Олексій Віталійович Хоменко, Алексей Витальевич Хоменко, Oleksii Vitaliiovych Khomenko et al. · Electronic Sumy State University Institutional Repository (Sumy State University) · 2011
An algorithm for molecular dynamics simulations of graphitic systems using realistic semiempirical interaction potentials of carbon atoms taking into account both short-range and long-range contributions is proposed. Results of the use of the algorithm for a graphite sample are presented. The scalability of the algorithm depending on the system size and the number of processor cores involved in the calculations is analyzed. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/30248
Cited by 0Open access
M. Bouayad, F. Pivot, Mirelis Rasúa López · 2021
Summary Geostatistical methods such as MPS (Multiple points statistics) are able to reproduce complex geological shapes, while honoring well data from so-called training images. However, depending on the complexity MPS technique struggles to achieve realistic reproduction. It is the case for complex geological context as turbiditic systems. To overcome the lack of MPS technique for turbidites, we have developed a new morphing algorithm in order to populate rough 3D geomodels with realistic geological information from 3D training images.
Cited by 0
Mohammed Abdel Razek, Claude Frasson · Communications in computer and information science · 2011
Cited by 1
Gweneth Choi, Albert Molinas · Water Resources Research · 1993
This paper presents a simultaneous solution algorithm for one‐dimensional unsteady flow routing through channel networks. This direct solution algorithm is based on the double‐sweep method and utilizes separate recursion equations for continuity, momentum and energy equations for each of the individual components of channel networks. Through separate recursion equations for each of the components, the new algorithm converts the channel network problem into a single‐channel problem. The new algorithm is utilized in conjunction with a linearized unsteady flow model using full dynamic flow equations. The required computer storage for the coefficient matrix of the whole system is reduced significantly from the 2 N × 2 N matrix to a 2 N × 4 matrix, where N is the number of cross sections used in the computation of flow variables in the channel network. The algorithm presented in this paper provides an efficient and accurate modeling of unsteady flow events through channel networks.
Cited by 59
Asimina Dimara, Christos‐Nikolaos Anagnostopoulos, Stelios Krinidis et al. · Energy Sources Part A Recovery Utilization and Environmental Effects · 2021
No energy-saving actions are implied without maintaining comfortable levels for the residents, as lack of comfort results in stress while threatening the occupants health and well-being. In this paper, a novel algorithm for the estimation of individual metabolic rate and comfort level is introduced. A Genetic Algorithm is utilized for the metabolic rate computation of thermal comfort by eradicating all speculative factors, while creating a personal thermal comfort evaluator. Based on the occupants feedback, the subjective personal factors of thermal comfort (clothing insulation, metabolic rate) are estimated, generating a personal thermal comfort profile. Therefore, the proposed approach can be adapted to create the resident’s personal preferences to achieve accurate comfort level estimation. Ultimately, the proposed algorithm is evaluated against real-life indoor sensor data and users’ feedback, while the experimental results illustrate the efficiency of the proposed system. The Genetic algorithm succeeds 100% in finding the optimal metabolic rate solution while improving the thermal comfort estimation error. The thermal comfort profile is 98% accurate compared to a solution based on ASHRAE tables that has 73% of accuracy.
Cited by 3
A.V. Khomenko, N.V. Prodanov · SHILAP Revista de lepidopterología · 2011
An algorithm for molecular dynamics simulations of graphitic systems using realistic semiempirical interaction potentials of carbon atoms taking into account both short-range and long-range contributions is proposed. Results of the use of the algorithm for a graphite sample are presented. The scalability of the algorithm depending on the system size and the number of processor cores involved in the calculations is analyzed.
Cited by 0Open access
Michał Konarski, Szymon Szomiński, Wojciech Turek · International Journal of Mechanical Engineering and Robotics Research · 2016
Cited by 4
Françoise Beaufays, Mitch Weintraub, Yochai Konig · 1998
This paper summarizes part of SRI’s effort to improve acoustic modeling in the context of the Large Vocabulary Continuous Speech Recognition (LVCSR) project. It concentrates on two problems that are believed to contribute to the large error rates observed with LVCSR databases: (1) the lack of discriminative power of the speech models in the acoustic space, and (2) the discrepancy between the criterion used to train the models (typically frame-level maximum likelihood) and the task expected from the models (word-level recognition). We address the first issue by searching for features that help in narrowing the model distributions, and by proposing a neural-networkbased architecture to combine these features. The neural networks (NNET) are used in association with a set of large Gaussian mixture models (GMM) whose mixture weights are dynamically estimated by the neural networks, for each frame of incoming data. We call the resulting algorithm DYNAMO, for dynamic acoustic modeling. To address the second problem, we propose two discriminative training criteria, both defined at the sentence level. We report preliminary results with the Spanish Callhome database. 1.
Cited by 0
A. E. Avdyushina, А.В. Платонов, Igor Bessmertny · Studies in systems, decision and control · 2023
Cited by 0
Zhengyu Yu, Chun-Chu Liu, Jiajia Shi · Sensors · 2023
The conventional methods for indoor localization rely on technologies such as RADAR, ultrasonic, laser range localization, beacon technology, and others. Developers in the industry have started utilizing these localization techniques in iBeacon systems that use Bluetooth sensors to measure the object's location. The iBeacon-based system is appealing due to its low cost, ease of setup, signaling, and maintenance; however, with current technology, it is challenging to achieve high accuracy in indoor object localization or tracking. Furthermore, iBeacons' accuracy is unsatisfactory, and they are vulnerable to other radio signal interference and environmental noise. In order to address those challenges, our study focuses on the development of error modeling algorithms for signal calibration, uncertainty reduction, and interfered noise elimination. The new error modeling is developed on the Curve Fitted Kalman Filter (CFKF) algorithms. The reliability, accuracy, and feasibility of the CFKF algorithms are tested in the experiments. The results significantly show the improvement of the accuracy and precision with this novel approach for iBeacon localization.
Cited by 3Open access
Bo Chen, Xiaofeng Jia · Geophysics · 2014
ABSTRACT In seismic migration, some structures such as those in subsalt shadow zones are not imaged well. The signal in these areas may be even weaker than the artifacts elsewhere. We evaluated a method to significantly improve the signal-to-noise ratio (S/N) in poorly illuminated areas of the model. We constructed a “phantom” wavefield: an extension of the wavefield to the complex domain. The imaginary wavefield was synchronized with the real wavefield, but it contained only the events relevant to a target region of the model, which was specified using a staining algorithm. The real wavefield interacted with the entire model. However, all structures except for the target were transparent to the imaginary wavefield, which is excited only when the real wavefront arrives at the target structure. The real and the imaginary source wavefields were crosscorrelated with the regular receiver wavefield. The results were revealed in two images: the conventional reverse time migration image and an image of the target region only. Synthetic experiments showed that the S/N of the target structures was improved significantly, with other structures effectively muted.
Cited by 36
Е. И. Шангина · AIP conference proceedings · 2023
Cited by 0
José de Jesús Rubio, Luis Arturo Soriano, Wen Yu et al. · 2014
In this paper, an analytic fuzzy model is introduced for the modeling of the wind turbine behavior. The proposed method is the combination of the analytic and fuzzy models. The fuzzy model is used as a compensator to improve the approximation of the analytic model.
Cited by 1
Oscar N. Bria, Horacio A Villagarcía · 1997
Cited by 0
Mario A. Rotea, Carlos Lana · 2004
This paper describes a robust estimation algorithm (REA) for estimating the device-specific parameters of the so-called spectral Neugebauer model. This physics-based model is used to characterize the response of color printers. The various steps required to use REA are given. A detailed case study, using a high-end color printer, was conducted to evaluate the performance of REA relative to the methods of least squares and total least squares. The main result of the study shows that the model obtained with REA achieves the smallest approximation errors in both spectral and L* a* b* color spaces.
Cited by 3
Panayiotis V. Benos, Alan S. Lapedes, D. S. FIELDS et al. · 2000
We are investigating the rules that govern protein-DNA interactions, using a statistical mechanics based formalism that is related to the Boltzmann Machine of the neural net literature. Our approach is data-driven, in which probabilistic algorithms are used to model protein-DNA interactions, given SELEX and/or phage data as input. In the current report, we trained the network using SELEX data, under the "one-to-one" model of interactions (i.e. one amino acid contacts one base). The trained network was able to successfully identify the wild-type binding sites of EGR and MIG protein families. The predictions using our method are the same or better than that of methods existing in the literature. However our methodology offers the potential to capitalise in quantitative detail, as well as to be used to explore more general model of interactions, given availability of data.
Cited by 27
Robert F. Harrington, Kelly Elder, Roger C. Bales · 1995
Methods for spatially distributed physical modeling of snowmelt are presented. Estimation of snow-water equivalence using regression trees, and distributed snowmelt modeling using iterative clustering are described; these methods are applied to Emerald Lake basin, a 120-ha seasonally snow covered basin in California. Modeled snowmelt and basin discharge substantially agree, yet modeled and observed snow covered area agree only over ~ 65 % of the basin after 5 weeks of melt, highlighting the importance of using snow cover patterns to assess model performance.
Cited by 0
O R Chayka, N S Fokin · REPAIR RECONDITIONING MODERNIZATION · 2018
Aim of the study is to show the pathogenetic importance of myocardial revascularization and to estimate quantitatively effi ciency of the treatment of cardiac allograft vasculopathy after heart transplantation. Materials and methods . 30 percutaneous coronary interventions (PCI) were performed to recipients of heart transplant (8 men and 7 women, aged from 18 to 56 years), who were diagnosed with cardiac allograft vasculopathy by coronary angiography within the time period from 1,5 to 12 years after heart transplantation. Before revascularization and one week after tolerances to physical activity, volume characteristics of the left ventricle were defi ned and diastolic function of heart was estimated. Average term of observation after stenting was 35,5 ± 5,5 months. Results. Tolerance to physical activity (from 76,6 ± 8,5 to 116,9 ± 9,6 W), its duration (from 5,4 ± 2,2 to 8,5 ± 4,1 min) and rate pressure product – RPP (from 198 ± 15 to 247 ± 24 P < 0,05) increased. There was a restoration of diastolic function (Ve/Va from 0,57 ± 0,18 to 1,15 ± 0,2 P < 0,05). Signifi cant distinction in time frames of vasculopathy development, frequency and reasons of repeated interventions depending on age of patients is revealed. In the group of patients younger than 30 years of age (7 patients), the time interval between heart transplantation and vasculopathy development is twice shorter, than in more senior patient group, over 45 years old (8 patients). Young patients showed the expressed tendency to develop stent restenosis (20 coronary interventions). Conclusion. Dynamics in functional condition of the left ventricle as a result of revascularization confi rms the leading role of miocardial ischemia in pathogenesis of transplant insuffi ciency due to vasculopathy. The signifi cant factor infl uencing upon long-term result of coronary intervention is the age of the patient.
Cited by 2Open access
Yuyu Zhu, Yuchen Li, Qinge Wu · Discover Applied Sciences · 2026
To solve the problem on storage and retrieval challenges associated with big data of map, this paper presents an image segmentation- reconstruction algorithm. This algorithm consists of four core steps, i.e., Firstly, it incorporates a semantic association mechanism for image segmentation and develops the corresponding segmentation method. Secondly, it determines the maximum remaining storage capacity of each server unit and performs a matching operation with a preset threshold. Thirdly, it establishes a topological mapping to realize the mapping transformation from the segmented original map to the map to be displayed. Finally, the map is reconstructed by using the location information recorded during the storage of features by image segmentation and mapping relationships. Experimental results show that the accuracy of the proposed reconstruction algorithm can reach 94.35%. To compared with existing image reconstruction algorithms, it not only achieves higher accuracy, faster speed, and stronger anti-interference ability, but also has lower information loss. These advantages of this proposed algorithm can offer an efficient framework for managing large-scale map datasets, thus addressing some critical challenges such as high computational overhead, information loss, and system unreliability in geospatial big data applications.
Cited by 0Open access
Jikun Ye, Humin Lei, Fei Wang et al. · 2010
Based on the input-output data , a multiple-model modeling method is suggested for the complex nonlinear system. Firstly, fuzzy partition is employed to on-line clustering for the input-output data; and then, the least-squares (LS) algorithm is employed to construct the local model for each clustering, and the parameter of each local model is updated by the new data. The proposed algorithm takes advantage of the TSK model, combines the fuzzy partition and multiple-model modeling, and updates on-line the number of the local model and the parameter of each by the input-output data, so as to realize the on-line modeling for the complex nonlinear system. Simulation result shows the effectiveness of the proposed method.
Cited by 1