DATA MODELING AND SIMULATION FOR BIOMEDICAL APPLICATIONS CONFERENCE


Data Modeling and Simulation for Biomedical Applications Conference is one of the leading research topics in the international research conference domain. Data Modeling and Simulation for Biomedical Applications is a conference track under the Biomedical and Biological Engineering Conference which aims to bring together leading academic scientists, researchers and research scholars to exchange and share their experiences and research results on all aspects of Biomedical and Biological Engineering.

internationalscience.net provides a premier interdisciplinary platform for researchers, practitioners and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of (Biomedical and Biological Engineering).

Data Modeling and Simulation for Biomedical Applications is not just a call for academic papers on the topic; it can also include a conference, event, symposium, scientific meeting, academic, or workshop.

You are welcome to SUBMIT your research paper or manuscript to Data Modeling and Simulation for Biomedical Applications Conference Track will be held at “Biomedical and Biological Engineering Conference in Paris, France in November 2019” - “Biomedical and Biological Engineering Conference in London, United Kingdom in January 2020” - “Biomedical and Biological Engineering Conference in Tokyo, Japan in March 2020” - “Biomedical and Biological Engineering Conference in Amsterdam, Netherlands in May 2020” - “Biomedical and Biological Engineering Conference in Istanbul, Turkey in June 2020” - “Biomedical and Biological Engineering Conference in Stockholm, Sweden in July 2020” - “Biomedical and Biological Engineering Conference in Zürich, Switzerland in September 2020” - “Biomedical and Biological Engineering Conference in New York, United States in November 2020” .

Data Modeling and Simulation for Biomedical Applications is also a leading research topic on Google Scholar, Semantic Scholar, Zenedo, OpenAIRE, BASE, WorldCAT, Sherpa/RoMEO, Elsevier, Scopus, Web of Science.

INTERNATIONAL BIOMEDICAL AND BIOLOGICAL ENGINEERING CONFERENCE

NOVEMBER 21 - 22, 2019
PARIS, FRANCE

  • Abstracts/Full-Text Paper Submission Deadline March 14, 2019
  • Notification of Acceptance/Rejection Deadline March 28, 2019
  • Final Paper and Early Bird Registration Deadline October 21, 2019
  • CONFERENCE CODE: 18BBE11FR
  • One Time Submission Deadline Reminder

INTERNATIONAL BIOMEDICAL AND BIOLOGICAL ENGINEERING CONFERENCE

JANUARY 21 - 22, 2020
LONDON, UNITED KINGDOM

  • Abstracts/Full-Text Paper Submission Deadline March 14, 2019
  • Notification of Acceptance/Rejection Deadline March 28, 2019
  • Final Paper and Early Bird Registration Deadline December 19, 2019
  • CONFERENCE CODE: 20BBE01GB
  • One Time Submission Deadline Reminder

INTERNATIONAL BIOMEDICAL AND BIOLOGICAL ENGINEERING CONFERENCE

MARCH 26 - 27, 2020
TOKYO, JAPAN

  • Abstracts/Full-Text Paper Submission Deadline March 14, 2019
  • Notification of Acceptance/Rejection Deadline March 28, 2019
  • Final Paper and Early Bird Registration Deadline February 27, 2020
  • CONFERENCE CODE: 20BBE03JP
  • One Time Submission Deadline Reminder

INTERNATIONAL BIOMEDICAL AND BIOLOGICAL ENGINEERING CONFERENCE

MAY 13 - 14, 2020
AMSTERDAM, NETHERLANDS

  • Abstracts/Full-Text Paper Submission Deadline March 14, 2019
  • Notification of Acceptance/Rejection Deadline March 28, 2019
  • Final Paper and Early Bird Registration Deadline April 14, 2020
  • CONFERENCE CODE: 20BBE05NL
  • One Time Submission Deadline Reminder

INTERNATIONAL BIOMEDICAL AND BIOLOGICAL ENGINEERING CONFERENCE

JUNE 25 - 26, 2020
ISTANBUL, TURKEY

  • Abstracts/Full-Text Paper Submission Deadline March 14, 2019
  • Notification of Acceptance/Rejection Deadline March 28, 2019
  • Final Paper and Early Bird Registration Deadline May 26, 2020
  • CONFERENCE CODE: 20BBE06TR
  • One Time Submission Deadline Reminder

INTERNATIONAL BIOMEDICAL AND BIOLOGICAL ENGINEERING CONFERENCE

JULY 14 - 15, 2020
STOCKHOLM, SWEDEN

  • Abstracts/Full-Text Paper Submission Deadline March 14, 2019
  • Notification of Acceptance/Rejection Deadline March 28, 2019
  • Final Paper and Early Bird Registration Deadline June 11, 2020
  • CONFERENCE CODE: 20BBE07SE
  • One Time Submission Deadline Reminder

INTERNATIONAL BIOMEDICAL AND BIOLOGICAL ENGINEERING CONFERENCE

SEPTEMBER 15 - 16, 2020
ZÜRICH, SWITZERLAND

  • Abstracts/Full-Text Paper Submission Deadline March 14, 2019
  • Notification of Acceptance/Rejection Deadline March 28, 2019
  • Final Paper and Early Bird Registration Deadline August 13, 2020
  • CONFERENCE CODE: 20BBE09CH
  • One Time Submission Deadline Reminder

INTERNATIONAL BIOMEDICAL AND BIOLOGICAL ENGINEERING CONFERENCE

NOVEMBER 05 - 06, 2020
NEW YORK, UNITED STATES

  • Abstracts/Full-Text Paper Submission Deadline March 14, 2019
  • Notification of Acceptance/Rejection Deadline March 28, 2019
  • Final Paper and Early Bird Registration Deadline October 05, 2020
  • CONFERENCE CODE: 20BBE11US
  • One Time Submission Deadline Reminder

Biomedical and Biological Engineering Conference Call For Papers are listed below:

Previously Published Papers on "Data Modeling and Simulation for Biomedical Applications Conference"

  • Improved Predictive Models for the IRMA Network Using Nonlinear Optimisation
    Authors: Vishwesh Kulkarni, Nikhil Bellarykar, Keywords: Synthetic gene network, network identification, nonlinear modeling, optimization. DOI:10.5281/zenodo.1474948 Abstract: Cellular complexity stems from the interactions among thousands of different molecular species. Thanks to the emerging fields of systems and synthetic biology, scientists are beginning to unravel these regulatory, signaling, and metabolic interactions and to understand their coordinated action. Reverse engineering of biological networks has has several benefits but a poor quality of data combined with the difficulty in reproducing it limits the applicability of these methods. A few years back, many of the commonly used predictive algorithms were tested on a network constructed in the yeast Saccharomyces cerevisiae (S. cerevisiae) to resolve this issue. The network was a synthetic network of five genes regulating each other for the so-called in vivo reverse-engineering and modeling assessment (IRMA). The network was constructed in S. cereviase since it is a simple and well characterized organism. The synthetic network included a variety of regulatory interactions, thus capturing the behaviour of larger eukaryotic gene networks on a smaller scale. We derive a new set of algorithms by solving a nonlinear optimization problem and show how these algorithms outperform other algorithms on these datasets.
  • 3D CFD Modelling of the Airflow and Heat Transfer in Cold Room Filled with Dates
    Authors: Zina Ghiloufi, Tahar Khir, Keywords: Numerical simulation, CFD, k-ω (SST), cold room, dates, cooling rate. DOI:10.5281/zenodo.1474827 Abstract: A transient three-dimensional computational fluid dynamics (CFD) model is developed to determine the velocity and temperature distribution in different positions cold room during pre-cooling of dates. The turbulence model used is the k-ω Shear Stress Transport (SST) with the standard wall function, the air. The numerical results obtained show that cooling rate is not uniform inside the room; the product at the medium of room has a slower cooling rate. This cooling heterogeneity has a large effect on the energy consumption during cold storage.
  • Cardiovascular Modeling Software Tools in Medicine
    Authors: J. Fernandez, R. Fernandez de Canete, J. Perea-Paizal, J. C. Ramos-Diaz, Keywords: Cardiovascular system, Modelica simulation software, physical modeling, teaching tool. DOI:10.5281/zenodo.1132543 Abstract: The high prevalence of cardiovascular diseases has provoked a raising interest in the development of mathematical models in order to evaluate the cardiovascular function both under physiological and pathological conditions. In this paper, a physical model of the cardiovascular system with intrinsic regulation is presented and implemented by using the object-oriented Modelica simulation software tools.  For this task, a multi-compartmental system previously validated with physiological data has been built, based on the interconnection of cardiovascular elements such as resistances, capacitances and pumping among others, by following an electrohydraulic analogy. The results obtained under both physiological and pathological scenarios provide an easy interpretative key to analyze the hemodynamic behavior of the patient. The described approach represents a valuable tool in the teaching of physiology for graduate medical and nursing students among others.
  • Rainfall–Runoff Simulation Using WetSpa Model in Golestan Dam Basin, Iran
    Authors: M. R. Dahmardeh Ghaleno, M. Nohtani, S. Khaledi, Keywords: Watershed simulation, WetSpa, stream flow, flood prediction. DOI:10.5281/zenodo.1132499 Abstract: Flood simulation and prediction is one of the most active research areas in surface water management. WetSpa is a distributed, continuous, and physical model with daily or hourly time step that explains precipitation, runoff, and evapotranspiration processes for both simple and complex contexts. This model uses a modified rational method for runoff calculation. In this model, runoff is routed along the flow path using Diffusion-Wave equation which depends on the slope, velocity, and flow route characteristics. Golestan Dam Basin is located in Golestan province in Iran and it is passing over coordinates 55° 16´ 50" to 56° 4´ 25" E and 37° 19´ 39" to 37° 49´ 28"N. The area of the catchment is about 224 km2, and elevations in the catchment range from 414 to 2856 m at the outlet, with average slope of 29.78%. Results of the simulations show a good agreement between calculated and measured hydrographs at the outlet of the basin. Drawing upon Nash-Sutcliffe model efficiency coefficient for calibration periodic model estimated daily hydrographs and maximum flow rate with an accuracy up to 59% and 80.18%, respectively.
  • Causal Modeling of the Glucose-Insulin System in Type-I Diabetic Patients
    Authors: J. Fernandez, N. Aguilar, R. Fernandez de Canete, J. C. Ramos-Diaz, Keywords: Causal modeling, diabetes, glucose-insulin system, diabetes, causal modeling, OpenModelica software. DOI:10.5281/zenodo.1132236 Abstract: In this paper, a simulation model of the glucose-insulin system for a patient undergoing diabetes Type 1 is developed by using a causal modeling approach under system dynamics. The OpenModelica simulation environment has been employed to build the so called causal model, while the glucose-insulin model parameters were adjusted to fit recorded mean data of a diabetic patient database. Model results under different conditions of a three-meal glucose and exogenous insulin ingestion patterns have been obtained. This simulation model can be useful to evaluate glucose-insulin performance in several circumstances, including insulin infusion algorithms in open-loop and decision support systems in closed-loop.
  • Structuring and Visualizing Healthcare Claims Data Using Systems Architecture Methodology
    Authors: Inas S. Khayal, Weiping Zhou, Jonathan Skinner, Keywords: Health informatics, systems thinking, systems architecture, healthcare delivery system, data analytics. DOI:10.5281/zenodo.1131770 Abstract: Healthcare delivery systems around the world are in crisis. The need to improve health outcomes while decreasing healthcare costs have led to an imminent call to action to transform the healthcare delivery system. While Bioinformatics and Biomedical Engineering have primarily focused on biological level data and biomedical technology, there is clear evidence of the importance of the delivery of care on patient outcomes. Classic singular decomposition approaches from reductionist science are not capable of explaining complex systems. Approaches and methods from systems science and systems engineering are utilized to structure healthcare delivery system data. Specifically, systems architecture is used to develop a multi-scale and multi-dimensional characterization of the healthcare delivery system, defined here as the Healthcare Delivery System Knowledge Base. This paper is the first to contribute a new method of structuring and visualizing a multi-dimensional and multi-scale healthcare delivery system using systems architecture in order to better understand healthcare delivery.
  • CompPSA: A Component-Based Pairwise RNA Secondary Structure Alignment Algorithm
    Authors: Ghada Badr, Arwa Alturki, Keywords: Alignment, RNA secondary structure, pairwise, component-based, data mining. DOI:10.5281/zenodo.1340240 Abstract: The biological function of an RNA molecule depends on its structure. The objective of the alignment is finding the homology between two or more RNA secondary structures. Knowing the common functionalities between two RNA structures allows a better understanding and a discovery of other relationships between them. Besides, identifying non-coding RNAs -that is not translated into a protein- is a popular application in which RNA structural alignment is the first step A few methods for RNA structure-to-structure alignment have been developed. Most of these methods are partial structure-to-structure, sequence-to-structure, or structure-to-sequence alignment. Less attention is given in the literature to the use of efficient RNA structure representation and the structure-to-structure alignment methods are lacking. In this paper, we introduce an O(N2) Component-based Pairwise RNA Structure Alignment (CompPSA) algorithm, where structures are given as a component-based representation and where N is the maximum number of components in the two structures. The proposed algorithm compares the two RNA secondary structures based on their weighted component features rather than on their base-pair details. Extensive experiments are conducted illustrating the efficiency of the CompPSA algorithm when compared to other approaches and on different real and simulated datasets. The CompPSA algorithm shows an accurate similarity measure between components. The algorithm gives the flexibility for the user to align the two RNA structures based on their weighted features (position, full length, and/or stem length). Moreover, the algorithm proves scalability and efficiency in time and memory performance.
  • Experimental Correlation for Erythrocyte Aggregation Rate in Population Balance Modeling
    Authors: Erfan Niazi, Marianne Fenech, Keywords: Red blood cell, Rouleaux, microfluidics, image processing, population balance modeling. DOI:10.5281/zenodo.1129964 Abstract: Red Blood Cells (RBCs) or erythrocytes tend to form chain-like aggregates under low shear rate called rouleaux. This is a reversible process and rouleaux disaggregate in high shear rates. Therefore, RBCs aggregation occurs in the microcirculation where low shear rates are present but does not occur under normal physiological conditions in large arteries. Numerical modeling of RBCs interactions is fundamental in analytical models of a blood flow in microcirculation. Population Balance Modeling (PBM) is particularly useful for studying problems where particles agglomerate and break in a two phase flow systems to find flow characteristics. In this method, the elementary particles lose their individual identity due to continuous destructions and recreations by break-up and agglomeration. The aim of this study is to find RBCs aggregation in a dynamic situation. Simplified PBM was used previously to find the aggregation rate on a static observation of the RBCs aggregation in a drop of blood under the microscope. To find aggregation rate in a dynamic situation we propose an experimental set up testing RBCs sedimentation. In this test, RBCs interact and aggregate to form rouleaux. In this configuration, disaggregation can be neglected due to low shear stress. A high-speed camera is used to acquire video-microscopic pictures of the process. The sizes of the aggregates and velocity of sedimentation are extracted using an image processing techniques. Based on the data collection from 5 healthy human blood samples, the aggregation rate was estimated as 2.7x103(±0.3 x103) 1/s.
  • Passive Neutralization of Acid Mine Drainage Using Locally Produced Limestone
    Authors: Reneiloe Seodigeng, Malwandla Hanabe, Haleden Chiririwa, Hilary Rutto, Tumisang Seodigeng, Keywords: Acid mine drainage, neutralization, limestone, modeling. DOI:10.5281/zenodo.1339620 Abstract: Neutralisation of acid-mine drainage (AMD) using limestone is cost effective, and good results can be obtained. However, this process has its limitations; it cannot be used for highly acidic water which consists of Fe(III). When Fe(III) reacts with CaCO3, it results in armoring. Armoring slows the reaction, and additional alkalinity can no longer be generated. Limestone is easily accessible, so this problem can be easily dealt with. Experiments were carried out to evaluate the effect of PVC pipe length on ferric and ferrous ions. It was found that the shorter the pipe length the more these dissolved metals precipitate. The effect of the pipe length on the hydrogen ions was also studied, and it was found that these two have an inverse relationship. Experimental data were further compared with the model prediction data to see if they behave in a similar fashion. The model was able to predict the behaviour of 1.5m and 2 m pipes in ferric and ferrous ion precipitation.
  • Development of a Harvest Mechanism for the Kahramanmaraş Chili Pepper
    Authors: O. E. Akay, E. Güzel, M. T. Özcan, Keywords: Kinematic simulation, four bar linkage, harvest mechanization, pepper harvest. DOI:10.5281/zenodo.1127278 Abstract: The pepper has quite a rich variety. The development of a single harvesting machine for all kinds of peppers is a difficult research topic. By development of harvesting mechanisms, we could be able to facilitate the pepper harvesting problems. In this study, an experimental harvesting machine was designed for chili pepper. Four-bar mechanism was used for the design of the prototype harvesting machine. At the result of harvest trials, 80% of peppers were harvested and 8% foreign materials were collected. These results have provided some tips on how to apply to large-scale pepper Four-bar mechanism of the harvest machine.