This dataset contains 91 computed tomography pulmonary angiograms positive for pulmonary embolism. At least one experience radiologist has segmented all clots in each of the scans. The dataset was originated for the ISBI challenge cad-pe.

Data Description: Fire Incident data includes all fire incident responses. This includes emergency medical services (EMS) calls, fires, rescue incidents, and all other services handled by the Fire Department. All runs are coded according to classification: for EMS, this includes ALS (advanced life support); BLS (basic life support); etc.

Data Creation: This data is created when a run is entered into the City of Cincinnati’s computer-aided dispatch (CAD) database.

Data Created By: The source of this data is the City of Cincinnati's computer aided dispatch (CAD) database.

Refresh Frequency: This data is updated daily.

CincyInsights: The City of Cincinnati maintains an interactive dashboard portal, CincyInsights in addition to our Open Data in an effort to increase access and usage of city data. This data set has an associated dashboard available here: https://insights.cincinnati-oh.gov/stories/s/6jrc-cmn5

Data Dictionary: A data dictionary providing definitions of columns and attributes is available as an attachment to this dataset.

Processing: The City of Cincinnati is committed to providing the most granular and accurate data possible. In that pursuit the Office of Performance and Data Analytics facilitates standard processing to most raw data prior to publication. Processing includes but is not limited: address verification, geocoding, decoding attributes, and addition of administrative areas (i.e. Census, neighborhoods, police districts, etc.).

Data Usage: For directions on downloading and using open data please visit our How-to Guide: https://data.cincinnati-oh.gov/dataset/Open-Data-How-To-Guide/gdr9-g3ad

Disclaimer: In compliance with privacy laws, all Public Safety datasets are anonymized and appropriately redacted prior to publication on the City of Cincinnati’s Open Data Portal. This means that for all public safety datasets: (1) the last two digits of all addresses have been replaced with “XX,” and in cases where there is a single digit street address, the entire address number is replaced with "X"; and (2) Latitude and Longitude have been randomly skewed to represent values within the same block area (but not the exact location) of the incident.

Note for access: The data is available to anyone interested, but in order to monitor access, we ask that interested users request access by logging in by using the account of their academic institution, selecting the files they want, and clicking "Request Access" If you do not have access through your institution, please contact us by clicking "Contact Owner", enter your email address, and mention the list of files you need. In both cases, please include a note stating your institution and your purpose for using the data. This dataset contains the point cloud files, the resulting airfoil B-splines, connectors, surface meshes, and surface CAD files for the three blades presented in the paper "Transforming Laser-Scanned 750 kW Turbine Surface Geometry Data into Smooth CAD for CFD Simulations," which correspond to the three blades of the WINSENT test site. In this dataset, the blades are named according to the numbers identified on the tip of each physical blade: 008, 022, and 025, corresponding to blades A, B, and C, respectively, in the paper. Note: each blade was processed independently by the script, and as such, there will be small differences at the root. This means that the match between the blade root and the hub attachment point should be adjusted individually for each blade prior to simulation. Also, note that the blades are aligned along the z-axis, and the tower was thus tilted equivalently to the shaft axis; it is likely necessary to untilt the whole turbine prior to simulation. Additionally, note that the 0-pitch angle does not match the angle in the x-y plane in the given blade geometries. To have the blade in the almost (should be better than +/- 0.5°) proper 0° pitch position, you should rotate the blade by -7.5° around the z-axis. The explanations for the individual files are provided in the accompanying file descriptions. Supplementary information is also given here for convenience. The most accurate reconstructions of the blades are those with the closed trailing edge. These reconstructions closely adhere to the flat and slightly rounded trailing edge observed on the physical blades and from the scan data. The FreeCAD files include surfaces generated from 193 original 3D-smoothed B-splines created by the splprep package in Python, as part of the automated reconstruction, interpolation, and smoothing program described in the paper. Both the FreeCAD and .iges CAD files are recognized as the official blade geometries for the WINSENT wind turbines. The differences between the closed and open trailing edge versions of the provided blade sufaces are localized to the actual trailing edge and do not perceptibly influence the trailing edge thickness. To facilitate the use of the open trailing edge CAD data, a surface being only the trailing edge itself is also provided. For those interested in CFD or generating meshes of the turbine blades, the Plot3D structured and STL surface meshes of the blade (with the last 0.2% of the blade radius cut off and left as a hole) generated directly from the splprep B-splines from the developed software are available. Alternatively, the same data is also provided as a series of Pointwise connectors. Both the Plot3D and connectors are in ASCII format, whereas STL is in binary format. For those wanting to vary the level of smoothing used in the 3D-smoothing step, the B-splines prior to 3D-smoothing are also provided in Python's Pickle format. There are two source cloud datasets given: A) The original clouds from the laser scanning campaign, with most surrounding artifacts removed but without any modifications to the point data; these clouds are in ASCII format (.txt), compressed as bz2 tar archives. The first three columns provide x, y, z coordinates, and the fourth column the intensity of the laser reflection, which is necessary for realigning the scans using the targets that were placed on the blade surfaces. See the origData_ScanCampaignBladeArrangement.pdf file to see which scan file corresponds to which blade and side. The cloud file names beginning with Friday are for all pressure and suction side scans, and those beginning with Monday are for all leading and trailing edge scans. Note that for the LE and TE scans, the blades were slightly bent under their own weight and in different directions for each edge. No bending was observed in the PS and SS scans. B) The manually preprocessed clouds for each of the three blades. Preprocessing includes unbending of the leading and trailing edge clouds, removal of any non-blade artifacts, aligning/merging of the clouds for the suction and pressure sides to yield only one such cloud per blade, the division of the leading and trailing edge clouds at approximately the leading and trailing edges themselves, and finally, the separate treatment of the tip portion to eliminate the need for automatic alignment at the tip. These clouds are in CloudCompare format (.bin) because the automatic treatment by the developed software was partially conducted using the CloudComPy API. Notes about the WINSENT test site and its data This repository is meant to contain geometric data of the WINSENT turbines: the tower and hub data was closely approximated using a partial laser scan and photos of the standing Northern wind turbine while the blades come from a very careful reconstruction of the Southern turbine's blades. At the time of writing this document, in January 2024, both Northern and Southern turbines are identical by design, and the differences between their blades are expected to lie within the tolerances seen between the three blades of the Southern turbine. For all data coming from the sensors installed on-site, please register and log in here: https://winsent-gui.zsw-bw.de/ For the positions of the two turbines and four met masts, either use the provided 'WINSENT_Test_Site.kml' file (e.g. by loading it in Google Earth) or the following coordinates (precise to the meter): GK3 (Gauß-Krüger, Bessel, Zone 3) Northern Turbine: (3561699, 5392296) Southern Turbine: (3561656, 5392158) NW Metmast: (3561565, 5392292) SW Metmast: (3561520, 5392153) NE Metmast: (3561823, 5392305) SE Metmast: (3561791, 5392165) WGS84 Northern Turbine: Latitude: 9.8365878, Longitude: 48.6652184 Southern Turbine: Latitude: 9.8359836, Longitude: 48.6639818 NW Metmast: Latitude: 9.8347682, Longitude: 48.6651956 SW Metmast: Latitude: 9.8341368, Longitude: 48.6639502 NE Metmast: Latitude: 9.8382723, Longitude: 48.6652871 SE Metmast: Latitude: 9.8378171, Longitude: 48.6640314 The terrain data is also available in the WINSENT_Elevation.tec and WINSENT_Trees_Buildings.tec files, but an official request must be made to receive them. Don't forget to also request the WINSENT_Terrain_Infos.pdf file to have some context on the data. The authors gratefully acknowledge the funding of the project WINSENTvalid (grant no. 03EE2048C) by the German Federal Ministry for Economic Affairs and Climate Action (BMWK). This work has been partially supported by the MERIDIONAL project, which receives funding from the European Union’s Horizon Europe Programme under the grant agreement No. 101084216. The support of Prof. Norbert Haala and Dr. Michael Kölle from the Institute for Photogrammetry and Geoinformatics of the University of Stuttgart for the preparation, execution and postprocessing of the scanning process is also recognized.

This dataset contains the generated cad assembly from three differents strategy from the article "Part-by-part interface-based search and automatic reassembly of CAD models for database expansion and model reuse".
In ReplacePart strategy, each assembly is available in .FCStd format which has the kinematic constraints in the A2+ workbench. A .STEP format of the assembly as well as a PNG screen of the assembly is also available. For the two other strategies, juste STEP files are availables.

The HybridCAD dataset is a novel resource tailored for hybrid additive-subtractive feature recognition in Computer-Aided Design (CAD) models, uniquely combining features from both manufacturing processes. Building on the MFCAD and MFCAD++ datasets, HybridCAD introduces additive manufacturing features alongside traditional subtractive ones, enabling the exploration and development of machine learning models for more complex, hybrid manufacturing applications. This dataset is especially suited for automatic feature recognition (AFR) research and model training in hybrid manufacturing contexts.

Dataset Composition

The dataset consists of 8,938 Boundary Representation (B-Rep) CAD models distributed into three main directories:

1. STEP Files:

   • Contains CAD models in STEP format, each representing a distinct part with hybrid manufacturing features.
   • Generated using PythonOCC CAD software, these CAD files serve as the foundation for feature recognition tasks.

2. Feature Labels:

   • File: feature_labels.txt
   • Provides unique label IDs for each B-Rep face in every CAD model, denoting the manufacturing feature name it belongs to.
   • Each CAD model face is labelled according to one of 29 hybrid additive-subtractive features, allowing for accurate and detailed feature recognition.

3. Hierarchical B-Rep Graphs:

   • Stored in HDF5 format for structured access to B-Rep data.
   • Detailed structural information is available in h5_structure.txt, explaining the hierarchical arrangement of B-Rep graphs.

Dataset Splits

The dataset is split into training, validation, and testing sets as follows:

• Training Set: 6,256 samples (70%)
• Validation Set: 1,342 samples (15%)
• Testing Set: 1,340 samples (15%)

Hybrid Manufacturing Features

HybridCAD includes a diverse range of additive and subtractive manufacturing features, expanding beyond the subtractive-only features of MFCAD++. This inclusion enables the exploration of hybrid manufacturing processes and the recognition of a broader feature set in CAD models. The complete feature list includes:

Label Feature
0 Chamfer
1 Through hole
2 Triangular passage
3 Rectangular passage
4 6-sided passage
5 Triangular through slot
6 Rectangular through slot
7 Circular through slot
8 Rectangular through step
9 2-sided through step
10 Slanted through step
11 O-ring
12 Blind hole
13 Triangular pocket
14 Rectangular pocket
15 6-sided pocket
16 Circular end pocket
17 Rectangular blind slot
18 Vertical circular end blind slot
19 Horizontal circular end blind slot
20 Triangular blind step
21 Circular blind step
22 Rectangular blind step
23 Round
24 Extrude cylinder
25 Extrude rectangle
26 Extrude triangle
27 Extrude hexagon
28 Extrude pentagon
29 Stock

Human studies and detected in blood. ICD-102016, ICD-10_Parent2016, MeSH_name (Coronary Artery Disease), MeSH_parent (Coronary Disease); Illumina Human v2 MicroRNA expression beadchip (IlluHSAv2MirRNA]; Searchlight Protein Array System (Searchlight ProtArray); Agilent-028004 SurePrint G3 Human GE 8x60K Microarray (AG-G3 HSAGE8x60K); TaqMan Open Array Human MicroRNA panel (TaqMan OpenHSA), studies statistical score threshold: p-, q-value, FDR

Data Description: This dataset captures all Cincinnati Police Department Calls for Service. The City of Cincinnati's Computer Aided Dispatch (CAD) system records police incident response activity, which includes all calls for service to emergency operators, 911, alarms, police radio and non-emergency calls. CAD records all dispatch information, which is used by dispatchers, field supervisors, and on-scene officers to determine the priority, severity, and response needs surrounding the incident. Once an officer responds to a call, he/she updates the disposition to reflect findings on-scene. This dataset includes both proactive and reactive police incident data.

Data Creation: This data is created through the City’s computer-aided dispatch (CAD) system.

Data Created By: The source of this data is the Cincinnati Police Department.

Refresh Frequency: This data is updated daily.

CincyInsights: The City of Cincinnati maintains an interactive dashboard portal, CincyInsights in addition to our Open Data in an effort to increase access and usage of city data. This data set has an associated dashboard available here: https://insights.cincinnati-oh.gov/stories/s/xw7t-5phj

Data Dictionary: A data dictionary providing definitions of columns and attributes is available as an attachment to this dataset.

Processing: The City of Cincinnati is committed to providing the most granular and accurate data possible. In that pursuit the Office of Performance and Data Analytics facilitates standard processing to most raw data prior to publication. Processing includes but is not limited: address verification, geocoding, decoding attributes, and addition of administrative areas (i.e. Census, neighborhoods, police districts, etc.).

Data Usage: For directions on downloading and using open data please visit our How-to Guide: https://data.cincinnati-oh.gov/dataset/Open-Data-How-To-Guide/gdr9-g3ad

Disclaimer: In compliance with privacy laws, all Public Safety datasets are anonymized and appropriately redacted prior to publication on the City of Cincinnati’s Open Data Portal. This means that for all public safety datasets: (1) the last two digits of all addresses have been replaced with “XX,” and in cases where there is a single digit street address, the entire address number is replaced with "X"; and (2) Latitude and Longitude have been randomly skewed to represent values within the same block area (but not the exact location) of the incident.

Computer Aided Dispatch (CAD) Market Outlook

The global Computer Aided Dispatch (CAD) market size was valued at approximately USD 2.7 billion in 2023 and is expected to grow significantly, reaching around USD 5.1 billion by 2032, with a Compound Annual Growth Rate (CAGR) of 7.1% during the forecast period. The growth of the CAD market is driven by the increasing demand for efficient emergency management systems and the rapid adoption of advanced technologies across various sectors such as public safety, transportation, and healthcare. The necessity for real-time data access and seamless communication among emergency response teams has further fueled the market's expansion. Additionally, the integration of CAD systems with Geographic Information System (GIS) and Internet of Things (IoT) technologies is enhancing situational awareness and decision-making processes, thereby contributing to the market's growth trajectory.

One of the primary growth factors in the Computer Aided Dispatch market is the rising need for public safety and security, which has been a major concern for governments and organizations worldwide. With the increase in urbanization and population density, the frequency and complexity of emergency incidents have escalated, necessitating the deployment of robust CAD systems to ensure efficient response times and resource allocation. The technological advancements in CAD solutions, such as enhanced data analytics, artificial intelligence, and machine learning, are enabling organizations to predict potential threats and optimize emergency response strategies. Furthermore, the growing awareness and investment in disaster management and mitigation plans are further propelling the demand for CAD systems, especially in regions prone to natural disasters and crises.

Another significant factor contributing to the growth of the CAD market is the exponential rise in the adoption of cloud-based services and solutions. Cloud-based CAD systems offer several advantages over traditional on-premises solutions, including scalability, cost-effectiveness, and ease of access. These benefits are particularly appealing to small and medium-sized enterprises (SMEs) and emerging markets, where budget constraints and resource limitations can be barriers to adopting advanced technologies. The flexibility provided by cloud solutions allows organizations to quickly adapt to changing operational needs, facilitating continuous improvement and innovation in emergency response systems. Moreover, the increasing collaboration between CAD solution providers and cloud service vendors is expected to further drive the market's growth during the forecast period.

Furthermore, the integration of CAD systems with advanced communication networks, such as 5G, is expected to play a crucial role in enhancing the performance and efficiency of emergency response operations. The high-speed and low-latency capabilities of 5G networks enable real-time data transmission and seamless connectivity among emergency responders, thereby improving situational awareness and decision-making processes. This technological advancement is anticipated to create new opportunities for CAD solution providers to develop innovative and comprehensive dispatch systems that cater to the evolving needs of public safety agencies and other sectors. Additionally, the increasing focus on interoperability and collaboration among different emergency services is driving the adoption of unified CAD platforms, which can efficiently coordinate multi-agency responses and resource management.

Component Analysis

The Computer Aided Dispatch market is segmented by components into software, hardware, and services, each playing a crucial role in the functionality and performance of CAD systems. The software component is considered the backbone of CAD systems, comprising various applications and modules that facilitate data processing, call management, and dispatch operations. The demand for advanced CAD software solutions is driven by the need for real-time data analysis, seamless communication, and efficient resource allocation during emergency situations. Features such as automated call distribution, incident data entry, and integrated mapping are essential in streamlining operations and enhancing situational awareness for emergency responders. Furthermore, the incorporation of artificial intelligence and machine learning algorithms in CAD software is expected to revolutionize the market by enabling predictive analytics and improved decision-making capabilities.

Hardware components are equally critical in the CAD market, as they provide the necessary infrastructure a

Market Size and Growth Prospects: The global 3D CAD tool market size was valued at USD 9.5 billion in 2023 and is projected to expand at a CAGR of 11.3% from 2023 to 2033. The market growth is driven by factors such as the increasing demand for personalized products, the growing adoption of cloud-based solutions, and the advancements in manufacturing technologies. Cloud-based 3D CAD tools offer flexibility, scalability, and cost-saving benefits, while advancements in artificial intelligence (AI) and machine learning (ML) are enhancing the efficiency and accuracy of design processes. Competitive Landscape and Key Trends: The 3D CAD tool market is highly competitive, with established players such as SOLIDWORKS, AutoCAD, and Siemens holding significant market shares. Emerging vendors are also gaining traction by offering niche solutions and innovative features. The market is witnessing a surge in adoption of cloud-based solutions, which provide seamless collaboration and remote access to design data. Additionally, the integration of IoT devices and data analytics capabilities is transforming the market, enabling real-time monitoring and optimization of design processes. Regional growth is expected to be driven by the Asia Pacific region, particularly China and India, due to increasing industrialization and government initiatives promoting innovation. North America and Europe are also expected to maintain their dominance in the market.

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3D Computer Aided Design (CAD) Software Market Size 2025-2029

The 3d computer aided design (cad) software market size is forecast to increase by USD 5.09 billion, at a CAGR of 7.1% between 2024 and 2029.

The market is witnessing significant growth, driven by the high adoption of these solutions in optimizing production value chains across various industries. The integration of 3D CAD software in design, engineering, and manufacturing processes enhances productivity, reduces errors, and improves product quality. Moreover, the emergence of new technologies, such as cloud computing, virtual reality, and the Internet of Things (IoT), is revolutionizing the global 3D CAD software market. These advancements enable real-time collaboration, remote access, and improved data management, making design and manufacturing processes more efficient and agile. However, the increasing availability of open-source and free versions of 3D CAD software poses a challenge for market players. These alternatives cater to small businesses and individual users, potentially disrupting the market dynamics and pricing structures. Companies must differentiate themselves by offering unique features, superior customer support, and seamless integration with other business applications to maintain their competitive edge.

What will be the Size of the 3D Computer Aided Design (CAD) Software Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free SampleThe 3D Computer-Aided Design (CAD) software market continues to evolve, driven by the dynamic interplay of various sectors and applications. Medical devices, for instance, benefit from CAD's precision in designing intricate components, while subtractive manufacturing optimizes production processes through solid modeling. Design review and quality control ensure product excellence, with industrial design and electrical engineering sectors reaping significant advantages. Computer-aided engineering (CAE) and version control facilitate seamless collaboration and iteration, enabling design automation and reverse engineering. The integration of AI-assisted design, CAM software, and parametric design propels innovation in consumer products and engineering plastics. Augmented Reality (AR) and Virtual Reality (VR) technologies merge CAD with immersive experiences, revolutionizing design thinking and design validation. Additive manufacturing and topology optimization transform manufacturing processes, while generative design and digital manufacturing streamline production. CAD software's continuous evolution encompasses mesh processing, surface modeling, and design verification, fostering process optimization and tolerance analysis. Collaboration tools, API integration, and engineering plastics further expand its applicability. The CAD landscape remains vibrant, with ongoing advancements in design automation, digital twin, and cloud computing shaping the future of product design.

How is this 3D Computer Aided Design (CAD) Software Industry segmented?

The 3d computer aided design (cad) software industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. DeploymentOn-premisesCloudApplicationManufacturingAECAutomotiveHealthcareOthersSectorLarge enterprisesSmall and medium enterprises (SMEs)Freelancers and individual designersPricing SchemeSubscription-based (SaaS)Perpetual licensePay-per-useGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKAPACChinaIndiaJapanSouth KoreaRest of World (ROW)

By Deployment Insights

The on-premises segment is estimated to witness significant growth during the forecast period.In the realm of Computer-Aided Design (CAD), on-premises 3D CAD software represents the traditional model, installed and operated on local computers or servers. This software's advantages lie in its customizability and optimization, catering to unique business requirements. Suitable for enterprises with robust IT capabilities, on-premises 3D CAD software allows for complete control over the software, including its setup and configuration. The integration of design thinking, 3D modeling, and design validation within this software enables companies to streamline their product development process. Additionally, supply chain management and design for manufacturing capabilities ensure efficient production and collaboration. Solid modeling and parametric design facilitate precise and accurate product design, while human-machine interface (HMI) and design automation enhance user experience and productivity. Material science and tolerance analysis contribute to the creation of high-quality consumer products, while additive manufacturing and g

Market Size and Growth: The global CAD Library market was valued at USD xx million in 2025 and is projected to reach USD xx million by 2033, exhibiting a CAGR of xx% during the forecast period. The increasing demand for efficient product design and development, coupled with the growing adoption of 3D modeling and simulation, is driving market expansion. The automotive, aerospace, and construction industries are key contributors to the market's growth, utilizing CAD libraries to optimize designs, reduce development time, and improve product quality. Industry Dynamics: The CAD Library market is influenced by several factors, including technological advancements, the integration of CAD software with other design tools, and the emergence of cloud-based solutions. The trend towards digital transformation in manufacturing and engineering is fueling the demand for CAD libraries, as they provide access to standardized and reusable design components, reducing design complexity and accelerating product development processes. However, challenges such as the need for specialized expertise and compatibility issues between different CAD platforms can hinder market growth. Major players in the market include Jytra Technology Solutions, Autodesk, Dassault Systèmes, and GrabCAD, among others.

The mobile CAD software market is experiencing robust growth, driven by the increasing adoption of smartphones and tablets for design and engineering tasks. The convergence of powerful mobile devices and sophisticated CAD applications has enabled professionals and hobbyists alike to access and utilize design tools anywhere, anytime. This trend is particularly pronounced in sectors like architecture, public safety (e.g., emergency response planning), and mechanical design, where immediate access to design data is crucial. The market's expansion is further fueled by advancements in cloud computing and collaborative design platforms, allowing seamless data sharing and project management across geographically dispersed teams. While initial adoption was primarily focused on 2D applications, the increasing availability of powerful 3D mobile CAD solutions is driving significant market expansion. We estimate the current market size (2025) to be around $2.5 billion, based on reasonable projections considering the growth of related tech sectors and penetration rates. A projected CAGR of 15% from 2025-2033 suggests a substantial market expansion to approximately $8 billion by 2033. This substantial growth is expected despite challenges like the need for improved mobile device processing power and occasional connectivity limitations in remote areas, which are gradually being overcome through technological innovation and improved infrastructure. The competitive landscape is dynamic, with established players like Autodesk, Siemens, and PTC alongside emerging specialized companies focusing on mobile-first CAD solutions. These companies are actively investing in user experience improvements, enhanced functionality, and integration with other design and collaboration tools. Regionally, North America and Europe currently dominate the market, but the Asia-Pacific region is projected to experience the fastest growth due to increasing infrastructure development and rising digital adoption. This dynamic market presents both opportunities and challenges for companies looking to establish a footprint or expand their share within this rapidly evolving sector. The increasing focus on user-friendly interfaces and specialized mobile-oriented features will be key to success in the coming years.

Data Description: CPD & CFD Calls For Service includes all Fire and Police calls for service from the current day. Calls For Service are the events captured in an agency’s Computer-Aided Dispatch (CAD) system used to facilitate incident response. This dataset includes both proactive and reactive police incident data.

Data Creation: This data is created when a run is entered into the City of Cincinnati’s computer-aided dispatch (CAD) database.

Data Created By: The source of this data is the City of Cincinnati's computer-aided dispatch (CAD) database.

Refresh Frequency: This data is updated every 15 minutes.

CincyInsights: The City of Cincinnati maintains an interactive dashboard portal, CincyInsights in addition to our Open Data in an effort to increase access and usage of city data. This data set has an associated dashboard available here: https://insights.cincinnati-oh.gov/stories/s/a4d9-vw5s and https://insights.cincinnati-oh.gov/stories/s/6jrc-cmn5

Data Dictionary: A data dictionary providing definitions of columns and attributes is available as an attachment to this dataset.

Processing: The City of Cincinnati is committed to providing the most granular and accurate data possible. In that pursuit the Office of Performance and Data Analytics facilitates standard processing to most raw data prior to publication. Processing includes but is not limited: address verification, geocoding, decoding attributes, and addition of administrative areas (i.e. Census, neighborhoods, police districts, etc.).

Data Usage: For directions on downloading and using open data please visit our How-to Guide: https://data.cincinnati-oh.gov/dataset/Open-Data-How-To-Guide/gdr9-g3ad

Disclaimer: In compliance with privacy laws, all Public Safety datasets are anonymized and appropriately redacted prior to publication on the City of Cincinnati’s Open Data Portal. This means that for all public safety datasets: (1) the last two digits of all addresses have been replaced with “XX,” and in cases where there is a single digit street address, the entire address number is replaced with "X"; and (2) Latitude and Longitude have been randomly skewed to represent values within the same block area (but not the exact location) of the incident.

Here are a few use cases for this project:

1. Structural Engineering Analysis: Use the "cad detecting-formal" model to identify and categorize dimensions and specifications related to structural columns, beams, and other components of building design for architects or engineers working with CAD drawings.

2. Automatic Dimension Extraction: Utilize the model to automatically extract critical dimensions from CAD drawings and create a database of relevant specifications and values, facilitating faster and more accurate calculations for construction projects.

3. CAD Drawing Validation: Implement the "cad detecting-formal" model as a tool for checking the correctness and consistency of CAD drawings by verifying the presence and accuracy of specified dimensions and elements.

4. CAD Search and Classification: Improve the searchability and organization of CAD files in a database by using the model to identify and classify CAD files based on the dimensions and elements present, allowing users to quickly find the files they need for specific projects.

5. CAD Design Optimization: Use the model to analyze the dimensions and design components within a CAD drawing, offering suggestions and solutions for optimizing structural design components (e.g., reducing materials cost or improving structural efficiency).

This Free CAD files are for the manuscript "A temperature-controlled patch-clamp platform demonstrated on Jurkat T lymphocytes and human stem cell derived neurons". The files allow for easily 3D-printing a housing box for the electronics.

The CAM & CAD software market was valued at USD 25.10 billion in 2022 and will reach USD 51.87 billion by 2030, registering a CAGR of 9.5% for the forecast period 2023-2030. Factors Affecting the CAM & CAD Software Market Growth

The increasing need for automation in industries is expected to drive the growth of the CAM & CAD software market.

Automation in the manufacturing industry is on a surge owing to the increasing demand to reduce operational costs, improvement in services and product qualities, and increase the efficiency of the processes. Moreover, automation provides manufacturers to reduce labor costs, make streamline processes, and improve customer satisfaction. Additionally, technological advancements in CAM & CAD software enable control of the production process, require less time complete operations and improve the efficiency of further operations. Furthermore, CAM & CAD software allows easy access to data at any location from several devices. Therefore, such technological advantages of this software for growing businesses propel the market growth of the CAM & CAD software market.

The lack of skilled professionals is expected to hinder the market growth of the CAM & CAD software market.

The CAM & CAD software requires skilled professionals and expert solutions which help in designing, developing, and servicing such software packages. Moreover, the complex nature of this software and its mechanisms require skilled professionals to handle it. Thereby, increasing the overall cost of CAM & CAD software. Furthermore, these factors make it challenging for manufacturers and businesses to appoint the right professionals for the software functioning. Thus, all such factors contribute to unexpected costs and tend to hinder the market growth of the CAM & CAD software market.

Impact of the COVID-19 Pandemic on the CAM & CAD Software Market:

The COVID-19 pandemic significantly impacted the CAM & CAD software market. Owing to the forced lockdowns and temporary closure of institutions and organizations there was a shift from fieldwork to digital or online platform work. Globally, all industries relied on technology to maintain productivity and stay connected with each other for several operations and functions. Thereby, leading to an increase in the adoption of CAM & CAD software solutions. Moreover, organizations required flexible and cost-effective solutions which were quickly integrated into the systems, indirectly propelling the market growth of software. Additionally, the key market players expanded CAM/CAD software solutions to various applications and focused on innovations to increase the advancement in present software. All these, factors boosted the market growth of the CAM & CAD software market during the pandemic. What is CAM & CAD software?

Computer-aided design and computer-aided manufacturing (CAD/CAM) software are solely responsible for designing and manufacturing prototypes (https://www.cognitivemarketresearch.com/virtual-prototypes-market-report), finished products, and manufacturing units. Moreover, this software creates 2D/3D designs for a variety of units and spaces. This software is associated with computer numerical control (CNC) machines and direct numerical control (DNC) systems. These two systems encode geometric data to get precise dimensions and simulate real-world conditions. The wide application of CAD/CAM software is seen in the automotive, aerospace, dentistry, and forensic sectors.

Data Description: This dataset captures all Cincinnati Police Department Calls for Service. The City of Cincinnati's Computer Aided Dispatch (CAD) system records police incident response activity, which includes all calls for service to emergency operators, 911, alarms, police radio and non-emergency calls. CAD records all dispatch information, which is used by dispatchers, field supervisors, and on-scene officers to determine the priority, severity, and response needs surrounding the incident. Once an officer responds to a call, he/she updates the disposition to reflect findings on-scene. This dataset includes both proactive and reactive police incident data.

Data Creation: This data is created through the City’s computer-aided dispatch (CAD) system.

Data Created By: The source of this data is the Cincinnati Police Department.

Refresh Frequency: This data is updated daily.

CincyInsights: The City of Cincinnati maintains an interactive dashboard portal, CincyInsights in addition to our Open Data in an effort to increase access and usage of city data. This data set has an associated dashboard available here: https://insights.cincinnati-oh.gov/stories/s/xw7t-5phj

Data Dictionary: A data dictionary providing definitions of columns and attributes is available as an attachment to this dataset.

Processing: The City of Cincinnati is committed to providing the most granular and accurate data possible. In that pursuit the Office of Performance and Data Analytics facilitates standard processing to most raw data prior to publication. Processing includes but is not limited: address verification, geocoding, decoding attributes, and addition of administrative areas (i.e. Census, neighborhoods, police districts, etc.).

Data Usage: For directions on downloading and using open data please visit our How-to Guide: https://data.cincinnati-oh.gov/dataset/Open-Data-How-To-Guide/gdr9-g3ad

Disclaimer: In compliance with privacy laws, all Public Safety datasets are anonymized and appropriately redacted prior to publication on the City of Cincinnati’s Open Data Portal. This means that for all public safety datasets: (1) the last two digits of all addresses have been replaced with “XX,” and in cases where there is a single digit street address, the entire address number is replaced with "X"; and (2) Latitude and Longitude have been randomly skewed to represent values within the same block area (but not the exact location) of the incident.

The analysis is based on the molecular elements that constitute the interactome of CAD. Topology analysis is based on degree centrality, which measures the number of links that connects to a node within a pathway. Regulation trend (Trend) is based on differential expression of either *compounds, or **gene\proteins, or ***both. Down-regulation (↓), up-regulation (↑), contradictory regulation or not applicable (NA). General pathway association (class): fatty acids (FA), amino acids (AA), aminoacylation of transfer RNAs (AAcylation), signalling (SIG), energy metabolism (EMET), vitamin 5 as precursor (Vit5), disease (DIS), immune system (IMM), antioxidants (AntiOx), hormonal (HOR), and cytoskeleton (Cytosk). Gene-centric or metabolite-centric analysis (|).

Cloud-Based CAD Software Market Outlook

The global market size for cloud-based CAD software was valued at approximately USD 2.8 billion in 2023 and is projected to reach USD 6.5 billion by 2032, growing at a compounded annual growth rate (CAGR) of 9.7% during the forecast period. The major growth factor propelling this market is the increasing demand for collaborative product development and design across various industries, coupled with the rising adoption of cloud technologies which offer scalability and cost-efficiency.

One of the primary growth drivers for the cloud-based CAD software market is the automotive industry's increasing reliance on advanced design tools to enhance vehicle design and development cycles. The ability to access design data from any location via the cloud, coupled with the growing trend towards electric and autonomous vehicles, is pushing automotive companies to adopt these advanced CAD solutions. This shift not only reduces costs but also shortens the time-to-market for new models, providing a competitive edge to manufacturers.

Another significant factor contributing to market growth is the aerospace and defense sector’s need for precise and complex design capabilities. Cloud-based CAD software allows for high-level collaboration among engineers and designers across different locations, ensuring that intricate designs meet stringent industry standards. The ongoing modernization efforts and increased defense budgets in several countries further bolster the adoption of these cloud solutions, ensuring robust growth in this sector.

The industrial machinery and electrical and electronics sectors are also witnessing substantial growth in the adoption of cloud-based CAD software. These industries demand high precision and innovation in design, which cloud-based CAD tools deliver by offering real-time collaboration and seamless integration with other enterprise software. The continuous evolution in smart manufacturing and Industry 4.0 initiatives are key drivers that are expected to sustain the demand in these sectors over the forecast period.

From a regional perspective, North America dominates the cloud-based CAD software market, largely due to the early adoption of advanced technologies and a high concentration of key market players. The region's strong foothold is supported by significant investments in R&D and a robust technological infrastructure. On the other hand, the Asia Pacific region is anticipated to exhibit the highest growth rate due to rapid industrialization, increasing adoption of cloud technologies, and supportive government policies encouraging digital transformation in countries like China and India.

Component Analysis

The cloud-based CAD software market can be segmented into software and services. The software segment holds the largest market share, driven by the continuous advancements in CAD software capabilities, including enhanced user interfaces, improved rendering features, and integration with other engineering tools. These software solutions provide comprehensive design tools that cater to various industry needs, from simple 2D drafting to complex 3D modeling and simulation. The ongoing innovation in software functionalities is expected to sustain this segment's dominance in the market.

Within the services segment, the market is further categorized into training and education, support and maintenance, and consulting services. As cloud-based CAD software becomes more sophisticated, there is a growing need for professional services to ensure optimal utilization of these tools. Training and education services help organizations upgrade the skills of their workforce, while support and maintenance services ensure the smooth functioning of software applications, which is crucial for continuous productivity. Consulting services, on the other hand, provide expert advice on integrating CAD solutions with other enterprise systems, thereby enhancing overall operational efficiency.

The growing complexity of design projects across various industries is also propelling the demand for specialized consulting services. These services help organizations tailor their CAD software capabilities to specific project requirements, ensuring that they achieve their design and development goals efficiently. The increasing trend of outsourcing CAD services to specialized vendors is also contributing to the growth of the services segment, as companies seek to leverage external expertise to enhance their design processes.

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3D CAD Software Market Outlook

According to our latest research, the global 3D CAD software market size reached USD 11.2 billion in 2024, driven by rapid digitalization across key industries and the growing need for advanced design solutions. The market is expected to expand at a robust CAGR of 7.6% from 2025 to 2033, ultimately reaching USD 21.7 billion by 2033. This significant growth is fueled by the increasing adoption of 3D modeling for product innovation, the proliferation of cloud-based solutions, and the integration of 3D CAD with emerging technologies such as AI and IoT.

One of the primary growth factors for the 3D CAD software market is the accelerating demand for enhanced product visualization and efficient design workflows across industries such as automotive, aerospace, and architecture. Organizations are increasingly leveraging 3D CAD solutions to streamline product development cycles, reduce time-to-market, and improve collaboration among multidisciplinary teams. The ability of 3D CAD software to facilitate precise modeling, simulation, and prototyping is revolutionizing how products are conceptualized and manufactured. This trend is particularly pronounced in sectors where innovation and customization are critical for competitive differentiation, prompting significant investments in advanced design tools.

Another key driver is the rising prevalence of cloud-based deployment models, which are transforming the accessibility and scalability of 3D CAD solutions. Cloud-based platforms enable organizations to access powerful design tools remotely, collaborate in real time, and scale resources according to project requirements. This flexibility is particularly attractive to small and medium enterprises (SMEs) that may lack the infrastructure for extensive on-premises installations. Furthermore, the integration of 3D CAD with cloud ecosystems supports seamless data management, version control, and enhanced security, making it easier for companies to adopt and integrate these solutions into their existing workflows.

Technological advancements, including the convergence of 3D CAD software with artificial intelligence, machine learning, and the Internet of Things (IoT), are opening new frontiers for the market. AI-powered features such as automated design suggestions, error detection, and predictive analytics are enhancing the efficiency and accuracy of design processes. Meanwhile, IoT integration allows for real-time monitoring and analysis of product performance, feeding valuable data back into the design loop. These innovations are not only improving productivity but also enabling the creation of smarter, more connected products, further expanding the scope and value proposition of 3D CAD software across diverse industry verticals.

From a regional perspective, North America continues to dominate the 3D CAD software market, accounting for the largest share of global revenues in 2024. This leadership is attributed to the strong presence of major industry players, high R&D investments, and early adoption of cutting-edge design technologies. However, Asia Pacific is rapidly emerging as a high-growth region, propelled by the expansion of manufacturing hubs, government initiatives supporting digital transformation, and increasing demand for advanced design tools in countries like China, India, and Japan. Europe also remains a significant market, with robust adoption in automotive and industrial sectors, while Latin America and the Middle East & Africa are witnessing steady growth as digitalization gains momentum.

Component Analysis

The component segment of the 3D CAD software market is bifurcated into software and services, each playing a pivotal role in driving industry growth. The software segment commands the lion's share of the market, encompassing a wide array of solutions designed for modeling, simulation, rendering, and collaboration. Leading software offerings are continuously evolving, integrating advanced features such as parametric modelin