Design a low-noise 5GHz wideband microwave power amplifier using 90nm CMOS technology with area reduction employing an active inductor by Taha Naufal Fadhil, A.Z. Yonis

“…We got these results: With an NF of 1.308 and an ideal power usage of 2.64 mW, we achieved an optimal gain of 27.21 dB(S2, 1). Our results show that evolutionary algorithms greatly improve LNA performance by pointing to the best settings for maximizing gain and reducing noise. …”
Get full text

Dispatching strategy of shared bicycles for morning peak tidal travel based on spatial distribution by Xiangyu Lei, Jiaqi Yang

“…The study identifies the spatial distribution characteristics of the tidal phenomenon by analyzing the riding order and electronic fence data and combining them with the KD-Tree algorithm; subsequently, a demand prediction model based on the XGBoost algorithm and a hierarchical scheduling model based on the greedy algorithm are constructed to dynamically optimize the spatial distribution of the bicycle resources with the demand fluctuation as the guide. …”
Get full text

Mapping individual tree crowns to extract morphological attributes in urban areas using unmanned aerial vehicle-based LiDAR and RGB data by Geonung Park, Bonggeun Song, Kyunghun Park

“…This approach also improved the effectiveness of the DL model, Mask R-CNN, by resolving challenges in label generation. …”
Get full text

Enhancing education quality with hybrid clustering and evolutionary neural networks in a multi phase framework by Saleem Malik, Chandrakanta Mahanty, Jnanaranjan Mohanty, Krunal Vaghela, T. Narmadha, R. Sivaranjani, Javed Khan Bhutto, Saiful Islam, Anwar Khan, Amanuel Zewdie

“…The algorithm improves prediction power through progressive convergence. …”
Get full text

Research on Book Recommendation Integrating Book Category Features and User Attribute Information by Yan Chen, Eric Blancaflor, Mideth Abisado

“…Aiming at the problem of poor recommendation effect caused by data sparsity in traditional collaborative filtering algorithm in book recommendation, this study proposes a personalized recommendation model (BCF-UAI) that combines book category features and user attribute information, aiming to improve the accuracy and generalization ability of the recommendation system. …”
Get full text

Research on intelligent energy management strategies for connected range-extended electric vehicles based on multi-source information by Xuewen Zhai, Hanwu Liu, Wencai Sun, Zihang Su

“…The Euclidean distance between consecutive traffic scenario matrices is used as a basis for similarity to optimize speed and predict future vehicle speeds. Moreover, a multi-objective intelligent EMS based on deep reinforcement learning (DRL) is employed, utilizing the Deep Deterministic Policy Gradient (DDPG) algorithm to comprehensively consider vehicle dynamics, energy consumption economy, and the degradation of batteries. …”
Get full text

Reconstruction for Scanning LiDAR with Array GM-APD on Mobile Platform by Di Liu, Jianfeng Sun, Wei Lu, Sining Li, Xin Zhou

“…This method avoids the need for field-of-view registration, improves data utilization, and reduces the complexity of the algorithm while eliminating the effect of LiDAR motion. …”
Get full text

Hunting Stability Enhancement of a Train Bogie Employing Inerter-Based Suspension Mechanism by Yong Wang, Chenyang Hong, Haodong Meng

“…The structural parameter analysis of inerter-based suspension mechanism is conducted, and the structural parameters are optimized using the nondominated sorting whale optimization algorithm (NSWOA). …”
Get full text

Protein docking by the underestimation of free energy funnels in the space of encounter complexes. by Yang Shen, Ioannis Ch Paschalidis, Pirooz Vakili, Sandor Vajda

“…This algorithm explores the free energy surface spanned by encounter complexes that correspond to local free energy minima and shows similarity to the model of macromolecular association that proceeds through a series of collisions. …”
Get full text

A Method of Locating and Measuring Train Wheel Tread Defects Based on YOLOv3-tiny by JIN Kairong, WANG Junping, CHEN Shenglan

“…In order to solve the key problems that the detection frame is too large and too small, traditional image algorithms such as Fourier transform, band-stop filter, and threshold segmentation are used to construct a defect size measurement model, contours of roughly located defects are extracted and detection frame size is optimized, and finally location and size of defect are accurately calculated. …”
Get full text

Systemic therapy for laryngeal carcinoma by Thorsten Fuereder, Florian Kocher, Jan Baptist Vermorken, Jan Baptist Vermorken

“…Consequently, multiple recent efforts have been made to integrate novel immunotherapies into the current treatment algorithm for LSCC. In particular, perioperative immunotherapy regimens appear to be the most promising approach for preserving laryngeal function and optimizing event-free and overall survival rates in the locally advanced setting. …”
Get full text

Breast Tumor-Like-Masses Segmentation From Scattering Images Obtained With an Ultrahigh-Sensitivity Talbot-Lau Interferometer Using Convolutional Neural Networks by Ionut-Cristian Ciobanu, Nicoleta Safca, Elena Anghel, Dan Popescu

“…U-Net demonstrated the most stable performance with an accuracy of 86.34% and an F1-score of 90.2%, making it the most reliable model for tumor segmentation in scattering images. …”
Get full text

Deep Learning–Based Prediction of Freezing of Gait in Parkinson's Disease With the Ensemble Channel Selection Approach by Sara Abbasi, Khosro Rezaee

“…Method To address this, we developed a novel algorithm for detecting FoG events based on movement signals. …”
Get full text

An interpretable integrated machine learning framework for genomic selection by Jinbu Wang, Jia Zhang, Wenjie Hao, Wencheng Zong, Mang Liang, Fuping Zhao, Longchao Zhang, Lixian Wang, Huijiang Gao, Ligang Wang

“…Moreover, we introduced the NuSVR model, which achieved the highest accuracy among nine compared algorithms. …”
Get full text

Uncertainty quantification with graph neural networks for efficient molecular design by Lung-Yi Chen, Yi-Pei Li

“…Using benchmarks from the Tartarus and GuacaMol platforms, our results show that UQ integration via probabilistic improvement optimization (PIO) enhances optimization success in most cases, supporting more reliable exploration of chemically diverse regions. …”
Get full text

GeoTemporal clustering for aquifer delineation: a big data approach to synchronizing and analyzing variable-length groundwater time series by Khalid ElHaj, Dalal Alshamsi

“…This technique is adaptive and can be improved through ongoing monitoring. The algorithm components are modular and upgradable thus future studies should optimize and test their generalizability using additional datasets.…”
Get full text

Modular-based psychotherapy (MoBa) versus cognitive–behavioural therapy (CBT) for patients with depression, comorbidities and a history of childhood maltreatment: study protocol fo... by Elisabeth Schramm, Martin Hautzinger, Carolin Jenkner, Moritz Elsaesser, Sabine Herpertz, Hannah Piosczyk

“…A modular-based psychotherapy (MoBa) approach provides a treatment model of independent and flexible therapy elements within a systematic treatment algorithm to combine and integrate existing evidence-based approaches. …”
Get full text

Rock Fracture Monitoring Based on High-Precision Microseismic Event Location Using 3D Multiscale Waveform Inversion by Yi Wang, Xueyi Shang, Kang Peng, Rui Gao

“…Based on this initial location, the multiscale waveform inversion strategy (from coarse to fine grids) and the L-BFGS iteration optimization algorithm were separately jointly selected to improve wavefield modeling speed efficiency and iterative convergence rate. …”
Get full text

Adaptive SDN switch migration mechanism based on coalitional game by Lan YAO, Julong LAN

“…The problem of poor control plane performance causes in software-defined Networking due to the unreasonable mapping relationship between controllers and switches.To address this issue,an adaptive switch migration mechanism based on coalitional game was proposed.First,comprehensively considering the controller resource utilization,control overhead,and flow establishment time,the switch migration problem was modeled as a combination optimization problem.Then,a game theory was introduced to design a distributed algorithm,where each controller ran control logic independently and implemented coalitional game between controllers to achieve an adaptive switch migration mechanism that adapted to traffic characteristics.The simulation results show that the proposed mechanism can better adapt to the flow characteristics,reduce the control traffic overhead by about 19% and the average flow settling time by 30%,and improve the controller resource utilization.…”
Get full text

Exploring Monte Carlo Negotiation Search with Nontrivial Agreements by Elijah Alden Malaby, John Licato

“…We demonstrate significant improvement of our algorithm over random agreement sampling, although further work is required to more consistently produce optimal agreements.…”
Get full text