ALS+PDR: Indoor Pedestrian Dead Reckoning Using a Smartphone Ambient Light Sensor by Sosuke Otsuka, Yusei Onishi, Mananari Nakamura, Hiromichi Hashizume, Masanori Sugimoto

“…The results indicated an average error of 11.30 m when only PDR was used, with a substantial reduction to 2.03 m when the proposed method was used. …”
Get full text

Fuzzy logic-based simulation of a weighted integrated GNSS receiver for mitigating blocking interference effects by K. Bahmani, M.R. Mosavi, A. Sadr

“…Specifically, an average improvement of 36.50% in Root Mean Square (RMS) error and a 31.10% reduction in Geometric Dilution of Precision (GDOP) have been observed compared to the Least Squares (LS) method.…”
Get full text

Efficient on-shell matching by Mikael Chala, Javier L. Miras, José Santiago, Fuensanta Vilches

“…The standard off-shell approach to matching requires the use of a Green's basis that includes redundant and evanescent operators. The reduction of such a basis to a physical one is often highly non-trivial, difficult to automate and error prone. …”
Get full text

Calculation Model of Multi-roll Straightening Process Based on Bilinear Hardening and Power Hardening by ZHU Xiaoyu, CHENG Zixing, WANG Xiaogang, HAN Peisheng

“…The results show that with increasing reduction, the error between hardened and ideal models increases. …”
Get full text

Investigating the accuracy of adjusting for examiner differences in multi-centre Objective Structured Clinical Exams (OSCEs). A simulation study of video-based Examiner Score Compa... by Peter Yeates, Gareth McCray

“…We replicated this 1000 times for each permutation to determine average error reduction and the proportion of students whose scores became more accurate. …”
Get full text

Sustainable energy: Advancing wind power forecasting with grey wolf optimization and GRU models by Zainab Al-Ibraheemi, Samaher Al-Janabi

“…The proposed approach addresses both larger datasets and the impact of noise samples on prediction errors. Additionally, an MLDDR model was introduced to predict DC power generated from wind datasets, encompassing five stages: Data Preparation, Feature Selection, Data Compression, GRU-Based Predictions, and Rate of Reduction. …”
Get full text

Numerical investigation of flow field characteristics over vertical drops with sudden contraction for different contraction ratios by Hossein Shahin, Afshin Eghbalzadeh, Mitra Javan

“…The simulation employed the RNG k-ε turbulence model in conjunction with the volume of fluid (VOF) method to capture free surface dynamics. The computational model was validated against experimental data, yielding acceptable levels of accuracy based on average percentage error (APE) and root mean square error (RMSE) metrics. …”
Get full text

Quantum Computing-Accelerated Kalman Filtering for Satellite Clusters: Algorithms and Comparative Analysis by Shreyan Prakash, Raj Bhattacherjee, Sainath Bitragunta, Ashutosh Bhatia, Kamlesh Tiwari

“…These advances significantly improve computational efficiency and error handling, making the method highly scalable under varying noise levels. …”
Get full text

Construction of a NOx Emission Prediction Model for Hybrid Electric Buses Based on Two-Layer Stacking Ensemble Learning by Jiangyan Qi, Xionghui Zou, Ren He

“…The evaluation metrics of the proposed model—mean absolute error, root mean square error, and coefficient of determination—are 0.0068, 0.0283, and 0.9559, respectively, demonstrating a significant advantage compared to other benchmark models.…”
Get full text

Residual learning based convolution neural network for improved channel estimation for VehA channel by Sunita Khichar, Yahui Meng, Abhishek Sharma, Muhammad Saadi, Amir Parniarifard, Sushank Chaudhary

“…Comprehensive simulations using the VehicularA (VehA) channel model demonstrate that the proposed method achieves up to 30% lower mean squared error (MSE) compared to LS estimation and 15% lower MSE compared to ChannelNet at an SNR of 12 dB. …”
Get full text

Smooth Guided Adversarial Fully Test-Time Adaptation by Dong Li, Panfei Yang

“…Experimentally, SAFTTA demonstrates state-of-the-art results, improving error rate by 0.7% on the CIFAR-10-C benchmark and achieving a 1.1% reduction in error rate on the ImageNet-C benchmark compared to existing methods. …”
Get full text

Correction of Faulty Sensors in Phased Array Radars Using Symmetrical Sensor Failure Technique and Cultural Algorithm with Differential Evolution by S. U. Khan, I. M. Qureshi, F. Zaman, B. Shoaib, A. Naveed, A. Basit

“…The hybrid method combines the cultural algorithm with differential evolution (CADE) which is used for the reduction of sidelobe levels and placement of nulls at their original positions. …”
Get full text

Sensor placement optimization for critical-grid coverage problem of indoor positioning by Hui Wu, Zhe Liu, Jin Hu, Weifeng Yin

“…At last, the simulation experiment and real environment validation were conducted for proposed method. The results showed that the optimized schemes obtain a lower error (1.13, 1.21 m) and a higher reduction of sensor deployment cost than the uniform deployment scheme (1.44 m). …”
Get full text

Any-to-any voice conversion using representation separation auto-encoder by Zhihua JIAN, Zixu ZHANG

“…In view of the problem that it was difficult to separate speaker personality characteristics from semantic content information in any-to-any voice conversion under non-parallel corpus, which led to unsatisfied performance, a voice conversion method, called RSAE-VC (representation separation auto-encoder voice conversion) was proposed.The speaker’s personality characteristics in the speech were regarded as time invariant and the content information as time variant, and the instance normalization and activation guidance layer were used in the encoder to separate them from each other.Then the content information of the source speech and the personality characteristics of the target one was utilized to synthesize the converted speech by the decoder.The experimental results demonstrate that RSAE-VC has an average reduction of 3.11% and 2.41% in Mel cepstral distance and root mean square error of pitch frequency respectively, and has an increasement of 5.22% in MOS and 8.45% in ABX, compared with the AGAIN-VC (activation guidance and adaptive instance normalization voice conversion) method.In RSAE-VC, self-content loss is applied to make the converted speech reserve more content information, and self-speaker loss is used to separate the speaker personality characteristics from the speech better, which ensure the speaker personality characteristics be left in the content information as little as possible, and the conversion performance is improved.…”
Get full text

LX-mixers for QAOA: Optimal mixers restricted to subspaces and the stabilizer formalism by Franz G. Fuchs, Ruben Pariente Bassa

“…We present a novel formalism to both understand and construct mixers that preserve a given subspace. The method connects and utilizes the stabilizer formalism that is used in error correcting codes. …”
Get full text

Improved Low-Complexity, Pilot-Based Channel Estimation for Large Intelligent Surface Systems by Ali Gashtasbi, Mário Marques da Silva, Rui Dinis

“…Collectively, these strategies lead to a significant reduction in the Bit Error Rate (BER) and a remarkable improvement in the overall system performance, offering a practical solution for complex LIS deployments.…”
Get full text

Causality-Driven Feature Selection for Calibrating Low-Cost Airborne Particulate Sensors Using Machine Learning by Vinu Sooriyaarachchi, David J. Lary, Lakitha O. H. Wijeratne, John Waczak

“…Similarly, for the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>PM</mi><mrow><mn>2.5</mn></mrow></msub></mrow></semantics></math></inline-formula> model, the proposed feature selection led to a 33.2% reduction in the mean squared error, outperforming the 30.2% reduction achieved by the SHAP value-based selection. …”
Get full text

Random-forest-based task pricing model and task-accomplished model for crowdsourced emergency information acquisition by Wenxiang Li, Shengqun Chen, Lijin Lin, Li Chen

“…In addition,the making money by taking photos dataset is used for a simulation of the proposed method in scikit-learn. Our simulation results demonstrate that the proposed method has an average reduction in Mean Squared Error (MSE) by 44.16 % for task pricing and an average increase in accuracy of 17.71 % for task-accomplished prediction compared to traditional regression models. …”
Get full text

Building Damage Visualization Through Three-Dimensional Reconstruction and Window Detection by Ittetsu Kuniyoshi, Itsuki Nagaike, Sachie Sato, Yue Bao

“…Experiments were conducted on prefabricated structures, detached houses, and dense residential areas to validate the method’s accuracy. Results show that the proposed approach achieved measurement accuracy comparable to or better than traditional methods, with an error reduction of approximately 19% in prefabricated structures and 21.72% in detached houses. …”
Get full text

The effect of resizing on the natural appearance of scintigraphic images: an image similarity analysis by Siraj Ghassel, Amir Jabbarpour, Jochen Lang, Eric Moulton, Eric Moulton, Ran Klein, Ran Klein, Ran Klein, Ran Klein

“…For each resizing method, we computed the similarity of resized images to count-matched images acquired at the target grid size with the structural similarity index measure and the logarithm of the mean squared error. …”
Get full text