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Big Data and Computing Visions
Scopus
ISSN 2783-4956 · REA Press · 126 artikel di indeks
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Artikel Jurnal Teks lengkap
Comprehensive review of machine learning models for breast cancer diagnosis (2018–2023)
Breast Cancer (BC) remains one of the most prevalent and life-threatening diseases among women worldwide. Early and accurate detection is crucial for effective treatment and for reducing mortality rates. Aim: This study aims to provide a comprehensive review of existing Machine Learning (ML) and…
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Unmanned aerial vehicle selection for defense applications: A comparative Multi-Fuzzy MCDM framework using evidential Fuzzy, IFNs-DST, SFNs-TOPSIS and T2NNs-CRITIC-MABAC
Unmanned Aerial Vehicles (UAVs) are used in many different fields today. Some of these are fire extinguishing, agriculture and spraying, meteorological measurements, damage assessment, search and rescue activities, examination of cloud properties, providing real-time image intelligence…
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Efficiency evaluation of smart libraries under distribution-driven uncertainty: A big-data-driven fuzzy SBM–DEA framework
This study develops a big-data-driven fuzzy Slack-Based Measure (SBM) Data Envelopment Analysis (DEA) framework to evaluate efficiency under distribution-driven uncertainty in smart libraries. Unlike conventional DEA models that rely on deterministic indicators, the proposed approach integrates…
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Leveraging large language models for model generation and verification in autonomous emergency braking systems
Automated emergency braking (AEB) systems require formal models that can be verified. These models must accurately capture emergency semantics. In this paper, we propose a model-driven pipeline supported by artificial intelligence. This pipeline automatically generates and then verifies AEB system…
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A hybrid approach for enhancing cloud computing performance via predictive auto-scaling and Qos-Aware load balancing
Good administration of cloud resources is critical to ensuring their efficacy, compliance with SLAs, and cost-effectiveness. To improve the capabilities of cloud computing, this study proposes a hybrid approach that combines predictive auto-scaling with QoS-Aware load balancing. At our disposal…
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A new approach to r,s,t-spherical fuzzy soft sets with applications to multi-criteria decision-making
As an extension of T-Spherical Fuzzy Soft Sets (T-SFSS), the notion of r,s,t-Spherical Fuzzy Soft Sets (rst-SFSS) is presented in this study. Incorporating the degrees of membership, neutral membership, and non-membership into a more adaptable structure, the suggested rst-SFSS model expands upon…
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A novel mathematical model with an LCA-based solution method to minimize earliness-tardiness costs on a single machine by considering batch delivery
This paper addresses a practical but complicated version of Just in Time (JIT) problem in which a set of available jobs with known processing times and due dates are processed on a single machine and delivered in batches of arbitrary size. A new mathematical model is developed to minimize the…
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A systematic approach and mathematical review to textile production optimization: implementing lean six sigma DMAIC for enhanced product consistency and quality in the field of industrial engineering management
The main aim of this paper is to analyze the application of LSS tools to enhance efficiency and product quality within the region's textile sector. Specifically, the paper's objective is three-fold: to discuss how Lean and Six Sigma may be implemented separately, to discuss how these two…
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A new product for soft sets with its decision-making: Soft star-product
Soft sets provide a robust mathematical framework for addressing uncertainty, offering innovative solutions for problems involving parametric data. Soft set operations are core concepts within soft set theory. In this paper, we introduce a novel soft product for soft sets, termed the soft…
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Video completion in the presence of moving subjects based on segmentation using neutrosophic sets
Image and video completion are essential tasks in the field of image and video processing, often used for restoring damaged regions in images and video frames. The primary challenge in these tasks is to complete them in such a way that they do not introduce noticeable artifacts or inconsistencies…
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An integrated approach to image quality: comparative analysis of bilinear and nearest neighbor interpolation
Pixel transitions are critical in image processing, largely depending on interpolation methods to ensure smoothness and clarity. This work focuses on two widely used image interpolation techniques: nearest neighbor interpolation and bilinear interpolation, both implemented using integrated software…
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Analyzing the impact of social media sentiments on government response during natural disasters in Pakistan
In light of the growing frequency of natural disasters, social networking sites are now used for polling perception and evaluating governmental performance. This study aims to examine the effects of negative and positive social media discussions on government responses to the flood disaster of 2010…
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A computational vision for prioritizing alternatives in the presence of qualitative big data
In complex and dynamic environments, strategic decision-making becomes challenging due to the inherent uncertainties and intricacies involved. To address these issues, a combination of hard and soft Operational Research (OR) methods is suggested, enhancing both flexibility and thoroughness in…
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Shree-L1: A dynamic CNN architecture for efficient tumor classification in medical imaging
Brain tumor classification is a crucial task in medical imaging for early diagnosis. In this paper, we propose a novel deep learning architecture, Shree-L1, designed for efficient brain tumor classification. Our architecture utilizes dynamic downscaling and upscaling blocks for enhanced feature…
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Sentiment analysis for identifying depression through social media texts using machine learning technique
This paper presents a detailed exploration of the evolving landscape of depression detection through Sentiment Analysis (SA) in online communication platforms. With depression being a widespread and often undetected mental health concern, leveraging technology for early intervention is crucial. The…
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Adaptive IoT routing protocols in wireless sensor networks
The swift expansion of the Internet of Things (IoT) has increased the application of Wireless Sensor Networks (WSNs) in various fields, such as environmental monitoring, smart cities, and industrial automation. Nevertheless, the fundamental energy constraints of sensor nodes pose considerable…
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The phenomenal non-stationary E_(-k)/M/1 queue transitions between stability, traffic intensity and chaos
This research investigates the unexplored domain of negative k parameters within dynamic systems, focusing on their influence across stability, traffic intensity, and chaotic phases. Using an iterative computational framework, we examine the sigma function ( σ ) to characterize system responses…
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Adaptive non-local means filtering improved by similarity and structure tensor
The classical Non-Local Means (NLM) filter employs a single exponential function to calculate pixel similarity weights and utilizes a uniform smoothing scale parameter globally. This approach suffers from two significant limitations: the rapid decay characteristic of the exponential function…
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Unequal domination via fuzzy edge status in fuzzy graphs
IIn this paper, we introduce fuzzy status unequal domination (fsu_d) based on a new fuzzy edge distance. We propose and explore the fuzzy edge distance in fuzzy graphs, along with related notions such as the fuzzy status of an edge, the status strength of connectedness, and status-strong arcs. For…
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Machine learning and fuzzy logic enhanced computational model for cancer detection with metastasis risk reduction
Cancer is still a primary worldwide health concern that requires sophisticated methods for early diagnosis and detection. This research offers a scientific method that combines the strengths of fuzzy logic and machine learning to diagnose cancer at an early stage, which is pivotal given the…