Academic Articles & Research Papers

A Cooperative Learning Approach for Decentralized Peer-to-Peer Energy Trading Markets and its Structural Robustness Against Cyberattacks

Peer-to-peer (P2P) energy trading has recently emerged as a promising paradigm for integrating renewable and distributed energy resources into local energy grids with the presence of active prosumers. However, prosumers often have different...

Laser Welding of Dissimilar Metal Joint of 6061 Al Alloy and Al Matrix Composite

In this paper, dissimilar metal joints of 6061 aluminum alloy and aluminum matrix composite material are investigated by laser welding. TiB2 particles were added into the lap joint. The welding process, microstructure, and the corrosion pro...

Anaerobic Digestion, Codigestion of Food Waste, and Chicken Dung: Correlation of Kinetic Parameters with Digester Performance and On-Farm Electrical Energy Generation Potential

Valorization of agro-food waste through anaerobic digestion (AD) is gaining prominence as alternative method of waste minimization and renewable energy production. The aim of this study was to identify the key parameters for digester perfor...

The Investigation of Impact of Complement Policy for Energy Price Policy Reform on Transport Sector in Iran by Computable General Equilibrium

With regard to the ever-increasing need for energy in current societies to satisfy various requirements, scientists and researchers from different countries, such as Iran, have a basic approach in their agenda to achieve renewable energies،...

GROWTH AND YIELD RESPONSES OF SOYBEAN (Glycine max L.) TO ZINC OXIDE (ZnO) NANOPARTICLES FOLIAR APPLICATION

Aim. This study was purposed to investigate the effects of zinc oxide nanoparticles (ZnO NPs) on the growth and yield performance of two soybean (Glycine max L.) varieties, TGX1904-6F and TGX1951-3F, under controlled experimental conditions...

Optimization of False Target Jamming against UAV Detection

Unmanned aerial vehicles (UAVs) have been widely used for target detection in modern battlefields. From the viewpoint of the opponents, false target jamming is an effective approach to decrease the UAV detection ability or probability, but ...

Assembly Function Recognition in Embedded Systems as an Optimization Problem

Many different aspects of software system development and verification rely on precise function identification in binary code. Recognition of the source Assembly functions in embedded systems is one of the fundamental challenges in binary p...

Optimization of Support and Relief Parameters for Deep-Buried Metal Mine Roadways

The management of rock mass deformation in high-stress roadways is a pivotal aspect of deep geotechnical engineering. Given the fruitful outcomes of research in rock mechanics regarding traditional confining pressure control methods, schola...

Proposing New Data Whitening Method through Application of LSTM Method for Fault Condition Prediction in Bearing Data

In the context of big data, data preprocessing, especially data whitening, plays a pivotal role in improving the effectiveness of AI models. While traditional whitening methods suffer from severe computational bottlenecks, arising from the ...

A computational tool for conceptual design and optimization of planetary rovers

The design process of a Mars rover is driven by multiple design constraints, namely overall mass, power consumption and volume (dimensions). Various systems, such as mobility, manipulation, handling, power, thermal, communication, navigatio...

Sequence Decision Transformer for Adaptive Traffic Signal Control

Urban traffic congestion poses significant economic and environmental challenges worldwide. To mitigate these issues, Adaptive Traffic Signal Control (ATSC) has emerged as a promising solution. Recent advancements in deep reinforcement lear...

Assessing perception and equity of cultural ecosystem services in urban parks using social media data

Abstract Scientific assessment of cultural ecosystem services (CESs) levels in urban parks and refined analysis of their spatial equity are essential for residents’ social well-being. However, traditional assessment methods often fail to ca...

Deep learning-based personalized learning path recommendation system for higher education

Abstract The growing variety of student profiles in higher education has made it more important than ever to have smart systems that can change learning experiences on the job. Current recommendation algorithms fail to capture the complex r...

Multi-Task Learning in Natural Language Processing: An Overview

Deep learning approaches have achieved great success in the field of Natural Language Processing (NLP). However, directly training deep neural models often suffer from overfitting and data scarcity problems that are pervasive in NLP tasks. ...

Which factors influence public perceptions of urban attractions? — A comparative study

To better serve the public, urban attractions must understand the public's likes and dislikes and continually adapt and optimize their service in response. However, traditional methods for gauging public opinion, such as questionnaires and ...

Natural language processing

Summary form only given. Natural language processing (NLP) is a major area of artificial intelligence research, which in its turn serves as a field of application and interaction of a number of other traditional AI areas. Until recently, th...

Autonomous Driving Roadway Feature Interpretation Using Integrated Semantic Analysis and Domain Adaptation

Lane detection is fundamental to autonomous driving, yet remains challenging in complex environments with occlusions, ambiguous markings, and varied lighting. We introduce the Global Semantic Enhancement Network (GSENet), a groundbreaking f...

Optimization for Computer Vision

Bridging the performance–efficiency gap: a resource-efficient hybrid DL-ML framework for jackfruit disease detection

Complex environment variability and limited computational resources in agricultural settings create challenges in automated detection in tropical regions, where jackfruit diseases pose major threats to harvest productivity and food security...

Sequential Normalization: Embracing Smaller Sample Sizes for Normalization

Normalization as a layer within neural networks has over the years demonstrated its effectiveness in neural network optimization across a wide range of different tasks, with one of the most successful approaches being that of batch normaliz...