Appl. Syst. Innov., Volume 3, Issue 3 (September 2020) – 13 articles

The world is facing a new challenge to overcome the pandemic disease of Coronavirus (COVID-19). An outbreak of COVID-19 to more than 213 countries and territories caused damage to the economy of every country. The proper vaccine to combat this pandemic disease is not invented yet. Due to the lockdown situation, there is a shortage of daily used products globally. To overcome the issue of food shortage and economic survival, the world has to ease the lockdown rules and become operational with the precautionary measures. COVID-19 has a fast transmission rate, therefore, while living with COVID-19, breaking the fast transmission chain of COVID-19 is the only vital solution. Furthermore, there is a dire need to disinfect every individual and his luggage at the entrance of every shopping mall, hospital, public and private institutions, bus stops, metro stations, and railway stations. Hence, the proposed walk-through gate (WTG) with different sensors, i.e., infrared thermal camera, UV disinfectant sensor, disinfectant spraying system, touch-less hand sanitizer, and box having a face mask with a dustbin to discard the previous mask can provide an effective and efficient relief. The world cannot stop working and cannot survive for more than 3–6 months in a lockdown, hence the proposed idea is to install the disinfectant automated spraying WTG with a security walk-through gate at every possible entrance to conform living with the COVID-19 disease such as many other diseases. Breaking the transmission chain is the only solution to win the battle against COVID-19 until an effective vaccine invention. Full article

In fields with high science linkage, such as the nanocarbon field, trends in academic papers are particularly important for identifying future technological trends. The use of the number of citations allows us to predict the qualitative trends on a paper-by-paper basis. At the same time, it is necessary to be able to comprehensively discuss both qualitative and quantitative aspects in the subject area. This study aimed to detect emerging areas in the nanocarbon field using network models and topic models. It was possible to not only construct a model that exceeded an 86.2% F1 measure but also to focus on an area that could not be detected by the prediction model. This was accomplished by focusing on paper units, such as the research on the chemical synthesis of zigzag single-walled carbon nanotubes. Thus, it is possible to obtain knowledge that contributes to diversified R&D strategies and innovation policies by considering the emergence of new fields from multiple perspectives. Full article

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