Applied System Innovation — Open Access Journal

Studies of systems engineering applications have revealed that systems engineering (SE) has a high potential for transferring economically inefficient oil and gas projects into a profitable zone due to preserving the value created at the concept stage right up to the implementation stage. To implement any project, including an organizational one, the company must have an economic justification for innovation. Studies into the global experience of assessing SE efficiency based on projects of various types have revealed the lack of a universal assessment method; however, individual studies have potential to be used in developing a method for quantifying the value of SE in oil and gas projects. Considering this fact, we developed our own method and prototype to assess the economic effect from the introduction of SE into oil and gas projects. The method is based on a decision tree used to calculate the Net Present Value considering the probability of projects’ success and failure in terms of budget and deadlines. This allowed us to predict the effect from introducing SE to an oil company’s capital project. The results obtained demonstrated the model’s performance capability and its possible applications in project resource planning stages. Full article

While admitting that neophobia and sociocultural factors negatively affect consumers’ propensity to consume insect-based foods, other aspects related to food values that consumers attach to these foods could have an influence on consuming decision. In order to identify the motivations and determinants that influence the propensity to consume insects and then to explore the drivers behind consumers’ willingness to consume insect-based foods, the data collected through the questionnaire were processed. After a descriptive analysis of the data, ANOVA was performed. Moreover, Student’s t test and pairwise correlation indices were estimated in order to determine statistically significant correlation. Our findings show that information about edible insects brought about an increase in food neophobia and appearance affected the expected liking levels. In addition, we have shown that respondents’ propensity to consume insect-based foods also depends on consumers’ subjective beliefs about food values such as healthiness, naturalness and environmental impact. We also found that respondents’ beliefs about food values associated with insect-based foods do not depend on the degree of information provided but are probably due to pre-existing prejudices about them. Full article

The COVID19 pandemic has indirectly changed the landscape of the business environment system through cloud intelligence within the digital ecosystem that has as a goal increasing the access, efficiency, effectiveness, equity and quality of business processes through cloud intelligent systems. Cloud intelligent systems are becoming revolutionary in today’s world pandemic causing a complete and drastic change to a variety of industries, including, security, transportation, business, logistics and manufacturing. The main purpose of cloud intelligence systems is to facilitate the ease of access from any location and the management of practical computing resources. One of the challenges faced by cloud technology today is scheduling. The role of scheduling algorithms is very important, since tasks are executed by orders that may need more attention. Here, scheduling algorithms intended to minimize monetary cost and minimize makespan time to execute the workflow are presented. This study proposes cloud intelligent systems apps through an approach to cloud computing scheduling that may lead to great benefits and efficiency. The result is very promising. It showed that there are numerous applications of intelligent systems due to the more advanced hardware being built nowadays, plus business processes advancing to become smarter and more efficient in growing profitably over a destructive digital ecosystem during the COVID19 pandemic. The results indicate that intelligent systems over the cloud play a big role not just for interacting with the world helping businesses grow, but as well as in the advancement for a better tomorrow. Full article

In order to study the influence of freeze-thaw cycles on the stability of cutting slopes in high-latitude and low-altitude permafrost regions, we selected a cutting slope (the K105+700–800 section of National Highway 332) in the Elunchun Autonomous Banner in Inner Mongolia as the research object. Located in the Greater Xing’an Mountains, the permafrost in the Elunchun Autonomous Banner is a high-latitude and low-altitude permafrost. The area is also dominated by island-shaped permafrost, which increases the difficulty of dealing with cutting slopes, due to its morphological complexity. Surface collapse, caused by freeze-thaw erosion in this area, is the main reason for the instability of the cutting slope. Indoor freeze-thaw tests, field monitoring, and an ABAQUS numerical simulation model were conducted so as to quantify the decrease in rock strength and slope stability under freeze-thaw conditions. The following conclusions were drawn. (1) As the number of freeze-thaw cycles increased, the compressive strength of the rock specimens obtained from this slope gradually decreased. After 50 freeze-thaw cycles, the uniaxial compressive strength measured by the test decreased from 40 MPa to 12 MPa, a decrease of 37%. The elastic modulus value was reduced by 47%. (2) The safety factor of the slope—calculated by the strength reduction method under the dynamic analysis of coupled heat, moisture, and stress—gradually decreased. After 50 freeze-thaw cycles, the safety factor of the slope was only 0.74. (3) Reasonably reducing the number of freeze-thaw cycles, reducing the water content of the slope, slowing down the slope, and increasing the number of grading steps can effectively improve the stability of the slope. The results of this study can provide a reference for the design and stability analysis of slopes in permafrost regions of the Greater Xing’an Mountains. Full article

Electric vehicles (EV) are becoming more common mobility in the transportation sector in recent times. The dependence on oil as the source of energy for passenger vehicles has economic and political implications, and the crisis will take over as the oil reserves of the world diminish. As concerns of oil depletion and security of the oil supply remain as severe as ever, and faced with the consequences of climate change due to greenhouse gas emissions from the tail pipes of vehicles, the world today is increasingly looking at alternatives to traditional road transport technologies. EVs are seen as a promising green technology which could lead to the decarbonization of the passenger vehicle fleet and to independence from oil. There are possibilities of immense environmental benefits as well, as EVs have zero tail pipe emission and therefore are capable of curbing the pollution problems created by vehicle emission in an efficient way so they can extensively reduce the greenhouse gas emissions produced by the transportation sector as pure electric vehicles are the only vehicles with zero-emission potential. However, there are some major barriers for EVs to overcome before totally replacing ICE vehicles in the transportation sector and obtain appreciable market penetration. This review evaluates the technological aspects of the different power train systems of BEV technology and highlights those technological areas where important progress is expected by focusing on reviewing all the useful information and data available on EV architecture, electrical machines, optimization techniques, and its possibilities of future developments as green mobility. The challenges of different electric drive trains’ commercialization are discussed. The major objective is to provide an overall view of the current pure electric vehicle powertrain technology and possibilities of future green vehicle development to assist in future research in this sector. Full article

This paper proposes a sensor-data-driven prognosis approach for the predictive maintenance of a liquefied natural gas (LNG) satellite plant. By using data analytics of sensors installed in the satellite plants, it is possible to predict the remaining time to refill the tank of the remote plants. In the proposed approach, the first task of data validation and correction is presented in order to transform raw data into reliable validated data. Then, the second task presents two methods for the prognosis of gas consumption in real time and the forecast of remaining time to refill the tank of the plant. The obtained results with real satellite plants showed good performance for direct implementation in a predictive maintenance plan. Full article

Generally, there are two types of working style, i.e., some people work in sitting conditions, and the remaining work mostly in a standing position. For people working in a standing position, they can spend hours in a day doing their work standing. These people do not realize that it can cause medical issues, especially for the feet, namely biometric problems. In addition, several doctors in Indonesia are already aware of this issue and state that the biometric problems faced by those kinds of people can be predicted from the load distribution on the foot. However, the tool used by the doctors in Indonesia to measure biometric problems is not a digital tool. Therefore it is very difficult to measure and predict the biometric problems quantitatively. This study aims to develop a low-cost static load measuring device using force-sensing resistor (FSR) sensors. The measuring instrument is designed in the form of a pressure plate platform which consist of 30 FSR 402 sensors. The sensors are placed right underneath the display area of the foot, 15 sensors on the soles of the left and right feet. Ten students from the Department of Mechanical Engineering, Diponegoro University (five men and five women) were asked to stand on the platform. Each subject also measured foot length (FL) to estimate shoe size, foot area contact (FAC) for validation between genders, and foot type using the digital footprint tools. From the results of measurements obtained for the left foot in the medial mid foot area, i.e., in sensors 5 and 7, not exposed to the load, on almost all subjects except subject number 3 with a load of 0.196 kg on sensor 7. The highest average load occurs in the heel area i.e., sensor 1 measured 0.713 kg and the smallest average load occurs in the five sensors, with 0 kg. A static load gauge that is designed to be used to measure each leg area for subjects with a shoe size of 40–42 with low price to be held in hospital-orthopedic hospitals and biomechanical research centers. Full article

The essential disadvantages of conventional glucose enzymatic biosensors such as high fabrication cost, poor stability of enzymes, pH value-dependent, and dedicated limitations, have been increasing the attraction of non-enzymatic glucose sensors research. Beneficially, patients with diabetes could use this type of sensor as a fourth-generation of glucose sensors with a very low cost and high performance. We demonstrate the most common acceptable transducer for a non-enzymatic glucose biosensor with a brief description of how it works. The review describes the utilization of graphene and its composites as new materials for high-performance non-enzymatic glucose biosensors. The electrochemical properties of graphene and the electrochemical characterization using the cyclic voltammetry (CV) technique of electrocatalysis electrodes towards glucose oxidation have been summarized. A recent synthesis method of the graphene-based electrodes for non-enzymatic glucose sensors have been introduced along with this study. Finally, the electrochemical properties such as linearity, sensitivity, and the limit of detection (LOD) for each sensor are introduced with a comparison with each other to figure out their strengths and weaknesses. Full article

This paper presents a comprehensive survey about the fundamental components of the artificial pancreas (AP) system including insulin administration and delivery, glucose measurement (GM), and control strategies/algorithms used for type 1 diabetes mellitus (T1DM) treatment and control. Our main focus is on the T1DM that emerges due to pancreas’s failure to produce sufficient insulin due to the loss of beta cells (β-cells). We discuss various insulin administration and delivery methods including physiological methods, open-loop, and closed-loop schemes. Furthermore, we report several factors such as hyperglycemia, hypoglycemia, and many other physical factors that need to be considered while infusing insulin in human body via AP systems. We discuss three prominent control algorithms including proportional-integral- derivative (PID), fuzzy logic, and model predictive, which have been clinically evaluated and have all shown promising results. In addition, linear and non-linear insulin infusion control schemes have been formally discussed. To the best of our knowledge, this is the first work which systematically covers recent developments in the AP components with a solid foundation for future studies in the T1DM field. Full article

A new technique is developed to extend the convergence ball of Newton’s algorithm with projections for solving generalized equations with constraints on the multidimensional Euclidean space. This goal is achieved by locating a more precise region than in earlier studies containing the solution on which the Lipschitz constants are smaller than the ones used in previous studies. These advances are obtained without additional conditions. This technique can be used to extend the usage of other iterative algorithms. Numerical experiments are used to demonstrate the superiority of the new results. Full article

The objective of this article is to propose and verify a reliable detection mechanism of multi-rotor unmanned aerial vehicles (UAVs). Such a task needs to be solved in many areas such as in the protection of vulnerable buildings or in the protection of privacy. Our system was firstly realized by standard computer vision methods using the Oriented FAST and Rotated BRIEF (ORB) feature detector. Due to the low success rate achieved in real-world conditions, the machine-learning approach was used as an alternative detection mechanism. The “Common Objects in Context dataset” was used as a predefined dataset and it was extended by 1000 samples of UAVs from the SafeShore dataset. The effectiveness and the reliability of our system are proven by four basic experiments—drone in a static image and videos which are displaying a drone in the sky, multiple drones in one image, and a drone with another flying object in the sky. The successful detection rate achieved was 97.3% in optimal conditions. Full article

This paper describes the design and modus of operation of a neuromorphic robotic platform based on SpiNNaker, and its implementation on the goalkeeper task. The robotic system utilises an address event representation (AER) type of camera (dynamic vision sensor (DVS)) to capture features of a moving ball, and a servo motor to position the goalkeeper to intercept the incoming ball. At the backbone of the system is a microcontroller (Arduino Due) which facilitates communication and control between different robot parts. A spiking neuronal network (SNN), which is running on SpiNNaker, predicts the location of arrival of the moving ball and decides where to place the goalkeeper. In our setup, the maximum data transmission speed of the closed-loop system is approximately 3000 packets per second for both uplink and downlink, and the robot can intercept balls whose speed is up to 1 m/s starting from the distance of about 0.8 m. The interception accuracy is up to 85%, the response latency is 6.5 ms and the maximum power consumption is 7.15 W. This is better than previous implementations based on PC. Here, a simplified version of an SNN has been developed for the ‘interception of a moving object’ task, for the purpose of demonstrating the platform, however a generalised SNN for this problem is a nontrivial problem. A demo video of the robot goalie is available on YouTube. Full article

In this study, a scaled-down system, which can be used as a benchmark test for the battery storage designing of electric vehicles (EVs) is proposed. This model was based on the hardware simulator of the battery storage system (BSS) used from a single cell up to 4 cells in a series pack system, which simulates a practical battery pack. The developed simulator can charge and discharge any rechargeable battery, such as Li-Ion, Ni–MH or Pb battery. The scaling ratio of the simulator was evaluated by the ratio of the current or power of the battery pack specimen related to the specification. Also, this study proposes an innovative state of charge (SoC) estimation of the battery pack for EVs based on genuine results obtained through practical tests. This estimation was carried out by an adaptive artificial neural network (ANN) algorithm, using simple inputs. As well, this model can deduct the state of health (SoH) of the battery pack based on the power output level and waveform characteristics. The results of the ANN showed high generalization, a low error of SoC estimation at the level of 1.1%, with a calculation time less than 16.5 s. Regarding the hardware simulator, the similarity of the results and waveform accuracy of the scaled-down battery systems compared with the real battery pack was very acceptable with a maximum deviation of 2.1% in the worst scenario. The cells cycled with different depths of discharge (DoD) or C-rates, at different temperatures with different initial SoCs using any arbitrary current waveforms. Our conclusions will help battery manufacturers to test and evaluate the performance of the BSS in different applications, such as EVs, PV generation, and wind farm, with significant cost reduction. Also, the ANN algorithm can be used and embedded in EVs or in any other industrial application, as proposed in this paper. This study contributed to the real-time diagnosis of the BSS without interrupting the normal operation based on its features. Full article

The reduction of carbon dioxide emissions has become a need of the day to overcome different environmental issues and challenges. The use of alternative and renewable-based technologies is one of the options to achieve the target of sustainable development through the reduction of these harmful emissions. Among different technologies thermally activated cooling systems are one which can reduce the harmful emissions caused by conventional heating, ventilation, and air conditioning technology. Thermal cooling systems utilize different porous materials and work on a reversible adsorption/desorption cycle. Different advancements have been made for this technology but still a lot of work should be done to replace conventional systems with this newly developed technology. High adsorption capacity and lower input heat are two major requirements for efficient thermally driven cooling technologies. In this regard, it is a need of the day to develop novel adsorbents with high sorption capacity and low regeneration temperature. Due to tunable topologies and a highly porous nature, the hybrid porous crystalline materials known as metal–organic frameworks (MOFs) are a great inspiration for thermally driven adsorption-based cooling applications. Keeping all the above-mentioned aspects in mind, this paper presents a comprehensive overview of the potential use of MOFs as adsorbent material for adsorption and desiccant cooling technologies. A detailed overview of MOFs, their structure, and their stability are presented. This review will be helpful for the research community to have updated research progress in MOFs and their potential use for adsorption-based cooling systems. Full article

The present paper addresses the problem of the dynamic response of a vibrating equipment for soil compaction. In essence, dynamic response vibrations are analysed by applying an inertial-type perturbing force. This is generated by rotating an eccentric mass with variable angular velocity, in order to reach the regime necessary to ensure the degree of compaction. The original character of the research is that during the compaction process, the soil layers with certain compositions of clay, sand, water and stabilizing substances change their rigidity and/or amortization. In this case, two situations were analysed, both experimentally and with numerical modelling, with special results and practical engineering conclusions, favourable to the evaluation of the interaction between vibrator roller–compacted ground. We mention that the families of amplitude–pulse and transmitted force–pulse response curves are presented, from which the dynamic effect in the compaction process results after each passage on the same layer of soil, until the necessary compaction state is reached. Full article

Throughout this paper, the model, its parameter estimation and a controller for a solution using a DC motor with a gearbox worm, coupled to a non-rigid joint, will be presented. First, the modeling of a non-linear system based on a DC Motor with Worm Gearbox coupled to a non-rigid joint is presented. The full system was modeled based on the modeling of two sub-systems that compose it—a non-rigid joint configuration and the DC motor with the worm gearbox configuration. Despite the subsystems are interdependent, its modelling can be performed independently trough a carefully chosen set of experiments. Modeling accurately the system is crucial in order to simulate and know the expected performance. The estimation process and the proposed experimental setup are presented. This setup collects data from an absolute encoder, a load cell, voltage and current sensors. The data obtained from these sensors is presented and used to obtaining some physical parameters from both systems. Finally, through an optimization process, the remaining parameters are estimated, thus obtaining a realistic model of the complete system. Finally, the controller setup is presented and the results obtained are also presented. Full article

The objective of this work is the financial optimization of a solar-driven organic Rankine cycle. Parabolic trough solar collectors are used as the most mature solar concentrating system and also there is a sensible storage system. The unit is examined for the location of Athens in Greece for operation during the year. The analysis is conducted with a developed dynamic model in the program language FORTRAN. Moreover, a developed thermodynamic model in Engineering Equation Solver has been used in order to determine the nominal efficiency of the cycle. The system is optimized with various financial criteria, as well as with energy criteria. The optimization variables are the collecting area and the storage tank volume, while the nominal power production is selected at 10 kW. According to the final results, the minimum payback period is 8.37 years and it is found for a 160 m² collecting area and a 14 m³ storage tank, while for the same design point the levelized cost of electricity is minimized at 0.0969 € kWh⁻¹. The maximum net present value is 123 k€ and it is found for a 220-m² collecting area and a 14-m³ storage tank volume. Moreover, the maximum system energy efficiency is found at 15.38%, and, in this case, the collecting area is 140 m² and the storage tank volume 12 m³. Lastly, a multi-objective optimization proved that the overall optimum case is for a 160-m² collecting area and a 14-m³ storage tank. Full article

Liquid single crystal elastomers (LSCEs) containing carbazole fluorogenic components alter their luminescence when they are stretched along the director direction. The differential luminescent behavior arises from the distinct interaction between the carbazole fluorophores and their local environment before and after the application of the mechanical input. Indeed, the uniaxial deformation of the material, along its anisotropic direction, forces a closer mesogen–fluorophore interaction, which leads to the quenching of the carbazole luminescence. Importantly, this intermolecular interaction is intimately related to the intrinsic order present in the LSCE. As a result, the amount of light emitted by the material in the form of fluorescence diminishes upon deformation. Thus, the application of mechanical stimuli to liquid-crystalline elastomers furnishes to two interconvertible states for the system with distinct optical properties (with either different emission color or fluorescence intensity). The initial state of the material is completely restored once the applied force is removed. In this way, this kind of macromolecular system can transduce mechanical events into detectable and processable optical signals, thus, having great potential as optical force sensors. In this context, the realization of the distinct structural factors that govern the interactions established between the mesogenic and fluorogenic units at the supramolecular level upon deformation is essential for the development of efficient LSCE-based force sensors. In fact, not only the density of carbazole units and their connection to the main polymer backbone, but also the presence of long range molecular order in the system and the type of mesophase exhibited by the LSCE are key factors for the conception of efficient force sensors based on these self-organized polymer networks. In this review, we present a comprehensive and systematic description of the different features that control the mechanoluminescent behavior of fluorescent liquid-crystalline elastomers and will guide the future design of LSCE-based force sensors with improved performances. Full article

This paper presents a general framework to address diverse notoriously difficult problems arising in the area of optimal resource management, exploitation of natural reserves, pension fund valuation, environmental protection, and storage operation. Using some common abstract features of this problem class, we present a technique which provides a significant reduction of decision variables. As an application, we discuss a battery storage control to show how a decision problem, which is practically unsolvable in the original formulation, can be treated by our method. Full article