The 2nd International Conference on Advances in Mechanical Engineering

The Second International Conference on Advances in Mechanical Engineering, ICAME-22, was held on 25th August, 2022 at the Mechanical Engineering Department of Capital University of Science and Technology. All articles underwent a rigorous single-blind peer review process. ICAME-22 accepted papers in the disciplines of experimental and computational fluid dynamics, thermodynamics, heat Ttransfer, machine and mechanisms, design, solid mechanics, manufacturing, production and industrial engineering, engineering management, technology management, renewable energy, environmental engineering, bioengineering, materials, failure analysis, and related fields

Task scheduling based on genetic algorithm for robotic system in 5G manufacturing industry

With the development of 5G technology, the robotic system has been bought into industrials. Even manufacturers plan the task flow by using project management. An error may occur and make the tasks overlap because they use the traditional scheduling method. It may waste much time between the tasks, and robots will get into standby mode to wait for the next tasks if the scheduling is failed. An algorithm with flexible scheduling is needed to arrange the tasks accordingly with the shortest total completion time. Genetic Algorithm (GA) is applied to task scheduling, and it provides a better solution from previous results or arrangements due to iteration. In this study, an analysis involves multi robots to complete various industrial operations, consisting of multi-tasks. To save time during processing and costs in production, GA may help it have the optimal value about total complete time to avoid any wastage. In short, the manufacturer will have higher productivity and better performance among the robots when applied a suitable Task Scheduling in the industry or workplace

Tracking variable fitness landscape in dynamic multi-objective optimization using adaptive mutation and crossover operators

Abstract: Many real-world problems are modeled as multi-objective optimization problems whose optimal solutions change with time. These problems are commonly termed dynamic multi-objective optimization problems (DMOPs). One challenge associated with solving such problems is the fact that the Pareto front or Pareto set often changes too quickly. This means that the optimal solution set at period t may likely vary from that at (t+1), and this makes the process of optimizing such problems computationally expensive to implement. This paper proposes the use of adaptive mutation and crossover operators for the non-dominated sorting genetic algorithm III (NSGA-III). The aim is to find solutions that can adapt to fitness changes in the objective function space over time. The proposed approach improves the capability of NSGA-III to solve multi-objective optimization problems with solutions that change quickly in both space and time. Results obtained show that this method of population reinitialization can effectively optimize selected benchmark dynamic problems. In addition, we test the capability of the proposed algorithm to select robust solutions over time. We recognize that DMOPs are characterized by rapidly changing optimal solutions. Therefore, we also test the ability of our proposed algorithm to handle these changes. This is achieved by evaluating its performance on selected robust optimization over time (ROOT) and robust Pareto-optimality over time (RPOOT) benchmark problems

Theoretical Computer Science and Discrete Mathematics

This book includes 15 articles published in the Special Issue "Theoretical Computer Science and Discrete Mathematics" of Symmetry (ISSN 2073-8994). This Special Issue is devoted to original and significant contributions to theoretical computer science and discrete mathematics. The aim was to bring together research papers linking different areas of discrete mathematics and theoretical computer science, as well as applications of discrete mathematics to other areas of science and technology. The Special Issue covers topics in discrete mathematics including (but not limited to) graph theory, cryptography, numerical semigroups, discrete optimization, algorithms, and complexity

Bio-Inspired Robotics

Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field

UAVs for the Environmental Sciences

This book gives an overview of the usage of UAVs in environmental sciences covering technical basics, data acquisition with different sensors, data processing schemes and illustrating various examples of application

The Mars Gravity Biosatellite as an innovative partial gravity research platform

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2008.Includes bibliographical references (leaves 269-275).The Mars Gravity Biosatellite is an unprecedented independent spaceflight platform for gravitational biology research. With a projected first launch after 2010, the low Earth orbit satellite will support a cohort of fifteen 14.5- to 25.5-week-old female BALB/cByJ mice for up to five weeks. During this time, the spacecraft will rotate at a rate of 31.6 rpm to generate Mars-equivalent artificial gravity of magnitude 0.38-g. Reentry capability will permit the return of live specimens to the Earth's surface at the culmination of the study. The proposed first mission aims to explore the physiological impacts on mice of 0.38-g. On board the Mars Gravity Biosatellite, a video acquisition and digitisation system will enhance in-flight collection of data on sensorimotor adaptation. As part of this thesis, a rotational ground control system has been designed and constructed at MIT. The apparatus incorporates a video processing module similar to that baselined for the mission. It also features the first custom-designed gondola centrifuge that accommodates up to four singlyhoused rodents in flight-equivalent habitat modules. At a rotation rate of 31.6 rpm, the centripetal acceleration experienced by each animal is less than 1.07-g. The 0.34 m radius of rotation is equivalent to that of the orbital vehicle. A behavioural study with four BALB/cByJ mice explores the effects of chronic rotation alone and confirms that they can be quantified and therefore decoupled from the anticipated on-orbit effects of rotation-induced Mars-equivalent gravity. The results provide justification for the scientific validity of the Mars Gravity Biosatellite as a rotating spaceflight platform. In addition, details are presented on the design, implementation, test and operation of a two-mouse closed-loop environmental control and life support system (ECLSS). The ground-based assembly is colocated with the centrifuge, and the entire apparatus is enclosed within a sealed zero-pressure urethane/polyethylene membrane. It incorporates scaled-down versions of a subset of flight-equivalent atmospheric reconditioning subassemblies together with sensors, actuators and a computer to perform autonomous feedback-driven supervisory control.(cont.) Data is presented that validates a system that includes oxygen replenishment, carbon dioxide scrubbing via reaction with lithium hydroxide, ammonia removal using acidtreated activated charcoal, and humidity control with a custom-designed condensing heat exchanger. Results of a multi-week test represent an experimental proof-of-concept for the Mars Gravity Biosatellite's ECLSS strategy, showing good control of environmental parameters within specified ranges. The work presented in this thesis offers four primary contributions to aerospace biomedical engineering and rodent behavioural science: 1. Preliminary design and operations plans for the Mars Gravity payload. This thesis claims specific contributions in the areas of electronics, instrumentation, software and systems-level design of the payload module. 2. The first direct measurement of the influence of chronic rotation on mice in flight-like habitats at 31.6 rpm. The first in-centrifuge use of video-based behavioural analysis. 3. Proof-of-concept justification for the Mars Gravity Biosatellite ECLSS strategy. 4. The conception, design, implementation and operation of the first integrated ground test apparatus to combine chronic rotation capability with an ECLSS testbed.by Thaddeus R. F. Fulford-Jones.Ph.D