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Blind Color Image Watermarking Using Deep Artificial Neural Network Using Statistical Features
With increasing digital content over the internet it is very important to secure the digital contents in such a way that the identity and integrity...
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SKGDC: Effective Segmentation Based Deep Learning Methodology for Banana Leaf, Fruit, and Stem Disease Prediction
In agriculture, detecting plant diseases is crucial for optimal plant growth. Initially, input images are collected from three datasets: banana leaf...
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Predicting Apple Plant Diseases in Orchards Using Machine Learning and Deep Learning Algorithms
Apple cultivation in the Kashmir Valley is a cornerstone of the region’s agriculture, contributing significantly to the economy through substantial...
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A Game-Based Cognitive Intervention for Young Learners with Reading Difficulties
The study’s primary contribution is a game-based cognitive intervention tool for young learners with reading difficulties. The second contribution is...
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An Experimental Evaluation of Summarisation-Based Frequent Subgraph Mining for Subgraph Searching
The subgraph searching is a fundamental operation for the analysis and exploration of graphs. Nowadays, molecular databases are nearing close to one...
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Decomposition-based long short-term memory model for price forecasting of agricultural commodities
Accurate and reliable price forecasting of agricultural commodities is one of the research hotspots, as these prices are inherently complex and...
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Predicting the Acceptance of Metaverse for Educational Purposes in Universities: A Structural Equation Model and Mediation Analysis of the Extended Technology Acceptance Model
This study investigated factors that predict the acceptance of metaverse applications for educational usage among university students from the facet...
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Predictive Assessment of the Interior Quality of Apartments Based on Multimodal Data with Variable Visual Input
Multimodal analyses in the context of automated real estate valuation (AVM) offer the possibility of enriching the models with additional...
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Virtual Machine Provisioning Within Data Center Host Machines Using Ensemble Model in Cloud Computing Environment
In the digital age of exponential data proliferation and growing computing demands, efficient resource management within data centers is crucial. A...
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A Semiautomatic Image Processing-Based Method for Binary Segmentation of Lungs in Computed Tomography Images
Precise biomedical image segmentation is pivotal in medical diagnosis and treatment. Among various methodologies, image processing-based techniques...
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On preferences and reward policies over rankings
We study the rational preferences of agents participating in a mechanism whose outcome is a ranking (i.e., a weak order) among participants. We...
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Stagnation Detection in Highly Multimodal Fitness Landscapes
Stagnation detection has been proposed as a mechanism for randomized search heuristics to escape from local optima by automatically increasing the...
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REDQT: a method for automated mobile application GUI testing based on deep reinforcement learning algorithms
As mobile applications become increasingly prevalent in daily life, the demand for their functionality and reliability continues to grow. Traditional...
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Parameterized complexity of candidate nomination for elections based on positional scoring rules
Consider elections where the set of candidates is partitioned into parties, and each party must nominate exactly one candidate. The P ossible P resident ...
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The viability of domain constrained coalition formation for robotic collectives
Applications, such as military and disaster response, can benefit from robotic collectives’ ability to perform multiple cooperative tasks (e.g.,...
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Introducing the Cosine Clustering Index (CCI): A Balanced Approach to Evaluating Deep Clustering
Amidst the surge of Big Data, deep clustering emerges as a pivotal technique in machine learning, necessitating robust and interpretable evaluation...
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Minimizing cache usage with fixed-priority and earliest deadline first scheduling
Cache partitioning is a technique to reduce interference among tasks running on the processors with shared caches. To make this technique effective,...
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A Novel Approach for Forecasting Price of Stock Market using Machine Learning Techniques
In today’s competitive business world, industries strive for rapid growth and leadership. Expanding a business requires additional capital, which can...
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