Volume 9 | Issue 6 |

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

chemical components, extraction of gel , processing,extraction of aloin, uses, etc.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In the world, a countless number of people are missing every day which includes most of them are children's. Most of them remain untraced. This project proposes a system that would help the police and the public by accelerating the process of searching using face recognition. When a child goes missing, the police can upload the picture of the child by taking the latest picture of child from the parents when the case is registered and he get stores in the database. With the advent of the technology, especially cameras which are installed in many public and private areas to provide surveillance activities. The footage of the cameras can be used to recognize the pretrained missing child on scene. In this model, an automated facial recognition system for Missing Child database was proposed using known Haar feature-based cascade classifier. This system will be able to detect face and recognize face automatically in real time.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Missing Child; Open CV; Face Detection; Deep Learning.

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Creative Commons Attribution 4.0 and The Open Definition

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The paper tries to link the gap existing in between the role of social media and democratization in the Arab world through the theory of social constructivism. It reveals why various scholars have perceived democracy to be incompatible with the Arab world, which eventually made it difficult to understand the sudden emergence of pro-democracy protests, particularly in countries like Tunisia and Egypt. It further explains what social media is, primarily taking into account the social networking sites like Twitter and Facebook. It gives instances of how social media defied the earlier notions of being marginal or elitist and rather endowed a platform for the Arabs to voice their opinions and dissent, which they were unable to do so with the traditional Arab media. The paper scrutinizes democratic institutions in the Arab world as a structure and the emergence of social media as a process rather than a platform. The question of identities and interests of the Arabs are explained on the lines of family, clan, tribes, and ethnicities, religious and non-religious contexts. The impact of identity and interest in the process of transforming structures is further analysed

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Social Media, Democracy, Identities and Interests, Social Constructivism, Arab Uprisings

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

GPS, GSM, ITS ,SMS.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Python, Query-Resolving, Relevant-Query output, GUI, Stack API

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Convolutional Neural Network, OpenCV, TensorFlow, Keras, Transfer Learning

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The liver is the largest gland and largest internal organ in the human body. The abnormal growth of cell in the liver causes liver cancer which is also known as hepatic cancer where, Hepatocellular Carcinoma (HCC). Most of the peoples who have liver tumour were died due to the fact of inaccurate detection. The detection of this tumours is difficult and mostly found at advanced stage which causes life-threatening issues. Hence it is far essential to discover the tumour at an early stage. So, the principle intention of this project is to detect liver cancer at earlier stage using image processing technique. Computer-aided diagnosis from various medical imaging techniques can assist significantly in detecting liver cancer at a very early stage. This project presents an automated method of detecting liver cancer in abdominal CT images and classifying them using the support vector machine (SVM) algorithm. The proposed model consists of several stages where the image is first normalized and pre-processed using a Median filter to remove noise in the image. After histogram equalization of image, the features are extracted based on Discrete wavelet transformation (DWT). Finally, liver CT images are classified implementing support vector machine and segmented results. The software used here is MATLAB.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Liver tumour detection, CT image, DWT, GLCM, K-Mean clustering, SVM segmentation.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

WEFSA, cyber security, cloud computing, AWS.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Bipolar Disorder is a complex disorder that affects millions of people in the world.1in every 100 people are affected by bipolar disorder.One of the fields of work that could benefit from Machine Learning is, without doubt, the field of medicine. It is our belief that with the use of Machine Learning we can help both patients and doctors make a better diagnosis of this illness. The goal of this project is to apply different Machine Learning algorithms to symptoms based patient data in order to help create a prediction model. This model would make it easier for psychiatrists to decide whether their patients might be tending towards a depression or mania episode, or staying in a euthymic state.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Machine Learning, Python, Gitpod, Bipolar Disorder, Mental illness, Patient data, Episodes.

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Creative Commons Attribution 4.0 and The Open Definition