on matching global self-similarities and compared it with the rest of the image backgrounds. The propose algorithm are link the gap between the present image indexing technology, developed in the pixel domain, and the fact that an increasing number of images stored on the computer are previously compressed by JPEG at the source. The similar images are found and send a few images inst
... Show MoreIn the reverse engineering approach, a massive amount of point data is gathered together during data acquisition and this leads to larger file sizes and longer information data handling time. In addition, fitting of surfaces of these data point is time-consuming and demands particular skills. In the present work a method for getting the control points of any profile has been presented. Where, many process for an image modification was explained using Solid Work program, and a parametric equation of the profile that proposed has been derived using Bezier technique with the control points that adopted. Finally, the proposed profile was machined using 3-aixs CNC milling machine and a compression in dimensions process has been occurred betwe
... Show MoreThe aim the research that definition on the impact a lot of Analysis and evaluation jobs impact in support the employees performance the property that are Analysis and evaluation jobs is one of the jobs however of the human resource management on organization and the impact footpace big on the chractericties and performance of the people and the impact that success of the organization , And here problem stool of the research in the omission the role for the Analysis and evaluation jobs impact in support the employees performance from the upward management in the organization , Polls were adopted as tools for obtaining data and the Depart
... Show MoreGeophysics is one of the branches of Earth sciences and deals with studying the Earth's interior by studying the variation of physical properties within rock layers. Applied geophysics depends on procedures that involve the measurements of potential fields, such as the gravitational method. One of the significant oil fields in southern Iraq is represented by the Nahr Omar structure. A power spectrum analysis (SPA) technique was used to collect gravity data within the chosen oil field area in order to confirm the salt dome in the subsurface layers. The analysis of SPA resulted from six surfaces representing the gravity variation values of the depths (m)14300, 3780, 3290, 2170, 810, and 93.5. Gravity surfaces have been converted to de
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