A Hybrid Model for Prediction in Asphalt Pavement Performance Based on Support Vector Machine and Grey Relation Analysis by Xuancang Wang, Jing Zhao, Qiqi Li, Naren Fang, Peicheng Wang, Longting Ding, Shanqiang Li

“…Meanwhile, the contrast with the grey model (GM (1, 1)), genetic algorithm optimization BP[[parms resize(1),pos(50,50),size(200,200),bgcol(156)]]081%, −0.823%, 1.270%, and −4.569%, respectively. …”
Get full text

Improving Imitation Skills in Children with Autism Spectrum Disorder Using the NAO Robot and a Human Action Recognition by Abeer Alnafjan, Maha Alghamdi, Noura Alhakbani, Yousef Al-Ohali

“…<b>Results:</b> We developed a deep learning approach based on the human action recognition algorithm for analyzing clapping imitation. <b>Conclusions:</b> Our findings suggest that integrating robotics into therapeutic practices can effectively enhance the imitation skills of children with ASD, offering valuable support to therapists.…”
Get full text

A Novel Energy Consumption Prediction Model Integrating Real-Time Traffic State Recognition and Velocity Prediction of BEVs by Yue Li, Yu Jiang, Jianhua Guo, Dong Xie

“…Consequently, we propose an improved Fuzzy C-Means (FCM) clustering algorithm that use historical traffic data and dynamic traffic information accurately identify traffic conditions. …”
Get full text

Obtaining patient phenotypes in SARS-CoV-2 pneumonia, and their association with clinical severity and mortality by Fernando García-García, Dae-Jin Lee, Mónica Nieves-Ermecheo, Olaia Bronte, Pedro Pablo España, José María Quintana, Rosario Menéndez, Antoni Torres, Luis Alberto Ruiz Iturriaga, Isabel Urrutia, COVID-19 & Air Pollution Working Group

“…We proposed a sequence of machine learning stages: feature scaling, missing data imputation, reduction of data dimensionality via Kernel Principal Component Analysis (KPCA), and clustering with the k-means algorithm. The optimal cluster model parameters –including k, the number of phenotypes– were chosen automatically, by maximizing the average Silhouette score across the training set. …”
Get full text

Perbandingan Metode Penyelesaian Permasalahan Optimasi Lintas Domain dengan Pendekatan Hyper-Heuristic Menggunakan Algoritma Reinforcement-Late Acceptance by Anang Firdaus, Ahmad Muklason, Vicha Azthanty Supoyo

“…In improving performance, this study examines the effect of the adaptation of the Reinforcement Learning (RL) algorithm as LLH selection combined with the Late Acceptance algorithm as a move acceptance. …”
Get full text

The efficacy of sinustrabeculectomy in the modern clinical practice by A.V. Antonova, V.P. Nikolaenko, V.V. Brzheskiy, A.Ya. Vuks

“…</p> <p> <b>Keywords</b>: glaucoma, sinustrabeculectomy , intraocular pressure, glaucoma surgery, cascade algorithm, complete success, qualified success, complete failure. …”
Get full text

A Three-Stage-Concatenated Non-Linear MMSE Interference Rejection Combining Aided MIMO-OFDM Receiver and its EXIT-Chart Analysis by Jue Chen, Siyao Lu, Tsang-Yi Wang, Jwo-Yuh Wu, Chih-Peng Li, Soon Xin Ng, Robert G. Maunder, Lajos Hanzo

“…Based on this concept, we then design a novel NL equalizer relying on the Smart Ordering and Candidate Adding (SOCA) algorithm. This reduced complexity NL detection algorithm is particularly well suited for practical hardware implementation using parallel processing at a low latency. …”
Get full text

Segmentasi Pelanggan Ritel Produk Farmasi Obat Menggunakan Metode Data Mining Klasterisasi Dengan Analisis Recency Frequency Monetary (RFM) Termodifikasi by Arief Wibowo, Andy Rio Handoko

“…The performance of the model is compared with the K-Medoids algorithm. The results of customer clustering in two categories using K-Medoids have a DBI value of 1,334. …”
Get full text

EyeLiner by Yoga Advaith Veturi, MSc, Steve McNamara, OD, Scott Kinder, MS, Christopher William Clark, MS, Upasana Thakuria, MS, Benjamin Bearce, MS, Niranjan Manoharan, MD, Naresh Mandava, MD, Malik Y. Kahook, MD, Praveer Singh, PhD, Jayashree Kalpathy-Cramer, PhD

“…Methods: Anatomical keypoints along the retinal blood vessels were detected from the moving and fixed images using a convolutional neural network and subsequently matched using a transformer-based algorithm. Finally, transformation parameters were learned using the corresponding keypoints. …”
Get full text

Delta radiomics modeling based on CTP for predicting hemorrhagic transformation after intravenous thrombolysis in acute cerebral infarction: an 8-year retrospective pilot study by Xiaxia Wu, Xiaxia Wu, Jinfang Yang, Jinfang Yang, Xianqun Ji, Yingjian Ye, Ping Song, Lina Song, Peng An, Peng An

“…This was confirmed by the XGboost algorithm, and decision curves confirmed the higher clinical net benefit of the combined model. …”
Get full text

APG mergence and topological potential optimization based heuristic user association strategy by Zhirui HU, Meihua BI, Fangmin XU, Meilin HE, Changliang ZHENG

“…Therefore, it is reasonable to model the problem of improving network scalable degree as minimizing network coupling degree,and it is feasible to improve network scalable degree by reducing network coupling degree.2)The upper limit of computational complexity of the proposed algorithm is <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"> <mi mathvariant="script">O</mi><mo stretchy="false">(</mo><mi>K</mi><mi>N</mi><msub> <mi>log</mi> <mn>2</mn> </msub> <mi>N</mi><mo>+</mo><msup> <mi>k</mi> <mn>2</mn> </msup> <mo>+</mo><mi>N</mi><mi>N</mi><msub> <mover accent="true"> <mi>N</mi> <mo>¯</mo> </mover> <mtext>p</mtext> </msub> <mo stretchy="false">)</mo></math></inline-formula>,while that of directly solving the optimization problem is<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"><mi mathvariant="script">O</mi><mo stretchy="false">(</mo><msup> <mi>N</mi> <mrow> <msub> <mover accent="true"> <mi>N</mi> <mo>¯</mo> </mover> <mtext>u</mtext> </msub> <mi>K</mi></mrow> </msup> <mo stretchy="false">)</mo></math></inline-formula>.3)For theoretical analysis of the network scalable degree,take Fig.3 as an example.If AP2 changes,12 APs in Fig. 3(a)are affected and the network scalable degree is η₂=0.51,while 4 APs in Fig.3(c)are affected and the network scalable degree is η₂=0.79.4)Fig.5 shows the simulation results of network scalable degree.Compared with the traditional strategy,the network scalable degree is improved by 9.59% with 4.43% user rate loss.Compared with the strategy in[10],the network scalable degree is improved by 22.15% with 4.99% user rate loss. 5) The algorithm parameters, the threshold β₀of overlap rate and the upper limit number N₀of AP associated, effect the performance.As shown in Fig.6,with β₀or N₀decreases,η increases and the total user rate decreases. …”
Get full text

Shannon Entropy and K-Means Method for Automatic Diagnosis of Broken Rotor Bars in Induction Motors Using Vibration Signals by David Camarena-Martinez, Martin Valtierra-Rodriguez, Juan P. Amezquita-Sanchez, David Granados-Lieberman, Rene J. Romero-Troncoso, Arturo Garcia-Perez

“…For automatic diagnosis, the K-means cluster algorithm and a decision-making unit that looks for the nearest cluster through the Euclidian distance are applied. …”
Get full text

Research on the Method of Traffic Organization and Optimization Based on Dynamic Traffic Flow Model by Shu-bin Li, Guang-min Wang, Tao Wang, Hua-ling Ren

“…Then the appropriated optimization model and algorithm were proposed according to different optimized content and organization goals, and the traffic simulation processes more suitable to regional optimization were designed exactly. …”
Get full text

Timetable Design for Urban Rail Line with Capacity Constraints by Yu-Ting Zhu, Bao-Hua Mao, Lu Liu, Ming-Gao Li

“…Then, based on the simulation results, a two-stage genetic algorithm is introduced to find the best timetable. …”
Get full text

Nonlinear Modeling and Identification of an Aluminum Honeycomb Panel with Multiple Bolts by Yongpeng Chu, Hao Wen, Ti Chen

“…In particular, the linear material parameters of the panel are identified via experimental tests at low excitation levels, whereas the nonlinear material parameters of the thin layer are updated by using the genetic algorithm to minimize the residual error between the measured and the simulation data at a high excitation level. …”
Get full text

Dynamic Shift Coordinated Control Based on Motor Active Speed Synchronization with the New Hybrid System by Ting Yan, Lin Yang, Bin Yan, Wei Zhou, Liang Chen, Wei Zhou

“…A new hybrid system with superior performances is applied to present the validity of the adopted control algorithm during upshift or downshift, which can represent planetary gear system and conventional AMT shift procedure, respectively. …”
Get full text

Multi-phase-field modeling and high-performance computation for predicting material microstructure evolution during sintering by Aoi Nakazawa, Shinji Sakane, Tomohiro Takaki

“…We also establish an efficient algorithm on graphics processing unit (GPU) to accelerate the computations of rigid-body motions of particles, which cause densification, and implement it on multiple GPUs in parallel. …”
Get full text

Predicting deep-seated landslide displacement on Taiwan's Lushan through the integration of convolutional neural networks and the Age of Exploration-Inspired Optimizer by J.-S. Chou, H.-M. Nguyen, H.-P. Phan, K.-L. Wang

“…The novel framework evaluates machine learning, time series deep learning, and convolutional neural networks (CNNs), identifying the most effective models to be enhanced by the Age of Exploration-Inspired Optimizer (AEIO) algorithm. Our approach demonstrates exceptional forecasting capabilities by utilizing 8 years of comprehensive data – including displacement, groundwater levels, and meteorological information from the Lushan (mountainous) region in Taiwan. …”
Get full text

Rate Dependent Multicontinuum Progressive Failure Analysis of Woven Fabric Composite Structures under Dynamic Impact by James Lua, Christopher T. Key, Shane C. Schumacher, Andrew C. Hansen

“…MCT treats the constituents of a woven fabric composite as separate but linked continua, thereby allowing a designer to extract constituent stress/strain information in a structural analysis. The MCT algorithm and material damage model are numerically implemented with the explicit finite element code LS-DYNA3D via a user-defined material model (umat). …”
Get full text

Sparse Representation Based SAR Vehicle Recognition along with Aspect Angle by Xiangwei Xing, Kefeng Ji, Huanxin Zou, Jixiang Sun

“…Initially, the sparse representation vector of a test sample is solved by sparse representation algorithm with a principle component analysis (PCA) feature-based dictionary. …”
Get full text