A novel architecture design for internet of things by Tuğrul Çavdar, Ercüment Öztürk

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Electrical Characterization of TiO2 Insulator Based Pd / TiO2 / Si MIS Structure Deposited by Sol-Gel Process by Kumar Shubham, R.U. Khan

“…Electrical characterization of a Pd / TiO2 / Si MIS structure has been reported in this paper. The TiO2 layer has been deposited on n-Si substrate by spin coating sol-gel process using Titanium Tetraisopropoxide [Ti(OC3H7)4]. …”
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Vector Autoregressive Hierarchical Hidden Markov Models for Extracting Finger Movements Using Multichannel Surface EMG Signals by Nebojša Malešević, Dimitrije Marković, Gunter Kanitz, Marco Controzzi, Christian Cipriani, Christian Antfolk

“…The obtained results show that using hidden semi-Markov models as the top layer, instead of the hidden Markov models, ranks top in all the relevant metrics among the tested combinations. …”
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Enhancing Sentiment Analysis with a CNN-Stacked LSTM Hybrid Model by Shao Shuaijie

“…This model uses CNN for its advantage of capturing local features in the sequence after the embedding process, and LSTM for its advantage of capturing long-term dependencies in such sequential data after CNN layer. …”
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Deepwater Renewal in a Large, Deep Lake (Lake Geneva): Identifying and Quantifying Winter Cooling Processes Using Heat Budget Decomposition by N. Peng, U. Lemmin, F. Mettra, R. S. Reiss, D. A. Barry

“…However, differential cooling between shallow and deep waters can produce density currents that flow into deep layers. In order to determine the role that these two cooling processes play in deepwater renewal, field measurements and 3D numerical modeling were combined to investigate heat content dynamics in Lake Geneva's large basin, the Grand Lac (maximum depth 309 m), during an exceptionally cold air spell in early 2012 where complete overturning had been reported. …”
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Combined L-Band Polarimetric SAR and GPR Data to Develop Models for Leak Detection in the Water Pipeline Networks by Yuyao Zhang, Hongliang Guan, Fuzhou Duan

“…We evaluate multiple linear regression (MLR), random forest (RF), and multi-layer perceptron neural network (MLPNN) models for their ability to predict the SSRDC values using the selected features. …”
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Multi-physics ensemble modelling of Arctic tundra snowpack properties by G. J. Woolley, N. Rutter, L. Wake, V. Vionnet, C. Derksen, R. Essery, P. Marsh, R. Tutton, B. Walker, M. Lafaysse, D. Pritchard

“…To improve the simulation of profiles of density and SSA, parameterisations of snow physical processes that consider the effect of high wind speeds, the presence of basal vegetation, and alternate thermal conductivity formulations were implemented into an ensemble version of the Soil, Vegetation, and Snow version 2 (SVS2-Crocus) land surface model, creating Arctic SVS2-Crocus. …”
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Peridynamic Model of Vibrations in a Two-Dimensional Periodic Structure by Yuldasheva, A.V.

“…Unlike classical continuum mechanics, where the linearized model is described by partial differential equations, the peridynamic model leads to an integro-differential equation with a non integrable kernel. …”
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A Method to Simulate the Migration and Accumulation of Hydrocarbon with Analogue Modeling by Jian Cui, Dong Jia, Hongbin Wang, Hongwei Yin, Yanjun Wang, Delong Ma, Wujun Wu, Ziyan Jing, Xiaogen Fan, Li Shen, Xiaojun Wu, Wenqiang Liu, Xiulei Yang

“…A NaI-saturated layered sandbox model was constructed with an along-strike basal discontinuity, which during compression allowed a simple anticline with doubly verging reverse faults to form. …”
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Photoacclimation and Photoadaptation Sensitivity in a Global Ocean Ecosystem Model by Charles A. Stock, John P. Dunne, Jessica Y. Luo, Andrew C. Ross, Nicolas VanOostende, Niki Zadeh, Theresa J. Cordero, Xiao Liu, Yi‐Cheng Teng

“…Abstract Chlorophyll underpins ocean productivity yet simulating chlorophyll across biomes, seasons and depths remains challenging for earth system models. Inconsistencies are often attributed to misrepresentation of the myriad nutrient supply, growth and loss processes that govern phytoplankton biomass. …”
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A Study on Optimal Data Bandwidth of Recurrent Neural Network–Based Dynamics Model for Robot Manipulators by Seungcheon Shin, Minseok Kang, Jaemin Baek

“…In this article, a recurrent neural network (RNN)‐based learning method is propdosed for achieving the overall dynamic model of robot manipulators. Several sections, e.g., data acquisition, learning model, hidden layers, nodes, activation function, and data bandwidth, are designed to make the RNN‐based learning method establish the overall dynamic model of the robot manipulators. …”
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Spring phenology in photosynthesis control and modeling for a temperate bog by Hongxing He, Tim Moore, Peter Lafleur, Oliver Sonnentag, Elyn Humphreys, Mousong Wu, Nigel Roulet

“…Model simulations incorporating the new phenology subroutine for two vegetation layers (shrubs and mosses) show improved agreement with the daily EC-derived GPP. …”
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Using the SWAT model to characterise the water regime of soils in agrolandscapes by E. V. Shein, A. G. Bolotov, A. V. Dembovetskiy, D. Yu. Usenko, N. A. Kharkhardinov, Yu. I. Vernyuk

“…Some examples are given in the article, which demonstrate that modeled data correspond well with experimental data on soil moisture dynamics in several points of agrolandscape for 3 depth levels, reflecting surface, deep (at groundwater level) and middle layers of soil profile, i. e. 10–20, 50–60 and 90–100 cm. …”
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Interpretive structural modeling of the implementation of the comprehensive scientific map of Iran by Bahram Akbari, Abouzar Alidadi Talkhestani, Mohammad Reza Navab Esfahani, Meysam Alipour

“…The statistical population of the research includes experts and officials implementing the country's scientific map, from which a sample size of 20 people was purposefully selected, and their opinions were used in responding to the structural-interpretive equations.Findings: The final model has been developed in two layers and consists of 5 dimensions, including "human factors," "infrastructural factors," "management factors," "process factors," and "external factors." …”
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Research on the elastoplastic localized damage constitutive model of raw coal by Susheng WANG, Shengqi YANG, Qiang ZHANG, Zhennan ZHU

“…The growing need for energy and resources is driving the search and extraction of mineral resources from deeper earth layers, resulting in significant nonlinear mechanical responses in rock masses under high ground stress. …”
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Effect of tightening torque on the mechanical performance and damage form of hybrid bonded/bolted joints by SHEN Jinyi, HU Weixin, ZHANG Tianyu, HU Junshan, LIAO Wenhe, TIAN Wei, SHEN Ye

“…The damage initiation and propagation of the composite material were judged using the three-dimensional Linde criterion. The cohesive force model was used to simulate the damage failure process of the adhesive layer. …”
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Design and evaluation of main terminal connectors for power modules in the service environment of high-speed EMUs by ZENG Xianghao, ZHANG Xiao, HE Guanqiang, WU Shuzhou

“…The analysis obtained using the energy-based Darveaux model more closely aligns with the degradation process of the solder layers in the main terminal structure of IGBTs. …”
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Application of Deep Learning to Identify Flutter Flight Testing Signals Parameters and Analysis of Real F-18 Flutter Flight Test Data by Sami Abou-Kebeh, Roberto Gil-Pita, Manuel Rosa-Zurera

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Accurate prediction of damage depth of multi-story structural footings with Matlab implementation by Ang LI, Weidong WANG, Qian MOU, Feng WANG, Zhenghe MA, Lei ZHAO, Gang HUANG, Yonggen ZHOU, Shengqi TIAN

“…The results show that ① most of the working conditions in the calculation of the damage depth of multilayer structure base plate need to be solved by Taylor expansion and quadratic equation several times, and the manual calculation process is long and complicated, which is very likely to lead to deviations in the calculation results; ② by comparing the maximum damage depth of the base plate under the same working condition with the same parameters by manual calculation and machine calculation (Matlab built-in function), it can be seen that with the increase of the number of layers of the base plate, the manual solution process leads to the maximum damage depth of the base plate due to the repeated application of Taylor expansion. ③ The main interface of the software contains the number of layers, layer thickness, mechanical parameters, input boxes, calculation buttons, etc., which can quickly and intelligently identify the working conditions and calculate the maximum depth of damage of the bottom slab and the maximum depth of damage from the mining face to the bottom slab. ④ will be a mine of flat coal related lithological mechanical parameters into the software solution, by comparing and analyzing the five-layer structure of the maximum depth of destruction of the base plate theoretical value, fitting value, measured value and software value can be seen, the theoretical value and measured results deviation of 0.57 m, software value and measured value of the difference of 0.14 m, the results of multi-layer calculations under the software calculations are more in line with the actual needs, can be for the bottom of the board of the prevention and control of water hazards and safety of mining to provide a reliable technology parameter.…”
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DeSPPNet: A Multiscale Deep Learning Model for Cardiac Segmentation by Elizar Elizar, Rusdha Muharar, Mohd Asyraf Zulkifley

“…By processing features at different spatial resolutions, the multiscale densely connected layer in the form of the Pyramid Pooling Dense Module (PPDM) helps the network to capture both local and global context, preserving finer details of the cardiac structure while also capturing the broader context required to accurately segment larger cardiac structures. …”
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