Matching Rate Research Articles

Automated description generation for software patches

Software patches are pivotal in refining and evolving codebases, addressing bugs, vulnerabilities, and optimizations. Patch descriptions provide detailed accounts of changes, aiding comprehension and collaboration among developers. However, manual description creation poses challenges in terms of time consumption and variations in quality and detail. In this paper, we propose PatchExplainer, an approach that addresses these challenges by framing patch description generation as a machine translation task. In PatchExplainer, we leverage explicit representations of critical elements, historical context, and syntactic conventions. Moreover, the translation model in PatchExplainer is designed with an awareness of description similarity. Particularly, the model is explicitly trained to recognize and incorporate similarities present in patch descriptions clustered into groups, improving its ability to generate accurate and consistent descriptions across similar patches. The dual objectives maximize similarity and accurately predict affiliating groups. Our experimental results on a large dataset of real-world software patches show that PatchExplainer consistently outperforms existing methods, with improvements up to 189% in BLEU, 5.7X in Exact Match rate, and 154% in Semantic Similarity, affirming its effectiveness in generating software patch descriptions.

Shifting tides in cardiology fellowship: an analysis of trends and the virtual interview revolution, 2017 to 2021

Introduction This investigation aimed to delineate the trends in cardiology fellowship applications and match rates between 2017 and 2021, with a particular focus on the effect of the COVID-19 pandemic. Methods Utilizing data from the National Resident Matching Program and the American Board of Internal Medicine covering 6693 applicants, we conducted chi-square tests to assess match rate variations. IBM SPSS version 23 was used for statistical analysis. Results The study noted an increase in matched US MD applicants (from 482 in 2017 to 549 in 2021, P = 0.0001) but a decrease in their match rate (from 89.8% to 83.1%). Matched US DO applicants rose significantly from 60 in 2017 to 103 in 2021 (P = 0.0001). A decline in first-choice matches and an increase in matches beyond the third choice were observed after the shift to virtual interviews. Conclusions The study’s analysis of cardiology fellowship trends from 2017 to 2021 underscores the escalating competitiveness in this field and signals a critical need for further research.

Exploring Recent Changes to the New Urology Residency Match.

This study assesses the effects of the recent changes to the urology residency match process. We emailed an anonymous, multiple-choice survey to each candidate who applied to any of our 3 urology programs for the 2024 Urology Residency Match. Of the 433 candidates invited, 146 (33.7%) completed the survey. Of the 133 respondents who matched, 38.3% matched where they did an away subinternship (sub-I), 20.3% matched with their home program, and 91.0% matched with a program where they sent a preference signal (PS); only 8 respondents (6.0%) matched with a program where they did not complete a sub-I or send a PS. Of the 4 candidates who did not take Step 2 before submitting their application, only 1 matched. The 126 applicants who completed 3 or more sub-Is, including the home sub-I, had a higher match rate (95.2%) than the 20 applicants who completed 1 or 2 (65.0%, P < .0005). Disclosing any geographic preferences was associated with a decreased probability of matching (relative risk = 0.89, P < .05). Taking Step 2 before submitting applications and completing 3 or more sub-Is were both correlated with a higher match rate. Geographic signaling was correlated with a lower match rate. There was little benefit to applying to programs outside of those where the applicant had completed a sub-I or sent a PS. Future candidates should consider these findings early in the application process. These findings should be taken into consideration when making future changes to the application process.

The evolution and impact of the Society for Vascular Surgery Resident and Student Program

ObjectiveThere is an ongoing national shortage in the vascular surgery (VS) workforce. To increase interest in the specialty, the Society for Vascular Surgery (SVS) Resident and Student Outreach Committee (RSOC) developed a dedicated general surgery (GS) resident and medical student (MS) program at the Vascular Annual Meeting (VAM) and invested in a scholarship program to help reduce attendee expenses. This study assesses the program’s effectiveness, correlating recipient feedback with the likelihood of matching into a VS training program. MethodsRecords related to the SVS VAM GS resident and MS program from 2013 to 2023 were reviewed, focusing on attendee evaluations of the program. The program included a simulation session from 2013 to 2019. VS training program match rates among scholarship recipients were determined. The annual average match rate in VS was used to divide the survey responses into two groups: below average (BA) and above average (AA) match rate groups. Survey responses were based on a 5-point Likert scale and allowed for comments. Responses were divided into high value, strongly favoring the activity (scores 4-5), and low value (scores 1-3) categories. The survey responses from the group of years with AA match rates were compared with the group of years with BA rates. ResultsThe SVS awarded 1040 GS resident and MS travel scholarships over the 10 years assessed. Overall, applicants had a 43% success rate in receiving a scholarship. During the study period, the annual number of applicants increased, whereas the number of scholarships and match success rates significantly decreased. The average match rate into VS among scholarship recipients was 50.2%. The survey response rate was 33%. During AA match rate years, evaluations for simulation allotted time and lectures were significantly more likely to be high value compared with BA years. Simulation content and the residency fair consistently had the most favorable evaluations (>90% high value), and overall, the program had a consistently positive impact on recipients’ interest in VS (>90% high value). Trainees in the AA group were significantly more likely to provide positive comments (73% vs 55%; P < .001). Numerous recipients commented on the need for a dedicated space to interact with faculty and mentors and highlighted simulation as the standout aspect of the program. ConclusionsThe SVS VAM RSOC program is positively correlated with attendee interest in VS, with approximately 50% of scholarship recipients matching into the field. The quality of the program and the number of scholarships correlate with VS match rates. Additional investments in similar programs could help close the workforce gap.

Linkage of administrative family court care proceedings and hospital records for mothers in England: linkage accuracy and cumulative incidence of family court care proceedings after a first live birth

IntroductionLinkage of public law family court care proceedings (CP) data to all women giving birth in NHS hospitals in England allows calculation of the cumulative incidence of CP involvement for mothers with first children born. ObjectivesTo assess linkage accuracy and determine the 10-year cumulative incidence of CP after a first live birth (FLB) for population subgroups. MethodNHS England linked records for mothers in Cafcass (Children and Family Court Advisory and Support Service) involved in CP (2007-2021) to all mothers with a delivery in England using Hospital Episode Statistics (HES: 1997-21). We calculated match rates and assessed indirect evidence of potential false positive and missed links. We used survival analyses to estimate cumulative incidence of CP within 10 years overall and for five-year maternal age groups at first live birth. ResultsOf 120,937 mothers involved in CP, 6.6% (n = 8,010) were excluded due to missing postcode or date of birth, or age &lt; 15 or &gt; 50. Of the remaining 112,927 mothers, 92,891 (82.8%) were linked to a HES delivery record. Match rates were lowest for mothers with an ethnic minority background, older at first case, or residing in Greater London, but improved over time. Of 3,572,737 mothers with a FLB, 38,462 had CP involvement. The cumulative incidence of CP at 10 years from FLB was 1.31% (95% Confidence Interval [CI]; 1.29-1.32) overall and highest in mothers aged 15--19 years (6.79%, 95% CI: 6.69-6.89) and those living in the most deprived areas (2.47%, 95% CI: 2.43-2.51). ConclusionOne in 77 of all mothers and one in 15 aged less than 20 at first live birth were involved in CP within 10 years. Linkage error may underestimate the incidence of CP for mothers in London or with an ethnic minority background.

Association of Medical School Gap Year Research and Degree Programs With Otolaryngology Interview and Match Outcomes.

To investigate whether a gap year for either research or a master's degree is associated with interview offers or match outcomes among otolaryngology applicants. Using the Texas Seeking Transparency in Application to Residency (Texas STAR) database, we conducted a cross-sectional analysis of otolaryngology applicants from 2018 to 2022. Applicants were stratified based on the presence and type of gap year during medical school. Applicant characteristics, signaling, research productivity, and application costs were analyzed, with primary outcomes including number of interview offers and match status. Among 564 otolaryngology applicant respondents to the Texas STAR survey, 160 (28%) reported a gap year, including 64 (40%) applicants participating in a research year, 65 (41%) completing a Master of Public Health or Science (MPH and MSc), and 31 (19%) completing a Master of Business Administration, Education, or other degree (MBA and MEd). Gap-year applicants who completed a research year or MPH/MSc degree received more interview offers (P < .01) than MBA, MEd applicants, or those without a gap year. Applicants with a research year had the most publications, oral presentations, abstracts, posters, and research experiences (all P < .01). When controlling for USMLE scores, clerkship honors, and applications submitted, applicants completing a research year or an MPH/MSc-degree received increased interview offers (P < .01). No significant differences were seen in expenditures or match rates. Research and MPH/MSc gap years were associated with increased residency interview offers but not increased match success. Further longitudinal studies are needed to assess how yearlong experiences affect long-term career outcomes.

Oxidation protection of tri‐layer La2Zr2O7/Yb2Si2O7/SiC‐coated Cf/SiC composites at high temperature

AbstractYtterbium silicate (Yb2Si2O7) and lanthanum zirconate (La2Zr2O7) ceramic powders were synthesized by the sol–gel method. A novel tri‐layer La2Zr2O7/Yb2Si2O7/SiC environmental barrier coating was prepared on the surface of C/SiC composites to improve the service temperature of the coating (above the Si melting point, 1683 K). Results show that both Yb2Si2O7 and La2Zr2O7 ceramic powders had extremely high purity and were accompanied by a large number of nanoparticles. The tri‐layer La2Zr2O7/Yb2Si2O7/SiC coating can efficiently prevent the oxidation failure of C/SiC composites in 1773 K air environment for more than 100 h with slight weight loss of 5.71 × 10−3 g·cm−2 and the matching weight loss rate of 5.71 × 10−5 g·cm−2·h−1. No significant chemical reaction was observed between Yb2Si2O7 middle and La2Zr2O7 outer coatings during the oxidation process at 1773 K, indicating that the tri‐layer La2Zr2O7/Yb2Si2O7/SiC coating had better oxidation stability in 1773 K air environment.

A new method for individual treetop detection with low-resolution aerial laser scanned data

In the past decade, the use of three-dimensional forest information from airborne Light Detection and Ranging (LiDAR) has become widespread in forest inventories. Accurate Individual Treetop Detection (ITD) and crown boundary delineation using LiDAR data are critical for obtaining precise inventory metrics. To address this need, we introduced a novel growing tree region (GTR)-driven ITD method that utilizes canopy height models (CHM) derived from very low-resolution airborne LiDAR data. The GTR algorithm consists of three key stages: (i) preserving all height layers through incremental cutting and stacking of CHM; (ii) employing a three-layer concept to identify individual treetops; and (iii) refining the detected treetops using a distance-based filter. Our method was tested in five temperate forests across Central Europe and was compared against the widely-used local maxima (LM) search combined with an optimized variable window filtering (VWF) technique. Our results showed that the GTR method outperformed LM with VWF, particularly in forests with high canopy density. The achieved root mean square accuracies were 74% for the matching rate, 19% for commission errors, and 27% for omission errors. In comparison, the LM with the VWF method resulted in a matching rate of 71%, commission errors of 20%, and omission errors of 31%. To facilitate the application of our algorithm, we developed an R package called TREETOPS, which seamlessly integrates with the lidR package, ensuring compatibility with existing treetop-based segmentation methods. By introducing TREETOPS, we provide the most accurate open-source tool for detecting treetops using low-resolution LiDAR-derived CHM.

Vehicle Seat Adjustment System based on Body Image Recognition

A vehicle seat adjustment system based on body image recognition is designed. The system uses body image recognition algorithms to calculate the physique parameters of passengers, and automatically adjusts the vehicle seat position. Through on-site testing, the matching rate between the automatically adjusted vehicle seat position and passenger body shape reaches 98.1%, which can effectively improve the convenience and comfort of the vehicle.

Extreme Resonant Eccentricity Excitation of Stars around Merging Black-Hole Binary.

We study the dynamics of a star orbiting a merging black-hole binary (BHB) in a coplanar triple configuration. During the BHB's orbital decay, the system can be driven across the apsidal precession resonance, where the apsidal precession rate of the stellar orbit matches that of the inner BHB. As a result, the system gets captured into a state of resonance advection until the merger of the BHB, leading to extreme eccentricity growth of the stellar orbit. This resonance advection occurs when the inner binary has a nonzero eccentricity and unequal masses. The resonant driving of the stellar eccentricity can significantly alter the hardening rate of the inner BHB and produce observational signatures to uncover the presence of nearby merging or merged BHBs.

Effect of a novel artificial intelligence (AI) –enabled multi-trial matching system on patient matching using real-world data.

e13501 Background: Currently clinical research teams at sites are manually matching patients to clinical trials, where each trial in our experience takes at least 25 minutes using highly trained dedicated resources. This limits cancer patients’ clinical trial options and enrollment rates. Moreover, the lack of NGS testing results may also negatively impact matching to clinical trials in targeted therapies. PCC, a consortium of 7 of the Top 20 Pharmaceutical companies, collaborated with Massive Bio to demonstrate how cancer patients’ matching rates can be increased if patients are prescreened to multiple trials simultaneously (i.e. multi-trial matching) instead of a single trial and NGS testing results are integrated into the matching process. Methods: Massive Bio has developed a first-in-class AI-enabled matching system to extract 180 structured clinical data from medical records using computer vision and natural language processing and a recommendation system for matching patients to parameterized inclusion/exclusion (I/E) criteria from over 14,000 actively recruiting interventional clinical trials.Our analysis included a sample of 5,707 cancer patients from the Massive Bio Synergy AI real-world database, corresponding to tumor types in 23 selected trials. We developed a decision-tree algorithm for retrospective matching analysis using modeled I/E criteria and compared these results to the theoretical matching rate (TMR) for each trial based on tumor type and biomarker prevalence, extent of disease at diagnosis and prior treatment history. Results: 690 patients matched to at least one trial were matched to 1.82 times more trials in multi-trial matching; 2.10 times more potential matches were obtained with hypothetical 100% NGS testing; and 99.9% matching time was reduced with AI enabled system; key findings are summarized (Table). Conclusions: This study confirms the underutilization of NGS technology and substantial benefits of AI and NGS in cancer trial matching. Their use resulted in a nearly two-fold increase in potential patient eligibility for trials, and an unprecedented reduction in manual effort, underscoring a significant advancement in the efficiency of the clinical trial matching process. A prospective country-wide analysis is under consideration. [Table: see text]

Fueling the future of neurosurgery: increasing trends in female enrollment expanding the neurosurgical workforce from 2010 to 2019.

Regular reporting on recruitment of women into neurosurgery is a mechanism to track the progress of minority inclusion and diversity. For more than 20 years, half of US medical students have been women, yet a disproportionate minority pursue a career in neurosurgery. The authors previously published data tracking women in neurosurgery for the prior decade from 2000 to 2009, which showed an increasing match rate of women over time, from 18 women matched at the beginning of the decade to 36 matched at the end. They now present updated data on the matriculation of women into neurosurgical residencies across the most recent decade, from 2010 to 2019. Public databases from the Association of American Medical Colleges were analyzed for applicants to neurosurgical residency from 2010 to 2019. Demographic data for those matched was obtained from the American Medical Association Masterfile and analyzed for year of match and gender. Secondary outcomes included program location, age, and gap year(s) between medical school and residency. Women made up 18.8% (394/2094) of residents matched into neurosurgery from 2010 to 2019, compared to 12% during the previous decade. There was an increase in overall match rate of 2.2% per year (male + female) from 2010 to 2019, representing the predicted need for expansion of the neurosurgical workforce to meet national needs. Women made up the majority of this expansion, rising by 5.5% over the time period (p = 0.002), compared to men increasing by 1.4% over the time period (p = 0.096). The percentage of women applicants who matched was 34.4%, compared to men at 38.6% (p = 0.009). There was no significant difference in gender with regard to age, number of gap years, or program location. The number of women matching into neurosurgery has continued to increase across the last 2 decades. Despite this, there remains significant disparity between the number of men and women matching into neurosurgery. Ongoing mitigation of barriers to recruitment of women into neurosurgery is critical. The authors' data highlight the fact that women are important to fueling the expansion of the neurosurgical workforce.

Exploring the Feasibility of GPT-4 as a Data Extraction Tool for Renal Surgery Operative Notes.

GPT-4 is a large language model with potential for multiple applications in urology. Our study sought to evaluate GPT-4's performance in data extraction from renal surgery operative notes. GPT-4 was queried to extract information on laterality, surgery, approach, estimated blood loss, and ischemia time from deidentified operative notes. Match rates were determined by the number of "matched" data points between GPT-4 and human-curated extraction. Accuracy rates were calculated after manually reviewing "not matched" data points. Cohen's kappa and the intraclass coefficient were used to evaluate interrater agreement/reliability. Our cohort consisted of 1498 renal surgeries from 2003 to 2023. Match rates were high for laterality (94.4%), surgery (92.5%), and approach (89.4%), but lower for estimated blood loss (77.1%) and ischemia time (25.6%). GPT-4 was more accurate for estimated blood loss (90.3% vs 85.5% human curated) and similarly accurate for laterality (95.2% vs 95.3% human curated). Human-curated accuracy rates were higher for surgery (99.3% vs 93% GPT-4), approach (97.9% vs 90.8% GPT-4), and ischemia time (95.6% vs 30.7% GPT-4). Cohen's kappa was 0.96 for laterality, 0.83 for approach, and 0.71 for surgery. The intraclass coefficient was 0.62 for estimated blood loss and 0.09 for ischemia time. Match and accuracy rates were higher for categorical variables. GPT-4 data extraction was particularly error prone for variables with heterogenous documentation styles. The role of a standard operative template to aid data extraction will be explored in the future. GPT-4 can be utilized as a helpful and efficient data extraction tool with manual feedback.

Crater Triangle Matching Algorithm Based on Fused Geometric and Regional Features

Craters are regarded as significant navigation landmarks during the descent and landing process in small body exploration missions for their universality. Recognizing and matching craters is a crucial prerequisite for visual and LIDAR-based navigation tasks. Compared to traditional algorithms, deep learning-based crater detection algorithms can achieve a higher recognition rate. However, matching crater detection results under various image transformations still poses challenges. To address the problem, a composite feature-matching algorithm that combines geometric descriptors and region descriptors (extracting normalized region pixel gradient features as feature vectors) is proposed. First, the geometric configuration map is constructed based on the crater detection results. Then, geometric descriptors and region descriptors are established within each feature primitive of the map. Subsequently, taking the salience of geometric features into consideration, composite feature descriptors with scale, rotation, and illumination invariance are generated through fusion geometric and region descriptors. Finally, descriptor matching is accomplished by computing the relative distances between descriptors and adhering to the nearest neighbor principle. Experimental results show that the composite feature descriptor proposed in this paper has better matching performance than only using shape descriptors or region descriptors, and can achieve a more than 90% correct matching rate, which can provide technical support for the small body visual navigation task.

Interlaboratory study on real-time PCR detection and quantification of the European anglerfish, pike, and seabream parvalbumin gene

This study presents a large-scale interlaboratory comparison (ILC) aimed at detecting and quantifying DNA from two European anglerfish (Lophius budegassa, Lophius piscatorius), pike (Esox lucius) and sea bream (Spondyliosoma cantharus) using real-time qPCR. To detect amplification of the parvalbumin genetic marker, single and multiplex qPCR assays using EvaGreen® dye or TaqMan™ probes were used. Genomic DNA isolated from target fish species and an advanced DNA calibrator, gBlocks® gene fragments, were used as standards. The DNA of anglerfish, pike and sea bream as well as their mixtures were analysed together with 14 other non-target fish species. All target fish samples were correctly identified by the participating laboratories. Qualitative assessment of anglerfish and seabream DNA showed an accuracy rate of 100%, while pike DNA achieved a match rate of 99%. Validation of quantitative protocols in four different laboratories consistently achieved z-scores below 2, indicating satisfactory performance and confirming the high degree of similarity of laboratory results. Furthermore, high accuracy and efficiency were demonstrated for the quantification of anglerfish and seabream DNA by triplex qPCR using TaqMan™ probes. Regarding the selected gene marker, the major fish allergenic protein parvalbumin enables indirect detection and quantification of the allergen in the sample. Therefore, the use of proposed protocols can significantly contribute to protecting the health of consumers and to controlling the food market.Graphical abstract

Respiratory motion tracking of the thoracoabdominal surface based on defect-aware point cloud registration.

The performance of conventional lung puncture surgery is a complex undertaking due to the surgeon's reliance on visual assessment of respiratory conditions and the manual execution of the technique while the patient maintains breath-holding. However, the failure to correctly perform a puncture technique can lead to negative outcomes, such as the development of sores and pneumothorax. In this work, we proposed a novel approach for monitoring respiratory motion by utilizing defect-aware point cloud registration and descriptor computation. Through a thorough examination of the attributes of the inputs, we suggest the incorporation of a defect detection branch into the registration network. Additionally, we developed two modules with the aim of augmenting the quality of the extracted features. A coarse-to-fine respiratory phase recognition approach based on descriptor computation is devised for the respiratory motion tracking. The efficacy of the suggested registration method is demonstrated through experimental findings conducted on both publicly accessible datasets and thoracoabdominal point cloud datasets. We obtained state-of-the-art registration results on ModelNet40 datasets, with 1.584∘ on rotation mean absolute error and 0.016 mm on translation mean absolute error, respectively. The experimental findings conducted on a thoracoabdominal point cloud dataset indicate that our method exhibits efficacy and efficiency, achieving a frame matching rate of 2 frames per second and a phase recognition accuracy of 96.3%. This allows identifying matching frames from template point clouds that display different parts of a patient's thoracoabdominal surface while breathing regularly to distinguish breathing stages and track breathing.

Evaluation of the Impact of ChatGPT on the Selection of Surgical Technique in Bariatric Surgery.

With the growing interest in artificial intelligence (AI) applications in medicine, this study explores ChatGPT's potential to influence surgical technique selection in metabolic and bariatric surgery (MBS), contrasting AI recommendations with established clinical guidelines and expert consensus. Conducting a single-center retrospective analysis, the study involved 161 patients who underwent MBS between January 2022 and December 2023. ChatGPT4 was used to analyze patient data, including demographics, pathological history, and BMI, to recommend the most suitable surgical technique. These AI recommendations were then compared with the hospital's algorithm-based decisions. ChatGPT recommended Roux-en-Y gastric bypass in over half of the cases. However, a significant difference was observed between AI suggestions and actual surgical techniques applied, with only a 34.16% match rate. Further analysis revealed any significant correlation between ChatGPT recommendations and the established surgical algorithm. Despite ChatGPT's ability to process and analyze large datasets, its recommendations for MBS techniques do not align closely with those determined by expert surgical teams using a high success rate algorithm. Consequently, the study concludes that ChatGPT4 should not replace expert consultation in selecting MBS techniques.

Pilot Study: Developing Curriculum to Prepare Fourth-Year Medical Students Applying for OBGYN Residency Within the Defense Health Agency.

Obstetrics and gynecology (OBGYN) is becoming increasingly competitive among medical specialties. As a result, many medical schools have frameworks to help their students increase their competitiveness to maximize chances of a successful match. However, "boot camps" have traditionally been geared toward the transition to intern year and not to sub-internships during the fourth year of medical school. We aimed to develop a boot camp for rising fourth-year medical students planning to apply into OBGYN before the initiation of their sub-internships and interview season. Sixteen students enrolled in this course led by faculty OBGYNs at our institution. We utilized a combination of mentorship, coaching, and education to achieve applicant success. The curriculum included formal lectures, surgical skills training, and focused feedback from our applicant development committee. Our response rate was 100% and 94% for the pre-intervention and post-intervention survey, respectively. Before the intervention, the majority of participants felt either neutral (47.4%) or unprepared (21.1%) regarding their knowledge before their sub-internships. However, after the intervention, all reported feeling more prepared for their rotations. All respondents either agreed (60%) or strongly agreed (40%) that the course increased their confidence in performing well on audition rotations. Our match rate increased from 62% for the class of 2022 (before this intervention) to 75% for the class of 2023. In light of the increasing residency match competitiveness, it is crucial to investigate programs that can assist students in developing stronger applications. This reproducible intervention utilizes few resources and can be implemented at most medical schools to better support their OBGYN applicants.

Matching UAV-Based Simulated High-Resolution SAR and Real SAR Images

Abstract. Our experiment focuses on generating simulated high-resolution (HR) Synthetic Aperture Radar (SAR) images from the photogrammetric 3D model derived from Unmanned Aerial Vehicle (UAV) imagery. The goal is to match these simulated images with real SAR data of complex scenes containing vegetation, buildings, roads, and the construction of receiving antennas. Simulated SAR reflectivity map was based on ray tracing techniques.Two feature matching algorithms, namely Scale-Invariant Feature Transform (SIFT) and Oriented FAST and Rotated BRIEF (ORB) were employed for co-registration of the simulated to the real SAR images. The effectiveness of these algorithms is evaluated by their matching rates. The experiment results of the matching process highlight the superior performance of ORB over SIFT, attributed to its robustness against rotation variations and noise. ORB emerges as a versatile choice for high-resolution real and simulated SAR registration tasks.

Multi-time scale economic regulation model of virtual power plant considering multiple uncertainties of source, load and storag

A novel multi-stage time scale economic dispatch scheme is proposed for virtual power plants, taking into account the uncertainties arising from the connection of distribution network sources. This research introduces specific scheduling schemes tailored to various time scales within distribution networks, including a fuzzy optimized day ahead scheduling scheme, an intra-day scheduling scheme combined with Deep Q Network, and an adaptive optimized real-time scheduling scheme. This plan mainly considers the impact of photovoltaic output and conducts scheduling one day in advance through fuzzy optimization. In the intraday scheduling, different strategies were adopted in the study. By combining with Deep Q Network, research on scheduling for intraday demand within the power system. The analysis is conducted through rigorous modeling. Experimental tests were conducted to evaluate the performance of the proposed schemes. The day ahead dispatching primarily considers the impact of photovoltaic output and calculates the cost associated with each link in the grid under three different meteorological conditions. In the intra-day scheduling, the total costs for Scenario 1, Scenario 2, and Scenario 3 are found to be 34,724.5 yuan, 36,296.5 yuan, and 33,275.8 yuan, respectively. Notably, strategies 1 and 2 demonstrate lower costs compared to the pre-day scheduling, with the exception of Scenario 3. In real-time scheduling, considering the matching between sources and sources, the matching rate between sources and sources can be maintained at over 95%, and the stability and cost of the power grid have significantly decreased. In summary, by proposing a multi-stage time scale economic scheduling scheme, this study fully considers the uncertainty of the power supply of the distribution network access, as well as the different needs of day, day and real-time scheduling, providing an effective solution for the power dispatching of virtual power plants and providing important technical support for the reliability and economy of the power system.