This dataset contains a time-series industrial data collected from a flow plant located in São Paulo University's Polytechnical School, which has a laboratory of industrial process controls (LIPC, or LCPI, in Portuguese), where the plant is located. This plant, designed exclusively for research and experimentation, consists on passing water through a closed circuit that contains multiple instruments, such as control valves, sensors (orifice plates, Coriolis) and other industrial assets. In this experiment, the pump was turned on, the process stabilized, then the disturbance valve, which was open, was manually closed to 50%, generating a disturbance in the process. As soon as the process stabilized again, the disturbance valve was opened from 50% to 100% again, the process stabilized and was finally shut down. The pump's PID was used as the control element. The data was collected using the plant's DCS ABB 800xA using the OPC DA protocol, and automatically sent to a cloud-based PIMS (GE Historian for Cloud).

Comprehensive dataset containing 37 verified PIMS locations in Russia with complete contact information, ratings, reviews, and location data.

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The global Plant Information Management System (PIMS) market is poised for significant expansion, projected to reach a substantial valuation. Driven by the increasing need for operational efficiency, data-driven decision-making, and stringent regulatory compliance across various industries, the PIMS market is expected to witness robust growth. Key sectors such as Automotive, Food & Beverages, and Semiconductors are increasingly adopting PIMS to streamline their complex manufacturing processes, enhance quality control, and ensure product traceability. The growing adoption of Industry 4.0 technologies, including the Industrial Internet of Things (IIoT), artificial intelligence (AI), and cloud computing, is further accelerating market growth by enabling real-time data capture, analysis, and predictive maintenance. This technological integration allows for proactive issue resolution, reduced downtime, and optimized resource utilization, all crucial for modern industrial operations. The market's upward trajectory is further supported by the continuous evolution of PIMS solutions, offering advanced functionalities like real-time performance monitoring, batch management, and regulatory reporting. The demand for integrated enterprise management systems that can seamlessly communicate with PIMS is also on the rise, fostering a more holistic approach to plant operations. While the market presents numerous opportunities, potential restraints such as high initial implementation costs and the need for skilled personnel to manage and operate these sophisticated systems may pose challenges. However, the undeniable benefits of improved productivity, enhanced safety, and compliance adherence are expected to outweigh these concerns, ensuring sustained market development. The forecast period is anticipated to see significant investment in PIMS, particularly in regions with a strong industrial base and a focus on digital transformation, such as North America and Asia Pacific, further cementing the PIMS market's vital role in the industrial landscape. This report provides a comprehensive analysis of the global Plant Information Management System (PIMS) market, encompassing its current state, future projections, and key drivers. The study period spans from 2019 to 2033, with the base year set at 2025. The forecast period for market projections is from 2025 to 2033, building upon the historical data from 2019 to 2024.

Discover the booming Plant Information Management System (PIMS) market! This comprehensive analysis reveals a $1389 million market in 2025, projected to grow at a 6.3% CAGR through 2033. Learn about key drivers, trends, and regional market share across automotive, food & beverage, and semiconductor industries. Explore the competitive landscape and future growth potential.

Both Trade and Inward investment are covered in - https://data.gov.uk/dataset/international-trade-support-performance-and-impact-monitoring-survey-pims

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Climate change adaptation is vital for Pacific SIDS. Long-term effects, including the increasing frequency and severity of extreme events such as high rainfall, droughts, tropical cyclones, and storm surges are affecting the people in this region. Coupled with non-climate drivers, such as inappropriate land use, overexploitation of resources, increasing urbanization and population increase, development in the region is increasingly undermined. For the low lying atolls, the likely economic disruption from climate change pressures could be catastrophic and potentially lead to population relocation and therefore social and cultural disruption and disproportion. Failure to reduce vulnerability may result in loss of future risk management opportunities when impacts may be greater and options fewer. Available online Call Number: [EL] Physical Description: 136 p.

Pims New Jersey Inc Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Legacy HR system, now phased out/migrated to Shared Services/Systems Applications and Products (SAP). Data stored - Name, Staff No., Pay Band, Work Hours, Org Unit and Cost centre

HR legacy data system. Stores Department for Transport central legacy data prior to the transfer of HR function to the DVLA Shared Services Centre Swansea in April 2008

Discover the booming Personal Identity Management System (PIMS) software market. Our analysis reveals a $15 billion market in 2025 projected to reach $50 billion by 2033, driven by stringent data privacy regulations and rising cyber threats. Learn about key players, regional trends, and growth opportunities in this comprehensive report.

The Patient Information Management System (PIMS) market is booming, projected to reach $3693.9 million in 2025 with a 7.8% CAGR. Discover key drivers, trends, and restraints shaping this rapidly evolving sector, including insights on EHR adoption, cloud-based solutions, and regional market share.

This bar chart displays books by publication date using the aggregation count. The data is filtered where the author is Pria Pims. The data is about books.

This dataset contains information about hospitals in England. National Health Service (NHS) Choices considers hospitals as locations that provide predominantly inpatient services. It includes information about organization and post codes, telephone number and email address for several hospital organizations in England.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

This study tackles the tricky problem of identifying metaphors in language that includes prepositions (e.g., Reijnierse, 2019, Herrmann et al., 2019, Nacey et al. 2019, Marhula and Rosiński, 2019) . The study is based on data from the Corpus of Contemporary American English (COCA, Davies, 2008). We demonstrate how the Procedure for Identifying Metaphorical Scenes (PIMS) reflected and evoked by linguistic expressions in discourse (Johansson Falck & Okonski, manuscript accepted for publication), can be used to identify metaphorical relations reflected in language. Two studies are presented that test the reliability of the procedure and the sensitivity of the tool for prepositions. Results show that PIMS provides a simple procedure that increases both reliability and sensitivity for prepositional constructions. By focusing on the scenes evoked by linguistic constructions, the procedure highlights the contextual meanings of the constructions and the specific experiences that they code.

References:

Davies, M. (2008). COCA. Corpus of Contemporary American English.

Herrmann, B., et al. (2019). Linguistic metaphor identification in German. In Nacey, S., Dorst, A. G., Krennmayr, T. W., Reijnierse, W. G. (Eds.). Metaphor Identification in Multiple Languages: MIPVU Around the World, Volume 22 (pp 113-136). Amsterdam/Philadelphia, John Benjamins Publishing Company.

Johansson Falck, M. and L. Okonski (manuscript accepted for publication). "Procedure for Identifying Metaphorical Scenes (PIMS): A Cognitive Linguistics Approach to Bridge Theory and Practice." Cognitive Semantics.

Marhula, J. and M. Rosiński (2019). Linguistic metaphor identification in Polish. In Nacey, S., Dorst, A. G., Krennmayr, T. W., Reijnierse, W. G. (Eds.). Metaphor Identification in Multiple Languages: MIPVU Around the World, Volume 22 (pp 183-202). Amsterdam/Philadelphia, John Benjamins Publishing Company.

Nacey, S., et al. (2019). Linguistic metaphor identification in Scandinavian. In Nacey, S., Dorst, A. G., Krennmayr, T. W., Reijnierse, W. G. (Eds.). Metaphor Identification in Multiple Languages: MIPVU Around the World, Volume 22 (pp 137-158). Amsterdam/Philadelphia, John Benjamins Publishing Company.

Reijnierse, W. G. (2019). Linguistic metaphor identification in French. In Nacey, S., Dorst, A. G., Krennmayr, T. W., Reijnierse, W. G. (Eds.). Metaphor Identification in Multiple Languages: MIPVU Around the World, Volume 22 (pp 69-90). Amsterdam/Philadelphia, John Benjamins Publishing Company.

In a first study, we used PIMS to identify metaphorical ‘into relations’ that are evoked by sentences that include the preposition into. The data was excepted from (Davies, 2008). We excerpted instances of into + noun collocations where into was tagged as a preposition and the noun was located in a window one word to the right of the preposition. For more information, please see Johansson Falck and Okonski (2022).

Reference: Davies, Mark. (2008-) The Corpus of Contemporary American English (COCA). Available online at https://www.english-corpora.org/coca/.

Johansson Falck, M. and L. Okonski (manuscript accepted for publication). "Procedure for Identifying Metaphorical Scenes (PIMS): A Cognitive Linguistics Approach to Bridge Theory and Practice." Cognitive Semantics, in press, https://doi.org/10.1080/10926488.2022.2062243.

The client surveys involve client interviews that give evidence for the quality of service UKTI provides to business. It is completed by an independent market research company specialising in business surveys. The survey is based on independent telephone interviews with a sample of users of UKTI’s services. All our client survey interviews are voluntary. Clients are guaranteed anonymity, which removes any bias in the way they respond to questions. The non-user surveys involved interviews with 300 exporters who have never used UKTI Services. It captures evidence on usage of non-UKTI export support, and measures the extent to which firms encounter barriers that give rise to the need for such services. More information see: https://www.gov.uk/government/collections/uk-trade-investment-performance-and-impact-monitoring-survey