Importance Of Data Acquisition Research Articles

Research on Digital Management Construction of Surveying and Mapping Geographic Information Data Archives

In today's era of digitization and informatization, surveying and mapping geographic information data archives are important information assets in the field of geographic information. This paper discusses the digital management construction of mapping geographic information data archives. In terms of key technologies for digitization of digital management archives, the importance of data acquisition and finishing technology, data storage and management technology, and data retrieval and sharing technology is emphasized. At the same time, digitally managing archives also involves issues such as laws and regulations, data compatibility, and data authenticity, the resolution of which is crucial to guaranteeing the feasibility and credibility of digital management. The design and implementation of an archive digital management system is a key step to realizing the digital management of mapping geographic information data archives, which is of positive significance to promoting the digital management construction of mapping geographic information data archives.

Acquisition, transmission and management of data in industrial practice in the digital age

Digital technologies permeate all aspects of industrial production and Logistics systems, accelerating the generation of large amounts of industrial data. Industry 4.0 and Industrial Internet of Things offers great development opportunities, new perspectives, a new paradigm of autonomous and decentralized production control. The information on the current status of industrial processes is invaluable in present times. Among others, it enables deliberate and rational management of available resources. Therefore, acquisition, transmission and management of data is an important issue in the systems for collecting data from production lines and a key element in the decision-making process. In industrial practice, the data acquisition process uses the information obtained from various sensors placed directly in production lines. The current level of microelectronics development enables acquisition and transfer of data from technological processes in real time. This article presents selected popular methods of automatic acquisition and transfer of data directly from production lines in the course of implementation of manufacturing processes. A review of all the issues discussed is supported by examples. Particular attention is paid to the nature and importance of data acquisition in the decisionmaking process. It was emphasized that the information itself is very important, but the value of information and the way it is processed and managed are also important. Data management in the unit optimizes the decision-making process and the work of the entire unit. On the other hand, data is a resource, the loss of which may result in the loss of competitive position or the loss of development opportunities.

Smart sheet metal forming: importance of data acquisition, preprocessing and transformation on the performance of a multiclass support vector machine for predicting wear states during blanking

In consequence of high cost pressure and the progressive globalization of markets, blanking, which represents the most economical process in the value chain of manufacturing companies, is particularly dependent on reducing machine downtimes and increasing the degree of utilization. For this purpose, it is necessary to be able to make a real-time prediction about the current and future process conditions even at high production rates. Therefore, this study investigates the influence of data acquisition, preprocessing and transformation on the performance of a multiclass support vector machine to classify abrasive wear states during blanking based on force signals. The performance of the model was quantitatively evaluated based on the model accuracy and the separability of the classes. As a result, it was shown, that the deviation of time series represents the key parameter for the resulting performance of the classification model and strongly depends on the sensor type and position, the preprocessing procedure as well as the feature extraction and selection. Furthermore, it is shown that the consideration of domain knowledge in the phases of data acquisition, preprocessing and transformation improves the performance of the classification model and is essential to successfully implement AI projects. Summarizing the findings of this study, trustworthy data sets play a crucial role for implementing an automated process monitoring as a basis for resilient manufacturing systems.

연하장애 분야의 인공지능 적용

The development and performance of Artificial intelligence (AI) have been revolutionary ever since adoption of deeplearning algorithms. It is expected that AI will induce tremendous changes in many parts of society and industry,including medicine. The spread of AI is accelerated by the availability of extensive Open Source Libraries and commonplatforms. Importance of data acquisition is increasingly emphasized for AI learning. Digitalization of imagesand medical records will contribute greatly to the application of AI technology in medical fields. Support systemsfor reading diagnostic images and decision-making for patient care are currently under development, depending onthe efficiency and precision of AI. Evaluation and management of dysphasia can be potentiated by AI, althoughthere is not much research in this field. Automated reading of videofluoroscopy, analysis of cervical auscultation,and dysphagia coaching system have all shown promising results. Hopefully, safer and more efficient care of dysphagiapatients will be possible through more active research on the utilization of AI technology.

Importance of data acquisition in problem based learning

This research paper demonstrates untraditional learning and teaching method that is developed from combination of experimentation, usage of computer simulations and problem based learning. Taking all previously mentioned methods together there can be created very successful learning environment which provides students to master electromagnetism more effectively. Research focuses on proper use of data acquisition modules and computer simulations in PBL teaching method. Based on the results of the research experimental PBL in various cases provides better learning outcomes, but there are also a few occasions where the results aren’t so pleasing. Overall PBL provides results that are at least as promising as results of other teaching and learning methods. Therefore this method will be utilized in Liepaja University to teach physics, especially electromagnetism.

Imaging of filter cakes through electrical impedance tomography

An experimental rig capable of automatically sequencing and collecting data from a dead-end pressure filter is described. The computer-controlled apparatus uses electrical impedance measurements in multiple vertical scanning planes to determine the status of a filter cake during either the cake formation, gas dewatering or displacement washing phases of a filter cycle. The data acquired are displayed in real time during a test in conjunction with liquor flow rates. Initial results from an experimental programme are presented, which show the filtration and dewatering characteristics of aqueous-based calcium, carbonate suspensions. The importance of data acquisition and system control are discussed, and an outline of future developments is given.