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Journal articles on the topic 'Data Workflow Efficiency'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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1

Graham, Andrew, Stephan Gmur, and Travis Scott. "Improved SCAT data workflow to increase efficiency and data accuracy." International Oil Spill Conference Proceedings 2017, no. 1 (2017): 2674–93. http://dx.doi.org/10.7901/2169-3358-2017.1.2674.

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ABSTRACT #2017-302 Traditional Shoreline Cleanup Assessment Technique (SCAT) data workflows typically entail collecting data in the field using notebooks, handheld GPS units and digital cameras, transcribing these data onto paper forms, and then manually entering into a local database. Processed data are pushed to a SCAT geographical information system (GIS) specialist, ultimately providing exports as paper and electronic versions of maps, spreadsheets and reports. The multiple and sometimes iterative steps required can affect the dissemination of accurate and timely information to decision ma

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Weigel, Tobias, Ulrich Schwardmann, Jens Klump, Sofiane Bendoukha, and Robert Quick. "Making Data and Workflows Findable for Machines." Data Intelligence 2, no. 1-2 (2020): 40–46. http://dx.doi.org/10.1162/dint_a_00026.

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Research data currently face a huge increase of data objects with an increasing variety of types (data types, formats) and variety of workflows by which objects need to be managed across their lifecycle by data infrastructures. Researchers desire to shorten the workflows from data generation to analysis and publication, and the full workflow needs to become transparent to multiple stakeholders, including research administrators and funders. This poses challenges for research infrastructures and user-oriented data services in terms of not only making data and workflows findable, accessible, int

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Mahaboobsubani, Shaik. "Enhancing Workflow Efficiency in Finance with O365 Graph API." Journal of Scientific and Engineering Research 9, no. 2 (2022): 178–85. https://doi.org/10.5281/zenodo.14356693.

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The use of the O365 Graph API to improve workflow efficiency in operations related to finance. The article is based on the capability of the Graph API to integrate data, automate business processes, and have real-time access to Microsoft services for seamless financial processes that reduce manual intervention and increase productivity. Among the main data integration methods discussed in the paper are automated data retrievals from SharePoint, Teams, and One Drive. It also quantifies the efficiency gains by reducing processing times, error rates, and operation costs compared to traditional ma

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Hribar, Michelle R., Sarah Read-Brown, Isaac H. Goldstein, et al. "Secondary use of electronic health record data for clinical workflow analysis." Journal of the American Medical Informatics Association 25, no. 1 (2017): 40–46. http://dx.doi.org/10.1093/jamia/ocx098.

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Abstract Objective Outpatient clinics lack guidance for tackling modern efficiency and productivity demands. Workflow studies require large amounts of timing data that are prohibitively expensive to collect through observation or tracking devices. Electronic health records (EHRs) contain a vast amount of timing data – timestamps collected during regular use – that can be mapped to workflow steps. This study validates using EHR timestamp data to predict outpatient ophthalmology clinic workflow timings at Oregon Health and Science University and demonstrates their usefulness in 3 different studi

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Liew, Chee Sun, Malcolm P. Atkinson, Radosław Ostrowski, Murray Cole, Jano I. van Hemert, and Liangxiu Han. "Performance database: capturing data for optimizing distributed streaming workflows." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 369, no. 1949 (2011): 3268–84. http://dx.doi.org/10.1098/rsta.2011.0134.

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The performance database (PDB) stores performance-related data gathered during workflow enactment. We argue that, by carefully understanding and manipulating these data, we can improve efficiency when enacting workflows. This paper describes the rationale behind the PDB, and proposes a systematic way to implement it. The prototype is built as part of the Advanced Data Mining and Integration Research for Europe project. We use workflows from real-world experiments to demonstrate the usage of PDB.

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Ma, Yinglong, Liying Zhang, and Moyi Shi. "Measuring Semantic and Structural Information for Data Oriented Workflow Retrieval with Cost Constraints." Mathematical Problems in Engineering 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/407809.

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The reuse of data oriented workflows (DOWs) can reduce the cost of workflow system development and control the risk of project failure and therefore is crucial for accelerating the automation of business processes. Reusing workflows can be achieved by measuring the similarity among candidate workflows and selecting the workflow satisfying requirements of users from them. However, due to DOWs being often developed based on an open, distributed, and heterogeneous environment, different users often can impose diverse cost constraints on data oriented workflows. This makes the reuse of DOWs challe

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Chakroborti, Debasish, Banani Roy, and Sristy Sumana Nath. "Designing for Recommending Intermediate States in A Scientific Workflow Management System." Proceedings of the ACM on Human-Computer Interaction 5, EICS (2021): 1–29. http://dx.doi.org/10.1145/3457145.

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To process a large amount of data sequentially and systematically, proper management of workflow components (i.e., modules, data, configurations, associations among ports and links) in a Scientific Workflow Management System (SWfMS) is inevitable. Managing data with provenance in a SWfMS to support reusability of workflows, modules, and data is not a simple task. Handling such components is even more burdensome for frequently assembled and executed complex workflows for investigating large datasets with different technologies (i.e., various learning algorithms or models). However, a great many

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Wen, Yiping, Junjie Hou, Zhen Yuan, and Dong Zhou. "Heterogeneous Information Network-Based Scientific Workflow Recommendation for Complex Applications." Complexity 2020 (March 19, 2020): 1–16. http://dx.doi.org/10.1155/2020/4129063.

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Scientific workflow is a valuable tool for various complicated large-scale data processing applications. In recent years, the increasingly growing number of scientific processes available necessitates the development of recommendation techniques to provide automatic support for modelling scientific workflows. In this paper, with the help of heterogeneous information network (HIN) and tags of scientific workflows, we organize scientific workflows as a HIN and propose a novel scientific workflow similarity computation method based on metapath. In addition, the density peak clustering (DPC) algor

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Satyam, Chauhan. "Enterprise Data Lakes for Financial Services." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 5, no. 5 (2019): 1–17. https://doi.org/10.5281/zenodo.14384176.

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Enterprise Data Lakes (EDLs) have emerged as transformative solutions for financial institutions seeking to address challenges associated with fragmented data systems, inefficient workflows, and stringent regulatory compliance. This paper presents an AWS-centric framework for building resilient and scalable EDLs tailored to the needs of financial services. Key aspects such as controlled change management, robust failover protocols, workflow orchestration, and secure data sharing are analyzed in detail. The study explores the design and implementation of data pipelines, leveraging AWS tools lik

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Wu, Keyao, and Shu Tang. "BIM-Assisted Workflow Enhancement for Architecture Preliminary Design." Buildings 12, no. 5 (2022): 601. http://dx.doi.org/10.3390/buildings12050601.

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China’s urban housing demand has directly influenced urbanization development. To stabilize the level of urbanization, it is urgent to optimize the whole life-cycle efficiency of construction and the preliminary design as the first step is even more significant. Building Information Modeling (BIM) is widely used as information technology in the construction industry to promote the implementation and management of projects. However, the traditional preliminary design approach still occupies the mainstream market without forming a systematic BIM workflow, which causes inefficiency. To address th

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Asma, A. Alzahrani, H. Alshammari Nouf, M. Alqahtani Shams, et al. "Exploring the Impact of Technology on Medication Management: A Mixed-Methods Study in a Tertiary Care Hospital." International Journal on Science and Technology 15, no. 1 (2024): 1–9. https://doi.org/10.5281/zenodo.14772803.

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Background: Medication errors pose significant challenges in healthcare, particularly in tertiary hospitals. Health information technology HIT) offers solutions to improve medication management, enhance patient safety, and optimize workflows. Objective: This study evaluates the impact of HIT on medication management using a mixed-methods approach.Methods: Quantitative data were collected through pre- and post-implementation comparisons of medication errors, adverse drug events ADEs), and workflow efficiency. Qualitative data included interviews and focus groups with healthcare providers a

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Hoffmann, Marc Steven, Adam Neiberger, Gloria Solis, Marshall Johnson, and Debbie Fernandez. "Sustaining safety and delivery of oral chemotherapy utilizing lean methodology." Journal of Clinical Oncology 39, no. 28_suppl (2021): 218. http://dx.doi.org/10.1200/jco.2020.39.28_suppl.218.

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218 Background: An oral chemotherapy safety event in 2017 prompted analysis of related workflows utilizing lean quality improvement methodology. Three kaizen workshops utilizing lean methodology with primary objectives to 1) develop safety standards for oral chemotherapy as rigorous as those for intravenous chemotherapy; 2) improve efficiency; and 3) design workflows that enable data collection and process control were conducted. Since 2017, our goal has been to sustain developed workflows to ensure oral chemotherapy patients have the right oral chemotherapy agent, at the right dose, at the ri

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Yeole, Priyanka, and Abhiroop Benkur. "Adaptive Workflow Orchestration using Neurophysiological Data in ERP and HRIS Systems." International Journal of Innovative Research in Computer and Communication Engineering 12, no. 12 (2023): 13136–46. https://doi.org/10.15680/ijircce.2024.1212018.

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The integration of neurophysiological data into Enterprise Resource Planning (ERP) and Human Resource Information Systems (HRIS) is an emerging area of research aimed at optimizing workflow orchestration in organizational environments. Traditional workflow management systems in ERP and HRIS often rely on static rulebased models that may not adapt efficiently to dynamic changes in user behavior, work conditions, or organizational needs. This paper explores the potential of adaptive workflow orchestration driven by neurophysiological data to create more personalized, responsive, and efficient sy

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Manish Prakashrao Dhaye, Mandar Gajanan Chatur, Pravesh Chandrashekhar Mhaiskar, Anushka Prakashrao Tayde, Prachi Prashant Ghatole, and Neha Gopal Rathi. "Enhancing hospital efficiency with AI-driven automation and blockchain-backed data management." International Journal of Science and Research Archive 15, no. 1 (2025): 205–14. https://doi.org/10.30574/ijsra.2025.15.1.0944.

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The management of hospitals has played a very critical role in the improvement of patient satisfaction and hospital activities. This paper addresses a new approach to the hospital management system: integrating artificial intelligence with blockchain technology to address the inefficiencies in traditional health workflow. It is characterized by AI-based appointment scheduling, disease-based recommendations for doctors, and virtual waiting rooms that minimize delay times and optimize resource usage. Blockchain technology provides secure data exchange of prescriptions, lab reports, and billing r

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Woolland, Oliver, Paul Brack, Stian Soiland-Reyes, Ben Scott, and Laurence Livermore. "Incrementally building FAIR Digital Objects with Specimen Data Refinery workflows." Research Ideas and Outcomes 8 (October 12, 2022): e94349. https://doi.org/10.3897/rio.8.e94349.

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<em>Specimen Data Refinery</em> (SDR) is a developing platform for automating transcription of specimens from natural history collections (Hardisty et al. 2022). SDR is based on computational workflows and digital twins using FAIR Digital Objects.We show our recent experiences with building SDR using the Galaxy workflow system and combining two FDO methodologies with open digital specimens (openDS) and RO-Crate data packaging. We suggest FDO improvements for incremental building of digital objects in computational workflows.SDR workflowsSDR is realised as the workflow system Galaxy (Afgan et a

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Lai, Yi Feng, Yan Ru Tan, Shu Xin Oh, Xianqi Wang, and Angelina Hui Min Tan. "Putting pharmacists in specialist outpatient clinics: a pilot approach to integrate services under one roof." Proceedings of Singapore Healthcare 27, no. 4 (2018): 290–93. http://dx.doi.org/10.1177/2010105818760049.

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Patient journey with multiple stopovers has long been recognized as suboptimal and attempts to co-locate pharmacists with physicians have been explored in various healthcare systems to integrate processes and improve patient experience. This prospective study aims to evaluate and compare process efficiency between a decentralized prescription review workflow (intervention) and conventional prescription filling workflow (control). Both workflows were concurrently assessed in selected specialist outpatient clinics. Outcome measure was end-to-end prescription processing time between intervention

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Researcher. "AI-DRIVEN DATA INTEGRATIONS AND AUTOMATIONS FOR CLINICAL RESEARCH OPERATIONS (CRO)." International Journal of Research In Computer Applications and Information Technology (IJRCAIT) 7, no. 2 (2024): 2140–49. https://doi.org/10.5281/zenodo.14348930.

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The complexity of modern clinical research operations (CRO) necessitates advanced solutions for managing vast datasets, streamlining workflows, and ensuring compliance with stringent regulatory requirements. AI-driven data integration and automation technologies have emerged as key enablers of efficiency and accuracy in CRO, facilitating real-time data synchronization, workflow automation, and predictive analytics. This comprehensive article examines the current challenges in clinical research operations, explores AI-driven solutions for data integration, evaluates automation technologies

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Hu, Liang, Xianwei Wu, and Xilong Che. "HICA: A Hybrid Scientific Workflow Scheduling Algorithm for Symmetric Homogeneous Resource Cloud Environments." Symmetry 17, no. 2 (2025): 280. https://doi.org/10.3390/sym17020280.

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With the increasing volume of scientific computation data and the advancement of computer performance, scientific computation is becoming more dependent on the powerful computing capabilities of cloud computing. On cloud platforms, tasks in scientific workflows are assigned to computational resources and executed according to specific strategies. Therefore, workflow scheduling has become a key factor affecting efficiency. This paper proposes a hybrid scientific workflow scheduling algorithm, HICA, to address the scheduling problem of scientific workflows in symmetric homogeneous cloud environm

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Haston, Elspeth, Robert Cubey, Martin Pullan, Hannah Atkins, and David Harris. "Developing integrated workflows for the digitisation of herbarium specimens using a modular and scalable approach." ZooKeys 209 (July 20, 2012): 93–102. https://doi.org/10.3897/zookeys.209.3121.

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Digitisation programmes in many institutes frequently involve disparate and irregular funding, diverse selection criteria and scope, with different members of staff managing and operating the processes. These factors have influenced the decision at the Royal Botanic Garden Edinburgh to develop an integrated workflow for the digitisation of herbarium specimens which is modular and scalable to enable a single overall workflow to be used for all digitisation projects. This integrated workflow is comprised of three principal elements: a specimen workflow, a data workflow and an image workflow.The

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Palanki, Vijaya Chaitanya. "AUGMENTING DATA SCIENCE WORKFLOWS: A COMPREHENSIVE ANALYSIS OF AI-DRIVEN PRODUCTIVITY ENHANCEMENTS." International Journal of Core Engineering & Management 5, no. 6 (2018): 89–95. https://doi.org/10.5281/zenodo.14064200.

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The rapid growth of artificial intelligence (AI) technologies has significantly impacted various fields, including data science. This paper explores how AI can enhance productivity in the data science workflow, from data collection and preprocessing to model development and deployment. We review key AI technologies such as automated machine learning, intelligent data cleaning, and AI-assisted coding; discussing their potential to streamline data science tasks and improve efficiency. Additionally, we examine the challenges and limitations of integrating AI into data science workflows, as well a

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Urban, Renáta, Sára Haluzová, Martin Strunga, et al. "AI-Assisted CBCT Data Management in Modern Dental Practice: Benefits, Limitations and Innovations." Electronics 12, no. 7 (2023): 1710. http://dx.doi.org/10.3390/electronics12071710.

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Within the next decade, artificial intelligence (AI) will fundamentally transform the workflow of modern dental practice. This paper reviews the innovations and new roles of dental assistants in CBCT data management with the support of AI. Its use in 3D data management brings new roles for dental assistants. Cone beam computed tomography (CBCT) technology is, together with intraoral 3D scans and 3D facial scans, commonly used 3D diagnostic in a modern digital dental practice. This paper provides an overview of the potential benefits of AI implementation for semiautomated segmentations in stand

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Wu, Danny T. Y., Lindsey Barrick, Mustafa Ozkaynak, Katherine Blondon, and Kai Zheng. "Principles for Designing and Developing a Workflow Monitoring Tool to Enable and Enhance Clinical Workflow Automation." Applied Clinical Informatics 13, no. 01 (2022): 132–38. http://dx.doi.org/10.1055/s-0041-1741480.

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Abstract Background Automation of health care workflows has recently become a priority. This can be enabled and enhanced by a workflow monitoring tool (WMOT). Objectives We shared our experience in clinical workflow analysis via three cases studies in health care and summarized principles to design and develop such a WMOT. Methods The case studies were conducted in different clinical settings with distinct goals. Each study used at least two types of workflow data to create a more comprehensive picture of work processes and identify bottlenecks, as well as quantify them. The case studies were

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Truong-Huu, Tram, Mohan Gurusamy, and Vishal Girisagar. "Dynamic embedding of workflow requests for bandwidth efficiency in data centers." Computer Networks 108 (October 2016): 184–98. http://dx.doi.org/10.1016/j.comnet.2016.08.018.

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Mariani, Marco Valerio, Carlo Lavalle, Giovanni Battista Forleo, et al. "HeartLogic™: real-world data—efficiency, resource consumption, and workflow optimization." European Heart Journal Supplements 25, Supplement_C (2023): C331—C336. http://dx.doi.org/10.1093/eurheartjsupp/suad058.

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Abstract Heart failure (HF) is a major and still growing medical problem and is characterized by episodes of acute decompensation that are associated with a negative prognosis and a significant burden on the patients, doctors, and healthcare resources. Early detection of incipient HF may allow outpatient treatment before patients severely decompensate, thus reducing HF hospitalizations and related costs. The HeartLogic™ algorithm is an automatic, remotely managed system combining data directly related to HF pathophysiology into a single score, the HeartLogic™ index. This index proved to be eff

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Prashant, Bhandare, Shinde Sourabh Baburao, Mali Mayur Mahesh, Dubal Rohit Mahadev, and Gardade Rohan Bibhishan. "Shree Clinical Laboratory Management Application Enhancing Workflow and Data Management Efficiency." International Journal of Computer Sciences and Engineering 12, no. 10 (2024): 56–61. https://doi.org/10.26438/ijcse/v12i10.5661.

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Monirah, I. Alenazi, I. Alhassoun Madawi, A. Alhammad Loulwah, and R. Alanazi Maryam. "Optimizing Laboratory Workflows for Enhanced Patient Care: Investigating Strategies to Streamline Processes and Improve Turnaround Times in Hospital Settings." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 6, no. 3 (2018): 1–6. https://doi.org/10.5281/zenodo.13375205.

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Objective: This study investigates strategies for optimizing laboratory workflows in hospital settings to enhance patient care and improve turnaround times for test results. Methods: A quantitative research design was employed across three large hospitals. Data were collected from 150 laboratory staff through structured surveys and hospital performance metrics. Turnaround times, staff perceptions, and laboratory performance metrics were analyzed before and after implementing workflow improvements, including automation, process redesign, and IT integration. Results: Significant reductions in tu

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Sun, Ziheng, Liping Di, Annie Burgess, Jason A. Tullis, and Andrew B. Magill. "Geoweaver: Advanced Cyberinfrastructure for Managing Hybrid Geoscientific AI Workflows." ISPRS International Journal of Geo-Information 9, no. 2 (2020): 119. http://dx.doi.org/10.3390/ijgi9020119.

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AI (artificial intelligence)-based analysis of geospatial data has gained a lot of attention. Geospatial datasets are multi-dimensional; have spatiotemporal context; exist in disparate formats; and require sophisticated AI workflows that include not only the AI algorithm training and testing, but also data preprocessing and result post-processing. This complexity poses a huge challenge when it comes to full-stack AI workflow management, as researchers often use an assortment of time-intensive manual operations to manage their projects. However, none of the existing workflow management software

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Prica, Teo, and Aleš Zamuda. "High-Performance Deployment Operational Data Analytics of Pre-Trained Multi-Label Classification Architectures with Differential-Evolution-Based Hyperparameter Optimization (AutoDEHypO)." Mathematics 13, no. 10 (2025): 1681. https://doi.org/10.3390/math13101681.

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This article presents a high-performance-computing differential-evolution-based hyperparameter optimization automated workflow (AutoDEHypO), which is deployed on a petascale supercomputer and utilizes multiple GPUs to execute a specialized fitness function for machine learning (ML). The workflow is designed for operational analytics of energy efficiency. In this differential evolution (DE) optimization use case, we analyze how energy efficiently the DE algorithm performs with different DE strategies and ML models. The workflow analysis considers key factors such as DE strategies and automated

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Farid, Mazen, Rohaya Latip, Masnida Hussin, and Nor Asilah Wati Abdul Hamid. "A fault-intrusion-tolerant system and deadline-aware algorithm for scheduling scientific workflow in the cloud." PeerJ Computer Science 7 (November 2, 2021): e747. http://dx.doi.org/10.7717/peerj-cs.747.

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Background Recent technological developments have enabled the execution of more scientific solutions on cloud platforms. Cloud-based scientific workflows are subject to various risks, such as security breaches and unauthorized access to resources. By attacking side channels or virtual machines, attackers may destroy servers, causing interruption and delay or incorrect output. Although cloud-based scientific workflows are often used for vital computational-intensive tasks, their failure can come at a great cost. Methodology To increase workflow reliability, we propose the Fault and Intrusion-to

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Fnu, Nagarajan. "Optimizing Customer Support in Ride-Hailing Platforms: Leveraging Data-Driven Decision-Making and Workflow Automation." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 9, no. 6 (2023): 1–4. https://doi.org/10.5281/zenodo.15087303.

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The ride-hailing industry has rapidly transformed urban mobility, offering convenient, on-demand transportation services to millions of users. However, as the industry has grown, customer expectations regarding service quality, reliability, and support have increased. Efficient customer support plays a critical role in retaining users and maintaining a competitive edge. Traditional support models, which rely heavily on manual intervention, often result in delays, inconsistencies, and inefficiencies. To address these challenges, ride-hailing platforms have embraced workflow automation and data-

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Saad, M. Aldhafyan, S. Alotaibi Mazen, A. Alahmari Abdullah, and N. Alshahrani Waseem. "Exploring the Impact of Pharmacy Workflow Design on Pharmacist Efficiency and Patient Safety: A Qualitative Study." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 6, no. 3 (2018): 1–7. https://doi.org/10.5281/zenodo.13348055.

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Background: Pharmacy workflow design significantly impacts pharmacist efficiency and patient safety. This qualitative study explores how pharmacists perceive the influence of workflow design on these factors. Objective: To investigate the effects of pharmacy workflow design on pharmacist efficiency and patient safety through pharmacists' experiences and perspectives. Methods: A qualitative study was conducted with semi-structured interviews of 20 pharmacists from various settings. Data were analyzed thematically to identify key themes related to workflow efficiency, patient safety, and job sat

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Sundari, Pipit, Grace Felas Silitonga, and Tettie Setiyarti. "Revolutionizing Workflows: The Role of Efficiency in Organizational Success." Ambidextrous Journal of Innovation Efficiency and Technology in Organization 2, no. 01 (2024): 1–10. http://dx.doi.org/10.61536/ambidextrous.v2i01.60.

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This research investigates the impact of workflow optimization and resource management on organizational success at PT. Citra Shipyard, with a particular focus on the mediating role of operational efficiency. Using a quantitative research design and random sampling of 80 employees, data were collected through structured questionnaires and analyzed with Smart PLS (Partial Least Squares Structural Equation Modeling). The study found that both workflow optimization and resource management significantly influence operational efficiency, which, in turn, has a strong effect on organizational success

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Sandhyarani Ganipaneni, Ravi Kiran Pagidi, Aravind Ayyagiri, Prof.(Dr) Punit Goel, Prof.(Dr.) Arpit Jain, and Dr Satendra Pal Singh. "Machine Learning for SAP Data Processing and Workflow Automation." Darpan International Research Analysis 12, no. 3 (2024): 744–75. http://dx.doi.org/10.36676/dira.v12.i3.131.

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In the rapidly evolving landscape of enterprise resource planning, the integration of Machine Learning (ML) into SAP data processing and workflow automation presents significant opportunities for enhancing operational efficiency and decision-making. This paper explores the methodologies and applications of ML algorithms in optimizing SAP environments, focusing on data processing, predictive analytics, and automation workflows. Firstly, we examine the role of ML in automating data extraction, transformation, and loading processes, which traditionally require substantial manual intervention. By

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Převorovský, Martin, Martina Hálová, Kateřina Abrhámová, Jiří Libus, and Petr Folk. "Workflow for Genome-Wide Determination of Pre-mRNA Splicing Efficiency from Yeast RNA-seq Data." BioMed Research International 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/4783841.

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Pre-mRNA splicing represents an important regulatory layer of eukaryotic gene expression. In the simple budding yeast Saccharomyces cerevisiae, about one-third of all mRNA molecules undergo splicing, and splicing efficiency is tightly regulated, for example, during meiotic differentiation. S. cerevisiae features a streamlined, evolutionarily highly conserved splicing machinery and serves as a favourite model for studies of various aspects of splicing. RNA-seq represents a robust, versatile, and affordable technique for transcriptome interrogation, which can also be used to study splicing effic

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Dr., Devidas Thosar, Sontakke Shubham, Aher Dnyanraj, Pethe Mahesh, and Patre Tanisha. "Smart Data Hub: Comprehensive Tool for Visualization, Mining, Cleaning & Prediction." Journal of Network Security and Data Mining 8, no. 2 (2025): 18–23. https://doi.org/10.5281/zenodo.15267546.

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<em>The exponential growth of data has led to an increased demand for platforms that streamline data processing and analysis. Smart Data HUB is a comprehensive solution that integrates data visualization, data mining, data cleaning, and predictive analysis in a unified system. This paper presents the architecture, implementation, and key functionalities of Smart Data HUB. The platform enables users to upload files in various formats (XML, CSV, Word, Text) and apply multiple data processing techniques efficiently. The experimental results indicate that the system enhances workflow efficiency by

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Lee, Jessica J. Y., Clara D. M. van Karnebeek, and Wyeth W. Wasserman. "Development and user evaluation of a rare disease gene prioritization workflow based on cognitive ergonomics." Journal of the American Medical Informatics Association 26, no. 2 (2018): 124–33. http://dx.doi.org/10.1093/jamia/ocy153.

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AbstractObjectiveThe clinical diagnosis of genetic disorders is undergoing transformation, driven by whole exome sequencing and whole genome sequencing (WES/WGS). However, such nucleotide-level resolution technologies create an interpretive challenge. Prior literature suggests that clinicians may employ characteristic cognitive processes during WES/WGS investigations to identify disruptions in genes causal for the observed disease. Based on cognitive ergonomics, we designed and evaluated a gene prioritization workflow that supported these cognitive processes.Materials and MethodsWe designed a

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Dervinis, Donatas. "EFFICIENCY STUDY OF A PRODUCTION LINE USING A DATA COLLECTION SYSTEMS." Applied Scientific Research 5, no. 1 (2025): 24–30. https://doi.org/10.56131/tmt.2025.5.1.343.

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This article presents a methodology for evaluating the efficiency of a conveyor-based production line in the textile industry using an automated data collection system. The primary goal of the study is to assess production performance through real-time data acquisition and analysis. The developed approach enables efficiency measurement through two alternative methods: analyzing individual worker productivity and evaluating the overall production line output. The research utilizes production data collected from a textile manufacturing company, incorporating both the company's ETON transportatio

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Nagarajan. "Scaling Business Process Automation: Case Studies from Ride-Hailing and Autonomous Vehicles." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 13, no. 1 (2025): 1–5. https://doi.org/10.5281/zenodo.15084384.

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As businesses scale, optimizing operational efficiency through workflow automation has become essential. Large-scale systems, such as ride-hailing platforms and autonomous vehicle networks, rely on process automation to enhance service reliability, reduce manual intervention, and improve customer experience. This paper explores how workflow automation optimizes operations and reduces inefficiencies in complex systems. Specifically, it examines Lyft’s automated dispute resolution system and Zoox’s incident response and fleet monitoring workflows as case studies of business process a

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Kumer, Jeff, and Eric Ibsen. "A Novel Approach to Improve Immunological Animal Study Conduct Efficiency, Data Integration, Consistency and Security and the Sharing of Results (124.16)." Journal of Immunology 188, no. 1_Supplement (2012): 124.16. http://dx.doi.org/10.4049/jimmunol.188.supp.124.16.

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Abstract The traditional management of immunological animal studies and results is challenging due to complex, varied workflows as well as the acquisition, analysis, secure storage and accessibility of disparate data types acquired and stored in multiple formats and locations. Existing approaches often poorly reflect the details of planned-versus-actual study conduct, animal welfare considerations, and integration of data types in various paper and electronic formats. Errors and non-standardized condition scoring, data acquisition, processing, analyses are common problems as is impeded access

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HARI SURESH BABU GUMMADI. "AI-Driven Workflow Optimization for Supply Chain Management: A Case Study Approach." Journal of Computer Science and Technology Studies 7, no. 3 (2025): 426–35. https://doi.org/10.32996/jcsts.2025.7.3.49.

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This technical article examines the application of artificial intelligence techniques to optimize workflows in supply chain management through a case study methodology. It analyzes how modern AI technologies including machine learning, deep learning, and reinforcement learning can address critical challenges in contemporary supply chains across diverse industries. Through detailed examination of five distinct organizations that have implemented AI-driven workflow optimization solutions, It identifies common technical challenges, success factors, and implementation approaches. It provides evide

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Li, Xiang, Lorenzo Teppati Losè, and Fulvio Rinaudo. "Documentation for Architectural Heritage: A Historical Building Information Modeling Data Modeling Approach for the Valentino Castle North Wing." ISPRS International Journal of Geo-Information 14, no. 4 (2025): 139. https://doi.org/10.3390/ijgi14040139.

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Although HBIM (Historical Building Information Modeling) excels in geometric data acquisition and modeling within Scan-to-BIM (Building Information Modeling) workflows, its application in digital documentation faces persistent challenges, such as balancing precision and efficiency, ambiguous information structures, and the absence of standardized protocols. To address these issues, this study refines key steps from the systematic Scan-to-BIM process and proposes a documentation-oriented HBIM workflow. The workflow is designed to tackle data complexity and semantic alignment challenges through

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Suman Ankampally. "Enterprise Data Workflow Automation: A Technical Guide to Implementation and Best Practices." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 6 (2024): 2264–74. https://doi.org/10.32628/cseit2410612430.

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This comprehensive technical article explores the revolutionary field of business data workflow automation, covering best practices and crucial implementation factors in a range of organizational areas. In addition to offering insights into upcoming trends, the study looks at technological implementation stacks, development frameworks, security protocols, real-world applications, and strategic planning approaches. This article illustrates how businesses can successfully switch from manual to automated workflows while preserving operational integrity and optimizing efficiency through in-depth i

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Kolbasin, Viacheslav. "ORCHESTRATION OF CUSTOMER INTERACTION WORKFLOWS IN ENTERPRISE APPLICATIONS." Bulletin of National Technical University "KhPI". Series: System Analysis, Control and Information Technologies, no. 2 (12) (December 24, 2024): 104–7. https://doi.org/10.20998/2079-0023.2024.02.16.

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Process automation is an important factor in the development of modern corporate systems, in particular e-commerce systems. One of the tasks that must be solved during development of such systems is the orchestration of customer interaction processes, which are asynchronous in nature. Modern popular orchestration frameworks (Airflow for example), are not very well adapted to simultaneously waiting for a response from the client for a large number of workflows. This leads to unnecessary costs of computing resources and a decrease in the economic efficiency of the system. This paper considers th

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Wijerathna, Ashirwada, Srinath Perera, Samudaya Nanayakkara, and Sisi Zlatanova. "Developing a Workflow for Transforming BIM Models into Immersive Virtual Reality Experiences." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4-2024 (October 21, 2024): 485–92. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-2024-485-2024.

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Abstract. The integration of Extended Reality (XR) and Building Information Modelling (BIM) has emerged as a promising approach for enhancing interaction with spatial data in the built environment. While the potential of BIM for advanced visualization has been recognized, there remains a need for standardized workflows that facilitate the transformation of BIM models into immersive virtual reality (VR) experiences. This research contributes to the ongoing development of BIM-VR integration by presenting a workflow that leverages Revit, Twinmotion, and Datasmith to create visually rich and inter

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Liu, Xiaozhen, Yicong Huang, Xinyuan Lin, Avinash Kumar, Sadeem Alsudais, and Chen Li. "Pasta: A Cost-Based Optimizer for Generating Pipelining Schedules for Dataflow DAGs." Proceedings of the ACM on Management of Data 2, no. 6 (2024): 1–26. https://doi.org/10.1145/3698832.

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Data analytics tasks are often formulated as data workflows represented as directed acyclic graphs (DAGs) of operators. The recent trend of adopting machine learning (ML) techniques in workflows results in increasingly complicated DAGs with many operators and edges. Compared to the operator-at-a-time execution paradigm, pipelined execution has benefits of reducing the materialization cost of intermediate results and allowing operators to produce results early, which are critical in iterative analysis on large data volumes. Correctly scheduling a workflow DAG for pipelined execution is non-triv

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Rakaeva, A., and A. Rakaeva. "Optimizing Business Processes with AI, BPMN 2.0, and Workflow Management Systems." ECONOMIC Series of the Bulletin of the L.N.Gumilyov ENU, no. 4 (December 31, 2024): 129–42. https://doi.org/10.32523/2789-4320-2024-4-129-142.

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This research discusses the integration of artificial intelligence (AI), workflow management systems (WMS) and business process models and notes (BPMN) to improve the efficiency of modern business processes. Advanced technologies can significantly increase productivity, reduce costs and improve decision-making. The data analysis and automation capabilities of artificial intelligence enable companies to solve problems faster, optimize resource allocation and make better decisions. In combination with WMS, AI optimizes processes, automates workflows and increases operational efficiency. BPMN 2.0

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Ashif Anwar. "Machine learning workflow in modern accounting: From data ingestion to risk analysis." World Journal of Advanced Engineering Technology and Sciences 15, no. 2 (2025): 2168–75. https://doi.org/10.30574/wjaets.2025.15.2.0729.

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This article explores the transformative impact of artificial intelligence on the accounting profession. The article shows how machine learning algorithms and natural language processing have revolutionized financial data analysis, enhancing pattern recognition capabilities and anomaly detection in financial statements. It shows the significant efficiency improvements in document review and data extraction achieved through NLP technologies, while highlighting how AI has fundamentally transformed budgeting and financial forecasting practices through sophisticated predictive modeling techniques.

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Cabaobao, Jr., Andresito A., Sushmita L. Malubag, Jesus Briones, and Marmelo V. Abante. "Evaluating Workflow Automation Efficiency in A Government Agency in the Philippines." International Journal of Entrepreneurship and Sustainability Studies 4, no. 2 (2024): 30–46. https://doi.org/10.31098/ijeass.v4i2.2749.

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Workflow automation plays a vital role in developing efficient government operations. Anchored on the Technology Acceptance Model, this descriptive-correlational study evaluated the efficiency of using automation tools in key work processes of a Philippine government agency. A census of the population was used to gather data from the 31 employees directly involved in the subject agency’s automation processes. Data were collected through a researcher-structured, validated questionnaire via Google Forms. These data were analyzed using frequency, percentage, weighted mean, multiple linear regress

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Fagbore, Olasunbo Olajumoke, Jeffrey Chidera Ogeawuchi, Oluwatosin Ilori, Ngozi Joan Isibor, Azeez Odetunde, and Bolaji Iyanu Adekunle. "Optimizing Client Onboarding Efficiency Using Document Automation and Data-Driven Risk Profiling Models." Journal of Frontiers in Multidisciplinary Research 3, no. 1 (2022): 241–57. https://doi.org/10.54660/.jfmr.2022.3.1.241-257.

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Client onboarding is a critical process in financial services, investment management, and regulatory compliance, where speed, accuracy, and risk mitigation determine client experience and institutional integrity. This study explores the optimization of client onboarding efficiency through the integration of document automation and data-driven risk profiling models. Drawing from my direct contributions in onboarding operations, the research focuses on workflow innovations and automated documentation systems that streamline identity verification, compliance checks, and KYC procedures. Traditiona

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Fernandez, Debbie, Kathy Hulen, Leigh Anne Scott, et al. "Enhancing safety and delivery of oral chemotherapy utilizing lean methodology." Journal of Clinical Oncology 36, no. 30_suppl (2018): 266. http://dx.doi.org/10.1200/jco.2018.36.30_suppl.266.

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266 Background: An oral chemotherapy safety event prompted analysis of related workflows utilizing lean quality improvement methodology. This analysis identified high variation in prescription processing, lack of standardized safety checks, inefficient use of pharmacy time, and inadequate data collection. Our goal was to create an oral chemotherapy protocol that could ensure patients have the right oral chemotherapy agent, at the right dose, at the right time, with independent and efficient safety checks by nursing, pharmacy, and providers. Methods: Multidisciplinary teams participated in two

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