Ethics of Artificial Intelligence and Robotics: Key Issues and Modern Ways to Solve Them by N. Yadav

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A Novel Method for Technology Roadmapping: Nanorobots by Huailan Liu, Zhen Li, Rui Zhang, Yufei Liu, Yixin He

“…To overcome these shortcomings, this paper introduces a novel framework that utilizes the ALBERT method combined with multi-source data for critical theme extraction. It integrates varied data sources, including academic papers and patents, to explore the interrelation within the nanorobot technology roadmap. …”
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Self-supervised learning reduces label noise in sharp wave ripple classification by Saber Graf, Pierre Meyrand, Cyril Herry, Tiaza Bem, Feng-Sheng Tsai

“…By utilizing SSL, we effectively relabel SWR data, leveraging the inherent structural patterns within time-series data to improve label quality without relying on external labeling. …”
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JSC "Gomselmash": on a Way to Digitalization of the Manufacture by A. S. Shantyko, V. I. Kozlov, S. V. Karabankova

“…In this article it is noted, that the next problem within the limits of JSC “Gomselmash” on a way of the concept «the Industry 4.0» development is a full integration on the basis of one informational platform not only various program systems, but also corporate data, and also guarantee of operative interacting between various divisions of holding. …”
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Business metrics in the age of digitalization: new challenges and opportunities by I. N Belousov, U. A. Borovy, K. G. Gladkov

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Effects of Dielectric Properties of Human Body on Communication Link Margins and Specific Absorption Rate of Implanted Antenna System by Soham Ghosh, Sunday C. Ekpo, Fanuel Elias, Stephen Alabi, Bhaskar Gupta

“…This study examines how the effective dielectric characteristics of the human torso affect the carrier-link-margin (CLM) and data-link-margin (DLM) of a biocompatible gelatin-encapsulated implantable medical device (IMD) that consists of a small implantable antenna, battery, printed circuit board (PCB), camera, and sensor operating at 2.5 GHz. …”
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Machine learning insights for predicting density and hardness in centrifugal SHS synthesized ceramic coatings by N. Radhika, M. Sabarinathan, S. Sivaraman

“…Gaussian noise augmentation is applied to generate noise data with the same standard deviation to improve the prediction accuracy of the models through an increase in the database volume. …”
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METHOD FOR EVALUATING THE EFFICIENCY OF UPGRADING SPECIALIZED INFORMATION SYSTEMS by Alina Mikhnova, Dmutro Mikhnov, Kateryna Chyrkova

“…The following tasks are solved in the article: analysis of the peculiarities of evaluating the effectiveness of specialized information systems; substantiation of influence of completeness and reliability of data of receiving information from automated workingplaces on the performance indicators of the organization; development of forming stages of the method of estimating the efficiency of modernization of automated workingplaces; practical testing of the method. …”
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ATM: Adaptive transformer model for reconstruction of remote sensing multi-temporal non-equispaced sequence imagery by Zhi-peng Qi, Zi-yi Zhao, Xing Jin

“…Abstract Due to the influence of the imaging characteristics of the solar orbiting satellite and atmospheric conditions, the multi-spectral observation data often have the missing of phase image, which brings difficulties to the efficient and automatic processing of regional remote sensing data. …”
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Visualising and Valuing Urban Agriculture for Land Use Planning: A Critical GIS Analysis of Sydney and Neighbouring Regions by Joshua Zeunert, Scott Hawken, Josh Gowers

“…Employing various spatial-data visualisations to contextualise agricultural production, we examine inherent biophysical agricultural capacity in Sydney and comparable regions along the eastern coast of NSW. …”
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Improving Disparity Consistency With Self-Refined Cost Volumes for Deep Learning-Based Satellite Stereo Matching by Jiyong Kim, Seoyeon Cho, Minkyung Chung, Yongil Kim

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Investigating the Capabilities of Ensemble Machine Learning Model in Identifying Near-Fault Pulse-Like Ground Motions by Jafar Al Thawabteh, Jamal Al Adwan, Yazan Alzubi, Ahmad Al-Elwan

“…The research integrates multiple ensemble techniques to develop a robust and efficient framework for seismic data analysis. These models offer superior performance in handling large datasets, noise reduction, and feature extraction, making them ideal for this application. …”
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Intelligent System for Student Performance Prediction Using Machine Learning by Mustafa S. Ibrahim Alsumaidaie, Ahmed Adil Nafea, Abdulrahman Abbas Mukhlif, Ruqaiya D. Jalal, Mohammed M AL-Ani

“…The high accuracy and efficiency of the proposed system highlight its potential for application in educational data mining. The findings of this proposed to improving student success rates in educational institutions by enabling timely and appropriate interventions. …”
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Real-time traffic monitoring system using IoT-aided robotics and deep learning techniques by Mohammed Qader Kheder, Aree Ali Mohammed

“…Furthermore, optimal distance was found between the ultrasonic sensors and the obstacles using ultrasonics’ waves time and speed to reduce road accidents. The data, which is collected by sensors and cameras, is processed using various image processing algorithms and it is sent to the cloud to be available for drivers and commuters through a mobile application. …”
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Improving guest satisfaction by identifying hotel service micro-elements failures through Deep Learning of online reviews by Sergey Kazakov, Pedro Cuesta-Valiño, Vera Butkouskaya, Daniel Muravsky

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A real-time 3D modeling method for buildings driven by IMU and RGB-D fusion by Yuhan Gao, Chao Dang, Jun Zhu, Yakun Xie, Ya Hu, Chunli Yan, Kun Yi, Chuan Yi, Xue Li

“…With the rapid development of cutting-edge technologies such as autonomous driving, augmented reality, and intelligent robotics, real-time 3D scene reconstruction is increasingly demonstrating its crucial value in diverse application domains. However, 3D reconstruction faces challenges such as redundant data acquisition, inaccurate pose estimation, and insufficient reconstruction precision, making it difficult to support rapid visualization and measurement analysis. …”
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Variable Rate Seeding and Accuracy of Within-Field Hybrid Switching in Maize (<i>Zea mays</i> L.) by Károly Bűdi, Annamária Bűdi, Ádám Tarcsi, Gábor Milics

“…This study evaluates the effectiveness of hybrid switching and the application of VRS technology in maize production, focusing on the accuracy of seeding rate and hybrid placement under varying field conditions. …”
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Analysis, Forecasting, and System Identification of a Floating Offshore Wind Turbine Using Dynamic Mode Decomposition by Giorgio Palma, Andrea Bardazzi, Alessia Lucarelli, Chiara Pilloton, Andrea Serani, Claudio Lugni, Matteo Diez

“…This article presents the data-driven equation-free modeling of the dynamics of a hexafloat floating offshore wind turbine based on the application of dynamic mode decomposition (DMD). …”
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Efficiency enhancement of energy supply chains using a machine learning-driven network evaluation framework for blockchain adoption by Ardavan Babaei, Erfan Babaee Tirkolaee, Shahryar Sorooshian, Sadia Samar Ali, Gongming Wang

“…The findings demonstrate that “single-use strategy” is effective in low-risk scenarios, while “substitution strategy” is optimal in high-risk scenarios. The application of the Super-Efficiency Network Data Envelopment Analysis (SENDEA) model represents its robustness in evaluating blockchain adoption within the industry. …”
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DESIGN OF AN IMPROVED MODEL FOR CARDIOVASCULAR DISEASE DETECTION USING DEEP CANONICAL CORRELATION ANALYSIS AND BIOINSPIRED OPTIMIZATION by Prakash Chandra Sahoo, Binod Kumar Pattanayak, Rajani Kanta Mohanty, Ayasa Kanta Mohanty

“…Moreover, these models have incomplete interpretation and optimization issues, which do not suit their application in a clinical setting. On this, we propose a novel framework for the detection of cardiovascular diseases and presiding analysis through multimodal data fusion, optimized neural networks, and explainable AI techniques. …”
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