CRASHWORTHINESS DESIGN AND OPTIMIZATION FOR COLLISION POST OF TRAIN by SHI YueQing, QIN RuiXian, CHEN BingZhi

“…Based on the optimal Latin hypercube experimental design method, a polynomial response surface surrogate model of the specific energy absorption and the peak crush force with respect to the wall thickness of the novel multi-cell collision post was established, the multi-objective optimization problem was conducted using the Non-dominated Sorting Genetic Algorithm-Ⅱ and the Pareto front was obtained. The optimization results show that the total energy and specific energy absorption of the novel multi-cell collision post are improved significantly while meeting the structural lightweight requirements compared with the conventional single-cell structure.…”
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Self-Organized Clustering Architecture for Vehicular Ad Hoc Networks by Cándido Caballero-Gil, Pino Caballero-Gil, Jezabel Molina-Gil

“…This paper proposes a new system based on 1-hop clustering to reduce the number of VANET communications in dense road traffic scenarios while maintaining the security of communications by combining public-key with secret-key cryptography. …”
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Cross-layer scheduling and dynamic resource allocation for MIMO-OFDMA/SDMA systems with multi-service by ZHONG Chong-xian1, LI Chun-guo1, YANG Lv-xi1

“…Cross-layer scheduling and dynamic resource allocation problems were investigated for downlink MIMO-OFDMA/SDMA systems with multi-service.Firstly,a mathematical formulation of the optimization problem was provided with the objective of maximizing the total system throughput under various constraints.Secondly,a user group-ing scheme was proposed utilizing clustering analysis method based on the type of services and the spatial compatibility of multiple users with multiple receive antennas.Thirdly,a new cross-layer scheduling and dynamic resource allocation algorithm was developed based on the proposed user grouping scheme combined with the priorities of different service,which maximizes the total system throughput by maximizing the throughput of each subcarrier.Simulation results show that compared with the existing schemes,the proposed algorithms obtain reasonable throughput performance while provide better QoS requirement for each user of different services.…”
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Energy-efficient cooperative sensing and transmission in relay-assisted cognitive radio network by Li FENG, Yu-jun KUANG, Bin-wei WU, Xin-chuan FU

“…An innovative EE-oriented cooperative sensing and transmission scheme in relay-assisted cognitive radio networks,called energy-efficient best-relay cooperative transmission (BCT) was proposed.Based on the BCT scheme,mean energy efficiency (MEE) maximization problem with sensing duration and transmitting power as optimization variables was modeled for fading channels under constraint of minimal secondary outage probability.By virtue of Jensen’s inequality,the original optimization problem was decomposed into two relatively independent subproblems which solved sensing duration and power allocation respectively.And for the two subproblems,an efficient cross iteration based algorithm was proposed to obtain the suboptimal solutions.Both analytical and simulation results demonstrate that the proposals can achieve significantly higher EE while enhancing reliability of secondary transmission remarkably compared to non-cooperation single cognitive transmission schemesin high QoS requirement.…”
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Differential privacy protection scheme based on edge betweenness model by Haiping HUANG, Kai WANG, Xiong TANG, Dongjun ZHANG

“…With the continuous development of social network application,user’s personal social data is so sensitive that the problem of privacy protection needs to be solved urgently.In order to reduce the network data sensitivity,a differential privacy protection scheme BCPA based on edge betweenness model was proposed.The 2K sequence corresponding to the graph structure based on the dK model was captured,and 2K sequences based on the edge betweenness centrality were reordered.According to the result of reordering,the 2K sequence was grouped into several sub-sequences,and each sub-sequence was respectively added with noise by a dK perturbation algorithm.Finally,a social network graph satisfying differential privacy was generated according to the new 2K sequences after integration.Based on the real datasets,the scheme was compared with the classical schemes through simulation experiments.The results demonstrate that it improves the accuracy and usability of data while ensuring desired privacy protection level.…”
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Antioptimisation of Trusses Using Two-Level Population-Based Incremental Learning by Phinit Tontragunrat, Sujin Bureerat

“…The task is to find the optimum solution of common design variables while simultaneously searching for the worst case scenario of those parameters with uncertainties. …”
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Performance analysis of secrecy rate for SWIPT in massive antenna by Hui BAO, Minmin ZHANG, Yaqing YAO, Hui WANG

“…In the multi-drop broadcast system,the existing research is to optimize the single-user security rate in the complete channel state information.In fact,it’s impossible that there exists only one user in the system.The base station often receives incomplete channel state information.Aiming at this problem,a robust beamforming scheme was proposed.In the multi-user case,considering the influence of channel estimation error on the system security rate,the particle swarm optimization algorithm was used to optimize the emission beamforming vector,artificial noise covariance and power split ratio to ensure that the user collects a certain energy while maximizing the safe transmission rate.The simulation results show that the proposed scheme is slightly lower than the security rate in the ideal case,but it is meaningful to the actual system,taking into account the existence of eavesdropping users and the estimation error.…”
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Guaranteed convergence control for consensus of mobile sensor networks with dynamical topologies by Xiangshun Li, Cheng Lei, Lijing Dong, Sing-Kiong Nguang

“…The topology graphs over the mobile sensors are unconnected, directed, dynamical and switched periodically at any moment, while the joint graphs of dynamical topologies are connected in a bounded time period. …”
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Backdoor defense method in federated learning based on contrastive training by Jiale ZHANG, Chengcheng ZHU, Xiang CHENG, Xiaobing SUN, Bing CHEN

“…In response to the inadequacy of existing defense methods for backdoor attacks in federated learning to effectively remove embedded backdoor features from models, while simultaneously reducing the accuracy of the primary task, a federated learning backdoor defense method called ContraFL was proposed, which utilized contrastive training to disrupt the clustering process of backdoor samples in the feature space, thereby rendering the global model classifications in federated learning independent of the backdoor trigger features.Specifically, on the server side, a trigger generation algorithm was developed to construct a generator pool to restore potential backdoor triggers in the training samples of the global model.Consequently, the trigger generator pool was distributed to the participants by the server, where each participant added the generated backdoor triggers to their local samples to achieve backdoor data augmentation.Experimental results demonstrate that ContraFL effectively defends against various backdoor attacks in federated learning, outperforming existing defense methods.…”
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Multifactor Stock Selection Strategy Based on Machine Learning: Evidence from China by Jieying Gao, Huan Guo, Xin Xu

“…The main findings are as follows: the support vector regression has the most stable successful rate for predicting, while ridge regression and linear regression have the most unstable successful rate with more extreme cases; algorithm of support vector regression fitting higher-degree polynomials in Chinese A-share market is optimized, compared with the traditional linear regression both in terms of stock return and retracement control; the results of support vector regression significantly outperforming the CSI 500 index prove further.…”
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Low-Complexity Relay Selection for Full-Duplex Random Relay Networks by Jonghyun Bang, Taehyoung Kim

“…In addition, we propose a low-complexity relay selection algorithm that constructs the candidate relay set while considering the selection diversity gain. …”
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Enhancing Cost and Security of Arabic SMS Messages over Mobile Phone Network by Abdullah Abdullah

“…This paper investigates a novel algorithm for compressing and encrypting Arabic short text messages (SMS messages). …”
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Biopharmaceutical aspects of the development of transdermal forms of Lisinopril dihydrate by Shyteyeva Tatyana, Bezchasnyuk Elena, Kryskiv Oleg, Baranova Inna

“…Optimization of the algorithm for the development of transdermal drugs involves in vitro preformulation studies of the membrane permeability of APIs and the identification of factors that affect this process.…”
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Quantum Zeno Monte Carlo for computing observables by Mancheon Han, Hyowon Park, Sangkook Choi

“…However, they remain susceptible to noise, necessitating noise resilient algorithms. We introduce Quantum Zeno Monte Carlo (QZMC), a classical-quantum hybrid algorithm that demonstrates resilience to device noise and Trotter errors while showing polynomial computational cost for a gapped system. …”
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An Efficient Energy Constraint Based UAV Path Planning for Search and Coverage by German Gramajo, Praveen Shankar

“…The computed trajectory maximizes spatial coverage while closely satisfying terminal constraints on the position of the vehicle and minimizing the time of flight. …”
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Adaptive Production Rescheduling System for Managing Unforeseen Disruptions by Andy J. Figueroa, Raul Poler, Beatriz Andres

“…The results demonstrate that this rescheduling method efficiently adjusts to the new conditions while minimizing deviations from the original schedule, achieving solutions within acceptable computational times.…”
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High-Throughput cDNA Screening Utilizing a Low Order Neural Network Filter by Guyang Matthew Huang, James Farkas, Leroy Hood

“…Evaluation of the detections with two other dissimilar computer prediction algorithms yielded strong transmembrane predictions for 15 of the detections, while 8 of the detections resulted in a definitive negative result. …”
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Copy number variation in familial Parkinson disease. by Nathan Pankratz, Alexandra Dumitriu, Kurt N Hetrick, Mei Sun, Jeanne C Latourelle, Jemma B Wilk, Cheryl Halter, Kimberly F Doheny, James F Gusella, William C Nichols, Richard H Myers, Tatiana Foroud, Anita L DeStefano, PSG-PROGENI and GenePD Investigators, Coordinators and Molecular Genetic Laboratories

“…DNA for all the cases was derived from whole blood, while the DNA for all controls was derived from lymphoblast cell lines. …”
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LEVELS OF PATIENTS EXPOSURE AND A POTENTIAL FOR OPTIMIZATION OF THE PET DIAGNOSTICS IN THE RUSSIAN FEDERATION by L. A. Chipiga, I. A. Zvonova, D. V. Ryzhkova, M. A. Menkov, М. B. Dolgushin

“…The computed tomography scan contributes up to 65 – 95% to the total patient effective dose for whole body examinations; 20 – 30% for head examinations. …”
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Structuring and centralizing breast cancer real-world biomarker data from pathology reports through C-LAB artificial intelligence platform by Florent Le Borgne, Camille Garnier, Camille Morisseau, Yanis Navarrete, Yanina Echeverria, Juan Mir, Jaume Calafell, Tanguy Perennec, Olivier Kerdraon, Jean-Sébastien Frenel, Judith Raimbourg, Mario Campone, Maria Fe Paz, François Bocquet

“…While the ESME database served as a benchmark, its reliance on single manual data entry without secondary review introduces potential inaccuracies, suggesting the observed performance reflects close alignment between human and algorithmic extractions rather than absolute accuracy. …”
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