Relevant bibliographies by topics / Algorithmic service encounters

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Academic literature on the topic 'Algorithmic service encounters'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Algorithmic service encounters"

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Hoang, Khang TRAN. "Cognitive-Affective Responses to Algorithmic Service Encounters: A Multi-Theoretical Analysis of AI-Mediated Customer Experience, Brand Relationship Quality, and Satisfaction Dynamics in Vietnam's Digital Marketplace." Journal of Economics, Finance And Management Studies 08, no. 05 (2025): 2274–84. https://doi.org/10.5281/zenodo.15501654.

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This research investigates the complex interplay between cognitive-affective responses and algorithmic service encounters in Vietnam's rapidly evolving digital marketplace. Through a multi-theoretical lens integrating service-dominant logic, cognitive appraisal theory, technology acceptance model, and relationship marketing frameworks, this study examines how artificial intelligence (AI) mediated customer experiences influence brand relationship quality and satisfaction. Employing a robust mixed-method approach combining structural equation modeling with partial least squares (PLS-SEM) and fuz
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Zhang, Zhiping, and Changda Wang. "Service Function Chain Migration: A Survey." Computers 14, no. 6 (2025): 203. https://doi.org/10.3390/computers14060203.

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As a core technology emerging from the convergence of Network Function Virtualization (NFV) and Software-Defined Networking (SDN), Service Function Chaining (SFC) enables the dynamic orchestration of Virtual Network Functions (VNFs) to support diverse service requirements. However, in dynamic network environments, SFC faces significant challenges, such as resource fluctuations, user mobility, and fault recovery. To ensure service continuity and optimize resource utilization, an efficient migration mechanism is essential. This paper presents a comprehensive review of SFC migration research, ana
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Tikaningsih, Ades. "Optimizing Waste Collection Routes in Purwokerto using the Dijkstra Algorithm." Publication of the International Journal and Academic Research 1, no. 2 (2025): 78–85. https://doi.org/10.63222/pijar.v1i2.21.

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Waste is a complex problem that has the potential to cause environmental degradation if not handled properly. Waste management in Banyumas Regency, particularly in the Purwokerto area, encounters several fundamental limitations, including the limited capacity of the transportation fleet and the lack of an integrated route distribution system. Based on the documentation of the Banyumas Regency Environmental Service, of the total daily waste generation amounting to 600 tons, only 45% is transported to the Final Disposal Site (TPA), highlighting the urgent need for optimization in the waste manag
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Ku, Chu-Chang, Chien-Chou Chen, Simon Dixon, Hsien Ho Lin, and Peter J. Dodd. "Patient pathways of tuberculosis care-seeking and treatment: an individual-level analysis of National Health Insurance data in Taiwan." BMJ Global Health 5, no. 6 (2020): e002187. http://dx.doi.org/10.1136/bmjgh-2019-002187.

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IntroductionPatients with tuberculosis (TB) often experience difficulties in accessing diagnosis and treatment. Patient pathway analysis identifies mismatches between TB patient care-seeking patterns and service coverage, but to date, studies have only employed cross-sectional aggregate data.MethodsWe developed an algorithmic approach to analyse and interpret patient-level routine data on healthcare use and to construct patients’ pathways from initial care-seeking to treatment outcome. We applied this to patients with TB in a simple random sample of one million patients’ records in the Taiwan
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Wang, Yuhong, and Yiqin Sheng. "Two-stage optimization of instant distribution of fresh products based on improved NSGA-III algorithm." International Journal of Industrial Engineering Computations 16, no. 3 (2025): 535–56. https://doi.org/10.5267/j.ijiec.2025.5.002.

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As an important part of the fresh produce business format, fresh food instant delivery encounters numerous challenges. Issues like high losses, complex cold chains and time sensitivity lead to increased costs. Additionally, the living space of end-delivery personnel is under pressure and the talent market is saturated. The platform algorithms focus on the interests of themselves and customers while relatively overlooking those of delivery personnel, which affects the overall operation quality, resulting in a significant reduction in delivery efficiency and a remarkable decline in service quali
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Zhu, Huiyi. "Risks and Countermeasures of Personal Information Processing in Minors’ Network Socialization." Law and Economy 4, no. 2 (2025): 58–67. https://doi.org/10.56397/le.2025.02.08.

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Minors experience network cognition, network imitation and network interaction in the algorithmic society. The invisible hand of algorithm is inseparable from every network action. When minors encounter algorithmic recommendation services on social media, their personal information is abused by the algorithm. The existing regulations for the protection of personal information based on algorithms have some problems, such as rigid age division of notification and consent mechanism and one-time notification and consent. In this regard, it is necessary to re-establish the risk assessment system fo
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Gruber, Jonathan, and Eszter Hargittai. "The importance of algorithm skills for informed Internet use." Big Data & Society 10, no. 1 (2023): 205395172311681. http://dx.doi.org/10.1177/20539517231168100.

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Using the Internet means encountering algorithmic processes that influence what information a user sees or hears. Existing research has shown that people's algorithm skills vary considerably, that they develop individual theories to explain these processes, and that their online behavior can reflect these understandings. Yet, there is little research on how algorithm skills enable people to use algorithms to their own benefit and to avoid harms they may elicit. To fill this gap in the literature, we explore the extent to which people understand how the online systems and services they use may
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G. Raja Ramesh. "Utilizing Hybrid Cloud Computing with Machine Learning and Deep Learning to Enhance Privacy, Security, and Empower Patients." Journal of Information Systems Engineering and Management 10, no. 3 (2025): 1226–36. https://doi.org/10.52783/jisem.v10i3.7194.

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This study investigates the effectiveness of Hybrid Cloud solutions in meeting the challenges encountered within the healthcare sector. Hybrid Cloud technology provides adaptable, on-demand services that empower hospitals and clinics to sidestep costly infrastructure upgrades and streamline maintenance costs. The scalability of cloud platforms addresses the fluctuating demands of the health and wellness industry, supported by fail-safes like disaster recovery and redundancy to ensure continuous service availability. At the heart of this infrastructure lies the Hybrid Health Cloud (HHC), servin
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Meer, Elana A., Maguire Herriman, Doreen Lam, et al. "Design, Implementation, and Validation of an Automated, Algorithmic COVID-19 Triage Tool." Applied Clinical Informatics 12, no. 05 (2021): 1021–28. http://dx.doi.org/10.1055/s-0041-1736627.

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Abstract Objective We describe the design, implementation, and validation of an online, publicly available tool to algorithmically triage patients experiencing severe acute respiratory syndrome coronavirus (SARS-CoV-2)-like symptoms. Methods We conducted a chart review of patients who completed the triage tool and subsequently contacted our institution's phone triage hotline to assess tool- and clinician-assigned triage codes, patient demographics, SARS-CoV-2 (COVID-19) test data, and health care utilization in the 30 days post-encounter. We calculated the percentage of concordance between too
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Kharitonova, Yu, N. S. Malik, and T. Yang. "The Legal Issue of Deterrence of Algorithmic Control of Digital Platforms: The Experience of China, the European Union, Russia and India." BRICS Law Journal 10, no. 1 (2023): 147–70. http://dx.doi.org/10.21684/2412-2343-2023-10-1-147-170.

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The authorities in a number of states are concerned about the need for public disclosure of the recommendation algorithms that are used in online services. The introduction of regulations aimed at software developers is frequently proposed as a potential solution to this problem of algorithm transparency. These requirements, which must be fulfilled by the developers of software products, can be administrative regulations or standards regulations. However, despite these efforts, in the absence of direct legislative regulation, users continue to encounter the possibility that a social network fe
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Books on the topic "Algorithmic service encounters"

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Mehta, Vaishali, Dolly Sharma, Monika Mangla, Anita Gehlot, Rajesh Singh, and Sergio Márquez Sánchez, eds. Challenges and Opportunities for Deep Learning Applications in Industry 4.0. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/97898150360601220101.

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The competence of deep learning for the automation and manufacturing sector has received astonishing attention in recent times. The manufacturing industry has recently experienced a revolutionary advancement despite several issues. One of the limitations for technical progress is the bottleneck encountered due to the enormous increase in data volume for processing, comprising various formats, semantics, qualities and features. Deep learning enables detection of meaningful features that are difficult to perform using traditional methods. The book takes the reader on a technological voyage of th
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Book chapters on the topic "Algorithmic service encounters"

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Högberg, Karin. "Technostress Among Hotel Employees - a Longitudinal Study of Social Media as Digital Service Encounters." In Information and Communication Technologies in Tourism 2021. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65785-7_6.

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AbstractThe increasing implementation of digital technologies in organizations such as social media platforms is fundamentally transforming the nature of services encounters [1, 2], not least in the hospitality industry. This causes new ways of working for hotel employees, causing disruption in service routines and work tasks. There are few qualitative studies that are focusing on the hospitality industry and technostress. The present study focus on technostress among employees in an international hotel chain. Data have been collected in eight European countries over a period of seven years. T
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Liao, Xinhai, Jiaqi Wu, Zilin Jia, and Jiaxing Xian. "Precise Services in Smart Cultural Tourism for Tourists." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2024. https://doi.org/10.3233/faia241443.

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In response to the specific problems encountered in addressing the needs of tourists in the cultural and tourism industry, innovations have been introduced how Big Data enhances precision services in smart tourism through a tourist-centric framework that improves personalization and accuracy using advanced algorithms. A service model centered on tourists and utilizing information technology to achieve precise smart cultural and tourism services has been proposed. Based on collaborative filtering recommendation systems, combined with the transformer model, predictions are made on tourist needs
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Shahra, Essa Qasem, Tarek Rahil Sheltami, and Elhadi M. Shakshuki. "A Comparative Study of Range-Free and Range-Based Localization Protocols for Wireless Sensor Network." In Sensor Technology. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2454-1.ch071.

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Wireless Sensor Network is deployed in many fields including military operations, mechanical applications, human services, smart homes, etc. However, deploying WSN encounters many challenges. One of the challenges is localizing the node position, especially mobile targets in critical situations. In this paper, the authors compare two types from range-free localization algorithms and one type from range-based algorithms, namely: Received Signal Strength (RSS), Centroid, and Distance Vector Hop (DV-Hops) protocols, using Cooja simulator. RSS localization algorithms require determining values of
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Liang, Wenkai, Yuanlong Yu, and Hangjiang Guo. "A Location Privacy Protection Scheme Combining Locality-Sensitive Hashing and Landmark Positioning." In Advances in Transdisciplinary Engineering. IOS Press, 2025. https://doi.org/10.3233/atde250297.

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Location data plays a crucial role in location-based services (LBS) as it enables service providers to analyze users’ daily activities and infer their behavioral patterns. Effectively protecting user privacy during the use of these services is a significant research topic in the field of cybersecurity. Currently, researchers have made substantial progress by generating cloaking points based on users’ actual locations to safeguard their location data. However, this method still encounters challenges related to inaccurate positioning and the potential to deduce actual locations. To address these
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Kitanov, Stojan, Borislav Popovski, and Toni Janevski. "Quality Evaluation of Cloud and Fog Computing Services in 5G Networks." In Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-5339-8.ch086.

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Because of the increased computing and intelligent networking demands in 5G network, cloud computing alone encounters too many limitations, such as requirements for reduced latency, high mobility, high scalability, and real-time execution. A new paradigm called fog computing has emerged to resolve these issues. Fog computing distributes computing, data processing, and networking services to the edge of the network, closer to end users. Fog applied in 5G significantly improves network performance in terms of spectral and energy efficiency, enable direct device-to-device wireless communications,
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Kitanov, Stojan, Borislav Popovski, and Toni Janevski. "Quality Evaluation of Cloud and Fog Computing Services in 5G Networks." In Research Anthology on Developing and Optimizing 5G Networks and the Impact on Society. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7708-0.ch012.

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Because of the increased computing and intelligent networking demands in 5G network, cloud computing alone encounters too many limitations, such as requirements for reduced latency, high mobility, high scalability, and real-time execution. A new paradigm called fog computing has emerged to resolve these issues. Fog computing distributes computing, data processing, and networking services to the edge of the network, closer to end users. Fog applied in 5G significantly improves network performance in terms of spectral and energy efficiency, enable direct device-to-device wireless communications,
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Kitanov, Stojan, Borislav Popovski, and Toni Janevski. "Quality Evaluation of Cloud and Fog Computing Services in 5G Networks." In Enabling Technologies and Architectures for Next-Generation Networking Capabilities. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-6023-4.ch001.

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Because of the increased computing and intelligent networking demands in 5G network, cloud computing alone encounters too many limitations, such as requirements for reduced latency, high mobility, high scalability, and real-time execution. A new paradigm called fog computing has emerged to resolve these issues. Fog computing distributes computing, data processing, and networking services to the edge of the network, closer to end users. Fog applied in 5G significantly improves network performance in terms of spectral and energy efficiency, enable direct device-to-device wireless communications,
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Thandayuthapani, S., P. Thirumoorthi, P. Elantheraiyan, Leena Jenefa, and M. Selvakumar. "An Exploration of Consumer Engagement Strategies Through the Lens of Artificial Intelligence in Marketing Personalization." In Advances in Marketing, Customer Relationship Management, and E-Services. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-7122-0.ch008.

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The study uses consumer involvement theory to examine AI's potential to change marketing through personalization. Using client data and past encounters, AI may adapt messaging and boost engagement. Gamification motivates consumers—AI provides individualized gamified marketing for greater brand interactions. Predictive algorithms employ user data to customize adverts, product recommendations, and demographic content. NLP systems assess sentiment from social media/reviews. Companies can make messaging more engaging. Conversational AI improves consumer connections with real-time product recommend
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Jindal, Priyanshi, and Harshit Gouri. "AI-Personalization Paradox." In Advances in Marketing, Customer Relationship Management, and E-Services. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-1918-5.ch004.

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The integration of AI into various aspects of our lives has significantly reshaped how we access information, products, and services. AI-driven personalization, a key feature of many platforms, aims to enhance user experiences by tailoring content to individual preferences. Advancement of AI personalization has given rise to the filter bubble and echo-chamber phenomena. Filter bubbles expose consumers to content that reinforces their existing beliefs and preferences, creating a paradox. This chapter explores the multifaceted implications of AI-personalization paradox on digital consumer behavi
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Singha, Surjit. "Social Media's Influence on Consumer Decision-Making." In Advances in Marketing, Customer Relationship Management, and E-Services. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-3811-7.ch004.

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Within the ever-evolving realm of social media marketing, enterprises encounter various obstacles and prospects. Effective strategies prioritize using narratives, fostering community, demonstrating transparency, and embracing authenticity. A combination of quantitative metrics and qualitative insights is necessary for calculating ROI. In anticipation of the future, social media platforms will feature personalized AI-driven experiences, immersive experiences, and an emphasis on audio-centric content. Amidst obstacles such as algorithm modifications and privacy apprehensions, prospects emerge th
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Conference papers on the topic "Algorithmic service encounters"

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Shaffer, Joshua, Joseph B. Kopena, and William C. Regli. "Web Service Interfaces for Design Repositories." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85386.

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Reuse of design knowledge is an important goal in engineering design, and has received much attention. A substantial set of algorithms, methodology, and developed systems exist which support various aspects of this goal. However, the majority of these systems are built around a particular user interface, often some form of Web-based repository portal. The work described here presents search and other core functionality as web services rather than a monolithic repository system. These services may then be employed by a variety of applications, integrating them into interfaces familiar to the de
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Hussein, Dina, Taha Belkhouja, Ganapati Bhat, and Janardhan Rao Doppa. "Energy-Efficient Missing Data Imputation in Wearable Health Applications: A Classifier-aware Statistical Approach." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/807.

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Wearable devices are being increasingly used in high-impact health applications including vital sign monitoring, rehabilitation, and movement disorders. Wearable health monitoring can aid in the United Nations social development goal of healthy lives by enabling early warning, risk reduction, and management of health risks. Health tasks on wearable devices employ multiple sensors to collect relevant parameters of user’s health and make decisions using machine learning (ML) algorithms. The ML algorithms assume that data from all sensors are available for the health monitoring tasks. However, th
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Rocher, Antonin, Jean-Charles Maré, and Roland Becquet. "Model-based Failure Anticipation and Predictive Maintenance: a Landing Gear Application." In Vertical Flight Society 77th Annual Forum & Technology Display. The Vertical Flight Society, 2021. http://dx.doi.org/10.4050/f-0077-2021-16800.

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In order to reduce maintenance for the operators and improve the availability of their aircrafts, new failure anticipation methods are being implemented at Airbus Helicopters. This paper focuses on the rapid development and entry into service of a monitoring and alerting algorithm able to provide a diagnosis for the most common faults encountered in-service on a landing gear system. This development is based on a hybrid approach combining analysis on historical data and multiphysics modelling and simulation. Reliable health indicators are built to greatly reduce the amount of data to be contin
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Bhende, Veena, Kamna Bhadoriya, Subodh Ghonge, Aryan Kadam, and Yash Kalange. "AI-Based Software Application Planner." In The Second International Conference of AI new Technology and open Discussion. Algorithm Lab, 2025. https://doi.org/10.63211/j.p.25.645302.

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AI planning aims to automate goal-oriented tasks through structured methodologies. While traditional AI tools demonstrate significant capabilities, they often encounter challenges in practical real-world applications. To overcome these limitations, we propose a service-oriented planning architecture that organizes AI planning functionalities into modular and reusable components. Our system automates project architecture design based on user inputs, employing algorithms such as decision trees to recommend optimal technology stacks. Users benefit from customized architectural diagrams that facil
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Drouet, Céline, Nicolas Cellier, Jérémie Raymond, and Denis Martigny. "Sea State Estimation Based on Ship Motions Measurements and Data Fusion." In ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/omae2013-10657.

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In-service monitoring can help to increase safety of ships especially regarding the fatigue assessment. For this purpose, it is compulsory to know the environmental conditions encountered: wind, but also the full directional wave spectrum. During the EU TULCS project, a full scale measurements campaign has been conducted onboard the CMA-CGM 13200 TEU container ship Rigoletto. She has been instrumented to measure deformation of the ship as well as the sea state encountered during its trip. This paper will focus on the sea state estimation. Three systems have been installed to estimate the sea s
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Cuanang, Jonas, Constantine Tarawneh, Martin Amaro, Jennifer Lima, and Heinrich Foltz. "Optimization of Railroad Bearing Health Monitoring System for Wireless Utilization." In 2020 Joint Rail Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/jrc2020-8060.

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Abstract In the railroad industry, systematic health inspections of freight railcar bearings are required. Bearings are subjected to high loads and run at high speeds, so over time the bearings may develop a defect that can potentially cause a derailment if left in service operation. Current bearing condition monitoring systems include Hot-Box Detectors (HBDs) and Trackside Acoustic Detection Systems (TADS™). The commonly used HBDs use non-contact infrared sensors to detect abnormal temperatures of bearings as they pass over the detector. Bearing temperatures that are about 94°C above ambient
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Ding, Wei, and Zhaoyi Li. "Analysis of Intelligent Design of Service Robot Based on Intelligent Transformation." In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1002317.

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Over the past 30 years from the end of the 20th century to the present, service robotics technology has made great progress, and many important results have been achieved in the broad interdisciplinary fields of robot mechanical structure, information transmission and interaction, material science, automation control, sensor technology, etc. . Every breakthrough in key technologies has enabled service robots to develop rapidly in the direction that people expect. With the in-depth development of Internet technology, the comprehensive popularization and promotion of the Internet of Things techn
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Bo, Cao, Song Yu, Xu Feng, and Peng Fukang. "Development of Time Series Drilling Datasets for Stuck Pipe Prediction Using Volve Field Data." In ASME 2024 43rd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/omae2024-128386.

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Abstract Numerous machine learning algorithms are applied in the oil and gas industry. However, the data used in these studies are difficult to obtain due to various limitations. Due to the lack of benchmark datasets, it is challenging to make performance comparisons across different algorithms. Volve field dataset was made public by Equinor, which provides raw data availability for the development of drilling and completion datasets. In this paper, we utilize the time-based drilling data from the Volve drilling platform and transform it into time series datasets for stuck pipe prediction. Spe
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Yue, Xizhou, Guoyu Li, Mingxue Ma, Shanjun Li, and John Zhou. "Simultaneous Correction of Shoulder-Bed and Anisotropy Effects on LWD Propagation Resistivity Logs in HAHZ Wells." In 2024 SPWLA 65th Annual Symposium. Society of Petrophysicists and Well Log Analysts, 2024. https://doi.org/10.30632/spwla-2024-0110.

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Petrophysicists are often confounded by which one of the many resistivity logs should be used in formation evaluation. There is a diverse number of logging-while-drilling (LWD) propagation tools on the market from a wide range of service providers. Depending on the vendor, one may encounter as many as eight to 30 propagation resistivity curves. These logs have varying degrees of measurement accuracy and different response characteristics. Furthermore, it is well known that shoulder-bed and formation anisotropy significantly affect the propagation resistivity readings, especially in high-angle
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Hanif, Amer, Elton Frost, Fei Le, Marina Nikitenko, Mikhail Blinov, and Nikolay Velker. "A Fast ANN Trained Solver Enables Real-Time Radial Inversion of Dielectric Dispersion Data & Accurate Estimate of Reserves in Challenging Environments." In SPE Middle East Oil & Gas Show and Conference. SPE, 2021. http://dx.doi.org/10.2118/204904-ms.

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Abstract Dielectric dispersion measurements are increasingly used by petrophysicists to reduce uncertainty in their hydrocarbon saturation analysis, and subsequent reserves estimation, especially when encountered with challenging environments. Some of these challenges are related to variable or unknown formation water salinity and/or a changing rock texture which is a common attribute of carbonate reservoirs found in the Middle East. A new multi-frequency, multi-spacing dielectric logging service, utilizes a sensor array scheme which provides wave attenuation and phase difference measurements
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