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Journal of ICT Research and Applications Vol. 16 Issue 2 2022

Vol. 16 No. 2 (2022)

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Articles Published in This Issue

Explore peer-reviewed research articles published in this issue.

researchpp. 101–122

Medium Access Control Protocol for High Altitude Platform Based Massive Machine Type Communication

Massive Machine Type Communication (mMTC) can be used to connect a large number of sensors over a wide coverage area. One of the places where mMTC can be applied is in wireless sensor networks (WSNs). A WSN consists of several sensor nodes that send their sensing information to the cluster head (CH), which can then be forwarded to a high altitude platform (HAP) station. Sensing information can be sent by the sensor nodes at the same time through the same medium, which means collision can occur. When this happens, the sensor node must re-send the sensing information, which causes energy…

Keywords
HAP MAC mMTC network efficiency WSN
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researchpp. 123–137

Context-Aware Sentiment Analysis using Tweet Expansion Method

The large source of information space produced by the plethora of social media platforms in general and microblogging in particular has spawned a slew of new applications and prompted the rise and expansion of sentiment analysis research. We propose a sentiment analysis technique that identifies the main parts to describe tweet intent and also enriches them with relevant words, phrases, or even inferred variables. We followed a state-of-the-art hybrid deep learning model to combine Convolutional Neural Network (CNN) and the Long Short-Term Memory network (LSTM) to classify tweet data based on…

Keywords
embedding neural networks sentiment analysis tweet enrichment deep learning
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researchpp. 152–166

Breast Cancer Diagnosis in Women Using Neural Networks and Deep Learning

Breast cancer is a deadly disease affecting women around the world. It can spread rapidly into other parts of the body, causing untimely death when undetected due to rapid growth and division of cells in the breast. Early diagnosis of this disease tends to increase the survival rate of women suffering from the disease. The use of technology to detect breast cancer in women has been explored over the years. A major drawback of most research in this area is low accuracy in the detection rate of breast cancer in women. This is partly due to the availability of few data sets to train classifiers…

Keywords
breast-cancer diagnosis deep learning mammography neural network
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researchpp. 167–183

Towards Enhancing Keyframe Extraction Strategy for Summarizing Surveillance Video: An Implementation Study

The large amounts of surveillance video data are recorded, containing many redundant video frames, which makes video browsing and retrieval difficult, thus increasing bandwidth utilization, storage capacity, and time consumed. To ensure the reduction in bandwidth utilization and storage capacity to the barest minimum, keyframe extraction strategies have been developed. These strategies are implemented to extract unique keyframes whilst removing redundancies. Despite the achieved improvement in keyframe extraction processes, there still exist a significant number of redundant frames in…

Keywords
keyframe extraction surveillance video video compression video storage video summarization
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researchpp. 184–196

A Questions Answering System on Hadith Knowledge Graph

Several works have presented the Hadith on different digital platforms, ranging from websites to mobile apps. These works were successful in presenting the text of the Hadith to users, but this does not help them to answer any particular questions about religious matters. Therefore, in this work we propose a question-answering system that was built on a Hadith knowledge graph. To interpret the user questions correctly, we used the Levenshtein distance function, and for storing the Hadith in graph format we used Neo4J as the graph database. Our main findings were: (i) a knowledge graph is…

Keywords
hadith knowledge graph semantic question-answer system reasoning
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