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Artykuły w czasopismach na temat „Store Trajectory Prediction”

Autor: Grafiati

Data publikacji: 6 września 2023

Data aktualizacji: 31 lipca 2025

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1

Ching, Tan Kok. "Grid Survey Approach to Store Separation Trajectory Prediction." Journal of Aircraft 37, no. 4 (2000): 736–38. http://dx.doi.org/10.2514/2.2662.

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Hashemi, Seyed Mohammad, Seyed Ali Hashemi, Ruxandra Mihaela Botez, and Georges Ghazi. "Aircraft Trajectory Prediction Enhanced through Resilient Generative Adversarial Networks Secured by Blockchain: Application to UAS-S4 Ehécatl." Applied Sciences 13, no. 17 (2023): 9503. http://dx.doi.org/10.3390/app13179503.

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This paper introduces a novel and robust data-driven algorithm designed for Aircraft Trajectory Prediction (ATP). The approach employs a Neural Network architecture to predict future aircraft trajectories, utilizing input variables such as latitude, longitude, altitude, heading, speed, and time. The model’s foundation is rooted in the Generative Adversarial Network (GAN) framework, known for its inherent generative capabilities, rendering it remarkably resilient against Adversarial Attacks. To enhance its credibility, the Blockchain is employed as a Ledger Technology (LT) to securely store leg

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3

Lee, Seungsoo, Minwoo Park, Kum Won Cho, and Jang Hyuk Kwon. "New Fully Automated Procedure for the Prediction of Store Trajectory." Journal of Aircraft 37, no. 6 (2000): 1038–49. http://dx.doi.org/10.2514/2.2709.

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KANDIEL, M., and M. ESSAWf. "PREDICTION OE STORE TRAJECTORY DROPPED 'FROM A HIGH SPEED AIRCRAFT." International Conference on Aerospace Sciences and Aviation Technology 1, CONFERENCE (1985): 1–13. http://dx.doi.org/10.21608/asat.1985.26482.

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Razzaghi, Mohammad Mehdi. "Numerical study on trajectory of released store with manipulation of grid connections." Aircraft Engineering and Aerospace Technology 93, no. 5 (2021): 768–75. http://dx.doi.org/10.1108/aeat-07-2020-0140.

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Purpose This study aims to present a moving grid method based on the manipulation of connections. Design/methodology/approach In this study, the grid’s connections were manipulated to simulate a released store’s displacement. The selected model in this research is the EGLIN test case. In the introduced method, connections are modified in specific nodes of the grid. Governing flow equations were solved with the finite volume method. The major characteristic of this technique is using the averaging method for calculating the flux of cells. Findings This method maintains the grid’s quality even i

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6

Lijewski, Lawrence E., and Norman E. Suhs. "Time-accurate computational fluid dynamics approach to transonic store separation trajectory prediction." Journal of Aircraft 31, no. 4 (1994): 886–91. http://dx.doi.org/10.2514/3.46575.

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Chakraborty, Debasis, K. Anandhanarayanan, Ankit Raj, Vaibhav Shah, and R. Krishnamurthy. "Separation Dynamics of Air-to-Air Missile and Validation with Flight Data." Defence Science Journal 68, no. 1 (2017): 5. http://dx.doi.org/10.14429/dsj.68.11480.

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<p class="p1">Prediction of flight characteristics of a store in the vicinity of an aircraft is vitally important for ensuring the safety of the aircraft and effectiveness of the store to meet the mission objective. Separation dynamics of an agile air-to-air-Missile from a fighter aircraft is numerically simulated using an integrated store separation dynamics suite. Chimera cloud of points along with a grid-free Euler solver is used to obtain aerodynamic force on the missile and the force is integrated using a rigid body dynamics code to obtain the missile position. In the present work,

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8

Wang, Shanshan. "Enterprise Management Optimization by Using Artificial Intelligence and Edge Computing." International Journal of Distributed Systems and Technologies 13, no. 3 (2022): 1–9. http://dx.doi.org/10.4018/ijdst.307994.

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In the internet era, huge data is generated every day. With the help of cloud computing, enterprises can store and analyze these data more conveniently. With the emergence of the internet of things, more hardware devices have accessed the network and produced massive data. The data heavily relies on cloud computing for centralized data processing and analysis. However, the rapid growth of data volume has exceeded the network throughput capacity of cloud computing. By deploying computing nodes at the edge of the local network, edge computing allows devices to complete data collection and prepro

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9

Velychko, Dmytro, Benjamin Knopp, and Dominik Endres. "Making the Coupled Gaussian Process Dynamical Model Modular and Scalable with Variational Approximations." Entropy 20, no. 10 (2018): 724. http://dx.doi.org/10.3390/e20100724.

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We describe a sparse, variational posterior approximation to the Coupled Gaussian Process Dynamical Model (CGPDM), which is a latent space coupled dynamical model in discrete time. The purpose of the approximation is threefold: first, to reduce training time of the model; second, to enable modular re-use of learned dynamics; and, third, to store these learned dynamics compactly. Our target applications here are human movement primitive (MP) models, where an MP is a reusable spatiotemporal component, or “module” of a human full-body movement. Besides re-usability of learned MPs, compactness is

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10

Yang, Yichi, Ruibin Yan, and Yijun Gu. "LTransformer: A Transformer-Based Framework for Task Offloading in Vehicular Edge Computing." Applied Sciences 13, no. 18 (2023): 10232. http://dx.doi.org/10.3390/app131810232.

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Vehicular edge computing (VEC) is essential in vehicle applications such as traffic control and in-vehicle services. In the task offloading process of VEC, predictive-mode transmission based on deep learning is constrained by limited computational resources. Furthermore, the accuracy of deep learning algorithms in VEC is compromised due to the lack of edge computing features in algorithms. To solve these problems, this paper proposes a task offloading optimization approach that enables edge servers to store deep learning models. Moreover, this paper proposes the LTransformer, a transformer-bas

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11

Zhang, Weini. "Research on Recognition Method of Basketball Goals Based on Image Analysis of Computer Vision." Journal of Sensors 2021 (September 20, 2021): 1–11. http://dx.doi.org/10.1155/2021/5269431.

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Moving target detection is involved in many engineering applications, but basketball has some difficulties because of the time-varying speed and uncertain path. The purpose of this paper is to use computer vision image analysis to identify the path and speed of a basketball goal, so as to meet the needs of recognition and achieve trajectory prediction. This research mainly discusses the basketball goal recognition method based on computer vision. In the research process, Kalman filter is used to improve the KCF tracking algorithm to track the basketball path. The algorithm of this research is

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12

Díaz-Casco, Manuel A., Blanca E. Carvajal-Gámez, Octavio Gutiérrez-Frías, and Fernando S. Osorio-Zúñiga. "Comprehensive—Model Based on Time Series for the Generation of Traffic Knowledge for Bus Transit Rapid Line 6 of México City." Electronics 11, no. 19 (2022): 3036. http://dx.doi.org/10.3390/electronics11193036.

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Mobile sensor networks consist of different types of integrated devices that collect, disseminate, process and store information from the environments in which they are implemented. This type of network allows for the development of applications and systems in different areas for the generation of knowledge. In this paper, we propose a model called the Metrobus Arrival Prediction (MAP) model for predicting the arrival times of Line 6 buses of the bus rapid transit (BTR) system, known as the Metrobus, in Mexico City (CDMX). The network is composed of mobile and static nodes that collect data re

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13

Kim, Wonjik, and Osamu Hasegawa. "Time Series Prediction of Tropical Storm Trajectory Using Self-Organizing Incremental Neural Networks and Error Evaluation." Journal of Advanced Computational Intelligence and Intelligent Informatics 22, no. 4 (2018): 465–74. http://dx.doi.org/10.20965/jaciii.2018.p0465.

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This study proposes a route prediction method using a self-organizing incremental neural network. The route trajectory is predicted from two location parameters (the latitude and longitude of the middle of a tropical storm) and the meteorological information (the atmospheric pressure). The method accurately predicted the normalized atmospheric pressure data of East Asia in the topological space of latitude and longitude, with low calculation cost. This paper explains the algorithms for training the self-organizing incremental neural network, the procedure for refining the datasets and the meth

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14

Xi, Ke, and Chao Yan. "CFD Transonic Trajectory Predictions of Three-Store Ripple Release Using Chimera Method." Applied Mechanics and Materials 513-517 (February 2014): 4490–93. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.4490.

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The complicated unsteady flows with moving boundary were simulated numerically by coupling solving unsteady compressible Navier-Stokes equations and 6DOF rigid-body dynamics equations. The Chimera grid technology was used to handle the relative motion. The three-store ripple release of the wing-store configuration was simulated using this method. The computational results are in good agreement with data from other literature, showing that the method used has a strong applicability to complex multi-body separation problem.

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15

Zhang, Lixiang, Yian Zhu, Jiang Su, Wei Lu, Jiayu Li, and Ye Yao. "A Hybrid Prediction Model Based on KNN-LSTM for Vessel Trajectory." Mathematics 10, no. 23 (2022): 4493. http://dx.doi.org/10.3390/math10234493.

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Trajectory prediction technology uses the trajectory data of historical ships to predict future ship trajectory, which has significant application value in the field of ship driving and ship management. With the popularization of Automatic Identification System (AIS) equipment in-stalled on ships, many ship trajectory data are collected and stored, providing a data basis for ship trajectory prediction. Currently, most of the ship trajectory prediction methods do not fully consider the influence of ship density in different sea areas, leading to a large difference in the prediction effect in di

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16

Hong, Keyyong, Sun-Young Kim, and Museok Song. "A REAL-TIME SIMULATION OF THE TRAJECTORY AND FATE OF SPILLED OIL AT SEA." International Oil Spill Conference Proceedings 1997, no. 1 (1997): 573–77. http://dx.doi.org/10.7901/2169-3358-1997-1-573.

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ABSTRACT On the basis of the physical modeling of the trajectory and fate of spilled oil at sea, an integrated computer program was developed for the real-time prediction of spilled oil behavior. The trajectory model describes the movement of the surface spill center of mass, and the trajectory is mainly governed by the velocity of the wind and the surface current. For the fate model, weathering effects of spreading, evaporation, emulsification, and shoreline interaction are included. The Windows-based GUI has a flexible preprocessor that enables one to use measured field data as well as numer

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Shipilova, Elena, Egor Nekrylov, and Tat'yana Kurchenkova. "Analysis and modeling of online service user behavior trajectories using the RETENTIONEERING platform." Modeling of systems and processes 15, no. 4 (2022): 82–93. http://dx.doi.org/10.12737/2219-0767-2022-15-4-82-93.

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The active development and widespread distribution of online stores and sales sites sets the task for marketers and IT specialists to analyze the results of sites and customer behavior to maximize store profits and predict the development of online sales. The article provides an analysis of the purchasing activity of Internet users of various categories in various periods, the postulates of online trading are formulated. To comprehensively analyze the impact of a variety of factors, predict the demand for goods, form additional recommendations and special support for purchases, the authors off

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18

Meng, Hongfei, Feiteng Wang, Guangzu Bai, and Huilin Li. "A Study on Dust Storm Pollution and Source Identification in Northwestern China." Toxics 13, no. 1 (2025): 33. https://doi.org/10.3390/toxics13010033.

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In April 2023, a major dust storm event in Lanzhou attracted widespread attention. This study provides a comprehensive analysis of the causes, progression, and dust sources of this event using multiple data sources and methods. Backward trajectory analysis using the HYSPLIT model was employed to trace the origins of the dust, while FY-2H satellite data provided high-resolution dust distribution patterns. Additionally, the MAIAC AOD product was used to analyze Aerosol Optical Depth, and concentration-weighted trajectory (CWT) analysis was used to identify key dust source regions. The study foun

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19

Gramajo, German, and Praveen Shankar. "An Efficient Energy Constraint Based UAV Path Planning for Search and Coverage." International Journal of Aerospace Engineering 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/8085623.

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A path planning strategy for a search and coverage mission for a small UAV that maximizes the area covered based on stored energy and maneuverability constraints is presented. The proposed formulation has a high level of autonomy, without requiring an exact choice of optimization parameters, and is appropriate for real-time implementation. The computed trajectory maximizes spatial coverage while closely satisfying terminal constraints on the position of the vehicle and minimizing the time of flight. Comparisons of this formulation to a path planning algorithm based on those with time constrain

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20

Georgieva, Hristina. "Aircraft noise level calculation during take-off." Aerospace Research in Bulgaria 32 (2020): 75–87. http://dx.doi.org/10.3897/arb.v32.e07.

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A mathematical model with 4 degree of freedom created in Matlab for aircraft departure trajectory is described in this article. As a reference aircraft a midsize commercial passenger aircraft similar to an Airbus A320 has been chosen. The aircraft is represented by the rigid body and the parameters of model are collected from Airbus and the simulated departure trajectory at the Munich airport is based on a Standard Instrumental Departure. A semi-empirical model of Stone for predicting the jet noise has been used. The proposed model is validated against 10 real flights obtained from aircraft no

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21

Wang, Huandong, Changzheng Gao, Yuchen Wu, Depeng Jin, Lina Yao, and Yong Li. "PateGail: A Privacy-Preserving Mobility Trajectory Generator with Imitation Learning." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 12 (2023): 14539–47. http://dx.doi.org/10.1609/aaai.v37i12.26700.

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Generating human mobility trajectories is of great importance to solve the lack of large-scale trajectory data in numerous applications, which is caused by privacy concerns. However, existing mobility trajectory generation methods still require real-world human trajectories centrally collected as the training data, where there exists an inescapable risk of privacy leakage. To overcome this limitation, in this paper, we propose PateGail, a privacy-preserving imitation learning model to generate mobility trajectories, which utilizes the powerful generative adversary imitation learning model to s

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22

Minh, Pham Thi, Hang Thi Nguyen, Thuy Kim Pham, and Gia Nguyen Hoang Cao. "An application of the multi-physical method of determining error of WRF models to simulate the track and intensity Usagi storm in 2018." Science & Technology Development Journal - Science of The Earth & Environment 5, no. 1 (2021): first. http://dx.doi.org/10.32508/stdjsee.v5i1.547.

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This paper presents the test results of the WRF model error determination methods simulating the trajectory and intensity of storm Usagi in 2018. The study conducted three experiments: (1) The Combination of 11 options physical model, 21 composites, no increase in error correlation (MP); (2) Using a set of physical model, 21 composite components, multiplier growth factor l = 6.5 (MI); (3) Using a set of physical model, 21 compositions, no increase in error correlation (PF). Test results show that the multi-physics (MP) method has quite well simulated the intensity as well as the moving directi

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23

Hollan, Michael A., and Brian C. Ancell. "Ensemble Mean Storm-Scale Performance in the Presence of Nonlinearity." Monthly Weather Review 143, no. 12 (2015): 5115–33. http://dx.doi.org/10.1175/mwr-d-14-00417.1.

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Abstract The use of ensembles in numerical weather prediction models is becoming an increasingly effective method of forecasting. Many studies have shown that using the mean of an ensemble as a deterministic solution produces the most accurate forecasts. However, the mean will eventually lose its usefulness as a deterministic forecast in the presence of nonlinearity. At synoptic scales, this appears to occur between 12- and 24-h forecast time, and on storm scales it may occur significantly faster due to stronger nonlinearity. When this does occur, the question then becomes the following: Shoul

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24

Carrió, Diego S. "Improving the predictability of the Qendresa Medicane by the assimilation of conventional and atmospheric motion vector observations. Storm-scale analysis and short-range forecast." Natural Hazards and Earth System Sciences 23, no. 2 (2023): 847–69. http://dx.doi.org/10.5194/nhess-23-847-2023.

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Abstract. The coastal population in the western Mediterranean Basin is frequently affected by high-impact weather events that produce huge economic and human losses. Among the wide spectrum of maritime severe weather events, tropical-like Mediterranean cyclones (a.k.a. medicanes) draw particular attention, specially due to their poor predictability. The accurate prediction of this kind of event still remains a key challenge to the weather forecast community, mainly because of (i) errors in the initial conditions, (ii) lack of accuracy of modeling micro-scale physics processes and (iii) chaotic

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Hamdan, Baida Abdulredha. "Neural Network Principles and its Application." Webology 19, no. 1 (2022): 3955–70. http://dx.doi.org/10.14704/web/v19i1/web19261.

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Neural networks which also known as artificial neural networks is generally a computing dependent technique that formed and designed to create a simulation to the real brain of a human to be used as a problem solving method. Artificial neural networks gain their abilities by the method of training or learning, each method have a certain input and output which called results too, this method of learning works to create forming probability-weighted associations among both of input and the result which stored and saved across the net specifically among its data structure, any training process is

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26

Georgieva, Hristina, and Krasin Georgiev. "Modeling of aircraft jet noise in airports." MATEC Web of Conferences 234 (2018): 01003. http://dx.doi.org/10.1051/matecconf/201823401003.

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A mathematical model with 4 degree of freedom created in Matlab for aircraft final landing trajectory is described in this paper. A midsize commercial passenger aircraft similar to an Airbus A320 has been chosen as a reference aircraft. The parameters of model are obtained from Airbus, Eurocontrol and the approach procedure at the Munich airport is selected up from Jeppesen Airway manual. A semi-empirical model of Stone for predicting the jet noise has been used. The proposed model was validated against 10 real flights obtained from Aircraft noise monitoring at Munich airport. The computed err

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27

Kang, J., T. H. Lee, B. S. Koo, S. Y. Park, S. Lee, and T. H. Kim. "OP0151 PREDICTION OF RADIOGRAPHIC PROGRESSION IN PATIENTS WITH ANKYLOSING SPONDYLITIS: USING GROUP-BASED TRAJECTORY MODELING AND DECISION TREE ANALYSIS." Annals of the Rheumatic Diseases 81, Suppl 1 (2022): 98.2–98. http://dx.doi.org/10.1136/annrheumdis-2022-eular.4433.

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BackgroundAnkylosing spondylitis (AS) tends to develop at a relatively young age and is characterized by long-term disease progression (1). During that time, various radiographic changes occur in the spine, which eventually lead to disability in the patient’s lifetime (2). Although the duration of the disease, aging, and passage of time are predicted to be highly associated with spinal progression of AS, it is difficult to predict its progression in the spine of patients.ObjectivesWe aimed to find ways to predict spinal progression over time in patients with AS and analyze its associated clini

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28

Zhang, Jin, Yuyan Dai, Jie Chen, et al. "SIDA." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 7, no. 3 (2023): 1–24. http://dx.doi.org/10.1145/3610919.

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The coronavirus disease 2019 (COVID-19) pneumonia still persists and its chief complaint is dry cough. Physicians design wireless stethoscopes to facilitate diagnosis, however, lung sounds could be easily interfered with by external noises. To achieve lung sound enhancement, prior researches mostly assume the amount of clean and noisy data are the same. This assumption is hardly met due to extensive labor effort for data collection and annotation. The data imbalance across domains widely happens in real-world IoT systems, e.g. sound enhancement and WiFi-based human sensing. In this paper, we p

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29

Lee, Dooyoul, Hwanjeong Cho, Min-Saeng Kim, and Kybeom Kwon. "Probabilistic Risk Analysis of Aircraft Self-Collisions: A Case Study." Aerospace 9, no. 2 (2022): 80. http://dx.doi.org/10.3390/aerospace9020080.

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Airborne self-collisions occur primarily in military aircraft because of external stores and are frequently experienced by personnel operating these aircraft. In most cases, objects causing self-collisions are irregularly shaped and unstable. Consequently, the trajectories of these objects are uncertain. A framework for the probabilistic risk analysis of aircraft self-collisions is proposed in this study. Based on the probabilistic trajectory prediction model, methods for estimating the probability of collision (POC) and the corresponding risks were developed. Subsequently, a self-collision ev

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Peng, Wei, Xinlei Zhang, and Xin Li. "Intelligent Behavior Data Analysis for Internet Addiction." Scientific Programming 2019 (November 29, 2019): 1–12. http://dx.doi.org/10.1155/2019/2753152.

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Internet addiction refers to excessive internet use that interferes with daily life. Due to its negative impact on college students’ study and life, discovering students’ internet addiction tendencies and making correct guidance for them timely is necessary. However, at present, the research methods used in analyzing students’ internet addiction are mainly questionnaires and statistical analysis, which relies on the domain experts heavily. Fortunately, with the development of the smart campus, students’ behavior data such as consumption and trajectory information in the campus are stored. With

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31

Xu, Yanchao, Dongxiang Zhang, Shuhao Zhang, Sai Wu, Zexu Feng, and Gang Chen. "Predictive and Near-Optimal Sampling for View Materialization in Video Databases." Proceedings of the ACM on Management of Data 2, no. 1 (2024): 1–27. http://dx.doi.org/10.1145/3639274.

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Scalable video query optimization has re-emerged as an attractive research topic in recent years. The OTIF system, a video database with cutting-edge efficiency, has introduced a new paradigm of utilizing view materialization to facilitate online query processing. Specifically, it stores the results of multi-object tracking queries to answer common video queries with sub-second latency. However, the cost associated with view materialization in OTIF is prohibitively high for supporting large-scale video streams. In this paper, we study efficient MOT-based view materialization in video databases

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Sedaghat, Atefe, Homayoon Arbabkhah, Masood Jafari Kang, and Maryam Hamidi. "Deep Learning Applications in Vessel Dead Reckoning to Deal with Missing Automatic Identification System Data." Journal of Marine Science and Engineering 12, no. 1 (2024): 152. http://dx.doi.org/10.3390/jmse12010152.

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This research introduces an online system for monitoring maritime traffic, aimed at tracking vessels in water routes and predicting their subsequent locations in real time. The proposed framework utilizes an Extract, Transform, and Load (ETL) pipeline to dynamically process AIS data by cleaning, compressing, and enhancing it with additional attributes such as online traffic volume, origin/destination, vessel trips, trip direction, and vessel routing. This processed data, enriched with valuable details, serves as an alternative to raw AIS data stored in a centralized database. For user interact

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Wang, Penggang, Yuejun He, Jiguang Zhang, Jiandong Liu, Ran Chen, and Xiang Zhuang. "Phenotypic Trait Acquisition Method for Tomato Plants Based on RGB-D SLAM." Agriculture 15, no. 15 (2025): 1574. https://doi.org/10.3390/agriculture15151574.

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The acquisition of plant phenotypic traits is essential for selecting superior varieties, improving crop yield, and supporting precision agriculture and agricultural decision-making. Therefore, it plays a significant role in modern agriculture and plant science research. Traditional manual measurements of phenotypic traits are labor-intensive and inefficient. In contrast, combining 3D reconstruction technologies with autonomous vehicles enables more intuitive and efficient trait acquisition. This study proposes a 3D semantic reconstruction system based on an improved ORB-SLAM3 framework, which

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Nallala, Jayakrupakar, Doriana Calabrese, Sarah Gosling, et al. "Abstract 3353: Predicting the prognosis of ductal carcinoma in situ through chemical analysis of breast microcalcifications and soft tissue using infrared and Raman spectroscopy." Cancer Research 85, no. 8_Supplement_1 (2025): 3353. https://doi.org/10.1158/1538-7445.am2025-3353.

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Abstract Introduction: Ductal carcinoma in situ (DCIS) is a potential precursor to invasive breast cancer (IBC). The trajectory of an individual’s DCIS, if it will progress to IBC or remain as DCIS is difficult to predict. Currently &gt;80% of DCIS is detected through mammographic screening of breast calcifications. Despite the close association of calcifications with DCIS, their role in the development of DCIS and/or its progression to IBC remains largely unexplored. In this study, we present a spectroscopy based analytical approach to probe chemical compositional changes of both DCIS ass

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Nallala, Jayakrupakar, Doriana Calabrese, Sarah Gosling, et al. "Abstract P2-08-07: Predicting DCIS prognosis using infrared and raman spectroscopy of breast calcifications and soft-tissue microstructure." Cancer Research 82, no. 4_Supplement (2022): P2–08–07—P2–08–07. http://dx.doi.org/10.1158/1538-7445.sabcs21-p2-08-07.

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Abstract Introduction: Ductal carcinoma in situ (DCIS) is a potential precursor of invasive breast cancer. The uncertain trajectory of DCIS, to progress to invasive disease or to remain in situ, currently drives treatment, despite lack of proven benefit. Therefore, understanding the molecular features of the DCIS trajectory may prevent overtreatment of this disease. Breast calcifications are a common feature in DCIS and are seen mammographically in over 80% of cases. Calcifications have been largely characterised based only on x-ray morphology; their chemical composition, their association wit

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Bertran, Eduard, Paula Tercero, and Alex Sànchez-Cerdà. "UAV generalized longitudinal model for autopilot controller designs." Aircraft Engineering and Aerospace Technology 94, no. 3 (2021): 380–91. http://dx.doi.org/10.1108/aeat-08-2020-0156.

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Purpose This paper aims to overcome the main obstacle to compare the merits of the different control strategies for fixed-wing unmanned aerial vehicles (UAVs) to assess autopilot performances. Up to now, the published studies of control strategies have been carried out over disperse models, thus being complicated, if not impossible, to compare the merits of each proposal. The authors present a worked benchmark for autopilots studies, consisting of generalized models obtained by merging UAVs’ parameters gathered from selected literature (journals) with other parameters directly obtained by the

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Stone, T. W., J. Bennett, D. H. S. Law, and J. A. Holmes. "Thermal Simulation With Multisegment Wells." SPE Reservoir Evaluation & Engineering 5, no. 03 (2002): 206–18. http://dx.doi.org/10.2118/78131-pa.

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Summary The extension of a previously reported well model to compositional and thermal applications is discussed. This multisegment, multibranching wellbore model has been fully coupled to a commercial reservoir simulator that can operate in black-oil, compositional, or thermal modes. In this paper, the discussion will focus on thermal, heavy-oil applications in which simulation requires a better representation of the wellbore geometry and the physics of fluid flow and heat transfer. Introduction Gravity-drainage processes with possible steam (SAGD) or gas vapor (VAPEX) assistance and other re

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Darikas, George, Anup Barai, Muhammad Sheikh, Peter Miller, Mark Amor-Segan, and David Greenwood. "Impact of Relaxation Time on the Accelerated Cycle Ageing Tests of Lithium-Ion Batteries." ECS Meeting Abstracts MA2022-02, no. 7 (2022): 2590. http://dx.doi.org/10.1149/ma2022-0272590mtgabs.

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As lithium-ion batteries are becoming the energy storage technology of choice for transport electrification, the accurate estimation and prediction of their service life remains a critical aspect for their successful adoption and integration. The established methods of lifetime estimation employ battery degradation models along with accelerated ageing test data. Although accelerated methods have been widely used in the literature over the last decade, there are still some discrepancies regarding the testing methodology and parameters. Specifically, in cycle ageing experiments, the relaxation t

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Balachandran, N., Rakesh Kumar, and D. Narayan. "Prediction of Store Separation Characteristics Using CFD and Validation with Flight Test Results." Journal of Aerospace Sciences and Technologies, August 7, 2023, 231–38. http://dx.doi.org/10.61653/joast.v62i4.2010.509.

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The design, integration and certification of a store configuration to a fighter aircraft involve extensive and expensive wind tunnel and flight testing with the objective of determining the operational and deployment envelopes for safe separation. Computational trajectory prediction techniques have shown to have the potential not only to reduce the number of flight/wind tunnel tests but also to design an intelligent test matrix. In this paper a Cartesian grid based Euler code-PARAS coupled with trajectory evaluation module (a 6-DOF time integration module) developed at ADA has been used to pre

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Pandey, Navdeep, and Aniruddha Sinha. "Multi domain decomposed reduced order model for store trajectory prediction." Sādhanā 49, no. 1 (2024). http://dx.doi.org/10.1007/s12046-023-02365-z.

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Peters, Nicholas, Andrew Wissink, and John Ekaterinaris. "Comparison of Data-Driven Approaches to Rotorcraft Store Separation Modeling." Journal of Aircraft, September 3, 2023, 1–16. http://dx.doi.org/10.2514/1.c037164.

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In this study, two surrogate modeling approaches will be investigated for their ability to predict store surface pressure distributions as a store is launched from a rotorcraft in hover. To generate these surrogate models, three computational fluid dynamics (CFD) simulations were completed while varying the propulsive force assigned to the store. Once the surrogate models were generated, an additional CFD simulation with a new propulsive force was assigned to the store. The results of this validation indicate that although the proper orthogonal decomposition (POD) surrogate model struggled to

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Shikhar Jaiswal, A., C. K. Niranjanan, Keshav Malagi, V. Ramesh, and S. M. Deshpande. "Grid Method Based Store Separation Suite Using Paranam Mesh Free Solver." Journal of Aerospace Sciences and Technologies, July 29, 2023, 214–18. http://dx.doi.org/10.61653/joast.v71i2.2019.139.

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A store separation suite based on Point Prediction methodology was developed at CSIR-National Aerospace Laboratories (NAL) using PARANAM (Parallel NAL MCIR) mesh free CFD solver along with 6-DOF code and dynamic point cloud pre-processor [7,8]. This store separation suite is well validated and tested and is being used widely for various strategic store separation projects at CSIR-NAL [7,8]. However, in some scenarios point prediction based method is difficult to employ owing to either large number of trajectory studies or time and resource requirements. In such scenarios a quick but sufficient

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Zuo, Yi, Junhao Jiang, and Katsutoshi Yada. "Application of hybrid gate recurrent unit for in-store trajectory prediction based on indoor location system." Scientific Reports 15, no. 1 (2025). https://doi.org/10.1038/s41598-024-84599-3.

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A.Shikhar, Jaiswal, C.K.Niranjanan, Malagi Keshav, V.Ramesh, and S.M.Deshpande. "Grid Method Based Store Separation Suite Using PARANAM Mesh Free Solver." May 1, 2019. https://doi.org/10.5281/zenodo.3355155.

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A  store  separation  suite  based  on  Point  Prediction  methodology  was  developed  at  CSIR-National   Aerospace  Laboratories  (NAL)  using  PARANAM  (P arallel  NAL  MCIR)  mesh  free  CFD  solver  along   with  6-DOF  code  and  dynamic  point  cloud  pre-processor  [7,8].  This  store  separation  suite  is  well   validated and tested and is being used widely for va rious strategic

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Huq, Faizul, Vernon Jones, and Douglas Alfred Hensler. "A time series projection model of online seasonal demand for American wine and potential disruption in the supply channels due to COVID-19." International Journal of Wine Business Research, December 22, 2021. http://dx.doi.org/10.1108/ijwbr-03-2021-0015.

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Purpose This study statistically examines the shifting distribution channels in the American wine industry based on the growth trajectory of sales, seasonality and disruption due to consumers switching to online platforms. The purpose of this paper is to design a model that will have general applicability beyond the wine industry. Design/methodology/approach The research uses regression-based additive decomposition of time series data to predict the trajectory of the market share for the digital distribution channel. The study develops a statistical prediction model using time series data betw

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A., Nishad, and Sajimon Abraham. "Contact tracing and mobility pattern detection during pandemics – a trajectory cluster based approach." International Journal of Pervasive Computing and Communications, July 14, 2022. http://dx.doi.org/10.1108/ijpcc-05-2021-0111.

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Purpose A wide number of technologies are currently in store to harness the challenges posed by pandemic situations. As such diseases transmit by way of person-to-person contact or by any other means, the World Health Organization had recommended location tracking and tracing of people either infected or contacted with the patients as one of the standard operating procedures and has also outlined protocols for incident management. Government agencies use different inputs such as smartphone signals and details from the respondent to prepare the travel log of patients. Each and every event of th

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Debasis Chakraborty. "Cfd Simulations of Store Separation: An Indian Perspective." Journal of Aerospace Sciences and Technologies, July 28, 2023, 220–44. http://dx.doi.org/10.61653/joast.v73i4.2021.102.

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CFD analysis played a very major role in predicting the safe separation of many stores including missiles, guided bombs, drop tanks from various airborne platforms namely, fighter aircraft, helicopters etc. Number of indigenous CFD based stores separation suites are developed by coupling flow solvers, 6 Degrees-of-freedom (6DOF) trajectory programs and efficient pre and post processors. These packages were validated against reliable experimental results and were applied to many practical applications. These analyses gave very good confidence to the designers, test pilots and certifying agencie

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Abuhanieh, Saleh, and Hasan U. Akay. "Numerical investigation of store separation from cavity problems at high speeds." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, September 20, 2023. http://dx.doi.org/10.1177/09544100231203404.

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In this work, the ability of open-source CFD tools to conduct store separation simulations from cavities is evaluated and validated using a generic test case from the literature. Firstly, the ability and accuracy of these tools for solving cavity flows at high speeds are evaluated. Secondly, their competence in predicting the trajectory of a generic store from a generic deep cavity is checked. Finally, and in order to reduce the associated computational costs, a release-time dependability factor from the recent literature is studied and evaluated. The obtained results using the selected open-s

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Kang, Juyeon, Tae-Han Lee, Seo Young Park, Seunghun Lee, Bon San Koo, and Tae-Hwan Kim. "Prediction of radiographic progression pattern in patients with ankylosing spondylitis using group-based trajectory modeling and decision trees." Frontiers in Medicine 9 (October 20, 2022). http://dx.doi.org/10.3389/fmed.2022.994308.

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ObjectiveThis study aimed to identify trajectories of radiographic progression of the spine over time and use them, along with associated clinical factors, to develop a prediction model for patients with ankylosing spondylitis (AS).MethodsData from the medical records of patients diagnosed with AS in a single center were extracted between 2001 and 2018. Modified Stoke Ankylosing Spondylitis Spinal Scores (mSASSS) were estimated from cervical and lumbar radiographs. Group-based trajectory modeling classified patients into trajectory subgroups using longitudinal mSASSS data. In multivariate anal

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Gray, Suzanne L., and Ambrogio Volonté. "Extreme low‐level wind jets in Storm Ciarán." Weather, September 19, 2024. http://dx.doi.org/10.1002/wea.7620.

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AbstractSatellite imagery of Storm Ciarán as it approached the UK early on 1 November 2023 showed characteristic banding that fuelled media reports that Ciarán could contain a sting jet, with enhanced likelihood of damaging surface winds and gusts. Here operational numerical weather prediction model output is used with trajectory analysis to reveal the existence of at least two wind speed maxima attributed to sting jets. The small‐scale sting jets are located beneath, and likely affected by, far broader overrunning strong wind regions attributed to a deeply descending dry intrusion, thus highl

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