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1

Zhang, Chen Yu, Guang Jie Han, Chuan Zhu, and Tong Qing Liu. "The Insights of Node Deployment for Localization Accuracy in Underwater Acoustic Sensor Networks." Advanced Materials Research 605-607 (December 2012): 1050–53. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.1050.

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Node deployment is a reflection of cost and performance in Underwater Acoustic Sensor Networks (UASNs). In this paper, we compared three different node deployment strategies, namely random deployment, grid deployment and tetrahedral deployment, on aspects of node number, end-to-end delay, localization accuracy, coverage and connectivity. Simulation shows that tetrahedral deployment strategy has the smallest localization error. As connectivity is to be ensured, coverage can be reduced depending on the ratio of r/s.
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Piridi, Sarat, Satyanarayana Asundi, and Dr James C. Hyatt. "Cross-Environment Deployment Strategies for Power Platform Solutions – Investigating best practices for managing multi-environment deployments, from development to production, using managed environments and DevOps." International Journal of Advanced Engineering Research and Science 12, no. 4 (2025): 66–75. https://doi.org/10.22161/ijaers.124.8.

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The cross-environment deployment strategies for Power Platform solutions which include moving Power Platform solutions from development to production using managed environments and DevOps practices. The paper takes advantage of ten key academic and industry sources to evaluate frameworks, automation tools and governing models to streamline deployment and enhance system reliability. The measurable benefits of such case studies are reduced deployment time and improved accuracy. With this DevOps deployed throughout cloud and hybrid platform and agile methodology, it facilitates scalable and secur
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Ma, J., Nobuyoshi Komuro, and Shiro Sakata. "Sensor Deployment for Location-Estimation Coverage." Key Engineering Materials 480-481 (June 2011): 1161–66. http://dx.doi.org/10.4028/www.scientific.net/kem.480-481.1161.

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Sensor deployment problem for target location estimation is important for sensor networks which fulfill the monitoring tasks. In this paper, we investigate the deployment schemes which guarantee the location estimation accuracy of an arbitrary point within the region, by connecting the location estimation problem with the perspective of k-coverage problem. Our strategies are deploying sensors to guarantee the location-estimation accuracy of an arbitrary point within the monitored region, and to minimize the number of required sensors. Compared with the random deployment, the deterministic depl
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Reddy, Vonteru Srikanth, and Kumar Debasis. "Statistical Review of Health Monitoring Models for Real-Time Hospital Scenarios." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 7s (2023): 465–81. http://dx.doi.org/10.17762/ijritcc.v11i7s.7025.

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Health Monitoring System Models (HMSMs) need speed, efficiency, and security to work. Cascading components ensure data collection, storage, communication, retrieval, and privacy in these models. Researchers propose many methods to design such models, varying in scalability, multidomain efficiency, flexibility, usage and deployment, computational complexity, cost of deployment, security level, feature usability, and other performance metrics. Thus, HMSM designers struggle to find the best models for their application-specific deployments. They must test and validate different models, which incr
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Du, Lei, Jianmin Gao, and Kun Chen. "A Comprehensive Error Analysis Method for Accuracy Reliability Deployment." Journal of Computational and Theoretical Nanoscience 13, no. 10 (2016): 7271–79. http://dx.doi.org/10.1166/jctn.2016.5708.

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To avoid equipment accuracy failure caused by degradation with use, the concept of Reliability Function Deployment (RFD) is employed to set up a comprehensive error analysis model. An operative matrix tool, called the House of Accuracy Reliability (HoAR) is presented. The HoAR is combined with Fault Tree Analysis (FTA), Failure Mode Effects and Criticality Analysis (FMECA) and Quality Function Deployment (QFD). In the HoAR, besides geometric error, thermal deformation error and load deformation error, a domino effect of error propagation is also taken into account for the risk assessment. Usin
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Aziz, Toufiq, and Koo Insoo. "Enhancing Indoor Localization Accuracy through Multiple Access Point Deployment." Electronics 13, no. 16 (2024): 3307. http://dx.doi.org/10.3390/electronics13163307.

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This study addresses the limitations of wireless local area networks in indoor localization by utilizing Extra-Trees Regression (ETR) to estimate locations based on received signal strength indicator (RSSI) values from a radio environment map (REM). We investigate how integrating numerous access points can enhance indoor localization accuracy. By constructing an extensive REM using RSSI data from various access points collected by a mobile robot in the intended interior setting, we evaluate several machine learning regression techniques. Our research pays special attention to an optimized ETR
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Campbell, Douglas, and Arup Maji. "Failure Mechanisms and Deployment Accuracy of Elastic-Memory Composites." Journal of Aerospace Engineering 19, no. 3 (2006): 184–93. http://dx.doi.org/10.1061/(asce)0893-1321(2006)19:3(184).

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Ukani, Neema Amish, and Saurabh S. Chakole. "Empirical analysis of machine learning-based moisture sensing platforms for agricultural applications: A statistical perspective." Journal of Physics: Conference Series 2327, no. 1 (2022): 012026. http://dx.doi.org/10.1088/1742-6596/2327/1/012026.

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Abstract Modelling of accurate detection & estimation soil moisture sensors requires integration of various signal processing, filtering, segmentation, and pattern analysis methods. Sensing of moisture is generally performed via use of resistive, or capacitive materials, which change their parametric characteristics w.r.t. changes in moisture levels. These sensors are further classified depending upon capabilities of measurements, which include, volumetric sensors, soil water tensor sensors, electromagnetic sensors, time domain reflectometry (TDR) sensors, Neutron probe sensors, tensiomete
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Umer, Waleed, and Mohsin K. Siddiqui. "Use of Ultra Wide Band Real-Time Location System on Construction Jobsites: Feasibility Study and Deployment Alternatives." International Journal of Environmental Research and Public Health 17, no. 7 (2020): 2219. http://dx.doi.org/10.3390/ijerph17072219.

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Ultra wide band (UWB)-based real-time location systems (RTLSs) have been widely adopted in the manufacturing industry for tracking tools, materials, and ensuring safety. Researchers in the construction domain have investigated similar uses for UWB-based RTLSs on construction jobsites. However, most of these investigations comprised small-scale experiments using average accuracy only to demonstrate use cases for the technology. Furthermore, they did not consider alternative deployment scenarios for practically feasible deployment of the technology. To overcome these limitations, a series of exp
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Thanneeru, Vyshnavi, and Murali Mohan Reddy Seelam. "Transforming Deployment and Release Management for Salesforce with Copado's AI." International Journal on Cybernetics & Informatics 14, no. 3 (2025): 75–79. https://doi.org/10.5121/ijci.2025.140306.

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This Research article explores the changing impact of AI (Artificial Intelligence) on automation capabilities of Copado, improving the deployment and change management in Salesforce DevOps. In this paper we have outlined the AI- based methodologies that automate the version control, optimize change management workflows, and improve accuracy of the deployments. The traditional Salesforce DevOps pipelines face many challenges like deployment errors, merge conflicts, roll back issues, and dependencies between the components. By implementing predictive analytics, machine learning, and automated ri
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Ladino, Karla S., and Michael Patrick Sama. "Short-Term Performance Evaluation of Real-Time Kinematic Global Navigation Satellite System Receivers in Unmanned Aircraft Systems." Journal of the ASABE 67, no. 6 (2024): 1433–46. http://dx.doi.org/10.13031/ja.16030.

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HighlightsAn evaluation of relative GNSS receiver accuracy was performed using a UAS-based GNSS accuracy testing system.RTK receivers displayed minimal mean error and consistent standard deviations across deployment strategies and error directions.Non-RTK receivers exhibited significantly greater mean error and variability across deployment strategies, particularly in elevation error.UAS deployment strategy did not have a meaningful impact on RTK receiver positioning performance.Abstract. Global navigation satellite system (GNSS) receivers commonly integrated into small unmanned aircraft syste
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Clarke, Lauren, Felix Holl, Thomas Raffort, Elvire Serres, Laura Archer, and Panu Saaristo. "From 2 Hours to 2 Seconds: Using the Red Cross Red Crescent Health Information System (RCHIS) to Complete the Emergency Medical Teams - Minimum Data Set Reporting." Prehospital and Disaster Medicine 37, S2 (2022): s74. http://dx.doi.org/10.1017/s1049023x2200173x.

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Background/Introduction:Standardization of data collection and reporting within EMTs is challenging. In past deployments, the Red Cross Red Crescent Type 1 and Type 2 facilities have collected data by hand using paper-based form and Excel spreadsheets. This process can be laborious, time-consuming, and often inaccurate.Objectives:To combat this issue with reporting, RCHIS (Red Cross Red Crescent Health Information System) has been designed to ensure that reporting is accurate and also very easy to complete, increasing compliance with the EMT-MDS reporting.Method/Description:RCHIS is both an el
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Zhang, Ruijie, Chunlei Xue, Zijie Sun, Kim Junhee, and Yunna Liu. "Characteristic extraction of Tai Chi movement data—Based on self-powered wearable sensors." Molecular & Cellular Biomechanics 21, no. 4 (2024): 848. https://doi.org/10.62617/mcb848.

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Although visual recognition has good recognition accuracy, it brings great hidden danger of privacy leakage. Although signal recognition has the advantages of device-free and privacy protection, it is sensitive to environmental noise and is not suitable for crowded environment, so sensor-based human behavior recognition is a more feasible choice. Therefore, this paper proposes a multi-level decision behavior recognition method based on self-powered wearable sensor fusion. In this paper, we propose a CM-WOA-based automatic dynamic sensor deployment optimization method for the feature extraction
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Clarke, Lauren, Felix Holl, Laura Archer, Thomas Raffort, Elvire Serres, and Panu Saaristo. "From Two hours to Two Seconds: Using the Red Cross Red Crescent Health Information System (RCHIS) to Complete the WHO Emergency Medical Teams - Minimum Data Set Reporting." Prehospital and Disaster Medicine 38, S1 (2023): s145—s146. http://dx.doi.org/10.1017/s1049023x23003813.

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Introduction:Standardization of data collection and reporting within EMT’s is challenging. In past deployments, the Red Cross Red Crescent Type one and two facilities (Emergency Response Units- ERU’s) have collected data by hand using paper-based form and Excel spreadsheets. This process can be laborious, time consuming and often inaccurate.Method:RCHIS is both an electronic medical record (EMR) and health information system (HIS). RCHIS has been designed to produce pre-made reports including the MDS in seconds extracting data from the patient records. Through significant testing and pilot dep
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Wu, Hui, Zhe Liu, Jin Hu, and Weifeng Yin. "Sensor placement optimization for critical-grid coverage problem of indoor positioning." International Journal of Distributed Sensor Networks 16, no. 12 (2020): 155014772097992. http://dx.doi.org/10.1177/1550147720979922.

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It is more practical and efficient to deploy sensors in critical areas rather than common areas to ensure indoor positioning accuracy and reduce deployment cost. This study focused on the sensor placement optimization for critical-grid coverage problem with two objectives: accuracy and cost. After reviewing some related works, this article proposed a multi-objective optimization model for critical-grid coverage problem of indoor positioning considering k-coverage problem as well as the topological rationality of sensor distribution. Then, NSGA-II algorithm was used to solve the optimizing mode
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Tong, Xing, Ming Li, and Zhichao Cui. "A Hybrid Traffic Sensor Deployment Model with Communication Consideration for Highways." Applied Sciences 14, no. 2 (2024): 536. http://dx.doi.org/10.3390/app14020536.

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This paper mainly studies the deployment of hybrid sensors on highways. By constructing the deployment location constraint model, the overall accuracy of sensor deployment can be maximized. In addition, in order to meet the needs of intelligent transportation, the consideration of traffic data communication is added to the work. The highway under study is first divided into several units, and the combination type of sensors is used to represent the possible layout of two adjacent sensors. Then, a 0–1 optimization model reflecting the interaction between the sensor position and the server posit
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Xue, Rui, Chang Ning Guo, Xiao Xin Yang, and Jing Yu Pei. "The Function Deployment of EDM Machine Tools." Key Engineering Materials 447-448 (September 2010): 242–46. http://dx.doi.org/10.4028/www.scientific.net/kem.447-448.242.

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This paper addresses the further developing and utilizing about the functions of EDM machine tool on the basis of researching the numerical controls of EDM machine tool itself. Experiments of testing critical gap distances, single pulse discharges and single pulse discharge gap distances have been performed by the machine tool without any extra help of auxiliary instruments or equipments. The measuring accuracy and repeated testing accuracy is the numerically controlled displacement precision of the machine tool itself. The development of this function would have a great impact on enlarging th
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Yamada, Ryuhei, and Yuichi Yaguchi. "Probability-Based LIDAR–Camera Calibration Considering Target Positions and Parameter Evaluation Using a Data Fusion Map." Sensors 24, no. 12 (2024): 3981. http://dx.doi.org/10.3390/s24123981.

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The data fusion of a 3-D light detection and ranging (LIDAR) point cloud and a camera image during the creation of a 3-D map is important because it enables more efficient object classification by autonomous mobile robots and facilitates the construction of a fine 3-D model. The principle behind data fusion is the accurate estimation of the LIDAR–camera’s external parameters through extrinsic calibration. Although several studies have proposed the use of multiple calibration targets or poses for precise extrinsic calibration, no study has clearly defined the relationship between the target pos
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Albanbay, Nurtay, Yerlan Tursynbek, Kalman Graffi, et al. "Federated Learning-Based Intrusion Detection in IoT Networks: Performance Evaluation and Data Scaling Study." Journal of Sensor and Actuator Networks 14, no. 4 (2025): 78. https://doi.org/10.3390/jsan14040078.

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This paper presents a large-scale empirical study aimed at identifying the optimal local deep learning model and data volume for deploying intrusion detection systems (IDS) on resource-constrained IoT devices using federated learning (FL). While previous studies on FL-based IDS for IoT have primarily focused on maximizing accuracy, they often overlook the computational limitations of IoT hardware and the feasibility of local model deployment. In this work, three deep learning architectures—a deep neural network (DNN), a convolutional neural network (CNN), and a hybrid CNN+BiLSTM—are trained us
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Hong, Zhang, Guo Bing, Shen Yan, Shen Yun-Cheng, Duan Xu-Liang, and Dong Xiang-Qian. "An observer deployment algorithm for information source positioning based on Naive Bayes." International Journal of Modern Physics C 31, no. 08 (2020): 2050115. http://dx.doi.org/10.1142/s0129183120501156.

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The accurate positioning of the propagation and diffusion source points of personal information is of great practical significance for the protection of personal information security. Currently, a popular method is to locate the data diffusion source point by deploying a certain number of observers and collecting the data propagation information from observers. In view of the deployment of observers, it was found that there is an important correlation between the observer deployment location and the data propagation time delay by analyzing the relationship between the positioning accuracy of i
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Yue, Shuai, Mengsheng Li, Zhen Zhao, Zhonghua Du, Chunbo Wu, and Qingzhan Zhang. "Parameter Analysis and Experiment Validation of Deployment Characteristics of a Rectangular Tether-Net." Aerospace 10, no. 2 (2023): 115. http://dx.doi.org/10.3390/aerospace10020115.

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Tether-nets in space applications are flexible capture systems for removing space debris. A new, low-mass, rectangular tether-net deployed by ten towing blocks is proposed in this paper for the purpose of capturing the main body of satellites. The dynamic model of a rectangular tether-net during the deployment process was established. The accuracy of the simulation model was validated by comparing it with on-ground experiments. In addition, the influence of towing block mass and launch speed on the maximum deployment area and the deployment lengths of the long side and short side of the rectan
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Soto, Paola, Miguel Camelo, Kevin Mets, et al. "ATARI: A Graph Convolutional Neural Network Approach for Performance Prediction in Next-Generation WLANs." Sensors 21, no. 13 (2021): 4321. http://dx.doi.org/10.3390/s21134321.

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IEEE 802.11 (Wi-Fi) is one of the technologies that provides high performance with a high density of connected devices to support emerging demanding services, such as virtual and augmented reality. However, in highly dense deployments, Wi-Fi performance is severely affected by interference. This problem is even worse in new standards, such as 802.11n/ac, where new features such as Channel Bonding (CB) are introduced to increase network capacity but at the cost of using wider spectrum channels. Finding the best channel assignment in dense deployments under dynamic environments with CB is challe
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Jin, Juan, Seunghan Kim, and Jiwon Moon. "Development of a Firefighting Drone for Constructing Fire-breaks to Suppress Nascent Low-Intensity Fires." Applied Sciences 14, no. 4 (2024): 1652. http://dx.doi.org/10.3390/app14041652.

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Korean forests are highly vulnerable to forest fires, which can severely damage property and human life. This necessitates the establishment of a rapid response system and the construction of firebreaks to prevent the spread of fires and protect key facilities. The existing firebreak construction methods can be classified into prevention- and response-stage methods. In the prevention stage, the progression and spread of fire are delayed, while in the response stage, primitive manual methods involving tools such as hooks are used, in addition to aerial deployment of water and fire retardants th
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Sun, Peng. "Research on Optimization of Node Deployment in Wireless Sensor Networks Driven by Artificial Intelligence." Transactions on Computer Science and Intelligent Systems Research 1 (October 12, 2023): 17–21. http://dx.doi.org/10.62051/za9bq189.

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The security deployment of WSN (Wireless Sensor Network) nodes also needs to ensure the performance of node coverage, which affects the accuracy and integrity of information detected by the network and the quality of service of the network. It is not enough to improve the network coverage and network performance of nodes only by adjusting the network topology of WSN, so there will be a problem of excessive node density in the network deployment area, which will lead to node redundancy and coverage hole, which will eventually affect the accuracy and integrity of monitoring information. In this
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Nath, Paresh Chandra, Md Sajedul Karim Chy, Md Refat Hossain, et al. "Comparative Performance of Large Language Models for Sentiment Analysis of Consumer Feedback in the Banking Sector: Accuracy, Efficiency, and Practical Deployment." Frontline Marketing, Management and Economics Journal 05, no. 06 (2025): 07–19. https://doi.org/10.37547/marketing-fmmej-05-06-02.

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In the rapidly evolving banking sector, understanding consumer sentiment is crucial for informed decision-making and enhancing customer experiences. This study investigates the efficacy of large language models (LLMs) for sentiment analysis of consumer feedback within the banking domain. We systematically evaluate five state-of-the-art LLMs—DistilBERT, BERT-base, RoBERTa-base, GPT-3.5, and GPT-4—on a domain-specific dataset of 10,000 consumer feedback entries collected from online banking forums and customer reviews. Each model is rigorously assessed in terms of accuracy, precision, recall, F1
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Tsu Yian, Lee, Faridahanim Ahmad, and Mohd Adib Sarijari. "OPTIMAL BLUETOOTH LOW ENERGY (BLE) SYSTEM DEPLOYMENT STRATEGY PRIOR TO SYSTEM APPLICATION ON THE CONSTRUCTION SITE." Jurnal Teknologi 85, no. 6 (2023): 161–68. http://dx.doi.org/10.11113/jurnalteknologi.v85.20140.

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The application of Bluetooth Low Energy (BLE) systems for labour tracking on construction sites is a popular research trend. Strategic system deployment is crucial for ensuring the overall reliability and feasibility of these systems. This study aims to identify the optimal BLE system deployment strategy for tiling work zones in three different renovation sites. The BLE system consists of BLE beacon, BLE gateway, Raspberry Pi (data logger), and MATLAB for data analysis. To ensure optimal placement of the BLE gateway, site visits were conducted to evaluate various conditions, such as power supp
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Wang, Shengliang, Ming Gao, Ling’ai Li, Dong Lv, and Yingqi Li. "UWB Base Station Deployment Optimization Method Considering NLOS Effects Based on Levy Flight-Improved Particle Swarm Optimizer." Sensors 25, no. 6 (2025): 1785. https://doi.org/10.3390/s25061785.

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The ultra-wideband (UWB) base station (BS) deployment pattern seriously affects mobile tag positioning accuracy, but the traditional classical deployment methods, such as rectangular and diamond deployment, cannot take into account the influence of non-line-of-sight (NLOS) occlusion, which leads to a blind area in positioning. In this paper, we propose a new UWB BS deployment optimization method that takes into account the influence of NLOS occlusion, determines the BS deployment range and occlusion by indoor map information, uses the locatable points coverage rate in the whole indoor position
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Fang, Xinpeng, Zhihao He, Shouxu Zhang, Junbing Li, and Ranjun Shi. "Improving Localization Accuracy under Constrained Regions in Wireless Sensor Networks through Geometry Optimization." Entropy 25, no. 1 (2022): 32. http://dx.doi.org/10.3390/e25010032.

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In addition to various estimation algorithms, the target localization accuracy in wireless sensor networks (WSNs) can also be improved from the perspective of geometry optimization. Note that existing placement strategies are mainly aimed at unconstrained deployment regions, i.e., the positions of sensors are arbitrary. In this paper, considering factors such as terrain, communication, and security, the optimal range-based sensor geometries under circular deployment region and minimum safety distance constraints are proposed. The geometry optimization problem is modeled as a constrained optimi
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Mehta, Rushabh. "Beyond Accuracy: Rethinking Data Quality as a Strategic Pillar in ERP Implementation." International journal of data science and machine learning 05, no. 01 (2025): 400–409. https://doi.org/10.55640/ijdsml-05-01-29.

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In recent years, a significant number of manufacturing enterprises globally have adopted Enterprise Resource Planning (ERP) systems as a strategic step toward digital transformation, leveraging advancements in cloud-based technologies. ERP systems, characterized by their comprehensive database structures, support advanced capabilities such as Artificial Intelligence (AI), Big Data analytics, Machine Learning (ML), and process automation. Given their integrative potential, these systems effectively consolidate essential business functions, including Sales, Accounting, Manufacturing, Human Resou
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Researcher. "MACHINE LEARNING MODELS IN PRODUCTION: A SYSTEMATIC FRAMEWORK FOR SCALABLE AND ROBUST DEPLOYMENT." International Journal of Research In Computer Applications and Information Technology (IJRCAIT) 15, no. 6 (2024): 1608–28. https://doi.org/10.5281/zenodo.14243017.

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This article presents a comprehensive framework for deploying and productizing machine learning models in real-world industrial settings, addressing the critical gap between laboratory development and production implementation. Through a systematic analysis of 47 enterprise-scale ML deployments across diverse industries, we identify key challenges and establish best practices for transforming experimental models into robust production systems. The methodology encompasses four primary dimensions: technical integration architecture, operational excellence, continuous monitoring systems, and
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Shu, Song, Ok-Youn Yu, Chris Schoonover, Hongxing Liu, and Bo Yang. "Unmanned Aerial Vehicle-Based Structure from Motion Technique for Precise Snow Depth Retrieval—Implication for Optimal Ground Control Point Deployment Strategy." Remote Sensing 15, no. 9 (2023): 2297. http://dx.doi.org/10.3390/rs15092297.

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Unmanned aerial vehicle (UAV)-based snow depth is mapped as the difference between snow-on and snow-off digital surface models (DSMs), which are derived using the structure from motion (SfM) technique with ground control points (GCPs). In this study, we evaluated the impacts of the quality and deployment of GCPs on the accuracy of snow depth estimates. For 15 GCPs in our study area, we surveyed each of their coordinates using an ordinary global positioning system (GPS) and a differential GPS, producing two sets of GCP measurements (hereinafter, the low-accuracy and high-accuracy sets). The two
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Peng, Qi’an, Sanmin Wang, Bo Li, Changjian Zhi, and Jianfeng Li. "Dynamics Analysis of Deployable Structures considering a Two-Dimensional Coupled Thermo-Structural Effect." International Journal of Aerospace Engineering 2018 (October 4, 2018): 1–10. http://dx.doi.org/10.1155/2018/1752815.

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The deployment accuracy of deployable structures is affected by temperature and flexibility. To obtain the higher accuracy, various measures such as the optimization design and the control process are employed, and they are all based on deployment dynamics characteristics of deployable structures. So a precise coupled thermo-structural deployment dynamics analysis is important and necessary. However, until now, only a one-dimensional thermal effect is considered in the literatures because of simplicity, which reduces the accuracy of the model. Therefore, in this paper, a new model coupling mec
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Wang, Gang, Guosheng Xu, Yukun Wang, et al. "Deployment Modes and Aerodynamic Analysis of UAV Orthogonal Biaxial Folding Wing." Aerospace 10, no. 1 (2022): 26. http://dx.doi.org/10.3390/aerospace10010026.

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Considering the deployment characteristics of the folding wing, this paper proposed three deployment modes, synchronous deployment, fixed-axis–non-fixed-axis stepwise deployment, and non-fixed-axis–fixed-axis stepwise deployment, to obtain the optimal deployment scheme of the orthogonal biaxial folding wing of Unmanned Aerial Vehicles (UAVs) at different airspeeds. On this basis, combined with the folding wing deployment action, the Lagrange method was used to establish the aerodynamic model of the folding wing, and the Fluent simulation software was used to simulate the aerodynamic simulation
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Broeders, Ivo A. M. J., and Jan D. Blankensteijn. "A Simple Technique to Improve the Accuracy of Proximal AAA Endograft Deployment." Journal of Endovascular Therapy 7, no. 5 (2000): 389–93. http://dx.doi.org/10.1583/1545-1550(2000)007<0389:asttit>2.0.co;2.

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Broeders, Ivo A. M. J., and Jan D. Blankensteijn. "A Simple Technique to Improve the Accuracy of Proximal AAA Endograft Deployment." Journal of Endovascular Therapy 7, no. 5 (2000): 389–93. http://dx.doi.org/10.1177/152660280000700506.

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Minion, David J., Christian C. Rodriguez, Erin M. Moore, Donald E. Patterson, and Eric D. Endean. "Technique of slow deployment of Gore Excluder endograft improves accuracy of placement." Journal of Vascular Surgery 43, no. 4 (2006): 852–54. http://dx.doi.org/10.1016/j.jvs.2005.12.049.

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Ramaraj, Prasanth, and Mohit Mittal. "DEEP LEARNING MODELS FOR AUTOMATED MEDICAL IMAGING: ACCURACY, ETHICS, AND DEPLOYMENT CHALLENGES." INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE AND DEEP LEARNING 2, no. 1 (2025): 11–31. https://doi.org/10.34218/ijaidl_02_01_002.

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Nikhila Pothukuchi. "Hardware-aware neural network training: A comprehensive framework for Efficient AI model deployment." World Journal of Advanced Engineering Technology and Sciences 15, no. 1 (2025): 1831–38. https://doi.org/10.30574/wjaets.2025.15.1.0344.

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This article presents a comprehensive guide to hardware-aware training techniques for artificial intelligence models, addressing the critical balance between performance optimization and resource efficiency. The discussion encompasses key strategies including quantization methods for precision reduction, systematic network pruning for architecture refinement, sparsity implementation for model optimization, and hardware-specific adaptations. Through detailed exploration of these techniques, the article demonstrates how integrating hardware considerations during the training process leads to sub
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Hauck, Sven R., Alexander Kupferthaler, Marlies Stelzmüller, et al. "Endovascular Stent-Graft Repair of the Ascending Aorta: Assessment of a Specific Novel Stent-Graft Design in Phantom, Cadaveric, and Clinical Application." CardioVascular and Interventional Radiology 44, no. 9 (2021): 1448–55. http://dx.doi.org/10.1007/s00270-021-02859-5.

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Abstract Purpose To test a stent-graft specifically designed for the ascending aorta in phantom, cadaver, and clinical application, and to measure deployment accuracy to overcome limitations of existing devices. Methods A stent-graft has been designed with support wires to fixate the apices toward the inner curvature, thereby eliminating the forward movement of the proximal end which can happen with circumferential tip capture systems. The device was deployed in three aortic phantoms, and in four cadavers, deployment precision was measured. Subsequently, the device was implanted in a patient t
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Xia, Jianghua, Han Wang, Qingfeng Zhuge, and Edwin Hsing-Mean Sha. "Knowledge Tracing Model and Student Profile Based on Clustering-Neural-Network." Applied Sciences 13, no. 9 (2023): 5220. http://dx.doi.org/10.3390/app13095220.

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Knowledge tracing models based on deep neural networks are currently widely studied to enhance personalized learning. However, to ensure the practical deployment of DNN-based KT models, prediction accuracy, training efficiency, and interpretability should be greatly improved. In this paper, we observe that the prediction accuracy of KT models can be improved by clustering the features of both students and questions. Based on this observation, a distributed KT scheme is proposed: (1) it classifies both students and questions based on clustering technology to reduce the interaction between diffe
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Eva Urankar. "Waste Detection on Mobile Devices: Model Performance and Efficiency Comparison." International Journal of Science and Research Archive 15, no. 1 (2024): 722–31. https://doi.org/10.30574/ijsra.2025.15.1.1052.

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This study evaluates object detection models for mobile deployment by comparing YOLOv11 and EfficientDet-Lite using a waste classification dataset. EfficientDet-Lite0 demonstrated higher speed (13 FPS), YOLOv11n was the most power-efficient (125,000 μAh in 590 seconds), and YOLOv11m achieved the highest accuracy (mAP@50: 0.694). The deployment of these models on an Android application highlights their trade-offs: EfficientDet-Lite0 suits speed-critical tasks, YOLOv11n excels in power-sensitive scenarios, and YOLOv11m and YOLOv11s perform best in accuracy-driven applications. These findings inf
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Maddel, Neeraj, Shantipal Ohol, and Anish Khobragade. "OPTIMIZING LLAMA 3.2 1B USING QUANTIZATION TECHNIQUES USINGBITSANDBYTES FOR EFFICIENT AI DEPLOYMENT." International Journal of Advanced Research 13 (March 31, 2025): 78–88. https://doi.org/10.21474/ijar01/20538.

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Large Language Models (LLMs) have transformed natural language processing, which has achieved state-of-the-art performance on various tasks. However, their high computational and memory requirements lead to significant challenges for deployment, especially on resource-constrained hardware. In this paper, we conduct a controlled experiment to optimize the LLaMA 3.2 1B model using post-training quantization techniques implemented using the Bitsandbytes library. Evaluating multiple precision settings like BF16, FP16, INT8, and INT4 compare their accuracy, throughput, latency, and resource utiliza
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Xie, Shao Guo, Yan Jun Hu, Yi Wang, Fang Jiang, Jing Jing Liu, and Ying Guan Wang. "A Model of Three Points for Location Estimation in Wireless Sensor Networks." Advanced Materials Research 787 (September 2013): 1066–71. http://dx.doi.org/10.4028/www.scientific.net/amr.787.1066.

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In this paper, we propose a novel model of three points named TP for location estimation in wireless sensor networks (WSNs) with random deployment of anchor nodes. In this model, we select three anchor nodes which have the strongest received signal strength (RSS) for location estimation, the centroid algorithm and the method of intersection of judgment are used to estimate the location of unknown nodes. To further exploit three nearest intersection points in TP, the enhanced TP (ETP) is proposed. The simulation results show that the proposed models outperform MMSE and BML in terms of the local
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Song, Liyuan, Hongliang Zou, and Tingting Zhang. "A Low Complexity Asynchronous UWB TDOA Localization Method." International Journal of Distributed Sensor Networks 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/675490.

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Impulse-radio ultrawideband (IR-UWB) is a promising technique for indoor localization due to its high accuracy and robustness against multipath interferences. In this paper, to deal with the synchronization challenges among anchors in traditional time-difference-of-arrival (TDOA) localization systems, we propose an asynchronous TDOA (ATDOA) localization method. Based on the ranging error model, we derive the theoretical lower bounds as the performance metrics of localization accuracy. Compared with the ideal TDOA method, ATDOA degrades on localization accuracy for eliminating the high accuracy
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Acácio, Marta, Philip W. Atkinson, João Paulo Silva, and Aldina M. A. Franco. "Performance of GPS/GPRS tracking devices improves with increased fix interval and is not affected by animal deployment." PLOS ONE 17, no. 3 (2022): e0265541. http://dx.doi.org/10.1371/journal.pone.0265541.

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The use of GPS tracking technologies has revolutionized the study of animal movement providing unprecedentedly detailed information. The characterization of GPS accuracy and precision under different conditions is essential to correctly identify the spatial and temporal resolution at which studies can be conducted. Here, we examined the influence of fix acquisition interval and device deployment on the performance of a new GPS/GSM solar powered device. Horizontal and vertical accuracy and precision of locations were obtained under different GPS fix acquisition intervals (1min, 20 min and 60 mi
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You, Xin, Daxin Tian, Wenbao Gao, Jinghui Lu, and Jinyin Xue. "Research on DL-TDOA Positioning Performance Optimization in Tunnel Scenarios." Journal of Physics: Conference Series 2670, no. 1 (2023): 012010. http://dx.doi.org/10.1088/1742-6596/2670/1/012010.

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Abstract High-precision vehicle positioning is a necessary condition for realizing intelligent transportation and autonomous driving, and positioning information is one of the basic elements to ensure the security of the Internet of Vehicles business. Aiming at the high-precision positioning requirements of tunnel scenarios, the DL-TDOA technology is analysed and optimized in this paper. First, the non-line-of-sight (NLOS) error suppression algorithm is optimized, then the influence of the deployment vertical and horizontal distance ratio of base station nodes on the positioning accuracy in th
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Zhang, Yue, Kai Chen, Jiawen Guo, and Cheng Wei. "Dynamics and Staged Deployment Strategy for a Spinning Tethered Satellite System." Aerospace 12, no. 7 (2025): 611. https://doi.org/10.3390/aerospace12070611.

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This paper investigates flexible multibody dynamic modeling and a staged deployment strategy for large-scale spinning tethered satellite systems, targeting deployment instability, inefficiencies, and tension-induced fracture risks. A nonlinear flexible multibody model is constructed using the absolute nodal coordinate formulation within an arbitrary Lagrangian–Eulerian framework, enabling accurate large-deformation modeling of the tether with geometric nonlinearity. This model surpasses traditional massless/rigid rod models by integrating tether mass distribution, flexible dynamics, and satell
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Kothwala, Dr. Deveshkumar Patel Hemant Bhatvedekar Neha*. "Advancing Venous Interventions: In-Vitro Evaluation of a Novel Self-Expanding Venous Stent System." International Journal of Scientific Research and Technology 2, no. 5 (2025): 169–76. https://doi.org/10.5281/zenodo.15345974.

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<strong>Background</strong>: Venoplasty and venous stenting are commonly used to treat chronically thrombosed veins. However, venous angioplasty alone is often insufficient due to low intravascular pressure in the venous system, necessitating the use of metal stents for long-term patency. Venous outflow obstruction can lead to chronic venous insufficiency, pain, and mobility impairment, requiring precise medical intervention. The Self-Expanding Venous Stent System is an endovascular device designed to maintain vessel patency by providing structural support. It consists of a hybrid closed-cell
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Currie, Maria E., A. Jonathan McLeod, John T. Moore, et al. "Augmented Reality System for Ultrasound Guidance of Transcatheter Aortic Valve Implantation." Innovations: Technology and Techniques in Cardiothoracic and Vascular Surgery 11, no. 1 (2016): 31–39. http://dx.doi.org/10.1097/imi.0000000000000235.

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Objective Transcatheter aortic valve implantation (TAVI) relies on fluoroscopy and nephrotoxic contrast medium for valve deployment. We propose an alternative guidance system using augmented reality (AR) and transesophageal echocardiography (TEE) to guide TAVI deployment. The goals of this study were to determine how consistently the aortic valve annulus is defined from TEE using different aortic valve landmarks and to compare AR guidance with fluoroscopic guidance of TAVI deployment in an aortic root model. Methods Magnetic tracking sensors were integrated into the TAVI catheter and TEE probe
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Wang, Hairong, Rong Lu, and Duo Yu. "Machine Vision Nondestructive Inspection System Assisted by Industrial IoT Supervision Mechanism." Mathematical Problems in Engineering 2022 (April 21, 2022): 1–11. http://dx.doi.org/10.1155/2022/8449518.

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This paper introduces the development status of machine vision nondestructive testing technology and industrial IoT supervision mechanism. The study designs and implements a machine vision nondestructive testing system from two aspects: construction of industrial IoT supervision and detection model, and optimization of machine vision nondestructive testing algorithm. In this paper, the random deployment of dynamic and static nodes is adopted. The coverage rate after random deployment and the moving distance of dynamic nodes are two necessary research parameters. To improve the initial coverage
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