International Journal of Science and Engineering Invention <p>The International Journal of Science and Engineering Invention (IJSEI) is an international open access multidisciplinary peer-reviewed journal and this leading international journal publishes scholarly papers and review articles on all aspects of the science, engineering, information technology, medical sciences and social studies of science.&nbsp;The principal mission of the journal is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.</p> <p><strong style="font-family: Arial; font-size: 18px; font-weight: 400; color: #333333;">IJSEI Publication Ethics Statement</strong></p> <p>IJSE takes the responsibility to enforce a rigorous peer-review together with strict ethical policies and standards to ensure to add high quality scientific works to the field of scholarly publication. Unfortunately, cases of plagiarism, data falsification, inappropriate authorship credit, and the like, do arise. IJSEI takes such publishing ethics issues very seriously and our editors are trained to proceed in such cases with a zero tolerance policy. To verify the originality of content submitted to our journals, we use iThenticate to check submissions against previous publications.</p> <p><strong style="font-family: Arial; font-size: 18px; font-weight: 400; color: #333333;">Copyright / Open Access</strong></p> <p><strong>Open Access</strong> - free for readers, with article processing charges (APC) paid by authors or their institutions.</p> <p><strong>Rapid publication:</strong> manuscripts are peer-reviewed and a first decision provided to authors approximately 20 days after submission; acceptance to publication is undertaken in 10 days.</p> <p><strong>Recognition of Reviewers: </strong>reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any IJSEI journal, in appreciation of the work done.</p> <p>Articles published in <em>IJSEI</em> will be Open-Access articles distributed under the terms and conditions of the Creative Commons Attribution License (CC BY). The copyright is retained by the author(s). IJSEI will insert the following note at the end of the published text:</p> <p>© 2018 by the authors; licensee IJSEI. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution License (</p> International Scientific Invention Journals en-US International Journal of Science and Engineering Invention 2455-4286 Magnetic Flow Scattering in Ferrite Rings <p>It is shown that, contrary to the prevailing opinion, the scattering of the magnetic flux, even in ferrites with high magnetic permeability, is very large. A description of the technique for measuring the parameters of ferrites and inductors on ferrite rings is given. The results of experimental measurements of parameters for various grades of ferrites and various values of magnetic permeability are presented. Recommendations on the design of high-frequency transformers and inductors on ferrite rings are given.</p> Andrew Chubykalo Augusto Espinoza Viktor Kuligin ##submission.copyrightStatement## 2019-01-02 2019-01-02 5 01 01 to 07 01 to 07 10.23958/ijsei/vol05-i01/126 Oil Demand Forecasting in Malaysia in Transportation Sector Using Artificial Neural Network <p>Energy industry in Malaysia is one of critical sector that plays a major role in contributing the nation economic and industrial growth. A forecasting model is required to be developed to provide the oil demand forecast in transportation sector. This research analyses different forecasting models including Artificial Neural Network (ANN) model to predict the future oil demand in transportation sector in Malaysia. In order to select the best forecasting model, the model validation is done using the error analysis techniques. Based on the model validation result, it is found that the Artificial Neural Network (Multivariate) model gives the least error in all the error analysis techniques. The model forecast that the oil demand in transportation sector in Malaysia for the year 2020, 2025 and 2030 would be 559.44, 581.779 and 609.941 kg of oil equivalent respectively.</p> Ali Mubarak Al-Qahtani Jebaraj S. ##submission.copyrightStatement## 2019-01-02 2019-01-02 5 01 08 to 15 08 to 15 10.23958/ijsei/vol05-i01/132 Support to IS/IT in Auxiliary Machinery Exploitation Mangement at the Open-Pit Coal Mine <p>With the aim of management improvement, availability and readiness increase and decrease in costs of the exploitation system (operative work and maintenance) of vehicles and operative machines at the open-pit coal mine, the modern business process access with the support of information system and technology was developed and applied (IS/IT). In the operation, the process of exploitation system with the respective software support and Reports development is displayed. IS/IT are designed regarding business processes, monitoring, analysis and management (planning, organizing, management and control) of the exploitation system</p> Milos Ivanovic, MSc Dr Sveta Mirkovic ##submission.copyrightStatement## 2019-01-17 2019-01-17 5 01 16 to 25 16 to 25 10.23958/ijsei/vol05-i01/115