Inventions, Volume 8, Issue 3 (June 2023) – 16 articles

To improve accessibility, this article describes a static, four-legged walker that can be constructed from materials and fasteners commonly available from hardware stores coupled by open-source 3D-printed joints. The designs are described in detail, shared under an open-source license, and fabricated with a low-cost open-source desktop 3D printer and hand tools. The resulting device is loaded to failure to determine the maximum load that the design can safely support in both vertical and horizontal failure modes. The experimental results showed that the average vertical failure load capacity was 3680 ± 694.3 N, equivalent to 375.3 ± 70.8 kg of applied weight with the fractured location at the wood dowel handlebars. The average horizontal load capacity was 315.6 ± 49.4 N, equivalent to 32.2 ± 5.1 kg. The maximum weight capacity of a user of 187.1 ± 29.3 kg was obtained, which indicates that the open-source walker design can withstand the weight requirements of all genders with a 95% confidence interval that includes a safety factor of 1.8 when considering the lowest deviation weight capacity. The design has a cost at the bottom of the range of commercial walkers and reduces the mass compared to a commercial walker by 0.5 kg (19% reduction). It can be concluded that this open-source walker design can aid accessibility in low-resource settings. Full article

This paper presents a small-size broadband slot monopole chip antenna for millimeter wave application. Using a 0.18 μm CMOS process, through metal_1, the artificial magnetic conductor (AMC) of the metal layer increased the impedance bandwidth of the chip antenna. The additional inverted C branch was used to achieve a better reflection coefficient. By adding an AMC and inverted C branch, the operating frequency of the chip antenna went to 33.8–110 GHz below the reflection coefficient of −10 dB, and its fractional bandwidth was 103.4%. The maximum gain was −6.3 dBi at 72 GHz. The overall chip size was 1.2 × 1.2 (mm²). Through measurement and verification, the proposed antenna reflection coefficient was close to the simulation trend and had better resonance. The frequency range of the chip antenna proposed in this paper covered the 5G NR FR2 band (24.2 GHz–52.6 GHz) and W-band (75 GHz–110 GHz). The proposed chip antenna can be applied to the Internet of Things, Industry 4.0, biomedical electronics, near field sensing and other related fields. Full article

Currently, there is a need to increase the density of interconnections on printed circuit boards (PCBs). Does this mean that the only option for quality PCB manufacturing is to proportionally increase precision of equipment, or is there another way? One of the main constraints on increasing the density of PCB interconnections is posed by the transition holes. As the number of conductive layers increases, the number of vias increases and they cover a significant space on the PCB. On the other hand, reducing the size of the vias is limited by the capability of spatial alignment of the PCB stack during manufacturing. There are standards that set limits for the design of contact pads on a PCB (IPC-A-600G, IPC-6012B). However, depending on the precision of production, the contact pads may be of poor quality. This raises the issue of determining the reliability of a contact pad with defined parameters at the design stage, taking into account manufacturing capabilities. This research proposes an analytical method for evaluation of reliability of a via or plated through-hole based on calculation of its probability of production in accordance with the current standards. On the basis of the method, a model was developed both for the case of a contact pad without any conductors connected to it (nonfunctional contact pad) and for the real case with a connected conductor. The model estimates the probability of making an acceptable via for a given reliability class depending on parameters such as the conductor width (minimum permissible and usable), drilled hole diameter, and pad diameter, as well as the accuracy of the drilling operation. The analysis of the modeling results showed that for the real case, a reduction in the reliability class would insignificantly affect the probability of making an acceptable via due to the tight limitation on the connection place of the conductor and the contact pad. In conclusion, we propose an algorithm for determining the optimal parameters of teardrops to minimize the negative impact of the conductor on the reliability of the vias. Full article

Growth factors affect farm owners, environmental conditions, nutrient adaptation, and resistance to chrysanthemum diseases. Healthy chrysanthemum plants can overcome all these factors and provide farms owners with a lot of income. Chrysanthemum white rust disease is a common disease that occurs worldwide; if not treated promptly, the disease spreads to the entire leaf surface, causing the plant’s leaves to burn, turn yellow, and fall prematurely, reducing the photosynthetic performance of the plant and the appearance of the flower branches. In Korea, chrysanthemum white rust disease most often occurs during the spring and autumn seasons, when temperature varies during the summer monsoon, and when ventilation is poor in the winter. Deep neural networks were used to determine healthy and unhealthy plants. We applied the Raspberry Pi 3 module to recognize white rust and test four neural network models. The five main deep neural network processes utilized for a dataset of non-diseased and white rust leaves include: (1) data collection; (2) data partitioning; (3) feature extraction; (4) feature engineering; and (5) prediction modeling based on the train–test loss of 35 epochs within 20 min using Linux. White rust recognition is performed for comparison using four models, namely, DenseNet-121, ResNet-50, VGG-19, and MobileNet v2. The qualitative white rust detection system is achieved using a Raspberry Pi 3 module. All models accomplished an accuracy of over 94%, and MobileNet v2 achieved the highest accuracy, precision, and recall at over 98%. In the precision comparison, DenseNet-121 obtained the second highest recognition accuracy of 97%, whereas ResNet-50 and VGG-19 achieved slightly lower accuracies at 95% and 94%, respectively. Qualitative results were obtained using the Raspberry Pi 3 module to assess the performance of the seven models. All models had accuracies of over 91%, with ResNet-50 obtaining a value of 91%, VGG-19 reaching a value of 93%, DenseNet-121 reaching 95%, SqueezeNet obtaining over 95%, MobileNet obtaining over 96%, and MobileNetv2-YOLOv3 reaching 92%. The highest accuracy rate was 97% (MobileNet v2). MobileNet v2 was validated as the most effective model to recognize white rust in chrysanthemums using the Raspberry Pi 3 system. Raspberry Pi 3 module was considered, in conjunction with the MobileNet v2 model, to be the best application system. MobileNet v2 and Raspberry Pi require a low cost for the recognition of chrysanthemum white rust and the diagnosis of chrysanthemum plant health conditions, reducing the risk of white rust disease and minimizing costs and efforts while improving floral production. Chrysanthemum farmers should consider applying the Raspberry Pi module for detecting white rust, protecting healthy plant growth, and increasing yields with low-cost. Full article

In the contemporary automobile scene, environmental effect abatement is being increasingly sought; this demands a full rethinking of the entire system and entails more than just the reduction in exhaust pollutant emissions. Currently, the most popular approach is the electrification of automobiles, which significantly reduces pollution in major urban areas while simultaneously posing a new set of problems. The two types of zero-emission vehicles that are now being developed the most are hydrogen fuel cells and battery electric cars, but another option is the Hydrogen Internal Combustion Engine (HYICE) engine, which is highly advantageous in terms of pollutants, aside from Nitrogen Oxides (NOx), which can be considerably decreased. The purpose of this study is to develop a novel vehicle design that transports this type of technology into a sporting context while striving for considerable environmental benefits and integrating them into a society where the love of automobiles still has a strong following. The cutting-edge Industrial Design Structure (IDeS) methodology is used in this work, and a sample structure was created to demonstrate how the problems and technical limitations represented can be solved. The steps of the methodology are followed to shape the final product, with careful consideration given to the design of the styling component through the use of the Stylistic Design Engineering (SDE) method. With the ultimate goal of achieving sustainable driving pleasure, the study looks into whether recyclable materials can be used for the body and whether extremely light materials can be used for the chassis. Full article

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