Operation Method Research Articles

A Low Power R-peak Detector Clocked at Signal Sampling Rate

This paper presents a real-time, low-power R-peak detector implemented in an FPGA. It is different from other implementations as it runs at the same signal sampling rate, rather than utilizing a high clock frequency as utilized in batch processing with high throughput systems. Such implementation relies on a Savitzky-Golay filter for power line noise filtering, and on an adapted version of the Difference Operation Method (DOM) algorithm. The modification in DOM is needed in order to be able to process the data either without increasing the clock to process data in a batch fashion or unsustainably increasing latency. It uses the Savitzky-Golay Digital Differentiator, eliminating further filtering stages. The prototype was characterized using both the MIT-BIH database and Fluke Prosim 8 Vital Signal Simulator. The proposed system features a high degree of matched R-peaks even being extremely efficient regarding power dissipation. Moreover, it shows similar performance when compared to the original Difference Operation Method implementation.The whole system consumes 260- uW operating at 192-Hz in an FPGA model 10M50DAF484C7G, which belongs to the MAX10 family of Altera devices.

Comparing accuracy in guided endodontics: dynamic real-time navigation, static guides, and manual approaches for access cavity preparation – an in vitro study using 3D printed teeth

ObjectivesTo assess root canal localization accuracy using a dynamic approach, surgical guides and freehand technique in vitro.Materials and methodsAccess cavities were prepared for 4 different 3D printed tooth types by 4 operators (n = 144). Deviations from the planning in angle and bur positioning were compared and operating time as well as tooth substance loss were evaluated (Kruskal-Wallis Test, ANOVA). Operating method, tooth type, and operator effects were analyzed (partial eta-squared statistic).ResultsAngle deviation varied significantly between the operating methods (p < .0001): freehand (9.53 ± 6.36°), dynamic (2.82 ± 1.8°) and static navigation (1.12 ± 0.85°). The highest effect size was calculated for operating method (ηP²=0.524), followed by tooth type (0.364), and operator (0.08). Regarding deviation of bur base and tip localization no significant difference was found between the methods. Operating method mainly influenced both parameters (ηP²=0.471, 0.379) with minor effects of tooth type (0.157) and operator. Freehand technique caused most substance loss (p < .001), dynamic navigation least (p < .0001). Operating time was the shortest for freehand followed by static and dynamic navigation.ConclusionsGuided endodontic access may aid in precise root canal localization and save tooth structure.Clinical relevanceAlthough guided endodontic access preparation may require more time compared to the freehand technique, the guided navigation is more accurate and saves tooth structure.

Identification of a disulfidptosis-related lncRNA signature for the prognostic and immune landscape prediction in head and neck squamous cell carcinoma

PurposeDisulfidptosis, a newly identified form of cell death, is triggered by disulfide stress. Herein, a unique signature was developed based on disulfidptosis-related lncRNAs (DRlncRNAs) for the prognostic and immune landscape prediction of head and neck squamous cell carcinoma (HNSCC).MethodsTranscriptome, somatic mutation, and clinical data were acquired at The Cancer Genome Atlas database. Individuals were partitioned into training and test cohorts at a 1:1 ratio to facilitate the development of a DRlncRNA signature using the least absolute shrinkage and selection operation method. Based on the median risk score, all HNSCC individuals were stratified into the high-risk group (HRG) and low-risk group (LRG). Kaplan–Meier survival and time-dependent receiver operating characteristic (ROC) analyses were used to estimate the prognostic value, and a nomogram was generated for survival prediction. To provide a more comprehensive assessment, the tumor microenvironment, functional enrichment, immune cell infiltration, and immunotherapeutic sensitivity were explored between LRG and HRG.ResultsA DRlncRNA signature was established with 10 DRlncRNAs. The corresponding values of areas under the ROC curves for 1–, 3–, and 5–year overall survival were 0.710, 0.692, and 0.640. A more favorable prognosis was noted in the patients with lower risk, along with higher immune scores, increased immune-related functions, and immune cell infiltration, as well as improved response to the immunotherapeutic intervention in comparison with individuals at higher risk.ConclusionThese findings demonstrate that the developed DRlncRNA signature holds promise as a reliable prognostic marker and predictor of immunotherapy response in HNSCC patients.

Reversible data hiding in encrypted image with secure multi-party for telemedicine applications

Privacy protection of electronic patient information (EPI) is a crucial concern in the telemedicine applications, especially when it comes to communication between patients and doctors. In this paper, we propose a high-capacity reversible data hiding (RDH) algorithm combined with secure multi-party computation for telemedicine applications. The pixel values within a 3 × 3-size image block are divided into embedded pixels (EPs) and sampled pixels (SPs), secret data is embedded into the prediction errors of EPs and SPs in two stages. In the first stage, two edge servers predict EPs using the four SPs in the block to obtain the prediction error of EPs. The secret data is embedded into EPs through addition operation and histogram shift method. In the second stage, the prediction error of SPs is calculated as the difference between EPs and SPs, and the embedding of secret data follows the same method as used in the first stage. The experimental results demonstrate that the proposed algorithm achieves a higher embedding rate compared to classical and state-of-the-art algorithms, with an average embedding rate of 0.47bpp on the UCID dataset. Furthermore, the proposed algorithm exhibits robustness against existing attacks.

Data-driven autonomous operation of VOCs removal system

Removal of volatile organic compounds (VOCs) from the air has been an important issue in many industrial fields. Traditionally, the operation of VOCs removal systems has relied on fixed operating conditions determined by domain experts based on their expertise and intuition. In practice, this manual operation cannot respond immediately to changes in the system environment. To facilitate the autonomous operation of the system, the operating conditions should be optimized properly in real time to adapt to the changes in the system environment. Recently, optimization frameworks have been widely applied to real-world industrial systems across various domains using different approaches. The primary motivation for this study is the effective implementation of an optimization framework targeting a VOCs removal system. In this paper, we present a data-driven autonomous operation method for optimizing the operating conditions of a VOCs removal system to enhance the overall performance. An optimization problem is formulated with the decision variables denoting the parameters associated with the operating condition, the environmental variables representing the measurements for the system environment, the constraints specifying the control ranges of the parameters, and the objective function representing the system performance as determined by the operating conditions and environment. Using the previous operation data from the system, a neural network is trained to model the system performance as a function of the decision and environmental variables to approximate the objective function. For the current state of the system environment, the optimal operating condition is derived by solving the optimization problem. A case study of a targeted VOCs removal system demonstrates that the proposed method effectively optimizes the operating conditions for improved system performance without intervention from domain experts.

A Multi-Level Operation Method for Improving the Resilience of Power Systems under Extreme Weather through Preventive Control and a Virtual Oscillator.

This paper proposes a multi-level operation method designed to enhance the resilience of power systems under extreme weather conditions by utilizing preventive control and virtual oscillator (VO) technology. Firstly, a novel model for predicting time intervals between successive failures of the power system during extreme weather is introduced. Based on this, this paper proposes a preventive control method considering the system ramping and transmission constraints prior to failures so as to ensure the normal electricity demand within the system. Further, a VO-based adaptive frequency control strategy is designed to accelerate the regulation speed and eliminate the frequency deviation. Finally, the control performance is comprehensively compared under different experimental conditions. The results verify that the method accurately predicted the time of the line fault occurrence, with a maximum error not exceeding 3 min compared to the actual occurrence; also, the virtual oscillator control (VOC) strategy outperformed traditional droop control in frequency stabilization, achieving stability within 2 s compared to the droop control's continued fluctuations beyond 20 s. These results highlight VOC's superior effectiveness in frequency stability and control in power systems.

Study on Impeller Optimization and Operation Method of Variable Speed Centrifugal Pump with Large Flow and Wide Head Variation

The benefits of variable speed centrifugal pumps include high stability, a broad operating range, and adjustable input power. In water distribution systems, the pump units are increasingly using variable speed technology. The energy-saving features and operational stability of the pump station are directly impacted by the hydraulic performance and the operation strategy. In this study, CFD numerical analysis and model tests were adopted to design and evaluate the hydraulic performance of the variable speed centrifugal pump with large flow and wide head variation in Liyuzhou Pump Station. Under the premise of ensuring the wide head variation, the optimized centrifugal pump met the requirements of hump margin and efficiency in the high head zone and the cavitation margin in the low head zone. The test results demonstrated that the operational range of the variable speed centrifugal pump was successfully widened by reasonable hydraulic parameters selection and impeller optimization. The safe and efficient operational range of the variable speed unit was determined by means of taking the performance requirements of the pump’s maximum input shaft power, cavitation characteristics and pressure fluctuation into consideration. The scientific and reasonable operational path to meet the various operation needs was also investigated and determined for the pump station’s actual operation needs. A high efficiency, safe operation, and a simplified control logic were achieved by using the operational path, which makes it a reasonable potential guide for hydraulic design and operational optimization of variable speed centrifugal pumps with large flow and wide head range.

Application of V-Y advancement flap with facial artery perforator for the repair of midface skin defects

Objective: To investigate the efficacy of V-Y advancement flap with facial artery perforator for the repair of midface skin defects. Methods: A retrospective analysis was performed on 18 patients with facial skin cancer, including 11 males and 7 females, aged 65-83 years, who underwent the repair of midface skin defects using V-Y advancement flap with facial artery perforator in the Department of Head and Neck Surgery, Affiliated Cancer Hospital of Nantong University from January 2020 to April 2023. Medium, large or complex midface skin defects developed after surgical resections of the primary lesions. According to the defect site, size, location information of facial vessels, a V-Y advancement flap with appropriate shape was designed for each case. During the operation, the facial vessels and their perforators were retained in the pedicle of the flap, the facial nerve branches were dissected and protected, and the further denuded pedicle was determined according to actual amount of advancement. After the flap was advanced, the facial defect area was repaired without tension, and the anatomical positions and functions of the eyes, nose and mouth were restored as far as possible. Postoperative follow-ups were conducted to observe the survival rate of the flaps, postoperative complications, recurrences and metastases of tumors. Results: Midface defects of 3.0 cm×3.5 cm-6.5 cm×7.5 cm were observed after tumor resections, which involved one or more subregions. The sizes of the flaps were 3.5 cm×9.0 cm-7.0 cm×18.0 cm. All flaps were completely alive except for one with temporary local bruising. With following-up of 4-40 months, 5 of the 12 patients with lower eyelid and inner canthus invasions had lower eyelid ectropion, but no exposed keratitis was found; one case with poorly differentiated squamous cell carcinoma had lymph node metastasis in the submandibular region and underwent neck dissection again; no recurrence or metastasis occurred in the remaining cases. Conclusion: The V-Y advancement flap with facial artery perforator can be used to repair medium, large or complex midface skin defects, with a high survival rate, and the operation method is safe and reliable.

Research on an optimal operation model for cascade pumping stations based on simulations

AbstractCascade pumping stations (CPS) consume a large amount of energy every year in lifting districts. To obtain a reasonable and feasible operation scheme for CPS, this paper proposes an optimal operation model for CPS based on simulations. A one‐dimensional unsteady flow model of open canals was coupled with the optimal operation model of CPS, and an energy‐dominated optimization was proposed with the water level of the inlet pool as the coordinated variable. The optimization model was solved by using the catch‐up method and the nondominated sorted genetic algorithm II (NSGA‐II). The optimal operation method was validated and implemented in the first‐stage and second‐stage pumping stations of the Zuncun Irrigation Project by lifting water from the Yellow River in Shanxi province. The results showed that the proposed optimization model can reduce the energy consumption of the CPS by 4% compared with the actual operation. In addition, the optimal operation model of the CPS coupled with simulation can realize the dynamic balance of flow by stabilizing the inlet pool level to operate within a safe range. The energy consumption of the CPS can be reduced by keeping the water level of the intake pool as high a level as possible.

A Decentralized Bi-Level Decomposition Method for Optimal Operation of Electric Vehicles in Coupled Urban Transportation and Power Distribution Systems

A Decentralized Bi-Level Decomposition Method for Optimal Operation of Electric Vehicles in Coupled Urban Transportation and Power Distribution Systems

Development of Oil and Gas Condensate Fields

In the world, with the development of science, brand new technologies are being created to generate energy resources (e.g., hydrogen energy, electric car, etc.). These inventions will reduce the consumption and cost of hydrocarbon resources. This leaves oil and gas resource producers with only one option – accelerated development of oil and gas fields with low capital investment. This monograph is devoted to the development of oil and gas fields in a short period of time with a reduction in the volume of drilling operations and well quality by at least 50%. The developed technology of simultaneous split operation will give an impetus to volumetric production of hydrocarbons, accelerated field development and reduction of capital investments, as well as lead to the production of all recoverable and non-recoverable reserves from the subsoil. This monograph also delves into the technological aspects of operating wells in the Altyguyi gas condensate field. The scientific work examines the operational and technological aspects of hydrodynamic and thermohydrodynamic studies. To support this research, patents for invention No. 643 and 644, dated January 6, 2015, were obtained (application numbers 14/101317 and 15/101320). These patents cover the “Simultaneous method of separate and joint operation of several productive horizons by one chink and device for its realization” and the “Method of dual oil and gas production from one well in a multizone”. Based on the findings of the conducted analyses, studies, and calculations, the implementation of the intensification of the gas condensate field using the oil and gas DC method by one well is justified. This approach represents a first in global practice and aims to reduce capital investments and accelerate development.

A PLC-based pomegranate sprout removal device design

Aiming at the current low degree of mechanization of pomegranate sprouting tiller pruning in China, all relying on manual pruning, this paper designs a PLC-based pomegranate sprouting tiller removal machine. This machine adopts the identification method of wireless map transmission, the sprouting tiller removal method of multi-cylinder cooperative operation, and the MCGS configuration to realize the interaction between the user and the system, which realizes the displacement and angle compensation of the end-effector under complex conditions to realize the all-around accurate removal of the pomegranate sprouting tiller. The performance test and finite element analysis showed that the device could remove up to 74.62% of sprouting tillers, and the damage rate was as low as 18%. This meets the requirements of pomegranate plantations for the removal of emergent tillers.

Low-Carbon Economy Optimization of Integrated Energy System Considering Electric Vehicles Charging Mode and Multi-Energy Coupling

To realize the multi-energy coupling integrated energy system to meet the multi-class load demand and achieve the goal of low-carbon economic operation, a bi-level optimal configuration method for low-carbon economic operation of multi-energy coupling integrated energy system under different charging modes of electric vehicles is proposed. Firstly, an integrated energy system including cooling-heating-power-gas coupling is established. Then, within the level of intraday scheduling, factors such as ladder carbon trading mechanisms and different charging modes of electric vehicles are considered to achieve the lowest daily scheduling cost. In the configuration planning level, based on the daily operation cost, the equipment capacity is configured with the lowest equipment investment and annual operation costs. The bi-level model is solved by CPLEX solver and the optimal configuration scheme and scheduling results are obtained by mutual iteration. Finally, the impact of different charging methods of electric vehicles on the system economy and low-carbon performance is demonstrated through simulation examples. The results show that the charging method of electric vehicles and the carbon trading mechanism in this paper can significantly reduce carbon emissions and improve the system's operating cost. The proposed configuration approach can well achieve low-carbon economic operation of the multi-energy coupling integrated energy system.

Исследование обводненности добывающих скважин Демьяновского месторождения

The article is devoted to the problem of waterlogging of borehole products during the extraction of hydrocarbon raw materials, which arises for various reasons. This may be due to the geological structure of the field, non-compliance with the operating modes of wells, poor-quality cementing of backwater spaces, etc. Waterlogging leads to undesirable consequences: reduction of oil and gas production and occurrence of emergency situations. The problems of waterlogging of borehole products are solved using various methods: the use of chemical reagents to reduce the viscosity of water, the use of technical solutions for separating oil and water, repair and insulation works, etc. The Demyansk oil field is considered: its geological features, geological exploration, the main indicators of well operation. The analysis of the dynamics of well flooding and a comparison of the design and actual indicators of the development of the Demyanovskoye field as of 01.01.2017 are presented. The actual dynamics of well flooding is also presented, the reasons for the rapid flooding of the production of wells of the Demyanovsky place of birth are considered. As a result of the analysis of the actual data obtained during the operation of the field, it was established that the main reason for the rapid flooding of the reservoir production of the field is the transfer of wells to a mechanized method of operation, which, in turn, leads to an increase in depression on the formation. It is concluded that the forecast indicators of well flooding calculated on the hydrodynamic model differ significantly from the real ones, and attention is also drawn to the need to select the optimal depression when transferring wells to a mechanized production method to prevent rapid product flooding.

Design and Simulation of Autonomous Up-and-down System for Transmission Line Live Operation Robot with the UAV Assistance

Aiming at the current bottleneck problem that restricts the practical application of robot system engineering in transmission line live operation, in order to improve the on-line and off-loading efficiency of live working robots on transmission lines and improve the practical level of the robot system as a whole, this paper proposes a design and operation method of autonomous on-line and off-loading mechanism of double-arm live working robots based on UAV assistance. Firstly, the realization process of autonomous up-and-down of the robot was analyzed, based on which the structure of the auxiliary hook of the up-and-down system and the lifting winch were designed. Then, the force analysis was carried out on the up-and-down process of the robot, and the appropriate winch drive motor was selected through theoretical calculation. In order to ensure the rationality of the up-and-down process, the operation motion planning was carried out on the up-and-down of the robot. Stress analysis and simulation were carried out on the maximum load bearing point of the auxiliary hook and the walking wheel mechanical arm under different states, and the results showed that the hook and the robot arm could meet the requirements of the robot loading and unloading, and the whole robot loading and unloading system was designed reasonably. Compared with the traditional loading and unloading system designed in this paper, the loading and unloading efficiency could be improved. It has important theoretical significance for the development of the physical system of robot uplink and down.

Robust Operation of Flexible Distribution Network With Large-Scale EV Charging Loads

The increasing integration of electric vehicles (EVs) significantly challenges the efficient operation of distribution networks. With the rapid development of power electronic devices represented by soft open point (SOP), flexible distribution networks (FDNs) provide a promising opportunity for integrating large-scale EVs. In this paper, a robust operation method is proposed to improve the economy of EVs and ensure the flexible operation of FDN. First, an EVs-aggregator (EVs-AGG) model is formulated to incorporate diverse charging behaviors. The EVs-AGG is efficiently integrated into FDN through the DC link of multi-terminal SOP. Then, optimal operation strategies are obtained by coordinating EVs charging/discharging power with the regulation of multi-terminal SOP. Furthermore, considering the uncertainties of EVs and photovoltaics, a robust operation framework is established to deal with uncertainties. Finally, case studies based on a practical distribution network indicate that through the interactive power regulation between multi-terminal SOP and EVs-AGG, the proposed method alleviates the negative impacts caused by large-scale EVs integration and improves the operational flexibility of FDN.

A bi-layer optimization method of the grid-connected microgrid based on the multi-strategy of the beluga whale algorithm

Endeavoring to enhance the penetration rate of renewable energy sources, concurrently ensuring economic and operational stability, this study proposes a novel bi-layer optimization method of the wind–solar-storage AC/DC microgrid (MG). First, by incorporating a superordinate electric and seasonal hydrogen hybrid energy storage system (E&amp;amp;SHESS), the topology structure of the microgrid is established. Subsequently, to rectify the intrinsic limitations of the conventional beluga whale optimization (BWO) algorithm, this paper proposes a multi-strategy hybrid improvement to BWO (MHIBWO). This innovative improvement integrates an MTent strategy, a step size adjustment mechanism, and a crisscross strategy. Then, constructing a bi-layer iterative model based on the topology, annual net income and grid-connected friendliness are introduced as optimization objectives for the outer and inner layers, respectively, utilizing MHIBWO and CPLEX for resolution. Through a nested iteration of the two layers, the model outputs the capacity scheme with the best performance of economy and stability. Finally, the simulation unequivocally demonstrated the superiority of MHIBWO and the model proposed. In addition, based on the real data of the Elia power station, the validity of the method in operation is tested using the fuzzy C-means algorithm (FCMA) to extract and aggregate typical days, thereby presenting a sophisticated solution for the field of microgrids optimization configuration.

Health Information Technology 기반 국내외 의료용 마약류 모니터링 시스템 비교 분석

This study was conducted to propose ways to improve the domestic system based on a comparative analysis of domestic and foreign Health Information Technology (HIT) system using cases to prevent misuse and abuse of controlled substances. Korea, the United States, and Australia were selected as the countries to be investigated as representative examples of nationwide use of HIT. Literature data was collected from the official website of the system operating organization and major literature databases and search engines such as Pubmed and Google Scholar using the name of each country's HIT system as a keyword. We focused on analyzing the purpose of system operation, target drugs, information collection method, system operation method, and compensation to system users. Korea’s Narcotics Information Management System (NIMS) is the only system that can track the serial numbers of controlled substances in connection with prescription and dispensing records, and is designed and operated with a focus on regulatory purposes to improve legal compliance. NIMS had a relatively long reporting cycle, so there were limitations in checking the latest controlled substances prescription and dispensing records. It was also the only system in which pharmacists did not have the authority and role to check and monitor prescription records. In order to effectively prevent misuse and abuse of controlled substances, the reporting cycle must be shortened by switching to a real-time monitoring system including nonreimbursement medications. In addition, there is a need to guarantee pharmacists the authority to request prescription records before dispensing and the roles that accompany this.

Prediction of bio-oil yield by machine learning model based on 'enhanced data' training

Bio-oil is widely used and has great application potential. With the development of artificial intelligence, machine learning has been gradually applied in the field of biomass, the data augmentation method is a common operation method for training models in the field of computer or data processing. In this study, the concept of 'enhanced data' was proposed for the first time. According to the composition characteristics of biomass raw materials, the sample data were divided into three different sample sets. Based on the light gradient boosting machine (Light GBM) and deep neural network (DNN) algorithm, a prediction model of bio-oil yield was established. Combined with the analysis of partial correlation, the influence of 'enhanced data' on the prediction accuracy of the model was explored. The results showed that the prediction accuracy of the model was improved to a certain extent after adding 'enhanced data'. The Light GBM model was more suitable for predicting bio-oil yield, and the Light GBM _ c model performed best, with R2 of 0.894, MAE of 3.622, and RMSE of 4.445. At the same time, this study also has certain reference significance for other prediction studies in the field of biomass thermochemical conversion.

Reagent dosage inference based on graph convolutional memory perception network for zinc roughing flotation

In froth flotation, the precise presetting of reagent dosage is crucial for enhancing mineral recovery and flotation efficiency. Considering that the manual operation method is susceptible to some subjective factors, many machine vision-based intelligent reagent dosage presetting approaches are developed. However, prevailing presetting methods primarily rely on empirical knowledge, and ignore the potential intelligent reasoning processes, resulting in a suboptimal flotation performance. In this paper, a reagent dosage inference method based on a graph convolutional memory perception network is proposed, which can leverage the power of both empirical knowledge and neural network to deduce the optimal reagent dosages. This method constructs a memory unit stored with representative operation data, which can be served as a reservoir of empirical knowledge, facilitating dosage inference by referencing relevant data according to the current flotation condition. Subsequently, a graph convolutional neural network is developed to acquire the logical connections between reagent dosage and key parameters of the flotation process. Finally, with the guidance of empirical knowledge, a multi-head attention perception module is employed to deduce the optimal reagent dosage according to the current flotation condition and the acquired logical connection. The effectiveness of the proposed method has been validated in the experiment. Compared to other methods, the proposed method obtains more accurate inference results, and its inferred reagent dosage achieves more satisfactory flotation effect.