i-manager's Journal on Computer Science (JCOM)


Volume 5 Issue 3 September - November 2017

Article

Internet of Things Based Smart Hospital System Using Arduino Mega

Dharmendra Singh* , SHISHIR DAS**, SNEHA BAGDE***, BRONNY MASIH****, AKANKSHA SHARMA*****, AKRITI SHARMA******, PARINITA GUPTA*******
*-** Assistant Professor, Electronics and Telecommunication, SSIPMT, Raipur, India.
***-******* Research Scholar, Electronics and Telecommunication, SSIPMT, Raipur, India.
Singh. D., Das. S.K., Bagde. S., Masih. B., Sharma. A., Sharma.A. and Gupta. P. (2017). Internet of Things Based Smart Hospital System using Arduino MegA. i-manager’s Journal on Computer Science, 5(3), 1-5. https://doi.org/10.26634/jcom.5.3.14015

Abstract

Nowadays, Internet of Things (IoT) have become very popular in every field. Even in hospitals, there are various instruments for diagnostic purposes that require accurate measurement along with proper monitoring. Automation is considered to be a way to achieve this. Smart Hospital is a concept of maintaining all the instruments through an online system, so that proper monitoring and accuracy could be obtained. There are various sensors that have been already developed to perform the same operation. All these sensors are connected to individual instruments, in order to achieve proper communication between them. In medical or healthcare system, data is considered to be more sensitive, so it is the main necessity of the system to provide security as well as privacy to the data. Since all the vital patient records and doctors' data are stored in the local mode, it is important to make both their data secure. The access control policy is based on the right to access medical data and privilege to an authorized entity, which is directly or indirectly connected with the patient's health. In this paper, the authors design a method to develop a Smart Hospital with low investment.

Research Paper

New Technology in Computer Aided Design, Computer Aided Manufacturing, Computer Aided Engineering Analytic Methodology, Automated and High Speed Mechanical System

Jeremy (Zheng)*
Jeremy (Zheng) Li (2017). New Technology in Computer Aided Design, Computer Aided Manufacturing, Computer Aided Engineering Analytic Methodology, Automated and High Speed Mechanical System. i-manager’s Journal on Computer Science, 5(3), 6-53. https://doi.org/10.26634/jcom.5.3.14016

Abstract

Computer aided Design (CAD), 3-D modeling and engineering analysis can be efficiently applied in many research and industrial fields including aerospace, defense, automobile, consumer product, and many other product development. These efficient research and engineering tools apply computer-assisted technology to perform 3-D modeling on different products, support geometrical design, make structural analysis, assist optimal product design, create graphic and engineering drawings, and generate production documents. This technology helps scientists and technical professionals efficiently import basic geometrical inputs and design information to accelerate the engineering design process, with well controlled design documents, to support production and manufacturing processes. Currently these research and engineering tools have been playing more and more important roles in different business and enterprises due to its financial and technical importance in business, industrial, engineering, and manufacturing applications. The computer aided modeling and analysis allow more sophisticated, flexible, reliable, and cost-effective manufacturing control. Automation and automated production system are to use control system to reduce human labor intervention during manufacturing processes and put strong impact on industries. Automation and automated system design not only raise the production rate but also control the product quality. It can effectively keep consistent product quality, reduce production lead time, ease material handling, maintain optimal work flow, and meet the product requirement by controlling the flexible and convertible manufacturing / production processes. Computer aided modeling and engineering design can quickly simulate and model the automated production systems and reduce product development life cycles. Computer aided engineering solution can improve and optimize the industrial integral processes in design, development, engineering analysis, and product manufacturing. Also the present and future economic globalization requires cost-effective manufacturing via highly industrial automation, efficient design tooling, and better production control. This keynote lecture describes the technology, types, and general applications of these research and engineering tools through conceptual analysis and real case study in computer aided design, 3-D modeling, and engineering analysis. Some new product systems, developed by author, are introduced to help readers understand how to design and develop new product systems by using computer aided design, engineering analysis, and prototype experiment. The case studies include design and development of green / sustainable energy systems (solar still, solar panel, and wind power energy), biomedical and surgical instruments, energy-saving cooling system, automated and high speed assembly system (highly viscous liquid filling and chemical gas charging), robotic system for industrial / automated manufacturing, magnetic sealing system, and high speed packaging machinery system. Multiple engineering case studies in this keynote lecture aim at the introduction, study and analysis by using computer aided modeling and engineering analysis for industrial and engineering applications. All these newly developed product systems have also been verified by prototyping and testing to validate the functionality of these new systems. Both computer aided analysis and experimental methodologies introduced in this keynote lecture show close results that positively show the feasibility and credibility of analytic and experimental methodologies introduced in this keynote lecture.

Research Paper

Fixed Content Based Image Retrieval Technique

Shaik Mohammed Ilias* , DINESH CHAUHAN**, SRINIVAS ESAPALLI***, VINEETH PADIGE****
* Professor, Department of Computer Science and Engineering, St. Peter’s Engineering College, Hyderabad, India.
**-**** Research Scholar, Department of Computer Science and Engineering, St. Peter’s Engineering College, Hyderabad, India.
Ilias. S.M., Chauhan. D., Esapalli. S., and Padige. V. (2017). Fixed Content Based Image Retrieval Technique. i-manager’s Journal on Computer Science, 5(3), 54-59. https://doi.org/10.26634/jcom.5.3.14017

Abstract

Different techniques are available for Image Retrieval and this paper provides Fixed Content Based Image Retrieval (FCBIR) based on Content-Based Image Retrieval (CBIR) technique. The authors’ aim is to highlight their proposed technique called Fixed Content Based Image Retrieval. The authors have provided some proof on how exact image is searched by using FCBIR technique.

Review Paper

Leveraging The Power of Hybrid Machine Learning Algorithms to Predict Cardiovascular Diseases - A Review

Anuradha. P* , VASANTHA KALYANI DAVID**
* Research Scholar, Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Tamil Nadu, India.
** Professor, Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Tamil Nadu, India.
Anuradha P., and David, V.K. (2017). Leveraging The Power of Hybrid Machine Learning Algorithms to Predict Cardiovascular Diseases - A Review. i-manager’s Journal on Computer Science, 5(3), 60-67. https://doi.org/10.26634/jcom.5.3.14018

Abstract

As people are becoming more health conscious, preventive health care is gaining importance over diagnostic health care. The goal of future medicine is to provide personalized medical care. According to World Health Organization (WHO), 31% of all global deaths are due to Cardiovascular Diseases (CVDs). In order to prevent heart diseases, the unexplored hidden information in the health care data can be efficiently obtained by applying hybrid Machine Learning Algorithms. These algorithms would help the medical practitioners to gain insight into higher dimensional data, thereby assisting them to predict cardiac arrests even before it occurs. This would enhance medical care and reduce costs for patients. This paper surveys and highlights on the suitable statistical and hybrid Machine Learning Algorithms used for feature selection, prediction, and performance evaluation.