Automatic Capture Research Articles

Development of an Electronic Health Record Registry to Facilitate Collection of Commission on Cancer Metrics for Patients Undergoing Surgery for Breast Cancer.

Accurate and efficient data collection is a challenge for quality improvement initiatives and clinical research. We describe the development of a custom electronic health record (EHR)-based registry to automatically extract structured Commission on Cancer axillary surgery-specific metrics from a custom synoptic note template included in the operative reports for patients with breast cancer undergoing surgery. The smart functionality of our enterprise-based EHR system was leveraged to create a custom smart phrase to capture axillary surgery-specific variables. A multidisciplinary team developed structured data elements correlating to each axillary surgery-specific variable. These data elements were then included in a note template for the operative report. Each variable could be aggregated and converted into a single flat database through the EHR's reporting workbench and serve as a live, prospective registry for all users within the EHR. The final axillary surgery-specific note template in a synoptic format allowed for efficient and easy entry and automatic collection of breast cancer-specific metrics. From initial adoption in February 2021-December 2021, there were 1,254 patients who underwent breast surgery with axillary surgery. The operative notes allowed for automatic capture of metrics from 60.5% (n = 759) of patients. Data capture improved from 37.6% in the initial adoption period of 6 months to 86.2% in the last 5 months. We were able to demonstrate successful implementation of provider-driven structured data entry into EHR systems that permits automatic data capture. The end result is a custom synoptic note template and a real-time, prospective registry of breast cancer-specific Commission on Cancer metrics that are robust enough to use for quality improvement initiatives and clinical research.

Kinematic Analysis of the Underwater Undulatory Swimming Cycle: A Systematic and Synthetic Review.

The increase of low-cost technology for underwater filming has made quantitative analysis an affordable resource for swimming coaches on a frequent basis. In this context, a synthesis of the kinematic determinants of underwater undulatory swimming (UUS) seems to be lacking. The aim of the present study was to synthesise the scientific evidence on the kinematic characteristics of competitive swimmers during UUS and the main kinematic determinants of UUS performance, as well as to summarise the main methodological considerations for UUS kinematic analysis. A systematic literature search was performed through four electronic databases following the PRISMA guidelines and STROBE for evaluating the quality of the included studies. Twenty-three research studies from the first search and two from the second search were finally considered. In total, 412 competitive swimmers (321 males and 91 females) with a performance standard of international B (11%), national (51%), or regional (35%) level were analysed. Most studies focused on a two-dimensional analysis of the ventral UUS performed from a push start and filmed 6–12 m from the starting wall. Kinematic analysis of UUS included kicking parameters (kicking length, frequency, and amplitude) as well as selected segmental kinematics in 76% of studies and the analysis of UUS performance determinants in 36%. Information about the determinants of UUS performance was inconsistent due in part to inconsistencies in the definition of kinematic parameters. Further research studies where automatic motion capture systems are applied to the analysis of UUS on the aforementioned conditions should be conducted.

Tree species classification from complex laser scanning data in Mediterranean forests using deep learning

Abstract Recent advances in terrestrial laser scanning (TLS) technology have enabled the automatic capture of three‐dimensional vegetation structure at high resolution, but the scalability of using these data for large‐scale forest monitoring is limited by reliance on intensive manual data processing, including the use of stem maps generated in the field to determine tree species. New methods from data science have the capacity to automate this identification process, reducing the hurdles towards automated inventories with TLS. In particular, contemporary developments in point cloud processing methods, alongside large increases in the computing power of consumer‐level graphics processing units, provide new opportunities. Here, we apply a deep learning‐based approach, based on joint classification from multiple viewpoints for each stem, to automatically classify tree species directly from laser scanning data obtained in structurally complex Mediterranean forests. We also explore the use of data augmentation techniques to maximise performance for a fixed number of manually labelled stems. Our method does not require expensive pre‐processing such as leaf‐wood separation or quantitative reconstructions. Using modern network architectures and data augmentation techniques, and without extensive pre‐processing, we are able to achieve high overall and per‐species accuracy that is comparable or higher than in existing work while using data from a water‐limited ecosystem complicated by structural convergence and multi‐stem trees. Our findings demonstrate the power of deep learning to remove a major TLS data processing obstacle—individual species identification—and to minimise the bottleneck created by manual data labelling requirements in the use of TLS for standard forest monitoring.

Automatic classification of document resources based on Naive Bayesian classification algorithm

World Wide Web has become big as the amount of documents collection is increasing rapidly. The automatic classification of document resources based on Naive Bayesian classification algorithm is detailed in this paper. Firstly, this paper introduces the relevant theories of naive Bayes classification and the automatic document classification system. Then, a massive network academic document automatic classification system is designed and implemented. The system uses modular design, including academic document automatic capture module, academic document word document matrix processing module, ontology integration module and semantic driven classification module. Finally, based on the Naive Bayesian classification algorithm, the training set of 12 categories preset is utilized in the professional classification directory of the Ministry of education.. Experiments show that the naive Bayesian classification algorithm can effectively complete the automatic capture, processing and classification of massive academic documents, which can not only improve the classification accuracy, but also reduce the running time of automatic classification. It solves the problems of the integration of two heterogeneous ontology libraries and also the problem that the traditional word vector space cannot meet people's needs for semantic classification.

Understanding People's Perceptions of Approaches to Semi-Automated Dietary Monitoring

The respective benefits and drawbacks of manual food journaling and automated dietary monitoring (ADM) suggest the value of semi-automated journaling systems combining the approaches. However, the current understanding of how people anticipate strategies for implementing semi-automated food journaling systems is limited. We therefore conduct a speculative survey study with 600 responses, examining how people anticipate approaches to automatic capture and prompting for details. Participants feel the location and detection capability of ADM sensors influences anticipated physical, social, and privacy burdens. People more positively anticipate prompts which contain information relevant to their journaling goals, help them recall what they ate, and are quick to respond to. Our work suggests a tradeoff between ADM systems' detection performance and anticipated acceptability, with sensors on facial areas having higher performance but lower acceptability than sensors in other areas and more usable prompting methods like those containing specific foods being more challenging to produce than manual reminders. We suggest opportunities to improve higher-acceptability, lower-accuracy ADM sensors, select approaches based on individual and practitioner journaling needs, and better describe capabilities to potential users.

An algorithm for matching original experimental records based on improved CDC

Aiming at the problems such as long time and occasional errors in the generation process of the current laboratory test report, we present an automatic capture technology of general original experimental records based on fence factor. First, the read files of the day are accurately filtered by calculating the overall Hash value of file. Then, we use the improved content-defined chunking (CDC) algorithm for chunking. The improvement of CDC algorithm includes setting the unit of the sliding window as the spacing of between two lines and setting the range of the byte size in the sliding window. When the text block is completed, a string matching algorithm based on pattern string is used to complete the matching process. The string matching algorithm constructs the mapping relationship between the pattern string and data block in data block index table, and then quickly matches the pattern string <italic>P_n</italic> to corresponding data block through the data block index table. The original experimental record files of customs laboratory are used for testing. The algorithm occupies the least memory and has the largest chunking throughput.

SVBRDF Estimation Using a Normal Sorting Technique

Spatially varying bidirectional reflectance distribution functions (SVBRDFs) play an important role in appearance modeling of real-world surfaces. Automatic capture of these surface properties is highly desirable, but many techniques only partially capture these properties or use complicated setups to do so. Micro surface roughness variations are especially difficult to capture using image-based methods. In this paper, we propose a novel approach towards estimating the complete SVBRDFs of surfaces using a portable projector-camera system made of standard consumer-grade components. Our approach uses insights about the relations between the illumination and viewing geometry and captured image statistics to estimate surface reflectance properties. Our technique should be of great value to practitioners seeking to model and render the geometric and reflectance properties of complex real-world surfaces.

Construction of Automatic Acquisition System for Multichannel Electronic Communication Signals Based on Sorting Optimization Algorithm

In both the military and the civilian world, multichannel electronic communication signals are widely used. The goal of signal processing in contemporary communication systems is to capture the signal. The traditional multichannel electronic communication signal automatic capture system has a limited range of performance, which slows down the rate of capture. This study used the sorting algorithm to build an automatic acquisition system for multichannel electronic communication signals in order to address this issue. The system processes the communication signal using the quick sorting method in the sorting optimization algorithm, achieving the goal of more precisely obtaining the carrier frequency and pseudo-code phase, and resolving the issue of slow system acquisition caused by the lengthy pseudo-code period. According to the experimental findings, the improved system’s acquisition rate is 6.89% higher than the conventional system’s, ensuring efficiency and reducing processing time in real-world communication applications.

Conventional Algorithms in Sports Training Based on Fractional Differential Equations

Abstract Basketball is one of the sports that people love. This paper uses fractional differential equations to perform shot visual proofreading. At the same time, we propose a visual proofreading method for the optimal shooting angle. We extract the features of the shooting trajectory according to the distribution of corner points and edge contours of the trajectory image. So far, the automatic capture method of basketball shooting trajectory based on the fractional differential equation is completed. We found that the algorithm in this paper greatly improves the player’s shooting technique through experimental simulation research.

Passport Verification System Using RFID and WiFi Technology

The venture planned is a verification framework where the identification holder is approved through RFID innovation. RFID is an abbreviation for Radio Frequency Identification. RFID is one part of the group of Automatic Identification and Data Capture (AIDC) advancements and is a quick and solid method for recognizing pretty much any material item. This undertaking can be utilized for security reasons where it gives data about the approved people and unapproved people. This can be applied progressively frameworks as such in recording the participation, in the organizations, air terminals for getting to the travel papers, and in enterprises to realize who are approved. The visa holder would have an RFID label that contains all the identification subtleties like name, number, ethnicity, and so forth. This tag must be swiped over the per-user and the data hence read is given to an Arduino. This data is coordinated with the one put away in the Arduino, if the information matches microcontroller shows an affirmation message in any case shows a forswearing message on an LCD screen. The situation with a specific individual can likewise be gotten through a status button in the framework. Assuming the identification validation bombs the servo engine closes and blocks the individual at the passage. The information is sent remotely from hub 1 to hub 2.

Assessment of the Potential Impact of Industry 4.0 Technologies on the Levers of Lean Manufacturing in Manufacturing Industries in Morocco

To increase their productivity, industrial companies are investing in the implementation of the Lean Manufacturing (LM) approach. Based on an analysis of the value chain, the approach reduces waste between the different production processes. The scope of this concept remains limited because it is based on static data. The technologies of the industry 4.0 concept allow the collection of data in real time. In this article, we present the results of a study conducted among companies in the automotive industry based in Morocco, in order to assess the level of deployment of the technologies of the 4.0 industry concept, and then analyze the impact of these technologies on the levers and key performance indicators of the Lean manufacturing approach. We have highlighted the technologies that have the most impact, namely: ERP, machine-to-machine communication (M2M communication), AIDC (Automatic Identification and Data Capture) and data analysis. The most impacted performance indicators are: Cycle Time, Takt Time, Lead Time and OEE.

Development of an electronic health record registry to facilitate collection of Commission on Cancer (CoC) metrics for patients undergoing surgery for breast cancer.

1549 Background: Accurate and efficient data collection is a challenge for quality improvement initiatives and clinical research. We describe the development of a custom electronic health record (EHR) based registry to automatically extract structured Commission on Cancer (CoC) axillary surgery specific metrics from a custom synoptic note template included in the operative reports for breast cancer patients undergoing surgery. Methods: The “Smart” functionality of our enterprise-based EHR system was leveraged to create a custom Smart phrase to capture axillary surgery specific variables. A multidisciplinary team developed structured data elements correlating to each axillary surgery-specific variable. These data elements were then included in a note template for the operative report. Each variable could be aggregated and converted into a single flat database through the EHR’s reporting workbench and serve as a live, prospective registry for all users within the EHR. Results: The final axillary surgery-specific note template in a synoptic format allowed for efficient and easy entry and automatic collection of breast cancer specific metrics. From initial adoption in February 2021 through December 2021, there were 1,254 patients who underwent breast surgery with axillary surgery. The operative notes allowed for automatic capture of metrics from 60.5% (n = 759) of patients. Data capture improved from 37.6% in the initial adoption period of six months to 86.2% in the last five months. Capture rate in December 2021 was 98%. Conclusions: We were able to demonstrate successful implementation of provider driven structured data entry into EHR systems that permits automatic data capture. The end result is a custom synoptic note template and a real-time, prospective registry of breast cancer-specific CoC metrics that are robust enough to use for quality improvement initiatives and clinical research.

A process-specific approach in the study of normal aging deficits in cognitive control: What deteriorates with age?

Bearing in mind that cognitive control is a complex function that includes several processes, it is not clear exactly which ones deteriorate with age. In fact, controversial results have been found. For example, some studies indicate that age-related deficits are observed in proactive and not in reactive control, others show that it is reactive control that is impaired and not proactive control, and some studies find no deficits at all (e.g., Kopp, Lange, Howe, & Wessel, 2014; Xiang et al., 2016). One possible reason is that the contribution of different processes to the deterioration of cognitive control was investigated separately, i.e., without testing all processes within the same paradigm. Therefore, the main goal of the present experiment was to study the impact of normal aging on several processes related to cognitive control within the same task, which included both Simon and Spatial Stroop trials. The study focused on the following processes: generation of conflict measured by automatic response capture (i.e., stronger task-irrelevant information processing compared to task-relevant information processing); conflict detection; and control implementation (which can be reactive control, both within trials and across trials, and proactive control, as a task-set strategy). The results showed larger automatic response capture for older adults when facing a stimulus-response conflict (Simon) but not a stimulus-stimulus conflict (Spatial Stroop). Similarly, older adults also showed larger detection effects for both conflicts. However, regarding control implementation, they only showed difficulties in inhibiting the early automatic response capture (within-trial reactive control) but not reactive control across trials or proactive control. In conclusion, it seems that older adults are more affected by the presence of task-irrelevant information, especially when it comes to resolving stimulus-response conflict. However, they showed no impairments in their ability to implement cognitive control both across trials and as a task-set strategy.

Automatic Capture Processing Method of Basketball Shooting Trajectory Based on Background Elimination Technology

The analysis and prediction of the shooting trajectory can be used to partially correct the shooting. The traditional automatic basketball shooting trajectory capture algorithm has a low capture accuracy and a long capture time, and thus is incapable of displaying the shooting trajectory in real time. To address this issue, this study proposes an automatic basketball shooting trajectory capture algorithm based on background elimination. The image of the basketball shooting trajectory is captured using imaging technology; the image is then preprocessed in four steps: binary erosion, binary expansion, closing operation, and opening operation to create a smooth image. After removing the background from the preprocessed image using the background difference method, the edge contour features are extracted, the candidate target area is set based on the extraction result, and a diagonal matrix reflecting the length and width of the trajectory target is introduced to calculate the probability of the color of the area in the shooting trajectory, thereby characterizing the trajectory. The target’s size changes in two directions to capture the basketball shooting trajectory automatically. The algorithm’s simulation results indicate that it has a higher accuracy and a shorter capture time.

Research on Reconstruction of Basketball Training Action Trajectory Based on Improved K-Means Clustering Algorithm

The automatic capture and analysis of basketball game movements can guide basketball training and provide an effective method for improving the efficiency of basketball training. This paper introduces the research status of clustering methods in the field of trajectory data mining and reconstruction in detail. By analyzing the trajectory data under the constraints of the road network, the spatiotemporal characteristics of the existing trajectory clustering methods, and the deficiencies of the existing trajectory clustering methods, a new trajectory clustering method based on trajectory segmentation and spatiotemporal similarity measurement is implemented. A motion capture and reconstruction method for basketball training based on visual image K-means clustering algorithm is proposed. Multiresolution frame scanning technology is used to collect machine images of basketball training movements, and edge contour processing is performed on the collected high-resolution basketball training movement images. Feature detection uses the three-dimensional model reconstruction method to segment the basketball training action area and combines the irregular triangle network model to realize the machine vision block template matching processing of basketball training actions and capture the basketball training action in the Gaussian fuzzy affine space. In time and feature extraction, wavelet lifting technology is used to identify the ambiguity of basketball training movements, image enhancement technology is used to improve the resolution and adaptability of basketball training movement capture, and machine vision image processing methods are used to achieve basketball training movement capture optimization. The simulation results show that the method has better adaptability and higher feature recognition ability for basketball training motion capture and improves the feature extraction and adaptive capture reconstruction ability of basketball training motion.

Comparison of mean total ridge count and mean ATD angle in OSMF and oral Leukoplakia patients

Introduction: Palm prints formed once does not change throughout life and is not influenced by environment. Palmar Dermatoglyphics can indicate the development of potentially malignant and malignant lesions and help in identifying persons at high risk of developing Oral submucous fibrosis (OSMF) and Oral squamous cell carcinoma (OSSC). Materials and Methods: Dermatoglyphic patterns were collected from randomly selected 120 patients using 3M™ CSD200i. Single-digit Optical Scanner (3M™, Canada, 2015) with automatic capture mechanism was applied to capture finger prints of all the 10 fingers of patients, who were divided in control and test group with respective subgroups of leukoplakia and OSMF. Mean total ridge count and ATD angle were measured in all patients and comparison was done between control group and patients with OSMF and leukoplakia. Results: The collected data was subjected to analysis using Chi-square test for comparison between the groups. The mean ATD angle in patints with osmf is 43.38, leukoplakia is 43.53, patients without lesion but with habit is 44.78, and patients without habit is 45.65.

Design of Automatic Motion Capture Algorithm for Yao’s Long Drum Dance Based on Multieye Machine Vision

Aiming at the problems of low accuracy and long time consumption in the existing dance motion automatic capture methods, this study designs an automatic capture algorithm of Yao’s long drum dance based on multieye machine vision. The images of Yao’s long drum dance are collected by the multieye machine vision measurement system, and the image signals under different lighting conditions are processed; on this basis, by determining the dance action image threshold and analyzing the change law of action image signal, the dance action image extraction of Yao’s long drum is completed. By converting the dance action images from different angles, the Euler angle of the images from different angles is determined and fused. On this basis, the observation items of the observation part of the Yao long drum dance action image are set, and the a priori conditions and a posteriori probability of the Yao long drum dance action image preprocessing are determined, so as to obtain the best result of the dance action image, and dance action image preprocessing is completed. According to the preprocessed image, the capture algorithm of area range is designed, the remaining areas to be captured are determined by means of classification, and the automatic capture algorithm design of Yao’s long drum dance is completed. The experimental results show that the motion image captured by the automatic motion capture algorithm of Yao’s long drum dance based on multieye machine vision has high accuracy, and the capture time is long, which is feasible.

Effect of voids on fatigue damage propagation in 3D5D braided composites revealed via automated algorithms using X-ray computed tomography

The main objective of this study is to analyze the effect of voids on damage evolution in three-dimensional five-directional (3D5D) braided composites under fatigue loading. This was achieved by the combination of Micro-CT and novel image algorithms during the interruptive fatigue tests. The present methodology enables the automatic capture of the detailed sequence of events during individual voids’ coalescence to cracking. Also, the “two-step” damage classification method was used to analyze the progressive damage mechanism of 3D5D braided composites under fatigue loading. Debonding dominates the fatigue damage propagation in the material within 76.9% of fatigue life and accounts for 82.5% of all fatigue damage. The voids located at the interface of yarns were inferred to be the critical voids under fatigue loading. More significantly, the deflection of the crack front of the voids was quantified via automated algorithms. It is expected that this study can provide unparalleled quantitative data for the development of fatigue life prediction models of 3D5D braided composites with voids.

A Low-Cost and Ultralight Unmanned Aerial Vehicle-Borne Multicamera Imaging System Based on Smartphones

Newly developed oblique photogrammetry (OP) techniques based on unmanned aerial vehicles (UAVs) equipped with multicamera imaging systems are widely used in many fields. Smartphones cost less than the cameras commonly used in the existing UAV OP system, providing high-resolution images from a built-in imaging sensor. In this paper, we design and implement a novel low-cost and ultralight UAV OP system based on smartphones. Firstly, five digital cameras and their accessories detached from the smartphones are then fitted into a very small device to synchronously shoot images at five different perspective angles. An independent automatic capture control system is also developed to realize this function. The proposed smartphone-based multicamera imaging system is then mounted on a modified version of an existing lightweight UAV platform to form a UAV OP system. Three typical application examples are then considered to evaluate the performance of this system through practical experiments. Our results indicate that both horizontal and vertical location accuracy of the generated 3D models in all three test applications achieve centimeter-level accuracy with respect to different ground sampling distances (GSDs) of 1.2 cm, 2.3 cm, and 3.1 cm. The accuracy of the two types of vector maps derived from the corresponding 3D models also meet the requirements set by the surveying and mapping standards. The textural quality reflected by the 3D models and digital ortho maps (DOMs) are also distinguishable and clearly represent the actual color of different ground objects. Our experimental results confirm the quality and accuracy of our system. Although flight efficiency and the accuracy of our designed UAV OP system are lower than that of the commercial versions, it provides several unique features including very low-cost, ultralightweight, and significantly easier operation and maintenance.

Construction of weak signal's automatic capture model of mechanical equipment for intelligent manufacturing

Aiming at the problem that the existing weak signal automatic capture model fails to effectively separate the blind source signal, which leads to its poor signal capture performance, the paper designs a weak signal automatic capture model of mechanical equipment for intelligent manufacturing. On the basis of obtaining the instantaneous frequency of the equipment, the stochastic resonance theory is used to process the signal's singular value decomposition and noise reduction. By separating and detecting blind source signals, automatic capture of weak signals of mechanical equipment for intelligent manufacturing can be realised. The experimental results show that the accuracy of the designed models are all higher than 80%, the automatic capture time is less than three minutes, and the automatic capture cost is always less than 360 yuan, which shows that the model has certain practical application value.