Inventions

This research paper aims to design and implement an intelligent least short time memory (LSTM) deep learning classification technique to detect possible anomalies in measurements dataset within a particular Li-ion battery type. For the state of charge (SOC) and battery faults estimation, a Joint State and Parameter Extended Kalman Filter (JEKF) estimator is developed. The SOC accuracy performance is excellent, with less than 0.5% error during steady-state, compared to the 2% error reported in the literature. For the design and implementation of JEKF SOC and parameter estimation is chosen a preset Li-ion battery Simulink Simscape generic model. It is also helpful to generate the healthy and faulty measurement dataset to design and implement the proposed intelligent LSTM classifier deep learning technique. The generic Li-ion battery model is wisely selected for the “proof concept” purpose, model validation, and algorithms’ robustness, accuracy, and effectiveness. Compared to the traditional EKF fault diagnosis and isolation (FDI), a model-based estimation strategy, the proposed classification LSTM technique is an intelligent data-driven-based deep learning algorithm of high accuracy (around 80%) and loss performance close to zero. Therefore, this feature makes data collection of dataset measurements directly from Li-ion battery sensors possible, which is beneficial for generating online fault scenarios. Additionally, the LSTM deep learning technique can remarkably classify all detected anomalies with high accuracy, independent of battery model accuracy, uncertainties, and unmodeled dynamics. Also, high-performance accuracy root mean square error (RMSE) of 0.0588 (voltage fault), approximately $5.5\times {10}^{-7}$ (healthy) and 8.87 ×${10}^{-6}$ (current fault) for deep learning shallow neural network (DLSNN) reveals an obvious superiority of both compared to the traditional FDI estimation strategies. Full article

While impressive progress has been already achieved in wide-bandgap (WBG) semiconductors such as 4H-SiC and GaN technologies, the lack of intelligent methodologies to control the gate drivers has prevented exploitation of the maximum potential of semiconductor chips from obtaining the desired device operations. Thus, a potent ongoing trend is to design a fast gate driver switching scheme to upgrade the performance of electronic equipment at the system level. To address this issue, this work proposed a novel intelligent scheme for the control of gate driver switching using the concept of quantum computation in machine learning. In particular, the quantum principle was incorporated into deep reinforcement learning (DRL) to address the hardware limitations of conventional computers and the growing amount of data sets. Taking potential benefit of the quantum theory, the DRL algorithm influenced by quantum specifications (referred to as QDRL) not only ameliorates the performance of the native algorithm on traditional computers but also enhances the progress of relevant research fields like quantum computing and machine learning. To test the practicability and usefulness of QDRL, a dc/dc parallel boost converter feeding constant power loads (CPLs) was chosen as the case study, and several power hardware-in-the-loop (PHiL) experiments and comparative analysis were performed. Full article

The article discusses the method and results of processing statistical data from an experimental study of vibrations in marine diesel engines caused by the operation of cylinder-piston groups. The results of the application of a ranking method for identifying factors that influence vibration in marine diesel engines are presented to determine the most significant ones. A series of experiments were conducted according to special plans to actively implement the random balance method. This helped to establish the correctness of selecting the most significant factors from a variety of factors that influence the process under study. The article presents a mathematical model that enables the calculation of current values and prediction of changes in the most significant indicators, with the clearance between the piston and the cylinder liner being the most important. Full article

Increasing CO₂ gas emissions results in climate change by increasing air temperature and worsening environmental problems. It is necessary to control CO₂ gas in the air to overcome this. This research aims to optimize the absorption of CO₂ gas in the air with 0.1 M NaOH absorbent in the column of the Raschig ring stuffing material using the response surface methodology (RSM). This research was conducted using a continuous system of three independent variables by varying the contact time (10–80 min), the flow rate of NaOH absorbent (2–5 L/min), and the flow rate of CO₂ gas (1–5 L/min). The response variables in this study were the absorption rate (L/min) and mass transfer coefficient, while the air flow rate was constant at 20 L/min. Air and CO₂ gas mix before absorption occurs and flow into the Raschig ring packing column so that contact occurs with the NaOH absorbent. Mass transfer of CO₂ gas occurs into the NaOH absorbent, resulting in absorption. The results showed that the effect of contact time (min), the flow rate of NaOH absorbent (L/min), and CO₂ gas flow rate individually and the interaction on CO₂ absorption rate and mass transfer coefficient were very significant at a p-value of 0.05. Chemical absorption of CO₂ also occurred due to the reaction between CO₂ and OH- to form CO₃²⁻ and HCO₃⁻, so the pH decreased, and the reaction was a function of pH. Optimization using Design Expert 13 RSM Box–Behnken Design (BBD) yielded optimal conditions at an absorption time of 80 min, NaOH absorbent flow rate of 5 L/min, CO₂ gas flow rate of 5 L/min, absorption rate of CO₂ gas of 3.97 L/min, and CO₂ gas mass transfer coefficient of 1.443 mol/min m² atm, with the desirability of 0.999 (≈100%). Full article

Developing countries in Asia widely use manual seed broadcasting methods due to a lack of appropriate seeding machinery. The agricultural sector is currently facing labor shortages and high labor costs, especially seasonal labor shortages for broadcasting and transplanting operations. However, the primary constraint in adopting existing broadcasting seeders for small-scale farmers in developing countries is the high initial purchase costs. Therefore, developing locally commercial accessible technology for small-scale farmers is an urgent requirement. In this regard, attempt was taken to develop a new low-cost 3D printed seeder that can be used for multi-crop seed broadcasting operations when integrated with an autonomous terrain vehicle. A new seed metering mechanism was proposed for seed broadcasting that can be controlled electronically from the autonomous terrain vehicle. Positional sensors based on the real time kinematics—global navigation satellite system (RTK-GNSS) were used to record positional information. The best observation was noted at a vehicle operational speed of 0.351 ms⁻¹ and had a coefficient of variation (CV) referring to the distribution uniformity of seeds of 19% for green peas, 22% for cowpeas, and 25% for chickpeas. The developed seeder could spread multi-crop seeds and adjust the seed rates electronically at the different ranges of rotational speeds. Therefore, the use of 3D printed fabricated prototype seed broadcasting units with small-scale autonomous vehicles can be implemented to help in labor supplements and perform the broadcasting of different seeds. Full article

This paper describes a universal method proposed by the author for the evaluative analytical calculation of the main parameters of synchronous electrical machines, including superconducting ones. Traditional methods for analytical calculation of parameters to build a phasor diagram of electrical machines require a calculation of all dimensions of the active zone, tooth-slot zone and frontal parts of armature windings. All sizes and local states of magnetic circuit saturation are necessary for the calculation of magnetic conductivities. Traditional analytical methods use, among other things, empirical formulas and non-physical coefficients and allow one to calculate only standard machines with classic tooth-slot zones and armature winding types. As a result of drawing a phasor diagram using traditional methods, the angle between the electromotive force and voltage is calculated, which is the machine’s internal parameter and has no major significance for users. The application of modern computer programs for simulation requires a preliminary analytical calculation in order to obtain all dimensions of the three-dimensional model. FEM simulation programs are expensive, require expensive high-performance computers and highly paid skilled personnel. Fast analytical techniques are also required to assess the correctness of the obtained automatic computer simulation results. The proposed analytical method makes it possible to quickly obtain all the main parameters of a newly designed machine (including superconducting ones and those of non-traditional design) without a detailed calculation of the dimensions of the tooth-slot zone and armature end-windings. The characteristic values of load angles are set according to the results of simple calculations, and the desired values, obtained via plotting, represent the inductive resistances of armature winding and inductive voltage drop across it. Results of practical significance, calculated from the voltage diagram, are as follows: the inductor’s magnetomotive force necessary to maintain the nominal load voltage value, regardless of the magnitude (including double overload) and type of the connected load, or the main dimensions of the active zone. Full article

This paper presents a microcontroller-based solution for generating real-time normal walking knee angle of a powered transfemoral prosthetic leg prototype. The proposed control algorithm was used to determine the prosthetic knee angle by utilizing seven hip angle movement features generated from only the inertia measurement unit (IMU) deployed on the prosthetic socket on the thigh of the same side. Then, a proportional–integral–derivative (PID) controller is developed to control the motor to reach the desired knee angle in real time. Furthermore, a novel parallel four-bar linkage-based master–slave validation framework combining a motion capture system was introduced to evaluate the performance of the knee angle generation on a speed-adjustable treadmill with able-bodied subjects. In the framework evaluation, 3 different walking speeds were applied to the treadmill to validate different speed adaptation capabilities of the prosthetic leg control system, precisely 50 cm/s, 60 cm/s, and 70 cm/s. Through the proposed 4-bar linkage framework, the prosthesis’s movement can simulate able-bodied subjects well with maximum RMSE never exceeding 0.27° in the swing flexion phase, 4.4° to 5.8° in the stance phase, and 1.953° to 13.466° in the swing extension phase. The treadmill results showed that the prosthetic leg is able to perform a normal walking gait following different walking speeds of the subject. Finally, a corridor walking experiment with a bypass adapter was successfully performed to examine the feasibility of real prosthetic walking situations. Full article

The surface layer determines the physical properties of aviation materials and, based on these properties, the calculation of surface energy anisotropy can be implemented. Moreover, the value of the surface energy determines the service time and the destruction of aircraft structures surface layer, while the surface layer thickness determines the distance at which this process usually takes place. In this work, a new atomically smooth crystal empirical model is built without considering the surface roughness. This model can be used to theoretically predict the surface energy anisotropy and surface layer thickness of metals and other compounds, in particular the aviation materials. The work shows that the surface layer of an atomically smooth metal, like other compounds, consists of two nanostructured layers: d(I) and d(II). Having sufficient accuracy, the proposed model would allow the prediction of aviation materials performance properties without the need for ultrahigh vacuum or other complicated theoretical methods to analyze the surfaces of nanosystem atomic structures. Full article

This study presents the results of the development of numerical models for predicting the timing of apricot flowering, including using experimental data on the emergence of plants from a state of deep dormancy. The best results of approximation of the process of accumulation of the necessary cooling in the autumn–winter period were obtained using the sigmoidal function. Models that take into account the combined effect of temperature and photoperiod on the processes of spring development showed a high accuracy of the process of accumulation of thermal units. Based on the results of testing, two models were selected with an accuracy of 3.0 days for the start of flowering and the absence of a systematic bias, which can be considered a good quality assessment These models describe well the interannual variability of apricot flowering dates and can be used to predict these dates. The discrepancy is no more than 2–4 days in 87–89% of cases. Estimates of the timing of flowering and the end of deep dormancy are very important for increasing the profitability of fruit production in the South of Russia without incurring additional costs, by minimizing the risks associated with irrational crop placement and the selection of varieties without taking into account the specifics of climate change. When constructing a system of protective measures and dates of treatments, it is also necessary to take into account the calendar dates of the shift in the development of plants. Full article

This paper proposes a small-size broadband triangular monopole chip antenna for millimeter wave band applications. Process using 0.18 μm CMOS process and antenna design using Met-al_6. Triangular patch design and feed line length analysis to achieve a better reflection coefficient and also dig three circular slots at the grounding point to achieve better impedance matching. The operating frequency of the chip antenna is 62–100 GHz below the reflection coefficient −10 dB standard, with a fractional bandwidth of 54%. The maximum gain is −0.4 dBi at 64 GHz. The efficiency is 40.9%. The overall chip size is 1.2 × 1.2 (mm²). After measurement and verification, the proposed antenna reflection coefficient is similar to the simulation trend and has better resonance. The chip antenna frequency range proposed in this article covers the 5G NR FR2 frequency band. The proposed chip antenna can be applied in related fields such as the Internet of Things, Industry 4.0, and biomedical electronics. Full article

The popularity of the online teaching model increased during the COVID-19, and virtual reality online education is now firmly established as a future trend in educational growth. Human–computer interaction and collaboration between virtual models and physical entities, as well as virtual multi-sensory cognition, have become the focus of research in the field of online education. In this paper, we analyze the mapping form of teaching information and cue information on users’ cognition through an experimental system and investigate the effects of the presentation form of online virtual teaching information, the length of the material, users’ memory of the information, and the presentation form of information cues on users’ cognitive performance. The experimental results show that different instructional information and cue presentation designs have significant effects on users’ learning performance, with relatively longer instructional content being more effective and users being more likely to mechanically remember the learning materials. By studying the impact of multi-sensory information presentation on users’ cognition, the output design of instructional information can be optimized, cognitive resources can be reasonably allocated, and learning effectiveness can be ensured, which is of great significance for virtual education research in digital twins. Full article

In this paper, the Ant-based Radial Basis Function Network (ARBFN) is proposed to determine the optimal daily dispatch of ice-storage air-conditioning systems. ARBFN is a novel algorithm that is integrated into the Ant Colony Optimization and Radial Basis Function Network. ARBFN is used to construct the function of the cost and operation for each chiller and ice-storage tank and is used to simulate the polynomial function of the cooling load and the cost of power consumption. The best learning rate in the training process is adjusted in ARBFN to improve the accuracy of constructing models for chillers and ice-storage tanks. The electricity savings are thus 4.130% on a summer day and 7.381% on a non-summer day. The results have shown that ARBFN can more accurately calculate the actual power consumption and cooling capability of each chiller and ice-storage tank. Lastly, ACO is used to calculate the daily dispatch of the ice-storage air-conditioning system. The results demonstrated the optimization of energy savings and efficiency for the operation of the ice-storage air-conditioning system. Full article

The COVID-19 pandemic exposed the vulnerability of global supply chains of many products. One area that requires improved supply chain resilience and that is of particular importance to electronic designers is the shortage of basic dual in-line package (DIP) electronic components commonly used for prototyping. This anecdotal observation was investigated as a case study of using additive manufacturing to enforce contact between premade, off-the-shelf conductors to allow for electrical continuity between two arbitrary points by examining data relating to the stock quantity of electronic components, extracted from Digi-Key Electronics. This study applies this concept using an open hardware approach for the design, testing, and use of a simple, parametric, 3-D printable invention that allows for small outline integrated circuit (SOIC) components to be used in DIP package circuits (i.e., breadboards, protoboards, etc.). The additive manufacture breakout board (AMBB) design was developed using two different open-source modelers, OpenSCAD and FreeCAD, to provide reliable and consistent electrical contact between the component and the rest of the circuit and was demonstrated with reusable 8-SOIC to DIP breakout adapters. The three-part design was optimized for manufacturing with RepRap-class fused filament 3-D printers, making the AMBB a prime candidate for use in distributed manufacturing models. The AMBB offers increased flexibility during circuit prototyping by allowing arbitrary connections between the component and prototyping interface as well as superior organization through the ability to color-code different component types. The cost of the AMBB is CAD $0.066/unit, which is a 94% saving compared to conventional PCB-based breakout boards. Use of the AMBB device can provide electronics designers with an increased selection of components for through-hole use by more than a factor of seven. Future development of AMBB devices to allow for low-cost conversion between arbitrary package types provides a path towards more accessible and inclusive electronics design as well as faster prototyping and technical innovation. Full article

The DSF (double-skin facade) system is an important element in building design and is used in adjacent spaces to control the inlet solar radiation, heat the air, reduce energy consumption, decrease the acoustics levels, and produce photovoltaic energy, among other improvements. The DSF system can, for example, be used in winter conditions to heat the air, which is then transported to non-adjacent spaces to improve the thermal comfort level and the indoor air quality that the occupants are subjected to. Smooth DSF systems, which are a focus in the literature, are subjected to higher solar radiation levels at a specific hour of the day. The semi-circular DSF system used in this work, which was built from a group of smooth DSF systems with different orientations, guarantees the reception of the highest incident solar radiation throughout the entire day. This work presents a numerical study of a new DSF system, called the semi-circular DSF. The DSF system consists of a set of 25 smooth DSFs with different orientations, each one consisting of an outer glazed surface and an inner surface provided by the outer facade of the auditorium, both separated by an air channel. In this work, the influence of the radius of the semi-circular DSF system and the opening angle of the DSF system on the thermal response of the auditorium was analysed. Thus, six auditoriums were considered: two sets of three auditoriums with radii of 5 m and 15 m, with each of the auditoriums having a different DSF opening angle (45°, 90°, and 180°). It was found that the greater the radius of the semi-circular DSF and the opening angle of the DSF system, the greater the area of its glazed surface and, consequently, the greater the availability of solar heating power. Therefore, during the occupation period, only the set of auditoriums with the largest semi-circular DSF radius managed to present acceptable levels of thermal comfort, which were verified from mid-morning until late afternoon. As for the opening angle of the DSF system, the influence was not very significant, although slight improvements in thermal comfort were noted when the value of this angle was reduced (see Case F as an example) due to the corresponding decrease in the volume of indoor air to be heated. In all auditoriums (see Case A to Case F), it was verified that the indoor air quality was acceptable for the occupants, so the airflow rate was adequately promoted by the ventilation system. Full article

Using a Central Composite Design, the extraction of bioactive compounds from red grape Băbească neagră peels was optimized by applying a conventional solvent extraction. On the anthocyanin content, total phenolic content, and antioxidant activity (using the DPPH method), the effects of extraction factors, including ethanol and citric acid concentrations, extraction temperature, and duration, were investigated. For each of the investigated parameters, a quadratic model was suggested. The maximum and minimum variables investigated in the coded form of the experimental plan are the concentrations of citric acid (0.10–2.64%), ethanol (38.06–96.93%), operating temperature (13.06–71.90 °C), and extraction time (11.36–78.63 min). The optimal mixture for recovering the most significant amount of polyphenol content and antioxidant activity was 85% ethanol, 0.85% citric acid, 52.14 min, and 57 °C. Based on the experimental approach, the anthocyanin content ranged from 1.71 to 2.74 mg C3G/g DW, the total phenolic content ranged from 24.67 to 43.97 mg/g, and the antioxidant activity ranged from 15.95 to 20.98 mM TE/g DW. Overall, it should be stressed that establishing operating factors to maximize model responses can improve the extraction process and the obtaining of red grape peel value-added extracts for creating functional food products. Full article

The objective of this study is to design a hull-mounted sonar dome of a ship using OpenFOAM with a bulbous bow effect at cruise speed in calm water. Verification and validation for the original sonar dome simulation are conducted. Next, the 1.44 million grid size is selected to study different dome lengths. By protruding the dome forward 7.5% of the ship’s length, the optimal 17% resistance reduction is achieved and is mainly caused by the pressure resistance decrease. The optimal sonar dome not only functions in the same way as a bulbous bow, but the viscous flow behaviors are also improved. The protrusion corresponding to 90 deg phase lag reduces the bow wave amplitude. The flow acceleration outside the boundary layer and ship wake velocity are higher coinciding with the much lower total resistance. A smaller flow separation and thinner boundary layer are also observed behind the sonar dome because its back slope is less steep. The high pressure covers a smaller area around the bow, and the smaller bow wave crest does not hit the ship’s flare to form high pressure. Consequently, the lower high pressure on the dome front and higher low pressure on the dome back result in the decreases in pressure resistance. The vortical structures are also improved. Full article

This article presents the constraining factors that limit the increase in the efficiency of logging production by modern multi-operation machines operating on the Scandinavian cut-to-length technology in the felling phase, namely the selection and registration of wood species. The factors for creating a complete architecture of a fully connected neural network (NN) are given. The dependence of the prediction accuracy of a fully connected NN on a test sample on the size of the training dataset, and an image of the dependence of the prediction accuracy on the number of trees in the random forest method for image classification is shown. For a fully connected NN, a sufficient number of images and a test sample size were established for training, using tree-trunk breed-class labels as target values. A selected list of trees was given, with the size of the training sample of images presenting a problem for the classification of tree trunks using the random forest method. The aim was the discovery of the optimal number of trees necessary to achieve prediction accuracy. Full article

We present a comparative study aiming to determine the most efficient multivariate model screening for the main drugs of abuse based on their ATR-FTIR spectra. A preliminary statistical analysis of selected spectra data extracted from the public SWGDRUG IR Library was first performed. The results corroborated those of an exploratory analysis that was based on several dimensionality reduction methods, i.e., Principal Component Analysis (PCA), Independent Component Analysis (ICA), and autoencoders. Then, several machine learning methods, i.e., Support Vector Machines (SVM), eXtreme Gradient Boosting (XGB), Random Forest, Gradient Boosting, and K-Nearest Neighbors (KNN), were used to assign the drug class membership. In order to account for the stochastic nature of these machine learning methods, both models were evaluated 10 times on a randomly distributed subset of the whole SWGDRUG IR Library, and the results were compared in detail. Finally, their performance in assigning the class identity of three classes of drugs of abuse, i.e., hallucinogenic (2C-x, DOx, and NBOMe) amphetamines, cannabinoids, and opioids, were compared based on confusion matrices and various classification parameters, such as balanced accuracy, sensitivity, and specificity. The advantages of each of the illicit drug-detecting systems and their potential as forensic screening tools used in field scenarios are also discussed. Full article