http://hdl.handle.net/10366/145968 2026-05-06T09:38:21Z 2026-05-06T09:38:21Z Srivastav, Rishi Kumar Agrawal, Devendra Shrivastava, Anurag http://hdl.handle.net/10366/146094 2025-06-05T12:36:20Z 2020-06-01T00:00:00Z

The blockchain technology firstly presented by Haber and Stornetta in the year 1990, and first time blockchain technology used in Bitcoin by Satoshi Nakamoto in 2008. The blockchain technology is truly decentralized technology. In blockchain technology, every block has consisted three main parts that is data, hash block, and the previous hash block. Hash is controls the uniqueness of each block and it is unique for each block. Each block also contains the hash of the previous block; thus, the blocks are connected to each other. A blockchain can divided into three categories public blockchain, consortium blockchain and private blockchain. The proposed paper provided the comparative and analytical review on the blockchain consensus algorithms.

2020-06-01T00:00:00Z Fatima, Noor http://hdl.handle.net/10366/146093 2025-06-05T12:36:20Z 2020-06-20T00:00:00Z

Adopting the most suitable optimization algorithm (optimizer) for a Neural Network Model is among the most important ventures in Deep Learning and all classes of Neural Networks. It's a case of trial and error experimentation. In this paper, we will experiment with seven of the most popular optimization algorithms namely: sgd, rmsprop, adagrad, adadelta, adam, adamax and nadam on four unrelated datasets discretely, to conclude which one dispenses the best accuracy, efficiency and performance to our deep neural network. This work will provide insightful analysis to a data scientist in choosing the best optimizer while modelling their deep neural network.

2020-06-20T00:00:00Z Adcaij, Editorial Team http://hdl.handle.net/10366/146095 2025-06-05T12:36:20Z 2020-11-30T00:00:00Z 2020-11-30T00:00:00Z Mishra, Akshansh http://hdl.handle.net/10366/146092 2025-06-05T12:36:20Z 2020-06-19T00:00:00Z

Friction Stir Welding process is an advanced solid-state joining process which finds application in various industries like automobiles, manufacturing, aerospace and railway firms. Input parameters like tool rotational speed, welding speed, axial force and tilt angle govern the quality of Friction Stir Welded joint. Improper selection of these parameters further leads to fabrication of the joint of bad quality resulting groove edges, flash formation and various other surface defects. In the present work, a texture based analytic machine learning algorithm known as Local Binary Pattern (LBP) is used for the extraction of texture features of the Friction Stir Welded joints which are welded at a different rotational speed. It was observed that LBP algorithm can accurately detect any irregularities present on the surface of Friction Stir Welded joint.

2020-06-19T00:00:00Z Aljojo, Nahla Banjarb, Ameen Alharbia, Basma Alshutayria, Areej Jamal, Amani Waggas, Dana Saleh, Ghydaa Alshehri, Rahaf Aljuaid, Shoroug Khayyat, Mashael Zainol, Azida http://hdl.handle.net/10366/146090 2025-06-05T12:36:20Z 2020-11-30T00:00:00Z

Geography is the study of local and spatial variations in physical and human events on Earth. Studies of the world's geography have grown together with human developments and revolutions. Atlases often present geographic features and boundaries of areas; an atlas is a compilation of different Earth maps or Earth regions, such as the Middle East, and the continents of Asia, and North America. Most teachers still use classical methods of teaching. Geographical concepts and map-reading skills are the most common aspects of learning that early-stage students find challenging. Hence, the objective of this application is to develop a geography application for children between the ages of 9 and 12 years that would allow them to learn maps. Nowadays, smartphones and mobile apps are drawing closer to becoming acceptable learning tools. To facilitate this, Kids' Atlas is an android application, the main purpose of which is to help children to learn easily and test their knowledge. The application improves learning through entertainment by adding technologies that will help children to learning geography. It captures their attention to learn by visualizing objects and allows them to interact more effectively than traditional methods teaching by visualizing the 3D items. The application intends to improve the individual's ability to understand by providing a training section containing simple quizzes, listening/voice recognition capability, and it has the ability to search for a country by voice recognition and zooming for searched country. The methodology involves a set of software development phases, beginning with the planning; analyze data, design, implementation, testing and maintenance phases. The result of this project is a geography learning application that assists children to enjoy learning geography. The result has shown positive indicators that improve children's ability and knowledge of geography. Learning geography also becomes enjoyable; encouraging and motivating children to continue learning. This project contributes to the growth of education in early childhood, which is essential to shape the nation for the future. Therefore, this project is significant and relevant, as it contributes to the knowledge society for Saudi Arabia.

2020-11-30T00:00:00Z Pimpalkar, Amit Purushottam Retna Raj, R. Jeberson http://hdl.handle.net/10366/146091 2025-06-05T12:36:20Z 2020-06-18T00:00:00Z

Data analytics and its associated applications have recently become impor-tant fields of study. The subject of concern for researchers now-a-days is a massive amount of data produced every minute and second as people con-stantly sharing thoughts, opinions about things that are associated with them. Social media info, however, is still unstructured, disseminated and hard to handle and need to be developed a strong foundation so that they can be utilized as valuable information on a particular topic. Processing such unstructured data in this area in terms of noise, co-relevance, emoticons, folksonomies and slangs is really quite challenging and therefore requires proper data pre-processing before getting the right sentiments. The dataset is extracted from Kaggle and Twitter, pre-processing performed using NLTK and Scikit-learn and features selection and extraction is done for Bag of Words (BOW), Term Frequency (TF) and Inverse Document Frequency (IDF) scheme. /nFor polarity identification, we evaluated five different Machine Learning (ML) algorithms viz Multinomial Naive Bayes (MNB), Logistic Regression (LR), Decision Trees (DT), XGBoost (XGB) and Support Vector Machines (SVM). We have performed a comparative analysis of the success for these algorithms in order to decide which algorithm works best for the given data-set in terms of recall, accuracy, F1-score and precision. We assess the effects of various pre-processing techniques on two datasets; one with domain and other not. It is demonstrated that SVM classifier outperformed the other classifiers with superior evaluations of 73.12% and 94.91% for accuracy and precision respectively. It is also highlighted in this research that the selection and representation of features along with various pre-processing techniques have a positive impact on the performance of the classification. The ultimate outcome indicates an improvement in sentiment classification and we noted that pre-processing approaches obviously suggest an improvement in the efficiency of the classifiers.

2020-06-18T00:00:00Z Gupta, Shivam Meena, Jyoti Gupta, O.p http://hdl.handle.net/10366/146089 2025-06-05T12:36:20Z 2020-11-12T00:00:00Z

Timely diagnosis is important for saving the life of epileptic patients. In past few years, a lot of treatment are available for epilepsy. These treatments involve use of medicines. But these are not effective in controlling frequency of seizure. There is need of removal of affected region using surgery. Electroencephalogram (EEG) is a widely used technique for monitoring the brain activity and widely popular for seizure region detection. It is used before surgery for locating affected region. This manual process using EEG graphs is time consuming and requires deep expertise. In the present paper, a model has been proposed that preserves the true nature of EEG signal in form of textual one dimensional vector. The proposed model achieves a state of art performance for Bonn University dataset giving an average sensitivity, specificity of 81% and 81.4% respectively for classification among all five classes. Also for binary classification achieving 99.9%, 99.5% score value for specificity and sensitivity instead of 2D models used by other researchers. Thus developed system will significantly help neurosurgeons in increasing their performance.

2020-11-12T00:00:00Z Jamal, Amani Munshi, Asmaa Aljojo, Nahla Qadah, Talal Zainol, Azida http://hdl.handle.net/10366/146088 2025-06-05T12:36:20Z 2020-06-28T00:00:00Z

Information needs for understanding cell divisions in the human body is important in the learning process. Although sketches, images and blocks of 3D puzzles were used for teaching and learning, unfortunately those tools are static and incapable of being manipulated. Hence, digital information is the best tool for the teaching and learning of cell divisions in the human body via software applications. A cell motion is a digital information application developed using leap motion to demonstrate cell movement in the human body. However, the factors that influence students towards adopting this application are not obvious and often ignored. The method for evaluating the factors influencing its user's acceptance is the Technology Acceptance Model (TAM) via a questionnaire distributed among medical students to gain statistically valid quantitative results through hypothesis-testing. The result indicates that digital information needs for the understanding of cell divisions in the human body are influenced by the user's Perceived Ease of Use (PEOU) and Perceived Usefulness (PU). However, the Attitude (AT) towards use did have a significant effect on PU and PEOU. Moreover, PEOU had a strong and significant influence on PU, while AT positively influenced users' behavioural intention (BI) of using digital information needs for the understanding of cell divisions in the human body.

2020-06-28T00:00:00Z Adcaij, Editorial Team http://hdl.handle.net/10366/146087 2025-06-05T12:36:20Z 2020-11-30T00:00:00Z 2020-11-30T00:00:00Z