77 hasil untuk "Mejdl Safran"
Menampilkan 1–20 · 0,34 detik · RSS
-
Artikel Jurnal
A Hybrid Framework for Real-Time Sentiment Analysis and Adaptive Conversational Outcome Prediction in Domain-Specific Dialogue Systems
The lack of non-verbal signals in text-based communication forces dialogue systems to rely entirely on dynamic textual sentiment changes to infer user intent and emotional shifts. However, substantial class imbalance and the static, post-hoc nature of existing text analysis models prevent dialogue…
-
Artikel Jurnal
Real-time recommendation algorithms for crowdsourcing systems
Crowdsourcing has become a promising paradigm for solving tasks that are beyond the capabilities of machines alone via outsourcing tasks to online crowds of people. Both requesters and workers in crowdsourcing systems confront a flood of data coming along with the vast amount of tasks. Fast…
-
Artikel Jurnal
PhishingGNN: Phishing Email Detection Using Graph Attention Networks and Transformer-Based Feature Extraction
Phishing emails remain a critical cybersecurity challenge, demanding detection frameworks that capture both textual semantics and structural relationships in email data. This study introduces PhishingGNN, a hybrid model that integrates DistilBERT for context-aware text analysis with Graph Attention…
-
Artikel Jurnal
DPXception: a lightweight CNN for image-based date palm species classification
IntroductionDate palm species classification is important for various agricultural and economic purposes, but it is challenging to perform based on images of date palms alone. Existing methods rely on fruit characteristics, which may not be always visible or present. In this study, we introduce a…
-
Artikel Jurnal
Dual-Resource Optimization Configuration and Collaborative Scheduling for Flexible Job Shop Under Worker Flexibility Constraints
Worker resources exhibit high flexibility, adaptability, and individual differences. It is critical to complete manufacturing tasks with a suitable worker resource allocation plan, given the increasing labor costs and the dynamic changes in production demands. It is often assumed in studies on…
-
Artikel Jurnal Teks lengkap
Domain adaptive learning for multi realm sentiment classification on big data
Machine learning techniques that rely on textual features or sentiment lexicons can lead to erroneous sentiment analysis. These techniques are especially vulnerable to domain-related difficulties, especially when dealing in Big data. In addition, labeling is time-consuming and supervised machine…
-
Artikel Jurnal Teks lengkap
A Hybrid Many-Objective Optimization Algorithm for Job Scheduling in Cloud Computing Based on Merge-and-Split Theory
Scheduling jobs within a cloud environment is a critical area of research that necessitates meticulous analysis. It entails the challenge of optimally assigning jobs to various cloud servers, each with different capabilities, and is classified as a non-deterministic polynomial (NP) problem. Many…
-
Artikel Jurnal
Hyperspectral Image Super-Resolution via Grouped Second-Order Spatial Features and Spectral Attention Network
Hyperspectral imaging (HSI) captures detailed spectral data across a wide range of wavelengths, making HSI invaluable for many computer vision applications. However, limitations of imaging systems result in low spatial resolution in HSI images. State-of-the-art research encounters challenges due to…
-
Artikel Jurnal
Combinatorial metaheuristic methods to optimize the scheduling of scientific workflows in green DVFS-enabled edge-cloud computing
A significant challenge in high-performance computing is to ensure the even distribution of applications across computational resources, preventing issues such as resource fragmentation and network congestion. While cloud computing offers advantages, it introduces scheduling delays caused by data…
-
Artikel Jurnal Teks lengkap
Workflow Scheduling Scheme for Optimized Reliability and End-to-End Delay Control in Cloud Computing Using AI-Based Modeling
In the context of cloud systems, the effectiveness of placing modules for optimal reliability and end-to-end delay (EED) is directly linked to the success of scheduling distributed scientific workflows. However, the measures used to evaluate these aspects (reliability and EED) are in conflict with…
-
Artikel Jurnal
Algorithmic and mathematical modeling for synthetically controlled overlapping
Abstract For most classifiers, overlapping regions, where various classes are difficult to distinguish, affect the classifier’s overall performance in multi-class imbalanced data more than the imbalance itself. In problem-data space, the overlapped samples share similar characteristics, resulting…
-
Artikel Jurnal
Classification of Oral Cancer Into Pre-Cancerous Stages From White Light Images Using LightGBM Algorithm
Cancer is one of the foremost reasons for death worldwide, with nearly 10 million deaths noted in 2020. Globally, oral cancer ranks sixth when compared to other cancers. It is lethal because most cases are noticed at advanced stages, which can be prevented if screened for or treated early in the…
-
Artikel Jurnal
Energy-latency trade-off analysis for scientific workflow in cloud environments: The role of processor utilization ratio and mean grey wolf optimizer
Cloud computing has demonstrated its effectiveness in handling complex data that requires substantial computational power, immediate responsiveness, and ample storage capacity. However, there are significant challenges when it comes to distributing intricate tasks, such as workflows structured in a…
-
Artikel Jurnal Teks lengkap
Image-Based Arabian Camel Breed Classification Using Transfer Learning on CNNs
Image-based Arabian camel breed classification is an important task for various practical applications, such as breeding management, genetic improvement, conservation, and traceability. However, it is a challenging task due to the lack of standardized criteria and methods, the high similarity among…
-
Artikel Jurnal
Classification of hyperspectral images using fusion of CNN and MiniGCN with SVM
Convolutional neural networks (CNNs) have gained popularity for categorizing hyperspectral (HS) images due to their ability to capture representations of spatial-spectral features. However, their ability to model relationships between data is limited. Graph convolutional networks (GCNs) have been…
-
Artikel Jurnal
Improved Crow Search-Based Feature Selection and Ensemble Learning for IoT Intrusion Detection
Network intrusion detection in the Internet of Things (IoT) framework has posed considerable challenges in recent decades. A wide variety of machine-learning approaches are introduced in network intrusion detection. The existing methodologies commonly lack consistency in achieving optimal…
-
Artikel Jurnal Teks lengkap
Detection of Drowsiness among Drivers Using Novel Deep Convolutional Neural Network Model
Detecting drowsiness among drivers is critical for ensuring road safety and preventing accidents caused by drowsy or fatigued driving. Research on yawn detection among drivers has great significance in improving traffic safety. Although various studies have taken place where deep learning-based…
-
Artikel Jurnal
Prediction of lumpy skin disease virus using customized CBAM-DenseNet-attention model
Abstract Lumpy skin disease virus (LSDV) is an extremely infectious, viral, and chronic skin disease that is caused by the Capripox virus. This viral disease is predominantly found in cows. Mosquitoes and ticks are the primary transmitters for the spread of this virus. Recently, LSDV has been…
-
Artikel Jurnal
Experimental Investigation and Machine Learning Prediction of Mechanical Properties of Rubberized Concrete for Sustainable Construction
Abstract Concrete is widely used in civil engineering applications and the natural aggregates which used in concrete are scarce, but its demand is increasing. The disposal of rubber tyres poses a significant environmental challenge, as their decomposition releases harmful chemicals into the soil…
-
Artikel Jurnal
A smart and sustainable framework for millet crop monitoring equipped with disease detection using enhanced predictive intelligence
Today, there is a visible reduction in productivity of common crops like rice and wheat in agricultural sector. At the same time, millet crops have emerged as an alternative to counter global food security issues because of their adaptability and nutritional value that can combat malnutrition…