Search Results (18)

In the regulatory market, it is not uncommon for ginseng radix et rhizoma (GR) to be adulterated with panacis quinquefolii radix (PR). Amid the digital transformation, this study puts forward a new method for the identification of GR adulterated with PR. Ultra-high-performance liquid chromatography–quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) was used to detect multiple batches of GR and PR to obtain mass spectrometry data. The common ions were isolated from multiple batches of GR and PR, serving as GR and PR’s “ion matrices”. Furthermore, GR and PR’s “ion matrices” were used to eliminate intersecting ion data to extract the top-100 ions as GR and PR “matrix identity cards” (MICs). Then, GR and PR’s MICs were employed as a reference for identification, yielding contrast credibility (CC) as feedback. The results indicated that leveraging the MICs of GR and PR enables efficient and precise digital identification of the two herbs: pure GR showed CC ≥ 95% when matched with GR MIC (≤2% with PR MIC), pure PR showed CC ≥ 93% with PR MIC (≤3% with GR MIC), and non-parametric analysis confirmed significant differences between groups (p < 0.01). Even in 5% PR-adulterated samples, CC ranged from 24% to 28% (avg. 25.8%) when matched with PR MIC, leading to a 26% adulteration detection threshold. Moreover, two adulterated batches were identified among ten GR blind samples, which was consistent with verification via PR-specific pseudo-ginsenoside F₁₁. This research is practically valuable for distinguishing between GR and PR, combating adulteration, and reinforcing GR quality management. It also informs the digital identification of GR via UPLC-QTOF-MS and “MICs”, contributing to the digital quality control of traditional Chinese medicines (TCMs). Full article

Vehicle-to-home (V2H) technology enables electric vehicles (EVs) to supply power to residential loads, offering enhanced energy self-sufficiency and backup capabilities. Accurate voltage regulation is essential in such systems, especially under nonlinear and time-varying load conditions. The control method for three-phase four-wire (3P4W) converters plays a vital role in addressing these challenges. In the control configuration of such systems, the non-ideal proportional-resonant (PR) controller stands out due to its ability to reject periodic disturbances. However, the comprehensive study on the discretization of this controller for digital implementation in 3P4W systems has not been available in the literature to date. This paper presents a comparative study of several discretization methods for non-ideal PR controllers. The continuous-time complete transfer function of the integral term of non-ideal PR controllers is discretized using techniques such as Forward Euler, Backward Euler, Tustin, Zero-Order Hold, and Impulse Invariance. Additionally, the discretization methods based on two discrete integrators for the non-ideal PR controller, such as Forward Euler and Backward Euler, Backward Euler and Backward Euler plus computational delay, and Tustin and Tustin, are also evaluated. In the MATLAB/Simulink platform, through evaluating the performance of the non-ideal PR controllers, which are discretized using the above discretization methods, in controlling the output voltage of the 3P4W converter in the V2H application under nonlinear load scenarios, including substantial and sudden changes in load, the discretization method Backward Euler and Backward Euler plus delay is recommended. Full article

Background: Home-based pulmonary rehabilitation (PR) is an effective alternative to center-based PR. However, not all participants exhibit sufficient therapeutic improvement, highlighting the need to identify appropriate candidates to maximize cost-effectiveness. This study aimed to identify the factors associated with favorable outcomes in home-based PR, focusing on the role of digital therapeutics (DTx). Methods: This secondary analysis used data from a randomized controlled trial. Participants with chronic respiratory disease (CRD) were divided into responders and non-responders based on a change in 6 min walk distance (6MWD) and patient-reported outcome measures (PROM) representing dyspnea and health-related quality of life. Factors such as baseline 6MWD, DTx use, and pulmonary function were analyzed for their predictive value in improving 6MWD and PROM scores. Results: Responders, particularly those using DTx, showed significantly greater improvements in 6MWD than non-responders. Participants with a baseline 6MWD under 500 m demonstrated a higher likelihood of exceeding the minimum clinically important difference in 6MWD. DTx use strongly predicted improvements in both 6MWD and PROM scores. The baseline diffusing capacity of the lungs for carbon monoxide was also a significant factor influencing improvements in the modified Medical Research Council scale. Conclusions: Responders to 8-week program of home-based PR exhibited a relatively lower baseline health status. Encouraging participants with poorer baseline health could improve adherence to PR and enhance cost-effectiveness. Additionally, improvements in 6MWD and PROM scores were associated with the use of DTx. Considering the functions of DTx, proper supervision for home-based exercise may be crucial for achieving optimal outcomes. Full article

The performance portrait method (PPM) can be characterized as a systematized digitalized version of the trial and error method—probably the most popular and very often used method of engineering work. Its digitization required the expansion of performance measures used to evaluate the step responses of dynamic systems. Based on process modeling, PPM also contributed to the classification of models describing linear and non-linear dynamic processes so that they approximate their dynamics using the smallest possible number of numerical parameters. From most bio-inspired procedures of artificial intelligence and optimization used for the design of automatic controllers, PPM is distinguished by the possibility of repeated application of once generated performance portraits (PPs). These represent information about the process obtained by evaluating the performance of setpoint and disturbance step responses for all relevant values of the determining loop parameters organized into a grid. It can be supported by the implementation of parallel calculations with optimized decomposition in the high-performance computing (HPC) cloud. The wide applicability of PPM ranges from verification of analytically calculated optimal settings achieved by various approaches to controller design, to the analysis as well as optimal and robust setting of controllers for processes where other known control design methods fail. One such situation is illustrated by an example of predictive integrating (PrI) controller design for processes with a dominant time-delayed sensor dynamics, representing a counterpart of proportional-integrating (PI) controllers, the most frequently used solutions in practice. PrI controllers can be considered as a generalization of the disturbance–response feedback—the oldest known method for the design of dead-time compensators by Reswick. In applications with dominant dead-time and loop time constants located in the feedback (sensors), as those, e.g., met in magnetoencephalography (MEG), it makes it possible to significantly improve the control performance. PPM shows that, despite the absence of effective analytical control design methods for such situations, it is possible to obtain high-quality optimal solutions for processes that require working with uncertain models specified by interval parameters, while achieving invariance to changes in uncertain parameters. Full article

This paper deals with a “digital twin” (DT) approach for processing, reprocessing, and scrapping (P/R/S) technology running on a modular production system (MPS) assisted by a mobile cyber–physical robotic system (MCPRS). The main hardware architecture consists of four line-shaped workstations (WSs), a wheeled mobile robot (WMR) equipped with a robotic manipulator (RM) and a mobile visual servoing system (MVSS) mounted on the end effector. The system architecture integrates a hierarchical control system where each of the four WSs, in the MPS, is controlled by a Programable Logic Controller (PLC), all connected via Profibus DP to a central PLC. In addition to the connection via Profibus of the four PLCs, related to the WSs, to the main PLC, there are also the connections of other devices to the local networks, LAN Profinet and LAN Ethernet. There are the connections to the Internet, Cloud and Virtual Private Network (VPN) via WAN Ethernet by open platform communication unified architecture (OPC-UA). The overall system follows a DT approach that enables task planning through augmented reality (AR) and uses virtual reality (VR) for visualization through Synchronized Hybrid Petri Net (SHPN) simulation. Timed Petri Nets (TPNs) are used to control the processes within the MPS’s workstations. Continuous Petri Nets (CPNs) handle the movement of the MCPRS. Task planning in AR enables users to interact with the system in real time using AR technology to visualize and plan tasks. SHPN in VR is a combination of TPNs and CPNs used in the virtual representation of the system to synchronize tasks between the MPS and MCPRS. The workpiece (WP) visits stations successively as it is moved along the line for processing. If the processed WP does not pass the quality test, it is taken from the last WS and is transported, by MCPRS, to the first WS where it will be considered for reprocessing or scrapping. Full article

Ginseng Radix et Rhizoma (GRR), Panacis Quinquefolii Radix (PQR), Notoginseng radix et rhizoma (NRR) and Platycodonis Radix (PR) are often confused in the material market because of similar appearances and characteristics. Moreover, chemical identification methods tend to characterize the whole herb with regard to a single or a few components, which is an inaccurate representation and does not demonstrate the effective utilization of unknown components, and the result is unconvincing. In order to strengthen quality control, improve identification efficiency, and realize digital identification at the individual level of traditional Chinese medicine (TCM), we have put forward the “matrix characteristics” of TCM, combined with a UHPLC-QTOF-MS analysis to explore and realize the digital identification of GRR, PQR, NRR, and PR. The mass spectrometry was quantized to extract common data from different batches of the same TCMs as their matrix characteristics, and the matching credibility (M) was given by matching the “matrix characteristics” with unknown Chinese medicines. The results show that within a reasonable parameter threshold range, the M of four TCMs was higher than 92.00% compared with their own “matrix characteristics”, which was significantly higher than the M ranked second. Furthermore, the digital identification of four TCMs can be successfully realized based on the UHPLC-QTOF-MS analysis and “matrix characteristics”. This has important reference significance for developing the digital identification of GRR at an individual level based on UPLC-QTOF-MS and “matrix characteristics”. Full article

Background: This study aimed to investigate the efficacy and safety of digital therapeutics (DTx), EASYBREATH, for pulmonary rehabilitation (PR) in patients with chronic respiratory diseases (CRDs). Materials and Methods: This prospective randomized controlled trial was conducted at multiple centers. Participants were randomly allocated 1:1 to the DTx group (DTxG), provided with DTx using EASYBREATH. The DTxG underwent an 8-week PR program with evaluations conducted at baseline, four weeks, and eight weeks. The control group (CG) underwent one PR session and was advised to exercise and undergo the same evaluation. The primary outcome was the change in six-minute walking distance (6MWD) over eight weeks, and secondary outcomes included changes in scores of Modified Medical Research Council (mMRC), chronic obstructive pulmonary disease assessment test (CAT), and St. George’s respiratory questionnaire (SGRQ). Results: The change in 6MWD after eight weeks demonstrated a significant difference between the DTxG and CG (57.68 m vs. 21.71 m, p = 0.0008). The change in mMRC scores (p = 0.0008), CAT scores (p < 0.0001), and total SGRQ scores (p = 0.0003) also showed a significant difference between the groups after eight weeks. Conclusions: EASYBREATH significantly improved exercise capacity, alleviated dyspnea, and enhanced the overall quality of life at eight weeks. EASYBREATH is a highly accessible, time-efficient, and effective treatment option for CRD with high compliance. Full article

We put forward and demonstrate a silicon photonics (SiPh)-based mode division multiplexed (MDM) optical power splitter that supports transverse-electric (TE) single-mode, dual-mode, and triple-mode (i.e., TE₀, TE₁, and TE₂). An optical power splitter is needed for optical signal distribution and routing in optical interconnects. However, a traditional optical splitter only divides the power of the input optical signal. This means the same data information is received at all the output ports of the optical splitter. The powers at different output ports may change depending on the splitting ratio of the optical splitter. The main contributions of our proposed optical splitter are: (i) Different data information is received at different output ports of the optical splitter via the utilization of NOMA. By adjusting the power ratios of different channels in the digital domain (i.e., via software control) at the Tx, different channel data information can be received at different output ports of the splitter. It can increase the flexibility of optical signal distribution and routing. (ii) Besides, the proposed optical splitter can support the fundamental TE₀ mode and the higher modes TE₁, TE₂, etc. Supporting mode-division multiplexing and multi-mode operation are important for future optical interconnects since the number of port counts is limited by the chip size. This can significantly increase the capacity besides wavelength division multiplexing (WDM) and spatial division multiplexing (SDM). The integrated SiPh MDM optical power splitter consists of a mode up-conversion section implemented by asymmetric directional couplers (ADCs) and a Y-branch structure for MDM power distribution. Here, we also propose and discuss the use of the Genetic algorithm (GA) for the MDM optical power splitter parameter optimization. Finally, to provide adjustable data rates at different output ports after the MDM optical power splitter, non-orthogonal multiple access—orthogonal frequency division multiplexing (NOMA-OFDM) is also employed. Experimental results validate that, in three modes (TE₀, TE₁, and TE₂), user-1 and user-2 achieve data rates of (user-1: greater than 22 Gbit/s; user-2: greater than 12 Gbit/s) and (user-1: greater than 12 Gbit/s; user-2: 24 Gbit/s), respectively, at power-ratio (PR) = 2.0 or 3.0. Each channel meets the hard-decision forward-error-correction (HD-FEC, i.e., BER = 3.8 × 10⁻³) threshold. The proposed method allows flexible data rate allocation for multiple users for optical interconnects and system-on-chip networks. Full article

In this paper, a solar and wind renewable energies-based hybrid AC/DC microgrid (MG) is proposed for minimizing the number of DC/AC/DC power conversion processes. High penetration rates of renewable energy increase MG instability. This instability can be mitigated by maintaining a balance between consumption demand and production levels. Coordination control is proposed in this study to address coordinated electricity flowing through both AC and DC links and to achieve system stability under variability of generation, load, and fault conditions. The MG adopts a bidirectional main converter that is controlled using a digital proportional resonant (PR) current controller in a synchronous reference frame. The PR controller plays a role as a digital filter with infinite impulse response (IIR) characteristics by virtue of its high gain at the resonant frequency, thereby reducing harmonics. Moreover, the applied PR controller quickly follows the reference signal, can adapt to changes in grid frequency, is easy to set up, and has no steady-state error. Moreover, the solar photovoltaic (PV)-based distribution generation (DG) is supported by a maximum power point tracker (MPPT)-setup boost converter to extract maximum power. Due to the usage of converter-connected DG units in MGs, power electronic converters may experience excessive current during short circuit faults. Fault detection is critical for MG control and operation since it empowers the system to quickly isolate and recover from faults. This paper proposed an intelligent online fault detection, diagnostic, and localization information system for hybrid low voltage AC/DC MGs using an artificial neural network (ANN) due to its accuracy, robustness, and quickness. The proposed scheme enables rapid detection of faults on the AC bus, resulting in a more reliable MG. To ensure the neural network’s validity, it was trained on various short circuit faults. The performance of the MG was evaluated using MATLAB software. The simulation findings indicate that the suggested control strategy maintains the dynamic stability of the MG, meets the load demand, and achieves energy balance as well as properly predicts faults. Full article

Nowadays, the microgrid (MG) concept is regarded as an efficient approach to incorporating renewable generation resources into distribution networks. However, managing power flows to distribute load power among distribution generators (DGs) remains a critical focus, particularly during peak demand. The purpose of this paper is to control the adopted grid-tied MG performance and manage the power flow from/to the parallel DGs and the main grid using discrete-time active/reactive power (PQ) control based on digital proportional resonant (PR) controllers. The PR controller is used to eliminate harmonics by acting as a digital infinite-impulse response (IIR) filter with a high gain at the resonant frequency. Additionally, the applied PR controller has fast reference signal tracking, responsiveness to grid frequency drift, and no steady-state error. Moreover, this paper describes the application of robust nonlinear sliding mode control (SMC)-technique-based buck–boost (BB) converters. The sliding adaptive control scheme is applied to prevent the output voltage error that occurs during DG failure, load variations, or system parameter changes. This paper deals with two distinct case studies. The first one focuses on applying the proposed control for two parallel DGs with and without load-changing conditions. In the latter case, the MG is expanded to include five DGs (with and without DG failure). The proposed control technique has been compared with the droop control and model predictive control (MPC) techniques. As demonstrated by the simulation results in MATLAB software, the proposed method outperformed the others in terms of both performance analysis and the ability to properly share power between parallel DGs and the utility grid. Full article

The Switched Reluctance Generator (SRG) has been widely studied for Wind Energy Conversion Systems (WECS). However, a major drawback of the SRG system adopting the conventional control is the slow response of the DC link voltage controller. In this paper, a Proportional Resonant (PR) control strategy is proposed to control the output voltage of the SRG system to improve the fast response. The SRG model has a high non-linearity, which makes the design of controllers a difficult task. For this reason, the important practical engineering aspect of this work is the role played by the SRG model linearization in testing the sensitivity of the PR controller performance to specific parameter changes. The characteristics of steady-state behaviors of the SRG-based WECS under different control approaches are simulated and compared. The controller is implemented on a digital signal processor (TMS320F28379D). The experimental results are carried out using a 250 W 8/6 SRG prototype to assess the performance of the proposed control compared with the traditional Proportional Integral (PI) control strategy. The experimental results show that the PR control enhances the steady-state performance of the SR power generation system in WECS. Compared to PI control, the rise and settling times are reduced by 45% and 43%, respectively, without an overshoot. Full article

Voltage source inverter (VSI) is a good candidate for grid forming microgrid because it provides constant amplitude, frequency, and sinusoidal shape voltage at point of common coupling (PCC). As the microgrid is separated from utility grid, voltage quality of the PCC is easily affected by the type of load. To ensure power quality in grid operation, a three-phase VSI providing automatic voltage compensation for unbalanced or nonlinear load is presented in this paper. To maintain voltage quality at a certain level, the Fast Fourier Transform (FFT) algorithm is embedded in a proportional-resonant (PR) controller to mitigate the total harmonic distortion (THD) at PCC. In the meantime, any change of voltage magnitude that is caused by the unbalanced load could be reduced as well. To further enhance the transient response with the change of load, a predictive current (PC) controller is integrated into the PR controller. All the control strategies are implemented by digital approach. The effectiveness of proposed controls is verified through experiments on a testbed of the three-phase stand-alone system. Full article

A/B testing is used in digital contexts both to offer a more personalized service and to optimize the e-commerce purchasing process. A personalized service provides customers with the fastest possible access to the contents that they are most likely to use. An optimized e-commerce purchasing process reduces customer effort during online purchasing and assures that the largest possible number of customers place their order. The most widespread A/B testing method is to implement the equivalent of RCT (randomized controlled trials). Recently, however, some companies and solutions have addressed this experimentation process as a multi-armed bandit (MAB). This is known in the A/B testing market as dynamic traffic distribution. A complementary technique used to optimize the performance of A/B testing is to improve the experiment stopping criterion. In this paper, we propose an adaptation of A/B testing to account for possibilistic reward (PR) methods, together with the definition of a new stopping criterion also based on PR methods to be used for both classical A/B testing and A/B testing based on MAB algorithms. A comparative numerical analysis based on the simulation of real scenarios is used to analyze the performance of the proposed adaptations in both Bernoulli and non-Bernoulli environments. In this analysis, we show that the possibilistic reward method PR3 produced the lowest mean cumulative regret in non-Bernoulli environments, which proved to have a high confidence level and be highly stable as demonstrated by low standard deviation measures. PR3 behaves exactly the same as Thompson sampling in Bernoulli environments. The conclusion is that PR3 can be used efficiently in both environments in combination with the value remaining stopping criterion in Bernoulli environments and the PR3 bounds stopping criterion for non-Bernoulli environments. Full article

The paper presents the study of a three-phase system coupling a DC power source to a power grid. This study, based on an FPGA, implements a real-time control system and digital models of the power circuit. The proposed proportional–resonant (P+R) controller with a modified structure was part of the system, which can be used as an alternative controller to traditional ones, e.g., in photovoltaic systems. Due to difficulties in implementing resonant controllers, a P+R with a new structure using a PI controller was elaborated. With an appropriate approach to the generation of phase current patterns, it is possible to set the reactive current and, thus, compensate for the reactive power. The operation of the system for typical operating conditions (e.g., system startup, change in preset load) was characterized and compared with a classical solution using a PI controller. Full article

In this paper, we propose an on-chip learning method that can overcome the poor characteristics of pre-developed practical synaptic devices, thereby increasing the accuracy of the neural network based on the neuromorphic system. The fabricated synaptic devices, based on Pr${}_{1-x}$Ca${}_x$MnO${}_3$, LiCoO${}_2$, and TiO${}_x$, inherently suffer from undesirable characteristics, such as nonlinearity, discontinuities, and asymmetric conductance responses, which degrade the neuromorphic system performance. To address these limitations, we have proposed a conductance-based linear weighted quantization method, which controls conductance changes, and trained a neural network to predict the handwritten digits from the standard database MNIST. Furthermore, we quantitatively considered the non-ideal case, to ensure reliability by limiting the conductance level to that which synaptic devices can practically accept. Based on this proposed learning method, we significantly improved the neuromorphic system, without any hardware modifications to the synaptic devices or neuromorphic systems. Thus, the results emphatically show that, even for devices with poor synaptic characteristics, the neuromorphic system performance can be improved. Full article