Call for Participation - 7th International Conference on Computer Science, Engineering and Information Technology (CSEIT 2020)
September 26-27, 2020, Copenhagen, Denmark
Call for Participation
We invite you to join us in Copenhagen, Denmark on September 26-27, 2020, for 7th International Conference on Computer Science, Engineering and Information Technology (CSEIT 2020)
The conference will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Computer Science, Engineering and Information Technology. The Conference looks for significant contributions to all major fields of the Computer Science and Information Technology in theoretical and practical aspects. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
Highlights of CSEIT 2020 include:
Registration Participants
Non-Author / Co-Author/ Simple Participants (no paper)
250 Euros (With proceedings)
For registration and details mail: cseit@cseit2020.org or cseitsecretary@yahoo.com
Accepted Papers
Learning for E-Learning
Carsten Lecon1 and Marc Hermann2, 1Department of Computer Science, Media Computer Science, Aalen University, Germany and 2Department of Computer Science, User Experience, Aalen University, Germany
Magnetic Resonance Image Classification of Major Depression Disorder Based on Deep Learning
Yu Wang, Changyang Fu, Chongchong Yu, Weijun Su, School of Computer and Information Engineering, Beijing Technology and Business University, Beijing, China
The Novel Mobile ECG Sensor with Wireless Power Transmission for UNTACH Health Monitoring
Jin-Chul Heo, Eun-Bin Park, Chan-Il Kim, Hee-Joon Park and Jong-Ha Lee, Department of Biomedical Engineering, School of Medicine,Keimyung University, Daegu, Korea
Factors Influencing Traders’ Continuous Usage Intention to E-transaction Cards in Wholesale Markets of Agriproducts: An Empirical Case Study in China
Xuechao Sui1 and Xianhui Geng2, 1School of Economics, Hefei University of Technology, Hefei, P.R. China, 2College of Economics and Management, Nanjing Agricultural University, Nanjing, P.R. China
Evaluating the impact of different types of crossover and selection methods on the convergence of 0/1 Knapsack using Genetic Algorithm
Waleed Bin Owais, Iyad W. J. Alkhazendar, and Dr.Mohammad Saleh, Department of Computer Science and Engineering, Qatar University, Doha
VIRTFUN: Function Offload Methodology to Virtualized Environment
Carlos A Petry, University of Campinas, Brazil
COSM: Controlled Over-sampling Method. A Methodological Proposal to Overcome the Class Imbalance Problem in Data Mining
Gaetano Zazzaro, Software Development, Information Management and HPC Lab, CIRA (Italian Aerospace Research Centre), Capua (CE), Italy
A Process for Complete Autonomous Software Display Validation And Testing (Using A Car-cluster)
Malobika Roy Choudhury, Innovation and Technology, SAP Labs India Pvt Lmt., Bengaluru, Karnataka, India
Analysis of the Displacement of Terrestrial Mobile Robots in Corridors Using Paraconsistent Annotated Evidential Logic Eτ
Flávio Amadeu Bernardini1, Marcia Terra da Silva1, Jair Minoro Abe1, Luiz Antonio de Lima1 and Kanstantsin Miatluk2, 1Graduate Program in Production Engineering Paulista University, Sao Paulo, Brazil, 2Bialystok University of Technology, Bialystok, Poland
A Study on the Minimum Requirements for the On-line, Efficient and Robust Validation of Neutron Detector Operation and Monitoring of Neutron Noise Signals using Harmony Theory Networks
Tatiana Tambouratzisa, Laurent Panterab and Petr Stulikc, aDepartment of Industrial Management & Technology, University of Piraeus, Piraeus 185 34, Greece, bLaboratoire des Programmes Expérimentaux et des Essais en Sûreté, CEA/DES/ IRESNE/DER/SPESI/LP2E/, Cadarache, F-13108 Saint-Paul-Lez-Durance, France, cDiagnostics and Radiation Safety Department, ÚJV Řež a.s., Hlavní 130, Řež, 250 68 Husinec
Penalized Bootstrapping for Reinforcement Learning in Robot Control
Christopher Gebauer and Maren Bennewitz, Humanoid Robots Lab, University of Bonn, Bonn, Germany
Deep Reinforcement Learning for Navigation in Cluttered Environments
Peter Regier, Lukas Gesing, and Maren Bennewitz, Humanoid Robots Lab, University of Bonn, Bonn, Germany
New Hybrid Artificial Intelligent Models Basedon Optimized-support Vector Machine and Locallylinear Neuro-fuzzy for the Supplier Assessment Problem
Hasti Mirhadi and Ali Rafiee, Department of Mathematics, Islamic Azad University, Tehran, Iran
Aerodynamic modeling of 3D compressor blades based on XGBoost
Shurong Hao1, Mingming Zhang2, 1School of Mathematics, Faculty of Science, Beijing University of Technology, Beijing 100124, China, 2School of Energy and Power, Beihang University, Beijing 100191, China
Sequential Minimal Optimization for One-classslab Support Vector Machine
Sourin Chakrabarti, Aashutosh Khandelwal and Prof. O.P. Vyas, IIIT Allahabad, India
Non-negative Matrix Factorization of Story W
