Journal of Computer Technology & Applications
Volume 14, Issue 2 (2023)
Published
Table of contents
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Designing an Application for Community Assistance: WedsPay
Abstract: As the world continues to adjust to the new normal of social distancing, we are seeing a significant shift toward digitalization in many aspects of our lives. In light of this, we have come up with an innovative idea of receiving gifts and blessings from loved ones in a digital format. Our platform, Wedspay, aims to make the process of accepting cash gifts as easy and seamless as possible by …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 1–6 Read article
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Agri-Crop Intelligent System for Detecting Crop Disease and Recommending Soil Nutrition Value Based on Soil Testing Using Machine Learning
Abstract: This research examines the economic importance of agriculture for nations like India as well as the ways in which innovation might advance agriculture. In order to assist farmers in increasing their production, the application can classify leaf diseases by evaluating provided photos and that will propose compatible crops and fertilisers according to soil characteristics and current meteorological data. The aim of this research is to develop a website that will …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 12–19 Read article
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Utilizing Machine Learning to Combat Plant Disease
Abstract: Plant diseases are a significant source of lost income and time for the agricultural industry. Accurately diagnosing an illness requires a high level of experience and dedication. Symptoms of plant diseases, such as spots or streaks of a different colour, are sometimes visible on the leaves of infected plants. Many fungal, bacterial, and viral organisms may also cause illness in plants. The indications and symptoms of a plant disease are …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 20–28 Read article
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Predictive Modeling System for Automated Skin Lesion Classification Using Deep Neural Networks and Voting Ensembles
Abstract: Skin cancer is one of the most prevalent cancers globally. Early and accurate diagnosis is critical for timely treatment and improved prognosis. This study presents a predictive modeling system for automated classification of skin lesions from dermoscopic images using deep neural networks and voting ensemble techniques. A customized 16-layer convolutional neural network architecture is developed for feature learning from lesion images. The concept of horizontal voting ensemble is implemented by …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 29–35 Read article
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Evaluation of Write Sequence Reordering Based Buffer Replacement Algorithms for Flash Memory Based Systems
Abstract: Many page replacement algorithms have been developed for disk-based systems. All of them consider the hit rate as a key performance measure. Flash memory has different characteristics than hard disks, such as asymmetric I/O latency among read, write, and erase operations. The read operation is faster than the write and erase operation, and it does not support in-place updates. Besides, write operations shorten the life of flash memories. Therefore, the …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 36–45 Read article
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A Review Paper on Recent Cyberattacks and Proactive Steps to Prevent Attacks
Abstract: Cybersecurity stands out as a significant contemporary challenge in today's world. With today's technology, we can communicate any sort of data, whether it be an audio file, a PDF document, or a video, with just a single click. Therefore, protecting information is crucial in the sphere of cyber security. As the globe becomes more and more connected to networks that may be used for conducting digital transactions, cyber security is …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 46–51 Read article
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Comparative Study of Classifiers for Monitoring Fake Reviews of Online Products Using Opinion Mining
Abstract: With the increasing popularity of e-commerce, online dealers seek reviews or opinions from customers regarding the quality and service of their sold products. As the number of customer reviews grows rapidly, potential buyers face difficulties in reading and assessing them to make informed decisions. Unfortunately, some review websites include fake positive reviews, either added by the product companies themselves or submitted by users who have not made a purchase. This …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 52–59 Read article
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A Review on Neural Networks and its Applications
Abstract: Neural Networks have been a hotspot domain for researchers due to its increasing area of applications in areas where huge amounts of data is used and the main goal is to infer patterns out of it. This passage offers an assessment of Neural Networks and their pragmatic uses in real-world situations. It provides information regarding the basic structure of Neural Networks and its working principles. There are also brief introductions …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 60–71 Read article
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Jaccard Index Versus Preferential Attachment: A Comparative Study of Similarity Based Link Prediction Techniques in Complex Networks
Abstract: Link prediction is a critical task in network analysis that aims to forecast potential connections between nodes. Numerous methods have been developed to address this challenge, with similarity-based techniques gaining substantial attention due to their simplicity and effectiveness. This research work presents a comprehensive review of two prominent similarity-based link prediction techniques, namely the Jaccard Index and Preferential Attachment. The Jaccard Index measures the similarity between two nodes based on …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 7–11 Read article
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An Abnormal Expression Detection System (AEDS) Using Deep Learning Algorithms
Abstract: In the last decade, many deep learning algorithms have achieved remarkable success and gained popularity in various computer vision tasks, including object detection, image recognition, and segmentation. This AEDS (Abnormal Expression Detection System)leverages the power of deep learning algorithms to detect abnormal facial expressions in real-time automatically. AEDS proposed two important models; those are Deep CNN and RNN. CNN is responsible for learning discriminative features from facial images and capturing …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 72–79 Read article