In today's research, sustainable gym concepts are rising in which, one can generate electricity from gyms equipment. The objective of this project is to harvest human energy from biceps exercise machine and transform into electrical energy. To complete this goal, a mechanism is fabricated and attached to the existing biceps machine accessible in any fitness centers. After mechanism is been fabricated, can be easily attached or detached to the biceps machine which converts the To and Fro motion to complete pure circular motion that helps to rotate the motors shaft in order to generate electricity. Battery is attached to the system that stores the electrical charges depends upon lifting the load, time taken to lift the load and these electrical charges can be access for later use. The concept of smart biceps machine is to provide exceptional features to enhance the user experience that can be able to produce electricity, Self-trained and defined the user basic health status.
The dependency of any embedded navigation in enhanced vehicular system rely on accurate and error free data on navigational information stored as well as refined to provides secured path. On evaluating the subsisting method, paramount trade-off is investigated among the present state of controller design and the subsisting navigational system on different case studies and applications. The controller system used in the subsisting design for navigation utilizing fault-prone INS/GPS information does not accentuate on sliding mode controller. Albeit, there has been effective research works in sliding mode controller, it is fewer endeavored for optimizing the performance in navigation of a conveyance. Consequently, this paper presents designing a new optimized sliding mode controller which may be deployed efficiently on advanced navigation system. The result of study was determined to provide optimal control signal, greater celerity and reduced error occurrences to manifest that proposed system provides optimized and reliable navigational accommodations in contrary to subsisting system.
Melanoma is the deadliest form of skin cancer. It is a type of cancer that develops from the pigment-containing cells known as melanocytes-mutate and become cancerous. Even in such a modern-cultured society of today, it is a very difficult task to detect such a disease and there are quite a few applications or systems developed for these tasks, which provide services only through paid subscriptions. We intend to develop an application that detects melanoma without any subscriptions. Melanoma is a hazardous type of skin cancer that is usually curable if detected early. As the biopsy (diagnosis) of this disease is a bit expensive and time-consuming procedure. Therefore, to tackle this issue we will be developing an android application through which we can detect Melanoma through the image processing techniques with the assistance of Convolutional neural network algorithm (CNN) with a training accuracy of 98% and testing accuracy of about 94%.
The Big Data and Cloud Computing is considered as one of the researching areas and leveraging technologies provided in United Nation's Sustainable Development Goals (SDGs) and 2030 agenda for global sustainable development. The Kingdom of Saudi Arabia (KSA) is set to fulfill regulatory obligations towards sustainability via 2030 Vision together with the National Transformation Program 2020 objectives. In this paper, the prospects with regards to studying and applying Big Data and Cloud computing in developing countries like KSA is presented. The research is focused on challenges and opportunities of data science, large volumes of data storage on clouds and its computing issues in KSA as well as need to analyze profitable projects for achieving sustainable development goals by 2030 in developing countries is presented. Furthermore, important factors considered as technical challenges to the socio-economic development and environmental differences of KSA are also reviewed.
One of the most intriguing topics over the past few years has been minimizing energy consumption in convenient gadgets and enhancing their battery life. The production of portable devices has made society's work more accessible and has increased comfort levels by using those devices to the maximum threshold. Batteries fuel such gadgets. Most of the companies invest their time, energy, and money looking for new ideas for increasing battery life, and most of these ideas are related to hardware. Their uptime subsequently depends on the vitality utilization of the parts and components. By exploring fresh approaches that empower frameworks to adjust powerfully at runtime, energy utilization can be effectively decreased. This article focuses on employing a portion of vitality administration that can dynamically select the most excellent calculation so that a battery can have maximum life and utilization. The analysis shows that quicksort is the first viable sorting approach when it comes to vitality sorting; For Minimal Spanning Tree: Prims, For Graph Searching: BFS and For Implementing and Searching Trees: RBT.
