Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has gained prominence in the last two decades due to its ease of application unsupervised, complex multidimensional problems which cannot be solved using traditional deterministic algorithms. The canonical particle swarm optimizer based on flocking behavior and social co-operation birds fish schools draws heavily from evolutionary these organisms. This paper serves provide thorough survey PSO algorithm...

Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has gained prominence in the last two decades due to its ease of application unsupervised, complex multidimensional problems which cannot be solved using traditional deterministic algorithms. The canonical particle swarm optimizer based on flocking behavior and social co-operation birds fish schools draws heavily from evolutionary these organisms. This paper serves provide thorough survey PSO algorithm...

The World Health Organization labelled the new COVID-19 breakout a public health crisis of worldwide concern on 30 January 2020, and it was named global pandemic in March 2020. It has had catastrophic consequences world economy well-being people put tremendous strain already-scarce healthcare systems globally, particularly underdeveloped countries. Over 11 billion vaccine doses have already been administered worldwide, benefits these vaccinations will take some time to appear. Today, only...

Recognizing a face is remarkable process that humans naturally use. Computer vision has tried to resemble this ability of human as biometric tool identify humans. Commercial and law enforcement applications are increasingly using recognition technology people. Currently, it one the most sought-after detection methods used in forensics for criminal identification purposes. Owing similarities appearance certain faces, especially cases, problem poses great challenge forensic investigation...

The human papillomavirus (HPV) is responsible for most cervical cancer cases worldwide. This gynecological carcinoma causes many deaths, even though it can be treated by removing malignant tissues at a preliminary stage. In developing countries, patients do not undertake medical examinations due to the lack of awareness, hospital resources and high testing costs. Hence, vital design computer aided diagnostic method which screen patients. this research, we predict probability risk contracting...

The development of non-invasive blood pressure monitoring systems remains a critical challenge, particularly in resource-constrained settings. This study proposes an efficient deep learning framework integrating Edge Artificial Intelligence for continuous estimation using photoplethysmography (PPG) signals. We evaluate three architectures: residual-enhanced convolutional neural network, transformer-based model, and attentive BPNet. Using the MIMIC-IV waveform database, we implement signal...

Quantum-behaved particle swarm optimization (QPSO) algorithm theoretically guarantees global convergence and has been implemented on a wide suite of continuous problems. In this paper, the nonlinear multimodal problem high pass FIR filter design is investigated using weighted mean best QPSO (WQPSO). The results are compared with competitive techniques such as keeping PSO PM references. It seen that WQPSO statistically outperforms in terms characteristics ripple performance designed filter.

In this paper we focus on application of data-driven methods for remaining useful life estimation in components where past failure data is not uniform across devices, i.e. there a high variance the minimum and maximum value key parameters. The system under study hard disks used computing cluster. analysis provided by Backblaze as discussed later. article, discuss architecture long short term neural network describe mechanisms to choose various hyper-parameters. Further, challenges faced...

Clustering is a widely used unsupervised learning technique across data mining and machine applications finds frequent use in diverse fields ranging from astronomy, medical imaging, search optimization, geology, geophysics, sentiment analysis, to name few. It therefore important verify the effectiveness of clustering algorithm question make reasonably strong arguments for acceptance end results generated by validity indices that measure compactness separability clusters. This work aims...

Fuzzy clustering has become a widely used data mining technique and plays an important role in grouping, traversing selectively using for user specified applications. The deterministic C-Means (FCM) algorithm may result suboptimal solutions when applied to multidimensional real-world, time-constrained problems. In this paper the Quantum-behaved Particle Swarm Optimization (QPSO) with fully connected topology is coupled Clustering tested on suite of datasets from UCI Machine Learning...

Knee osteoarthritis is one of the most prevalent chronic diseases. It leads to pain, stiffness, decreased participation in activities daily living and problems with balance recognition. Force platforms have been tools used analyse patients. However, identification early stages assessing severity using parameters derived from a force plate are yet unexplored best our knowledge. Combining artificial intelligence medical knowledge can provide faster more accurate diagnosis. The aim study...

Brain cancer is one of the most deadly cancers, with a very low survival rate. By understanding factors that lead to spreading, practitioners can concentrate their efforts on providing effective treatment, and they modify treatment plan as necessary. Also, knowing likelihood patient's over specified time period enable them make informed decisions about adjusting routines, future investments, other health-related decisions. The use data-driven models in research has gained increased...

Machine Reading Comprehension (MRC) has been a long-standing problem in NLP and, with the recent introduction of BERT family transformer based language models, it come long way to getting solved. Unfortunately, however, when variants trained on general text corpora are applied domain-specific text, their performance inevitably degrades account domain shift i.e. genre/subject matter discrepancy between training and downstream application data. Knowledge graphs act as reservoirs for either...

Lithium-ion batteries (Li-ion) have revolutionized energy storage technology, becoming integral to our daily lives by powering a diverse range of devices and applications. Their high density, fast power response, recyclability, mobility advantages made them the preferred choice for numerous sectors. This paper explores seamless integration Prognostics Health Management within batteries, presenting multidisciplinary approach that enhances reliability, safety, performance these powerhouses....

Semantic similarity is a long-standing problem in natural language processing (NLP). It topic of great interest as its understanding can provide look into how human beings comprehend meaning and make associations between words. However, when this looked at from the viewpoint machine understanding, particularly for under resourced languages, it poses different altogether. In paper, semantic explored Bangla, less language. For ameliorating situation such most rudimentary method (path-based)...

Gender identification systems nowadays, are gaining momentum in terms of popularity because their wide areas application. They can be used a variety fields ranging from security and authentication services to content based information retrieval also criminal investigations. detection has started gain importance the fact that recent studies conducted showed performance gender dependent speech recognition models performs much better than independent models. In proposed work, we aim build such...

Physical and cloud storage services are well-served by functioning reliable high-volume systems. Recent observations point to hard disk reliability as one of the most pressing issues in data centers containing massive volumes devices such HDDs. In this regard, early detection impending failure at level aids reducing system downtime reduces operational loss making proactive health monitoring a priority for AIOps settings. work, we introduce methods extracting meaningful attributes associated...

In this paper a novel Quantum Double Delta Swarm (QDDS) algorithm modeled after the mechanism of convergence to center attractive potential field generated within single well in double Dirac delta setup has been put forward and preliminaries discussed. Theoretical foundations experimental illustrations have incorporated provide first basis for further development, specifically refinement solutions applicability problems high dimensional spaces. Simulations are carried out over varying...

There exists a scarcity of work done in choosing the optimal WSD algorithm as applicable for different situations and even less has been applying techniques to low-resourced languages like Bengali. This paper presents three modified versions Lesk along with original version, applied The results obtained from experimentation, particularly our dependency tree based variant proves be highly robust handling sense disambiguation task