Blockchain Scalability Analysis and Improvement of Bitcoin Network through Enhanced Transaction Adjournment Techniques by Umar Danjuma Maiwada

“…The second part of this research work proposes an effective algorithm that improves scalability of Bitcoin network through efficient transaction deferment. …”
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Optimizing low complexity encoding method for systematic polar code by Linhua MA, Shiping LIU, Xing HU, Tianyu HUANG, Bin XU

“…In order to solve the delay caused by step-by-step calculation and the computational complexity caused by iterative “exclusive-or” computation during the encoding process,a dimensionality reduction strategy was proposed and defined.Based on this,system polarization code parallel coding algorithm for cracking strategy was proposed.Simulation and computational complexity analysis were carried out on AWGN channel.The results show that the coding gain of the above algorithm is slightly better than the traditional one or almost the same,but the computational complexity is up to 80.92%,which is more suitable for hardware implementation and engineering application.It is more suitable for hardware implementation and has a certain practical value.…”
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Challenges in COVID-19 Pandemic Triaging: An Indian and US Perspective by Muralidhar Varma, Robin Sudandiradas, Mauli Mahendra Patel, Trini Ann Mathew, Marcus Zervos, Shashikiran Umakanth, Asha Kamath, Mahadev Rao, Vandana Kalwaje Eshwara, Chiranjay Mukhopadhyay, Vijaya Arun Kumar

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Implementation of an Active Vibration Control System on a Cogeneration Plant by Emanuele Voltolini, Daniel Pinardi, Andrea Toscani, Marco Binelli, Angelo Farina, Jessica Ferrari, Andrea Zenaro, Stefano Maglia, Enrico Calzavacca

“…This paper presents a noise reduction solution for a cogeneration plant, consisting of an Active Vibration Control (AVC) system applied to the cogenerator enclosure. …”
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Collaborative filtering based on nonnegative/binary matrix factorization by Yukino Terui, Yuka Inoue, Yohei Hamakawa, Kosuke Tatsumura, Kazue Kudo, Kazue Kudo

“…While previous studies have applied NBMF primarily to dense data such as images, this paper proposes a modified NBMF algorithm tailored for collaborative filtering with sparse data. …”
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Advance path loss model for LoRaWAN coverage estimation by Van Lic Tran, Tran Dang Khoa Phan, Tran Thi Minh Hanh, Vu Van Thanh, Thai Van Tien, Thai Vu Hien, Tran Anh Kiet

“…This paper demonstrates that, using multiple data points around each gateway allows for the creation of accurate coverage heat maps by using a proposed LoRaWAN coverage estimation algorithm. This method effectively identifies areas with varying signal strength across Da Nang City, highlighting where additional gateways are needed to improve network reliability. …”
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Determining Driving Risk Factors from Near-Miss Events in Telematics Data Using Histogram-Based Gradient Boosting Regressors by Shuai Sun, Montserrat Guillen, Ana M. Pérez-Marín, Linglin Ni

“…It can be seen that the machine learning algorithm offers the prospect of more accurate risk assessments and insurance pricing.…”
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The Machine Learning-Based Task Automation Framework for Human Resource Management in MNC Companies by Suchitra Deviprasad, N. Madhumithaa, I. Walter Vikas, Archana Yadav, Geetha Manoharan

“…MNCs are now beginning to use ML algorithms in combination with Artificial Intelligence (AI) to streamline the HR processes. …”
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Discovering the Influences of Complex Network Effects on Recovering Large Scale Multiagent Systems by Yang Xu, Pengfei Liu, Xiang Li, Wei Ren

“…Those interesting discoveries are helpful to predict how complex network attributes influence on system performance and in turn are useful for new algorithm designs that make a good use of those attributes.…”
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Single cell analysis of host response to helminth infection reveals the clonal breadth, heterogeneity, and tissue-specific programming of the responding CD4+ T cell repertoire. by Ivy K Brown, Nathan Dyjack, Mindy M Miller, Harsha Krovi, Cydney Rios, Rachel Woolaver, Laura Harmacek, Ting-Hui Tu, Brian P O'Connor, Thomas Danhorn, Brian Vestal, Laurent Gapin, Clemencia Pinilla, Max A Seibold, James Scott-Browne, Radleigh G Santos, R Lee Reinhardt

“…Antigen-reactivity of the broader repertoires was predicted to be shared across both tissues and individual mice. …”
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ANALISIS KINERJA MODEL STACKING BERBASIS RANDOM FOREST DAN SVM DALAM KLASIFIKASI RUMAH TANGGA BERDASARKAN GARIS KEMISKINAN MAKANAN DI PROVINSI JAWA BARAT by Ghardapaty Ghaly Ghiffary, Nabila Tri Amanda, Rizky Ardhani, Bagus Sartono, Aulia Rizki Firdawanti

“…The stacking method is an ensemble technique in machine learning that combines predictions from several base models to improve classification accuracy. …”
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Vibration Diagnostic Methods from Methodsof Obtaining Data to Processing It Using Modern Means by Anton O. Zhuravlev, Alexey O. Polyakov, Denis A. Andrikov

“…Thus, self-diagnosis, combined with a high level of automated analytics, makes it possible to predict a malfunction with a high degree of probability, warn about the timing of its occurrence and methods of preventive elimination. …”
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Integrating feedback control for improved human-structure interaction analysis by Santiago A. Lopez, Daniel Gomez, Albert R. Ortiz, Sandra Villamizar

“…The results of this study indicate that feedback controllers accurately predict the experimental structural response for different subjects. …”
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A Novel Admixture-Based Pharmacogenetic Approach to Refine Warfarin Dosing in Caribbean Hispanics. by Jorge Duconge, Alga S Ramos, Karla Claudio-Campos, Giselle Rivera-Miranda, Luis Bermúdez-Bosch, Jessicca Y Renta, Carmen L Cadilla, Iadelisse Cruz, Juan F Feliu, Cunegundo Vergara, Gualberto Ruaño

“…<h4>Results</h4>The admixture-adjusted, genotype-guided warfarin dosing refinement algorithm developed in Caribbean Hispanics showed better predictability (R2 = 0.70, MAE = 0.72mg/day) than a clinical algorithm that excluded genotypes and admixture (R2 = 0.60, MAE = 0.99mg/day), and outperformed two prior pharmacogenetic algorithms in predicting effective dose in this population. …”
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Machine Learning Modeling of Disease Treatment Default: A Comparative Analysis of Classification Models by Michael Owusu-Adjei, James Ben Hayfron-Acquah, Frimpong Twum, Gaddafi Abdul-Salaam

“…The focus on contextual nonbiomedical measurements using a supervised machine learning modeling technique is aimed at creating an understanding of the reasons why treatment default occurs, including identifying important contextual parameters that contribute to treatment default. The predicted accuracy scores of four supervised machine learning algorithms, namely, gradient boosting, logistic regression, random forest, and support vector machine were 0.87, 0.90, 0.81, and 0.77, respectively. …”
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Analyzing and forecasting under-5 mortality trends in Bangladesh using machine learning techniques. by Shayla Naznin, Md Jamal Uddin, Ishmam Ahmad, Ahmad Kabir

“…Projections indicate further reductions in under-5 mortality to 29.87 per 1,000 live births by 2030 and 26.21 by 2035.…”
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Efficient and Stable Learning for Distribution Network Operation: A Model-Based Reinforcement Learning Approach by Dong Yan, Zhan Shi, Xinying Wang, Yiying Gao, Tianjiao Pu, Jiye Wang

“…Despite the improved control flexibility, traditional prediction-plus-optimization models struggle to adapt to rapidly shifting demands. …”
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Multitarget Vehicle Tracking and Motion State Estimation Using a Novel Driving Environment Perception System of Intelligent Vehicles by Yuren Chen, Xinyi Xie, Bo Yu, Yi Li, Kunhui Lin

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Identifying and prioritizing antifragile tourism strategies in a Neutrosophic environment by Mahdi Ghaforiyan, Ali Sorourkhah, Seyyed Edalatpanah

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Dissertation council in the state scientific certification system: Organizational and management mechanisms of digital transformation by Sergey I. Pakhomov, Elena A. Loginova, Oleg V. Kulyamin, Mikhail P. Petrov

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