Retentive Time Series: A Scalable Machine Learning Model for Traffic Prediction in Elastic Optical Networks by Faranak Khosravi, Mehdi Shadaram

“…Extensive simulations performed on traffic datasets have shown that Ret-TS reduces prediction errors and network blocking probabilities under different traffic loads in three network topologies: NSFNET, Janos-US, and US100. …”
Get full text

Reliable smart models for estimating frictional pressure drop in two-phase condensation through smooth channels of varying sizes by M. A. Moradkhani, S. H. Hosseini, Mengjie Song, A. Abbaszadeh

“…However, the available models are only applicable to specific operating conditions and channel sizes. …”
Get full text

Natural Gas Consumption Forecasting Model Based on Feature Optimization and Incremental Long Short-Term Memory by Huilong Wang, Xianjun Gao, Ying Zhang, Yuanwei Yang

“…Specifically, it achieves notably low average prediction errors of 0.0556 and 0.0392 on the top 10 heating and non-heating days, respectively. …”
Get full text

A Multimedia Medical Expert System for Human Diseases Diagnosis by Ahmed Ameen, Baydaa Khaleel

“…With the great expansion and development of computer science and its systems. Its applications are used in most areas of life, which facilitated the solution of many simple and complex issues, as it was used in multiple fields, including the medical field, where computer applications were designed to help the specialist doctor in his work and reduce the time in diagnosis. …”
Get full text

Applying neural networks as direct controllers in position and trajectory tracking algorithms for holonomic UAVs by Cezary Kownacki, Slawomir Romaniuk, Marcin Derlatka

“…The results highlight that DNNs achieved the highest trajectory tracking accuracy, as measured by root mean squared errors (1.0830) and correlation coefficients (0.9624 given as Pearson’s correlation) while providing satisfactory results and stable flight across untrained scenarios, in opposite to other neural networks. …”
Get full text

Lay-interviewer training protocol for the WHO Flexible Interview for ICD-11 for the National Mental Health Survey – 2 (India) by Lakshmi Jogi, Harsh Khandelwal, Avani Sharma, Niharika Singh, T. S Jaisoorya, Geoffrey M. Reed, Karen T. Maré, Girish N. Rao, Vivek Benegal

“…Training further minimizes human errors by ensuring uniformity in administration of the instrument. …”
Get full text

Professional Balance and it’s Psychological Valences by Mariana ZUBENSCHI

“…Also, the balance theory provides apprehensions about the mechanism of causal reasoning that underlies at the retrospective base of prejudice, also about the justification of personal actions by attributing relational models, and the attribution of errors and successes in the contexts of organizational psychology. …”
Get full text

Blackman–Tukey spectral estimation and electric network frequency matching from power mains and speech recordings by Georgios Karantaidis, Constantine Kotropoulos

“…Maximum correlation coefficient and minimum standard deviation of errors are employed to measure ENF estimation accuracy. …”
Get full text

Survey of node localization scheme in underwater wireless sensor network by YANG Qiuling, ZHU Rongxin, TANG Zhichao, LI Wenjie, HUANG Xiangdang

“…However, localization errors were found to potentially induce data deviations and even cascading failures of system functions. …”
Get full text

Adaptive Fractional Hybrid Impedance Control of Rotary Series Elastic Actuator in Flat Terrains by Muhammed Özdemir, Zafer Bingül

“…The results confirm that AFH‐IC significantly enhances force‐tracking accuracy and robustness in real‐world applications.…”
Get full text

A system dynamics approach for leveraging blockchain technology to enhance demand forecasting in supply chain management by SeyyedHossein Barati

“…It also provides a foundation for future studies to explore the scalability of blockchain in different sectors and its broader applications in optimizing supply chain functions.…”
Get full text

Reforming Real Estate Valuation for Financial Auditors With AI: An In-Depth Exploration of Current Methods and Future Directions by Silviu-Ionut BABTAN

“…This article examines several AI methods – Regression Models, Decision Trees, Random Forests, Artificial Neural Networks, and XGBoost – and explores their applications for improving property valuation accuracy and efficiency, with implications for other professions involved, e.g. audit. …”
Get full text

A Regional Gravimetric and Hybrid Geoid Model in Northern Greece from Dedicated Gravity Campaigns by Georgios S. Vergos, Dimitrios A. Natsiopoulos, Elisavet G. Mamagiannou, Eleni A. Tzanou, Anastasia I. Triantafyllou, Ilias N. Tziavos, Dimitrios Ramnalis, Vassilios Polychronos

“…The determination of physical heights is of key importance for a wide spectrum of geoscientific applications and, in particular, for engineering projects. …”
Get full text

Key Perception Technologies for Intelligent Docking in Autonomous Modular Buses by Ye Xiao, Yuxuan Zheng, Xin Liu, Yifen Ye

“…Experimental results demonstrate that our method achieves a substantial reduction of errors in x and y axes, as well as the heading angle compared with other state-of-the-art perception methods. …”
Get full text

On Risk Assessment for Out-of-Distribution Detection by Anton Vasiliuk

“…Finally, an analysis of popular computer vision benchmarks reveals that ID errors often dominate overall risk, highlighting the importance of strong ID performance as a foundation for effective OOD detection. …”
Get full text

Mounting Angle Prediction for Automotive Radar Using Complex-Valued Convolutional Neural Network by Sunghoon Moon, Younglok Kim

“…The model was trained and validated using mounting angle offsets ranging from −3° to +3° and exhibited errors no greater than 0.15° across all tested offsets. …”
Get full text

Survey of evolutionary kernel fuzzing by Yan SHI, Weizhong QIANG, Deqing ZOU, Hai JIN

“…Fuzzing is a technique that was used to detect potential vulnerabilities and errors in software or systems by generating random, abnormal, or invalid test cases.When applying fuzzing to the kernel, more complex and challenging obstacles were encountered compared to user-space applications.The kernel, being a highly intricate software system, consists of numerous interconnected modules, subsystems, and device drivers, which presented challenges such as a massive codebase, complex interfaces, and runtime uncertainty.Traditional fuzzing methods could only generate inputs that simply satisfied interface specifications and explicit call dependencies, making it difficult to thoroughly explore the kernel.In contrast, evolutionary kernel fuzzing employed heuristic evolutionary strategies to dynamically adjust the generation and selection of test cases, guided by feedback mechanisms.This iterative process aimed to generate higher-quality test cases.Existing work on evolutionary kernel fuzzing was examined.The concept of evolutionary kernel fuzzing was explained, and its general framework was summarized.The existing work on evolutionary kernel fuzzing was classified and compared based on the type of feedback mechanism utilized.The principles of how feedback mechanisms guided evolution were analyzed from the perspectives of collecting, analyzing, and utilizing runtime information.Additionally, the development direction of evolutionary kernel fuzzing was discussed.…”
Get full text

Photo-CIDNP for quantification of micromolar analytes in urine by Marta Stefańska, Thomas Müntener, Sebastian Hiller

“…We report limits of quantification (LOQs) in complex matrices down to 3.5 μM and average errors of less than 26% with the spiking method and less than 11% using biofluid dilution. …”
Get full text

Reliability assessment model for multiple stress factors accelerated degradation test using a Wiener process with random effects. by Qianqian Huang, Jiayin Tang, Xuefeng Feng

“…In practical applications, products are usually exposed to multiple stress factors (including environmental stresses and operating stresses) simultaneously. …”
Get full text

Iterative learning control of neuronal firing based on FHN and HR models. by Chunhua Yuan, Xiaotong Wang, Xiangyu Li, Yueyang Zhao

“…Numerical simulations demonstrate that the proposed control method significantly outperforms conventional PI control, achieving lower tracking errors, enhanced control accuracy, and improved system stability. …”
Get full text