Appl. Syst. Innov., Volume 3, Issue 2 (June 2020) – 12 articles

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

While visual assessment is the standard technique for burn evaluation, computer-aided diagnosis is increasingly sought due to high number of incidences globally. Patients are increasingly facing challenges which are not limited to shortage of experienced clinicians, lack of accessibility to healthcare facilities and high diagnostic cost. Certain number of studies were proposed in discriminating burn and healthy skin using machine learning leaving a huge and important gap unaddressed; whether burns and related skin injuries can be effectively discriminated using machine learning techniques. Therefore, we specifically use transfer learning by leveraging pre-trained deep learning models due to deficient dataset in this paper, to discriminate two classes of skin injuries—burnt skin and injured skin. Experiments were extensively conducted using three state-of-the-art pre-trained deep learning models that includes ResNet50, ResNet101 and ResNet152 for image patterns extraction via two transfer learning strategies—fine-tuning approach where dense and classification layers were modified and trained with features extracted by base layers and in the second approach support vector machine (SVM) was used to replace top-layers of the pre-trained models, trained using off-the-shelf features from the base layers. Our proposed approach records near perfect classification accuracy in categorizing burnt skin ad injured skin of approximately 99.9%. Full article

Location-based services are becoming extremely popular due to the widespread use of smartphones and other mobile and portable devices. These services mainly rely on the sincerity of users, who can spoof the location they report to them. For applications with higher security requirements, the user should be unable to report a location different than the real one. Proof of Location protocols provide a solution to secure localization by validating the device’s location with the help of nearby nodes. We propose QuietPlace, a novel protocol that is based on ultrasound and provides strong identities, proving the location of the owner of a device, without exposing though their identity. QuietPlace provides unforgeable proof that is able to resist to various attacks while respecting the users’ privacy. It can work regardless of certificate authority and location-based service and is able to support trust schemas that evaluate the participants’ behavior. We implement and validate the protocol for Android devices, showing that ultrasound-based profiles offer a better performance in terms of maximum receiving distance than audible profiles, and discuss its strengths and weaknesses, making suggestions about future work. Full article

The nonlinear dynamical behaviour of a network that is submitted to disturbances is the starting point of this work, where we consider a low voltage line (the network) with nonlinear varistor filters responding, dynamically, to those disturbances. Network models consider static measurements, and here we develop an iterative model to deal with dynamical measurements. We begin with the one-dimensional communication line model using reflected and incident signals, which are dependent on the node parameters, proceeding a time-step computation. Each node is a space representation that consolidates parameters for a specific vertex and its edges. Nonlinear functions are applied within the node and will contribute to the general process running on the structure. The idea of a structure and its related processes leads to a new concept of sustainability and system robustness. This concludes the work, along with several experimental and simulation results, with direct advantages to electromagnetic interference control and mitigation. Full article

A problem for wind turbine operators is decreasing prices for wind-generated electricity. Many turbines are approaching their rated 20-year lives. A more economically viable and sustainable solution that reduces Levelized Cost of Energy (LCOE) and avoids expensive turbine replacement is retrofitting new spar caps blades. A new cost model assesses the feasibility of retrofitting 35 to 75 m turbines with GFRP (glass fiber reinforced polymer composite) and longer length CFRP (carbon fiber reinforced composite) spar caps. Spar cap cost scales with features such as mass, volume fraction and complexity. Organizational learning is a cost factor. Material and direct labor increase as proportions of total cost while tooling, capital, utilities, and indirect labor decrease. There is good agreement between a manufacturer and the model. Twenty-year turbines were compared with retrofitted spar caps over 25 years for LCOE. Same length GFRP and longer length CFRP spar cap retrofits decrease LCOE. Longer length CFRP spar caps decrease LCOE compared with GFRP retrofits over 25 years. CFRP material cost impacts CFRP retrofit feasibility. Retrofitted turbines must meet engineering, operational performance, and planning requirements criteria. Software algorithms may improve human learning and enable automatic updates from varying design and cost inputs, thereby increasing cost prediction accuracy. Full article