The accumulation of solid waste in the urban area is becoming a great concern, and it would result environmental pollution may be hazardous to human health if not properly managed. It important have an advanced/intelligent management system manage variety materials. One most steps separation into different components this process normally done manually by hand-picking. To simplify process, we propose intelligent material classification system, which developed using 50-layer residual net...

Heart disease is the leading cause of death globally, and early detection crucial in preventing progression disease. In this paper, an improved machine learning method proposed for prediction heart risk. The technique involves randomly partitioning dataset into smaller subsets using a mean based splitting approach. various partitions are then modeled classification regression tree (CART). A homogeneous ensemble created from different CART models accuracy weighted aging classifier ensemble,...

Abstract The recent advances of e-commerce and e-payment systems have sparked an increase in financial fraud cases such as credit card fraud. It is therefore crucial to implement mechanisms that can detect the Features frauds play important role when machine learning used for detection, they must be chosen properly. This paper proposes a (ML) based detection engine using genetic algorithm (GA) feature selection. After optimized features are chosen, proposed uses following ML classifiers:...

Immunotherapy through stimulating the host immune system has emerged as a powerful therapeutic strategy for various malignant and metastatic tumors in clinic. However, harnessing cancer treatment often fails to obtain durable response rate due poor immunogenicity strong immunosuppressive milieu tumor site. Herein, redox-activated liposome was developed from self-assembly of porphyrin–phospholipid conjugate coencapsulation indoleamine 2,3-dioxygenase (IDO) inhibitor into interior lumen via...

Hybrid energy storage systems (HESS) are regarded as combinatorial growing power capacity system in the world. Many researchers have devoted time and attention to studying systems, many outcomes been obtained implemented. Despite its significance expanding renewable stations for electric vehicles, HESS still faces numerous issues. This study assesses optimization methods used address problem of durability, charging/discharging, increasing temperature, manufacturing cost lifespan. The battery...

Algorithms are used to optimize both single and multi-objective system limits. This research aimed detect the optimal location size of DGs, which can significantly minimize power loss improve stability voltage. The uses binary particle swarm optimization shuffled frog leap (BPSO-SLFA) algorithms for simulation testing an flow (OPF) on 33 69 bus radial distribution system. result shows that give better DG allocation minimizes losses but at nascent stage advancement. associated with have...

In this paper a two stage method is proposed to effectively predict heart disease. The first involves training an improved sparse autoencoder (SAE), unsupervised neural network, learn the best representation of data. second using artificial network (ANN) health status based on learned records. SAE was optimized so as train efficient model. experimental result shows that improves performance ANN classifier, and more robust compared other methods similar scholarly works.

The advance in technologies such as e-commerce and financial technology (FinTech) applications have sparked an increase the number of online card transactions that occur on a daily basis. As result, there has been spike credit fraud affects issuing companies, merchants, banks. It is therefore essential to develop mechanisms ensure security integrity transactions. In this research, we implement machine learning (ML) based framework for detection using real world imbalanced datasets were...

The ascent of Industry 4.0 and smart manufacturing has emphasized the use intelligent techniques, tools, methods such as predictive maintenance. maintenance function facilitates early detection faults errors in machinery before they reach critical stages. This study suggests design an experimental framework, for conveyor motors, that efficiently detects a system's impairments considerably reduces risk incorrect diagnosis plant; We achieve this remarkable task by developing machine learning...

The prevailing competitive manufacturing industry calls for continuous customer satisfaction business sustainability. With the emergence of Industry 4.0 paradigm, product customization, which gives customers means to personalized products meet their needs, has become a strategy increase companies' value. High-tech firms are already diving deep into standards adopting innovative strategies outstand themselves in market, while small plants slow embracing digital transformation. high cost...

The efforts to revolutionize electric power generation and produce clean sustainable electricity have led the exploration of renewable energy systems (RES). This form is replenished cost-effective in terms production maintenance. However, RES, such as solar wind energies, intermittent; this one drawbacks its usage. In order overcome limitation, studies been undertaken forecast availability output. current trending method forecasting generated by RES artificial intelligence (AI) method. with...

Abstract Intrusion detection systems play a critical role in the mitigation of cyber-attacks on Internet Things (IoT) environment. Due to integration many devices within IoT environment, huge amount data is generated. The generated sets most cases consist irrelevant and redundant features that affect performance existing intrusion (IDS). selection optimal plays enhancement systems. This study proposes sequential feature approach using an optimized extreme learning machine (ELM) with SVM...

Numerous potential advantages to the requirements and effectiveness of supplied electricity can be accomplished by installation distributed generation units. In order take full advantage these benefits, it is essential position Distributed Generation (DG) units in appropriate locations. Otherwise, their may have an adverse effect on quality energy system operation. Several optimization techniques been created over years optimize integration. Optimization are therefore constantly changing...