Machine learning based QSAR and Molecular Dynamics simulations in the structural design and mechanism of action of imidazole derivatives with anti-melanoma activity by Rosalvo Ferreira de Oliveira Neto, Sérgio Ruschi Bergamachi Silva, Cintia Emi Yanaguibashi Leal, Edilson Beserra de Alencar Filho

“…The QSAR model allows for the design and prediction of nine new analogues with favourable predicted IC50 values. …”
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STEEL WIRE ROPE CORE RUBBER CONVEYOR BELT GENERALIZED CONSTITUTIVE MODELING AND EXPERIMENTAL VALIDATION by CHEN HongYue, BAI YangXi, DENG WenHao, MAO Jun

“…The experiments of the dynamic strain loading on the steel wire and the rubber base body are performed respectively,and the parameters for the two constitutive models are obtained,and the prediction of the visco-elastic mechanics characteristics by applying the generalized constitutive model is performed. …”
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Analysis and Design of an Optimal Noise Estimation and Cancellation Filter in Wireline Communication by Mohammad Emami Meybodi, Hossein Shakiba, Ali Sheikholeslami

“…This paper presents a comprehensive study of noise prediction and cancellation techniques in high-speed wireline communication systems. …”
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New Prospective for the Management of Low-Risk Pulmonary Embolism: Prognostic Assessment, Early Discharge, and Single-Drug Therapy with New Oral Anticoagulants by Alessandro Squizzato

“…Several parameters have been proposed and investigated to identify low-risk PE: clinical prediction rules, imaging tests, and laboratory markers of right ventricular dysfunction or injury. …”
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Enhanced Dynamic Model of Pneumatic Muscle Actuator with Elman Neural Network by Alexander Hošovský, Ján Piteľ, Kamil Židek

“…Recurrent neural network was preferred over feedforward type due to its better long-term prediction capabilities well suited for simulation use of the model. …”
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The Magical World of Disney: building relationships with clients from the brand personality by Gabriela Nobre Dias, Gisela Demo, Fernanda Scussel

“…Brand personality, the second-order factor, was formed by first-order factors (Credibility, Joy, Sophistication, Audacity and Sensitivity), all of them with positive effects on customer relationship perception. The prediction was 29%, considered a great effect. Hence, we confirm the relation between brand personality and relationship perception and the Credibility dimension as the main driver of long-term relationships in the T&H sector. …”
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An Elliptic Curve Based Schnorr Cloud Security Model in Distributed Environment by Vinothkumar Muthurajan, Balaji Narayanasamy

“…The HCSA-based auditing improves the malicious activity prediction during the data transfer. The duplication in the cloud server degrades the performance of EC-Schnorr based encryption schemes. …”
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Recommendation System with Biclustering by Jianjun Sun, Yu Zhang

“…Specifically, the proposed novel biclustering method is first adopted to obtain local similarity and local prediction. Second, item-based collaborative filtering is used to generate global predictions. …”
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The Intrinsic Experience of Tourism Autobiographical Memory on Environmentally Responsible Behavior: A Self-Expansion Perspective by Junxian Shen, Cora Un In Wong, Hongfeng Zhang, Fanbo Li, Jianhui Chen

“…In addition, the implicit theories of personality moderate the prediction of tourist autobiographical memory on self-expansion. …”
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FBXW7 metabolic reprogramming inhibits the development of colon cancer by down-regulating the activity of arginine/mToR pathways. by Qing Li, Yan Li, Tong Zhou, Yong Zhang, Huiyu Li, Fajia Yuan, Yanghui Bi

“…The research findings provide a theoretical foundation for the prognostic prediction and therapeutic planning of CRC based on metabolic reprogramming.…”
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STUDY ON RELIABILITY DISTRIBUTION MODELS OF FATIGUE LIFE OF ANTI-VIBRATION RUBBER MATERIALS (MT) by WANG XiaoLi, PENG XiaoYang, LIU XiangNan, DUAN XiaoCheng, XU Wei

“…Based on the test data of uniaxial tensile fatigue experiment of rubbers, the cumulative distribution function and probability density function of residual fatigue life corresponding to two typical probability distribution models of three parameters Weibull distribution（3 PWD） and logarithmic normal distribution（LND） were derived and applied to the prediction of residual life reliability, in order to determine the minimum required under different probability distribution model of sample number and working condition number. …”
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State-of-Charge Estimation and Active Cell Pack Balancing Design of Lithium Battery Power System for Smart Electric Vehicle by Z. C. Gao, C. S. Chin, W. D. Toh, J. Chiew, J. Jia

“…The strong tracking cubature extended Kalman filter (STCEKF) gave an accurate SOC prediction compared to other Kalman-based filter algorithms. …”
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Influence of Humidity State on Dynamic Resilient Modulus of Subgrade Soils: Considering Repeated Wetting-Drying Cycles by Gongfeng Xin, Anshun Zhang, Zijian Wang, Quanjun Shen, Minghao Mu

“…The main results are as follows: (i) the MR decreased with the increase of deviator stress and rose with the growth of confining pressure; (ii) the humidification effect caused by the increase in moisture content attenuated the MR; (iii) the accumulation of WD cycles damaged the MR; however the decline rate was gradually retarded until it was stable with WD cycles 5 times; (iv) the satisfactory prediction model for the MR of subgrade soils considering WD cycles was proposed and verified. …”
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Wavelet Domain Multidictionary Learning for Single Image Super-Resolution by Xiaomin Wu, Jiulun Fan, Jian Xu, Yanzi Wang

“…In order to alleviate the uncertainty in HF detail prediction, the HR and LR images are usually decomposed into 4 subbands after 1-level discrete wavelet transformation (DWT), including an approximation subband and three detail subbands. …”
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Comparison of mechanical properties of recent and 400-year-old European larch wood by Enej Lipovec Zupanc, Gorazd Fajdiga, Miha Humar

“…Due to its repeated and widespread use in construction, the prediction of mechanical properties and their change over time is also very well known, as the overall safety of all buildings also depends on it. …”
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Efficient Lane Detection Technique Based on Lightweight Attention Deep Neural Network by Zhiting Yao, Xiyuan Chen

“…The proposed network integrates fine details captured by local interaction of pixels at high resolution into global contexts at low resolution, computing dense feature maps for prediction task. Based on the attributes of disparate feature resolution characteristics, different attention mechanisms are adopted to guide the network to effectively exploit the model parameters. …”
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Fault Diagnosis Method for Bearing of High-Speed Train Based on Multitask Deep Learning by Jia Gu, Ming Huang

“…Then, based on the operating condition identification and multitask deep learning, the bearing temperature prediction model is constructed. In addition, according to statistical quality control theory, the difference between the value predicted by the model and the real value is used to diagnose the anomaly of the bearing temperature of the high-speed train. …”
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Forecasting slipform labor productivity in the construction of reinforced concrete chimneys by Şahin Tolga Güvel

“…The aim of this study is to identify the factors that influence productivity in the construction of reinforced concrete chimney (RCC) and to develop a predictive model for forecasting slipform labor productivity in RCC projects. …”
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A Customized Deep Neural Network Approach to Investigate Travel Mode Choice with Interpretable Utility Information by Zhengchao Zhang, Congyuan Ji, Yineng Wang, Yanni Yang

“…Validated by a practical city-wide multimodal traffic dataset in Beijing, our model significantly outperforms the random utility models and simple fully connected neural network in terms of the prediction accuracy. Besides the comparison of the predictive power, we also present the interpretability of the proposed model.…”
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The Use of Machine Learning Approaches for the Diagnosis of Acute Appendicitis by Omer F. Akmese, Gul Dogan, Hakan Kor, Hasan Erbay, Emre Demir

“…Retrospective clinical records were analyzed with predictive data mining models. The predictive success of the models obtained by various machine learning algorithms was compared. …”
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