Integrated algorithms in analysis of architecture and environment interaction- Case study: Stepped villages of Iran by Elham Zamani, Behshid Hosseini, Hossein Zabihi

“…The current research is based on the process of algorithmic design and simulation of village boundaries using the Grasshopper plugin in the Rhino software. …”
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Task Grid-Based Urban Environmental Information Release Mechanism for Mobile Crowd Sensing by Zhenwei Chen, Yang Lu, Zusong Li, Xiancun Zhou

“…For the sensing data, through an efficient data fusion algorithm designed in this study, the sensing information is fused to obtain the fine-grained environmental information of different task grids in the area. …”
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RWA-BFT: Reputation-Weighted Asynchronous BFT for Large-Scale IoT by Guanwei Jia, Zhaoyu Shen, Hongye Sun, Jingbo Xin, Dongyu Wang

“…This paper introduces RWA-BFT, a reputation-weighted asynchronous Byzantine Fault Tolerance (BFT) consensus algorithm designed to address the scalability and performance challenges of blockchain systems in large-scale IoT scenarios. …”
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Leveraging paired mammogram views with deep learning for comprehensive breast cancer detection by Jae Won Seo, Young Jae Kim, Kwang Gi Kim

“…This study introduces paired mammogram view based-network(PMVnet), a novel algorithm designed to enhance breast lesion detection by integrating relational information from paired whole mammograms, addressing the limitations of current methods. …”
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Surface defect detection on industrial drum rollers: Using enhanced YOLOv8n and structured light for accurate inspection. by Guofeng Qin, Qinkai Zou, Mengyan Li, Yi Deng, Peiwen Mi, Yongjian Zhu, Hao Liu

“…The system and algorithm designed in this paper can better ensure the production quality of drum rollers. …”
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Harnessing the potential of shared data in a secure, inclusive, and resilient manner via multi-key homomorphic encryption by David Ha Eun Kang, Duhyeong Kim, Yongsoo Song, Dongwon Lee, Hyesun Kwak, Brian W. Anthony

“…Grounded in statistical learning principles, we introduce the Multi-Key Homomorphic Encryption Logistic Regression (MK-HELR) algorithm, designed to execute logistic regression on encrypted multi-party data. …”
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Artificial intelligence-driven mobile interpretation of a semi-quantitative cryptococcal antigen lateral flow assay by David Bermejo-Peláez, Ana Alastruey-Izquierdo, Narda Medina, Daniel Capellán-Martín, Oscar Bonilla, Miguel Luengo-Oroz, Juan Luis Rodríguez-Tudela

“…We developed an AI algorithm designed for the automated interpretation of CrAgSQ LFAs. …”
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Enhancing precision in multiple sclerosis lesion segmentation: A U-net based machine learning approach with data augmentation by Oezdemir Cetin, Berkay Canel, Gamze Dogali, Unal Sakoglu

“…This study proposes a robust machine learning algorithm designed to identify MS lesions using both single-modal and multi-modal MRI data. …”
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RETRACTED ARTICLE: Confidence level based complex polytopic fuzzy Einstein aggregation operators and their application to decision-making process by Khaista Rahman, Mohammad Khishe

“…With these operators, we create an algorithm designed to solve multiattribute decision-making problems in a Polytopic fuzzy environment. …”
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LoRa Resource Allocation Algorithm for Higher Data Rates by Hossein Keshmiri, Gazi M. E. Rahman, Khan A. Wahid

“…In this paper, we introduce the LoRa Resource Allocation (LRA) algorithm, designed to address these limitations by enabling parallel transmissions, thereby reducing the total transmission time (<i>T_tx</i>) and increasing the bit rate (BR). …”
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A novel method for developing post-quantum cryptoschemes and a practical signature algorithm by Nikolay Andreevich Moldovyan, Dmitriy Nikolaevich Moldovyan

“…The practical purpose is to propose a fundamentally new method for development of algebraic digital signature algorithms. Design/methodology/approach – The proposed method is distinguished by the use of two different finite commutative associative algebras as a single algebraic support of the digital signature scheme and setting two different verification equation for a single signature. …”
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Cardiovascular Disease Detection through Innovative Imbalanced Learning and AUC Optimization by Karthikeyan Palanisamy, Krishnaveni Krishnasamy, Praba Venkadasamy

“…Furthermore, we have incorporated a tailored Differential Evolution (DE) algorithm designed to navigate the complex hyperparameter space with finesse. …”
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NOMA-Based Rate Optimization for Multi-UAV-Assisted D2D Communication Networks by Guowei Wu, Guifen Chen, Xinglong Gu

“…Simulation results show the following: (1) the proposed algorithm can achieve higher system throughput than several other benchmark algorithms with different numbers of D2D clusters, different D2D cluster communication spacing, and different UAV sizes; (2) the proposed algorithm designs UAV trajectory optimization with a 27% improvement in system throughput compared to the 2D trajectory; and (3) in the NOMA scenario, compared to the case of no decoding order constraints, the system throughput shows on average a 34% improvement.…”
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A Personalised Optimising Level Adaptation (OLA) Difficulty Algorithm for Scenario Simulations in Professional VR Simulators by Marcin Wolański Robert, Karol Jędrasiak

“…Aim: This study introduces the Optimising Level Adaptation (OLA) algorithm, designed to enhance scenario simulations for professional VR training by dynamically adjusting difficulty levels to match user performance, thereby supporting personalised learning and readiness for high-stakes situations such as firefighting and emergency response. …”
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How do electronic risk assessment tools affect the communication and understanding of diagnostic uncertainty in the primary care consultation? A systematic review and thematic synt... by Sarah Gerard Dean, Joshua Feyi-Waboso, Mark Tarrant, Raff Calitri, Elizabeth Shephard, Alex Burns, Brian Donnelly

“…Objectives To conduct a systematic review and synthesise qualitative research of electronic risk assessment tools (eRATs) in primary care, examining how they affect the communication and understanding of diagnostic risk and uncertainty. eRATs are computer-based algorithms designed to help clinicians avoid missing important diagnoses, pick up possible symptoms early and facilitate shared decision-making.Design Systematic search, using predefined criteria of the published literature and synthesis of the qualitative data, using Thematic Synthesis. …”
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Algorithm of Behaviour of Virtual Avatars During Public Speaking Training in a VR Environment by Karol Jędrasiak, Robert Robert Wolański, Damian Bereska

“…Project and methods: The project involved developing an innovative algorithm designed to control the behaviour of virtual avatars during public speaking training in a VR environment. …”
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A deep learning algorithm to generate synthetic computed tomography images for brain treatments from 0.35 T magnetic resonance imaging by Luca Vellini, Flaviovincenzo Quaranta, Sebastiano Menna, Elisa Pilloni, Francesco Catucci, Jacopo Lenkowicz, Claudio Votta, Michele Aquilano, Andrea D’Aviero, Martina Iezzi, Francesco Preziosi, Alessia Re, Althea Boschetti, Danila Piccari, Antonio Piras, Carmela Di Dio, Alessandro Bombini, Gian Carlo Mattiucci, Davide Cusumano

“…This study introduces a Deep Learning (DL) algorithm designed to quickly generate synthetic CT (sCT) images from low-field MR images in the brain, an area not yet explored. …”
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Adversarial measurements for convolutional neural network-based energy theft detection model in smart grid by Santosh Nirmal, Pramod Patil, Sagar Shinde

“…The attack comprises two methods: the first is we originally propose a novel Adversarial Data Generation Method (ADGM), which is an algorithm designed to generate adversarial data, and the other is Fast Gradient Sign Method (FGSM). …”
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Clinical validation of an artificial intelligence algorithm for classifying tuberculosis and pulmonary findings in chest radiographs by Thiago Fellipe Ortiz de Camargo, Thiago Fellipe Ortiz de Camargo, Guilherme Alberto Sousa Ribeiro, Guilherme Alberto Sousa Ribeiro, Maria Carolina Bueno da Silva, Luan Oliveira da Silva, Pedro Paulo Teixeira e Silva Torres, Denise do Socorro Rodrigues da Silva, Mayler Olombrada Nunes de Santos, William Salibe Filho, Marcela Emer Egypto Rosa, Magdala de Araujo Novaes, Thiago Augusto Massarutto, Osvaldo Landi Junior, Elaine Yanata, Marcio Rodrigues da Cunha Reis, Gilberto Szarf, Pedro Vieira Santana Netto, Joselisa Peres Queiroz de Paiva

“…This study evaluates a deep learning algorithm designed for CXR interpretation, focusing on its utility for non-specialists in thoracic radiology physicians.PurposeTo assess the performance of a Convolutional Neural Networks (CNNs)-based AI algorithm in interpreting CXRs and compare it with a team of physicians, including thoracic radiologists, who served as the gold-standard.MethodsA retrospective study from January 2021 to July 2023 evaluated an algorithm with three independent models for Lung Abnormality, Radiological Findings, and Tuberculosis. …”
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Population Dynamics of the Crocodile Shark, <i>Pseudocarcharias kamoharai</i>, in the Tropical Equatorial Pacific Ocean, Ecuador by Marcos Douglas Calle-Morán, Eugenio Alberto Aragón-Noriega, Ana Rosa Hernández-Téllez, Emigdio Marín-Enríquez, Javier Tovar-Ávila, Juan Francisco Arzola-González, Jorge Payán-Alejo

“…These values were similar to the six algorithms designed for cartilaginous fish, ranging from 0.16 to 0.35; for this reason, these mortality rates were considered low. …”
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