247 results about "Detailed data" patented technology

The invention provides an urban low-altitude unmanned aerial vehicle instant distribution scheduling and path planning method considering demand prediction. The method comprises the following steps: establishing a three-dimensional environment map of an unmanned aerial vehicle distribution system by adopting a grid-topology hybrid modeling strategy based on three-dimensional urban environment map data; according to the three-dimensional environment map of the unmanned aerial vehicle distribution system, the starting point and the target point of the unmanned aerial vehicle, the optimal flight path of the unmanned aerial vehicle, the time required by the optimal path and the transportation cost are obtained by using an unmanned aerial vehicle path planning algorithm of space-time improvement A *; and according to the order data, the unmanned aerial vehicle performance parameters, the optimal flight path of the unmanned aerial vehicle, the time required by the optimal path and the transportation cost, using the CNN-LSTM-Attention order prediction model and the task allocation model to output a task allocation scheme including a virtual order and an actual order. Accurate spatial data support is provided for path planning of the unmanned aerial vehicle, the reasonability of low-altitude logistics distribution path planning is improved, and finer data support is provided for urban airspace management.

The invention relates to the technical field of self-adaptive starting, and discloses a self-adaptive starting method and system based on voltage and current monitoring, and the method comprises the steps that an MCU (Microprogrammed Control Unit) triggers an auxiliary silicon controlled rectifier and a main silicon controlled rectifier through preset starting logic to start a motor, and carries out the high-frequency sampling of current and voltage data in real time; once starting failure is detected, short-time voltage sequences and short-time current sequences before and after a failure occurrence point can be automatically captured and stored. Then, key features are extracted from the sequences, and failure causes are determined through decision tree model analysis. And based on the analysis result and the current retry times, the MCU outputs a corresponding retry strategy to ensure that the motor can be successfully started or enter a safety mode. Thus, the reliability of motor starting is improved, subsequent fault diagnosis is supported through detailed data recording, and the maintainability and safety of the system are greatly improved.

The invention relates to the technical field of geographic information data, in particular to an ecological remote sensing data processing system which comprises a remote sensing layer acquisition module, a boundary position checking module, a region coding integration module, a spatial change splicing module and an ecological trend drawing module. According to the method, by accurately matching the geographic identification information and the spatial boundary value, the coverage range and the positioning precision of the ground feature pattern spots are remarkably improved, the time information and the spatial information are effectively integrated, the continuity and the accuracy of the data are enhanced, the boundary resetting technology effectively reduces the errors of the geographic information, and the time-space continuity of the data is improved; the processing efficiency is greatly improved by constructing a continuous layer structure and optimizing a data retrieval process, the fine boundary splicing technology also allows fine tracking of ecological changes, more detailed data support is provided for ecological monitoring, the ability of ecological trend analysis is enhanced, and thus the overall effect and application value of ecological monitoring are improved.

The embodiment of the invention discloses a test sample information updating method, device and equipment based on multi-dimensional data. A specific embodiment of the method comprises the following steps: obtaining a test sample detailed data list of each piece of test sample information in a test sample information list to generate a test sample detailed data list, and obtaining a test sample detailed data list set; generating a test sample information state list set according to the list access frequency set; in response to determining that the test sample information state representing the abnormal state exists in the test sample information state list set, performing abnormal operation processing on at least one piece of test sample information representing the abnormal state to generate a processed test sample information set; and updating the processed test sample information set to the test sample storage equipment. According to the embodiment, leakage of test sample information is avoided, and the integrity and safety of the test sample information are improved.

The invention relates to the technical field of wind power energy storage, and discloses a collaborative peak regulation method and system based on a wind power energy storage system, and the method comprises the steps: collecting the detail data and SCADA data of a power generation fan, carrying out the time sequence alignment, constructing a prediction error model, calculating a standardized prediction error, constructing a hybrid prediction model, and dynamically adjusting the model parameters; a time-function double-layer decomposition strategy is constructed to calculate an energy storage attenuation value, a multi-objective optimization model is constructed in combination with the energy storage attenuation value, cross-day balance is carried out, and a charging and discharging strategy is optimized; constructing a three-channel reward function, dynamically adjusting the weight coefficient of the reward function, and automatically adjusting the weight according to the real-time state of the power grid to realize multi-target dynamic balance; the method comprises the following steps: constructing a hybrid hierarchical control execution framework, optimizing an edge layer, obtaining a wind power fluctuation rate, judging whether to trigger super capacitor pre-charging, performing model prediction control MPC optimization, realizing credible synchronization of energy storage SOC data in combination with an intelligent contract, and performing health state early warning.

The invention relates to a soil state monitoring method and system based on a sensor network, and the method comprises the steps: reasonably arranging a plurality of sensor nodes in a target soil region to form a sensor network, and comprehensively and precisely collecting soil attribute data corresponding to each node in different time periods; and the original monitoring data set can reflect the soil state in all directions. According to the method, detailed data preprocessing is carried out on an original monitoring data set, abnormal data is cleaned, error information possibly interfering analysis is effectively removed, soil attribute data of different dimensions are normalized, and a uniform and accurate data basis is provided for subsequent processing. A fusion state feature set is generated through feature fusion processing, and the soil state can be deeply described from multiple dimensions. And determining a soil state category label according to the fusion state feature set, and generating an optimization strategy to be fed back to the monitoring terminal, so that the soil state can be accurately grasped, the strategy can be dynamically adjusted, and the accuracy and reliability of soil state monitoring can be improved.

The invention discloses a social governance risk early warning large model, which comprises a data acquisition unit, an event comparison unit, an early warning analysis table generation unit, an early warning research and judgment unit, an early warning disposal unit and an interaction unit, and is characterized in that the data acquisition unit is used for generating a detailed data set of key personnel; the event comparison unit is used for generating a comparison event data set; the early warning analysis table generation unit is used for generating a key personnel comparison early warning analysis table; the early warning research and judgment unit is used for constructing an early warning research and judgment agent; the early warning processing unit is used for building an early warning processing agent; and the interaction unit is used for displaying the key personnel risk research and judgment situation overview map and the risk disposal strategy in real time, and building an intelligent interaction question and answer window through the early warning research and judgment agent and the early warning disposal agent. According to the invention, by introducing big data analysis and artificial intelligence technologies, intelligent early warning, research and judgment and disposal management of key personnel are realized, and the efficiency and level of social governance are improved.

The invention discloses an interest rate risk prevention and control method and device, electronic equipment and a storage medium, and the method and device are applied to the electronic equipment, specifically, multiple interest rate scenes based on business configuration are sequentially applied to full-amount detail data in a pre-configured financial tool table, and a detail data copy corresponding to each interest rate scene is generated; each detail data copy is stored in a financial tool table; a distributed task scheduling engine is adopted to distribute each detail data copy to a plurality of calculation nodes for parallel cash flow calculation and conversion, and cash flow data information of the financial tool table is obtained; calculating the cash flow data information to obtain a plurality of cash flow financial elements; and performing calculation according to cash flow financial elements to obtain right and interest value interest rate sensitivity. According to the scheme, the interest rate risk prevention and control information can be quickly and efficiently obtained, so that the user can perform interest rate risk avoidance operation in time according to the risk prevention and control information.

The invention relates to the technical field of functional group analysis, and discloses an adsorption material surface functional group analysis method and system based on a Gaussian function model.According to the method, proton binding isotherm data of an adsorption material under different pH conditions are obtained through an incremental titration method, and the proton binding isotherm data are input into a Gaussian function model; the method comprises the following steps: carrying out characterization analysis on different types of functional groups, fitting experimental data by using a nonlinear least square method to obtain optimized parameters, verifying the accuracy of the optimized parameters by using a preparatory test means, analyzing the proportions of various functional groups in the adsorption material based on the verified optimized parameters, and generating a surface functional group distribution map. According to the method, distribution of different functional groups is accurately analyzed through the Gaussian function model, the defect that quantitative analysis of a traditional method is not accurate is overcome, high accuracy of a result is ensured, detailed data support is provided for design and optimization of an adsorption material, and the problem that in the prior art, when multiple functional groups coexist, the detection effect is not accurate is solved.

The invention relates to the technical field of brain-computer interaction, in particular to a patient mental state assessment system for a clinician, which comprises a semantic manifold calibration module, a state trajectory projection module, a geometric curvature resolving module and an emotion transformation quantification module. According to the method, electroencephalogram data are collected and deeply analyzed, high-dimensional neural activity characteristics are converted into a visual three-dimensional state track in combination with titer and awakening degree information, continuous dynamic monitoring of the mental state of a patient is achieved, then the emotion conversion process is quantitatively analyzed according to the geometric curvature change rate of the state track, and therefore the mental state of the patient can be rapidly and accurately monitored. According to the method, rapid emotion fluctuation which is difficult to perceive in a traditional evaluation mode can be accurately recognized and marked, objective and fine data support is provided for clinical diagnosis, and the accuracy and instantaneity of mental state evaluation are remarkably improved.

The invention discloses a ground-air cooperative early warning system based on big data identification. The method comprises the following steps: firstly, dividing an area to be inspected by a cooperative system, enabling an unmanned aerial vehicle to enter a target area to start autonomous inspection after the unmanned aerial vehicle lifts off, completing data acquisition on the ground in an inspection process, carrying out primary processing on the acquired data, carrying out cross matching with a big data model which is trained in advance and deployed, and marking suspected points according to the matching degree; then the suspected point coordinates are sent to the ground intelligent auxiliary equipment, after the ground intelligent auxiliary equipment receives the suspected point coordinates, a path for going to the suspected point area is generated according to the position of the ground intelligent auxiliary equipment and an airborne map, and the ground intelligent auxiliary equipment goes to the suspected point through autonomous obstacle avoidance navigation. After the ground intelligent auxiliary equipment reaches the suspected point recognition area and within the suspected point recognition area, an airborne high-precision composite sensor is used for recognizing the suspected point and the surrounding area of the suspected point, and more detailed data are obtained; and after data processing is completed, the data is compared with a big data model, and after accurate identification of a suspected area is completed, a matching identification result is sent to the cooperative system and the unmanned aerial vehicle. And after receiving the identification result and the corresponding coordinate, the cooperative system sends a disposal instruction to the unmanned aerial vehicle according to the result type and the judgment of the worker, and the unmanned aerial vehicle disposes the suspected point. According to the method, the advantages of the unmanned aerial vehicle and the ground intelligent auxiliary equipment are maximized by using a big data model and air-ground cooperation, and guidance is provided for improving the inspection efficiency and the judgment accuracy.

The invention discloses a knowledge base construction and application method based on a large language model, and the method comprises the steps: obtaining external data, carrying out the feature extraction of the external data, obtaining entity features, and enabling the external data to comprise detailed data of intellectual property data content; the method comprises the following steps: acquiring instance entity feature associated data, matching entity features with the entity feature associated data to obtain matched associated data, and performing relationship generation on the entity features through a large model according to the matched associated data to obtain a relationship of the entity features; constructing a knowledge graph according to the entity features and the corresponding relationship, and constructing a knowledge base according to the knowledge graph; and obtaining knowledge retrieval information required by a user, performing retrieval in the knowledge base according to the knowledge retrieval information, and analyzing a retrieval result through the large model to obtain reply information of the knowledge retrieval information.

The invention provides a technical photographing system for calligraphy and painting cultural relics, and relates to the technical field of photographing and repairing of the calligraphy and painting cultural relics, and the system comprises an automatic light source adjustment unit which comprises a light source recognition module and a light source optimization module, and the light source recognition module is used for recognizing physical feature parameters of the calligraphy and painting cultural relics and optimizing the light source parameters of the calligraphy and painting cultural relics; the physical characteristic parameters comprise materials, sizes and surface characteristics of the calligraphy and painting cultural relics. According to the photographing system for the calligraphy, painting and cultural relic technology, a multi-spectral image sequence is cooperatively collected by combining multiple light sources, detailed data including an ultraviolet fluorescence image, an infrared reflection image, a light-transmitting image and a sidelight texture image can be obtained, and the light sources in the lamp set are automatically selected and combined; therefore, precise illumination adjustment for different types of calligraphy and painting cultural relics is realized, the acquisition quality of the multispectral image sequence is ensured, and the accuracy and definition of the image are improved.

The invention relates to the technical field of fault prediction, and particularly discloses a communication network fault early warning method and system based on artificial intelligence, and the method comprises the steps: firstly, deploying a distributed data collection unit at each edge node of a communication network, and monitoring the communication state of the edge nodes in real time; when the data acquisition unit detects frequency adjustment trigger conditions such as network topology change or burst traffic impact, the data acquisition unit adjusts the acquisition frequency correspondingly to obtain a more detailed data feature set. And after the collection frequency is adjusted, the edge computing node receives the data feature sets and evaluates the abnormal fluctuation feature value of each communication link, so that the network operation state of each communication link is judged. And then, the edge computing node uploads a judgment result to the central computing node, and the central computing node performs early warning response according to the result. Through the mode, the state of the communication network can be monitored and analyzed in real time, the network fault can be early warned in time, and the reliability and the stability of the communication network are improved.

This invention discloses a method, apparatus, device, and computer-readable storage medium for analyzing vintage-like indicators, relating to the field of risk data analysis technology. The method includes: acquiring underlying raw data; for each key value under the detailed primary key in the underlying raw data, calculating the wide table row information corresponding to each key value based on the detailed data corresponding to each key value in the underlying raw data, to obtain a target wide table composed of the wide table row information of each key value; upon receiving a statistical instruction for a vintage-like indicator, searching in the target wide table for each target key value corresponding to the target statistical dimension indicated by the statistical instruction, and calculating the vintage-like indicator value under the target statistical dimension according to the intermediate data corresponding to each target key value. This invention proposes an analysis scheme for vintage-like indicators, reducing the complexity of vintage indicator analysis operations and improving analysis efficiency.

A kind of department operational performance data real-time display and target dynamic benchmarking method and device belong to hospital management information technology field, to solve department operational performance data display lag, target adjustment after benchmarking state update not timely and early warning index detailed positioning efficiency low problem, the present application is by periodically obtaining department operational raw data, generates department operational index data, multi-benchmarking result, dashboard display data and early warning judgment result, and after receiving adjusted target value, corresponding benchmarking, early warning and display data are regenerated, can improve the continuity of department operational index display, target dynamic benchmarking and detailed data query, it is suitable for hospital department operational performance data display, target benchmarking, index early warning and detailed query etc. field.

The application discloses a kind of real-time summary method, device, electronic equipment and storage medium of detailed data, it is related to data processing technical field.The method comprises: obtaining different categories of detailed data generated by real-time business system;Wherein, detailed data includes at least one of the following: business data, entity data, rule data and configuration data;In response to the request instruction of target summary index, determine the candidate detailed data matched with request instruction from detailed data;Candidate detailed data is processed based on target data processing model, and target summary result matched with target summary index is obtained;Candidate detailed data and target summary result are rendered and displayed on target display page.The scheme of the application can quickly and accurately determine the summary result of detailed data, and display in the same page, to avoid the inconsistency between detailed data and summary result displayed in the same page provides basis.

The invention discloses a method for screening water quality driving factors of a long-distance water transfer project based on a machine learning method. The screening method comprises the following steps: acquiring a water body sample of the long-distance water transfer project; obtaining influence factor data as much as possible according to historical water quality characteristics and hydrogeological conditions of the water transfer project; constructing different factor input data sets according to the detailed data; a clustering analysis method and a correlation analysis method are applied to assist a Boruta algorithm to screen internal causes and external causes of water quality driving factors of different sections in a long-distance water transfer project, and the driving factors are obtained for importance sorting. According to the method, two statistical methods are coupled, meanwhile, the water quality driving factors of the long-distance water transfer project are screened in combination with a machine learning method, water quality driving internal causes and external causes of different sections can be rapidly screened out, importance ranking can be conducted on the driving factors, operability is high, and the method has certain popularization value and is worthy of popularization. Reliable technical guarantee is provided for a long-distance water transfer management department to treat sudden water pollution accidents, control water quality risks and improve water quality.

The invention discloses a template search method and device based on multi-path recall, and the method comprises the steps: receiving a keyword and a user ID input by a user, combining a vector database and ElasticSearch, and adopting a multi-path recall strategy to obtain a recall template set, the multi-path recall strategy comprising three recall paths of keyword vectorization recall, historical behavior recall and classification label recall; template detailed data are retrieved according to the recall template set, a comprehensive sorting model of dynamic weight adjustment is introduced, a comprehensive sorting score is calculated in combination with a plurality of sorting factors, recall templates are sorted and then returned, and the sorting factors comprise correlation scores, template values, top values and new time; the vector representation of the hot template is pre-calculated and cached in a vector database, and the ElasticSearch synchronously updates the index; according to the multi-path recall mechanism, the recall coverage rate is remarkably increased; and a comprehensive sorting model for dynamic weight adjustment is introduced, so that the sorting accuracy is improved.

1. The name of the design product: premium viewing graphical user interface of electronic device. 2. The use of the design product: an electronic device. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: for viewing statistical data of premium. 6. The human-computer interaction mode of the graphical user interface: the front view is the premium viewing interface, clicking the this-month or this-year button above the interface switches the statistical time; clicking the premium data card in the interface can view detailed data; clicking the four buttons below the interface can open different premium functions. 7. Other circumstances that need to be explained: XXX in the interface represents replaceable words and / or numbers and / or characters.

This invention discloses a hierarchical public data visualization retrieval system and method based on crowdsourcing analysis and data standardization. The system includes: a crowdsourcing analysis platform for receiving and reviewing feature indicators extracted from public data by expert users; a data standardization module for performing unified exchange rate conversion and reporting period standardization on financial data to ensure data comparability; an indicator calculation module for calculating individual development indicators according to specific formulas; an index generation module for generating individual development indices, regional development indices, and global development indices based on benchmark values, and generating macro-trend charts; a multi-level index database for storing multi-level data and external links; an interactive response module for responding to chart click events and drilling down to obtain detailed data; a data display module for generating the next level of charts; and a context-aware navigation module for automatically navigating to preset external information sources based on user-selected function tags and entity clicks in the charts. This invention lowers the barrier to data utilization through crowdsourcing, ensures the comparability of global data through standardization, and achieves seamless and efficient retrieval and navigation from macro trends to micro information.

This invention discloses a method and system for real-time monitoring and prediction of carbon intensity, belonging to the field of carbon emission monitoring technology. The method acquires and processes electricity-related data such as installed capacity and real-time load of each province hourly through an ETL data channel; it draws a map of China based on ECharts, dividing it into five color-level intervals according to carbon intensity values: 0-300, 301-500, 501-700, 701-900, and 901-1200 gCO2 / kWh; responding to user clicks on provinces, it displays detailed data for each province through indicator cards, circular progress charts, and one-sided bar charts; it calls a pre-trained STFCI hybrid model to predict carbon intensity hourly for the next 24 hours. This model integrates a 2-layer 128-neuron LSTM unit with an XGBoost unit with 100 trees and a learning rate of 0.1, outputting predicted values ​​after feature concatenation and a fully connected layer; the prediction results are displayed as a bar chart, marking customizable low-carbon threshold lines, highlighting low-carbon periods, and generating electricity consumption suggestions. The corresponding system includes a data interface, database, visualization, prediction, and WeChat service modules. The database adopts an InfluxDB+MySQL combined architecture, and the WeChat service module supports mobile text and image queries. The STFCI model of this invention has an average absolute error of only 12.3 gCO2 / kWh, significantly improving prediction accuracy, realizing hourly real-time monitoring and multi-dimensional visualization of carbon intensity, and providing precise decision support for power dispatching and energy conservation and emission reduction when combined with mobile services.

The application discloses a battery temperature anomaly detection method and medium. The method can include: acquiring real-time temperature sensing data of a vehicle power battery and extracting abnormal temperature sensing data; setting an abnormal temperature sensing warning level and determining the corresponding warning level according to the abnormal temperature sensing data; and extracting abnormal temperature sensing detailed data, including the abnormal temperature sensing data and the corresponding warning level. The application is based on historical data of the power battery, efficiently calculates the temperature rise rate, the temperature drop rate and the temperature difference at the same time of the battery in batches on a big data platform, sets a threshold, detects vehicles and corresponding battery modules with abnormalities in advance, reduces maintenance costs, safety accidents and improves customer experience.

The invention relates to the technical field of road and traffic engineering safety, and discloses a device for determining an underground goaf range and a detection method, the device comprises a shell, and the shell is provided with a power unit, a transmitting unit, a receiving unit, a visualization unit and a self-inspection unit; the power unit is used for driving the shell to move; the transmitting unit comprises a transmitting assembly and a converter, the transmitting assembly is used for transmitting multi-wavelength spectrum laser radar electromagnetic wave signals to the stratum of a detection target area, and the converter is electrically connected with the transmitting assembly and used for adjusting the frequency and type of the transmitting signals of the transmitting assembly; the receiving unit is used for receiving reflection electric signals of the stratum of the detection target area. According to the invention, omnibearing and intelligent nondestructive detection operation of the distribution condition of the underground goaf can be realized, the operation is simple, the anti-interference capability is strong, the detection precision is high, the operation can be carried out in various complex field severe environments, and detailed data and technical support are provided for the safety of a mining area.

The invention discloses a conference room control method and system based on an intelligent sensing smart home, and the method comprises the steps: enabling a controller to sense the meeting of a current preset conference starting condition based on smart home equipment, controlling an intelligent conference table to collect and obtain current conference voice data, and controlling an image collection device group to collect and obtain current conference video data; and then the current conference voice data and the current conference video data are respectively identified to obtain current conference summary text data and a current conference user participation degree identification result, and the current conference summary text data and the current conference user participation degree identification result are filled into the conference summary template to generate a current conference detailed data report. According to the embodiment of the invention, a plurality of intelligent home devices in the intelligent conference room can intelligently sense the conference participation condition of participants, and carry out high-safety sound and video data and video data collection after the conference begins. And when the conference is finished, the current conference detailed data report for evaluating the conference participation degree of the participants is intelligently generated, so that the intelligent and efficient processing of the conference related data is realized.

A data platform for providing large scale data discovery with near real time data cataloguing and detailed lineage. Data is received from one or more sources, and the received data is written to a data storage systems. The received data is processed at the data storage systems using sensors at the data storage systems. Metadata and data definitions associated with the data are sent to a data service in near real-time. A data catalog is generated at the data service based on the metadata and data definitions associated with the data. Data lineage for the data is created at the data service. The data catalog and data lineage are presented at a data discovery interface.

The present application provides a large-scale composite material detection method based on infrared and ultrasonic data fusion, which utilizes the infrared large-scale rapid advantage to rapidly locate the impact marks on the surface of the composite material, cooperates with ultrasonic positioning detection to obtain detailed data of the impact defects, and finally realizes rapid positioning and accurate detection of the defects of the large-scale composite material structure.

The invention discloses a blast furnace incoming iron management data processing system and method. Comprising a data display module, a query module, an export module and a data operation module. The data display module is provided with a converter molten steel receiving display unit, a molten steel receiving team statistical display unit, a blast furnace incoming iron scrap display unit and a blast furnace incoming iron team statistical display unit; and the converter molten steel receiving and displaying unit is used for displaying detailed data received by the converter, wherein the detailed data comprises converter heat, blast furnace heat, time, ladle number, molten iron components and operation information. According to the invention, by integrating blast furnace incoming iron related data and intensively displaying various types of data on different pages, unified management of the data is realized. Meanwhile, convenient data entry, modification and deletion operation and efficient query and export functions are achieved, the time and labor cost of data management are greatly saved, and the data management efficiency is improved.

Embodiments of the present application provide a kind of based on database data processing method, device and equipment and storage medium.The method comprises: obtaining the data set generated by preset business in preset use scene;Wherein, multiple business links are included in preset business, business link includes at least one of business item and business department, and the data set includes in the first time period of preset, the multiple detailed data of business department on business item;For each business department and each business item, determine the target details of business department on business item in the first time period of preset;Wherein, target details represent the multiple detailed data of business department in business item;According to the target details of each business department in each business item, build target data table;Wherein, the data stored in target data table is used to generate the data report of preset business.The method is used to improve the data processing efficiency of database.

The application relates to the field of data processing, and in particular to a method and device for reconstructing an expressway in an interchange area, equipment and a medium. The method comprises the following steps: the application accurately determines the interchange type by comprehensively considering the traffic engineering diagram of the current expressway, historical accident data, location information and reconstruction reasons, deeply analyzes the structural influence of the reconstruction on the existing road network, combines the current turning traffic volume and the long-term predicted traffic volume, scientifically formulates the geometric layout optimization scheme and the road technical index, and finally generates a targeted reconstruction plan, which effectively improves the foresight, rationality and safety of the reconstruction project, ensures that the expressway can better adapt to future traffic demand after reconstruction, optimizes the road network structure, and reduces the risk of traffic accidents, so that the effectiveness of the reconstruction is improved through comprehensive and detailed data analysis and design optimization.