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Advances in Distributed Computing and Artificial Intelligence Journal
Scopus
ISSN 2255-2863 · Ediciones Universidad de Salamanca · 414 artikel di indeks
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Artikel Jurnal
CNN Based Automatic Speech Recognition: A Comparative Study
Recently, one of the most common approaches used in speech recognition is deep learning. The most advanced results have been obtained with speech recognition systems created using convolutional neural network (CNN) and recurrent neural networks (RNN). Since CNNs can capture local features…
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Resolving Covid-19 with Blockchain and AI
In the early months of 2020, a fast-spreading outbreak was brought about by the new virus SARS-CoV-2. The uncontrolled spread, which led to a pandemic, illustrated the healthcare system’s slow response time to public health emergencies at that time. Blockchain technology was anticipated to be…
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CyberUnits Bricks: An Implementation Study of a Class Library for Simulating Nonlinear Biological Feedback Loops
Feedback loops and other types of information processing structures play a pivotal role in maintaining the internal milieu of living organisms. Although methods of biomedical cybernetics and systems biology help to translate between the structure and function of processing structures, computer…
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Optimal Positioning and Sizing of Distributed Energy Sources in Distribution System Using Hunter-Prey Optimizer Algorithm
The integration of distributed generation (DG) based on renewable energy (RE), in distribution power networks (DPN) has become indispensable for reducing power losses and voltage deviation along the DPN. Typical DGs are placed adjacent to the load in DPN and locally distribute adequate active and…
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A Parallel Approach to Generate Sports Highlights from Match Videos Using Artificial Intelligence
Publishing highlights after a sports game is a common practice in the broadcast industry, providing viewers with a quick summary of the game and highlighting interesting events. However, the manual process of compiling all the clips into a single video can be time-consuming and cumbersome for video…
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Bus Ridership Prediction and Scenario Analysis through ML and Multi-Agent Simulations
This paper introduces an innovative approach to predicting bus ridership andanalysing transportation scenarios through a fusion of machine learning (ML) techniques and multi-agent simulations. Utilising a comprehensive dataset from an urban bus system, we employ ML models to accurately forecast…
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A Review on Covid-19 Detection Using Artificial Intelligence from Chest CT Scan Slices
The outbreak of COVID-19, a contagious respiratory disease, has had a significant impact on people worldwide. To prevent its spread, there is an urgent need for an easily accessible, fast, and cost-effective diagnostic solution. According to studies, COVID-19 is frequently accompanied by coughing…
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Computer-Aided Detection and Diagnosis of Breast Cancer: a Review
Statistics across different countries point to breast cancer being among severe cancers with a high mortality rate. Early detection is essential when it comes to reducing the severity and mortality of breast cancer. Researchers proposed many computer-aided diagnosis/detection (CAD) techniques for…
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Systematic Literature Review of Machine Learning Models for Detecting DDoS Attacks in IoT Networks
The escalating integration of Internet of Things (IoT) devices has led to a surge in data generation within networks, consequently elevating the vulnerability to Distributed Denial of Service (DDoS) attacks. Detecting such attacks in IoT Networks is critical, and Machine Learning (ML) models have…
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ML-Based Quantitative Analysis of Linguistic and Speech Features Relevant in Predicting Alzheimer’s Disease
Alzheimer’s disease (AD) is a severe neurological condition that affects numerous people globally with detrimental consequences. Detecting AD early is crucial for prompt treatment and effective management. This study presents a novel approach for detecting and classifying six types of cognitive…
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Harigeeta: Cic Mechanism with Euclidean Steiner Tree for Service Latency Prediction in Delay-Sensitive Cloud Services
Data establishment and resource provision are the most crucial tasks in the data center. To achieve minimum service latency, it is required to have a balance between the virtual machine and physical machine for proper execution of any query into the cloud data center. Cloud services have a huge…
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Deep and Machine Learning for Acute Lymphoblastic Leukemia Diagnosis: A Comprehensive Review
The medical condition known as acute lymphoblastic leukemia (ALL) is characterized by an excess of immature lymphocyte production, and it can affect people across all age ranges. Detecting it at an early stage is extremely important to increase the chances of successful treatment. Conventional…
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Sarcasm Text Detection on News Headlines Using Novel Hybrid Machine Learning Techniques
One of the biggest problems with sentiment analysis systems is sarcasm. The use of implicit, indirect language to express opinions is what gives it its complexity. Sarcasm can be represented in a number of ways, such as in headings, conversations, or book titles. Even for a human, recognizing…
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Investigation of the Role of Machine Learning and Deep Learning in Improving Clinical Decision Making for Musculoskeletal Rehabilitation
Musculoskeletal rehabilitation is an important aspect of healthcare that involves the treatment and management of injuries and conditions affecting the muscles, bones, joints, and related tissues. Clinical decision-making in musculoskeletal rehabilitation involves complex and multifactorial…
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An Ensemble Based Machine Learning Classification for Automated Glaucoma Detection
Glaucoma is an irredeemable eye disease that causes sight degeneration and is the fourth leading cause of vision impairment as per the World Report on Vision 2019. Several techniques exist for the screening, detection, treatment, and rehabilitation of glaucoma. But still, they are not sufficient to…
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Optimizing Credit Card Fraud Detection: A Genetic Algorithm Approach with Multiple Feature Selection Methods
In today’s cashless society, the increasing threat of credit card fraud demands our attention. To protect our financial security, it is crucial to develop robust and accurate fraud detection systems that stay one step ahead of the fraudsters. This study dives into the realm of machine learning…
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Federated Learning in Data Privacy and Security
Federated learning (FL) has been a rapidly growing topic in recent years. The biggest concern in federated learning is data privacy and cybersecurity. There are many algorithms that federated models have to work on to achieve greater efficiency, security, quality and effective learning. This paper…
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Artikel Jurnal
Performance Analysis of Software-Defined Networking in Band Controllers for Different Network Topologies
With the great increase in the complexity of networking, software-defined networks have been developed to help administrators operate and configure network services with controllers such as Pox, Ryu, Floodlight and OpenDaylight. Those controllers offer an appropriate platform for applications that…
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An Efficient Approach to Extract and Store Big Semantic Web Data Using Hadoop and Apache Spark GraphX
The volume of data is growing at an astonishingly high speed. Traditional techniques for storing and processing data, such as relational and centralized databases, have become inefficient and time-consuming. Linked data and the Semantic Web make internet data machine-readable. Because of the…
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A Systematic Analysis of Various Word Sense Disambiguation Approaches
The process of finding the correct sense of a word in context is known as word sense disambiguation (WSD). In the field of natural language processing, WSD has become a growing research area. Over the decades, so many researchers have proposed the many approaches to WSD. A development of this field…