Search
Search Results
-
An exploratory evaluation of code smell agglomerations
Code smell is a symptom of decisions about the system design or code that may degrade its modularity. For example, they may indicate inheritance...
-
De-confounding representation learning for counterfactual inference on continuous treatment via generative adversarial network
Counterfactual inference for continuous rather than binary treatment variables is more common in real-world causal inference tasks. While there are...
-
Exploring the potential of Easy Language for enhancing website sustainability
Sustainable design principles have become increasingly important in website development, mainly focusing on reducing carbon emissions and energy...
-
Gradient-based explanation for non-linear non-parametric dimensionality reduction
Dimensionality reduction (DR) is a popular technique that shows great results to analyze high-dimensional data. Generally, DR is used to produce...
-
Enhancing racism classification: an automatic multilingual data annotation system using self-training and CNN
Accurate racism classification is crucial on social media, where racist and discriminatory content can harm individuals and society. Automated racism...
-
Global adaptive histogram feature network for automatic segmentation of infection regions in CT images
Accurate and timely diagnosis of COVID-like virus is of paramount importance for lifesaving. In this work, deep learning techniques are applied to...
-
TOPCOAT: towards practical two-party Crystals-Dilithium
The development of threshold protocols based on lattice-signature schemes has been of increasing interest in the past several years. The main...
-
Examining ALS: reformed PCA and random forest for effective detection of ALS
ALS (Amyotrophic Lateral Sclerosis) is a fatal neurodegenerative disease of the human motor system. It is a group of progressive diseases that...
-
Explainable decomposition of nested dense subgraphs
Discovering dense regions in a graph is a popular tool for analyzing graphs. While useful, analyzing such decompositions may be difficult without...
-
MIM: A multiple integration model for intrusion detection on imbalanced samples
The quantity of normal samples is commonly significantly greater than that of malicious samples, resulting in an imbalance in network security data....
-
Multi-task learning and mutual information maximization with crossmodal transformer for multimodal sentiment analysis
The effectiveness of multimodal sentiment analysis hinges on the seamless integration of information from diverse modalities, where the quality of...
-
Unveiling the impact of employee-customer familiarity on customer purchase intentions: an empirical investigation within the realm of web-based date analytics
This research delves into the intricate dynamics of employee-customer familiarity and its profound influence on customer purchase intentions within...
-
Emotion AWARE: an artificial intelligence framework for adaptable, robust, explainable, and multi-granular emotion analysis
Emotions are fundamental to human behaviour. How we feel, individually and collectively, determines how humanity evolves and advances into our shared...
-
RefCit2vec: embedding models considering references and citations for measuring document similarity
This study outlines the intellectual structure of Library and Information Science in terms of the venues with RefCit2vec, an embedding method...
-
Survey-based analysis of cybersecurity awareness of Turkish seafarers
In recent years, vessels have become increasingly digitized, reflecting broader societal trends. As a result, maritime operations have become an...
-
Smart contract vulnerabilities detection with bidirectional encoder representations from transformers and control flow graph
Up to now, the smart contract vulnerabilities detection methods based on sequence modal data and sequence models have been the most commonly used....
-
A principal label space transformation and ridge regression-based hybrid gorilla troops optimization and jellyfish search algorithm for multi-label classification
Classification as an essential part of Machine Learning and Data Mining has significant roles in engineering, medicine, agriculture, military, etc....
-
Negative-sample-free knowledge graph embedding
Recently, knowledge graphs (KGs) have been shown to benefit many machine learning applications in multiple domains (e.g. self-driving, agriculture,...
-
ASDMG: business topic clustering-based architecture smell detection for microservice granularity
Microservices architecture smells can significantly affect the quality of microservices due to poor design decisions, especially the granularity...
-
Similarity-based face image retrieval using sparsely embedded deep features and binary code learning
Human face retrieval has long been established as one of the most interesting research topics in computer vision. With the recent development of deep...
